Impact of Sodium on Hypertension in a Variety of Adult American
Subpopulations: Analysis of the NHANES Data Set for the
Years 2005-2014
By
ELLEN KESEWAA OSEI
A Dissertation Submitted to Faculty of the School of Health Related
Professionals, Rutgers State University of New Jersey in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy in Biomedical Informatics
Department of Health Informatics
Spring 2016
APPROVAL PAGE
Impact of Sodium on Hypertension in a Variety of Adult American Subpopulations:
Analysis of the NHANES Data Set for the
Years 2005-2014
By
ELLEN KESEWAA OSEI
Dissertation Committee:
Fredrick D. Coffman, Ph.D., Committee Chair
Shankar Srinivasan, Ph.D., Committee Member
Syed Haque, Committee Member
Approved by the Dissertation Committee:
Date:
Date:
Date:
i
ABSTRACT
Impact of Sodium on Hypertension in a Variety of Adult American Subpopulations:
Analysis of the NHANES Data Set for the Years 2005-2014
By
ELLEN KESEWAA OSEI
Research shows that high sodium consumption is positively correlated with hypertension.
However, little is known about variations on the impact of high sodium consumption on hypertension among a variety of adult American subpopulations. This study investigated the impact of sodium on hypertension in a variety of adult America subpopulations by conducting an analysis of Centers for Disease Control's (CDC) National Health and
Nutrition Examination Survey (NHANES) 24-hour dietary recall data from 2005-2014.
Participants ages 20 years and above were used in the study. Analysis of the data included applying weighted factors to the selected sample to account for sampling bias and allow for accurate comparisons between samples and population estimates. Data analysis was done using SAS version 9.4 Software Package. There was a decrease in the two year period 2007-2008 of sodium consumption and a increase in hypertension rate.
There was no significant change in sodium consumption from 2005-2014. Fifty four percent of the people consumed more than the daily recommended sodium intake by the
American dietary guidelines. Results showed that African Americans consumed more sodium than any other race in America. Also, African Americans have the highest hypertensive rate in the study. Highly educated individuals consume more than the
ii recommended amount of sodium (2300mg) compared to those with less than high school education. On the contrary, the results further shows that less educated participants had higher blood pressure than the more educated individuals. It was found that, low income earners consumed more sodium but middle income earners had highest hypertension.
Male consume more sodium than their females counter parts and has higher hypertension than females.
The results shows that 98% of the participants had isolated systolic hypertension and as people age, their blood pressure becomes higher. The results further shows participants with higher BMI consume more sodium and had higher blood pressure. Also, the more you age the higher your blood pressure.
The study highlighted areas that can be targeted for designing health intervention programs that will be targeted to specific subgroups of the American population
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ACKNOWLEDGEMENTS
Let your speech be seasoned with salt; Colossians 4:6
Dr. Fredrick D. Coffman, my research chair and advisor. I thank you for your patience, and advise throughout my completion of this dissertation. Dr. Coffman your leadership, insightful comments, contributions and advise helped me sail through this journey. I want to thank Drs. Frederick D. Coffman, Syed Haque, Shankar Srinivasan and Masayuki
Shibata, for their guidance. I am very grateful to be their student.
I acknowledge the department chair Dr. Haque for his continuous leadership. Dr. Haque you are a light to Biomedical Informatics world in the United States.
Dr. Shankar Srinivasan thank you for believing in me and encouraging me that I can reach high heights in life. I am forever grateful for your support, guidance, and the joy and good fortune that you bring. I appreciate your valuable comments throughout this dissertation.
Special thanks goes to Dr. John K. Kwagyan Director, Design of Biostatistics &
Population Studies, Georgetown-Howard U Center for Clinical & Translation Science
(GHUCCTS) Howard University; College of Medicine for his insightful comments and guidance.
I also thank all my professors both past and present especially Drs. John K. Kwagyan and Constant Gewa
For the SAS programming, Sir Victor Nyamete made significant contribution to the guidance in writing good SAS code and telling the story that can be understood by all.
iv
For this dissertation, I would like to thank my reading committee members especially
Drs. Coffman, Srinivasan, and Kwagyan for their time, patience, interest, advise and insightful comments throughout my research work. I thank my family for their love and encouragement.
Thanks to my mother who was always comforting me and encouraging me to never give up.
I greatly acknowledge the funding source that made my Ph.D. possible. I was funded by my husband Eugene Addo Agyekum. Thank you Eugene for holding on and picking me up anytime I fall.
Finally, I would like to acknowledge all my friends and course mates for their encouragement and support.
v
DEDICATION
I dedicate this work to the Lord God almighty and my late father Daniel Akwasi Osei.
Daddy made sure his little princess Ellen Maame Kesewaa Osei Agyekum got the best education and he sacrificed everything for me while he was alive. An equal dedication goes to my husband Eugene Addo Agyekum for his patience, encouragement, and love. I would also, like to dedicate this dissertation to my mother her royal highness Comfort
Abena Mirekwaa Amobi Kyei Osei. Additionally to my siblings, Ken, Rosemond,
Ebenezer, Ernestina, Alex, Rita and Felix. I am very grateful to you Felix for your support, prayers and encouragement. And to my uncle Rev. Dr. Obiri Addo of Drew
University.
Finally to all those who made positive impact on my life.
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List of Abbreviations
AHA American Heart Association
ANOVA Analysis of Variance
ATP Adult Treatment Panel III
BMI Body Mass Index
CAPI Computer Assisted Personal Interview
CI Confidence Interval
DASH Dietary Approach to Stop Hypertension
DBP Diastolic Blood Pressure
EBSCO Elton B. Stephen Co.
FDA Food and Drug Administration
GDP Gross Domestic Product
HBM Health Believe Model
IOM Institutes of Medicine
JNC 7 The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7)
JSTOR Journal Storage
MEC Mobile Examination Center
MeSH Medical Subject Headings mRFEI Modified Retail Food Environment Index
NCDs Non- Communicable Diseases
NCEP National Cholesterol Education Program
NHANES National Health and Nutrition Examination Survey
NHF National Heart Foundation
OR Odd Ratio
vii
SAS Statistical Analysis Software
SBP Systolic Blood Pressure
SCT Social Cognitive Theory
TOHP Trials of Hypertension Prevention
TPB Theory of Planned Behavior
US United States
WHO World Health Organization
VIF Variance Inflation Factors
R1 Research question one
R2 Research question two
R3 Research question three
R4 Research question four
R5 Research question five
R6 Research question six
R7 Research question seven
H1 Hypotheses one
H1 Hypotheses two
H1 Hypotheses three
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H1 Hypotheses four
H1 Hypotheses five
H1 Hypotheses six
H1 Hypotheses seven
ISH Isolated Systolic Hypertension
IDH Isolated Diastolic Hypertension
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Table of Contents List of Abbreviations ...... ii
ABSTRACT ...... ii ACKNOWLEDGEMENTS ...... iv DEDICATION ...... vi CHAPTER 1 ...... 1 INTRODUCTION ...... 1 1.1 Statement of the Problem ...... 1 1.2 Nature of the Study ...... 5 1.2.1 Assumptions ...... 5 1.2.2 Significance of the Study ...... 5 1.2.3 Goals ...... 6 1.2.4 Research Questions ...... 6 1.3 Hypothesis...... 7 1.3.1 Theoretical Framework ...... 13 1.3.2 Summary of the theoretical framework ...... 18 CHAPTER 2 ...... 19 LITERATURE REVIEW ...... 19 2.1 Literature Search Strategies ...... 19 2.1.2 What Is High Blood Pressure/Hypertension? ...... 19 2.1.3 Risk Factors for High Blood Pressure ...... 23 2.1.4 Gender, Race and Blood Pressure ...... 23 2.2 Diabetes and blood pressure ...... 25 2.2.1 Obesity and high blood pressure: ...... 26 2.2.3 How Sodium Increases Blood Pressure ...... 31 2.2.4 Sodium Consumption in the US and Globally ...... 32 2.2.5 Sodium Consumption and the Food Industry ...... 36 2.3 Salt reduction in the US and other countries ...... 37 2.3 Sodium Consumption, Body Mass Index and Blood Pressure ...... 39 2.4 Education, Sodium Intake and Blood Pressure ...... 41
x
2.4.1 Economic Impact of Hypertension ...... 42 2.4.2 Effects of Sodium on Blood Pressure Using Dietary Studies ...... 43 2.4.3 Effects of Sodium on Blood Pressure Using Urinary Studies ...... 44 2.4.4 Effects of Sodium on Blood Pressure Using Animal Studies ...... 45 2.4.5 The Impact of Sodium and Potassium Interaction on blood pressure ...... 46 CHAPTER 3 ...... 50 METHODOLOGY ...... 50 3.1 Study Design ...... 50 3.1.3 Study Group/ Inclusion/ Exclusion Criteria ...... 52 3.4 NHANES Data Set and Data Elements ...... 52 3.4.1 Data Cleaning and Data Processing Using SAS 9.4 ...... 54 3.4.3 Demographic Data ...... 55 3.4.4 Dietary Data ...... 56 3.4.5 Dietary Interview: Total Nutrient Intakes First Day ...... 57 3.5 Total Nutrient Intakes Files (DR1TOT and DR2TOT) ...... 57 3.5.1 Examination Data...... 58 3.5.2 Laboratory Data ...... 58 3.5.3 The variables to be used in the analysis will be recorded as follows ...... 59 3.5.5 Statistical Analysis and Data Cleaning ...... 62 RESULTS ...... 71 4.3 Sodium and High Blood Pressure ...... 79 4.4 Education and Sodium ...... 90 4.4.1 Income and Blood Pressure ...... 95 4.5 Body Mass Index and Blood Pressure ...... 100 4.6: Age and Blood Pressure ...... 104 CHAPTER 5 ...... 117 DISCUSSIONS AND LIMITATIONS ...... 117 CHAPTER 6 ...... 124 SUMMARY AND CONCLUSIONS ...... 124 6.1 FUTURE STUDIES...... 126 REFERENCES ...... 1278
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LIST OF TABLES
Table 1: Number of High Blood Pressure Mortality cases by Gender and Race …….…24
Table 2: Sodium Intake Trends by Age and Gender Groups over 5 NHANES Cycles …25
Table 3: Demographic Variables and Sample Weight ………………………………….55
Table 4: The variables obtained from the dietary data file ……………………………...57
Table 5: The variables obtained from the total nutrients data file……………………….57
Table 6: The variables obtained from the examination data file ………………………..58
Table 7: The variable obtained from the laboratory data file …………………………...59
Table 8: Classification of the variables used in the analysis ……………………………62
Table 9: Means of the Variables NHANES 2005-2012 ………………………………..66
Table 10: Weighted Demographics Characteristics persons 20years and older ……..72-73
Table 11: Collinearity Check for Continues Variables ……………………………...73-75
Table 12: Cross tabulations of Sodium Consumption and Hypertension using
NHANES data 2005-2012 ……………………………………………………....80
Table 13: Results of Chi-Square test for the association between Races
Sodium Intake and Hypertension NHANES 2005-2012 ……………………...86
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Table14: Regression of Sodium and Race from Blood Pressure ………………….87-90
Table 15: Cross tabulations of Education and Sodium Consumption
NHANES data 2005-2012 ………………………………………………....91
Table 16: Education by Blood Pressure NHANES 2005-2012 ……………………....92
Table 17: The Effects of Education and Sodium on Hypertension 2005-2012 …..….93
Table 18: House Hold Income by Blood Pressure………………………………... 95
Table 19: Cross tabulations of Household Income and Blood Pressure Consumption
NHANES data 2005-2012 …………………………………………...... 96
Table 20: Effect of Sodium on Blood Pressure Controlling for Income on
NHANES 2005-2012………………………………………………………… 97
Table 21: Cross tabulations of Sex and Blood Pressure Consumption NHANES …....98
Table 22: Cross tabulations of Sex and Sodium Intake Consumption NHANES
data 2005-2012………………………………………………………………98
Table 23: Significance of Gender/Sex and Sodium on Hypertension NHANES
2005-2012 …………………………………………………………………..99
Table 24: Cross tabulations of BMI and Blood Pressure NHANES data 2005-2012...101
Table 25: Cross tabulations of BMI and Sodium Intake Consumption NHANES
data 2005-2012 ………………………………………………………………..104
Table 26: The Effect of Body Mass Index and Sodium on Hypertension ……………...103
Table 27: Significance of Age and Sodium on Hypertension NHANES 2005-2012…...105
Table 28 Systolic Isolated Hypertension by Gender …………………………………... 107
Table 29: Systolic Isolated Hypertension by Age ………………………………………107
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Table 30: Cross tabulations of Isolated Hypertension by Sodium intake…………….. 107
Table 31: Risk Estimate for Significant Independent Variables Using
Logistic Regression ……………………………………………………………108
Table 32: Test for Association of the Categorical Variables to the
Dependent Variable ……………………………………………………………113
Table 33: Risk Estimate for Significant Independent Variables Using
Logistic Regression …………………………………………………..………. 113
LIST OF FIGURES
Figure 1: How the body regulates blood pressure ………………………………………22
Figure 2: The cluster of co-morbidities associated with and aggravated by obesity…… 27
Figure 3: A flow chart showing the link between daily sodium, blood pressure …...... 29
Figure 4: The paleolithic diet vs modern diet …………………………………………..32
Figure 5: The Mean Dietary Sodium Intake among U.S. Men and Women
Ages 18-74 years – NHANES 1971-2010 …………………………………...…34
Figure 6: The Amount of Sodium Contained in a Ham Sandwich………………...... 35
Figure 7: Global Sodium Consumption ………………………………….……………...38
Figure 8: Break down of the data used in the study ……………………………………..51
Figure 9: Distribution of blood pressure by Gender/sex NHANES 2005-2012 ……….77
Figure 10: Distribution of Sodium Consumption by Sex NHANES 2005-2012 ………..78
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Figure 11: Sodium Intake and Hypertension NHANES 2005-2012 …………………….81
Figure 12: Sodium intake and hypertension NHANES 2005-2012 ……………………..83
Figure 13: The effect of sodium on hypertension NHANES 2005-2012 ………………84
Figure 14: Effects of Sodium by Blood Pressure Controlling for Race
NHANES 2005-2012 ……………………………………………………85
Figure 15: Sodium Consumption, Education by Blood Pressure ……………………….94
Figure 16: Subgroup Analysis of Sodium Intake, Blood Pressure by Household
Income NHANES 2005-2012 …………………………………………..96
Figure 17: Analysis of Sodium Intake Blood Pressure by Sex/Gender
NHANES 2005-2012 ………………………………………………….99
Figure 18: Analysis of Sodium Intake, Blood Pressure by BMI
NHANES 2005-2014 …………………………………………………101
Figure 19: Comparing Sodium Intake by Blood Pressure in Age 20 and Older
NHANES 2005-2012 …………………………………………………104
Figure 20: Analysis of Systolic Isolated hypertension by Gender by Age …………....108
Figure 21: Distribution of Blood pressure by Sodium ……………………………….109
Figure 22: Distribution of Blood pressure by Race …………………………………..110
Figure 23: Distribution of Blood pressure by Education …………………………...... 110
Figure 24: Distribution of Blood pressure by Income ………………………………..111
Figure 25: Distribution of Blood pressure by Gender ……………………………….. 111
Figure 26: Distribution of Blood pressure by BMI ………………………………..…112
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Figure 27: Distribution of Blood pressure by Age ………………………………….112
Figure 28: Prevalence of Hypertension NHANES 2005-2015 Ages 20
Years and Older ……………………………………………………………115
Figure 29: Incidence of Hypertension among Adults Ages 20 and Older
NHANES 2005 2014 ……………………………………………………....116
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CHAPTER 1
INTRODUCTION
1.1 Statement of the Problem
There has been a dramatic increase in sodium*consumption in the United States over the years. Processed food and restaurant meals contributes to more than 75% of sodium that is consumed by Americans1,2. The increased sodium consumption has reflected the changing tastes of the American consumer. Furthermore, sodium is being used as a preservative to increase the shelf life of many foods.3,4
Studies show that even though sodium is an essential nutrient in the human body, the amount needed by the human body per day is no more than 184-230 mg/day.5
Historical review of sodium consumption shows that during the evolution of human beings, sodium exposure was not as much as what it is today.6 Human beings were only exposed to the salt that occurred naturally in foods and water. 7 During the early stages of agricultural and human husbandry development and because of the need to have food reserves, food preservation became necessary and this was accomplished by adding salt to dairy products, meats and fish. As a result, more salt was introduced into the human diet. However, the human species evolved during a time of low sodium diet and the body was adapted to retention of only limited salt naturally present in foods. Today, even though we consume large amounts of salt in our diet, the kidney is not adapted to excreting large amounts of sodium from the body. However, beverage food companies and organizations representing industrial and commercial interests actively promote high salt intake and claim that there is no scientific justification for reducing salt intake.8
*“sodium” is the term used in the US while other countries use the term "salt" 1
Research shows that excess salt leads to the constriction and stiffness of arterial walls and that continuous exposure to high levels of salt in the American diet contributes to cases of hypertension and cardiovascular diseases.9 According to the American institutes of medicine, sodium is responsible for 20 to 40 percent of all the high blood pressure cases in the United States. 10 Other studies have found that people diagnosed with hypertension consume significantly more sodium than those with normal blood pressure. Increased sodium consumption increases the risk of kidney disease, stroke and cardiovascular disease.11 In their study, Lewington, et al. reported that every 20 mm Hg increase in systolic pressure above the normal blood pressure doubles the risk of mortality from heart disease and stroke.12
There is a growing body of clinical, epidemiological, and genetic research that shows that sodium contributes to high blood pressure. 13 These studies show that there is a causal relationship between consistent sodium intake and the onset of high blood pressure. Even though it is not fully understood how sodium contributes to high blood pressure, existing research shows that the human kidney was not designed to excrete large amounts of salt, yet the American consumer ingests more salt than can be used by the human body. 9 Based on the NHANES data from 2009 to 2012, 32.6% of US adults aged 20 years and older reported having hypertension. This represents approximately 80 million US adults.14 The report further shows that hypertension prevalence is high among
African American adults in America. Te age- adjusted prevalence of hypertension among non Hispanic black men and women am Among non - Hispanic black men and women, the age- adjusted prevalence of hypertension was 44.9% and 46.1 % respectively.14
2
A study done by to the centers for disease control (CDC), reported that high blood pressure claimed more than 2.4 million lives in the U.S. About 77.9 million or 1 in 3
American adults will be diagnosed with high blood pressure.15 Hypertension has been termed as a "silent killer" because it is asymptomatic in nature and it contributes to high mortality rate worldwide.16 Research shows that hypertension is the most common primary diagnosis reported for ambulatory care visits.17 Data from NHANES for 2009 -
2012 shows that almost 47% of adults aged 20 and over who have hypertension continued to have uncontrolled high blood pressure. High blood pressure costs the nation
$46 billion each year.18 The yearly hypertension cost in America includes cost of medications, health care services and absent days that individuals missed from work.
