Relationship Between Short Sleep Duration and Cardiovascular Risk Factors in a Multi-Ethnic Cohort – the Helius Study

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The role of sleep in ethnic inequalities in health: Cardiovascular disease and risk factors

Anujuo, K.O.

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Download date:24 Sep 2021 CHAPTER 4

RELATIONSHIP BETWEEN SHORT SLEEP DURATION AND CARDIOVASCULAR RISK FACTORS IN A MULTI-ETHNIC COHORT – THE HELIUS STUDY

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Kenneth Anujuo, Karien Stronks, Marieke B. Snijder, Girardin Jean-Louis, Femke Rutters, Bert-Jan van den Born, Ron J. Peters, Charles Agyemang. Relationship between short sleep duration and cardiovascular risk factors in a multi-ethnic cohort – the HELIUS study. Sleep Med. 2015;16:1482-1488.

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ABSTRACT

Objective: To investigate the association between short sleep duration and CVD risk factors including hypertension, diabetes, obesity, and lipid profile among various ethnic groups (South-Asian Surinamese, African Surinamese, Ghanaians, Turks, Moroccans and Dutch) living in the Netherlands. We also examined the contribution of social economic status (SES) and lifestyle factors to this association.

Method: 12805 participants (aged 18-70 years) from the multi-ethnic HELIUS cohort. Short sleep duration was defined as <7 hours/night. The association between short sleep and CVD risk factors, and the contribution of SES and lifestyle factors were assessed using prevalence ratios (PRs).

Results: Short sleep was significantly associated with obesity in four out of six ethnic groups, with the socio-demographic adjusted PR of 1.45 (95% CI, 1.07-1.95) in Dutch, 1.21 (1.01-1.44) in South-Asian Surinamese, 1.25 (1.09-1.43) in African Surinamese and 1.16 (1.04-1.29) in Turks. Short sleep was significantly associated with diabetes in African Surinamese (1.45, 1.14-1.84), Turks (1.59, 1.26-2.02), and Moroccan (1.29, 1.02-1.63). By contrast, the associations between other cardiovascular risk factors and short sleep were not significant in most ethnic groups, with the exception of the association with hypertension in Dutch and Turks, and dyslipidaemia in South-Asians Surinamese (reduced HDL cholesterol and triglyceride) and Moroccans (raised total cholesterol). SES and lifestyle factors contributed little to the observed associations.

Conclusion: Our findings indicate that short sleep is associated with obesity and diabetes in most ethnic groups. The associations for other risk factors vary between ethnic groups. Further studies are needed to establish the potential factors that might lead to the observed differences across populations.

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INTRODUCTION

Cardiovascular disease (CVD) is the leading cause of global mortality. Several prospective and retrospective studies have shown that hypertension, diabetes, obesity and dyslipidaemia are important risk factors for CVD [1,2]. As the prevalence of these risk factors (especially obesity and diabetes) is increasing in adult populations in most countries [3], the necessity to identify potential modifiable risk factors increases, in order to reduce adverse CVD outcomes.

Recently, several studies have shown conflicting reports on the association between sleep duration and cardiovascular risk factors including hypertension [4,5], diabetes [6-9], obesity [10-12] and dyslipidaemia [13- 19]. The fact that two independent studies showed an association between short sleep and cardiovascular mortality is supportive of the hypothesis that short sleep is related to CVD risk factors [20,21]. Recent studies indicated that the relationship between sleep duration and CVD risk factors varies between study populations [22-23]. This suggests the potential importance 4 of contextual factors such as sociocultural and lifestyle factors which may influence the association. Previous studies suggested that the association between sleep duration and CVD risk may be mediated by SES, lifestyle factors and other covariates, they were therefore recommended to be included in future studies [24].

