|Year : 2021 | Volume
| Issue : 3 | Page : 348-355
Obesity among the urban poor: Evidence from a community-based study among adults residing in an underprivileged area of Bengaluru city, India
Avita Rose Johnson1, Sakthi Arasu1, Mitchell Singstock2, Nancy Angeline1
1 Department of Community Health, St. John's Medical College, Bengaluru, Karnataka, India
2 Department of Community Health, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
|Date of Submission||22-Apr-2021|
|Date of Acceptance||22-May-2021|
|Date of Web Publication||30-Sep-2021|
Dr. Sakthi Arasu
Department of Community Health, St. John's Medical College, Bengaluru - 560 034, Karnataka,
Source of Support: None, Conflict of Interest: None
BACKGROUND AND OBJECTIVE: Obesity is increasing among the urban poor and is a major risk factor for diabetes, cardiovascular disease, and cancer. The objective of this study is to assess the prevalence and determinants of obesity among adults over the age of 30 years in an underprivileged community of Bengaluru city.
MATERIALS AND METHODS: A cross-sectional study was conducted in an underprivileged area of Southern Bangalore. Sociodemographic details, diet, and lifestyle risk factors were assessed by a pretested questionnaire. Anthropometric measurements of height, weight, and waist circumference were recorded and World Health Organization Asian cutoffs for body mass index (BMI) and waist circumference were used. The Chi-square and Fischer exact tests were used, and adjusted odds ratios (AORs) with 95% confidence interval calculated by logistic regression.
RESULTS: Of the 2244 participants in the study, 60.8% were obese and 14.7% were overweight. The prevalence of abdominal obesity was 79.2% and was significantly higher among women than among men (P < 0.001). Among those with normal BMI, 42.4% had abdominal obesity. Obesity was significantly associated with 40–59 years age group (AOR = 1.35 [1.10–1.64], P = 0.004), higher education (AOR = 1.49 [1.08–2.06], P = 0.016), higher income (AOR = 1.52 [1.18–2.280, P = 0.042), married status (AOR = 1.43 [1.13–1.820, P = 0.003), and daily consumption of salty foods (AOR = 2.01 [1.30–3.92], P = 0.041).
CONCLUSION: Our study in an urban underprivileged area of Bengaluru city found a high prevalence of obesity and abdominal obesity. Targeted interventions are needed to reduce obesogenic environments in urban underprivileged areas, improve access to fresh fruits and vegetables, behavior change communication and screening for diabetes, hypertension and dyslipidemia among the urban poor, considering the high levels of obesity in this population.
Keywords: Abdominal obesity, diet, obesity, overweight, urban underprivileged
|How to cite this article:|
Johnson AR, Arasu S, Singstock M, Angeline N. Obesity among the urban poor: Evidence from a community-based study among adults residing in an underprivileged area of Bengaluru city, India. Indian J Health Sci Biomed Res 2021;14:348-55
|How to cite this URL:|
Johnson AR, Arasu S, Singstock M, Angeline N. Obesity among the urban poor: Evidence from a community-based study among adults residing in an underprivileged area of Bengaluru city, India. Indian J Health Sci Biomed Res [serial online] 2021 [cited 2022 Jan 17];14:348-55. Available from: https://www.ijournalhs.org/text.asp?2021/14/3/348/327264
| Introduction|| |
Obesity is described as excess body fat or weight, higher than what is considered healthy for a given height. Adult overweight and obesity are defined as body mass index (BMI) of 25–29.9 kg/m2 and ≥30 kg/m2, respectively, with 23–24.9 kg/m2 and ≥25 kg/m2, respectively, being the suggested BMI cutoffs for South Asian populations. Obesity is a major risk factor for noncommunicable diseases (NCDs) such as diabetes, cardiovascular disease (CVD), and cancer, which are leading causes of morbidity and mortality among adults worldwide. The World Health Organization (WHO) has defined abdominal obesity (central obesity) as waist circumference ≥90 cm among Asian men and ≥80 cm among Asian women and has stratified the risk of developing Type 2 diabetes mellitus, hypertension and CVD, based on BMI and waist circumference.
