|Year : 2019 | Volume
| Issue : 1 | Page : 23-29
Overweight and obesity among adults in rural Bengal: A community-based cross-sectional study
Nabarun Karmakar1, Udit Pradhan2, Indranil Saha3, Soumalya Ray4, R Parthasarathi5, Rabindranath Sinha6
1 Department of Community Medicine, Tripura Medical College and Dr. BRAM Teaching Hospital, Agartala, Tripura, India
2 Department of Community Medicine, Sikkim Manipal Institute of Medical Sciences, Gangtok, Sikkim, India
3 Department of Community Medicine, IQ City Medical College, Durgapur, India
4 Department of Community Medicine, Burdwan Medical College, Burdwan, West Bengal, India
5 Department of Community Medicine, Government Thiruvarur Medical College, Thanjavur, Tamil Nadu, India
6 Department of Maternity and Child Health, All India Institute of Hygiene and Public Health, Kolkata, India
|Date of Submission||16-Jan-2018|
|Date of Decision||26-Apr-2018|
|Date of Acceptance||11-Jun-2018|
|Date of Web Publication||14-Feb-2019|
Assistant Professor, Department of Community Medicine, Sikkim Manipal Institute of Medical Sciences, 5th Mile, NH 31A, Tadong, Gangtok - 737 102, Sikkim
Source of Support: None, Conflict of Interest: None
Background: Globally, more people are obese than underweight – this occurs in every region except parts of Sub-Saharan Africa and Asia. Overweight and obesity are linked to more deaths worldwide than underweight. Objective: The objective of this study is to find the prevalence of overweight and obesity and its association with sociodemographic and behavioral factors, if any among adult population in rural communities of Singur block of West Bengal. Materials and Methods: This community-based study was conducted among 510 people aged 20 years and above from October 2014 to June 2015 in rural communities of Singur block, West Bengal, a rural field practice area of All India Institute of Hygiene and Public Health, Kolkata. The study participants were interviewed using predesigned and pretested questionnaire regarding sociodemographic characteristics supplemented with clinical and anthropometrical examination. Results: Among 510 participants, 22.4% were overweight and 30.4% fall in the obese category. Nearly half 46.5% of the participants (21.2% males vs. 68.2% females) had abdominal obesity. The prevalence of obesity was more among in the age group of 30–40 years (26.4%) and 20–30 and 40–50 years (each group, 25.3%, P < 0.001). Female participants were predominantly obese (58% vs. 42%) than males (P < 0.05). Higher prevalence of obesity was seen among participants belonging to Hindu religion (87%), general caste (48%), currently married (84.8%), and joint families (52%) which were statistically significant (P < 0.05). Nonworking group of participants was more obese (58.4% vs. 41.6%) than working group (P > 0.05). Less overweight/obesity was seen among those having family history (29%) of noncommunicable disease (P < 0.001), habit of consumption of alcohol (5.2%), and tobacco (20.4%) (P > 0.05). Conclusion: The study revealed rising trend of overweight and obesity among adults in rural area of West Bengal. Prevention of overweight and obesity has to be recognized as a public health priority, creating awareness among rural population.
Keywords: Adults, obesity, overweight, prevalence, rural
|How to cite this article:|
Karmakar N, Pradhan U, Saha I, Ray S, Parthasarathi R, Sinha R. Overweight and obesity among adults in rural Bengal: A community-based cross-sectional study. CHRISMED J Health Res 2019;6:23-9
|How to cite this URL:|
Karmakar N, Pradhan U, Saha I, Ray S, Parthasarathi R, Sinha R. Overweight and obesity among adults in rural Bengal: A community-based cross-sectional study. CHRISMED J Health Res [serial online] 2019 [cited 2019 Oct 17];6:23-9. Available from: http://www.cjhr.org/text.asp?2019/6/1/23/252293
| Introduction|| |
Overweight and obesity are defined as abnormal or excessive fat accumulation that presents a risk to health. A crude population-level measure of obesity is the body mass index (BMI), a person's weight (in kilograms) divided by the square of his or her height (in meters). A person with a BMI of ≥30 kg/m2 is generally considered obese. A person with a BMI equal to or more than 25 kg/m2 is considered overweight.