Studies investigating the relationship between sleep duration and cardiovascular risk factors have not considered differences among ethnic minority groups with different migration backgrounds. In addition, CVD and risk factors also differ between ethnic groups [25-29]. For instance, Surinamese people in Netherlands have higher incidence rates of stroke than the European Dutch. By contrast, Moroccans have lower incidence rates of stroke compared with Dutch [30]. Also, ethnic minority groups tend to experience shorter sleep duration compared to their host European majority populations [29]. Given the variation in the association between short sleep and CVD risk factors between populations, it is important to elucidate how short sleep is related to CVD risk factor in different ethnic groups. Furthermore, the data on the relationship between short sleep and CVD risk factors across ethnic minority groups are lacking particularly in Europe. Using data from the Healthy Life in an Urban Setting (HELIUS) study, the aim of this study was to investigate whether there are differences in the association of sleep duration with cardiovascular risk factors between

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various ethnic minority groups living in the Netherlands. In addition, the contribution of SES and lifestyle factors to these associations was examined.

STUDY POPULATION AND METHODS

Study population

This study was based on baseline data from the HELIUS study. The aims and design of the HELIUS study have been described elsewhere [30]. In brief, HELIUS is a large-scale prospective cohort study on health and health care among different ethnic groups living in Amsterdam. The study started in 2011 and it includes individuals aged between 18 and 70 years from the six major ethnic groups in Amsterdam (African-Surinamese, South-Asian Surinamese, Turks, Moroccan, Ghanaian, and Dutch origin). This study focuses on three major disease categories: cardiovascular disease, mental health and infectious diseases. Participants were randomly sampled from the municipal registers and stratified by ethnicity. The study protocols were approved by the Academic Medical Center (AMC) Ethical Review Board. All participants provided written informed consent.

This study used baseline data that were collected until June 2014. The study included 13,316 participants from whom data from both questionnaire and the physical examination were available. Participants with a Javanese Surinamese background (n=137), other/unknown Suriname background (n=141) or other/unknown background (n=26) were excluded because of the small sample sizes. In addition, individuals with no data on sleep duration (n=207) were also excluded from the analysis. This resulted in a dataset of 12,805 participants, including 2146 Dutch, 2158 African-Surinamese, 2262 South-Asian Surinamese, 1795 Ghanaians, 2242 Turks and 2202 Moroccans.

Measurements

Sleep duration Participants were asked to provide information on their average hours of sleep at night. Sleep duration was assessed using the item, `How many hours do you sleep on average per night?` Short sleep was defined as having <=6 hours of sleep per night according to National Sleep Foundation (NSF), American Academy of Sleep Medicine (AASM), and Sleep Research Society

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(SRS) which recommend 7 to 8 hours as the basal sleep need for healthy adults [31, 32]. We focused on short sleep only because in our previous study, we previously demonstrated that short sleep was the major problem for the ethnic minority groups [29], and because previous studies found that short sleep was more consistently related to CVD risk factors compared to long sleep [22-23], [33-35].

Ethnicity Participant’s ethnicity was defined according to the country of birth of the participant as well as that of their parents. Specifically, a participant is considered to be of ethnic minority origin if he/she fulfils either of the following criteria: 1) he or she was born abroad and has at least one of his/ her parents born abroad; or 2) he or she was born in the Netherlands but has both his/her parents born abroad [30]. The Surinamese population is made up of several ethnic subgroups including those of Africa Surinamese, South- Asian Surinamese, Javanese, Amerindian, and Chinese origin. Therefore, in Surinamese, self-identification was also used to further distinguish the subgroups of Surinamese origin. Surinamese are migrants from Suriname, 4 which is a former Dutch colony in South America. Surinamese people who have an African-Caribbean background are mostly of West African descent, while those with a South Asian background have North Indian origins. They all migrated from Suriname to the Netherlands due to the political instability, in Suriname in 1975 and 1980. Ghanaians migrated to the Netherlands between 1974 and 1983 predominantly for economic reasons, while others migrated due to drought, political instability and the deportation of Ghanaians from Nigeria in the early 1990s. The Turkish and Moroccans migrated to the Netherlands in the 1960s and early 1970s to fill labour shortages which were lacking in unskilled occupations. During 1970–1980, Turkish and Moroccans guest workers brought their spouses and children to the Netherlands.