Once considered a problem only in high-income countries, overweight and obesity are now increasingly common in low- and middle-income countries, particularly in urban settings. The fundamental cause of obesity is an energy imbalance between calories consumed and calories expended. Globally, there has been a shift in sociocultural and dietary practices toward increased intake of energy-dense foods that are high in saturated fats and simple sugars, as well as, physical inactivity due to an increasingly sedentary lifestyle, especially in urban areas. There is robust evidence from published medical literature to suggest that individuals who are overweight or obese should be encouraged to lose weight to prevent CVD. The Sustainable Development Goals target 3.4 aims to reduce premature mortality from NCDs by one-third through prevention and treatment, by the year 2030.
The nationwide National Family Health Survey (NFHS-4) in India revealed that around 40% of adults surveyed were either overweight or obese. The ICMR-INDIAB study found the prevalence of abdominal obesity among adults to be 16.9%–36.1% across four states in India, with higher prevalence in the urban areas. However, there is a paucity of data regarding the prevalence and determinants or associated risk factors of obesity among the urban poor, who are largely comprised of minority, migrant, and marginalized populations, with limited or no access to screening and care for obesity and its consequences. This study was therefore conducted with the aim of assessing the prevalence of obesity in an underprivileged community of Bengaluru City and associated factors, as well as determining the risk of developing Type 2 diabetes mellitus, hypertension, and CVD in this population. The results of this study would aid the formulation of targeted interventions directed toward reducing the burden of obesity in communities in similar sociocultural settings.
| Materials and Methods|| |
The Urban Health Training Center (UHTC) of a medical college in Bengaluru city, Karnataka state, provides health care to the nearby underprivileged community of 6285 people, as per the health information system of the center, which includes digitized household-level data of this community.
Adults aged 30 years and above, residing in this community.
Based on ICMR-INDIAB data which found a prevalence of 35.7% of obesity among urban-dwelling adults in Tamil Nadu state, the sample size was calculated with 10% relative precision and 95% confidence limits to be 692. However, since the subjects would be screened for overweight/obesity and referred to the UHTC for further evaluation and management of NCDs, as well as receive lifestyle and dietary counseling, it was felt that no adult in this underprivileged community should miss this opportunity for screening. It was therefore decided to forego sampling and instead invite all the adults in the community to be a part of this study. Hence, a universal sampling technique was employed.
House to house visits were conducted by a team of trained community health workers (CHWs). Written informed consent was obtained from all participants.
Adults aged 30 and above, residing in the area since at least 6 months.
Participants with mental or other illnesses that prevented them from understanding the questions were excluded from the study. Participants who were not present even after two visits by the CHWs were also excluded from the study.
A pretested, face-validated, structured interview schedule was used to capture sociodemographic details and various risk factors for obesity as listed in the multi-country INTERHEART study, which included dietary risk factors, alcohol, and physical activity.
Height, weight, and waist circumference were recorded. Height was measured to the nearest 0.1 cm using a portable stadiometer (Seca, Germany) and weight was recorded to the nearest 100 g using a calibrated digital weighing scale (Salter, India). Waist circumference was measured to the nearest 0.1 cm in the horizontal plane mid-way between the lowest rib and the iliac crest, using a nonstretchable measuring tape, ensuring the tape was snug, but not tight. The data were collected in EpiCollect application on mobile phones.
BMI: weight in kilograms divided by height in metres squared. Overweight: BMI of 23–24.9 kg/m2 and obesity: ≥25 kg/m2.,, Abdominal obesity: Waist circumference ≥90 cm among men and ≥80 cm among women., Disease risk for type 2 diabetes, hypertension, and CVD: Classified as low risk to extremely high risk, based on WHO Asian cutoffs for BMI and waist circumference. Poverty line: Per capita income of <Rs. 1,407/month (US$ 0.65 or Rs. 47/day. High-activity occupation: Waiter, cleaner, gardener, construction, laborer, and material mover. Smokers: Current tobacco users and those who quit smoking <1 year before the assessment. Regular consumption of alcohol: consumes ≥3 times a week.