Globally, there are more people who are obese than underweight – this occurs in every region except parts of Sub-Saharan Africa and Asia. Overweight and obesity are linked to more deaths worldwide than underweight. Globally, in 2014, more than 1.9 billion adults of 18 years and older were overweight among which over 600 million were obese. Furthermore, around 3.4 million adults die each year as a result of being overweight or obese. In India in last one decade, men and women who were overweight and obese (BMI ≥25.00 kg/m2) increased from 9.3%–18.6% to 12.6%–20.7%, respectively.
Many low- and middle-income countries are now facing a “double burden” of diseases with a rapid upsurge in noncommunicable disease (NCD) risk factors such as overweight and obesity apart from existing infectious disease and undernutrition. Overweight and obesity are major risk factors for a number of chronic diseases; around 44% of diabetes, 23% of ischemic heart disease, and 7%–41% of certain cancer burdens are attributable to overweight and obesity.
The sedentary and dietary patterns as a result of environmental and societal changes due to urbanization and modernization are often stamped for propagating overweight and obesity though little research has examined the risk factors contributing to rising prevalence in rural areas where 70% of the Indian population live and modernization has occurred less rapidly. Studies of NCD biomarkers have long conferred the possibility of an “Asian Indian phenotype” that produces higher risk central adiposity at a lower BMI than comparable populations in Europe and North America, indicating that Asian Indians are more susceptible to the negative health consequences of overweight and obesity. In-depth examinations of overweight and obesity in rural regions are therefore essential, especially considering that these regions are often compromised by low literacy and poor access to health-care services. With this background, the present study was carried out to elicit the prevalence of obesity and overweight and its association with sociodemographic, behavioral factors, if any among adult population in rural communities of Singur block, Hooghly district of West Bengal, which is the rural field practice area of Rural Health Unit and Training Centre (RHUTC), under All India Institute of Hygiene and Public Health, Kolkata.
| Materials and Methods|| |
This community-based epidemiological study with a cross-sectional design was conducted among people aged 20 years and above from October 2014 to June 2015 in rural communities of Singur block, Hooghly district of West Bengal, which is the rural field practice area of RHUTC, under All India Institute of Hygiene and Public Health, Kolkata.
Taking prevalence of obesity 17.7% with 20% relative allowable error sample size becomes 464 after applying the formula – Sample size = Zα2 pq/L2, where Zα= Standard normal deviate at a desired confidence level (95%); P = Previous prevalence; q = 100 – P; and L = allowable error. At 95% confidence level, Zα value is 1.96. An additional 10% increase was required to compensate for any nonresponse among study participants. Hence, the final sample size for the study was calculated to be 510 and was collected for the study.
From the list of villages in the in the catchment area of RHUTC, Mollasimla, a village was randomly selected using random numbers from random number table. Then, line listing of all individuals aged 20 years and above (1752 persons) residing in Mollasimla was made (sampling frame) from the electoral list of 2011 available to the local panchayat. A total of 510 such individuals were identified by systematic random sampling (every 3rd individual was selected) using the available electoral lists as the sampling frame. All the inhabitants aged 20 years and above. Unwilling individuals, pregnant women, and physically disabled and moribund patients were excluded from the study.
Predesigned and pretested schedule, a nonstretchable measuring tape, and weighing machine are used in this study.
