Hostname: page-component-848d4c4894-4rdrl Total loading time: 0 Render date: 2024-06-25T16:54:00.706Z Has data issue: false hasContentIssue false
  • English
  • Français

SELF-REPORTED MORBIDITY AND BURDEN OF DISEASE IN UTTAR PRADESH, INDIA: EVIDENCE FROM A NATIONAL SAMPLE SURVEY AND THE MILLION DEATHS STUDY

Published online by Cambridge University Press:  05 October 2015

Ajit Kumar Yadav ,
Jitendra Gouda  and
F. Ram
Ajit Kumar Yadav*
Affiliation:
International Institute for Population Sciences, Deonar, Mumbai, India
Jitendra Gouda
Affiliation:
International Institute for Population Sciences, Deonar, Mumbai, India
F. Ram
Affiliation:
International Institute for Population Sciences, Deonar, Mumbai, India
*
1Corresponding author. Email: ajitkumaryadav1989@gmail.com
Get access Rights & Permissions [Opens in a new window]

Summary

Uttar Pradesh is India’s most populous state with a population of 200 million. Any change in its fertility and mortality is bound to bring change at the national level. This study analysed the burden of disease in the state by calculating the disability-adjusted life year (DALY) for infectious and non-communicable diseases. Data were from two rounds (52nd and 60th) of the National Sample Survey Organization (NSSO) survey conducted in 1995–96 and 2004, respectively, and the Million Deaths Study (MDS) of 2001–03. Descriptive and multivariate analyses were carried out to identify the determinants of different types of self-reported morbidity and DALY. The results show that in Uttar Pradesh the prevalence of all selected self-reported infectious and non-communicable diseases increased over the study period from 1995 to 2004, and in most cases by more than two times. The highest observed increase in prevalence was in non-communicable diseases excluding CVDs, which increased from 7% in 1995 to 19% in 2004. The prevalence was higher for those aged 60 and above, females, those who were illiterate and rich across the time period and for all selected morbidities. The results were significant at p<0.001. The estimation of the DALY revealed that the burden of infectious diseases was higher during infancy, noticeably among males than females in 2002. However, females aged 1–5 years were more likely to report infectious diseases than corresponding males. The age distribution of the DALY indicated that individuals aged below 5 years and above 60 years were more susceptible to ill health. The growing incidence of non-communicable diseases, especially among the older generation, puts an additional burden on the health system in the state. Uttar Pradesh has to grapple with the unresolved problem of preventable infectious diseases on the one hand and the growth in non-communicable disease on the other.

