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Does living in slums or non-slums influence women's nutritional status? Evidence from Indian mega-cities

Listed author(s):
  • Gaur, Kirti
  • Keshri, Kunal
  • Joe, William
Registered author(s):

    This article examines the intra-city distribution of women's nutritional status across eight Indian mega-cities with a specific focus on slum–non-slum divide. The analysis is based on the National Family Health Survey (2005–06) of India and highlights the dual burden of malnutrition among urban women. The results show that one in every two women in mega-cities is malnourished (either undernourished or overnourished), but a biased, analytical focus on citywide averages conceals the nature of the problem. Overnutrition among women is notably higher in non-slum areas whereas underweight persists as a key concern among slum dwellers. Cities located in the Central India (Nagpur and Indore) have the highest proportion of underweight women whereas the cities in South India (Chennai and Hyderabad) show a high prevalence of overweight women across both slum and non-slum areas. The intensity of income-related inequalities in underweight outcome is much greater for non-slum areas, whereas inequalities in overweight outcomes are higher among slums. Furthermore, regression analysis indicates that place of residence as such has no significant impact on women's nutritional status and that this elementary association is primarily a ramification mediated through other key socioeconomic correlates. Results suggest that, it would be rational to develop a comprehensive urban nutritional plan that focuses on dietary planning and behaviour change to address both type of malnutrition at the same time.

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    Article provided by Elsevier in its journal Social Science & Medicine.

    Volume (Year): 77 (2013)
    Issue (Month): C ()
    Pages: 137-146

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    Handle: RePEc:eee:socmed:v:77:y:2013:i:c:p:137-146
    DOI: 10.1016/j.socscimed.2012.11.017
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    1. Wagstaff, Adam & Paci, Pierella & van Doorslaer, Eddy, 1991. "On the measurement of inequalities in health," Social Science & Medicine, Elsevier, vol. 33(5), pages 545-557, January.
    2. Deon Filmer & Lant Pritchett, 2001. "Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 115-132, February.
    3. Robert, Stephanie A. & Reither, Eric N., 2004. "A multilevel analysis of race, community disadvantage, and body mass index among adults in the US," Social Science & Medicine, Elsevier, vol. 59(12), pages 2421-2434, December.
    4. Harrington, Daniel W. & Elliott, Susan J., 2009. "Weighing the importance of neighbourhood: A multilevel exploration of the determinants of overweight and obesity," Social Science & Medicine, Elsevier, vol. 68(4), pages 593-600, February.
    5. Cohen, Deborah A. & Finch, Brian K. & Bower, Aimee & Sastry, Narayan, 2006. "Collective efficacy and obesity: The potential influence of social factors on health," Social Science & Medicine, Elsevier, vol. 62(3), pages 769-778, February.
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