Urbanisation and geographic variation of overweight and obesity in India: a cross-sectional analysis of the Indian Demographic Health Survey 2005-2006

Spatiotemporal variations and determinants of overweight/obesity among women of reproductive age in urban India during 2005-2021

BACKGROUND

India has witnessed rapid urbanization in recent decades, leading to a worrisome surge in non-communicable diseases, particularly overweight/obesity, which now present a critical public health concern. Therefore, this study seeks to examine spatiotemporal variations and determinants of overweight/obesity among women of reproductive age (WRA) in urban India and its states during 2005-2021.

METHODS

The study used 44,882, 171,443, and 135,272 WRA aged 15-49 from National Family Health Survey (NFHS)-3 (2005-06), NFHS-4 (2015-16), and NFHS-5 (2019-21), respectively. The outcome variable was overweight/obesity, defined as a Body Mass Index (BMI) of ≥ 25 kg/m2. Chi-squared test and multivariable logistic regression were used to identify the determinants of overweight/obesity.

RESULTS

Overweight/obesity prevalence among WRA in urban India has risen significantly, from 23% in 2005-06 to 33% in 2019-21. This increase is particularly pronounced among SC/ST women and women with lower educational levels. During the study period, overweight/obesity rates in different states exhibited varying increases, ranging from 3 percentage points (pp) in Rajasthan to 22 pp in Odisha. Certain southern (e.g., Tamil Nadu and Andhra Pradesh) and northeastern states saw a significant 15 pp or more increase. In contrast, several northern, central, and eastern states (e.g., Punjab, Haryana, Rajasthan, Madhya Pradesh, Chhattisgarh, Jharkhand, West Bengal) experienced relatively smaller increases ranging from 5 to 8 pp. As of 2019-21, two regions exhibited high prevalence rates of overweight/obesity, exceeding 35%: the southern region (Tamil Nadu, Andhra Pradesh, Kerala, and Karnataka) and the northern region (Punjab, Himachal Pradesh, Uttarakhand, and Haryana). In contrast, the Empowered Action Group states had relatively lower rates (25% or less) of overweight/obesity. Regression results showed that older women [AOR: 5.98, 95% CI: 5.71-6.27], those from the richest quintile [AOR: 4.23, 95% CI: 3.95-4.54], those living in south India [AOR: 1.77, 95% CI: 1.72-1.82], and those having diabetes [AOR: 1.92, 95% CI: 1.83-2.02] were more likely to be overweight/obese.

CONCLUSION

Considering the significant increase in overweight/obesity among urban WRA in India, along with substantial disparities across states and socioeconomic groups, it is imperative for the government to formulate state-specific strategies and policies based on determinants to effectively combat overweight/obesity.

Spatial inequality and explaining the urban-rural gap in obesity in India: Evidence from 2015-16 population-based survey

OBJECTIVE

This study assessed the spatial dimension of urban-rural disparity in obesity prevalence and identified the determinants explaining the urban-rural gap in obesity prevalence in India.

METHODS

Using cross-sectional survey data from the 2015-16 National Family Health Survey, the prevalence rates of obesity were calculated for aged 15-49 years. Two multiscale geographically weighted regressions were performed separately from rural and urban spaces for Indian districts to examine the spatial relationship of the outcome variable and covariates at different geographical scales. Fairlie decomposition analysis was carried out to explore the contribution of each variable in the urban-rural gap.

RESULTS

The rural-urban obesity prevalence difference has increased in a decade time for India from 13.0 to 14.6. Urban counterparts tended to have more people with excess weight. 15 states had an urban-rural prevalence ratio of 2 or higher. The MGWR model showed that varying covariates operated at different scales, i.e. global, regional and local scales, and determined the spatial heterogeneity of obesity prevalence. The only variable, i.e. age (9.49 per cent), had contributed in reducing the gap. Conversely, the socioeconomic variables, i.e. income (96.39 per cent), education (4.95 per cent), caste (4.78 per cent) and occupation (3.11 per cent), had widened the gap.