According to the American heart association, from 2000 to 2010, the death rate attributed to hypertension increased by 16.0% and the actual number of deaths rose by 41.5%.19
Hypertension accounted for over 360,000 American deaths in 2013 with a daily rate of almost 1,000.20 On a state by state basis, the highest percentage of adults who said they have hypertension is in Mississippi, with 35.9 percent. Minnesota has the lowest rate.
Broadly, states in the South have the highest hypertension rates and states in the West have the lowest. Reported data shows that blacks develop high blood pressure more often and at an earlier age than whites and Hispanics. Further, more black women than black men have high blood pressure. Age is an inevitable consequence of hypertension because of structural changes such as large artery stiffness.21 There are higher densities of high blood pressure among women 65 years and older compared to men. However, blood pressure rates are higher in men than women for the population 45 and below.
3
Hypertension presents a major economic burden in the US. In 2010, treatment costs for hypertension totaled $42.9 billion, with a half of the cost being used for prescription medication. Further, the annual expenditure for those being treated for high blood pressure averaged $733 per adult. Per person per year treatment costs were highest among Hispanic and non- Hispanic blacks ($981 and $887 respectively) followed by non-
Hispanic white and non-Hispanic others ($679 and $661 respectively). 22,23
Globally, hypertension is one of the major causes of premature death, causing nearly 8 million deaths every year. Further, over 1 billion people are living with high blood pressure. The global overall prevalence of high blood pressure in adults aged 25 and over is 40% (including those on medication for high blood pressure).24 A 2010
World Health Organization (WHO) reported shows that non- communicable diseases
(NCDs) such as hypertension have contributed to more than 75% of the world's Gross
Domestic Product (GDP).25
A number of studies have been conducted using NHANES data on the impact of sodium on high blood pressure. Many of these studies have used only one year of NHANES data. Few studies have used several years. No study has looked at the impact of sodium on high blood pressure using more than 8 years of cross sectional data. The purpose of this paper is to investigate the impact of salt on high blood in different human subgroups separated by sex, age, ethnicity, and socioeconomic factors by conducting an analysis of pressure by conducting an analysis of the NHANES data from 2005-2014. The results of this analysis will add to the understanding of the impact of salt on high blood pressure.
4
1.2 Nature of the Study
This research will use an existing National Health and Nutrition Examination
Survey (NHANES) data collected by the Centers for Disease Control (CDC); a cross - sectional sample of non-institutionalized U.S. populations. NHANES data is designed to access the health and nutritional status of adults and children in the United States.
NHANES data collection started in the 1960s and contains information on health and nutrition on the sample reflecting changing nutritional and health trends among
Americans. This research used the NHANES data from 2005 to 2014. NHANES data is available in the public domain and is free. The survey design was a stratified, multistage probability sample of the target population. Data collection was done in accordance with the NHANES procedures and protocols.
1.2.1 Assumptions
This research assumes the following:
All data was collected using the NHANES data collection procedures and
protocols.
All the study participants fell within the NHANES eligibility.
All data was handled and stored in acceptable manner.
1.2.2 Significance of the Study
Review of published literature shows that a comprehensive analysis of the 2005-
2014 NHANES data on the impact of sodium on high blood pressure in adult American subpopulations has not been done. This research will seek to answer these questions:
What does the 2005-2014 NHANES data say about sodium consumption in the US sub
5 populations? What is the trend of sodium consumption among the subpopulations during the years covered by the study? These changes will be correlated with public health messages by various public health institutions such as American Heart Association
(AHA) and CDC to determine whether these messages had any impact on sodium consumption among the subpopulations.
A careful analysis of the 2005-2014 data will be done to determine whether there are significant disparities in sodium consumption among a variety of human subpopulations.
The findings of these analyses will be a significant addition to the understanding of the impact of salt on blood pressure.
1.2.3 Goals
The goal of this study is to investigate the impact of sodium on hypertension in a variety of American adult subpopulation: educated vs. uneducated, wealthy vs. poor, male vs. female, low vs. high BMI, and in different ethnic groups by conducting an analysis of NHANES data from 2005-2014.
1.2.4 Research Questions
This research will seek to answer the following questions:
1. Is sodium a significant determinant of hypertension?
2. Is there a significant relationship between sodium and hypertension in all ethnic
groups studied?
6
3. Is there a significant relationship between sodium and hypertension in all
education groups studied?
4. Is there a significant relationship between sodium consumption and hypertension
in all income groups studied?
5. Is there a significant relationship between sodium and hypertension based on
sex?
6. Is there a significant relationship between sodium and hypertension in all BMI
categories?
7. Has sodium consumption, hypertension, or the relationship between sodium
consumption and hypertension changed in any of the groups studies between
2005 -2014?
1.3 Hypothesis
1. Sodium has a significant determinant of hypertension
Null Hypothesis: H0 =H1
Alternative Hypothesis: H0 ≠ H1
2. There a significant relationship between sodium and hypertension in all ethnic
groups studied
Null Hypothesis: H0 =H1
Alternative Hypothesis: H0 ≠ H1
7
3. There is a significant relationship between sodium and hypertension in all
education groups studied
Null Hypothesis: H0 =H1
Alternative Hypothesis: H0 ≠ H1
4. There is a significant relationship between sodium consumption and hypertension
in all income groups studied
Null Hypothesis: H0 =H1
Alternative Hypothesis: H0 ≠ H1
5. There a significant relationship between sodium and hypertension based on sex
Null Hypothesis: H0 =H1
Alternative Hypothesis: H0 ≠ H1
6. There a significant relationship between sodium and hypertension in all BMI
categories
Null Hypothesis: H0 =H1
Alternative Hypothesis: H0 ≠ H1
Aims and Techniques to Answer the Research Requisitions
1. Is sodium a significant determinant of hypertension?
This question is aimed at developing a clear understanding on the impact of
sodium on blood pressure with the support of literature and the NHANES data
from 2005 to 2014. By answering this question, the researchers will conduct chi-
8
square to determine whether there is a significant association between sodium and
blood pressure variables. The chi-square test will be followed by logistic
regression.
The following guiding questions can be deduced from it:
Guiding Questions
What is the degree of significance in sodium to blood pressure?
Is there a change in the results over the years?
The guiding questions are not specific questions to determining the study relevance in the area of interest. The guiding questions are not necessarily to be answered but rather serve as an aide - memoire to make the study productive. Raise unforeseen issues that may have emerged in the analysis.
2. Is here a significant relationship between sodium consumption and
hypertension in all ethnic groups studied?
The second research question is aimed at determining the impact of race on sodium consumption. Race is a concomitant of the determinant of high blood pressure.
This research is informed by literature that shows that different races have different genetic backgrounds, consume different traditional staple foods, and exist in different cultural environments. This question will investigate the effects of these factors on sodium consumption.
In order to answer this research question, the researchers will compare the sodium intake across the various races. By drawing these statistical inferences, chi-square test
9 will be used to assess the relationship between race, sodium consumption and blood pressure.
The following guiding questions have been deduced from it:
Guiding Questions
What is the relationship between race and sodium consumption?
What is the relationship between sodium consumption and hypertension
for each ethnic group?
3. Is there a significant relationship between sodium and hypertension in all
education groups studied?
The aim of the third research question is to generate a link between the interpretative paradigm of the preliminary results that showed a positive association between education and sodium and the rest of the data. Chi-square tests will be used to test for the association between sodium consumption and hypertension among different educational attainment levels and the amount of dietary sodium that the study population consumed. The following guiding questions can be deduced from it:
Guiding Questions
What is the percentage of highly educated individuals who have
elevated blood pressure?
How does level of education correlate with sodium consumption in all populations?
10
4. Is there a significant relationship between sodium consumption and
hypertension in all income groups studied?
The purpose of the forth research question is to develop an understanding of the relationship between household income and blood pressure. In order to answer this research question, the researchers was used chi-square to assess the relationship, compare the sodium intake and blood pressure between different income levels.
The following guiding questions can be deduced from it:
Guiding Questions
What income level consumes more sodium?
Is income a determinant of high blood pressure?
Does income have effect on blood pressure level?
5. Is there a significant relationship between sodium and hypertension based on
sex?
The fifth research question is aimed at determining the impact of sex/gender on
sodium consumption and hypertension. This research is informed by literature
that shows that different men and women have different biological effect on
sodium consumption and hypertension. This question will investigate the effects
of gender on sodium consumption.
To answer this question, Chi-square tests was used. The relationship was further accessed by using, logistic regression.
11
The following guiding questions have been deduced from it:
Guiding Questions
What is the relationship between sex and sodium consumption?
How sodium consumption and hypertension does vary among male and
females?
6. Is there a significant relationship between sodium consumption and
hypertension in all BMI categories?
The sixth research question is aimed at developing an understanding of the
relationship between BMI, sodium consumption and hypertension. To answer this
question, Chi-square test will be used.
The following guiding questions can be deduced from it:
Guiding Question
What is the relationship between BMI and sodium consumption in terms
of race?
7. Has sodium consumption, hypertension, or the relationship between sodium
consumption and hypertension changed in any of the groups studies between
2005 -2014?
The purpose of the last research question is to develop an understanding of the relationship between sodium consumption and blood pressure over the years. To answer this question, sodium consumption, hypertension, or the relationship between sodium
12 consumption and hypertension will be assessed in different years histogram will be used to check the changes over the years.
The following guiding questions can be deduced from it:
Guiding Questions
What is the change in sodium consumption and hypertension over the
years?
1.3.1 Theoretical Framework
The Mosaic Theory of hypertension proposed by Irvin Page 60 years ago holds that “many factors, including genetics and the environment, adaptive, neural, mechanical, and hormonal disturbances interlink to raise blood pressure.” 26 Page introduced the
Mosaic Theory by arguing that even the simplest hypertension is a mosaic where many factors are involved in different degrees. Consequently, high blood pressure is a result of many forces acting on the circulatory system. Although recent research continues to challenge the Mosaic Theory, many of the factors they point to are ultimately found in the Mosaic Theory. For example, Dr. Arthur Guyton made the case that hypertension is primarily due to alteration of the renal function. However, Dr. Guyton points out that several factors contribute to alteration of the renal function. These factors, which include hormones and dietary intake of salt, are part of the Mosaic Theory.27
Recent research has shown that common molecular and cellular events in various organs are key aspects of the Mosaic Theory. Two of these events are production of reactive oxygen species and inflammation. These events promote sodium retention in the kidney by coordinating the actions of several organs, including the brain, the vasculature
13 and the kidney and ultimately raise blood pressure. Factors such as genetics and environment further contribute to oxidant generation and inflammation. Furthermore, other cell reactions, which include calcium signaling and endoplasmic reticulum stress, are similarly disturbed in different cells in hypertension. Page's Mosaic Theory has been instrumental in studies of molecular and cellular signals in the context of hypertension, and has contributed to the understanding of high blood pressure.26
As further elaboration of The Mosaic Theory, available literature suggests that an individual’s health is determined by interaction of several factors: genetics (for example, height and gender), natural physical environment ( atmosphere, temperature, rain forests), and human made physical environment (technology, overcrowding, water systems, noise, traffic), social environment (income, marital status, education, culture), access to and quality of health care (hospitals, clinics, health insurance), and personal behavior (eating habits, exercise, sleep).
Natural and human made physical environment can be controlled by public policies that keep air and water clean, lower noise pollution and provide proper sanitation facilities. The government can also ensure provision of adequate and access to health care. The most difficult factor to deal with is social environment and personal behavior, in changing health habits. Yet, understanding individual health behavior is critical to designing public health programs to change health behavior and promote healthy living.
Models that address patterns by which prevention activities can be achieved are critical. Behavior change can be approached from an individual, interpersonal and community level and several individual, interpersonal and community level theories have been advanced to explain how an individual’s health behavior is determined.
14
Individual
An individual bears responsibility for his or her health. Factors that influence the individual such as beliefs, motivation, knowledge, past experience and attitudes will affect an individual’s views towards health change. Human health behavior models have been used in order to determine the best health policies and program to use in disease prevention. One such model is the health believe model (HBM). Health belief model is the most commonly used in designing disease prevention, health education and promotion programs. The model was developed in the 1950s to explain why U.S. Public
Health Service screening programs for tuberculosis and other diseases were not successful.28-30 The central concept of the HBM is that in other for individuals to accept a health behavior, what they perceive to be the threat in reference to the disease and what they considered to be the benefit to their actions to prevent the disease must be more than the barriers to the behavior. The key constructs of this model are: perceived barriers to action, perceived susceptibility, perceived severity, self-efficacy, perceived benefits, and cues to action of action.31,32 This theoretical framework is useful in understanding sodium consumption and high blood pressure.
Interpersonal
Society plays a critical role in an individual’s perception of health and risk of disease. The social environment will influence behavior. For example, advice and support from family and friends are crucial in how an individual will react to health messages.
The impact of opinion leaders in society will also influence what an individual does in changing health behavior. Furthermore, people will change behavior if they know that the change is urgent and will improve their health. And, as individual change, the society will
15 also change. This theoretical framework is relevant in explaining sodium consumption and its impact on high blood pressure.
Another theory that is useful in understanding sodium consumption and high blood pressure in the US population is the social cognitive theory (SCT). This theory holds that health behavior change is the result of interactions among the environment, personal factors, and attributes of the behavior itself. Self-efficacy is one of the most important characteristics that determine behavioral change. The theory posits that part of an individual’s knowledge acquisition is directly related to observing others in the context of social interactions, experiences, and outside media influences. Based on the theory, when people observe a significant behavior and its consequences, they remember the sequence of events and use this information to guide subsequent behaviors. The key constructs of this theory are: self-efficacy, reciprocal determinism, behavioral capability, outcome expectations, and observational learning.33
The theory of planned behavior (TPB) can also offer explanation on the impact of sodium on high blood pressure. According to TPB, people’s behaviors are linked to their beliefs. People’s perceived control over the opportunities, resources, and skills needed to perform a behavior affect behavioral intentions, as do the two factors in the theory of reasoned action. The key constructs in this theory are: attitude towards the behavior, outcome expectations, value of outcome expectations, subjective norms, beliefs of others, desire to comply with others, and perceived behavioral control 33
Community
The community plays an important role in disease prevention. For prevention programs to work, the community must be involved. The ecological theory holds that
16 effective interventions must influence multiple levels because health is shaped by many environmental subsystems, including family, community, workplace, beliefs and traditions, economics, and the physical and social environments. The key constructs of this model are: intrapersonal, institutional, community, and public policy.
Another community model that might explain patterns of dealing with chronic diseases such as high blood pressure is the community organization model. This model holds that public health workers help communities identify health and social problems, and they plan and implement strategies to address these problems.34,35 According to this theory, active community participation is essential. The key constructs of this model are: social planning, locality development, and social action.34,35
Organizational change theory might also explain patterns of community involvement in changing health behavior. The theory holds that certain processes and strategies might increase the chances that healthy policies and programs will be adopted and maintained in formal organizations.36 The key constructs here are: definition of the problem (awareness stage), initiation of action (adoption stage), implementation of change, and finally, institutionalization of change. These theories explain how the community can be instrumental in adopting healthy behaviors in order to combat high blood pressure.36
Finally, self- management education programs of chronic diseases are relevant to chronic disease management. The idea behind self-management programs is to enable patients to acquire preventive or therapeutic health care activities. This is done in collaboration with health care providers. The programs emphasize the role of patient education in preventive and therapeutic health care activities and consist of organized
17 learning experiences which are designed to facilitate adoption of health-promoting behaviors. These programs are separate from clinical patient care, but are run with the collaboration of health care professionals. Self-management education programs exist for many chronic conditions, including hypertension.37
1.3.2 Summary of the theoretical framework
The individual, interpersonal, and community theories outlined above provide a useful framework in explaining the role of all the stakeholders involved in contributing to sodium consumption and its impact on blood pressure in the US. These stakeholders include: individuals, the community, public health institutions, the government, and the food industry (farmers, food processing and packaging industries and restaurants). At the individual level are beliefs about the impact of sodium in raising blood pressure and the danger sodium poses to long term health. At the community and institutional level are the
CDC, AMA, and other organizations that are responsible for public health programs and messages meant to raise public awareness on the dangers of high blood pressure. At the industry level are the restaurants, food industries and associations that market food products and are responsible for determining the amount of sodium in processed foods.
The theories can also provide a useful framework for bringing all the stakeholders together and designing programs that can lead to lower sodium consumption and consequently, lower blood pressure in the US population.
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CHAPTER 2
LITERATURE REVIEW
2.1 Literature Search Strategies
Review of literature was conducted to identify articles on the impact of sodium on blood pressure. Relevant studies were obtained from PubMed, Medline EBCOS, JSTOR,
Google Scholar search and Web of Science, including books. The selection processes was done according to significance to the topic. Exclusion and inclusive criteria was done as follows: The articles that were closely related to the study topic (topic sentence) were reviewed and summarized for the inclusion and exclusion criteria. Search words included: blood pressure and sodium, dietary intake and blood pressure, blood pressure, hypertension, prospective study, and sodium chloride. Medical Subject Headings
(MeSH) key words. Abstracts were read to make sure each article was related to the topic sentence and only full text articles were included in the review. There was no age cutoff for the articles as long as they were relevant to the topic.
2.1.2 What Is High Blood Pressure/Hypertension?†
Etiology and Definition of High Blood Pressure/ Hypertension
According to the Mayo Clinic38 blood pressure is determined by how much blood a person's heart pumps through the arteries and the amount of resistance to the blood flow in the arteries, resulting in a force that blood exerts on the arterial walls as the heart pumps blood. Arteries are blood vessels that carry blood and oxygen from the heart to the rest of the body. Blood pressure continuously varies in the arteries because the heart pumps blood intermittently. Blood pressure is measured in millimeters of mercury
† In this paper high blood pressure and hypertension are used interchangeably 19
(mm/Hg) and has two measurements: systolic pressure and the diastolic pressure. Systolic blood pressure (SBP) measures blood pressure in the arteries as the heart contracts or beats to send the blood to the rest of the body while diastolic blood pressure (DBP) measures the blood pressure in the arteries while the heart is at rest, between beats.2,13
Individuals are classified into three groups of blood pressure based on their measurements. Individuals with blood pressure between 90/60 and 120/80 have normal blood pressure, those below 90/60 have low blood pressure (hypotension), those between
120/80 -139/89 are pre-hypertensive, and those with blood pressure above 140/90 are hypertensive.13,39,40 The blood pressure definition is based on The Seventh Report of the
Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High
Blood Pressure: The JNC 7 Report (7).40 High blood pressure is a condition where the force of blood against artery walls is high enough that it eventually results in health problems. The more blood the heart pumps and the narrower the arteries, the higher the pressure, leading to high blood pressure (hypertension).