Cardiovascular risk factors Weight was measured in light clothing with SECA877 to the nearest 0.1 kg. Height was measured without shoes with a portable stadiometer (SECA 217) to the nearest 0.1 cm. Blood pressure (BP) was measured using a validated automated digital BP device (Microlife WatchBP Home, Microlife AG, Heerbrugg, Switzerland) on the left arm in a seated position after the participant had seated for at least 5 minutes. All measurements were performed in duplicate; the mean of the two measurements was used in the analyses.

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Fasting blood samples were taken in the morning and used to determine the concentration of glucose by spectrophotometry, using hexokinase as primary enzyme (Roche Diagnostics, Japan). Total cholesterol, triglycerides and high-density lipoprotein (HDL) cholesterol were determined by colorimetric spectrophotometry (Roche Diagnostics, Japan). Low-density lipoprotein cholesterol (LDL) was calculated according to the Friedewald formula [36].

Body mass index (BMI) was calculated as weight (kg) divided by height squared (m2). Participants were considered obese if the BMI was > 30 kg/ m2. Hypertension was defined as systolic BP ≥ 140 mmHg, or diastolic BP ≥ 90 mmHg, or being on antihypertensive medication, or self-reported hypertension. Type 2 diabetes was defined as increased fasting glucose ≥ 7mmol/L or current use of medication prescribed to treat diabetes as recorded at the physical examination, or self-reported diabetes. Individual components of dyslipidemia were determined separately using the recommended cut off as follows: Total serum cholesterol (TC) > 6.22mmol/L, high density lipoprotein cholesterol (HDL-C) < 1.04mmol/L, low density lipoprotein cholesterol (LDL- C) > 4.14mmol/L, and triglyceride (TG), > 1.69mmol/L [37-38].

Other measurements The level of educational level was determined using participant’s highest level of education (either in the Netherlands or in the country of origin). Participants were categorized into those who have never been to school or had elementary schooling only (1st category), those with lower vocational schooling or lower secondary schooling (2nd category), those with intermediate vocational schooling or intermediate/higher secondary education schooling (3rd category), and those with higher vocational schooling or university (4th category). The first two categories were combined because of small numbers during this analysis.

Marital status included married/ registered/ partnership, living together, unmarried/ never married, divorced/separated, or widowed. Using a questionnaire, the alcohol intake in the past 12 months (yes/no) and smoking status (yes/no/ex-smoker) were obtained.

Habitual physical activity was measured using the Short Questionnaire to Assess Health-Enhacing Physical Activity (SQUASH) questionnaire [39]. The SQUASH questions about multiple activities refer to a normal week

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in the past months. Participants were categorized according to the Dutch guideline for physical activity by summing up the number of days per week for each moderate- and high- intensity activity lasting at least 30 minutes. A total of 5 days resulted in participants being categorized as achieving the Dutch norm for physical activity.

Data Analysis

Baseline data were expressed as percentages or means with 95% CI. Chi- square tests were used to test the differences in categorical variables between ethnic groups. Comparisons among ethnic groups were made using Prevalence Ratios (PRs) with sleep duration categories as independent variables and cardiovascular risk factors as outcomes, with adjustment for potential confounders (age, gender) and possible mediators (education, marital status, BMI, smoking, alcohol consumption, physical activity). For all outcome variables, interaction between ethnicity and sleep duration was tested. All analyses were performed using STATA 11.0 (Stata Corp, Station, 4 TX). A p-value of <0.05 was considered as statistically significant.

RESULTS

Characteristics of the study population

Table 1 shows the characteristics of the study population by ethnic group. Moroccans and Turks were younger, had lower educational levels, consume less alcohol, less often achieved the physical activity norm, and had lower prevalence of hypertension compared to Dutch and other ethnic origin groups. South-Asian Surinamese, African Surinamese, and Ghanaian participants had a lower mean sleep duration and higher prevalence of short sleep than Dutch, Turks and Moroccans. Dutch and South-Asian Surinamese were less obese than other ethnic groups. The prevalence of diabetes was higher in all ethnic minority groups while lipid profile was mostly favourable for the ethnic minority groups as compared with Dutch.

