Relative contribution of diet and physical activity to increased adiposity among rural to urban migrants in India: A cross-sectional study
Autoři:
Sanjay Kinra aff001; Poppy Alice Carson Mallinson aff001; Jenny A. Cresswell aff001; Liza J. Bowen aff001; Tanica Lyngdoh aff002; Dorairaj Prabhakaran aff002; Kolli Srinath Reddy aff002; Mario Vaz aff003; Anura V. Kurpad aff003; George Davey Smith aff004; Yoav Ben-Shlomo aff004; Shah Ebrahim aff001
Působiště autorů:
Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
aff001; Public Health Foundation of India, New Delhi, India
aff002; St John’s Research Institute, St John’s National Academy of Health Sciences, Bangalore, India
aff003; Population Health Sciences, University of Bristol, Bristol, United Kingdom
aff004; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
aff005
Vyšlo v časopise:
Relative contribution of diet and physical activity to increased adiposity among rural to urban migrants in India: A cross-sectional study. PLoS Med 17(8): e32767. doi:10.1371/journal.pmed.1003234
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pmed.1003234
Souhrn
Background
In common with many other low- and middle-income countries (LMICs), rural to urban migrants in India are at increased risk of obesity, but it is unclear whether this is due to increased energy intake, reduced energy expenditure, or both. Knowing this and the relative contribution of specific dietary and physical activity behaviours to greater adiposity among urban migrants could inform policies for control of the obesity epidemic in India and other urbanising LMICs. In the Indian Migration Study, we previously found that urban migrants had greater prevalence of obesity and diabetes compared with their nonmigrant rural-dwelling siblings. In this study, we investigated the relative contribution of energy intake and expenditure and specific diet and activity behaviours to greater adiposity among urban migrants in India.
Methods and findings
The Indian Migration Study was conducted between 2005 and 2007. Factory workers and their spouses from four cities in north, central, and south of India, together with their rural-dwelling siblings, were surveyed. Self-reported data on diet and physical activity was collected using validated questionnaires, and adiposity was estimated from thickness of skinfolds. The association of differences in dietary intake, physical activity, and adiposity between siblings was examined using multivariable linear regression. Data on 2,464 participants (median age 43 years) comprised of 1,232 sibling pairs (urban migrant and their rural-dwelling sibling) of the same sex (31% female) were analysed. Compared with the rural siblings, urban migrants had 18% greater adiposity, 12% (360 calories/day) more energy intake, and 18% (11 kilojoules/kg/day) less energy expenditure (P < 0.001 for all). Energy intake and expenditure were independently associated with increased adiposity of urban siblings, accounting for 4% and 6.5% of adiposity difference between siblings, respectively. Difference in dietary fat/oil (10 g/day), time spent engaged in moderate or vigorous activity (69 minutes/day), and watching television (30 minutes/day) were associated with difference in adiposity between siblings, but no clear association was observed for intake of fruits and vegetables, sugary foods and sweets, cereals, animal and dairy products, and sedentary time. The limitations of this study include a cross-sectional design, systematic differences in premigration characteristics of migrants and nonmigrants, low response rate, and measurement error in estimating diet and activity from questionnaires.
Conclusions
We found that increased energy intake and reduced energy expenditure contributed equally to greater adiposity among urban migrants in India. Policies aimed at controlling the rising prevalence of obesity in India and potentially other urbanising LMICs need to be multicomponent, target both energy intake and expenditure, and focus particularly on behaviours such as dietary fat/oil intake, time spent on watching television, and time spent engaged in moderate or vigorous intensity physical activity.
Klíčová slova:
Adipose tissue – Bioenergetics – Diet – Food – India – Obesity – Physical activity – Urban environments
Zdroje
1. Luhar S, Mallinson PAC, Clarke L, Kinra S. Trends in the socioeconomic patterning of overweight/obesity in India: a repeated cross-sectional study using nationally representative data. BMJ Open. 2018;8. doi: 10.1136/bmjopen-2018-023935 30344181
2. Prentice AM. The emerging epidemic of obesity in developing countries. Int J Epidemiol. 2006;35: 93–99. doi: 10.1093/ije/dyi272 16326822
3. Fall CHD. Non-industrialised countries and affluence: Relationship with Type 2 diabetes. Br Med Bull. 2001;60: 33–50. doi: 10.1093/bmb/60.1.33 11809617
4. Office of the Registrar General & Census Commissioner India. Census of India Website. Available from: http://censusindia.gov.in/. [cited 10 Feb 2020].
