Social epidemiology of excess weight and central adiposity in older Indians: analysis of Study on global AGEing and adult health (SAGE)

Socio-demographic and behavioral correlates of excess weight and its health consequences among older adults in India: Evidence from a cross-sectional study, 2017-18

BACKGROUND

Rapid population aging is expected to become one of the major demographic transitions in the twenty-first century due to the continued decline in fertility and rise in life expectancy. Such a rise in the aged population is associated with increasing non-communicable diseases. India has suffered from obesity epidemic, with morbid obesity affecting 5% of the population and continuing an upward trend in other developing countries. This study estimates the prevalence of excess weight among older adults in India, and examines the socio-demographic and behavioral factors and its health consequences.

METHODS

The study used data from the Longitudinal Ageing Study in India (LASI) wave 1 (2017-18). A total sample of 25,952 older adults (≥ 60 years) was selected for the study. Descriptive statistics, bivariate Chi-Square test, and logistic regression models were applied to accomplish the study objectives. Body mass index (BMI) has been computed for the study according to the classification of the World Health Organization, and "excess weight" refers to a score of BMI ≥ 25.0 kg/m2.

RESULTS

Overall, 23% of older adults (≥ 60 years) were estimated with excess weight in India, which was higher among women irrespective of socioeconomic and health conditions. The higher levels of excess weight (than the national average of ≥22.7%) were observed among older adults in states like Haryana, Tamil Nadu, Telangana, Maharashtra, Gujarat, Manipur, Goa, Kerala, Karnataka, Himachal Pradesh, Punjab, Sikkim and some other states. After adjusting for selected covariates, the odds of excess weight were higher among females than males [OR: 2.21, 95% CI: 1.89, 2.60]. Similarly, the likelihood of excess weight was 2.18 times higher among older adults who were living in urban areas compared to their rural counterparts [OR: 2.18; 95% CI: 1.90, 2.49]. Higher level of education is significantly positively correlated with excess weight. Similarly, higher household wealth index was significantly positively correlated with excess weight [OR: 1.98, CI: 1.62, 2.41]. Having hypertension, diabetes and heart diseases were associated with excess weight among older adults. Regional variations were also observed in the prevalence of excess weight among older adults.

CONCLUSION

The findings suggest that introducing measures that help to reduce the risk of non-communicable diseases, and campaigns to encourage physical activity, and community awareness may help reduce the high burden of excess weight and obesity among older Indians. The findings are important for identifying the at-risk sub-populations and for the better functioning of any public health programme and suitable intervention techniques to lower the prevalence and risk factors for excess weight in later life.

Association between socioeconomic positions and overweight/obesity in rural Nepal

Introduction

Obesity and its association with socioeconomic factors are well-established. However, the gradient of this relationship among rural populations in low- and middle-income countries such as Nepal is not fully understood. We sought to assess the association of socioeconomic factors (education, income, and employment status) with overweight/obesity.

Methods

This cross-sectional study analyzed data from 260 participants aged ≥18 years and attending a rural health center in Dolakha, Nepal. Self-reported data on demographic, socioeconomic, and lifestyle factors was collected, and weight and height were measured for all the study participants. Those with a body mass index of <25 kg/m2 were regarded as non-overweight/obese and those with ≥25 kg/m2 were regarded as overweight/obese. Poisson regression models were used to estimate prevalence ratios and corresponding 95% confidence intervals to assess the association between socioeconomic factors and overweight/obesity. In addition, we assessed the effect of modification by age and gender to study the effect of socioeconomic factors on overweight/obesity.

Results

The age-standardized prevalence of overweight/obesity was higher for individuals with higher education (23%) and high-income (32%) and those who were unemployed (42%). Compared to the low-income and no formal education groups, the prevalence ratio of overweight/ obesity was 1.69 and 2.27 times more for those belonging to the high-income and high school and above groups, respectively. No evidence of effect modification by gender and age was observed.

Conclusions

Socioeconomic factors, education, and income were positively associated with overweight/obesity prevalence in rural Nepal. Further large studies using longitudinal settings are necessary to replicate our findings.

