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Body Adiposity Index Is Worse Than Body Mass Index When Eval ISSN: 2469-5858 Fogal et al. J Geriatr Med Gerontol 2017, 3:035 DOI: 10.23937/2469-5858/1510035 Volume 3 | Issue 4 Journal of Open Access Geriatric Medicine and Gerontology RESEARCH ARTICLE Body Adiposity Index is Worse than Body Mass Index when Eval- uating the Factors Associated with Adiposity in Elderly People Aline Siqueira Fogal, Sylvia do Carmo Castro Franceschini, Giana Zarbato Longo and Andréia Queiroz Ribeiro* Departamento de Nutrição, Universidade Federal de Viçosa, Viçosa, Brazil *Corresponding authors: Andréia Queiroz Ribeiro, Professor Adjunto IV, Departamento de Nutrição e Check for Saúde, Universidade Federal de Viçosa, Brazil, E-mail: [email protected] updates Abstract Introduction Background: Body Mass Index (BMI) is an easily measurable In the elderly, obesity is associated with accelerated indicator of body fat and with low cost. However, as an indicator loss of cognitive function, frailty and functional disabil- of risk of development of chronic diseases in the elderly, it has ity and premature death from Cardiovascular Disease limitations, as it does not reflect mainly the regional distribution of fat that occurs with the aging process. As an alternative to (CVD), diabetes, cancer and musculoskeletal diseas- BMI, the Body Adiposity Index (BAI) has been proposed. This es and other chronic non-communicable diseases [1]. index showed a high correlation with the measurement of body These diseases affect both quality of life and longevity fat in adults indicating that it could replace BMI. However, BAI and generate high costs to health systems. is still understudied in the elderly. Due to the accelerated process of population aging Objective: To determine factors associated with adiposity in elderly people, according to sex and in accordance with two in the world and the concomitant increase in the prev- anthropometric indices, Body Mass Index (BMI) and Body Ad- alence of overweight and obesity, it is necessary to in- iposity Index (BAI). vestigate factors that determine or are associated with Methods: We used cross-sectional data from 532 participants increased weight in order to implement interventions (261 women, aged 60 to 94 years) who were randomly recruit- more effective in the treatment/prevention of this con- ed from Viçosa, Minas Gerais, and Brazil. Adiposity was defined dition [2]. using Body Mass Index (weight (kg)/height (m)2) and Body Adi- posity Index (hip circumference (cm)/height (m)1.5) - 18). The as- The World Health Organization (WHO) recommend- sociations between the two indexes (BMI and BAI) and factors ed BMI as is an easily measurable indicator of body fat associated with adiposity (socio-demographic variables, lifestyle and with low cost [3]. The index is highly correlated with characteristics, health status, waist circumference and functional capacity) were explored using linear regression. measures of total body fat in adults of both sexes, as well as other anthropometric indexes of subcutaneous Results: In men, with the exception of age and alcohol, the variables associated with BMI were also associated with the and abdominal fat. However, as an indicator of risk of BAI. In women, we observed that the same variables were as- development of chronic diseases in the elderly, it has sociated with BMI and BAI. However, the coefficient of deter- limitations, as it does not reflect mainly the regional dis- mination of the final models of multiple linear regressions was tribution of fat that occurs with the aging process. As an higher for BMI. alternative to BMI, the Body Adiposity Index (BAI) has Conclusion: The BAI was worse than BMI when evaluated been proposed [4]. the factors associated with adiposity in elderly people. As an alternative, has been proposed the Body Adi- Keywords posity Index (BAI) based on height and hip circumference Body mass index, Body adiposity index, Adiposity, Aged (BAI = (hip circumference (cm)/height (m) 1.5) - 18). This Citation: Fogal AS, Franceschini SCC, Longo GZ, Ribeiro AQ (2017) Body Adiposity Index is Worse than Body Mass Index when Evaluating the Factors Associated with Adiposity in Elderly People. J Geriatr Med Gerontol 3:035. doi.org/10.23937/2469-5858/1510035 Received: April 07, 2017: Accepted: October 28, 2017: Published: October 30, 2017 Copyright: © 2017 Fogal AS, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Fogal et al. J Geriatr Med Gerontol 2017, 3:035 • Page 1 of 8 • DOI: 10.23937/2469-5858/1510035 ISSN: 2469-5858 index showed a high correlation with the measurement Study variables of body fat in adults by Dual-energy X-ray Absorptiome- The dependents variables of this study were adi- try (DXA) in African Americans and Mexican Americans posity measured by the Body Mass Index (BMI) and the [5], indicating that it could replace BMI. Body Adiposity Index (BAI). However, studies carried out in populations with The independent variables were: age (years and age