5. Sobngwi E, Mbanya J-C, Unwin NC, Porcher R, Kengne A-P, Fezeu L, et al. Exposure over the life course to an urban environment and its relation with obesity, diabetes, and hypertension in rural and urban Cameroon. Int J Epidemiol. 2004;33: 769–776. doi: 10.1093/ije/dyh044 15166209
6. Kinra S, Andersen E, Ben-Shlomo Y, Bowen L, Lyngdoh T, Prabhakaran D, et al. Association Between Urban Life-Years and Cardiometabolic Risk: The Indian Migration Study. Am J Epidemiol. 2011;174: 154–164. doi: 10.1093/aje/kwr053 21622949
7. Khandelwal S, Reddy KS. Eliciting a policy response for the rising epidemic of overweight-obesity in India. Obes Rev. 2013;14: 114–125. doi: 10.1111/obr.12097 24103051
8. Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants. The Lancet. 2016;387: 1377–1396. doi: 10.1016/S0140-6736(16)30054-X
9. Kuh D, Ben-Shlomo Y. Geography and migration with special reference to cardiovascular disease. A lifecourse approach to chronic disease epidemiology. Oxford: Oxford University Press, 2004.
10. Commentary: Beyond urban–rural comparisons: towards a life course approach to understanding health effects of urbanization. Int J Epidemiol. 2004;33: 777–78. doi: 10.1093/ije/dyh161 15166197
11. He J, Klag MJ, Wu Z, Qian MC, Chen JY, Mo PS, et al. Effect of migration and related environmental changes on serum lipid levels in southwestern Chinese men. Am J Epidemiol. 1996;144: 839–848. doi: 10.1093/oxfordjournals.aje.a009018 8890662
12. Creber RMM, Smeeth L, Gilman RH, Miranda JJ. Physical activity and cardiovascular risk factors among rural and urban groups and rural-to-urban migrants in Peru: a cross-sectional study. Rev Panam Salud Publica Pan Am J Public Health. 2010;28: 1–8.
13. Gregory CO, Dai J, Ramirez-Zea M, Stein AD. Occupation is More Important than Rural or Urban Residence in Explaining the Prevalence of Metabolic and Cardiovascular Disease Risk in Guatemalan Adults. J Nutr. 2007;137: 1314–1319. doi: 10.1093/jn/137.5.1314 17449598
14. Rosenkranz RR, Dzewaltowski DA. Model of the home food environment pertaining to childhood obesity. Nutr Rev. 2008;66: 123–140. doi: 10.1111/j.1753-4887.2008.00017.x 18289177
15. Birch LL. Development of food preferences. Annu Rev Nutr. 1999;19: 41–62. doi: 10.1146/annurev.nutr.19.1.41 10448516
16. Reddon H, Guéant J-L, Meyre D. The importance of gene–environment interactions in human obesity. Clin Neurosci Res. 2016;130: 1571–1597. doi: 10.1042/CS20160221 27503943
17. Lyngdoh T, Kinra S, Shlomo YB, Reddy S, Prabhakaran D, Smith GD, et al. Sib-recruitment for studying migration and its impact on obesity and diabetes. Emerg Themes Epidemiol. 2006;3: 2. doi: 10.1186/1742-7622-3-2 16533387
18. Ebrahim S, Kinra S, Bowen L, Andersen E, Ben-Shlomo Y, Lyngdoh T, et al. The Effect of Rural-to-Urban Migration on Obesity and Diabetes in India: A Cross-Sectional Study. PLoS Med. 2010;7: e1000268. doi: 10.1371/journal.pmed.1000268 20436961
19. Bowen L, Bharathi AV, Kinra S, DeStavola B, Ness A, DM SE. Development and evaluation of a semi-quantitative food frequency questionnaire for use in urban and rural India. Asia Pac J Clin Nutr. 2012;21: 355–60. 22705424
20. National Institute of Nutrition (India), Gopalan C, Rama Sastri BV, Balasubramanian SC. Nutritive value of Indian foods. Hyderabad, India: National Institute of Nutrition, Indian Council of Medical Research; 1971.