There are two types of hypertension: primary hypertension and secondary hypertension. Primary hypertension, also known as essential hypertension, occurs gradually over a long period of time and is associated with ageing. Secondary hypertension, on the other hand, is caused by existing underlying conditions which include thyroid problems, kidney disease, defects in blood vessels, some medications, illegal drugs, alcohol abuse and sleep apnea.41
According to Rodriguez et al. hypertensive crisis can occur when blood pressure is not controlled. They defined hypertensive crisis as systolic blood pressure greater than
180 mm Hg or diastolic blood pressure greater than 120 mm Hg.42 Hypertensive crisis
20 can be classified as "hypertensive emergencies", the presence of acute or ongoing end- organ damage or as "hypertensive urgency," a situation when blood pressure is elevated with the absence of target organ damage involvement and no immediate threat to the integrity of the cardiovascular system.40,42,43 One can be considered to have high blood pressure if the person has been told at least twice by a physician or other health professional that one has high blood pressure.
Hypertension has been described as a silent killer because it presents no warning signs or symptoms until it is too late. Meanwhile, it will have damaged blood vessels and the heart. If not checked, high blood pressure increases the risk of stroke and heart disease, two of the leading causes of death in the U.S. 39 It can also lead to kidney damage and other vital organs. Most heart failures are caused by high blood pressure.
Hypertension related deaths in the US are estimated at 600,000 a year. 44 This number is almost evenly distributed between male and female. Existing evidence shows that despite increased availability of a wide variety of medications to treat hypertension, most people cannot control their hypertension. 45 According to the Center for Disease
Control/NCHS, data from NHANES for 2009 -2012, almost 47% of adults aged 20 and over who have hypertension continued to have uncontrolled high blood pressure in. The
Centers for Disease Control (CDC) estimates that there is one in three adults who suffer from hypertension. This translates to about 77.9 million Americans with high blood pressure. Further, according to the CDC less than half of those Americans suffering from the condition, have their blood pressure under control.46 The following figure shows how the body regulates blood pressure.
21
Figure 1: How the body regulates blood pressure47
Evidence shows that blood pressure is not constant and continually adjusts cardiac output and arterial resistance to provide oxygen and nutrients to tissues and organs throughout the body. When blood pressure falls, the nervous system (1 on the above figure) sends a signal to the kidneys to release renin into the blood stream which creates angiotensin. Angiotensin gets converted into smaller pieces (2 on the graph) causing small arteries to constrict, leading to high blood pressure. Angiotensin (3 on the graph) spurs the adrenal glands to release another hormone, aldosterone. The aldosterone causes the kidneys (number 4 on the graph) to retain sodium and water, which raises blood volume and blood pressure.
22
2.1.3 Risk Factors for High Blood Pressure
There are several risk factors associated with high blood pressure: Age: Research shows that hypertension risk increases with age. Among men, hypertension risk begins after age 45 while for women the risk begins are age 65. According to Martins, et. al. increase of dietary salt intake and age are associated with increase in hypertension.48
Evidence shows that the risk of blood pressure and the rate of complications of high blood pressure such as stroke, kidney failure and stroke are more prevalent among blacks.
Other risk factors such as family history, physical inactivity, being overweight and obese, using tobacco, too little vitamin D, too much alcohol, stress and certain chronic conditions, being diabetic and Sodium consumption contribute to high blood pressure. 49
2.1.4 Gender, Race and Blood Pressure
In America and around the world, more women die from high blood pressure- related complications.50,51 David Martin and colleagues report findings that show that there are significant differences in lifestyle and environmental risk factors for hypertension between genders and among racial and ethnic groups. The results further show that African-Americans have a higher dietary salt intake and also have higher sensitivity to blood pressure changes arising from dietary salt consumption. 48
Populations that consume diets that are low in sodium have been shown not to have high blood pressure as they grow older. 52 Further, according to the NHANES data, a higher percentage rate of men having hypertension than women until 45 years of age; from 45 to
54 and from 55 to 64 years of age, the percentage of men and women with hypertension is similar. After that, a higher percentage of women with hypertension than men.53 In a study conducted on the prevalence of hypertension in Hispanic and non-Hispanic White
23 populations by Lorenzo Carlos et. al., "in Spaniards (odd ratio [OR], 1.53; 95% confidence interval [95% CI], 1.24 to 1.90).A deficit in hypertension prevalence was statistically significant in Mexican nationals (OR, 0.67; 95%CI, 0.53 to 0.85) and close to significance in San Antonio Mexican Americans (OR, 0.86; 95% CI, 0.71 to 1.03)."54
Wright et al conducted a study looking at ethnic differences to salt sensitivity using crossover protocol among 199 hypertensive and normotensive persons giving low- salt and high salt diet (20mEq/d and 200 mEq/d respectively) showed a higher prevalence of high blood pressure among black women. Ethnic difference in response to dietary sodium loading have been reported, with a greater rise in systolic blood pressure in
African-American women compared to white women (23mmHg vs. 15 mmHg, respectively). 55 Table 1 shows high blood pressure mortality cases by gender and race.
According to the table, in 2010 more females died from high blood pressure regardless of race. However, when looking the death rate per 100,000, black men had the highest death rate at 50.2, followed by black women at 37.1.
Table 1: Number of High Blood Pressure Mortality cases by Gender and Race
Year 2010 Whites Blacks White Males 20,819 Black Males 6,670 White Females 26,798 Black Females 6,923
Total deaths 47,617 13, 593 Death rate per 100,000 Whites Blacks White Males 17.2 Black Males 50.2 White Females 15.0 Black Females 37.1 The 2010 overall death rate from high pressure was 18.8 per 100,000 Source: American Heart Association (2010)
These results show that in general more females and blacks are dying from high blood pressure -related condition than whites. There is ample research evidence that
24 shows that blacks disproportionately die from high blood pressure.15 Table 2 below shows ten years of sodium intake trend from NHANES data for adults ages 19 to 50 years and 51 years and over of different ethnicities. The table shows that sodium intake consumed by Americans irrespective of their gender and ethnicity was more than 2300mg
/day. The results also show that for each NHANES cycle, male adults (ages 19-50 years) and older adults (ages 51 years and above) consistently consumed more sodium than female adults and female older adults respectively in all the ethnic groups.56
Table 2: Sodium Intake Trends by Age and Gender Groups over 5 NHANES Cycles in Population (solid line 19 to 50 years, dotted line 51 years and up)57
2.2 Diabetes and blood pressure
According to Tuck et al.58 high prevalence of high blood pressure in diabetics is caused by the increased salt sensitivity due to sodium retention, as well as increased body weight. Damaged blood vessels among diabetics also contribute to high blood pressure.
Furthermore, evidence shows that the main cause of kidney disease and failure is high
25 blood pressure. 59 The association between hypertension and diabetes in young adults was reported in a study by McDonough and Wilhelmj.12 The prevalence of seniors with diabetes ages 65 and older with diabetes was 11.8 million. Studies show that about 25.9% of children who consume high sodium diet tend to have hypertension.60 61 However, up to 77% of people with type 2 diabetes are affected by hypertension.62 Trends in blood pressure control treatment in diabetics show that only 30% of diabetics with high blood pressure have their blood pressure under control.63 According to the center for Disease control blood pressure level is a major determinant of cardiovascular morbidity and mortality in individuals with diabetes mellitus. Further, guidelines now recommend intensive blood pressure lowering treatment for many individuals with diabetes. 64 The
CDC reports that for every 10 mmHg reduction in systolic blood pressure, the risk for any complication related to diabetes is reduced by 12 %. Also, major cardiovascular events associated with diabetes can be reduced by 50% when systolic blood pressure is reduced from 90mmHg to 80 mmHg in people with diabetes.65
2.2.1 Obesity and high blood pressure:
There is direct evidence that shows that the left ventricular muscle mass increases because of large body size, obesity, and high blood pressure. 66 Obesity is included in the cluster of metabolic syndrome risk factors for cardiovascular disease ( figure 2).67 The cluster of risk factors of obesity includes diabetes mellitus, cardiovascular disease including hypertension, chronic kidney disease, and metabolic syndrome. Sodium retention is commonly found in obese individuals. There is a decrease rate of hypertension when individuals lose weight. 68
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Figure 2: The cluster of co-morbidities associated with and aggravated by obesity69
2.2.2 Sodium and High Blood Pressure
Sodium is an essential nutrient necessary for maintenance of plasma volume, acid-base balance, transmission of nerve impulses and normal cell function.70 Normal sodium plasma concentration is 136-145mM. Hyponatremia results when sodium level in the blood drops below 135 mEq per L (135mM).71 Salt is the combination of sodium and chloride and is very important to the human body. When combined with potassium, salt contributes to the proper functioning of the nerves and in the contraction of muscles in body. Salt contributes to electrolyte balance, fluid balance and pH balance. However, too much salt has been found to be harmful to the body.‡ High sodium consumption contributes to the pathogenesis of hypertension.
‡The conversion of different units for sodium and salt is: 1 gram of sodium =2.5 grams of salt; and1 mol salt = 58.8 milligram sodium; 1gram of salt = 0.4 gram sodium; and 1 The amount of sodium that is in various amounts of salt (sodium chloride) is: 1 gram of sodium = 2.5 grams of salt; 1 mmole of salt = 22.99 milligrams of sodium; 1 gram of salt = 17 mmole of sodium. Salt (sodium chloride) is the major source of dietary sodium, contributing approximately 90% of our daily intake. (1 mole of sodium = 22.99 grams; 1 mole of chlorine = 35.45 grams; 1 mole of sodium chloride = 58.44 grams
27
Five thousand years ago, Emperor Huangdi of China wrote: “If too much salt is used in food, the pulse hardens.” He is considered to be the first to suspect that eating dietary salt might contribute to high blood pressure.72 Grollman and his collaborators reported in 1945 that sodium restricted therapy is essential in blood pressure reduction.73
In 1960, Dahl published scientific evidence linking salt consumption to blood pressure.
Dahl's study is considered to be the first scientific evidence for a positive association between salt and blood pressure.5 Other studies such as randomized control clinical trials, animal experiments have been conducted since Dahl's study was conducted.
Excessive sodium consumption increases blood pressure resulting in increased risk for stroke, heart failure and renal disease74. Reduction in sodium intake 1,200 mg of sodium per day would lead to a decrease in new cases of coronary disease by between
60,000 to 120,000 and stroke cases by between 32,000 and 66,000 leading to savings of
$20 billion a year in medical cost savings.46,75 The dietary guidelines of America 2005 recommend daily sodium intake of no more than 1,500 mg/day for specific groups such as people with hypertension, blacks, and older adults. Other adults should take no more than 2,300 gm/day of sodium.
28
Figure 3: A flow chart showing the link between daily sodium, blood pressure, morbidity or mortality
Adapted from World Health Organization76
Figure 3 above illustrates how sodium intake affects high blood pressure. The figure shows that high sodium intake leads to high blood pressure which in turn results in cardiovascular diseases.
A large body of scientific inquiry shows that sodium intake has a significant impact on high blood pressure. More research is being done in this area due to the increased cases of high blood pressure and stroke. Initially, it was thought that sodium intake should be controlled only among older Americans. However, cases of blood pressure are being seen among younger adults as well. The CDC reports that an average
American consumes about 3,436 gm of sodium per day15,77. This is more than twice the recommended daily sodium intake. An average hamburger in McDonald's, one of the popular fast food restaurants, contains 800 mg of sodium. With the addition of French fries and condiments, one will have consumed the recommended daily sodium intake in
29 one meal. An observation of an intervention follow-up study was conducted by 78Cook et al. on the long term effects of dietary sodium reduction on cardiovascular outcomes.
Study participants were divided into two groups. One group received salt-intake reduction intervention and the other group served as a control. 78At the end of the study vital statistics were obtained from the two groups. These data included risk of cardiovascular and other information on morbidity. The results showed that the group that received sodium reduction intervention had 25% lower cardiovascular risk than the control. The study concluded that sodium intake reduction may result in reduction of cardiovascular disease. 78,79
Pimenta conducted an observational study looking at the role of sodium sensitivity in the development of resistant hypertension. The study looked at the effect of sodium restriction in subjects with resistant hypertension by using 12 subjects who had resistant hypertension and were on anti-hypersensitive medication.80 Findings of the study show that low sodium diet results in reduction in systolic and diastolic blood pressure by 22.7 and 9.1 mmHg respectively. The research concluded that high sodium intake contributes to resistance to antihypertensive treatment.80
A study done by Sacks, et al81 on the effects of reduced dietary sodium and dietary approaches to stop hypertension (DASH) DIET on blood pressure using 412 randomly selected participants found that reducing sodium intake resulted in a significant lowering of both systolic and diastolic blood pressure in a stepwise fashion, with both the control diet and the DASH diet. The study also showed that dietary sodium from
30 controlled diet had almost twice as great an effect on blood pressure as it did with the
DASH diet (p<0.001 for the interaction).
An Intersalt study was done by Intersalt Cooperative Research Group using sodium intake and BP in adults using 24 hour urinary sodium in 1988. In this cross population analyses study, there were 10079 men and women aged 20-59 sampled from
52 centers around the world with a median age 40. The findings show that there was a significant positive relationship between 24 hour urinary sodium excretion and systolic blood pressure.82,83 Another Intersalt study was conducted in the 80s. This study reported that populations with low dietary salt intakes (i.e. less than 3 g/24h or 1.1 g of sodium/24h) experienced lower blood pressure increase with age and that the increase in systolic blood pressure with age was positively associated with dietary salt intake.
2.2.3 How Sodium Increases Blood Pressure
Studies show that even though sodium is an essential nutrient in the human body, the amount needed by the human body per day is no more than 184-230 mg/day 5.84 The words salt and sodium are often used synonymously, although on a weight basis, salt comprises of 40% sodium and 60% chloride. Historical review of sodium consumption during the evolution of human beings shows that human beings did not have the same exposure to salt that we have today, as shown in figure 4 below. They were only exposed to the salt that occurred naturally in foods and water85. When agricultural and human husbandry was developed and because of the need to have food reserves, it became necessary to preserve food by adding salt to dairy products, meats and fish and as a result more salt was introduced into the human diet. However, the human species evolved
31 during a time of low sodium diet and thus the body was adapted to retention of only limited salt naturally present in foods. As a result, even though we consume large amounts of salt in our diet, the kidney is not adapted to excreting large amounts of sodium from the body.
When foods that are high in salt are digested there is increase in the amount of sodium in the blood stream, which in turn leads to water retention in the kidneys. When more water is stored, it reduces the ability of the kidney to recycle or gets rid of water.
This puts strain on the kidneys, arteries, heart, and brain, leading to increased blood pressure. 86
Figure 4: The paleolithic diet vs modern diet 47
2.2.4 Sodium Consumption in the US and Globally
As the American population becomes increasingly adapted to a fast life style, and more and more people join the labor force, so too is the increased consumption of processed, frozen, and restaurant foods which are high in sodium. Further, sodium is the main component of preservatives in most frozen foods87. The introduction of many
32 cultural foods in the American diet has good economic advantage because it is fast and is at relatively affordable prices but these foods are high in sodium. High sodium intake leads to high blood pressure. When salt intake is reduced, blood pressure begins to decrease for most people within a few days to a week.44 Figure 5 shows the trend in sodium consumption among men and women in the US using the NHANES data set. The figure shows that both men and women consumed far more than the recommended daily sodium intake. Men now consume more than 4,000 mg of sodium per day on average while women consume 3,000 mg per day on average.
Figure 6 shows the amount of sodium contained in a ham sandwich. The sodium level of the of the sandwich containing cheese, ham, and condiments (1522 mg) is almost two times the sandwich with low sodium (852 mg) and this is only in one meal. When one considers that the recommended salt intake per day is no more than 2400 mg/day for all populations and 1500 mg/day for populations at risk, it’s evident that with diets consisting of processed foods, the American consumer ingests far more than the daily requirement of sodium88
In April 2013, the United States Food and Drug Administration (FDA) issued two proposed regulations that would ensure calorie labeling on menus, chain restaurants, menu boards, retail food establishments, merchandize in vending machines which have twenty or more locations and many more.89 The proposed regulation is based on the 2010 Affordable
Health Care Act sitting on putting food information such as fat, calorie and sodium content on the food menu.90
33
Figure 5: The Mean Dietary Sodium Intake among U.S. Men and Women Ages 18-74 years – NHANES 1971-201091
.
34
Figure 6: The Amount of Sodium Contained in a Ham Sandwich92
1522 mg 852 mg
High sodium consumption is not restricted to the United States. Over consumption of daily sodium is common throughout the world, especially the industrialized countries.
93The burden of high mortality rate caused by high blood pressure is a global challenge since hypertension and related heart disease claim about 2.5 million lives globally each year.10
According to World Health Organization, industrialized countries consume much more salt than less developed countries.76 What is also clear is that a country like China which is developing rapidly has high sodium consumption. With increased economic development comes the reliance on processed foods and dining in restaurants, both of which contribute over three quarters of the sodium consumed in industrialized countries.
Meanwhile, some countries have taken national initiative to regulate sodium intake by working with food manufactures to decrease the amount of sodium in foods that they manufacture.
35
2.2.5 Sodium Consumption and the Food Industry
While the Food and Drugs Administration (FDA) has required the display of nutritional fact labels for off-the-shelf food items to inform healthy consumer choices, fewer successes have been made. As consumers become aware of harmful food contents on the common grocery shelves, marketers have also become increasingly clever in the way they represent nutritional facts on food labels. For example, shoppers may select one type of low- fat yogurt from shelves without realizing that servings from other brands contain more sugar than ice cream. For this reason, the FDA came up with stringent specifications of how to represent nutritional facts on food items on grocery shelves. Comparing food items by their food labels can help consumers choose the best value for their health. The Department of
Health and Human Services (DHHS), FDA, Center for Food Safety and Applied Nutrition
(CFSAN), provide requirements under the Federal Food, Drug, and Cosmetic Act (FFDCA) in its amendments. Research shows that eating out by Americans increased by 200%, from
1977 to 1995. And as a result, Americans are consuming excess sodium from routinely served and processed foods. 94 A 2015 survey showed that on average Americans eat out
4.5 times per week. Most of the food items that American eat are high in sodium some food items contain more that the daily recommended intake of salt (2300 mg). The increased sodium intake has posed a public health challenge due to the increase cases of hypertension and cardiovascular diseases. Any strategy to reduce sodium intake in the
American population requires the cooperation of the food industry, restaurants and public health institutions
An example is the vigorous salt reduction campaign in the United Kingdom which has resulted in an estimated population-wide reduction in sodium intake of close
36 to10%95 . Currently, in the US, the restaurant industry is working with food and drug administration (FDA) to establish sodium reduction in restaurants and on packaged foods.
2.3 Salt reduction in the US and other countries
The American heart association in conjunction with the center for disease control
(CDC) has made recommendations to reduce daily sodium intake to 2300mg per day. In
England, the Department of health has encouraged food manufactures to incrementally reduce added sodium. They targeted that the sodium intake for individuals will be
200mg/d which was estimated to have saved 6000 lives in 2010.