All the study participants were interviewed at their family; followed by weight, height,, waist and hip circumference measurement and in addition to that, review of any past records such as OPD tickets and doctor's prescription etc were done. For assessment of obesity, both World Health Organization (WHO) definition (BMI ≥25 as overweight and BMI ≥30 as obesity) and Asian cutoff (BMI ≥23.0 as overweight and BMI ≥25.0 as obesity) based on the WHO Asia-Pacific Guidelines were used. Waist circumference (WC) and waist-hip ratio (WHR) were measured to assess the central obesity. The International Diabetes Federation cutoff values for WC ≥80 cm among females and ≥90 cm among males and WHO cutoff values for WHR ≥0.8 and ≥0.9 among women and men were used to define the increased health risk due to overweight.,
This was assessed using updated B.G. Prasad classification for the month of May 2016 where social class is divided into five categories based on per capita income limits where lowest social class is Class V (percutaneous coronary intervention [PCI] < Rs. 942/-), Class IV (PCI = Rs. 942–1882/-), and highest Class I (PCI ≥ Rs. 6277/-).
A house-to-house survey was done during October 2014–June 2015. The participants were made comfortable and were told the purpose of the study and their co-operation was sought. Then, they were interviewed personally using predesigned and pretested questionnaire in their family setting, and information was collected about sociodemographic characteristics supplemented with clinical and anthropometrical examination of individuals. The members of the house not available at the time of home visits were contacted later by repeated visits. During the study, individuals with BMI ≥ 23.00 were advised for lifestyle modifications and to visit the nearest union health centers for further investigations and treatment, if necessary.
At first, the proposal with the interview schedule was submitted for ethical clearance to the Institutional Ethics Committee of All India Institute of Hygiene and Public Health, Kolkata. Data collection was initiated only after receiving the Ethical Clearance Certificate. Informed written/verbal consent in the local language was taken from every interviewee.
The collected data were entered in Microsoft Excel worksheet (Microsoft, Redwoods, WA, USA) and checked for any duplicate or erroneous entry. Data were presented in appropriate diagrams and tables; Significance of association between obesity (dependent variable) and different other independent variables were analyzed by Chi-square (χ2) test in SPSS software, version 19.0 (Statistical Package for the Social Sciences Inc., Chicago, IL, USA). P < 0.05 was considered as statistically significant.
| Results|| |
In this study, a total of 510 adults had participated. [Table 1] revealed that among 510 participants, majority (34.3%) belonged to 20–30 years' age group, followed by 22.5% in 30–40 years' age group, and least (4.7%) were in 60 years and above; 53.7% were female. Mean age of the population was 37.2 ± 12.8 years. Most of the study participants (89.6%) were Hindu and only 10.4% were from Muslim community; 55.1% of the study participants belonged to nuclear family. Among the study participants, 81.2% were currently married followed by 15.7% who were never married. Least number of study participants (3.3%) comprised widow, widower, or separated. Nearly 30.6% had a literacy status up to primary school completion followed by 22.4% middle school completion and 15.3% were illiterate. Majority of the participants (59.2%) were in nonworking category, while carrying out this study by occupation, 42.4% of study populations were housewife, 16.8% students, and 15.8% farmers. Majority of the participants (58%) belonged to Class V socioeconomic category followed by 38% in Class IV socioeconomic category as per modified B.G. Prasad scale May 2016.
|Table 1: Distribution of study population according to sociodemographic characteristics (n=510)|
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[Table 2] showed that out of the study population, most of them 301 (59%) had a normal BMI followed by 135 (26.5%) overweight. Least number of study population, i.e., 20 (3.9%) fall in the obese category. Again, by WHO cutoffs for Asians, most of the study participants, i.e., 187 (36.7%) had a normal BMI followed by 155 (30.4%) obese. Least number of study population, i.e., 54 (10.6%) fall in the underweight category.
|Table 2: Distribution of the study population according to obesity body mass index (n=510)|
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The mean body weight of the study population was 56.9 ± 9.9 kg with a range between 30 and 114 kg and mean body height was 156.4 ± 9.5 cm having a range of 124–188 cm. Mean BMI was 23.4 ± 4.1.