CONCLUSIONS

Even though this study evidenced the rural-urban gap in obesity prevalence, it indicated the gap's closing shortly, as it was witnessed in a few states. It is urgent to address the obesity epidemic, especially in urban India, due to its higher prevalence and prevent the further increase of prevalence in rural India, mainly because it shelters nearly 70 per cent of the Indian population.

Thirty-Year Urbanization Trajectories and Obesity in Modernizing China

The effects of long-term urbanization changes in obesity are unclear. Data were obtained from the China Health and Nutrition Survey (CHNS) 1989-2018. A multidimensional urbanicity index was used to define the urbanization level for communities. Group-based trajectory modeling was used to identify distinct urbanization change trajectories. Gender-stratified multilevel models were used to investigate the association between urbanization trajectories and weight/BMI, through the PROC MIXED procedure, as well as the risk of being overweight + obesity (OO)/obesity (OB), through the PROC GLIMMIX procedure. A total of three patterns of the trajectory of change in urbanization were identified in 304 communities (with 1862 measurements). A total of 25.8% of communities had a low initial urbanization level and continuous increase (termed "LU"), 22.2% of communities had a low-middle initial urbanization level and constant increase (termed "LMU"), and 52.0% of communities had a middle-high initial urbanization and significant increase before 2009, followed by a stable platform since then (termed "MHU"). During the 30 follow-up years, a total of 69490 visits, contributed by 16768 adult participants, were included in the analysis. In the period, weight and BMI were observed in an increasing trend in all urbanization trajectory groups, among both men and women. Compared with LU, men living in MHU were related to higher weight, BMI, and an increased risk of OO (OR: 1.46, 95%CI: 1.26 to 1.69). No significant associations were found between urbanization trajectories and OB risk in men. Among women, the associations between urbanization and all obesity indicators became insignificant after controlling the covariates. Obesity indicators increased along with urbanization in the past thirty years in China. However, the differences among urbanization trajectories narrowed over time. More urbanized features were only significantly associated with a higher risk of obesity indicators in Chinese men. The effects of urbanization on obesity among women were buffered.

Epidemiology of overweight and obesity in Indian adults - A secondary data analysis of the National Family Health Surveys

AIMS

National Family Health Survey (NFHS) conducted in India provide nationally comparable data on socio-demographic characteristics and anthropometric estimates. Present study was conducted to examine the prevalence of Indian adults who are living with overweight/obesity, their correlates, and trends observed between the last two rounds of the NFHS 2005-06 to 2015-16).

METHODS

Socio-demographic characteristics and anthropometric estimates of respondents from NFHS round III & IV were analysed. Asian cut-offs were used for obesity classification. Of the total 198,754 and 811,808 eligible respondents, adults ≥18 years of age were included in the analysis. Prevalence and correlates were presented after taking into account stratification, clustering and sampling weights. GIS mapping was done to depict regional variations.

RESULTS

Prevalence of men and women living with overweight/obesity were observed to be 38.4% and 36.2% respectively. Wide variations were observed in prevalence across the regions of India. Results of multivariate analysis showed that the strongest predictors for being overweight or obese were older age, currently in union, higher education, richest wealth quintile, and living in urban areas.

CONCLUSION

The present study highlights the rising prevalence across the urban and rural locations and has implications for policy change based on the prevalence estimates.