The North Carolina state legislature recently enacted a legislation aimed at reducing heart disease and stroke by encouraging citizens to reduce the amount of salt in their diet. The resolution stated that if the average American can reduce consumption of salt to 1,500 mg of sodium per day, there would be a nationwide decrease of blood pressure case by 25.6% and $26.2 billion in health care saving.96
In New Zealand/Australia, the National Heart Foundation has developed a sodium lowering labeling program called “Pick the Trick” which identifies foods that meet strict standards for sodium, as well as fat, fiber and calories. In Finland, the government requires that foods are labeled “high salt” since the 1970’s.
This action has resulted in reduction of stroke and blood pressure in the country by 60%. In a systemic analysis of 24 hours urinary sodium excretion and dietary surveys worldwide on sodium intakes in 1990 and 2010, Ezzati et al used Bayesian hierarchical modeling to convert self- reported dietary values to comparable 24 hour urine values and was informed by regional hierarchies and country level covariates.97
37
Based on this study, the global mean for sodium intake in 2010 was 3.95 g/day, with a 95% confidence interval of 3.89 to 4.10. Sodium intake in men was almost 10% higher than in women. East Asia, Eastern Europe and Central Asia had a mean of more than 4.2g/day. Results in Middle East/ North Africa and Central Europe showed sodium intake of 3.9 to 4.4g/day. North America and Western Europe ranged from3.4 to
3.8g/day. These results point to a modest increase in sodium intake between 1990 and
2010.97 The results further point to the fact that sodium consumption is the lowest among industrialized parts of the world, and programs to reduce sodium consumption would achieve greater health benefits for populations in less industrialized countries. Still, at 3.4 to 3.8 g/day, sodium consumption in the US is high compared to the recommended daily intake of 1.5 to 2.4 g/day.
Figure 7: Global Sodium Consumption98
38
2.3 Sodium Consumption, Body Mass Index and Blood Pressure
Body Mass Index (BMI) is calculated by dividing an individual’s weight in kilograms by the height in meters squared to determine whether one is underweight, overweight, or normal weight. A BMI of less than 18 indicates that one is underweight, a
BMI of 18 to 24.9 is considered healthy, and a BMI of 25 to 29.9 is considered overweight while a BMI of 30 and up is considered obese.
There is a growing body of literature that has looked at the association of blood pressure and BMI and sodium consumption. A team of researchers conducted an analysis of the association between blood pressure and BMI across three countries, one in Africa and two in Asia—Ethiopia, Vietnam and Indonesia-- using data on BMI, blood pressure, and other background data on a selected sample of participants. This data was obtained using the STEP wise approach to surveillance (STEPS) developed by WHO. Results also show that the mean BP levels increased with increase in BMI. According to the researchers, the risk of hypertension was higher among population groups with overweight and obesity individuals. BMI was significantly and positively correlated with both systolic blood pressure (SPB) and diastolic blood pressures (DBP) in all the three countries. The study also found out that prevalence of hypertension increases sharply at higher BMI quintiles.99
An 11-year prospective population study conducted by Droyvold et. al 100 on the impact of body mass index on blood pressure reported a strong association between change in BMI and change in SBP and DBP among both men and women with the association being strongest among those who were 50 years and older. Further, change in
SBP and DBP was higher for those where BMI changed between the first and second
39 survey than for those who kept the same BMI in both surveys. 100The study also reported that both men and women who increased their BMI had significantly higher SBPs compared to those who had stable BMI. On the other hand, participants with a reduction in BMI had a significantly lower increase in SBP compared to the stable group. This study confirms the findings by other studies which show that BMI has an independent impact on blood pressure in both men and women and that people who increase their
BMI are at a higher risk for hypertension. 100Droyvold notes that the exact mechanism between change in BMI and blood pressure is still not understood. They point out that what is known is that weight gain stimulates sympathetic activation and that insulin and lept in might be involved. Further, activation of the renin-angiotens system as well as physical compression of the kidney may provide the association linking body weight and increased blood pressure.
Stevens looked at the effect of age on the association between BMI and mortality on American participants who had been followed for over 12 years. The study reported that higher body mass index is associated with higher mortality from cardiovascular disease and other causes; however this risk decreases with age.101 They looked at the impact of weight on blood pressure among an ethnically diverse sample of adolescents in
Britain, hereby known as Medical Research Council DASH study. 101Among the study participants, 23% of the girls and 19% of the boys were overweight, and 8% were obese.
Those who were overweight and obese had a higher prevalence of high normal and high blood pressure compared to those not overweight at the ages of 11-13 years. According to the authors, the tendency for high blood pressure among adult Black African was not evident among the participants.
40
Droyvold measured change in BMI and its effect on blood pressure. Their results confirmed that BMI is a factor in blood pressure increase. Other research used different data sets and came to same conclusion that BMI contributes to blood pressure. In addition, intervention studies of cardiac patients in hospitals and cross country studies also found a strong correlation between BMI and blood pressure. 100
2.4 Education, Sodium Intake and Blood Pressure
A number of studies have investigated the relationship between education and sodium intake and hypertension in a variety of human populations. The results show that depending on the subpopulation being examined, in some cases hypertension and sodium consumption have an inverse relationship with education and in other cases there is a positive correlation between hypertension and sodium consumption and education.
McLaren and colleagues reported findings of a study conducted to look at the impact of education on sodium consumption. These findings show a positive association between education and sodium in women and negative association between education and sodium in men. Women of higher education consumed more sodium than women of lower education in 2004. On the other hand, men showed positive income to sodium relationship in 1970/1971 but showed a negative association in 2004. 102
A study done by Nawi Ng and colleagues on the preventable risk factors for non- communicable diseases in rural Indonesia showed a higher prevalence of hypertension among the richest quintile with high education compared (the study classified participants who were more than 45 years old with higher educational attainment as the richest quintile) with the poorest quintile with low educational standards. 103
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Colhoun et al. conducted a study on the association between socioeconomic status and high blood pressure and found that there was a higher prevalence of obesity, high salt and alcohol intake among wealthier socioeconomic groups.104
Earlier studies conducted between 1940 and 1960 in the United States and United
Kingdom found that individuals with high education and high social economic status were at greater risk of high blood pressure.105 In a study done in rural Swedish using a health examination survey, black men had significant inverse relation between educational level and blood pressure among younger subjects. The results further indicated that among the men with high blood pressure, men and women with less formal
106 education had the highest rate of hypertention. In another study conducted by Zhijie
Yu and colleagues on 4000 individuals whose age range from 15 – 69 years on socioeconomic factors and blood cardiovascular disease showed that more women than men have risk factors to cardiovascular than men.107
2.4.1 Economic Impact of Hypertension
According to the world health organization, cardiovascular disease accounts for about 8 to 22% of a country’s expenditure. Families with loved ones suffering from cardiovascular diseases are affected financially because of the high cost of treating cardiovascular disease. Families also are also affected socially as well due to disability and death of loved ones.13 The American Heart Association estimates that costs of hypertension (direct and indirect costs) are well in excess of $93.5 billion per year. The
Association further estimates that cardiovascular disease and stroke are responsible for
17% of the country’s total annual health expenditures108. When comparing the cost involved in treating high blood pressure, 109 "number needed to treat" analysis shows that
42 the costs of drugs to prevent one death would be $1800 (1104 Euros) in Africa and
$14000 to $1m (8589 to 613496 Euros) in the United states.
According to Feng11, there is enough research evidence to show that the reduction of salt intake can prevent hypertension and cardiovascular disease worldwide. According to the authors, the challenge faced with policy makers is to engage other countries with the aim of implementing specific country policies that can result in reduction of population salt intake. These actions can result in improvements in health related cost savings—the cost associated with salt intake are estimated to be between 5% to 15% of the gross domestic product in high income countries and 2.5%-8% in Latin America and
Caribbean. The study shows that Latin America has the highest stroke mortality, a key outcome of high blood pressure. Feng and his team confirm other research findings which show that salt intake is the major cause of increased blood pressure. The authors report that the relationship between salt intake and high blood pressure come from epidemiological studies, migration, and population based intervention, genetics, and treatment trials.
2.4.2 Effects of Sodium on Blood Pressure Using Dietary Studies
A study done by Sacks et. al. using diet rich in vegetables, fruits and low-fat dairy products, in hypertensive and nomatensive individuals on the effects on blood pressure of reduced dietary sodium and the Dietary Approach to Stop Hypertension (DASH) diet with 412 randomly selected participants showed that dietary pattern with low sodium reduced systolic blood pressure by 7.1 mmHg in adults without hypertension and by 11.5 mmHg in adults with hypertension.81
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In a post hoc analysis of long term effects of dietary sodium reduction on cardiovascular disease trail by Cook and his colleagues; a Trials of Hypertension
Prevention (TOHP) participants randomized to low sodium interventions had 25% lower risk of cardiovascular disease (RR, 0.75; 95% CI, 0.5-0.99) after 10 to 15 years of follow up following the original trial that showed limited association of dietary sodium consumption and its association to heart disease.78
Randomized control study done on 462 hypertension and normotensive Northern
Chinese population in hypertensive subjects, there was an overall decrease in the mean systolic and diastolic blood pressure between the two groups, a 4 mmHg (95% confidence interval 2 -6 mmHg, P<0.5) decrease between the two groups.110
2.4.3 Effects of Sodium on Blood Pressure Using Urinary Studies
In a recent cross sectional study done using 24- hour urine collection in New
York City on 1656 adults on the association of sodium intake with elevated pressure,111 a higher sodium intake (3395 mg/d) was associated with higher blood pressure for non-
Hispanic Blacks and 3066 mg/d (P<.05) for non- Hispanic Whites. The study concluded that sodium intake was higher in non-Hispanic Blacks.111
Even though data from the 112 Framingham cardiovascular study did not reveal any significant differences between blood pressure and 24 hour urinary sodium output among the four groups divided according to sodium excretion, there are many other urinary analysis studies that shows positive correlation between high salt consumption and blood pressure.
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In another study, Humayika et al. 113 conducted an 18 month randomized trial using 327 no-hypertensive individuals who were assigned to reduced sodium behavioral intervention and 417 who were assigned to the control group. Results showed that there was a mean net reduction in urinary sodium excretion of 44 mM (1.0g) per day and a reduction of systolic/diastolic pressure of 2.1/1.2 mm Hg pointing to a direct dose- response relationship for both systolic and diastolic blood pressure.
2.4.4 Effects of Sodium on Blood Pressure Using Animal Studies
Animal studies provide researchers with an opportunity to study the effect of sodium in a controlled environment. In a 20 month study done on a colony of 26 chimpanzees on the effects of increased salt intake on blood pressure, half of the chimpanzees were given fruits and low sodium vegetables and the other half had salt added progressively to their diet during the 20 months. The ones that were given the high salt diet showed significant increase in diastolic and systolic blood pressure.114
In another study done by Paul Elliott et. al. on the change in salt intake and how it affects blood pressure in chimpanzees, a species closest to Homosapins, results showed the chimpanzees that were fed with biscuit diet of high sodium content over 3 years had a significant level of blood pressure increase by 2- tailed P<0.001, unadjusted for age sex, and baseline weight and systolic pressure higher by 10 mm Hg. 115 These results show that there is a need to intensify public health effort to lower salt consumption.
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2.4.5 The Impact of Sodium and Potassium Interaction on blood pressure
Several studies have been conducted to investigate the interaction between sodium and Potassium and their impact on blood pressure. These studies show that when sodium and potassium are combined in certain proportions they may contribute to lowering of blood pressure. Zhang et al., for example looked at the association between usual sodium and potassium intake and blood pressure and hypertension among U.S. adults. The study analyzed data on 10,563 participants aged 20 years in the 2005–2010
NHANES data who were neither taking anti-hypertensive medication nor on a low sodium diet.116 The researchers used measurement error models to estimate usual intakes, multivariable linear regression to assess their associations with blood pressure, and logistic regression to assess their associations with hypertension. The results of this study provide population-based evidence that higher sodium and lower potassium consumption are associated with hypertension.116
In another study, O'Donnell, et al. investigated the association between urinary sodium and potassium excretion and mortality and cardiovascular events. The researchers obtained morning fasting urine samples from 101,945 persons in 17 countries and estimated 24-hour sodium and potassium excretion (used as a surrogate for intake).117
The researchers further examined the association between estimated urinary sodium and potassium excretion and the composite outcome of death and major cardiovascular events.117 Their findings showed that sodium intake between 3 g per day and 6 g per day was associated with a lower risk of death and cardiovascular events than was either a higher or lower estimated level of intake, while a higher potassium excretion was associated with a lower risk of death and cardiovascular events.117 These results show
46 that a diet higher in potassium and lower in sodium is associated with lower cardiovascular deaths. 117
Similar results were observed by Mente, et al. who looked at the association between urinary sodium and potassium excretion and blood pressure using 157,543 adults
35 to 70 years of age from 667 communities in 18 low-, middle-, and high-income countries on 5 continents. After adjusting for covariates, the team found a significant positive association between estimated sodium excretion and systolic blood pressure
(P<0.001) and between estimated sodium excretion and diastolic blood pressure
(P<0.001). 118 The positive sodium excretion and blood pressure was observed in all geographical regions. The team also found a significant inverse association between estimated potassium excretion and systolic blood after adjustment for covariates
(P<0.001). Furthermore, there was a strong and linear association between estimated sodium-to-potassium ratio and systolic blood pressure (P<0.001) and between the sodium-to-potassium ratio and diastolic blood pressure (P<0.001), after adjustment for covariates. 118 These results also point to the need to increase potassium intake and reduce sodium intake in diets in order to reduce blood pressure.
Greer, et al. conducted a study on the association of the neighborhood retail food environment with sodium and potassium intake among US adults. The study analyzed data from 8,779 participants in the 2005–2008 NHANES data using linear regression.119
The study also assessed the relationship between modified Retail Food Environment
Index (mRFEI) and sodium intake, potassium intake, and the sodium–potassium ratio.119
All the models were stratified by region (South and non-South) and included participant and neighborhood characteristics. Results showed that there was no association between
47 mRFEI and sodium intake. There was also no association between mRFEI and potassium intake and the sodium–potassium ratio varied by region. The researchers concluded that national strategies to reduce sodium in the food supply may be most effective to reduce sodium intake.119 Strategies aimed at the local level should consider regional context and neighborhood characteristics.
Nguyen et al. conducted a review of nutritional factors in hypertension management and concluded that a diet rich in fruits and vegetables, higher potassium level and lower sodium intake have the potential to reduce high blood pressure.120
According to Laragh potassium and sodium work together to maintain the correct amount osmotic balance inside cells. Boosting potassium intake increases sodium excretion and hence is likely to reduce blood pressure.121
Geleijnse, et al. in 1994 conducted a randomized double blind placebo controlled trial using a sample from the general population of a suburb of Rotterdam to investigate the impact of a reduction in blood pressure with a low sodium, high potassium, high magnesium salt in older subjects with mild to moderate hypertension.122 The sample consisted of 100 men and women between 55 and 75 years of age with untreated mild to moderate hypertension. During six months of the study the intervention group received a mineral salt (sodium: potassium: magnesium at 8:6: 1 ratio) and foods prepared with the mineral salt. The control group received common salt and foods. The findings of the study suggest that replacing sodium salt with a low sodium, high potassium, high magnesium mineral salt has the potential to offer an important non-pharmacological approach to lowering blood pressure in mild to moderate hypertension in older people.122
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Umesawa et al. conducted a collaborative cohort study for evaluating cancer risks among a sample of Japanese individuals. The study looked at the relation between dietary sodium and potassium intakes and mortality from cardiovascular disease. The study was conducted between 1988 and 1990 and involved a total of 58,730 Japanese subjects (n =
23,119 men and 35,611 women) aged 40-79 years with no history of stroke, coronary heart disease, or cancer. The results of this study suggest that a high sodium intake and a low potassium intake may increase the risk of mortality from cardiovascular disease.
123,124
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CHAPTER 3
METHODOLOGY
3.1 Study Design
This research used an existing National Health and Nutrition Examination Survey
(NHANES) data collected by the Centers for Disease Control (CDC); a cross - sectional sample of non-institutionalized U.S. populations. NHANES data is designed to access the health and nutritional status of adults and children in the United States. NHANES data collection started in the 1960s and contains information on health and nutrition on the sample reflecting changing nutritional and health trends among Americans. Each year the data collected consists of a nationally representative sample of about 5, 000 respondents selected from all the counties in the United States. The data contains demographic, examination, dietary, and laboratory information. The examination component consists of medical, dental, and physiological measurements. NHANES data collection is administered by highly trained medical personnel.125 In addition to containing measurements on blood pressure, the data also contains information on sex, race, education, sodium intake and more. NHANES dataset uses a stratified random sampling.
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3.1.2 Impact of Sodium on Hypertension Ages 20 and Above in the United States
NHANES 2005 -2014
Figure 8: Break down of the data used in the study:
Population aged 20 old and above in United States
i Sample size = 21,858
High Sodium Intake Low High Sodium Intake
Estimated exposure Hypertension No- Hypertension and Hypertension No- Hypertension Outcome
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3.1.3 Study Group/ Inclusion/ Exclusion Criteria
The research will analyze the NHANES data collected by the Centers for Disease
Control (CDC), from 2005-2014. The analysis will use Statistical Analysis Software
(SAS version 9.4). The NHANES data set contains respondents aged a few months to over 80. In order to be included in the study, participant must be adults from ages (in years) 20 and over. People that are less than 20 years were excluded from the study.
Participants using anti -hypertensive medications were also excluded from the study.
Recoding and truncation strategies were conducted to control outliers in the variables to keep the individual in the data set and at the same time minimize the harm to statistical inference. 126 Weighting was done to ensure that the means can be compared to the national population.
3.4 NHANES Data Set and Data Elements
The NHANES data files are accessible to the public and they contain the following data:
Demographic
Dietary
Dietary interview - Total Nutrient Intakes , Second day (DR2TOT)
Examination
Blood Pressure (BPX)
Body Measures (BMX)
Laboratory
HDL- Cholesterol (HDL)
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Cholesterol - Total (TCHOL)
Questionnaire
Blood Pressure and Cholesterol (BPQ)
Prescription medication (RXQ_RX)
The following variables will be selected from the data files for the study:
In the Demographic data file, the variables selected were:
Years at screening, (adults 20+ years)
Gender,
Race,
Education level 20 years and older
Adults 20 years and older
Annual household income.
In the Dietary data file: Dietary interview - individual foods second day data file was selected. Variable selected were: Cholesterol (mg), Sodium (mg), Potassium (mg).
In the Examination data file:
-Body Measure, Body Mass Index, Blood Pressure,
We used a variable name called SEQN to merge the files for the analysis.
