Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-25T14:05:49.990Z Has data issue: false hasContentIssue false
  • English
  • Français

Livelihoods, nutrition and health in Dhaka slums

Published online by Cambridge University Press:  22 December 2006

Jane A Pryer ,
Stephen Rogers ,
Charles Normand  and
Ataur Rahman
Jane A Pryer*
Affiliation:
Royal Free and University College Medical School, University College London, Department of Primary Care and Population Sciences, Royal Free Campus, Rowland Hill Street, London NW3 2PF, UK
Stephen Rogers
Affiliation:
Royal Free and University College Medical School, University College London, Department of Primary Care and Population Sciences, Royal Free Campus, Rowland Hill Street, London NW3 2PF, UK
Charles Normand
Affiliation:
London School of Hygiene and Tropical Medicine, University of London, Health Services Research Unit, London, UK
Ataur Rahman
Affiliation:
Institute for Policy Analysis and Advocacy, Proshika, Dhaka, Bangladesh
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract:

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objectives:

To identify groups within Dhaka slums that report similar patterns of livelihood, and to explore nutritional and health status.

Design:

A random sample of households participated in a longitudinal study in 1995–1997. Socio-economic and morbidity data were collected monthly by questionnaire and nutritional status was assessed. Cluster analysis was used to aggregate households into livelihood groups.

Setting:

Dhaka slums, Bangladesh.

Subjects:

Five-hundred and fifty-nine households.

Main outcome measures: Socio-economic and demographic variables, nutritional status, morbidity.

Results:

Four livelihood groups were identified. Cluster 1 (n = 178) was the richest cluster with land, animals, business assets and savings. Loans as well as income were higher, which shows that this group was credit-worthy. The group was mainly selfemployed and worked more days per month than the other clusters. The cluster had the second highest body mass index (BMI) score, and the highest children's nutrition status. Cluster 2 (n = 190) was a poor cluster and was mainly dependent selfemployed. Savings and loans were lower. Cluster 3 (n = 124) was the most vulnerable cluster. Members of this group were mainly casual unskilled, and 40% were femaleheaded households. Total income and expenditure were lowest amongst the clusters. BMI and children's nutritional status were lowest in the slum. Cluster 4 (n = 67) was the second richest cluster. This group comprised skilled workers. BMI was the highest in this cluster and children's nutritional status was second highest.

Conclusions:

Cluster analysis has identified four groups that differed in terms of socioeconomic, demographic and nutritional status and morbidity. The technique could be a practically useful tool of relevance to the development, monitoring and targeting of vulnerable households by public policy in Bangladesh.

Keywords

Cluster analysisLivelihood groupSocio-economic profileNutritional statusMorbidity
Type
Research Article
Information
Public Health Nutrition , Volume 5 , Issue 5 , December 2002 , pp. 613 - 618
Copyright
Copyright © CABI Publishing 2002

