Factors associated with BMI, underweight, overweight, and obesity among adults in a population of rural south India: a cross-sectional study

Abstract

BackgroundOverweight, obesity, and related chronic diseases are becoming serious public health concerns in rural areas of India. Compounded with the existing issue of underweight, such concerns expose the double burden of disease and may put stress on rural healthcare. The purpose of this article was to present the prevalence and factors associated with underweight, overweight, and obesity in an area of rural south India.MethodsDuring 2013 and 2014, a random sample of adults aged 20–80 years were selected for participation in a cross-sectional study that collected information on diet (using a food frequency questionnaire), physical activity (using the Global Physical Activity Questionnaire), socioeconomic position (using a wealth index), rurality (using the MSU rurality index), education, and a variety of descriptive factors. BMI was measured using standard techniques. Using a multivariate linear regression analysis and multivariate logistic regression analyses, we examined associations between BMI, overweight, obesity, and underweight, and all potential risk factors included in the survey.ResultsAge and sex-adjusted prevalence of overweight, obesity class I, and obesity class II were 14.9, 16.1, and 3.3 % respectively. Prevalence of underweight was 22.7 %. The following variables were associated with higher BMI and/or increased odds of overweight, obesity class I, and/or obesity class II: Low physical activity, high wealth index, no livestock, low animal fat consumption, high n-6 polyunsaturated fat consumption, television ownership, time spent watching television, low rurality index, and high caste. The following variables were associated with increased odds of underweight: low wealth index, high rurality index, and low intake of n-6 PUFAs.ConclusionUnderweight, overweight, and obesity are prevalent in rural regions of southern India, indicating a village-level dual burden. A variety of variables are associated with these conditions, including physical activity, socioeconomic position, rurality, television use, and diet. To address the both underweight and obesity, policymakers must simultaneously focus on encouraging positive behaviour through education and addressing society-level risk factors that inhibit individuals from achieving optimal health.

Gender differences in sociodemographic and behavioural factors associated with BMI in an adult population in rural Burkina Faso – an AWI-Gen sub-study

“…Despite the controversy regarding the use of BMI [4–7] to predict disease, BMI remains the most commonly used marker of whole body obesity. By 2014, it was estimated that approximately a billion adults were overweight and that 600 million were obese worldwide [8]. Within SSA, the prevalence of obesity has been increasing over the past 30 years with regional disparities [9].…”

Longitudinal changes and predictors of adolescents enjoyment in physical education

“…As seen in Tables 4 to 6, gender, VO2peak, overweightedness and physical activity level were not predictors of enjoyment in PE, when the effects of the other possible predictors were controlled for. The absence of such group differences in enjoyment among others are surprising, in a positive way, especially because previous research indicate such differences (Biddle et al, 2011;Bjerke et al, 2016;Flagestad, 1996;Flagestad and Skisland, 2002;Kjønniksen et al, 2009;Larsson and Redelius, 2008;Latty et al, 2007;Little et al,, 2016;Säfvenbom et al, 2014;Wabakken, 2010). As earlier pointed out, the fostering of an autonomy supportive environment by PE teachers in high school may help explain the lack of group differences at high school.…”

Body Mass Index and Associated Factors of Obesity and Underweight in a General Out-patient Population in a Tertiary Hospital in Nigeria

“…[13,16] Factors associated with obesity included: sex, leisure-time, physical exercise, (and educational level appear to influence obesity) low physical activity, high wealth index, no livestock, low animal fat consumption, high n-6 polyunsaturated fat consumption, television ownership, time spent watching television, low rurality index, high caste, older age, rural living, current smoking, lower systolic pressure, urbanization, higher systolic pressure, and diabetes. [10,13,17,18] On the other hand, studies have shown that underweight was associated with low wealth index, high rurality index, low intake of n-6 PUFAs and less urbanization. [10,18] There is a paucity of studies on the associated factors of underweight, overweight and obesity in the general out patients in Nigeria.…”

“…[10,13,17,18] On the other hand, studies have shown that underweight was associated with low wealth index, high rurality index, low intake of n-6 PUFAs and less urbanization. [10,18] There is a paucity of studies on the associated factors of underweight, overweight and obesity in the general out patients in Nigeria. This has prompted us to evaluate BMI and the factors which might be associated with underweight and obesity in this group of people.…”

“…[7,8,9] Under-nutrition is high among rural dwellers in developing countries. [10] The prevalence of overweight was 62% and obesity 26% for both sexes in the World Health Organization (WHO) region of the Americas, compared to overweight of 14% and obesity 3% in South East Asia. [11] In Nigeria, the prevalence of overweight ranged from 20.3% -35/1% and obesity 8.1% -22.3% in adults.…”