[Table 3] showed that most of the study population (62.7% males vs. 92.3% females) had abdominal obesity as per WHR. The mean body WC of the study population was 83.9 ± 10.8 cm with a range between 57 and 122 cm and mean hip circumference was 92.1 ± 9.6 cm having a range of 60–121 cm. With WC and WHR cutoffs, abdominal obesity was observed among 46.5% and 78.6% of the participants. Almost two-thirds (68.2%) of the females were having more WC as compared to one-fifth males (21.2%). Overall, central obesity was more common among females.
|Table 3: Distribution of the study population according to overweight/obesity and Central Obesity (n=510)|
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[Table 4] showed that the prevalence of obesity was more among the age group of 30–40 years (26.4%) and 20–30 and 40–50 years (each group, 25.3%), and this difference in prevalence of obesity with respect to various age groups was found statistically significant (χ2 = 22.457; d.f. = 4; P < 0.001). Again, female participants were predominantly obese (58%) than males (42%) which was statistically significant (χ2 = 4.169; d.f. = 1; P < 0.05). Higher prevalence of obesity was seen among participants belonging to Hindu religion (87%) and general caste (48%); these associations were statistically significant (P < 0.05). Participants residing in a joint family were more obese (52%) in comparison to those living in nuclear families (48%) which was statistically significant (χ2 = 11.739; d.f. = 1; P < 0.001); interestingly, those living in pakka house (19.3%) were less obese than those living in kaccha (25.3%) or mixed (55.4%) type of houses, but this association was not statistically significant (χ2 = 2.221; d. f. = 2; P > 0.05). More obese persons were seen among currently married (84.8%) than widow/widower (4.1%) and never married (11.1%); this association was found statistically significant (χ2 = 10.326; d.f. = 3; P < 0.01). Nonworking group of participants was more obese than working group (58.4% vs. 41.6%), but the association was not found statistically significant (P > 0.05). Those having family history of NCD were less obese (29%) than others (71%) without any family history, and surprisingly, this association was found statistically significant (χ2 = 6.783; d.f. = 1; P < 0.001). Participants from lower socioeconomic status were more obese (56.5% and 37.9% in Class V and Class IV), but the association was not significant statistically (P > 0.05). Less overweight/obesity was seen among those having habit of consumption of alcohol (5.2%) and tobacco (20.4%), but no statistical significance (P > 0.05) was found.
|Table 4: Distribution of the overweight/obesity and nonoverweight study participants according to sociodemographic and behavioral characteristics (n=510)|
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| Discussion|| |
The present cross-sectional study was conducted among 510 adults to explore the prevalence of overweight and/or obesity in the rural population of Bengal. As per the WHO BMI guidelines for Asians, overall prevalence of obesity was 30.4% among adults and prevalence of overweight was 22.4% as per the study population. In rural India, recent developmental changes in the form of better transport, electricity, and mechanized cultivation have greatly influenced the day-to-day lifestyle of the rural people which is giving rise increase burden of overweight/obesity. The prevalence of overweight and/or obesity (52.4%) observed in this study was higher than some previous study by Chauhan et al. in a rural coastal area in South India, Kumar et al. in rural Meerut, Shrivastava et al. in rural Pondicherry, Sen et al., and Gothankar but lower than some other studies done in a rural area in Trivandrum by Anil Bindhu et al., in rural USA by Befort et al., and in rural Sri Lankan adults by Katulanda et al. The diversity in prevalence was due to varying age groups taken for different studies, different criteria and methodologies adopted for defining obesity, and difference between racial subgroups related to geographic, dietary, and cultural factors in different study setting.
Our study showed that in the lower (20–30 years) and middle age (30–40, 40–50 years) group, more participants were overweight and/or obese similar to the findings with some recent studies by Shrivastava et al., Sen et al., and Katulanda et al., but higher (50–59 years) age group was found more obese by Kumar et al. in rural Meerut.
The present study showed that 46.5% were centrally obese, whereas relatively lower prevalence (26.2%) of overweight and obesity, particularly abdominal obesity, was seen among adults in Sri Lanka. Among adults who are found to be having normal BMI (<23), 29.2% had high WC than recommended for Asians.