The data were exported to Microsoft Excel and then analyzed using the IBM Corp. Released 2011. IBM SPSS Statistics for Windows, Version 20.0. (Armonk, NY: IBM Corp.). Sociodemographic and risk factors variables were described using frequency, proportion, mean and standard deviation, median, and interquartile range. Chi-square and Fischer exact tests were used to assess the association between obesity and various independent covariates. Variables with a P < 0.2 were entered into a binomial logistic regression model, to calculate Adjusted Odds Ratios with 95% confidence interval. P < 0.05 was considered statistically significant for all analyses.
| Results|| |
Among the 2244 participants in the study, the mean age was 47 ± 12.91 years, comprising three-fourths of women (74.9%). Majority were aged 40–59 years (47.4%). Median years of formal education was 8 (interquartile range [IQR]: 5,10) and 5.7% people were illiterate. Majority had studied up to secondary school (65.8%). Most were married (78.7%) and most (68.5%) belonged to a nuclear family. A total of 768 (34.2%) people were gainfully employed while 1459 (86.8%) women were home makers. The median per capita income of the study population was INR 2500 (IQR: 1600, 3750), with 21.8% below poverty line set by the Indian government and 83.9% below the internationally accepted poverty line of US$1.90.
Obesity and disease risk
The prevalence of obesity was 60.8%, and 14.7% was found to be overweight. The combined prevalence of overweight/obesity was 75.5%, whereas 3.8% was underweight [Table 1]. The prevalence of abdominal obesity was 79.2%. While there was no difference in the distribution of obesity among men and women, the proportion of abdominal obesity was significantly higher among women (84.3%) than among men (64.2%) (P < 0.001) [Table 2]. Among those with normal BMI, 42.4% had abdominal obesity, whereas 70.6% of overweight participants had abdominal obesity and 98% of obese participants had abdominal obesity [Table 3]. High, very high, or extremely high risk for Type 2 diabetes, hypertension, and CVD were found in 1598 (71.2%) of the study population. Among those with abdominal obesity, 88.4% had high risk as compared to 3.3% of those without abdominal obesity.
|Table 1: Classification of obesity based on Asian body mass index cutoffs (n=2244)|
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|Table 3: Disease risk for type 2 diabetes, hypertension, and cardiovascular disease based on Asian cut-offs for body mass index and waist circumference (n=2244)|
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Proportion of obesity was significantly higher among those aged 40–59 years (P < 0.001), married subjects (P < 0.001), and those above poverty line (P < 0.001), proportion of obesity was significantly lower among those with education up to primary school (P = 0.002) [Table 4].
Majority (99.4%) did not consume fruit and 97.8% did not consume vegetables daily. Only 0.4% of the population consumed ≥4 servings of fruits and vegetables in a day. Almost everyone (99%) used a vegetable-based oil, but majority (85.5%) had ≥500 ml monthly per capita oil consumption. Daily consumption of salty food and meat was reported by 0.2% and 0.4% of the population. Junk food was reportedly consumed at least once in the previous week by 59.3% of the participants. A high-activity occupation was reported by 10.9% of participants. Smoking and alcohol consumption was reported to be 3.5% and 2.5%, respectively. Proportion of obesity was significantly higher (P = 0.020) among those who used cooking oils rather than vegetable oils, such as coconut oil, lard, butter, clarified butter (ghee) or hydrogenated oil (Vanaspati) as well as among those who consumed alcohol regularly (P = 0.049) [Table 5].
Factors associated with obesity
Obesity was significantly associated with the 40–59 years of age group adjusted odds ratio (AOR = 1.35 [1.10–1.64], P = 0.004), higher education (AOR = 1.49 [1.08–2.06], P = 0.016), higher income (AOR = 1.52 [1.18–2.280, P = 0.042), married status (AOR = 1.43 [1.13–1.820, P = 0.003), and daily consumption of salty foods (AOR = 2.01 [1.30–3.92], P = 0.041) [Table 6].
|Table 6: Multiple regression analysis of factors associated with obesity (n=2244)|
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| Discussion|| |
The present study sought to explore the issue of obesity among the urban poor. The majority of the study population was women, as data collection happened during working hours while most men were at work. This also explains the high proportion of homemakers among the participants. Due to migration into urban areas in search of better jobs and education opportunities, majority of the families were of nuclear type, having left the extended members of their family in the rural areas. Like most urban underprivileged areas in India, the median income was found to be low, with one in every five persons below the poverty line set by the Government of India (Rs. 47 or US$0.65 daily/capita), and four in every five persons below the international poverty line (US$1.90 daily/capita).