Type
Research Article
Information
Journal of Biosocial Science , Volume 48 , Issue 4 , July 2016 , pp. 472 - 485
Copyright
Copyright © Cambridge University Press, 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agrawal, G. & Arokiasamy, P. (2009) Morbidity prevalence and healthcare utilization among older adults. Indian Journal of Applied Gerontology 29(2), 155–179.Google Scholar
Allen, W. R. (1995) African American family life in societal context: crisis and hope. In Sociological Forum. Vol. 10, No. 4. Kluwer Academic Publishers, Plenum Publishers, pp. 569–592.Google Scholar
Andre, C., Velasquez, M. & Mazur, T. (1993) Voluntary Health Risks: Who Should Pay? URL: https://www.scu.edu/ethics/publications/lie/v6n1/voluntary.html Google Scholar
Baker, J. L. (2008) Urban Poverty: A Global View. World Bank, Washington, DC.Google Scholar
Burström, B. (2012) Commentary: self-rated health and mortality in low income settings. International Journal of Epidemiology 41(6), 1727–1728.Google Scholar
Buvinic, M., Médici, A., Fernández, E. & Torres, A. C. (2006) Gender differentials in health. In Jamison, D. T., Breman, J. G., Measham, A. R., Alleyne, G., Claeson, M. et al. (eds) Disease Control Priorities in Developing Countries, 2nd edition. World Bank, Washington, DC, pp. 195–210.Google Scholar
Diamond-Smith, N. & Bishai, D. (2014) Evidence of self-correction of child sex ratios in India: a district-level analysis of child sex ratios from 1981 to 2011. Demography 52(2), 641–646.Google Scholar
Dyson, T. & Moore, M. (1983) On kinship structure, female autonomy, and demographic behavior in India. Population and Development Review 9(1), 35–60.CrossRefGoogle Scholar
Ezeamama, A. E., Viali, S., Tuitele, J. & McGarvey, S. T. (2006) The influence of socioeconomic factors on cardiovascular disease risk factors in the context of economic development in the Samoan archipelago. Social Science & Medicine 63(10), 2533–2545.CrossRefGoogle ScholarPubMed
Forastieri, V. (1999) Improvement of working conditions and environment in the informal sector through safety and health measures. Occupational Safety and Health Branch Working Paper, OH/9907/08. ILO Geneva.Google Scholar
Ghosh, S. & Arokiasamy, P. (2010) Emerging patterns of reported morbidity and hospitalization in west Bengal, India. Global Public Health 5(4), 427–440.Google Scholar
Gupte, M. D., Ramachandran, V. & Mutatkar, R. K. (2001) Epidemiological profile of India: historical and contemporary perspectives. Journal of Biosciences 26(4), 437–464.Google Scholar
Jacobs, B., Ir, P., Bigdeli, M., Annear, P. L. & Van Damme, W. (2012) Addressing access barriers to health services: an analytical framework for selecting appropriate interventions in low-income Asian countries. Health Policy and Planning 27(4), 288–300.Google Scholar
Kumar, P. & Kumar, A. (2012) Socioeconomic status and self rated health status of the elderly in rural Uttar Pradesh. Indian Journal of Preventive Medicine 43(3), 255–259.Google Scholar
Lozano, R. et al. (2013) Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet 380(9859), 2095–2128.Google Scholar
Madhavan, S., Adams, A. & Simon, D. (2003) Women’s networks and the social world of fertility behavior. International Family Planning Perspectives 29(2), 58–68.CrossRefGoogle ScholarPubMed
Mangen, M. J., Gibbons, C., Kretzschmar, M., de Wit, A., Havelaar, A., van Lier, A. & Rüütel, K. (2011) Current and Future Burden of Communicable Diseases in the European Union and EEA/EFTA Countries (BCoDE). Methodology protocol, ECDC Technical Report, ECDC, Stockholm.Google Scholar
Mathers, C. D., Boerma, T. & Fat, D. M. (2009) Global and regional causes of death. British Medical Bulletin 92, 7–32.CrossRefGoogle ScholarPubMed
Montgomery, M. R., Gragnolati, M., Burke, K. A. & Paredes, E. (2000) Measuring living standards with proxy variables. Demography 37(2), 155–174.Google Scholar
Musaiger, A. O., Hassan, A. S. & Obeid, O. (2011) The paradox of nutrition-related diseases in the Arab countries: the need for action. International Journal of Environmental Research and Public Health 8(9), 3637–3671.Google Scholar
National Sample Survey Organization (1998) Survey of Person Aged 60 Years and Above. NSS 52th round, July 1995–June 1996. Report No. 441, Ministry of Statistics and Programme Implementation, Government of India.Google Scholar
National Sample Survey Organization (2006) Morbidity, Health Care and the Condition of the Aged. NSS 60th round, January–June 2004. Report No. 507. Ministry of Statistics and Programme Implementation, Government of India.Google Scholar