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Interaction between ethnicity and sleep duration

A statistically significant interaction was observed between ethnicity and sleep duration for obesity in South-Asian Surinamese (p= 0.033), Ghanaians (p= 0.002), Turks (p= 0.030) and Moroccan (p= 0.008); as well as for hypertension in Ghanaians (p= 0.049) No statistically significant interaction was found between sleep duration and other CVD risk factors by ethnic background.

Sleep duration and obesity

Figure 1 (first part) shows the relationship between sleep duration and the prevalence of obesity by ethnic group. The prevalence of obesity was consistently higher in those reporting short sleep duration, with this association being statistically significant in people of Dutch origin, and South-Asian Surinamese, African Surinamese, and Turks. The significant association persisted after adjustment for covariates.

Sleep duration and diabetes

Also the prevalence of diabetes was consistently higher in those reporting short sleep duration (middle part of Figure 1). Table 2 shows that short sleep was significantly related to diabetes in three ethnic minority groups: African Surinamese, Turks, and Moroccan participants, after adjustment for age and sex. The significant associations persisted after adjustment for all covariates.

Sleep duration and hypertension

Figure 1 (last part) shows the relationship between sleep duration and prevalence of hypertension by ethnic group. It shows that the prevalence of hypertension was consistently higher in those reporting short sleep duration. After adjustment for age and gender, there was a significant positive relationship between short sleep and hypertension in Dutch and Turks only (Table 2). After further adjustment for education, marital status, BMI, smoking, alcohol consumption and physical activity, the observed significant association in Dutch disappeared but remained in Turks.

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Sleep duration and dyslipidaemia

Figures 2 show the relationship between sleep duration and lipid levels by ethnic group. In general, lipid levels did not vary much by sleep duration. A significant positive association of short sleep with high total cholesterol in Moroccans was observed, with low HDL cholesterol in South-Asian Surinamese, and with high triglycerides in South-Asian Surinamese, after adjusting for age and gender (Table 2). These observed associations persisted after adjustment for other factors.

Anujuo_binnenwerk_FINAL.indd 81 30/07/2018 21:19 Chapter 4 n = 2202 Moroccan 50.4 (48.3-52.5) 16.2 (14.8-17.9) 7.2 (7.1, 7.2) 33.3 (31.3-35.3) 26.9 (25.1-28.8) 40.2 (39.6-40.7) 24.9 (23.1-26.7) 11.4 (10.1-12.7) 11.4 30.1 (28.2-32.0) 5.05 (4.13-5.96) 17.8 (16.2-19.4) 6.09 (5.09-7.09) 9.46 (8.24-10.7) n = 2242 Turks 52.0 (49.9-54.1) 13.8 (12.3-15.2) 7.1 (7.0, 7.2) 34.2 (32.3-36.2) 28.7 (26.9-30.6) 40.4 (39.9-40.9) 30.3 (28.4-32.2) 10.5 (9.24-11.8) 36.1 (34.1-38.1) 8.8(7.58-9.92) 27.4 (25.5-29.2) 9.9 (8.63-11.1) 20.8 (19.1-22.4) n = 1795 Ghanaian 63.6 (61.4-65.9) 6.27 (5.14-7.39) 6.8 (6.7, 6.8) 30.1 (27.9-32.2) 43.2 (40.9-45.5) 45.0 (44.5-45.5) 57.8 (55.5-60.1) 11.9 (11.4-13.4) 11.9 33.3 (31.1-35.5) 10.8 (9.38-12.3) 6.80 (5.64-7.97) 10.9 (9.48-12.4) 3.4 (2.56-4.24) n = 2158 African Surinamese 69.8 (67.9-71.8) 23.4 (21.6-25.2) 6.7 (6.5, 6.7) 6.81 (5.74-7.88) 44.6 (42.5-46.7) 47.4 (46.9-47.9) 50.6 (48.5-52.7) 12.0 (10.7-13.4) 29.9 (28.1-31.9) 9.9 (8.62-11.1) 11.1 (9.76-12.4) 11.1 10.0 (8.70-11.2) 6.1 (5.11-7.13) n = 2262 62.2 (60.2- 64.2) South-Asian Surinamese 21.8 (20.0- 23.5) 6.9 (6.7, 6.9) 16.1 (14.6- 17.6) 38.5 (36.5-40.5) 45.9 (45.4-46.5) 43.8 (41.8-45.9) 19.7 (18.1-21.4) 19.3 (17.7-20.9) 12.2 (10.9-13.6) 21.8 (20.1-23.5) 14.5 (13.1-15.9) 16.9 (15.4-18.5) n = 2146 36.7 (34.6- 38.7) 60.4 (58.3- 62.4) Dutch 7.3 (7.2, 7.3) 3.00 (2.27- 3.72) 15.6 (14.1-17.2) 46.3 (45.8-46.9) 30.5 (28.6-32.5) 3.6 (2.77-4.35) 9.8 (8.53-11.1) 16.8 (15.2-18.4) 8.90 (7.69-10.1) 14.9 (13.5-16.5) 12.5 (11.1-13.8)