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3.4.1 Data Cleaning and Data Processing Using SAS 9.4
The NHANES data, file XPT data was read into SAS then SAS dataset was created. The first step before any statistical analysis is to evaluate the distribution of the data .127 To clean the data simple frequencies were done using SAS software to make sure sample sizes matched those reported by NHANES analysis. For example, are the cumulative frequencies obtained using SAS similar to the NHANES reported frequencies? To accomplish this, the research used SAS procedure (PROC FREQ) to create simple frequencies. PROC FREQ procedure was also used to show the distribution of the categorical variables. Again, data were compared to make sure cumulative frequencies obtained using SAS were similar to the NHANES reported frequencies.
PROC MEANS, PROC SORT, PROC TABULATE, were used in the analysis.
The variables of interest were sorted and merged and more frequencies were done on the selected variables to make sure they were similar to reported frequencies. Some variables were coded into categorical variables (age, blood pressure, sodium consumption, education and income). Other variables such as ethnicity and gender were also recoded.
3.4.2 Checking for Outliers and Normality
Sampling weights for each survey respondent were used for the data analysis.
Sample weights was calculated to have good precision of the in the estimates of the subpopulations of the data, we included the interview / examination status variable and limited it to participants who were both interviewed and MEC examined. Only full sample 2 year MEC exam weight was used for the analysis. To calculate for the weight, 8 years of mobile examination center weight was divided by 2.
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3.4.3 Demographic Data
According to the CDC the demographic data was collected by trained interviewers who administered the interviews in either English or Spanish. The interviewers used computer assisted personal interview (CAPI) methodology. Printed questionnaires were used for questions that were unable to be answered using the CAPI methodology. The demographic data frequency counts were checked, sorted out and patterns were validated to ensure completeness, and consistency of the variables. Some demographic questions were asked exclusively of certain subgroups within.128
The Centers for Disease Control (CDC) provides a detailed explanation of the demographic data file. The file contains demographic information about the household reference person, such as education age, race/Hispanic, gender, military, marital status, origin service status, country of birth, citizenship, and years of U.S. residence and other selected demographic information 129
Table 3: Demographic Variables and Sample
SEQN Respondent sequence number RIAGENDER Gender RIDAGEYR Age at Screening RIDRETH1 Race/Ethnicity DMDEDUC2 Education Level- Adults 20+ INDHHINC Annual Household Income INDHHIN2 Annual Household Income WTINT2YR Full Sample 2 Year Interview Weight WTMEC2YR Full Sample 2 Year MEC Exam Weight SDMVPSU Masked Variance Pseudo- PSU SDMVSTRA Masked Variance Pseudo-Stratum
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3.4.4 Dietary Data
According to the CDC, the 24-hour dietary recall interview were conducted by trained Spanish and English data collectors on individuals ages zero to eighty years and above. These interviews were done in Mobile Examination Center (MEC) with standardized measures for all interviewees. The tools for the standardize measures are intended to be used as a measuring tool that helps interviewees to quantify the amount of food they consume.130 NHANES collect second dietary telephone recall in 3 to 10 days after the first recall.
Dietary Interview: Individual Foods first day. Under this data, NHANES has Cholesterol, sodium, and potassium
1. Dietary Interview: Individual Foods second day. Under this data, NHANES has
Cholesterol, sodium, and potassium
For the purpose of this study, dietary interview individual foods first day was used the first day because the Day 1 file includes information on salt use in cooking and at the table. All NHANES participant are eligible for two 24-hour dietary recall interviews. The first dietary recall interview is collected in-person in the Mobile Examination Center
(MEC) and the second interview is collected by telephone 3 to 10 days later. There were two Individual Foods files and two Total Nutrient Intakes files. Each file includes one day of intake data. The number “1” or “2” in the file name identifies the day (and mode) of the interview: 1 = first day (in-person), 2 = second day (phone).131
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Table 4: The variables obtained from the dietary data file
DR2TCHOL Cholesterol (mg)
DR2TSODI Sodium (mg)
DR2TPOTA Potassium (mg)
3.4.5 Dietary Interview: Total Nutrient Intakes First Day
According to CDC after the dietary interview data collection, four data files are derived from the collected data: two Individual Foods files and two Total Nutrient
Intakes files. Each file includes one day of intake data. The number “1” or “2” in the file name identifies the day (and mode) of the interview: 1 = first day (in-person), 2 = second day (phone). The amounts in these files reflect only nutrients obtained from foods, beverages, and water including tap and bottled water. They do not include nutrients obtained from dietary supplement intakes, antacids, or medications.131
3.5 Total Nutrient Intakes Files (DR1TOT and DR2TOT)
The NHANES code book states that the Total Nutrient Intakes file contains nutrient intakes from foods, daily total energy and beverages. It also documents whether the food intake was usual or not. Salt intake, weight loss, and sea food information are found in The Day 1 file. 131
Table 5: The variables obtained from the total nutrients data file
DR2TCHOL Cholesterol (mg) DR2TSODI Sodium (mg) DR2TPOTA Potassium (mg)
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3.5.1 Examination Data
From the examination data file, the following variables will be obtained:
Blood Pressures; systolic blood pressure 1st to 4th reading (average)
Diastolic blood pressure; 1st to 4th reading (average)
Body Mass Index which is measured in (kg/m**2)
Table 6: The variables obtained from the examination data file
PEASCST1 Blood Pressure Status BPXSY1 Systolic: Blood pres (1st rdg) mm Hg BPXDI1 Diastolic: Blood pres (1st rdg) mm Hg BPXSY2 Systolic: Blood pres (2nd rdg) mm Hg BPXDI2 Diastolic: Blood pres (2nd rdg) mm Hg BPXSY3 Systolic: Blood pres (3rd rdg) mm Hg
BPXDI3 Diastolic: Blood pres (3rd rdg) mm Hg
BPXSY4 Systolic: Blood pres (4rd rdg) mm Hg BPXDI4 Diastolic: Blood pres (4rd rdg) mm Hg BMXBMI Body Mass Index (kg/m**2)
3.5.2 Laboratory Data
NHANES laboratory data was collected at the medical examination center
(MEC). Eligibility for specific laboratory tests is based on the survey participants’ gender and age at the time of screening. The controlled environment of the MEC allowed laboratory measurements to be done under identical conditions at each survey location.
NHANES collects biological specimens (bio-specimens) for laboratory analysis to provide detailed information about participant's health and nutritional status.131 The bio-
58 specimens collected by NHANES for the laboratory data include: blood, Urine, oral rinse and vaginal swabs. In order to exhibit quality control monitoring measures for the laboratory test, quality assurance and quality control procedures were performed in the
MEC as well as contract laboratories. Also, all laboratory staff are trained professionals.
Cholesterol levels were classified according to the standards of the National Cholesterol education Program and the American Heart Association.132 Total cholesterol was classified as Desirable" <200mg/dL, "Borderline-high risk" 200-239 mg/ dL, and "Very high risk" >/240 mg/dL."
Table 7: The variable obtained from the laboratory data file
LBXTC Total cholesterol (mg/dL)
3.5.3 The variables to be used in the analysis will be recorded as follows
1. Blood Pressure Normal Pre-hypertension Stage 1 Hypertension Stage 2 Hypertension 2. Sodium <1500mg 1500-2400mg 2400-3399mg 3400mg
3. Body Mass Index Underweight Healthy Weight Overweight Obese 4. House hold income <20,000 <=20,000 -<=45,000
59
>45,000 - <=65000 65,000>
House Hold Income
if INDHHINC in (1, 2 , 3) then HHincome= 0 ;
if INDHHINC in (4, 5, 6, 12, 13 ) then HHincome= 1 ;
if INDHHINC in ( 7, 8, 9, 10 ) then HHincome= 2;
if INDHHINC in ( 11 ) then HHincome= 3 ;
if INDHHIN2 in (1, 2 , 3) then HHincome= 0 ;
if INDHHIN2 in (4, 5, 6, 12, 13 ) then HHincome= 1 ;
if INDHHIN2 in ( 7, 8, 9, 10 ) then HHincome= 2;
if INDHHIN2 in ( 11 ) then HHincome= 3 ;
5. Age Age was stratified by year group,
>=20 <=29 <=39 <=49 <=59 >60 data mergedata2; set mergedata2;
if ridageyr > =20 and ridageyr <= 29 then agegp = 0;
else if ridageyr <= 39then agegp = 1;
else if ridageyr <= 49 then agegp = 2;
else if ridageyr <= 59 then agegp = 3;
else if ridageyr >60 then agegp = 5; run;
6. Education
Less than high school High School Grad/GED College Graduate or more 60
Education collapsed into 4 and giving it a new name called educa4. By
doing that education 1 and 2 was collapsed to be zero. Which means
education level less than 9th grade and 9-11th grade =0 which is less than
high school.
High school graduate/ GED equivalent = 3 (=1);
Some college or AA degree=4 (2);
College graduates and above = 5 (=3);
if DMDEDUC2 in (1 2) then educa4=0;
if DMDEDUC2=3 then educa4=1;
if DMDEDUC2=4 then educa4=2;
if DMDEDUC2=5 then educa4=3;
7. Gender Sex 0='Male' 1='Female'; 8. Race Race 0= 'Mexican American' . 1='Other Hispanic' . 2='Non-Hispanic White' . 3='Non-Hispanic Black' . 4='Other Race - Including Multi-Racial'; 9. Weighting variables WTI2YR WTMEC2YR
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3.5.4 Study Variables and Covariates
Table 8: Classification of the variables used in the analysis
Variable Variable Name Label Level of Measurement Dependent Blood Pressure: bpxsy1 Categorical bpxsy2 bpxsy3 bpxsy4 bpxdi1 bpxdi2 bpxdi3 bpxdi4 Independent Sodium DR2TSODI Categorical Covariate Gender RIAGENDER Categorical Covariate Age RIDAGEYR Categorical Covariate BMI BMIBMI Categorical Covariate Race RIDRETH1 Categorical Covariate Education DMDEDUC2 Categorical Covariate Household Income INDHHINC Categorical INDHHIN2
3.5.5 Statistical Analysis and Data Cleaning
All analyses were done using SAS 9.4. Sample weight, masked variance pseudo -
PSU, and masked variance pseudo-stratum were applied to the recoding of the variables.
In the first part of the analysis, simple frequencies and cross tabulations were conducted using PROC FREQ on all variables in order to determine what variables have complete data and which ones have missing values. The frequencies helped to determine the sub- sample to be used. NOCUM (no cumulative statistics) was used in the PROC FREQ for the frequency output to show frequency count for each unique character values.
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NOCUL, NOROW and NOCUM statements were used on the tables to customize the table for the purpose of the analysis to obtain the desired results. Less than p<0.05 significant level were set for the entire statistical test.
To conduct the analysis, several of the variables were re-coded. The dependent variable-blood pressure- has two measurements; systolic and diastolic blood pressure measured in mmHg. The data set contains four separate readings on both systolic and diastolic blood pressure. To recode this variable, the first step was to get an average of all these values using the “proc. means” procedure in SAS. The next step was to recode the new variable into a binary variable containing values of 0 and 1. For the purpose of this study, those who had an average blood pressure reading of 140 or more or had a diastolic blood pressure of 90 or more were considered hypertensive and were coded as “1.” All others were considered normal and coded as “0.”
The sodium variable used in this study was the total 24- hour sodium intake recall reported by the respondent. This variable was re-coded into four categories: less than
1500 mg/day = 1, between 1500 and 2399 mg/day=2, between 2400 and 3399 mg/day =3 and 3400 mg/day or more=4. Everyone under the age of twenty was excluded from the study. The age variable was coded into five age categories: greater or equal to 20 and less or equal to 29 =0, less or equal 39 = 1, less or equal to 49 = 2, less or equal to 59 = 3, and
60 greater = 4.
The following is an example of how the variables were re-coded. In this example the age variable is recoded into a variable called "agegp."
63
Data mergedata2; set mergedata2;
if ridageyr > =20 and ridageyr <= 29 then agegp = 0;
else if ridageyr <= 39then agegp = 1;
else if ridageyr <= 49 then agegp = 2;
else if ridageyr <= 59 then agegp = 3;
else if ridageyr >60 then agegp = 4; run; proc format; value agegp 0='20<=age<=29' 1='29 tables Age; title 'Table of Age Group in Years'; run; The race variable was coded into five race categories: Mexican American =1, Hispanic = 2, Non- Hispanic = 3, non- Hispanic Black =4 and White =5. The body mass index (BMI) variable was coded into four categories; less than18 = 1 (underweight), less or equal to 24.9 = 2 (Healthy weight), less or equal to 29.9 =3 (Overweight) and greater than 30 = 4 (Obese) and sex was coded as “1” for male and “0” for female. Potassium was coded less or equal to 1771 =0, between 1772 and 2529 =1, between 2530 and 3450 =2 and more or equal to 3450=3. Cholesterol values were categorized using American heart association guidelines; "desirable", "borderline-high risk", and "very high risk". We recoded cholesterol levels as less or equal 200= 0 " desirable", less or equal 240= 1, "borderline-high risk" and greater than 240= 2, very high risk". The income variable had four categories: (1,2,3) = 0, (4,5,6,12, 13) = 1, (7, 8, 9, 10) =2, and (11) =3. 64 Sampling weights were used in the data analysis to take into account the complex sample design and non-respondent to MEC examination. Distribution of the study 3.6 Descriptive statistics Descriptive statistics that were used to summarize the demographic data include means, standard deviations, percentages and frequency counts. Percentage and frequencies tables were used to describe the categorical and ordinal variables. We recoded the variables to account for outliers. The PROC frequencies showed missing cases and outliers. In this study, missing cases and outliers were dropped. Proc means were used to calculate the mean values, determine the mean number of missing values, identify outliers and compare estimates with and without outliers. Sample weight was applied to the recoding of the variables therefore the means calculated for this multi-stage probabilistic sample is weighted arithmetic mean. The following syntax and formula were used to calculate the means. This means in this formula, x represents the value, w represents the weights, Σ represents the sum . 65 3.6.1 Means and Standard Deviations for Continues Variables SAS syntax for Arithmetic means: proc means data= mergedata1; VAR riagendr ridreth1 ridageyr indhhin2 indhhinc bpxsy1 bpxdi1 bpxsy2 bpxdi2 bpxsy3 bpxdi3 bpxsy4 bpxdi4 bmxbmi dmdeduc2; TITLE 'PROC MEANS'; Table 9 provides the mean of the variables used in the study. The PROC MEANS produce statistical summary report for all the variables. The table also shows that some of the variables had large standard deviations. Further examinations of the variables were done using PROC frequencies. Where: N= number of respondents Std Dev = Standard Deviation Table 9 Measures of Association between selected Variables NHANES 2005-2012 66 3.7 Inferential statistics Inferential statistics that were used in the study were chi-square and regression analysis. Chi square test of association was used to test for the presence of the systematic relationship between the dependent variables (blood pressure) and the independent variables (subgroups). There after the significant variables from the chi square test were the only factors included for the ordinal regression. The logistic regression and Cramer's V statistic were further used to identify if sodium is determinant of hypertension. Further the Cochran-Armitage Trend test was used to examine the prevalence trend of hypertension, sodium, education, sex, race, income BMI and age categories. Dependent Variable. Blood pressure was the dependent variable in the study. Blood pressure was converted to a categorical variable before performing inferential statistical analysis based on the Eighth Joint National Committee (JNC8) blood pressure recommendation. Blood pressure variable was coded Normal (120/8090 mmHg), pre- hypertension (between 120 mmHg and 139/89 mmHg), stage 1 hypertension readings of greater than 140/90 mmHg and stage 2 hypertension readings of greater than 150/90 mmHg or higher. The blood variable further coded as normal (Systolic BP <120 AND Diastolic BP <80), pre-hypertension (Systolic BP= 120–139 OR Diastolic BP= 80-89), stage 1 hypertension (Systolic BP= 140–159 OR Diastolic BP= 90-99) and stage 2 hypertension (Systolic BP= 160 or higher OR Diastolic BP= 100 or higher). The 89) and no hypertension (Systolic BP< 139 OR Diastolic BP < 89).71,133 The analysis of isolated systolic hypertension was also analyzed. The systolic pressure was coded as more than 140mmHg and the diastolic was less than 90mmHg.134 67 Independent Variable. The primary independent variable of interest used in the study was sodium. Prior to performing inferential statistical analysis the independent variable sodium was re-coded into a categorical variable. Logistics was performed to identify the determinate of determine if there were any collinearity between the independent variables. Covariates. Household income, education, age, race, gender, age and BMI were the covariates used in the analysis of this research. Logistics was performed to identify the determinate of the covariates with the effects of sodium on hypertension. Next, the population at risk was examined by stratifying education level and sodium consumption. Education by high blood pressure was examined by using 2X2 tables. Continuous variables were expressed by calculating their standard deviations and means. The prevalence of age and high blood pressure conditions in the population were compared and tested by using 2x2 tables. Chi-square test of significance for the relationship at 5% level of significance was conducted to detect the relationship between body mass index and high blood pressure. Next, the relationship between income and high blood pressure was examined by using 2X2 cross tabulations of income and blood pressure. 