Contrary to the popular perception of obesity being a disease of the rich, our study found that the prevalence of overweight/obesity among the urban poor was very high, with three fourths of the population being either overweight (14.7%) or obese (60.8%). The WHO has reported that globally in 2016, 39%, and 13% of adults were overweight and obese, respectively; therefore, almost half of all adults globally are either overweight or obese. The ICMR-INDIAB study across four states in India found that in the urban areas, 13.1%–18.9% of adults were overweight and 26.1%–40.3% were obese. Our study had considered the age group of 30 years and above, as compared to the WHO report which included ages 18 and above and the ICMR-INDIAB study which considered those who were 25 years and above. Although the larger proportion of obesity in our study may be explained by the older age of our subjects, it is also a fact that the urban poor live in an obesogenic environment. Impoverished living conditions throw up many barriers to engaging in healthy behaviors. Poor families with a limited food budget and limited range of food choices, end up choosing energy dense foods such as sugars, cereals, and oily foods, as well as food with excess oil content, because these foods are more affordable and last longer than fresh vegetables and fruits. Poor families often live in disadvantaged neighborhoods where healthy foods are hard to find; yet, but there are plenty of junk food outlets, fried, and oily “street foods” and small provision stores that stock cheap, unhealthy, packaged snacks. Options for regular physical activity are also restricted for the poor, with the lack of public spaces and parks, inability to afford gyms, yoga or exercise classes, and sometimes even lack of safe walking paths and footpaths.
This obesogenic environment in urban slums is also reflected in our study, where nearly four out of every five adults were found to have abdominal obesity, which was much higher than the levels of abdominal obesity found by the ICMR-INDIAB study (26.7%–46.6% in urban areas). Our study interestingly revealed that a large proportion (42%) of those with normal BMI had abdominal obesity. This may be explained by the “feast and famine” hypothesis, where in the Indian sub-continent, poverty, and repeated famines over past generations have resulted in chronic energy deficiency. When faced with periods of sufficient or excess energy intake, South Asians allocate fat disproportionately in the visceral area, despite an absence of excess weight gain. This results in the typical “thin-fat” phenotype, characterized by the accumulation of truncal and abdominal body fat, but relatively poor muscle mass. Not surprisingly, these features appear to be present from birth as Indian neonates tend to have increased proportion of body fat compared to their Caucasian counterparts despite lower birth weights. Unfortunately abdominal obesity, even in the absence of high BMI is an independent risk for CVD. Based on the presence of generalised and abdominal obesity, the WHO has stratified the risk of developing Type 2 diabetes, hypertension, and CVD among Asian populations. We found high, very high, or extremely high risk among nearly three-fourths of our study population. This risk proportion was found to be much higher among those with abdominal obesity. While there was no difference in the prevalence of generalized obesity among males and females, women had significantly higher proportions of abdominal obesity as compared to men. This has far-reaching public health implications as CVD does not just affect men, it is the number one killer of women as well. In developing countries, women who develop CVD are more likely to die from it than women in industrialized nations, due to reduced access to health care, low autonomy, and low index of suspicion of CVD as women are more likely to experience atypical symptoms of heart attack such as shortness of breath, nausea, vomiting, and jaw pain.
NFHS-4 data showed that obesity was associated with higher education and higher income. In our study, among the urban underprivileged, we had similar findings. This may be because, while obesity affects the poor because of lack of affordability of healthy food, it is even worse among the poor who can afford junk food, fast food, and packaged convenience foods. This was demonstrated by our finding that those whose income put them above the poverty line were significantly more like to be obese than those below this cutoff.