category (%) nd Characteristics of the study population by ethnicity category (%) category (%) rd th Sleep duration (h) 4 Short sleep (% yes) 3 Age Hypertension (% yes) Diabetes (% yes) Obese (% yes) Cholesterol (Total) Cholesterol (Total) >6.22mmol/l HDL cholesterol HDL <1.04 mmol/L LDL cholesterol LDL >4.14mmol/L Triglyceride (TG) Triglyceride >1.69 mmol/L Education 1st and 2 Table 1: Table

Anujuo_binnenwerk_FINAL.indd 82 30/07/2018 21:19 Association of sleep with CVD risk factors in adults n = 2202 Moroccan 57.9 (55.8-59.9) 2.36 (1.73-2.99) 27.2 (25.3-29.0) 10.4 (9.08-11.6) 1.77 (1.22-2.32) 74.1 (72.3-75.9) 12.5 (11.1-13.9) 13.3 (11.8-14.7) 47.6 (45.5-49.7) 7.56 (6.45-8.66) n = 2242 Turks 63.4 (61.4-65.4) 3.61 (2.84-4.39) 19.9 (18.3-22.6) 9.95 (8.71-11.2) 2.72 (2.05-3.39) 47.2 (45.1-49.3) 18.6 (16.9-20.2) 33.9 (31.9-35.9) 42.2 (40.2-44.3) 21.9 (20.2-23.6) n = 1795 Ghanaian 16.9 (15.2-18.6) 17.8 (16.1-19.6) 32.6 (30.4-34.8) 30.4 (28.2-32.5) 0.89 (0.46-1.33) 86.2 (84.6-87.8) 8.69 (7.39-9.99) 4.74 (3.75-5.72) 53.9 (51.7-56.3) 49.4 (47.0-51.7) 4 n = 2158 African Surinamese 19.0 (17.3-20.7) 10.6 (9.31-11.9) 52.6 (50.5-54.8) 15.4 (13.9-16.9) 1.48 (0.97-1.99) 49.8 (47.7-51.9) 19.5 (17.8-21.1) 30.5 (28.6-32.4) 57.8 (55.7-59.9) 67.1 (65.1-69.1) n = 2262 South-Asian Surinamese 35.5 (33.6-37.5) 10.0 (8.79-11.3) 30.9 (29.0-32.9) 19.7 (18.0-21.3) 3.40 (2.66-4.15) 58.0 (55.9-60.0) 13.8 (12.4-15.2) 28.0 (26.2-29.9) 52.9 (50.8-54.9) 56.3 (54.2-58.3) n = 2146 Dutch 37.9 (35.9-40.0) 18.3 (16.7-19.9) 32.9 (30.9-34.9) 8.76 (7.56-9.96) 1.82 (1.25-2.38) 36.4 (34.4-38.4) 38.0 (35.9-40.1) 25.4 (23.6-27.2) 75.1 (73.2-76.9) 91.8 (90.7-92.9) Marital status Married (% yes) Living together (% yes) Single (% yes) Divorced (% yes) Widowed (% yes ) Smoking status Never smoked (% yes) Ex-smoker (% yes) Current smoker (% yes) Physical activity (% yes) Alcohol intake (% yes) Table 1 - continued Table Data are presented as mean and percentages with 95% CI