3.8 Logistic regression Logistic regression can be extended to incorporate more than one explanatory variable. For selected categorical variables multivariate logistic regression analysis with hypertension as the outcome variable were performed and the corresponding odds ratio and their 95% confidence intervals were calculated. We used simple logistic regression 68 to access the association between dichotomous blood pressure (Y) and sodium (X j). Multiple logistic regression was used to explore the associations between dichotomous blood pressure and race, education, income, age sex, and BMI. The purpose of the multiple regression was to isolate the relationship between sodium and blood pressure from the effects of race, education, age, sex, annual household income using 95% confidence interval. Logistic regression was used to further quantify the values of the strength of association by adjusting for other independent variables. Ordinal logistic regression models were used to access the impact of variables that were significantly associated (p<0.05) with both sodium intake and hypertension. The logistic model can be written as follows: The above formula, Pr(Y=1) means the probability that the event occurs and the 'log' in this equation indicates natural log. The following is the syntax for logit regression. The following is the SAS syntax used for logistic regression: **logistic regression**; proc logistic data=mergedata2; class Sodium; model blood pressure=BMI race sex income; label BMI = 'Body Mass Index'; title "Regression of sodium intake from hypertension' Pressure"; format BMI BMI. RACE RACE. SEX SEX. SODIUM SODIUM. Income HHincome. run; 69 A multivariate regression tests was used to estimate the association between sodium and hypertension adjusting for potential confounding factors: age, gender, BMI, race, education, and annual household income. SAS 9.4 Stepwise Regression procedure was performed by adding and removing independent variables that are not significant. This is the variables are added one by one and those that were not significant were removed from the regression model. 3.9 Cochran - Armitage Trend Test Using SAS Cochran - Armitage Trend test was used to measure the growth of blood pressure in the different subpopulations over the years. It also used to check for the propositions and statistical significance of the various levels within the subgroups. According to Nam135 this test is more powerful than the chi-square test of homogeneity when it comes to identifying trends. For this analysis the blood pressure was coded hypertension (Systolic BP> 139 OR Diastolic BP > 89) and no hypertension (Systolic BP< 139 OR Diastolic BP < 89). 70 CHAPTER 4 RESULTS 4.1 Introduction This chapter presents the findings, analysis and interpretation of the NHANES dataset from 2005 to 2014 with the aim of finding the relationship between high sodium intake and hypertension. The analysis presented below is the results of study sample from NHANES dataset from 2005-2014 from ages 20 years and above. Table 10 (pages 72-73) shows the demographic characteristics of the study sample. The sample consisted of 21,858 participants after adjusting for missing values and factoring in the survey weights. Most of the participants fell within ages 50 and above which was 47.20% of the entire population. Female participants were 51.54% whiles male participant were 48.46%. Non- Hispanic Whites and Non- Hispanic Black were the highest proportion of participants they constituted 67.19% of the population. Other Hispanics and Other Race - Including Multi-Racial were the lowest proportion of participants. Other Hispanics and Other Race - Including Multi-Racial were less when combined than the Non -Hispanic white. Majority of the participants had some college or AA degree followed by those with less than high school. There was nearly the same percentage of participants with college graduate and those with GED. 40% of the individuals had income between $20,000 to $45,000. Many of the participants were obsessed. And 31% of the sample consumed more than 3400 mg of sodium per day. 71 Table 10: Weighted Demographics Characteristics persons 20years and older (n=21858), NHANES Dataset 2005-2014 VARIABLE FREQUENCY PERCENTAGE Age 20 – 29 3864 18.06% 30 - 39 3730 17.43% 40 - 49 3704 17.31% 50 - 59 3335 15.58% 60 and older 6766 31.62% Total 21399 Gender: Male 10630 48.63% Female 11228 51.37% Total 21858 Race/Ethnicity: Mexican American 3563 16.30% Other Hispanics 1940 8.88% Non- Hispanic White 9913 45.35% Non- Hispanic Black 4774 21.84% Other Race - Including Multi- 1668 7.63% Racial Total 21858 Educational Level: Less than high school 6089 27.90% High school graduate/ GED 5056 23.16% Some college or AA degree 6117 28.02% College graduate+ 4565 20.91% Income: income < 20,000 3026 17.71% 20,000 <= income <45,000 6983 40.86% 45,000<=income < 65,000 6028 35.27% income >=6500 1052 6.16% Total BMI BMI<18 233 1.09% 18 <=BMI<=24.9 6097 28.51% 25<=BMI<=29.9 7243 33.87% BMI >29.9 7811 36.53% Total 21384 Sodium <=1500 mg sodium daily 5811 26.59% 1500 mg < sodium <=2399 mg 4209 19.26% daily 72 2399 mg < sodium <= 3400 mg 4870 22.28% daily sodium> 3400 mg daily 6968 31.88% Total 21858 Table 11: Collinearity Check for Continues Variables Income as the dependent variable Variance Inflation OBS Variable (VIF) 1 Intercept 0 2 Sodium 1.05624 3 Race 1.07584 4 BMI 1.01595 5 Sex 1.02985 6 Education 1.10732 7 Age 1.14392 8 Blood pressure 1.13699 Sodium as the dependent variable Variance Inflation OBS Variable (VIF) 1 Intercept 0 2 Race 1.07799 3 BMI 1.01427 4 Sex 1.00817 5 Education 1.18231 6 Blood pressure 1.13643 7 Age 1.14269 8 Income 1.10417 73 BMI as the dependent variable Variance Inflation OBS Variable (VIF) 1 Intercept 0 2 Sex 1.02974 3 Education 1.20020 4 Blood pressure 1.13715 5 Age 1.14183 6 Income 1.10617 7 Sodium 1.05641 8 Race 1.07336 Sex as the dependent variable Variance Inflation OBS Variable (VIF) 1 Intercept 0 2 Education 1.19619 3 Blood pressure 1.13709 4 Age 1.14479 5 Income 1.10309 6 Sodium 1.03300 7 Race 1.07817 8 BMI 1.01301 Education as the dependent variable Variance Inflation OBS Variable (VIF) 1 Intercept 0 2 Blood pressure 1.13594 3 Age 1.13949 4 Income 1.01910 5 Sodium 1.04089 6 Race 1.01339 7 BMI 1.01449 8 Sex 1.02780 74 Age as the dependent variable Variance Inflation OBS Variable (VIF) 1 Intercept 0 2 Income 1.10490 3 Sodium 1.05580 4 Race 1.07524 5 BMI 1.01292 6 Sex 1.03232 7 Education 1.19590 8 Blood pressure 1.02231 Race as the dependent variable Variance Inflation OBS Variable (VIF) 1 Intercept 0 2 Income 1.10385 3 Sodium 1.05804 4 BMI 1.01147 5 Sex 1.03279 6 Education 1.12978 7 Age 1.14219 8 Blood pressure 1.13372 Blood pressure as the dependent variable Variance Inflation OBS Variable (VIF) 1 Intercept 0 2 Income 1.10514 3 Sodium 1.05664 4 Race 1.07400 5 BMI 1.01513 6 Sex 1.03185 7 Education 1.19970 8 Race 1.02876 75 Table 11 (pages 73-75) above shows the results of multicollinearity of continues variables. Linear regression analysis was done using variance inflation factors (VIF) to check the multicollinearity. The parameter estimate for the VIF was less than 10. If VIF it is greater than 10 then there is a presence of multicollinearity in the data. In this model, is not close to 10 indicating that the problem of multicollinearity is not present. The results above show that there is no presence of multicollinearity. The results show that the independent variables are not correlated to each other. 4.2 Distribution of Blood Pressure by Sex Of the total sample, 10,630 were male representing 48.63 % of the total sample. Approximately 19.58% had normal hypertension, 19.61% were pre-hypertensive, 7.14% were stage 1 hypertensive and 2.30% were stage 2 hypertensive. The total number of females was 11228, representing 51.37% of the study participants 27.76% were normal hypertension, 14.86% were pre-hypertensive and 5.93% were stage 1 hypertensive 2.81% stage 2 hypertensive. This results show that even though there is a high number of males with normal blood pressure, pre-hypertensive levels is high in males. Research shows that people who are pre-hypertensive turn to be diagnosed with hypertension. 76 Figure 9: Distribution of blood pressure by Gender/sex NHANES 2005-2012 4.2.1 Distribution of sodium Consumption by Sex NHANES 2005-2012 Out of the 2,671 participants who consumed <1500mg of sodium daily, 12.22% were male. Of those who consumed (1461) daily sodium 1500mg < sodium <=2399mg, 6.68% were male. 9.60% of the males (2099) consumed 2399mg 20.13% of the male participants consumed more than 3400mg daily. This results confirms the fact that more Americans consume more than the recommended daily sodium intake. 77 Out of the 3,140 participants who consumed <1500mg of sodium daily, 14.37% were female. Of the 2,748 who consumed daily sodium 1500mg < sodium <=2399mg, 12.57% were female. Out of the 2,771 females who consumed 2,399mg <=3400mg sodium daily, 12.68 % were female. 11.75% of the female participants (2569) consumed more than 3400mg daily. This results confirm the fact that more Americans consume more than the recommended daily sodium intake. Figure 10: Distribution of Sodium Consumption by Sex NHANES 2005-2012 78 R1 - Is sodium a significant determinant of hypertension? H1- Sodium has a significant determinant on hypertension 4.3 Sodium and High Blood Pressure Table 12 below shows the relationship between sodium consumption and high blood pressure for the period 2005-2012. The results show that well over a half (55%) of the respondents who were either pre-hypertensive or had hypertension in 2005/2006 sample consumed more than 2400 mg of sodium per day. The percentage drops somewhat in the 2007/08 sample but increases to 56% in the 2009/2010 period and to 57% in the 2011/2012 period. The chi-square test on the relationship between sodium and blood pressure for each of the years is significant at 1% level of significance and the likelihood chi-square ratio is also significant at 1%. These results indicate that there exists a strong correlation between sodium consumption and blood pressure. Those who consume high amounts of salt are at risk of developing high blood pressure. Further investigation will be done to confirm that this relationship. 79 Table 12: Cross tabulations of Sodium Consumption and Hypertension using NHANES data 2005-2012 Year: 2005 -2012 05/06 07/08 09/010 011/012 Sodium Normal Pre- Hypertensi Normal Pre- Hypertens Normal Pre- Hypertensio Normal Pre- Hypertension hypertensio on hypertensi ion hypertension n hypertension n on <1500mg n=476 n=356 n=231 n=638 n=541 n=351 n=603 n=476 n=297 n=551 N=442 n=255 (10.54%) (7.88%) (5.12%) (11.75%) (9.97%) (6.47%) (10.52%) (8.24%) (5.14%) (10.86%) (8.71%) (5.05%) 1500- n=389 n=313 n=203 n=471 n=368 n=269 n=514 n=369 n=211 n=422 n=331 n=193 2400mg (8.61%) (6.93%) (4.50%) (8.68%) (6.78%) (4.95%) (8.89%) (6.39%) (3.65%) (8.32%) (6.52%) (3.80%) 2400- n=478 n=371 n=208 n=502 n=440 n=248 n=356 n=461 n=240 n=477 n=446 n=219 3399mg (10.58%) (8.22%) (4.61%) (9.25%) (8.10%) (4.57%) (10.99%) (7.98%) (4.15%) (9.40%) (8.79%) (4.32%) 3400+mg n=723 n=536 n=232 n=700 n=645 n=256 n=923 n=748 n=297 n=779 n=693 n=265 (16.01%) (11.87%) (5.14%) (12.89%) (11.88%) (4.72%) (15.97%) (12.94%) (5.14%) 15.36%) (13.66%) (5.22%) Total n=2066 n=1576 n=871 n=2311 n=1994 n=1124 n=2680 n=2054 n=1045 n=2229 n=1912 n=932 (45.75%) (34.90%) (19.35%) (42.57%) (36.73%) (20.70%) (46.37%) (35.54%) (18.08%) (43.94%) (37.69%) (18.37%) 80 Figure 11: Sodium Intake and Hypertension NHANES 2005-2012 Figure 11 Sodium intake and Hypertension NHANES 2005-2012 40 35 30 25 20 Sodium Intake 15 Frequency in % in Frequency Hypertension 10 5 0 0 1 2 3 4 5 Years Note: year1=2005-2006, year 2= 2007-2008, year 3 = 2009-2010 and year 4= 2011-2012 Figure 11 presents the trend of consumption of the highest level of sodium (>3400 g of salt daily) and the trend of hypertension cases using the NHANES data for the 2005 to 2012 period. The percentage of people who consumed the highest level of sodium decreased from over 30 percent in 2005-2006 period to less than 30 percent during the 2007-2008 data collection period. The percentage increased during the 2008- 2009 data collection period and remained steady during the two next data collection periods covering 2009-2012. On the other hand, hypertension cases increased from around 18 percent during the 2005-2006 period to slightly over 20 percent during the 2007-08 data collection period. This increase is much less than the increase in consumption of the highest level of sodium. The percentage of hypertension cases decreased to less than 17 percent during the 2009-2010 periods and has remained steady. 81 It can be concluded that even though the percentages of those who consume high amounts of sodium has remained high, the number of cases of hypertension have not matched these high sodium consumption percentages. When the two highest levels of daily sodium consumption (>2399 g of salt daily) and the hypertension and pre-hypertension cases are combined, the result is shown in Figure 12; The figure shows that there was a sharp decline of both the hypertension and pre-hypertension cases between 2005-2006 and 2007-2008 data collection periods. Since hypertension cases did not have a dramatic decrease during this period (Figure 11), it can be assumed that this increase was due to the increase in the number of pre-hypertension cases during this period. This was followed by an increase in the percentage of cases during the 2009-2010 period. These results are in line with other studies that report that around one third of the adult US population is either hypertensive or pre-hypertensive. It should be noted that these two graphs only show the correlation between sodium consumption increase and the increase in hypertension/pre-hypertension cases. This relationship was further investigated using ordinal logistic regression analysis and the results showed that sodium was a predictor of blood pressure. The error line for the variability check was 5%. 82 Figure 12: Sodium intake and hypertension (pre and hypertension cases) NHANES 2005-2012 Pre-hypertension & Hypertension % Sodium % 62 60 58 56 54 52 50 48 46 44 2005-2006 2007-2008 2009-2010 2011-2012 Year Pre-hypertension & Hypertension % Sodium % 2005-2006 54.25 55.00 2007-2008 57.43 50.45 2009-2010 53.06 56.14 2011-2012 56.06 55.45 83 Figure 13: The effect of sodium on hypertension NHANES 2005-2012 Blood pressure levels by sodium 60 50 40 30 20 % of Bloodof Pressure % 10 0 Pre - Stage 1 Stage 2 Normal Hypertension Hypertension Hypertension BLOOD PRESSURE <1500 49.25 31.23 13.25 6.26 1500-2399 46.38 32.81 14.64 6.18 2399-3400 45.93 35.28 13.72 5.07 >3400 47.3 37.63 11.54 3.53 Figures 12 (page 83) and 13 compares the trend of the highest levels of sodium consumption (2399m g) to the trends of pre and hypertension (>120/80) for the 2005- 2012 NHANES data. Pre-hypertension and hypertension cases decreased dramatically between the 2005 -2006 data collection cycle and 2007- 2008 data collection cycle while the number of people who consumed the highest levels of sodium increased dramatically during the same period. Between 2008 - 2009 to 2011 - 2012, pre-hypertension and hypertension cases increased while sodium consumption decreased to about similar percentages. This trend suggests that sodium consumption did not affect the number pre- hypertension and hypertension cases during the 8 -year period. 84 R2- Is there a significant relationship between sodium and hypertension in all ethnic groups studied? H2- There a significant relationship between sodium and hypertension in all ethnic groups studied Figure 14 shows the impact of sodium on hypertension while controlling for race. The number of hypertension cases is highest among non-Hispanic Blacks. The "Other Hispanic” category has the lowest percentage of people with hypertension. It should be noted that in every sodium consumption level, non-Hispanic Blacks have the highest number of hypertension cases compared to all other race categories. Figure 14: Effects of Sodium by Blood Pressure Controlling for Race NHANES 2005-2012 70 60 50 40 30 20 Normal % of Bloodof Pressure % 10 Pre- Hypertension 0 Hypertension 2399 3400 2399 3400 3400 2399 2399 3400 2399 3400 ------ <1500 <1500 >3400 <1500 >3400 <1500 >3400 >3400 <1500 >3400 1500 2399 1500 2399 2399 1500 1500 2399 1500 2399 Mexican Other Non- Non- Other American Hispanic Hispanic Hispanic Race White Black Sodium Consumption by Race 85 Table 13 Results of Chi-Square test for the association between Race, Sodium Intake and Hypertension NHANES 2005-2012 RACE Pre - Stage 1 Stage 2 Normal Hypertension Hypertension Hypertension P-Value RACE Sodium % % % % Mexican American <1500 51.45 31.64 10.96 5.96 0.0004 1500-2399 27.33 56.02 11.64 5.01 0.0004 2399-3400 34.18 5220 8.37 5.25 0.0004 >3400 53.68 34.15 9.82 2.35 0.0004 Other Hispanic <1500 51.09 30.28 12.89 5.75 0.0506 1500-2399 32.41 50.25 11.56 5.78 0.0506 2399-3400 36.48 49.23 9.44 4.85 0.0506 >3400 34.39 54.35 8.5 2.77 0.0506 Non- Hispanic White <1500 50.78 31.29 12.63 5.29 <.0001 1500-2399 33.49 44.46 15.83 6.22 <.0001 2399-3400 35.99 44.96 14.24 4.81 <.0001 >3400 45.44 39.33 11.95 3.28 <.0001 Non- Hispanic Black <1500 42.77 31.80 16.56 8.87 <.0001 1500-2399 36.9 37.34 17.64 8.12 <.0001 2399-3400 34.35 40.14 19.14 6.38 <.0001 >3400 41.14 39.93 13.36 5.57 <.0001 Other Race <1500 53.71 29.84 12.12 4.34 0.3848 1500-2399 29.06 60.68 7.69 2.56 0.3848 2399-3400 33.66 54.46 9.24 2.64 0.3848 >3400 56.57 30.45 10.21 2.77 0.3848 86 Table 13 shows the relationship between sodium and hypertension, while controlling for race/ethnic groups. The chi square test for independence with an alpha set at 0.05 is significant at p=0.0004 for Mexican Americas, p= 0.0506 for other Hispanics, <.0001 for Non- Hispanic whites, p=<.0001 for Non - Hispanics Blacks and p=0.3848 for other race. This support the hypothesis that race affects the relationship between sodium and hypertension. The table indicates that 46% of Non- Hispanic blacks consume more than 2399 mg of sodium and they are hypertensive and 25.43% of that same group who consume less than 1500 mg of sodium is also hypertensive. Also, 34.28% of Non- Hispanic whites who consume more than 2399 mg of sodium are hypertensive. And the race that NHANES considers to be “other race" has the low rate of hypertension. The logit regression results are confirmed by a logit model which shows that the odds ratios of getting hypertension based on race and sodium intake. For sodium, estimate (0.1442) = 1.155 (odds ratio estimates). Table 14: Regression of Sodium and Race from Blood Pressure The LOGISTIC Procedure Model Information Data Set WORK.MERGEDATA2 Response Variable Blood Pressure Number of Response Levels 2 Model binary logit Optimization Technique Fisher's scoring Number of Observations Read 21858 Number of Observations Used 20762 Response Profile 87 Ordered Blood Pressure Total Value Frequency 1 Normal and pre-hypertension (<=120 mmHg) 16787 2 Hypertension (=>140 mmHg) 3975 Probability modeled is Blood pressure ='Normal and pre-hypertension (<=120 mmHg) Class Level Information Class Value Design Variables race Mexican American 1 0 0 0 Non-Hispanic Black 0 1 0 0 Non-Hispanic White 0 0 1 0 Other Hispanic 0 0 0 1 Other Race - Including Multi-Racial -1 -1 -1 -1 Model Convergence Status Convergence criterion (GCONV=1E-8) satisfied. Model Fit Statistics Criterion Intercept Only Intercept and Covariates AIC 20279.276 20039.743 SC 20287.217 20087.388 -2 Log L 20277.276 20027.743 Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 249.5331 5 <.0001 Score 252.9051 5 <.0001 Wald 248.8524 5 <.0001 Type 3 Analysis of Effects Effect DF Wald Pr > ChiSq Chi-Square 88 Type 3 Analysis of Effects Effect DF Wald Pr > ChiSq Chi-Square sodium 1 90.6959 <.0001 race 4 162.4881 <.0001 Analysis of Maximum Likelihood Estimates Parameter DF Estimate Standard Wald Pr > ChiSq Error Chi-Square Intercept 1 1.1667 0.0434 722.2998 <.0001 sodium 1 0.1442 0.0151 90.6959 <.0001 race Mexican American 1 0.1805 0.0433 17.3472 <.0001 race Non-Hispanic Black 1 -0.4350 0.0353 151.7070 <.0001 race Non-Hispanic White 1 -0.1005 