Our study also showed that those who were married were more likely to be obese. NFHS-4 results similarly demonstrated this, as well as a study in Eastern Sudan. It has been suggested that weight gain after marriage may occur because of increased opportunities for eating due to shared, regular meals and larger portion sizes, as well as decreased physical activity and a decline in weight maintenance, as attracting a potential intimate or life partner is no longer a purpose. Married individuals are also less likely to smoke and more likely to quit smoking, and smoking cessation is associated with weight gain. Single, divorced, and widowed persons are more likely to lack social and economic support and might have additional stress or depression that reduces dietary intake and timely meals.
Only a miniscule proportion of our study participants consumed at least four daily servings of fruits and vegetables as recommended by the WHO. A study across five cities in India summarized that on an average, urban-dwelling Indian adults consumed 1.5 servings of fruits and 2 servings of vegetables per day, but in our study, the vast majority did not consume any fruits or vegetables daily. Poor consumption of fruits and vegetables is linked to their high cost. The adequate supply of rice, wheat, sugar, and oil through the public distribution system in this community ensure that their daily carbohydrate and fat needs are met; however, protein content is often lacking in the diet along with fresh fruits and vegetables. Similar findings are presented by the National Nutrition Monitoring Bureau (NNMB) report in 2016–2017.
More than four out of every five participants exceeded the limit of oil consumption (500 ml/capita, per month). The NNMB report also states that fats and oils are consumed at 159% of the recommended dietary allowance. Foods cooked with greater quantities of oil tend to keep well without refrigeration and also provide higher satiety, which probably explains the high oil consumption among the urban poor, along with the easy availability and affordability of oil through the public distribution system. However, the type of oil consumed is also linked to obesity, as shown in our study, where those who consumed saturated fats and trans-fats were more likely to be obese. These “unhealthy fats” are linked to obesity and CVD.
The preference for salted foods is evident as majority of our study population reported consuming salty foods in the previous week. A systematic review by the George Institute for Global Health shows that an Indian on an average consumes 10.98 g of salt/day, which is much higher than the recommended daily intake of 5–6 g/day.
Does losing weight reduce the cardiovascular risk for those who are overweight or obese? Meta-analyses of randomized controlled trials have shown that a weight-reduction diet, combined with exercise, produces significant weight loss, reduces total cholesterol and low-density lipoprotein-cholesterol, increases high-density lipoprotein-cholesterol, and improves control of blood pressure and diabetes. An alarming trend is that obesity in India has more than doubled over the last 15 years.
Due to certain constraints, this study was carried out during working hours, which resulted in a skewed gender distribution, with female preponderance. We were not able to quantify physical activity in this study. Questions on tobacco and alcohol consumption may have elicited answers with a social desirability bias.
| Conclusion|| |
Our study in an urban underprivileged area of Bengaluru city found a high prevalence of obesity with three out of every five persons having obesity and four out of every five persons having abdominal obesity. High, very high or extremely high risk for Type 2 diabetes, hypertension, and CVD were found in three-fourths of the study population. Targeted interventions are needed to reduce obesogenic environments in urban underprivileged areas, improve access to fresh fruits and vegetables, behavior change communication and screening for diabetes, hypertension, and dyslipidemia among the urban poor, considering the high levels of obesity in this population.
To effectively capitalize on this updated evidence, policy-makers need to frame targeted interventions to reduce obesogenic environments in urban underprivileged areas, by improving access to fresh fruits and vegetables through the existing public distribution system, creating public spaces and parks, behavior change communication, and engaging with urban communities in planning these key strategies to reduce obesity. Screening for diabetes, hypertension, and dyslipidemia among the urban poor is also needed, considering the high levels of obesity in this population.
Ethical Clearance was obtained from the Institutional Ethical Committee of St John's Medical College, Bangalore, India with reference number 316/2020 dated 28th January 2021.
Informed written consent was obtained from all the participants.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Misra A, Chowbey P, Makkar B, Vikram N, Wasir J, Chadha D, et al.
Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India 2009;57:163-70.
World Health Organization. The Asia-Pacific Perspective: Redefining Obesity and its Treatment. Western Pacific Region. Sydney: Health Communications Australia; 2000.