Anujuo_binnenwerk_FINAL.indd 83 30/07/2018 21:19 Chapter 4 Hypertension Diabetes Obesity Association between sleep duration and obesity, diabetes, and hypertension among ethnic groups in Amsterdam diabetes, and hypertension among ethnic groups in Association between sleep duration and obesity, Fig. 1:

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HDL Cholesterol HDL 4 LDL Cholesterol LDL High Cholesterol Association between sleep duration and dyslipidaemia among ethnic groups in Amsterdam Association between sleep duration and dyslipidaemia among ethnic groups in Fig. 2:

Anujuo_binnenwerk_FINAL.indd 85 30/07/2018 21:19 Chapter 4 1.53 (1.03-2.27)** 1.55 (1.04-2.29)** 1.57 (1.06-2.33)** 0.93 (0.80-1.08) 0.94 (0.81-1.09) 0.94 (0.81-1.09) 1.30 (1.03-1.64)** 1.29 (1.02-1.63)** 1.27 (1.01-1.59)** 1.10 (0.97-1.26) 1.10 (0.97-1.26) PR (95%CI) Moroccan n = 2202 1.09 (0.96-1.24) 0.96 (0.71-1.29) 0.95 (0.70-1.28) 0.95 (0.71-1.27) 1.17 (1.03-1.32)** 1.21 (1.07-1.37)** 1.21 (1.07-1.37)** 1.47 (1.16-1.87)** 1.59 (1.26-2.02)* 1.63 (1.28-2.07)* 1.14 (1.03-1.29)** 1.16 (1.04-1.29)** PR (95%CI) Turks Turks n = 2242 1.17 (1.05-1.31)** 0.89 (0.67-1.19) 0.89 (0.66-1.18) 0.92 (0.69-1.22) 0.98 (0.91-1.06) 0.98 (0.91-1.06) 0.98 (0.90-1.05) 1.00 (0.76-1.32) 0.99 (0.75-1.29) 1.04 (0.79-1.35) 1.05 (0.92-1.21) 1.04 (0.91-1.19) PR (95%CI) Ghanaian n = 1795 1.05 (0.92-1.20)

0.84 (0.64-1.09) 0.83 (0.63-1.08) 0.83 (0.64-1.08) 1.03 (0.96-1.12) 1.06 (0.98-1.15) 1.06 (0.98-1.15) 1.37 (1.09-1.74)** 1.45 (1.14-1.84)** 1.46 (1.15-1.85)** 1.25 (1.11-1.44)** 1.25 (1.09-1.43)** PR (95%CI) African Surinamese n = 2158 1.26 (1.10-1.43)** 0.91 (0.71-1.16) 0.88 (0.69-1.12) 0.89 (0.70-1.12) 1.03 (0.95-1.13) 1.06 (0.98-1.16) 1.06 (0.97-1.15) 0.98 (0.84-1.17) 1.02 (0.86-1.21) 1.01 (0.85-1.18) 1.20 (1.01-1.43)** 1.21 (1.01-1.44)** PR (95%CI) 1.19 (0.99-1.42) South-Asian 2262 = Surinamese n 0.93 (0.73-1.19) 0.97 (0.76-1.23) 0.97 (0.76-1.23) 1.08 (0.95-1.25) 1.15 (1.00-1.33)** 1.19 (1.04-1.37)** 1.05 (0.63-1.73) 1.18 (0.70-1.99) 1.31 (0.78-2.19) 1.41 (1.04-1.89)** 1.45 (1.07-1.95)** PR (95%CI) 1.53 (1.14-2.06)** Dutch n = 2146 Prevalence ratio(s) for the relationship between sleep duration (short vs normal sleep) and cardiovascular risk factors by ethnicity Model 3 Model 2 Raised Total Raised Total cholesterol Model 1 Model 3 Model 2 Hypertension Model 1 Model 3 Model 2 Diabetes Model 1 #Model 3 Model 2 Obesity Model 1 Table 2: Table