Geriatric Conditions and Functional Disability among a National Community-Dwelling Sample of Older Adults in India in 2017-2018

This study aimed to determine the prevalence of geriatric conditions and their association with disability in older community-dwelling adults in India. The cross-sectional sample consisted of 31,477 individuals (≥60 years) from the Longitudinal Ageing Study in India (LASI) Wave 1 in 2017–2018. Geriatric conditions assessed included injurious falls, impaired cognition, underweight, dizziness, incontinence, impaired vision and impaired hearing. More than two in five participants (44.3%) had no geriatric condition, 32.7% had one, 15.9% two and 7.1% had three or more geriatric conditions; 26.9% were underweight, 14.5% dizziness, 13.7% had impaired vision, 9.6% impaired hearing, 9.3% impaired cognition, 8.2% major depressive disorder, 5.7% injurious falls, 4.0% incontinence, and 7.4% had Activity of Daily Living (ADL) dependencies. In logistic regression analysis, adjusted by sociodemographic factors and the number of chronic conditions, we found a higher number of geriatric conditions, and a higher number of chronic conditions were associated with ADL dependencies. In a model adjusted for sociodemographic factors and the type of chronic conditions, we found that a higher number of geriatric conditions and heart disease, stroke, and bone or joint disorder were positively associated with ADL dependencies. The odds of ADL dependencies increased with impaired cognition, impaired vision, impaired hearing, and major depressive disorder. Impaired cognition, incontinence, impaired vision and major depressive disorder were positively associated with dressing, bathing, eating, transferring, and toileting dependency. In addition, impaired hearing was associated with transferring and toileting dependency. More than half of older adults in India had at least one geriatric condition. The prevalence of geriatric conditions was as high as the prevalence of chronic conditions, which in some cases were associated with disability. Geriatric conditions should be included in health care management.

Obesity in midlife: lifestyle and dietary strategies

As the rate of obesity increases globally, so does the incidence of other non-communicable diseases such as diabetes, cardiovascular disease, cancer, osteoporosis, osteoarthritis, and dementia, which have been referred to as 'adiposity-based chronic disease'. With timely lifestyle modification such as behavioral changes, implementation of a healthy diet, and proper physical activity, many of these diseases can be prevented. Weight gain is one of the major health concerns of midlife. Midlife body changes are the result of aging, menopause, and other influences unique to menopausal women which interfere with adoption of a healthy lifestyle. Reduced metabolism levels lead to low energy levels, which discourage physical activity. In addition, with the onset of bone loss, menopausal women begin to lose muscle mass and gain more fat, resulting in osteopenic sarco-obesity. Adoption of a healthy lifestyle is a first-line option in the treatment for these midlife changes. Lifestyle medicine offers a broad set of network-based interventions, which need to be brought to the forefront in preventing and managing obesity at all stages. This review article focuses on evidence-based lifestyle changes and their benefits for reducing morbidity and mortality related to obesity and its complications prevalent at midlife and beyond.

Obesity in the geriatric population - a global health perspective

The obesity crisis has been a major concern for public health organizations worldwide, and affects the geriatric population in parallel to that of the general population. Though geriatric obesity has been recognized in developed countries, such trends have also extended into developing countries due to disproportionate consumption of energy-dense low-cost food and increasingly sedentary lifestyles. The consequences of geriatric obesity include impaired physical function, decreased quality of life, institutionalization and death. The aim is to describe the obesity epidemic in both developed and developing countries, as well as highlight current surveillance efforts to monitor geriatric obesity on a global scale such as the Study on Global Ageing and Adult Health (SAGE study), which evaluates epidemiology trends in six different countries (China, Ghana, India, Mexico, Russia and South Africa). The impact of obesity on health, disease and systems worldwide will be described, as well as projections of future trends of this disease.

Do trends in the prevalence of overweight by socio-economic position differ between India's most and least economically developed states?

Background

India’s economic development and urbanisation in recent decades has varied considerably between states. Attempts to assess how overweight (including obesity) varies by socioeconomic position at the national level may mask considerable sub-national heterogeneity. We examined the socioeconomic patterning of overweight among adults in India’s most and least economically developed states between 1998 and 2016.

Methods

We used state representative data from the National Family Health Surveys from 1998 to 99, 2005–06 and 2015–16. We estimated the prevalence of overweight by socioeconomic position in men (15–54 years) and women (15–49 years) from India’s most and least economically developed states using multilevel logistic regressions.

Results

We observed an increasing trend of overweight prevalence among low socioeconomic position women. Amongst high socioeconomic position women, overweight prevalence either increased to a smaller extent, remained the same or even declined between 1998 and 2016. This was particularly the case in urban areas of the most developed states, where in the main analysis, the prevalence of overweight increased from 19 to 33% among women from the lowest socioeconomic group between 1998 and 2016 compared to no change among women from the highest socioeconomic group. Between 2005 and 2016, the prevalence of overweight increased to similar extents among high and low socioeconomic status men, irrespective of residence.

Conclusions

The converging prevalence of overweight by socioeconomic position in India’s most developed states, particularly amongst urban women, implies that this subpopulation may be the first to exhibit a negative association between socioeconomic position and overweight in India. Programs aiming to reduce the increasing overweight trends may wish to focus on poorer women in India’s most developed states, amongst whom the increasing trend in prevalence has been considerable.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-7155-9) contains supplementary material, which is available to authorized users.