0.0310 10.5226 0.0012 race Other Hispanic 1 0.1218 0.0541 5.0761 0.0243 Odds Ratio Estimates Effect Point 95% Wald Estimate Confidence Limits Sodium 1.155 1.121 1.190 race Mexican American vs Other Race - Including 0.949 0.801 1.123 Multi-Racial race Non-Hispanic Black vs Other Race - 0.513 0.438 0.600 Including Multi-Racial race Non-Hispanic White vs Other Race - 0.716 0.616 0.833 Including Multi-Racial race Other Hispanic vs Other Race - Including 0.895 0.741 1.079 Multi-Racial Association of Predicted Probabilities and Observed Responses Percent Concordant 53.0 Somers' D 0.159 Percent Discordant 37.1 Gamma 0.176 89 Association of Predicted Probabilities and Observed Responses Percent Tied 9.9 Tau-a 0.049 Pairs 66728325 c 0.579 R3- Is there a significant relationship between sodium and hypertension in all education groups studied? H3- There is a significant relationship between sodium and hypertension in all education groups studied 4.4 Education and Sodium Table 15 shows a cross tabulation of sodium consumption by education. Of the 21827 participants in the education variable, 7.98% consumed more than 3400mg of sodium and are highly educated. Table 16 shows cross tabulation between education and hypertension. Those who had at least some college education and had hypertension (>140/90) represented almost 8% of the sample. Cross tabulations of the relationship between education and sodium among all the respondents in the 2005-2012 survey are presented in table 17. Of those who had at least some college 29.62% consumed more than 2400 mg of salt. The chi-square test for this relationship was significant at 1% level of significance. This clearly indicates a strong correlation between education and sodium consumption. An argument may be advanced that those who have high education consume more sodium and are likely to have high blood pressure. This result goes against the expected outcome which suggests that those with more education should consume less sodium. The rationale behind this argument is that those with high education will 90 have more knowledge of the negative impact of sodium and consume less of it as a consequence. The results should not be interpreted to mean that education causes high blood pressure. It may mean, however, that more educated people are more likely to work in stressful jobs and tend to eating on the go more leading to consumption of more processed foods which contain higher levels of sodium. Further, those with higher education are most likely employed and “too busy” to prepare home cooked meals and tend to consume more frozen and processed foods and tend to eat out more. Eating out is a function of income and those with higher education have the disposable income necessary to eat out more. While this finding is significant, it should be interpreted with caution. The significance of the relationship between the two variables may be due to the large sample size. It is important to note here that these are preliminary results. Further analysis of the data will tease out any anomalies that may exist in the data before definitive conclusions can be made regarding this inference. Nevertheless, the results are intriguing enough to lead one to question the existing understanding. Table 15: Cross tabulations of Education and Sodium Consumption NHANES data 2005- 2012 Education by Sodium Intake Sodium Intake Education <1500 1500-2399 2400-3400 >3400 Less than High School n=2179 n=1270 n=1179 n=1461 (9.98%) (5.82%) (5.4%) (6.69%) High school graduate n=1360 n=969 n=1147 n=1580 (6.23%) (4.44%) (5.25%) (7.24%) Some college /AA degree n=1390 n=1173 n=1372 n=2182 (6.37%) (5.37%) (6.29%) (10%) College graduate+ n=868 n=789 n=1167 n=1741 (3.98%) (3.61%) (5.35%) (7.98%) 91 Table 16: Education by Blood Pressure NHANES 2005-2012 BLOOD PRESSURE Stage 1 Stage 2 Pre - Hypertension % Education Normal % Hypertension % Hypertension % n=447 Less than High School n=2611 n=2104 n=927 (2.05%) (11.96%) (9.64%) (4.25%) n=301 High school graduate n=1998 n=1816 n=690 (10.30%) 8.32% (3.16%) (1.38%) n=229 Some college /AA degree n=2713 n=2126 n=769 (13.71%) (9.74%) (3.52%) (1.05%) n=137 College graduate+ n=2289 n=1481 n=468 (11.36%) (6.74%) (2.14%) (0.63%) While this finding is significant, it should be interpreted with caution. The significance of the relationship between the two variables may be due to the large sample size. It is important to note here that these are preliminary results. Further analysis of the data will tease out any anomalies that may exist in the data before definitive conclusions can be made regarding this inference. Nevertheless, the results are intriguing enough to lead one to question the existing understanding. 92 Table 17: The Effects of Education and Sodium on Hypertension 2005-2012 BLOOD PRESSURE Pre - Stage 1 Stage 2 Normal Hypertension Hypertension Hypertension Education Sodium % % % % p Less than High 8.21 31.67 School <1500 44.47 15.65 <.0001 1500-2399 42.52 32.99 16.22 8.27 2399-3400 40.12 36.90 15.95 7.04 >3400 43.05 38.33 13.14 5.48 High school 6.40 32.13 graduate <1500 49.26 12.21 <.0001 1500-2399 42.62 33.64 16.41 7.33 2399-3400 41.15 36.79 14.47 7.59 >3400 43.92 39.94 12.59 3.54 Some college 4.32 30.86 /AA degree <1500 52.52 12.30 0.0003 1500-2399 48.42 32.74 13.73 5.12 2399-3400 47.96 36.08 12.76 3.21 >3400 47.53 37.49 12.01 2.98 College 4.26 29.38 graduate+ <1500 55.88 10.48 0.0064 1500-2399 54.12 31.56 11.28 3.04 2399-3400 54.16 31.19 11.91 2.74 >3400 53.70 35.21 8.56 2.53 93 Figure 15: Sodium Consumption, Education by Blood Pressure Figure 15: Sodium Consumption, Educaion by Blood Pressure 60 50 40 30 20 Normal % % ofPressureBlood % 10 Pre - Hypertension % 0 Hypertension % 2399 3400 2399 3400 2399 3400 2399 3400 ------ <1500 >3400 <1500 >3400 <1500 >3400 <1500 >3400 1500 2399 1500 2399 1500 2399 1500 2399 Less than High High school Some college College School graduate /AA degree graduate+ Sodium by Education Table 16 and figure 15 shows that the chi square test (X2) for the relationship between sodium and hypertension, controlling for education, is significant (p<0.0001, 0.0001, 0.0003, 0.0064) indicating that education has an impact on the relationship between sodium consumption and hypertension. A closer look at the tables shows that in general, those with higher education consume more sodium than those with less education. However, the more educated have less hypertension cases than those with low education. This is an interesting finding because the assumption is that higher sodium consumption should lead to more hypertension. The question arising from this finding is, why do those who are more educated have less hypertension and yet they consume more sodium? Could 94 this be related to the fact that the more educated are more conscious and practice health preventive measures that cancel out the impact of sodium? Or is there another explanation for this outcome? R4- Is there a significant relationship between sodium consumption and hypertension in all income groups studied? H4- There is a significant relationship between sodium consumption and hypertension in all income groups studied 4.4.1 Income and Blood Pressure Table 18 presents cross tabulations of income by blood pressure. The relationship between income and blood pressure was significant at 5% level of significance. The table shows that 7.22% of those with income of over $45,000 a year have high blood pressure. Also, 12.89% of those with income of less than $45,000 a year have high blood pressure. This result corresponds with the findings of the impact of education and income. Education is a proxy for income and thus would be expected to have the same impact on high blood pressure as income. It is important to note that as with education, income is positively correlated with blood pressure, contrary to the expected outcome. Table 18: House Hold Income by Blood Pressure Year 2005-2012 Blood Pressure House Normal Pre-hypertension Stage 1 Stage 2 Hold Income $ Hypertension Hypertension <19,999 n=1324 n=1001 n=444 n=257 (7.22%) (5.86%) (2.60%) (1.50%) 20,000 - 44,999 n=3230 n=2357 n=991 n=405 (18.90%) (13.79%) (5.80%) (2.37%) 45,000 - 64,999 n=2588 n=2149 n=778 n=264 (16.60%) (12.58%) (4.55%) (1.54%) >6500 n= 522 n=398 n=101 n=31 (3.05%) (2.33%) (0.59%) (0.18%) 95 Figure 16: Subgroup Analysis of Sodium Intake, Blood Pressure by Household Income NHANES 2005-2012 Figure 16: Subgroup Analysis of Sodium intake, Blood Pressure by Household Income NHANES 2005-2012 20 15 10 Normal % 5 Pre - Hypertension % % of Hypertensionof % Hypertension % 0 < 20,000 <=20,000 - <= >45,000 - = < income >6500 <45,000 65,000 Household Income by Sodium intake Table 19: Cross tabulations of Household Income and Blood Pressure Consumption NHANES data 2005-2012 Sodium Intake Income <1500 1500-2399 2400-3400 >3400 <19,999 n=1039 n=583 n=606 n=798 6.08% 3.41% 3.55% 4.67% 20,000 - 44,999 n=1938 n=1450 n=1534 n=2061 11.34% 8.48% 8.98% 12.51% 50,000 - 64,999 n=1440 n=1156 n=1381 n=2051 8.43% 6.76% 8.08% 12.00% >65,000 n=191 n=187 n=260 n=414 1.12% 1.09% 1.52% 2.42% 96 Table20: Effect of Sodium on Blood Pressure Controlling for Income on NHANES 2005-2012 BLOOD PRESSURE Pre - Stage 2 Stage 2 Normal Hypertension Hypertension Hypertension Income $ Sodium % % % % P-Value <19,999 <1500 45.33 28.39 16.27 10.01 <0.0001 1500-2399 41.51 32.93 15.44 10.12 2399-3400 43.73 33.99 13.86 10.12 >3400 43.36 38.60 12.66 5.39 20,000 - 44,999 <1500 48.92 30.60 13.57 6.91 <0.0001 1500-2399 44.48 32.62 16.69 6.21 2399-3400 44.20 34.94 14.99 5.87 >3400 46.53 36.63 12.42 4.42 50,000 - 64,999 <1500 48.19 34.86 12.29 4.65 0.0014 1500-2399 45.33 34.08 14.88 5.71 2399-3400 45.47 35.63 13.98 4.92 >3400 48.32 37.10 11.51 3.07 >65,000 <1500 55.50 30.89 10.99 2.62 0.1840 1500-2399 52.94 33.16 9.63 4.28 2399-3400 49.23 38.46 10.38 1.92 >3400 45.65 42.75 8.45 3.14 The relationship between sodium and hypertension, while controlling for income, is presented in the above table. The chi square test for independence is significant at p=0.001 indicating that income affects the relationship between sodium and hypertension. The table reveals that 24% of those with incomes higher than USD 65,000 and consume high levels of sodium (> 2,399 mg) have hypertension while 29% of those who consume less than 1500 mg of sodium and have low income (less that USD 20,000) have hypertension. These results would indicate that those with high incomes get hypertension at lower rates that those with less income. The logit regression results are confirmed by a 97 logit model which shows that the odds ratios of getting hypertension based on income were. R6: Is there a significant relationship between sodium and hypertension based on sex? H6 There is a significant relationship between sodium and hypertension based on sex The following results (Tables 21, 22 and figure 16) seek to answer the above hypothesis and research question Table 21: Cross tabulations of Sex and Blood Pressure Consumption NHANES data Blood Pressure 2005- Stage 2 Stage 2 2012 Pre - Hypertension (SEX Normal Hypertension Hypertension n=503 Male n=4279 n=4287 n=1561 (4.73%) (40.25%) (40.33%) (14.68%) Female n=6068 n=3249 n=1297 n=614 (54.04%) (28.94%) (11.55%) (5.47%) Table 22: Cross tabulations of Sex and Sodium Intake Consumption NHANES data 2005- 2012 Sodium Intake SEX <1500 1500-2399 2400-3400 >3400 Male n=2671 n=1461 n=2099 n=4399 12.22% 6.68% 9.60% 20.13 Female n=3140 n=2748 n=2771 n=2569 14.37% 12.47% 12.68% 11.75% 98 Table 23: Significance of Gender/Sex and Sodium on Hypertension NHANES 2005-2012 Blood Pressure Stage 1 Stage 2 Pre - Hypertension Hypertension p Hypertension % % SEX Sodium Normal % % Male <1500 42.68 35.72 15.31 6.29 <.0001 1500-2399 38.47 38.81 17.59 5.13 2399-3400 37.49 41.69 15.86 4.95 >3400 40.69 42.99 12.78 3.55 Female <1500 54.84 27.42 11.50 6.24 <.0001 1500-2399 50.58 29.62 13.06 6.73 2399-3400 52.33 30.42 12.09 5.16 >3400 58.62 28.45 9.42 3.50 Figure 17: Analysis of Sodium Intake Blood Pressure by Sex/Gender NHANES 2005-2012 Figure 17: Analysis of Sodium Intake, Blood Pressure by Sex/Gender NHANES 2005-2012 70 60 50 40 30 20 Normal % ofPressureBlood % 10 Pre-Hypertension 0 Hypertension 2399 3400 2399 3400 - - - - >3400 <1500 <1500 >3400 1500 2399 1500 2399 Male Female Sex/Gender by Sodium Intake 99 The chi square test (X2) for the relationship between sodium and hypertension controlling for gender is significant (p<0.0001) indicating that gender has an impact on the relationship between sodium consumption and hypertension. Further inspection of the table shows that approximately 35% of men who consume more than 3400 mg of sodium have hypertension. This percentage is over two and half times higher than women with high hypertension who consume more than 3400 mg of sodium (13%). Based on this finding it can be concluded that men consume less sodium but have more hypertension cases than women. These results are confirmed by a logit model which shows that the odds ratios of getting hypertension among men who consume high levels of sodium are higher than for women. R6- Is there a significant relationship between sodium and hypertension in all BMI categories? H6- There a significant relationship between sodium and hypertension in all BMI categories The following seek to answer the above research question and hypothesis: 4.5 Body Mass Index and Blood Pressure Table 24 shows the relationship between body mass index (BMI) and blood pressure. There is a strong association between body mass index and high blood pressure. The chi-square test of significance for the relationship is significant at 5% level of significance. Over three quarters (75.7%) of the total number of respondents who were either hypertensive or who had hypertension were overweight. From these results it can be inferred that being overweight is a factor in having high blood pressure. 100 Table 24: Cross tabulations of BMI and Blood Pressure NHANES data 2005-2012 Blood Pressure Body Mass Index Normal Pre-hypertension Stage 1 Stage 1 Hypertension Hypertensio n Underweight n=144 n=50 n=22 n=17 (61.80%) (21.46%) (9.44%) (7.30%) Healthy Weight n=3447 n=1734 n=625 n=291 (56.54%) (28.44%) (10.25%) (4.77%) Overweight n=3395 n=2536 n=951 n=361 (46.87%) (35.01%) (13.13%) (4.98%) Obese n= 3121 n=3072 n=1198 n=420 (39.96%) (39.33%) (15.34%) (5.38%) Figure 18: Analysis of Sodium Intake, Blood Pressure by BMI NHANES 2005-2014 Analysis of Sodium intake Blood Pressure by BMI NHANES 2005-2014 18 16 14 12 10 8 6 Normal % 4 % of Bloodof pressure % Pre - Hypertension % 2 0 Hypertension % BMI by sodium intake 101 Table 25: Cross tabulations of BMI and Sodium Intake Consumption NHANES data 2005-2012 Sodium Intake Body Mass Index <1500 1500-2399 2400-3400 >3400 Underweight n=82 n=44 n=44 n=63 0.38% 0.21% 0.21% 0.29% Healthy Weight n=1687 n=1133 n=1323 n=1954 7.89% 5.30% 6.19% 9.14% Overweight n=1908 n=1420 n=1630 n=2285 8.92% 6.64% 7.62% 10.69% Obese n=1959 n=1503 n=1167 n=2555 9.16% 7.03% 8.39% 11.95% Table 25 shows the relationship between body mass index (BMI) and sodium intake. Blood pressure level is higher in overweight and obese participants compared to those with normal weight. The chi-square test of significance for the relationship is significant at 5% level of significance. Over three quarters (73%) of the total number of respondents consumed more than 1500mg of sodium per day. The result also shows that the participants who were overweight consume more sodium than those with normal weight and underweight. 102 Table 26: The Effect of Body Mass Index and Sodium on Hypertension Blood Pressure Pre - Stage 1 Stage 2 Normal Hypertension Hypertension Hypertension p BMI Sodium % % % % Underweight <1500 65.85 19.51 6.10 8.54 0.1177 1500-2399 61.36 18.18 6.82 13.64 2399-3400 47.73 31.82 18.18 2.27 >3400 66.67 19.05 9.52 4.76 Healthy 5.93 <1500 56.61 26.85 10.61 <0.0012 Weight 1500-2399 54.99 28.51 11.12 5.93 2399-3400 54.20 29.55 11.41 4.84 >3400 58.96 29.02 8.65 3.38 Overweight <1500 47.69 31.97 13.78 6.55 <0.0001 1500-2399 45.49 33.52 14.79 6.20 2399-3400 47.24 34.97 13.50 4.29 >3400 46.78 38.51 11.29 3.41 Obese <1500 42.73 35.78 15.42 6.07 <0.0001 1500-2399 40.72 35.99 16.83 6.45 2399-3400 38.85 39.69 15.44 6.02 >3400 38.16 43.76 14.32 3.76 The results in tables 25, 26 and figure 18 show that a chi square test (X2) for the relationship between sodium and hypertension controlling for BMI is significant at p<0.0001 indicating that BMI has an impact on the relationship between sodium consumption and hypertension. On the other hand, for those underweight, there was no significance for the study indicating that people who are underweight does not for the most part have high blood pressure. This support the literature which indicated that overweight and obsessed are significantly affected with high blood pressure136. 103 Approximately 41% of participants with BMI of more than 29 and who consume more than 3400 mg of sodium have hypertension. This percentage is about 5% higher than those who have normal BMI (<18) and have hypertension. The logit model shows that the odds ratios of getting hypertension among participants with high BMI is higher than those with low BMI. 4.6: Age and Blood Pressure Figure 18 shows the impact of sodium on hypertension while controlling for age. The number of hypertension cases increase with age. At the lowest age categories, sodium seems to have less to no impact on hypertension while at higher age groups sodium has a positive impact on hypertension. Figure 19: Comparing Sodium Intake by Blood Pressure in Age 20 and Older NHANES 2005-2012 Figure 19: Comparing Sodium Intake by Blood Pressure in Ages 20 and older NHANES 2005-2012 90 80 70 60 50 40 30 Normal 20 Pre- Hypertension Blood Pressure Bloodlevels % in 10 0 Hypertension 2399 3400 2399 3400 2399 3400 2399 3400 2399 3400 ------ <1500 >3400 <1500 >3400 <1500 >3400 <1500 >3400 <1500 >3400 1500 2399 1500 2399 1500 2399 1500 2399 1500 2399 20-29 30-39 40-49 50-59 60+ Sodium leveles by age group 104 Table 27: Significance of Age and Sodium on Hypertension NHANES 2005-2012 Blood Pressure Pre - Stage 1 Stage 2 Normal Hypertension Hypertension Hypertension p Age Sodium % % % % 20-29 <1500 72.69 24.14 2.80 0.36 0.0425 1500-2399 77.04 20.13 2.00 0.83 2399-3400 74.48 23.31 1.82 0.39 >3400 69.91 26.85 2.88 0.36 30-39 <1500 66.22 25.69 5.83 2.25 <0.0001 1500-2399 70.00 23.83 5.67 0.50 2399-3400 67.06 28.04 3.70 1.19 >3400 57.48 34.65 6.80 1.07 40-49 <1500 54.08 32.03 11.13 2.76 <0.0409 1500-2399 53.51 34.95 9.36 2.18 2399-3400 50.29 37.69 9.57 2.45 >3400 47.98 39.11 9.58 3.33 50-60 <1500 41.24 38.01 16.02 4.72 <0.0007 1500-2399 44.09 35.45 15.00 5.45 2399-3400 34.61 44.61 15.92 4.87 >3400 35.77 45.59 14.14 4.50 60 + <1500 28.47 34.45 22.77 14.32 <0.0001 1500-2399 25.09 38.26 24.10 12.30 2399-3400 26.63 38.90 24.41 10.05 >3400 28.42 42.39 21.40 7.79 Table 27 shows the relationship between sodium and hypertension, while controlling for age groups. The table shows that hypertension was very low among those ages 20-29 and highest among those who are 60 years and over. This support the hypothesis that age affects the relationship between sodium and hypertension. 