References

1Pryer, JA. Socio-economic and environmental aspects of undernutrition and ill-health in an urban slum in Bangladesh. PhD Thesis, University of London, London, 1990.Google Scholar
2Huttly, SRA, Victora, CG, Barros, FC, Teixeira, AMB, Vaughn, PJ. The timing of nutritional status determination: implications for interventions and growth monitoring. Eur. J. Clin. Nutr. 1991;45:85–95.Google ScholarPubMed
3Jongpiputvanich, S, Poomsuwan, P, Phittayanon, P. Prevalence and risk factors of protein energy malnutrition (PEM) in preschool children of Klong-Toey Slum, Bankok, Thailand. J. Med. Assoc. Thailand 1992;75(1):39–44.Google Scholar
4Khin-Maung, U, Khin, M, Wai, NN, Hman, NW, Myint, TT, Butler, T. Risk factors for the development of persistent diarrhoea and malnutrition in Burmese children. Int. J. Epidemiol. 1992;21(5):1021–9.CrossRefGoogle Scholar
5Engle, PL. Influences of mother's and father's income on children's nutritional status in Guatemala. Soc. Sci. Med. 1993;37(11):1303–12.Google Scholar
6Ricca, JA, Becker, S. Risk factors for wasting and stunting among children in Metro Cebu, Philippines. Am. J. Clin. Nutr. 1996;63:966–75.CrossRefGoogle Scholar
7Mbago, MCY, Namfua, PP. Some determinants of nutritional status of one- to four old children in low income areas in Tanzania. J. Trop. Paediat. 1992;38:299–306.Google Scholar
8Defo, BK, Young, TB. Correlates of malnutrition among children under 2 years of age admitted to hospital in Yaounde, Cameroon. J. Trop. Paediat. 1993;39:68–75.Google Scholar
9Madzingira, N. Malnutrition in children under five in Zimbabwe: effects of social-economic factors and disease. Soc. Biol. 1995;42(3–4):239–46.CrossRefGoogle Scholar
10Doan, RM, Bishatarat, L. Female autonomy and child nutritional status: the extended family residential unit in Amman. Soc. Sci. Med. 1990;31(7):783–9.CrossRefGoogle ScholarPubMed
11Lima, M, Figuira, MD, Ebrahim, GJ. Malnutrition among children of adolescent mothers in a squatter community of Redclife, Brazil. J. Trop. Paediat. 1990;36:14–9.Google Scholar
12Rao, KV, Balakrishna, N. Discriminant function analysis: a case study of some socio-economic constraints on child nutrition. Indian J. Med. Res. 1990;92:66–71.Google Scholar
13Engle, PL. Maternal work and child care strategies in periurban Guatemala: nutritional effects. Child Dev. 1991;62(5):954–65.Google Scholar
14Islam, MA, Rahman, MM, Mahalanabis, D. Maternal and socioeconomic factors and the risk of a severe malnutrition in a child: a case–control study. Eur. J. Clin. Nutr. 1994;48:416–24.Google Scholar
15Thaver, IH, Ebrahim, GJ, Richardson, R. Infant mortality and undernutrition in the squatter settlements of Karachi. J. Trop. Paediat. 1990;36:135–40.CrossRefGoogle ScholarPubMed
16Ramphlele, MA, Helap, M, Trollip, DK. Health status of hostel dwellers, part iii. Nutritional status of children 0–5 years. S. Afr. Med. J. 1991;79:705–9.Google Scholar
17Harpham, T, Lusty, T, Vaughan, P. The Shadow of the City: Community Health and the Urban Poor. Oxford: Oxford Medical Publications, 1988.Google Scholar
18Hariss, B, Gillespie, S, Pryer, J. Poverty and malnutrition at extremes of South Asian food systems. Economic and Political Weekly 1990;2783–99.Google Scholar
19Pryer, J. Nutritionally vulnerable households in the urban slum economy: a case study from Khulna, Bangladesh. In: Schell, LM, Smith, M, Bilsborough, A, eds. Urban Ecology and Health in the Third World. Cambridge: Cambridge University Press, 1993.Google Scholar
20Government of Bangladesh. Report of the Task Forces on Bangladesh Development Strategies for the 1990s. Vol. 3. Developing the Infrastructure. Dhaka: Government of Bangladesh, 1992.Google Scholar
21World Bank. Entering the 21st Century. World Development Report, 1999/2000. Oxford: Oxford University Press, 1999.Google Scholar
22Islam, N, ed. Addressing the Urban Poverty Agenda in Bangladesh. Dhaka: Asian Development Bank/University Press Ltd, 1997.Google Scholar
23Everitt, B. Cluster Analysis. London: Heineman Educational Books, 1980.Google Scholar
24Blashfield, RK. Mixture models tests of cluster analysis: accuracy of four agglomerative hierarchical methods. Psychol. Bull. 1979;83(3):377–88.Google Scholar
25Aldenderfer, MS, Blashfield, RK. Cluster Analysis. Quantitative Applications in Social Sciences Series. London: Sage Publications, 1984.CrossRefGoogle Scholar
26Armitage, P. Statistical Methods in Medical Research. Oxford: Blackwell, 1983.Google Scholar
27Centre for Urban Studies. The Urban Poor in Bangladesh. Dhaka: Department of Geography, University of Dhaka, 1989.Google Scholar
28Miah, MAQ, Weber, KE, Islam, N. Upgrading a Bustee Settlement in Bangkok, Thailand. Bangkok: Division of Human Settlements, Asian Institute of Technology, 1988.Google Scholar
29Madjumder, PP, Mamud, S, Asfar, R. Squatter Life in the Agargoan Area. Dhaka: Bangladesh Institute of Development Studies, 1989.Google Scholar
30Ecob, R, Davey Smith, G. Income and health: what is the nature of the relationship? Soc. Sci. Med. 1999;48:693–705.Google Scholar
31Vagero, D. Health inequalities as a policy issues – reflections on ethics, policy and public health. Sociol. Health Illness 1995;17(1):1–19.Google Scholar
32Kanbur, SMR. Malnutrition and poverty in Latin America. In: Dreze, J, Sen, A, eds. Endemic Hunger. Vol.3. Oxford: Oxford Press, 1991.Google Scholar
33Townsend, P, Davidson, N, eds. The Black Report. London: Penguin Books, 1990.Google Scholar
34De Vasconcellos, MTL. Body mass index: its relationship with food consumption and socio-economic variables in Brazil. Eur. J. Clin. Nutr. 1994;3(Suppl. 3):S115–23.Google Scholar
35Delpeuch, A, Cornu, JP, Massamba, P, Trissac, P, Maire, B.Is body mass index sensitively related to socio-economic status and economic adjustment? A case from the Congo. Eur. J. Clin. Nutr. 1994;48(Suppl. 3):S148–54.Google ScholarPubMed