21. Agriculture Research Service. Washington: United States Department of Agriculture. Available from: https://www.ars.usda.gov/research/publications/publication/?seqNo115=199178. [cited 30 Apr 2020].
22. Holland B, Welch AA, Unwin ID, Buss DH, Paul AA, Southgate D a. T. McCance and Widdowson’s The Composition of Foods (5th edition). London: Royal Society of Chemistry, 1991.
23. Sullivan R, Kinra S, Ekelund U, AV B, Vaz M, Kurpad A, et al. Evaluation of the Indian Migration Study Physical Activity Questionnaire (IMS-PAQ): a cross-sectional study. Int J Behav Nutr Phys Act. 2012;9: 13. doi: 10.1186/1479-5868-9-13 22321669
24. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of Physical Activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32: S498. doi: 10.1097/00005768-200009001-00009 10993420
25. Human energy requirements. Scientific background papers from the Joint FAO/WHO/UNU Expert Consultation. October 17–24, 2001. Rome, Italy. Public Health Nutr. 2005;8: 929–1228. doi: 10.1079/phn2005778 16277811
26. Vaz M, Karaolis N, Draper A, Shetty P. A compilation of energy costs of physical activities. Public Health Nutr. 2005;8: 1153–1183. doi: 10.1079/phn2005802 16277826
27. Bharathi AV, Sandhya N, Vaz M. The development & characteristics of a physical activity questionnaire for epidemiological studies in urban middle class Indians. Indian J Med Res. 2000;111: 95–102. 10937385
28. Conway JM. Human Energy Requirements: A Manual for Planners and Nutritionists. Am J Clin Nutr. 1991;53: 1506–1506. doi: 10.1093/ajcn/53.6.1506
29. Pate RR, Pratt M, Blair SN, Haskell WL, Macera CA, Bouchard C, et al. Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA. 1995;273: 402–407. doi: 10.1001/jama.273.5.402 7823386
30. Indian Institute of Population Sciences. National Family Health Survey 2. Mumbai: IIPS, 2000. Available from: http://rchiips.org/nfhs/volume_2.shtml. [cited 6 Apr 2020].
31. Kuriyan R, Petracchi C, Ferro-Luzzi A, Shetty PS, Kurpad AV. Validation of expedient methods for measuring body composition in Indian adults. Indian J Med Res. 1998;107: 37–45. 9529779
32. Oyebode O, Pape UJ, Laverty AA, Lee JT, Bhan N, Millett C. Rural, Urban and Migrant Differences in Non-Communicable Disease Risk-Factors in Middle Income Countries: A Cross-Sectional Study of WHO-SAGE Data. PLoS ONE. 2015;10: e0122747. doi: 10.1371/journal.pone.0122747 25849356
33. Food and Nutrition in India: Facts and Interpretations. Econ Polit Wkly. 2015; 7–8.
34. Mohan V, Mathur P, Deepa R, Deepa M, Shukla DK, Menon GR, et al. Urban rural differences in prevalence of self-reported diabetes in India—The WHO–ICMR Indian NCD risk factor surveillance. Diabetes Res Clin Pract. 2008;80: 159–168. doi: 10.1016/j.diabres.2007.11.018 18237817
35. Mackenbach JD, Rutter H, Compernolle S, Glonti K, Oppert J-M, Charreire H, et al. Obesogenic environments: a systematic review of the association between the physical environment and adult weight status, the SPOTLIGHT project. BMC Public Health. 2014;14. doi: 10.1186/1471-2458-14-233 24602291
36. Carles Milà, Otavio Ranzani, Margaux Sanchez, Albert Ambrós, Santhi Bhogadi, Sanjay Kinra, et al. Land-Use Change and Cardiometabolic Risk Factors in an Urbanizing Area of South India: A Population-Based Cohort Study. Environ Health Perspect. 128: 047003. doi: 10.1289/EHP5445 32243204
37. Siegel K, Narayan KMV, Kinra S. Finding A Policy Solution To India’s Diabetes Epidemic. Health Aff (Millwood). 2008;27: 1077–1090. doi: 10.1377/hlthaff.27.4.1077 18607043
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