Trends in the prevalence of adult overweight and obesity in Australia, and its association with geographic remoteness

The prevalence of overweight and obesity has been increasing globally and has become a significant public health concern in Australia in the two past decades. This study explores the most recent national prevalence and trends of adult overweight and obesity in Australia. It will also investigate geographic remoteness as a potential risk factor for an individual being overweight or obese in adulthood. A retrospective longitudinal study that utilised 14 successive waves (wave 6 through 19) of a nationally representative linked individual-level survey. Data was obtained from the Household, Income and Labour Dynamics in Australia survey. The data on 199,675 observations from 26,713 individuals aged ≥ 15 years over the period 2006 to 2019 was analysed. Random-effects logit model was employed to estimate the association between geographic remoteness and the risk of excessive weight gain. The results reveal that the prevalence of overweight, obesity and combined overweight and obesity among Australian adults in 2019 were 34%, 26% and 60%, respectively. The analysis shows that the prevalence of overweight and obesity varies by geographic remoteness. Adults from regional city urban (OR 1.53, 95% CI 1.16-2.03) and rural areas (OR 1.32, 95% CI 1.18-1.47) were more likely to be obese compared with their counterparts from major city urban areas. The results also show that adults living in major city urban areas, regional city urban areas, and regional city rural areas in Australia were 1.53 (OR 1.53, 95% CI 1.16-2.03), 1.32 (OR 1.32, 95% CI 1.18-1.47), and 1.18 (OR 1.18, 95% CI 1.08-1.29) times more likely to be overweight compared with their counterparts from major city urban areas in Australia. Substantial geographic variation in the prevalence of overweight and obesity exists among Australian adults and appears to be increasing. Public health measures should focus on contextual obesogenic factors and behavioural characteristics to curb the rising prevalence of adult obesity.

Urban-rural differences in overweight and obesity among 25-64 years old Myanmar residents: a cross-sectional, nationwide survey

OBJECTIVES

To investigate whether urban-rural location and socioeconomic factors (income, education and employment) are associated with body mass index (BMI) and waist-hip ratio (W/H-ratio), and to further explore if the associations between urban-rural location and BMI or W/H-ratio could be mediated through variations in socioeconomic factors.

DESIGN

Cross-sectional, WHO STEPS survey of non-communicable disease risk factors.

SETTING

Urban and rural areas of Myanmar.

PARTICIPANTS

A total of 8390 men and women aged 25 to 64 years included during the study period from September to December 2014. Institutionalised people (Buddhist monks and nuns, hospitalised patients) and temporary residents were excluded.

RESULTS

The prevalence of overweight and obesity was higher in the urban areas and increased with increasing socioeconomic status (SES) score. Mean BMI was higher among urban residents (ß=2.49 kg/m²; 95% CI 2.28 to 2.70; p<0.001), individuals living above poverty line, that is, ≥US$1.9/day (ß=0.74 kg/m²; 95% CI 0.43 to 1.05; p<0.001), and those with high education attainment (ß=1.48 kg/m²; 95% CI 1.13 to 1.82; p<0.001) when adjusting for potential confounders. Similarly, greater W/H-ratio was observed in participants living in an urban area, among those with earnings above poverty line, and among unemployed individuals. The association between urban-rural location and BMI was found to be partially mediated by a composite SES score (9%), income (17%), education (16%) and employment (16%), while the association between urban-rural location and W/H-ratio was found to be partially mediated by income (12%), education (6%) and employment (6%).

CONCLUSION

Residents living in urban locations had higher BMI and greater W/H-ratio, partially explained by differences in socioeconomic indicators, indicating that socioeconomic factors should be emphasised in the management of overweight and obesity in the Myanmar population. Furthermore, new national or subnational STEPS surveys should be conducted in Myanmar to observe the disparity in trends of the urban-rural differential.