Ebbert JO, Elrashidi MY, Jensen MD. Managing overweight and obesity in adults to reduce cardiovascular disease risk. Curr Atheroscler Rep 2014;16:445.
National Family Health Survey-4 (2015-16). Indian Institute for Population Sciences and Ministry of Health and Family Welfare. New Delhi; Government of India; 2017. Available from: http://rchiips.org/nfhs/pdf/NFHS4/India.pdf
. [Last accessed on 2020 Oct 01].
Pradeepa R, Anjana RM, Joshi SR, Bhansali A, Deepa M, Joshi PP, et al.
Prevalence of generalized and abdominal obesity in urban and rural India – The ICMR-INDIAB Study (Phase-I) [ICMR- NDIAB-3]. Indian J Med Res 2015;142:139-50.
] [Full text]
Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, et al.
INTERHEART Study Investigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): Case-control study. Lancet 2004;364:937-52.
Ismail M, IASO - International Association for the Study of Obesity. Redefining Obesity and its Treatment. Geneva, Switzerland: World Health Organization; 2000. p. 56.
World Health Organization (WHO). Waist Circumference and Waist-Hip Ratio: Report of a WHO Expert Consultation. Geneva, Switzerland: World Health Organization; 2008.
Planning Commission, Government of India. Report of the Expert Group to Review the Methodology for Measurement of Poverty. New Delhi, India; 2014.
Steeves JA, Tudor-Locke C, Murphy RA, King GA, Fitzhugh EC, Harris TB. Classification of occupational activity categories using accelerometry: NHANES 2003-2004. Int J Behav Nutr Phys Act 2015;12:89.
Wells JC. Commentary: Why are South Asians susceptible to central obesity? The El Niño hypothesis. Int J Epidemiol 2007;36:226-7.
Kulkarni ML, Mythri HP, Kulkarni AM. 'Thinfat' phenotype in newborns. Indian J Pediatr 2009;76:369-73.
Prasad DS, Kabir Z, Dash AK, Das BC. Abdominal obesity, an independent cardiovascular risk factor in Indian subcontinent: A clinico epidemiological evidence summary. J Cardiovasc Dis Res 2011;2:199-205.
] [Full text]
Al Kibria GM, Swasey K, Hasan MZ, Sharmeen A, Day B. Prevalence and factors associated with underweight, overweight and obesity among women of reproductive age in India. Glob Health Res Policy 2019;4:1-2.
Omar SM, Taha Z, Hassan AA, Al-Wutayd O, Adam I. Prevalence and factors associated with overweight and central obesity among adults in the Eastern Sudan. PLoS One 2020;15:1-10.
Dinour L, Leung MM, Tripicchio G, Khan S, Yeh MC. The association between marital transitions, body mass index, and weight: A review of the literature. J Obes 2012;2012:1-6.
World Health Organization (WHO) and FAO. Diet, nutrition and the Prevention of Chronic Diseases. Geneva, Switzeland: World Health Organization (WHO) and FAO; 2003.
National Institute of Nutrition. Diet and Nutrition Status of Urban Population in India and Prevalence of Obesity, Hypertesnion, Diabetes and Hyperrtension in Urban Men and Women – A brief NNMB Urban Nutrition Report. Hyderabad: National Institute of Nutrition; 2017.
Briggs MA, Petersen KS, Kris-Etherton PM. Saturated fatty acids and cardiovascular disease: Replacements for saturated fat to reduce cardiovascular risk. Healthcare (Basel) 2017;5:29.
Johnson C, Praveen D, Pope A, Raj TS, Pillai RN, Land MA, et al.
Mean population salt consumption in India: A systematic review. J Hypertens 2017;35:3-9.
Avenell A, Brown TJ, McGee MA, Campbell MK, Grant AM, Broom J, et al.
What are the long-term benefits of weight reducing diets in adults? A systematic review of randomized controlled trials. J Hum Nutr Dietetics 2004;17:317-35.
Shannawaz M, Arokiasamy P. Overweight/Obesity: An emerging epidemic in India. J Clin Diagn Res 2018;12:LC01-5.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]