Anujuo_binnenwerk_FINAL.indd 86 30/07/2018 21:19 Association of sleep with CVD risk factors in adults 0.84 (0.63-1.12) 0.85 (0.64-1.15) 0.83 (0.62-1.11) 1.08 (0.75-1.54) 1.09 (0.76-1.57) 1.08 (0.75-1.56) 0.87 (0.71-1.05) 0.89 (0.73-1.09) PR (95%CI) Moroccan n = 2202 1.89 (0.73-1.09) 1.00 (0.84-1.19) 1.07 (0.90-1.28) 1.05 (0.89-1.25) 0.97 (0.74-1.29) 0.98 (0.74-1.29) 0.97 (0.74-1.28) 1.04 (0.91-1.19) 1.09 (0.95-1.26) PR (95%CI) Turks Turks n = 2242 1.09 (0.95-1.26) 0.96 (0.58-1.57) 0.94 (0.57-1.54) 0.87 (0.53-1.41) 0.75 (0.56-0.99)** 0.72 (0.55-0.96)** 0.75 (0.57-0.99)** 1.19 (0.83-1.71) 1.16 (0.79-1.67) PR (95%CI) Ghanaian n = 1795 1.10 (0.77-1.58)

4 . 0.81 (0.58-1.14) 0.85 (0.61-1.19) 0.85 (0.60-1.18) 0.79 (0.60-1.04) 0.83 (0.63-1.09) 0.83 (0.63-1.08) 0.91 (0.72-1.17) 0.98 (0.77-1.26) PR (95%CI) African Surinamese n = 2158 0.99 (0.78-1.27)

1.49 (1.24-1.81)* 1.58 (1.31-1.91)* 1.57 (1.30-1.89)* 0.90 (0.73-1.12) 0.90 (0.73-1.12) 0.90 (0.73-1.12) 1.29 (1.11-1.51)** 1.41 (1.21-1.65)* PR (95%CI) 1.40 (1.20-1.64)* South-Asian 2262 = Surinamese n 0.95 (0.72-1.25) 1.06 (0.80-1.40) 1.12 (0.84-1.48) 0.91 (0.69-1.19) 0.96 (0.73-1.25) 0.95 (0.73-1.23) 1.10 (0.79-1.55) 1.19 (0.85-1.68) PR (95%CI) 1.27 (0.91-1.79) Dutch n = 2146 Model 3 Model 2 Raised Triglyceride Model 1 Model 3 Model 2 Raised LDL Raised LDL cholesterol Model 1 Model 3 Model 2 Reduced HDL Reduced HDL cholesterol Model 1 Table 2 - continued Table Model 1: adjusted for Age and sex, model 2: 1 plus education marital status, 3: 2 BMI, smoking, alcohol Model 1: adjusted for physical inactivity (*: p < 0.001, **: 0.05) #Obesity model 3: 2 plus smoking, alcohol and physical inactivity

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4. DISCUSSION

Key finding

This study investigated whether there are differences in the association between short sleep duration and CVD risk factors across various ethnic minority groups living in the Netherlands. The result of this study demonstrated that sleep duration was association with CVD risk factors, but the association varies between ethnic groups and depend on CVD risk factor being considered. Short sleep was significantly associated with obesity and diabetes in most ethnic groups. By contrast, the associations between short sleep and hypertension and lipid levels were absent in most ethnic groups with the exception of association with hypertension in Dutch and Turks, reduced HDL cholesterol and triglyceride in South-Asian Surinamese, and raised total cholesterol in Moroccans. Additional adjustment for SES and lifestyle factors did not substantially change the observed associations.