Disparity in childhood stunting in India: Relative importance of community-level nutrition and sanitary practices

Despite rapid macro-economic growth, one-third of the global burden of childhood stunting is contributed by India. This burden is characterized by wide-spread geographical variation within the country. This paper explores two research questions: (i) are the drivers of severe and moderate stunting similar? (ii) differential endowments or policy-effect, how do community-level nutrition and sanitary practices affect inter-state differences? Using data from Indian National Family and Health Survey 4, 2015-16, six states holding different ranks in the stunting continuum are compared to Tamil Nadu, taken as the benchmark state due to its laudable performance in the health care sector. Applying quantile regression approaches, the difference in state-level performance is decomposed into detailed covariate effects (differential endowments) and coefficient effects (differential strength of association between the drivers and outcome). The explanatory variables are not similarly associated with severe and moderate stunting. Decomposition results demonstrate a significant role of community-level sanitation practices compared to child nutrition behaviour in explaining the inter-state disparity. Coefficient effects play a dominant role in the lower tail of HAZ distribution for the poor performing states indicating that the worse outcomes of these states are due to weaker policy effects of the control variables on stunting. Multi-sectoral approach, identification and differentiation between severe and moderate stunting cases can be more instrumental in managing and reducing the scourge. This paper also advocates the potential benefits of customizing centrally-launched policies as per the state's performance and introducing the concept coproduction in the existing nutrition and health policy framework. This will instigate a feeling of ownership of the problem of childhood stunting among the policy consumers and strengthen the influence of policies on the outcomes.

Application of single-level and multi-level modeling approach to examine geographic and socioeconomic variation in underweight, overweight and obesity in Nepal: findings from NDHS 2016

Nepal's dual burden of undernutrition and over nutrition warrants further exploration of the population level differences in nutritional status. The study aimed to explore, for the first time in Nepal, potential geographic and socioeconomic variation in underweight and overweight and/or obesity prevalence in the country, adjusted for cluster and sample weight. Data came from 14,937 participants, including 6,172 men and 8,765 women, 15 years or older who participated in the 2016 Nepal Demography and Health Survey (NDHS). Single-level and multilevel multi-nominal logistic regression models and Lorenz curves were used to explore the inequalities in weight status. Urban residents had higher odds of being overweight and/or obese (OR: 1.89, 95% CI: 1.62-2.20) and lower odds of being underweight (OR: 0.81, 95% CI: 0.70-0.93) than rural residents. Participants from Provinces 2, and 7 were less likely to be overweight/obese and more likely to be underweight (referent: province-1). Participants from higher wealth quintile households were associated with higher odds of being overweight and/or obese (P-trend < 0.001) and lower odds of being underweight (P-trend < 0.001). Urban females at the highest wealth quintile were more vulnerable to overweight and/or obesity as 49% of them were overweight and/or obese and nearly 39% at the lowest wealth quintile were underweight.

Rural-Urban Differences in Dietary Behavior and Obesity: Results of the Riskesdas Study in 10-18-Year-Old Indonesian Children and Adolescents

Obesity has become a significant problem for developing countries, including Indonesia. High duration of sedentary activity and high intake of unhealthy foods were associated with high risk of overweight and obesity. The objective of this study was to compare the distributions of sedentary activity and dietary behavior with overweight/obesity risks between urban and rural areas among children and adolescents aged 10-18 years in Indonesia. This is a cross-sectional study. Data from a national survey in 33 Indonesian provinces (Basic Health Research /Riskesdas 2013) were analyzed. Multiple logistic regression models were used to calculate the odds ratio (OR) adjusted with all variables, such as age, gender, residency, education level, physical activity, and food intake. An urban-rural residence difference was found in the factors related to obesity. Daily caffeinated soft drinks and energy drinks consumption (OR = 1.12, 95% CI: 1.01-1.23) were related to risk of overweight and obesity in urban areas. Daily grilled foods (OR = 1.32, 95% CI: 1.22-1.42) and salty food (OR = 1.09, 95% CI: 1.04-1.15) consumption were significantly associated with obesity in rural areas but not in urban areas. Furthermore, sedentary activity was correlated with overweight and obesity among those who lived in urban and rural areas. Our findings suggest that education, environmental, and policy interventions may need to specifically target urban settings, where access is high to a wide range of processed and traditional high-sugar, high-fat snack foods and beverages.