different ethnic groups consistently reveal that the BAI range), sex (male and female), education (never studied; tends to overestimate fatness in individuals with a low- studied until the early elementary grades; final grades er percentage of body fat and underestimate body fat in of elementary school or more), individual income (quar- those with higher adiposity [6-8]. Furthermore, BAI has tiles), co-habitation (live alone and do not live alone), better ability to predict body fat in the elderly compared practice of physical activities (yes or no), smoking (no to BMI only when data are not stratified by gender [6]. history of smoking; former smoker; current smoker), al- Nevertheless, little is known about the best indirect cohol consumption (yes, no and ex-alcoholic), functional measures to predict factors associated with adiposity in capacity (adequate or inadequate), waist circumference populations, especially in the elderly [9,10]. (changed and unchanged) and self-reported morbidities Therefore, the purpose of this study was to deter- (diabetes, hypertension, dyslipidemia and musculoskel- mine the factors associated with adiposity in the el- etal disorders). derly, stratified by sex, using as outcome the adiposity Data collection assessed according to two anthropometric indices, BMI and BAI. A trained team interviewed the elderly in their own Methods homes, under the supervision of the study investigators. The interview included a semi-structured questionnaire. If Experimental design, target population and sample the elderly reported difficulty in reporting the information requested, the caregiver was asked to answer. This is a population-based, cross-sectional study, conducted utilizing a random sample of the elderly, liv- We obtained income from the sum of the individu- ing in Viçosa, Brazil. al yields of each elderly respondent considering retire- ment, pension or any other income and divided into The target population for this study consisted of elderly quartiles. people aged 60 years or older, living in urban and rural Vi- cosa (MG). This group was surveyed during ‘‘The National The following anthropometric measurements were Campaign for Elderly Vaccination’’ from April to May 2008. obtained using the standard procedures [12]. Weight With the aim of identifying non-participants in the vaccina- was measured on portable scale (digital electronic) with tion campaign, the campaign’s database was merged with a capacity of 199.95 kg and 50 gram accuracy (model LC 200 pp, Marte Scales and Precision Instruments Ltd., other databases, namely: Database of the Viçosa’s, Federal Brazil). Height was measured using a portable stadi- University employees, active and retired, the registers of ometer, with a maximum calibration of 2.13 m to the the municipality’s health services, such as Elderly Health nearest 0.1 mm (brand Altura Exata, Brazil). Hip circum- Program (PSF), Physiotherapy service, the Center of Wom- ference was measured at the most prominent gluteal en’s Health, Psychosocial Services, Care Unit, Hiperdia and region. the Polyclinic. This merged data aimed to identify older people who had not participated in the 2008 vaccination We calculate Body Mass Index (BMI) and the Body campaign to complement the database. After combination Adiposity Index (BAI) as (hip circumference (cm)/height 1.5 of these lists, 7980 people aged 60 and over were identi- (m) ) - 18. fied and this number formed the basis for obtaining the Individuals who did not have data regarding height, sample. We excluded institutionalized elderly from the weight, and hip circumference (n = 75) were excluded sample. from the sample. Outliers with BAI greater than 50.0 (n = 14) were also excluded after analysis using the box The sample size calculation was performed consid- plot chart. ering the reference population of 7980 elderly, confi- dence level of 95% and estimated prevalence of the out- Data analysis come of 50%, 4.0% of variability and 20% of losses for The dependent variables were tested for normality the initial sample of 670 elderly, selected by the simple using the Shapiro-Wilk test and as they had no normal random sampling method. This loss was incurred due to distribution they were log-transformed. refusal (3.6%), address not being located (1.2%), death (1.3%), change of address (1.2%) and inability to direct- A descriptive analysis of the data was performed. ly measure the height (10.4%). Thus, 621 elderly were Later, the student’s t test was applied and the analysis actually assessed. Further details regarding the meth- of variance was complemented with Bonferroni test to odology of the project can be obtained in Nascimento, determine the effect of each independent variable on et al. [11]. BMI and BAI. Fogal et al. J Geriatr Med Gerontol 2017, 3:035 • Page 2 of 8 • ISSN: 2469-5858 DOI: Table 1: Distribution of Body Mass Index and Body Adiposity Index, according to sociodemographic, behavioral and health variables, Viçosa, 2009.
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