105 4.6.1 Isolated Hypertension Isolated hypertension is when the systolic pressure is more than 140mmHg and the diastolic is less than 90mmHg.134 In this dissertation, systolic Isolated hypertension is measured as systolic blood pressure of >140 mmHg. More than 98% of the participants fall in this group. Even though systolic isolated blood pressure is normally geared towards elderly, there was significantly high number of young people in the data with ISH. Participants between the ages 20-29 as shown in table 28 pages 107 who had ISH were 17.85%. In addition, the results in table 28 shows that female have higher percentage of isolated hypertension compared to their male counterpart. Also, participants that were 60 years or older had the higher rate of systolic isolated hypertension with a percentage of 31.45%. Further, there is a significance value of <.0001 in both male and female. The cross tabulation of ISH by Sodium intake in table 29 and table 30 page 107 shows that more than 53% of the participants with ISH consume 2400mg of sodium or higher. Further analysis using logistic regression in table shows that sodium, income and education are not determinants of ISH. And a decrease in age can decrease ISH by more than 19% (0.778, 0.887) CI. Further, one increase in BMI can cause 49.4 % (0.778, 0.887) CI increase in ISH. 106 Table 28 Systolic Isolated Hypertension by Gender Sex Normal Isolated Hypertension Male n=263 n=10367 (1.20%) (47.43%) Female n=118 n=11110 (0.54%) (50.83%) p-Value <.0001 Table 29: Systolic Isolated Hypertension by Age Age Normal Isolated Hypertension 20-29 n= 44 n= 3820 (0.21%) (17.85%) 30-39 n= 91 n= 3639 (0.43%) (17.01%) 40-49 n= 122 n= 3582 (0.57%) (16.74%) 50-59 n= 79 n= 3258 (0.37%) (15.22%) = >60 n= 37 n= 6729 (0.37%) (31.45%) p-Value <.0001 Table 30: Cross tabulations of Isolated Hypertension by Sodium intake Isolated Systolic Hypertension Sodium Normal % ISH % <1500 0.43 26.15 >=1500-2399 0.25 19.00 >=2399-<=3400 0.37 21.91 >3400 0.69 31.19 p-value 0.0054 107 Figure 20: Analysis of Systolic Isolated hypertension by Gender by Age 120 100 80 60 40 Normal 20 ISH 0 % of Isolated of % systolic Hypertension 20-29 30-39 40-49 50-59 60 20-29 30-39 40-49 50-59 60 and and above above Male Female Sex/Gender by Age ISH = Isolated systolic hypertension Table 31: Risk Estimate for Significant Independent Variables Using Logistic Regression Independent Coefficient P-value 95% CI for Variable Estimates Odds Ratio Income 0.1068 0.1539 (0.961, 1.289) Sodium 0.00777 0.8767 (0.914, 1.112) Race 0.2106 0.0002 (1.107, 1.377) BMI 0.4946 <.0001 (1.408, 1.909) Education 0.0490 0.4221 (0.932, 1.18) Age -0.1856 <.0001 (0.778, 0.887) Sex (REF=male) -0.8525 <.0001 (0.332, 0.547) 108 4.7 Cochran - Armitage Trend Test Using SAS Cochran - Armitage Trend test was used to measure the growth of blood pressure in the different subpopulations over the years. For each subgroup, the test was further used to determine whether there was a significant trend of blood pressure across the different categories of the subpopulations. The results in Figure 21 - 27 (pages 108-114) shows that for each subpopulation, there was a trend with hypertension. Figure 21: Distribution of Blood pressure by Sodium 109 Figure 22: Distribution of Blood pressure by Race Note: Race 0= 'Mexican American', 1='Other Hispanic', 2='Non-Hispanic White' 3='Non-Hispanic Black', 4='Other Race Multi-Racial' Figure 23: Distribution of Blood pressure by Education Note: Education: 0= 'Less than High School', 1='High school graduate/GED or equivalent', 2='Some college or AA degree', 3='College graduate or above' 110 Figure 24: Distribution of Blood pressure by Income Note: Income 0=<19,999, 1=20,000-44, 999, 2=50,000-64,999, 3=>65,000 Figure 25: Distribution of Blood pressure by Gender Note: 0= Male, 1 = Female 111 Figure 26: Distribution of Blood pressure by BMI Note: 1= Underweight, 2= Healthy Weight, 3= Overweight, 4= Obese Figure 27: Distribution of Blood pressure by Age Note: 0=20-29, 1=30-39, 2=40-49, 3=50-59, 5=60> 112 4.8 Summary of Hypothesis Testing The chi-square of association shows that the categorical independent variables were associated to the dependent variable. Further, the Cramer's V statistics shows less than 0.5 which means that the association not strong. Table 32 shows the association of the independent variables to blood pressure (p<.0001). Table 32: Test for Association of the Categorical Variables to the Dependent Variable Chi-Square Cramer's V Variable value p-Value Statistics Income 109.95 <.0001 0.0463 Education 273.38 <.0001 0.0646 Race 265.64 <.0001 0.0636 BMI 414.24 <.0001 0.0804 Age 3474.82 <.0001 0.2327 Sex 471.70 <.0001 0.1469 Sodium 130.09 <.0001 0.0445 Table 33: Risk Estimate for Significant Independent Variables Using Logistic Regression Independent Coefficient P-value 95% CI for Variable Estimates Odds Ratio Income 0.0952 0.0006 (1.042, 1.161) Education 0.1145 <.0001 (1.074, 1.170) Race -0.1630 <.0001 (0.816, 0.885) BMI -0.1281 <.0001 (0.835, 0.927) Age -0.4729 <.0001 (0.608, 0.639) Sex (REF=male) 0.1781 <.0001 (1.097, 1.302) Sodium (REF=sodium 2300mg) 0.0898 0.0001 (1.054, 1.135) Table 33 shows the results of the risk estimate using logistic regression. As indicated in table 33, income, income, education, race, BMI, age, sex, and sodium are predictors of hypertension. 113 The result also, shows a coefficient estimate of change of log odd of hypertension associated with one unit increase in the independent variables. The results can be explained as when compared to normal blood pressure and all other variables being constant; one increase in education is associated with an increase of 0.1145 in log odds Table 33 shows that one unit decrease in BM1 is associated with 12.8% decrease in the log odds of getting hypertension. 4.9 Prevalence of hypertension NHANES 2005 -2014 ages 20 years and older Figure 26 and figure 27 present the trend of hyper tension from 2005 and 2014. Figure 19 shows there was an increase of blood pressure rate of 1.35% from 2005-2006 to 2007 -2008. 2.62% decrease from 2007-2008 to 2009-2010. There was a slight increase in from 2011-2012 and 1% decrease in 2013-2014. The percentage of hypertension incidents 2005-2014 analysis shows 2% decrease in hypertension. As indicated in figure 20, for each of the years, participants with pre-hypertension were almost double the number of participants with hypertension. 114 Figure 28: Prevalence of Hypertension NHANES 2005-2015 Ages 20 Years and Older Prevelance of Hypertension NHANES 2005-2014 ages 20 year and older 21 20 19 18 Hypertension % 17 % of Hypertensionof % 16 15 2005-2006 2007-2008 2009-2010 2011-2012 2013-2014 115 Figure 29: Incidence of Hypertension among Adults Ages 20 and Older NHANES 2005 2014 Incidence of hypertension amog adults ages 20 and older NHAHES 2005-2014 50 45 40 35 30 25 Normal % Pre - Hypertension % 20 % of Hypertensionof % Hypertension % 15 10 5 0 2005-2006 2007-2008 2009-2010 2011-2012 2013-2014 Blood pressure by year 116 CHAPTER 5 DISCUSSIONS AND LIMITATIONS Trend analysis of the 2005-2012 NHANES data shows that sodium consumption has increased over the eight years of data collection while hypertension cases have not increased commensurate with this increased sodium consumption. This would appear to disqualify the hypothesis that increased sodium consumption leads to hypertension. Between the years 2005-2006 and 2007-2008, the highest level of sodium consumption (3400+ mg) decreased slightly from over 30 percent of the sample to less than 30 percent of the sample. During the following data collection cycle there was an increase in the percentage of the sample that consumed the highest levels of sodium to slightly less than 35 percent and this number stayed almost constant for the next two cycles. On the other hand, between 2005-2006 and 2007-2008, hypertension cases increased slightly but decreased in the next two data collection cycles. When looking at hypertension alone without sodium, there has been a decrease from 2005 to 2014. What would explain this anomaly? One argument that could be advanced is that even though sodium consumption levels increased, individuals were more physically active and hence the consequences of high sodium consumption were cancelled out. Another explanation is that those who consumed more sodium were mostly young people who are naturally more active and would not be affected by high levels of sodium consumption. This would also lend support to the argument that perhaps sodium alone does not lead to hypertension but enhances the underlying existing conditions such as kidney disease and old age. 117 The results shown in Figure 19 confirm that, controlling for age, the number of hypertension cases increase with sodium consumption. At the two lowest age categories, (20-29 and 30-39) individuals do not seem to be affected by increased sodium consumption. However, from age group 40-49, the number of hypertension cases starts to increase and are at the highest level at the 60 and above age group. Again, this result confirms that age affects the number of hypertension cases and sodium seems to be a catalyst. When controlling for gender, males have more than twice the number of hypertension cases as females (35% vs. 13%) at the highest level of sodium consumption. This result is also true at all the other levels of sodium consumption. The question that might be asked is; do men get more affected by sodium consumption than women? What would be the reason for this? Education seems to have a positive impact on sodium consumption. The higher the education levels the more the sodium consumption. However, this result does not translate into higher hypertension cases as was expected. There could be two reasons for this. First, those who are highly educated are consuming more sodium because they eat out more and evidence shows that restaurant foods have more sodium compared to other foods. Second, this group is also more educated and more health conscious. Thus, even though they consume more sodium they are also the group that is more likely to exercise and reduce the impact of high sodium consumption. This observation needs to be confirmed by more research. 118 The impact of race on sodium consumption and hypertension from the NHANES data analysis followed the expected outcome from previous research. Non-Hispanic Blacks have the highest percentage of hypertension cases and they also consume more sodium followed by Mexican Americans. Other Hispanic group has the lowest number of hypertension cases. It would seem that the impact of sodium is more significant among blacks because of their underlying genetic makeup that makes them more susceptible to increased sodium consumption. If these underlying conditions can be well understood, programs targeting this specific group can be designed. Another way to answer this question would also be, why is it that non-Hispanic whites do not have high percentage of hypertension even though they consume high amounts of sodium? Can these be translated to Blacks? These results suggest that more analysis is needed to study the specific American subgroups and how they respond to high sodium consumption and its impact on hypertension. 5.1: Discussion of Hypothesis • Hypothesis 1 -Sodium has a significant impact on hypertension In the case of hypothesis one, sodium consumption of <1500mg, is statistically significant predictor of hypertension status at the alpha =.05 level, chi-square = 9.81 and p=.0017. Sodium consumption between1500mg and 2399mg, is a statistically significant predictor of hypertension status at the alpha =.05 level, chi-square = 3.54 and p=.0598 and for sodium consumption between 2399mg and >3400mg, there was 119 no statistically significant predictor of hypertension status at the alpha =.05 level, chi-square = 0.01 and p=.9073. The logistic regression test also confirmed the significance level with a p-value of<0.0001 in table 27. Hypothesis 1 was supported. • Hypothesis 2-There a significant relationship between sodium and hypertension adjusting for ethnicity The findings shown in the regression analysis and table 12, results of chi- square test for the association between race, sodium intake and hypertension was significant. The logistic regression test also confirmed the significance level with a p-value of <0.0001 in table 27. Hypothesis 2 was supported. • Hypothesis 3- There is a significant relationship between sodium and hypertension adjusting for education The findings shown in Table 12 with the chi- square test of significance shows that there is a relationship between education, sodium intake and hypertension were significant. The logistic regression test also confirmed the significance level with a p-value of <0.0001 in table 27. Hypothesis 4 was supported. • Hypothesis 4- There is a significant relationship between sodium consumption and hypertension adjusting for income The findings showed in table 27 shows the significance level with a p-value of 0.0006 at alpha level of 0.05. Hypothesis 2 was supported. 120 • Hypothesis 5- There is a significant relationship between sodium and hypertension adjusting for gender Table 18 shows that there was a significant relationship between sodium and hypertension based on sex. Table 27 also confirmed the significance level with a p-value of <0.0001 using logistic regression. Hypothesis 5 was supported. • Hypothesis 6- There is a significant relationship between sodium and hypertension adjusting for BMI The findings shown in Table 27 shows that, even though some of the BMI levels has p- values of <0.0001, the alpha level of 0.05. Hypothesis 6 was supported. The findings shown in table 27 shows the significance level with a p-value of <0.0001 at alpha level of 0.05. Hypothesis 2 was supported. • Hypothesis 7- There is a significant relationship between sodium and hypertension adjusting for Age The findings shown in table 26 shows that there is association between blood pressure and sodium given the alpha level of 0.05 and table 27 shows the significance level with a p-value of <0.0001. Hypothesis 7 was supported. 121 LIMITATIONS The current findings for the dissertation were subject to little limitations; even though five cycles of NHANES data representing 10 years data analysis of NHANES provided large sample size that calls for precision in outcome measurement. Dietary recall can be over -estimated or under estimated when giving account of caloric intake and sodium. And self reported sodium intake can result in under estimation which can create reporting bias because one cannot estimate for sodium that was added while cooking or sodium that was added at the table. NHANES being a cross-sectional study does not allow casual inference in the study. Further, 2013-2014 sodium data is not available which means the analysis with sodium was subject to 8 years instead of 10 years. NHANES data has previously been used for estimations of prevalence in several studies: Meanwhile, primarily NHANES data are restricted to non-institutionalized participants. This means institutionalized populations such as those in prisons, assisted living and other institutions are not represented. Moreover, research findings on non-institutionalized population do not represent hundred percent of the population. Besides, people eat differently on different days; people turn to eat more restaurant foods on weekends and depending on the day that the interview was done can also affect the sodium intake report. Further, most foods such as breads, cereal, and cookies that are high in sodium do not taste salty. Finally, in addition to the aforementioned limitations, the multi-stage probability nature of NHANES does not address time. Sampling parameters can vary over time. To avert these limitations, the government and policy makers should come together to work with food industries and the restaurant industries to set bench marks for sodium reduction in foods. Different states should emulate New York City's initiative for 122 lowering sodium in food products giving that increased sodium intake in adult Americans leads to hypertension. 123 CHAPTER 6 SUMMARY AND CONCLUSIONS This research investigated the impact of sodium on blood pressure by using NHANES data set collected by CDC in addition to reviewing previous studies which show that sodium causes hypertension. Simple frequencies and cross tabulations were conducted to investigate the relationship between sodium and hypertension. Chi-square tests of significance were also conducted. The chi-square tests showed there is between sodium and high blood pressure. Cross tabulations on the relationship between sodium and education, sodium and income, sodium and race, sodium and gender, sodium and BMI, sodium and age, sodium and Iisolated systolic hypertension were also conducted. Chi-square tests on these relationships were also significant at 1% level of significance. Findings of this research also indicated that sodium has a positive and significant effect on blood pressure. Education was also found to have a strong relationship with blood pressure. However, the impact of sodium on education was unexpected. Contrary to theory, there seems to be a strong relationship between high sodium consumption and high level of education, a finding that needs further investigation. Results of this study show that reducing sodium intake is an effective tool for public health policy. However, there needs to be more analysis on the impact of sodium on various American subgroups in order to determine how well to address the impact of increased sodium consumption and design more effective and well targeted intervention programs. Further, huge savings in medical care costs can be achieved by reducing salt intake. Lost work days and inpatient bed days can be reduced by this one public health 124 policy. Aggressive public health programs should be launched to encourage people to adopt diets with less sodium. The current recommendations in the US to reduce salt intake to 1500 mg day for those with high blood pressure and 2400 mg per day for the general population should help reduce high blood pressure among the US population. Evidence shows that the WHO recommendation of reducing sodium intake reduction to less than 5g per day might not be sufficient. Experts suggest that this level should be reduced to 3g per day. The American heart association recommends the dietary approaches to reduce hypertension (DASH) diet to those with pre-hypertension and those with hypertension. This diet is rich in grains, fruits, vegetables and low-fat dairy products81. Given the existing knowledge on the effect of sodium on blood pressure, this recommendation should be pursued as a matter of public policy. Further review of the literature on the impact of sodium on blood pressure was conducted. This review look at the different data sets used in investigating the relationship between sodium and high blood pressure, analysis procedures used and the list of variables used. 125 6.1 FUTURE STUDIES The goals for the study were met. NHANES data is valuable in accessing the national disease prevalence. Meanwhile in the future studies can look at the impact of sodium on children and adolescents. Instead of 10 years, future studies can focus on one NHANES cycle (two years) and limit the subgroups to just two groups such as race and education. Future studies can include cholesterol as an independent variable to see if it has any influence on the impact of sodium on hypertension. Also, one can use two dependent variables such as hypertension and diabetes to predict if there is a correlation between hypertension and diabetes and the other independent variables. 126 REFERENCES 1. Blood Pressure and Your Health. 2010. at http://www.ash- us.org/documents/BloodPressureHealthEnglish.pdf. 2. 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