The Prevalence of Overweight, Obesity, Hypertension, and Diabetes in India: Analysis of the 2015-2016 National Family Health Survey

Overweight, obesity, hypertension, and diabetes increase the risk of non-communicable diseases and all-cause mortality worldwide. Previous studies have not determined the prevalence of these conditions/diseases throughout India. Therefore, this study was aimed to address this limitation. Data on these conditions/diseases among men and women aged ≥ 18 years were obtained from the fourth National Family Health Survey conducted throughout India between January 2015 and December 2016. The prevalence and prevalence rate per 100,000 population were calculated at the national level and by age group, sex, and type of residence for each state and union territory. The national prevalence of overweight, obesity, hypertension, and diabetes were 14.6%, 3.4%, 5.2%, and 7.1%, respectively. The highest prevalence of these conditions/diseases at the national level was seen among those aged 35–49 years (54 years for men), especially women living in urban areas. In India, 1 out of every 7, 29, 19, and 14 individuals at the national level had overweight, obesity, hypertension, and diabetes, respectively—between 2015 and 2016. These results are important for the healthcare system and government policies in the future. Moreover, targeted efforts are required to establish public health strategies for the prevention, management, and treatment of these conditions/diseases throughout India.

Geographical variation and urban-rural disparity of overweight and obesity in Chinese school-aged children between 2010 and 2014: two successive national cross-sectional surveys

PURPOSE

The urban-rural disparity for childhood overweight and obesity shows different patterns in most countries. This study aimed to examine the recent trend of urban-rural disparity for childhood overweight and obesity at national and subnational levels in Chinese children from 2010 to 2014.

DESIGN

Two successive national cross-sectional studies. Overweight and obesity were classified using Chinese national age-specific and sex-specific body mass index reference. The prevalence of overweight and obesity was compared between urban and rural areas at national and subnational levels.

SETTING

Thirty-one provinces in China.

PARTICIPANTS

Data were obtained from the Chinese National Survey on Students' Constitution and Health in 2010 and 2014 with 215 214 (107 741 in 2010 and 107 473 in 2014) children aged 7-12 years.

RESULTS

The overweight and obesity prevalence increased from 17.1% in 2010 to 22.5% in 2014. The overweight and obesity prevalence in both urban and rural areas was higher in the eastern provinces but lower in the western provinces. The urban-rural disparity in overweight and obesity decreased steadily from 2010 to 2014 (1.79 to 1.42 for prevalence OR). There was greater urban-rural disparity in western China than eastern China. A reversal occurred in 2014 in several eastern provinces where the overweight and obesity prevalence in rural children surpassed that of their urban peers.

CONCLUSIONS

A narrowing urban-rural disparity and the reversal signal between urban and rural areas in overweight and obesity would contribute to a growing proportion of obese children in rural areas. Therefore, urgent region-specific policies and interventions with a forward-looking approach should be considered for Chinese children, especially in rural areas.

Determinants of cardiovascular disease and sequential decision-making for treatment among women: A Heckman's approach

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Women over age 40, from lower socio-economic status and those widowed/divorced are at elevated risk.

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Diabetes, hypertension, obesity and unhealthy diet are the major risk factors.

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Treatment-seeking is higher in women over age 40, from upper socio-economic status and those married.

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Autonomy, accessibility, affordability and availability influence treatment-seeking behaviour.

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 and Cancer: Concepts and Challenges

The rates of overweight and obesity are increasing worldwide in both developed and developing countries. Obesity is a major public health problem as it is associated with many diseases, including diabetes, hypertension, dyslipidemia, atherosclerosis, and some types of cancer. Breast cancer is a malignancy in which both the risk of development and the prognosis are negatively impacted by the obese state. The precise mechanisms pathophysiologically linking obesity and cancer are still under investigation. The biological basis for these associations includes both systemic and local tissue effects and white adipose tissue inflammation appears to be a critical component. A comprehensive understanding of the mechanisms linking obesity, inflammation and cancer may provide an opportunity for the development of strategies to attenuate the negative impact of obesity.