Independent urban effect on hypertension of older Indians: identification of a knowledge gap from a Study on Global AGEing and Health

Among older Indians, more cardiovascular diseases and risk factors are observed in the city dwellers than in the rural population. Clustering of socioeconomic privileges and consequent obesity in the Indian cities are known to underlie this phenomenon. But, it is unclear whether an independent urban effect exists on age-related ailments, unexplained by concentration of privileges and excess weight in the Indian cities. Hence, we aimed to estimate the independent urban effect on hypertension among older Indians after controlling for these factors. Nationally representative data of Indians aged 50 years and older (n = 7273) were collected by Study on global AGEing and health. Hypertension was defined as systolic and/or diastolic blood pressure >139 and > 89 mm Hg, respectively, and/or someone receiving antihypertensive medications. Permanent place of residence (urban/rural) during interview was recorded. Socioeconomic determinants included caste, occupation, assets, and education. Body mass index, abdominal circumference, smoking, alcohol, and physical activity were also controlled. The age- and sex-adjusted odds ratio of hypertension for urban residents was 1.64 (146-1.83), which partially attenuated to 1.22 (1.07-1.38) after controlling for all the covariates. This study highlights 22% excess odds of hypertension among the older Indian city dwellers, unexplained by the greater urban concentration of socioeconomic privileges and obesity. Future research should explore the constituents of this urban effect.

Trends in the socioeconomic patterning of overweight/obesity in India: a repeated cross-sectional study using nationally representative data

OBJECTIVES

We aimed to examine trends in prevalence of overweight/obesity among adults in India by socioeconomic position (SEP) between 1998 and 2016.

DESIGN

Repeated cross-sectional study using nationally representative data from India collected in 1998/1999, 2005/2006 and 2015/2016. Multilevel regressions were used to assess trends in prevalence of overweight/obesity by SEP.

SETTING

26, 29 and 36 Indian states or union territories, in 1998/99, 2005/2006 and 2015/2016, respectively.

PARTICIPANTS

628 795 ever-married women aged 15-49 years and 93 618 men aged 15-54 years.

PRIMARY OUTCOME MEASURE

Overweight/obesity defined by body mass index >24.99 kg/m².

RESULTS

Between 1998 and 2016, overweight/obesity prevalence increased among men and women in both urban and rural areas. In all periods, overweight/obesity prevalence was consistently highest among higher SEP individuals. In urban areas, overweight/obesity prevalence increased considerably over the study period among lower SEP adults. For instance, between 1998 and 2016, overweight/obesity prevalence increased from approximately 15%-32% among urban women with no education. Whereas the prevalence among urban men with higher education increased from 26% to 34% between 2005 and 2016, we did not observe any notable changes among high SEP urban women between 1998 and 2016. In rural areas, more similar increases in overweight/obesity prevalence were found among all individuals across the study period, irrespective of SEP. Among rural women with higher education, overweight/obesity increased from 16% to 25% between 1998 and 2016, while the prevalence among rural women with no education increased from 4% to 14%.

CONCLUSIONS

We identified some convergence of overweight/obesity prevalence across SEP in urban areas among both men and women, with fewer signs of convergence across SEP groups in rural areas. Efforts are therefore needed to slow the increasing trend of overweight/obesity among all Indians, as we found evidence suggesting it may no longer be considered a 'diseases of affluence'.

Socioeconomic patterns of underweight and its association with self-rated health, cognition and quality of life among older adults in India

BACKGROUND

Underweight defined as body mass index (BMI) < 18.5 is associated with negative health and quality of life outcomes including mortality. Yet, little is known about the socioeconomic differentials in underweight and its association with health and well-being among older adults in India. This study examined the socioeconomic differentials in underweight among respondents aged ≥50 in India. Consequently, three outcomes of the association of underweight were studied. These are poor self-rated health, cognition and quality of life.

METHODS

Cross-sectional data on 6,372 older adults derived from the first wave of the WHO's Study on global AGEing and adult health (SAGE), a nationally representative survey conducted in six states of India during 2007-8, were used. Bivariate and multivariate regression analyses were applied to fulfil the objectives.

RESULTS

The overall prevalence of underweight was 38 percent in the study population. Further, socioeconomic status showed a significant and negative association with underweight. The association of underweight with poor self-rated health (OR = 1.60; p < .001), cognition (β = -0.95; p < .001) and quality of life (β = -1.90; p < .001) were remained statistically significant after adjusting for age, sex, place of residence, marital status, years of schooling, wealth quintile, sleep problems, chronic diseases, low back pain and state/province.