Nongkynrih, B., Patro, B. K. & Pandav, C. S. (2004) Current status of communicable and non-communicable diseases in India. Journal of the Association of Physicians of India 52, 118–123.Google ScholarPubMed
Omran, A. R. (1971) The epidemiological transition: a theory of epidemiology of population change. Millbank Memorial Fund Quarterly XLIX(1), 599–638.Google Scholar
Prentice, A. M. (2006) The emerging epidemic of obesity in developing countries. International Journal of Epidemiology 35, 93–99.Google Scholar
Prinja, S., Jeet, G. & Kumar, R. (2012) Validity of self-reported morbidity. Indian Journal of Medical Research 136(5), 722.Google Scholar
RGI (1971a) Sample Registration System Based Abridged Life Tables. Office of RGI, New Delhi, India.Google Scholar
RGI (1971b) Sample Registration System Statistical Report 1970. Office of RGI & Census Commission of India, MOHA, Delhi.Google Scholar
RGI (2002) Sample Registration System Based Abridged Life Tables. Office of RGI, New Delhi, India.Google Scholar
RGI (2011) Sample Registration System Statistical Report 2011. Census commissioner of India, Ministry of Home Affairs (MOHA), Government of India.Google Scholar
RGI (2013a) Sample Registration System Based Abridged Life Tables. New Delhi, India.Google Scholar
RGI (2013b) Sample Registration System Statistical Report 2012. Office of RGI & Census Commission of India, MOHA, Delhi.Google Scholar
RGI (2013c) Sample Registration System Statistical Report 2005 & 2009. Office of RGI & Census Commission of India, MOHA, Delhi.Google Scholar
Saikia, N., Jasilionis, D., Ram, F. & Shkolnikov, V. M. (2010) Estimates of Mortality under Age 60 in India and its States, 1970–2004. MPIDR Technical Report TR-2010-006. Max Planck Institute for Demographic Research, Rostock. URL: http://www.demogr.mpg.de/papers/technicalreports/tr-2010-006.pdf Google Scholar
Selvaraj, S. & Karan, A. K. (2009) Deepening health insecurity in India: evidence from national sample surveys since 1980s. Economic and Political Weekly 44(4), 55–60.Google Scholar
Shah, B. & Mathur, P. (2010) Surveillance of cardiovascular disease risk factors in India: the need & scope. Indian Journal of Medical Research 132(5), 634.Google ScholarPubMed
Sinha, R. & Kapoor, A. K. (2010) Cultural practices and nutritional status among premenopausal women of urban setup in India. Open Anthropology Journal 3, 168–171.Google Scholar
Subramanian, S. V., Nandy, S., Irving, M., Gordon, D., Lambert, H. & Smith, G. D. (2006) The mortality divide in India: the differential contributions of gender, caste, and standard of living across the life course. American Journal of Public Health 96(5), 818.Google Scholar
Subramanian, S. V., Subramanyam, M. A., Selvaraj, S. & Kawachi, I. (2009) Are self-reports of health and morbidities in developing countries misleading? Evidence from India. Social Science & Medicine 68(2), 260–265.Google Scholar
Suryanarayana, M. H. (2012) Morbidity Profiles of Kerala and All-India: An Economic Perspective. Indira Gandhi Institute of Development Research, Mumbai.Google Scholar
Taylor, D. W. (2010) The Burden of Non-Communicable Diseases in India. Cameron Institute, Hamilton, ON. URL: http://www.cameroninstitute.com/wp-content/uploads/2014/11/044_The-burden-of-non-communicable-dieases-in-India.2010.pdf Google Scholar
Thankappan, K. R., Shah, B., Mathur, P., Sarma, P. S., Srinivas, G., Mini, G. K. & Vasan, R. S. (2010) Risk Factor Profile for Chronic Non-Communicable Diseases: Results of a Community-Based Study in Kerala, India. URL: http://imsear.hellis.org/handle/123456789/135407 Google Scholar
United Nations. (2012) Changing Levels and Trends in Mortality: the Role of Patterns of Death by Cause. Department of Economic and Social Affairs, Population Division, United Nations publication ST/ESA/SER.A/318.Google Scholar
WHO (2003) Gender, Health and Aging. Unit of Aging and Life Course at 20. Department of Gender and Women’s Health, Avenue Appia, Geneva, Switzerland.Google Scholar
WHO (2004) The Global Burden of Disease Concept. URL: http://www.who.int/quantifying_ehimpacts/publications/en/9241546204chap3.pdf Google Scholar
WHO (2009) Key Messages on Non-Communicable Diseases and Injuries which have Emerged from Discussions at ECOSOC During the First Half of 2009. URL: http://www.who.int/nmh/publications/ecosoc_summary_en.pdf Google Scholar
WHO (2012) International Classification of Diseases (ICD). WHO, Geneva.Google Scholar