Discussion of key findings

Previous studies have shown that short sleep was related to poor health outcomes, and the results of this study partly support this finding [40]. This study showed that short sleep was significantly associated with higher prevalence of some CVD risk factors in some ethnic minority groups, but this was not consistent for each risk factor or each ethnic group. The association between short sleep and CVD risk factors was more consistent for obesity and diabetes. This supports the biological mechanism linking short sleep and obesity and diabetes, as has been proposed in several studies [41-52]. For instance, short sleep has been associated with altered metabolic hormones (leptin and ghrelin) [41 - 43], energy balance [44, 45], time available to eat [44], timing of meals [46, 47], and increased intake of high-calorie foods [46-49] which could eventually induce obesity. It has been proposed that reduced sleep may lead to a reduction in brain glucose utilization, increase in growth hormone, elevation in evening cortisol concentrations and sympathetic nervous activity. These mechanisms may give rise to diabetes. There was no significant association (except in few ethnic groups) for other risk factors (hypertension and lipids). This seems to suggest that apart from known proposed biological mechanisms linking short sleep and hypertension and lipids, [15, 53-57], a different unidentified or non-biological mechanism may be involved.

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Although these mechanisms might drive the association between short sleep and obesity/diabetes, the association between short sleep and obesity/ diabetes are rather consistent across groups, though in some groups, there were no associations. The authors` finding is partly similar to a recent study that found ethnic-specific associations between self-reported sleep and cardiometabolic risk factors in various ethnic groups in the USA [22]. The reason for this observation is not fully understood, but may be partly related to differences in lifestyle factors and eating behaviour, particularly during the awake period, which may differ between ethnic groups, and may alter the association between short sleep and CVD risk factors. Ethnic differences may also be due to the quality of sleep during the remaining short sleep time. So, if there is no interruption of sleep during the short sleep time, and therefore a better sleep quality, this may also influence CVD risk factors. Unfortunately, data on sleep quality are not available in this study.

No significant association between short sleep and CVD risk factors in Ghanaians was observed. The lack of association between short sleep and CVD risk factors among Ghanaian is surprising, given that the prevalence 4 of short sleep is much higher in this group compared to the other groups. Smoking prevalence is indeed lower among Ghanaians, and therefore might be protective from increased CVD risk. However, smoking prevalence was lower in both short (5.7%) and normal sleep (3.7%) Ghanaian groups, and therefore could not explain the lack of association with CVD risk factors. Furthermore, if smoking was categorised into: Heavy smokers (15 or more cigarettes per day, light smokers (1-14 cigarettes per day), ex-smokers and never smokers were included in the model, the result remains essentially the same. Another reason for the lack of association between short sleep and CVD risk in the Ghanaian group may partly be attributed to various coping strategies employed by Ghanaians to forestall the manifestation of CVD risk factors even though they were short sleepers. It could be that the Ghanaians used adaptive coping strategies positively to better their health. Previous studies have shown that stress, which can increase prevalence of short sleep among ethnic groups [57-58], may or may not predispose to CVD risk factors depending on how the affected individuals cope with the stress to which they are exposed [59]. It has been documented that Ghanaians were able to cope with challenges related to migration stress and acculturation in a flexible way and were able to maintain health [60], thus, this may further explain why we did not found significant association between short sleep and CVD risk factors in Ghanaians. Further study is needed to examine to what extent coping strategies can influence or mediate

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the association between sleep duration and CVD risk factors among various ethnic minority groups.

The strength of this study lies in the large sample sizes, hence a more reliable estimations. In addition, investigation was conducted on multiple ethnic groups living together in one city in a similar manner. A limitation of the study is that only self-reported data on sleep were used, which is subject to recall bias; hence the participants may have under -or over- reported short sleep durations. However, because of such large numbers used in this study, this will probably level out. Being a cross-sectional study, causal associations between short sleep and CVD risk factors could not be established, although important associations of short sleep and CVD risk factors were observed in some ethnic groups. In addition, information on daytime sleeping which may affect sleep duration was lacking. The authors were unable to stratify the analysis by sex, or include very short sleep as a category because of small numbers.

In conclusion, the results of this study demonstrated that short sleep was significantly associated with obesity and diabetes in most ethnic groups. By contrast, the associations between short sleep and hypertension and dyslipidaemia were absent in most ethnic groups. SES and lifestyle factors contributed little to the observed association. This finding highlights that the potential factors linking short sleep and CVD risk factors and coping strategies may vary between ethnic groups. Future studies should examine the factors contributing to the different associations between short sleep and CVD risk factors among ethnic groups.

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