CONCLUSION

The results indicated significant socioeconomic differentials in underweight and its association with poor self-rated health, cognition and quality of life outcomes. Interventions focussing on underweight older adults are important to enhance the overall wellbeing of the growing older population in India.

Obesity in Low- and Middle-Income Countries: Burden, Drivers, and Emerging Challenges

We have reviewed the distinctive features of excess weight, its causes, and related prevention and management efforts, as well as data gaps and recommendations for future research in low- and middle-income countries (LMICs). Obesity is rising in every region of the world, and no country has been successful at reversing the epidemic once it has begun. In LMICs, overweight is higher in women compared with men, in urban compared with rural settings, and in older compared with younger individuals; however, the urban–rural overweight differential is shrinking in many countries. Overweight occurs alongside persistent burdens of underweight in LMICs, especially in young women. Changes in the global diet and physical activity are among the hypothesized leading contributors to obesity. Emerging risk factors include environmental contaminants, chronic psychosocial stress, neuroendocrine dysregulation, and genetic/epigenetic mechanisms. Data on effective strategies to prevent the onset of obesity in LMICs or elsewhere are limited. Expanding the research in this area is a key priority and has important possibilities for reverse innovation that may also inform interventions in high-income countries.

Associations between Obesity and Spinal Diseases: A Medical Expenditure Panel Study Analysis

Background: The link between body weight status and spinal diseases has been suggested by a number of cross-sectional and cohort studies with a limited range of patient populations. No population-representative samples have been used to examine the link between obesity and spinal diseases. The present study is based on a nationally representative sample drawn from the Medical Expenditure Panel Survey. Methods: Using the cross-sectional sample of the 2014 Medical Expenditure Panel Study, we built four weighted logistic regression analyses of the associations between body weight status and the following four spinal diseases: low back pain, spondylosis, other cervical disorders and intervertebral disc disorder (IDD). Each respondent's body weight status was used as the key independent variable with three categories: normal/underweight, overweight, and obese. We controlled for marital status, gender, age, smoking status, household income, health insurance coverage, educational attainment and the use of health services for other major categories of diseases. Results: A total sample of 23,048 respondents was used in our analysis. Overweight and obese respondents, as compared to normal/underweight respondents, were more likely to develop lower back problems (Overweight: logged odds = 0.218, p < 0.01; Obese: logged odds = 0.395, p < 0.001) and IDD (Overweight: logged odds = 0.441, p < 0.05; Obese: logged odds = 0.528, p < 0.001). The associations between bodyweight status and spondylitis were statistically insignificant (Overweight: logged odds = 0.281, p = 0.442; Obese: logged odds = 0.680, p = 0.104). The associations between body weight status and other cervical disorders (Overweight: logged odds = -0.116, p = 0.304; Obese: logged odds = -0.160, p = 0.865) were statistically insignificant. Conclusions: As the first study using a national sample to study bodyweight and spinal diseases, our paper supports the hypothesis that obesity adds to the burden of low back pain and IDD. Longitudinal and interventional studies are needed to understand the specific mechanisms behind these positive associations.

Determining the Prevalence of and Risk Factors for Depressive Symptoms among Adults in Nepal

Context

Nepal is currently experiencing a rapid growth in non-communicable diseases (NCDs). Depression has previously been associated with NCDs in South Asia; however, data regarding its prevalence and risk factors is lacking in Nepal.

Aims

This study aims to describe the prevalence of and risk factors for depressive symptoms in a suburban population of adults within Nepal.

Setting and Design

We conducted a cross-sectional analysis of baseline data collected from participants enrolled in the Dhulikhel Heart Study (DHS), a population-based, longitudinal cohort study investigating cardiovascular risk factors in Dhulikhel, a suburban town outside Kathmandu.

Subjects and Methods

Baseline questionnaire data from 1,073 adults age 18 years and older included the Center for Epidemiologic Studies Depression Scale (CESD). A score of 16 or greater on the CESD has been shown to indicate major depressive symptomatology.

Statistical Analysis

Using STATA 13 we conducted Pearson's chi-squared tests and multiple logistic regressions to examine associations between the binary CESD score and gender, age, education, marital status, body mass index (BMI), physical activity, and hypertensive status.

Results

The mean CESD score in the sample was 11.7 (SD: 5.3), with 21.3% scoring 16 or greater. Age over 60 and lack of formal education were associated with increased risk of depressive symptoms. Being physically active was associated with decreased risk of depressive symptoms.

Conclusions

The estimated prevalence of depression among adults in Dhulikhel was 21.3%. Significant risk factors for increased depressive symptoms included lack of formal education, age over 60, and physical inactivity.