In this study, we observed that the overweight and/or obesity was more among females (56.9%) than males (47.9%) which was statistically significant and was similar with some recent studies done by Kumar et al., Sen et al., Anil Bindhu et al., and Katulanda et al. (P < 0.05) but did not match with few other studies by Chauhan et al. where results showed slightly higher prevalence in males. Binu and Harnagle found increased prevalence of overweight among females and obesity among males in elderly population of rural area of Kerala. Female participants were more centrally obese (92.3% by WHR and 68.2% by WC) than males (62.7% by WHR and 21.2% by WC) in this current study which was similar to the findings by Chauhan et al. and Anil Bindhu et al.
Hindus were more overweight and/or obese than Muslim which was found statistically significant (P < 0.01). Almost half (48%) of the overweight and/or obesity individuals were from general caste than scheduled caste and other backward castes (P < 0.01) similar to Kumar et al. in rural Meerut and Little among adults in a population of rural South India.
Almost all lower socioeconomic groups (Class IV and V) were obese followed by 4.5% in Class III, but the association between socioeconomic status and overweight and/or obesity was not statistically significant, whereas Sen et al. found higher odds (2.99, 95% confidence interval [CI]: 2.07–4.32, P < 0.05) of obesity with family income ≥Rs. 10,000/month. Higher income predicted obesity occurrence substantially as per Shrivastava et al. Rathi et al. found that females with lower socioeconomic status were lean than females with higher socioeconomic status. The present study showed that majority residing in mixed type of house were overweight/obese (P > 0.05) similar to Little et al. among adults in a population of rural South India (P < 0.05).
Majority of the overweight and/or obesity (84.5%) participants were found among currently married persons followed by never married and widow/widower which was found statistically significant (P < 0.01) similar to Kumar et al., Sen et al., and Befort et al.
There was no significant association between education level and overweight and/or obesity (P > 0.05). In contrast, Shrivastava et al. and Katulanda et al. showed that higher education was associated with overweight and obesity.
Overweight and/or obesity (58.4%) was found more among nonworking group than working population which was not statistically significant (P < 0.05), but this finding did not match with that of Shrivastava et al. might be due to use of different classification of occupation-based activities in a different setting. Binu and Harnagle found that obesity was more (20%) in unemployed persons (P > 0.05) similar to the current study.
Overweight and/or obesity was found more (52%) in those study participants who were from joint family (P < 0.05) whereas Sen et al. found higher odds (1.40, 95% CI: 1.01–16, P < 0.05) of obesity in joint families. This current study finding was similar with the studies by Kumar et al. where the prevalence of overweight and obesity in persons belonging to nuclear and joint families was 16.5% and18.2%, respectively.
In the present study, majority (71%) of the overweight and/or obese participants did not have any family history of NCD (P < 0.01); Shrivastava et al. found that individuals with family history of Type 2 diabetes mellitus had 2.25 times chance of being obese (P < 0.001).
The current study found that less overweight/obesity was seen among those having habit of consumption of alcohol and smoking, but no statistical significance (P > 0.05) was found which was similar to the findings by Anil Bindhu et al. Kumar et al. showed more overweight/obesity among alcoholics (18.6%) while smokers were having lower prevalence of overweight (10.6%).
| Conclusion|| |
The study revealed that obesity is an important public health problem in the adults of rural area of West Bengal with overall prevalence of obesity and overweight in a rural population of Singur, West Bengal, 30.4% and 22.4%, respectively. The prevalence of central obesity was also very high, even prevalent among those with normal BMI. The burden of obesity on health care system will be very high, due to its long-term consequences. Prevention of overweight and obesity has to be recognized as a public health priority in the form of awareness generation among rural population, addressing the importance of changing lifestyle, promotion of physical activity, and yoga in daily life to maintain health.
Authors would like to thank all the participants who consented to participate in the study. Authors also thank the health workers, ASHA who helped in collecting data.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4]