Physiological Health and Wealth Status of Children in Thanjavur Corporation, Tamil Nadu, India-A Geo-Spatial Study

T. Ponnyin Selvi, S. Vadivel

Abstract


At every stage of life, health is robustly associated with socio-economic status such as income, educational attainment, and occupational prestige. These relationships evidencing that the children from low-income households weigh less at birth, are more likely to be born prematurely, and are increasingly at greater risk for chronic health conditions as they grow. Childhood health is in turn positively related to a number of later outcomes, including skills, scholastic achievement, and adult economic status. In adults, it is also a well-established fact that individuals with higher incomes enjoy better health outcomes.

Objectives: 1) To study the socio-economic and demographic profile of the children, 2) To identify the wealth and physiological health conditions of children and 3) To examine the spatial patterns of wealth and physiological characteristics of children in Thanjavur Corporation.

Sample: Stratified Random sampling method used for the present study. There are 51 wards, 24 children from each Wards aged between 0 to 6 years, totally 1224 children were selected from Thanjavur Corporation and they are the respondents for the present study.

Methodology: This study is based on the measurements of physiological characteristics such as children’s circumference of head, chest and waist hip, length of arm and leg, and their body weight and height. Body Mass Index (BMI) was calculated dividing weight and height meter square. Wealth index (WI) was also measured (Kuppuswamy. 2003) with reference to respondent’s family monthly income, educational status and occupation. Then the mean values are inserted in to the ArcGIS software and physiological and wealth index maps of children aged less than six years are generated. This spatial variations and relationships are proved by the Pearson Correlation. 

Conclusion: There is no significant relationship between the variable head circumference, chest circumference and waist-hip circumference with wealth index, but there is a significant relationship with the variable length of leg and arm length with wealth index. Nowadays, small family norms, noon meal scheme, Anganwadi nutrition food programme and parental care are keeping children in well physiological growths.


Keywords


Child health, Physiological health, Wealth Index,

Full Text:

PDF

References


Acheson D (1998). Independent Inquiry into Inequalities in Health. The Stationery Office, London.

Benzeval M, Judge K, Whitehead M, eds (1995). Tackling Health Inequalities: An Agenda for Action. King’s Fund, London.

Blumenshine P, Egerter S, Barclay CJ, Cubbin C, Braveman PA (2010). Socioeconomic disparities in adverse birth outcomes: a systematic review. Am J Prev Med.; 39(3):263-72.

Boyle, P.J., Gatrell, A.C. and Duke-Williams, O. (1999). The effect on morbidity of variability in deprivation and population stability in England and Wales. Social Science and Medicine 42, 843–55.

Braveman P, Barclay C (2009). Health disparities beginning in childhood: a life-course perspective. Pediatrics.124 Suppl 3:S163-75.

Braveman PA, Cubbin C, Egerter S, Williams DR, Pamuk E (2010). Socio-economic disparities in health in the United States: What the patterns tell us. Am J Public Health. 2010 14(1):20-35.

Diez Roux AV, Mair C. Neighborhoods and health (2010). Ann N Y Acad Sci.1186:125-45.

Gatrell, A.C. and Bailey, T.C. (1996): Interactive spatial data analysis in medical geography. Social Science and Medicine 42, 843–55.

Graham H, (2000). Understanding Health Inequalities. Open University Press, Maidenhead.

Hajat A, Kaufman JS, Rose KM, Siddiqi A, Thomas JC (2010). Do the wealthy have a health advantage? Cardiovascular disease risk factors and wealth. Soc Sci Med. 71(11):1935-42.

Hajat A, Kaufman JS, Rose KM, Siddiqi A, Thomas JC (2010). Long-term effects of wealth on mortality and self-rated health status. Am J Epidemiol.

Kawachi I, Berkman LF (2003), editors. Neighborhoods and health. New York: Oxford University Press.

Kim, Y.E., Gatrell, A.C. and Francis, B.J. (2000): The geography of survival after surgery for colorectal cancer in southern England. Social Science and Medicine 50, 1099–107.

Krueger PM, Rogers RG, Hummer RA, LeClere FB, Huie SAB (2003). Socioeconomic status and age: The effect of income sources and portfolios on U.S. adult mortality. Sociological Forum. 18(3):465-482.

Lynch J, Smith GD, Harper S, Hillemeier M, Ross N, Kaplan GA, et al (2004). Is income inequality a determinant of population health? Part 1. A systematic review. Milbank Q. 82 (1):5-99.

Lynch J, Smith GD, Harper S, Hillemeier M (2004). Is income inequality a determinant of population health? Part 2. U.S. National and regional trends in income inequality and age- and cause-specific mortality. Milbank Q. 82 (2):355-400.

Mishra, D., Singh, H.P. (2003). Indian Journal of paediatrics, Kuppuswamy’s Socio-economic Status Scale-A revision.

Parker, E.B. and Campbell, J.L. (1998): Measuring access to primary medical care: some examples of the use of geographical information systems. Health and Place 4, 183–93.

Pickett KE, Pearl M (2001). Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review. J Epidemiol Community Health. 55 (2):111-22.

Pollack CE, Chideya S, Cubbin C, Williams B, Dekker M, Braveman P (2007). Should health studies measure wealth? A systematic review. Am J Prev Med. 33 (3):250-64.

Robert S, House JS (1996). SES differentials in health by age and alternative indicators of SES. J Aging Health. 8(3):359-388.

Robert SA (1998). Community-level socioeconomic status effects on adult health. J Health Soc Behav. 39(1):18-37.

Sabel, C.E., Gatrell, A.C., Loytonen, M., Maasilta, P. and Jokelainen, M. (2000): Modelling exposure opportunities: estimating relative risk for motor neurone disease in Finland. Social Science and Medicine 50, 1121–37.

Schweikart, J. and Kristemann, T. (2000): Geographical information systems in medical geography. Petermans Geographische Mitteilungen 145, 18–29.

Wall, P.A. and Devine, O.J. (2000): Interactive analysis of the spatial distribution of disease using a geographic information system. Journal of Geographic Information Systems 2, 243–56.

Wilkinson RG, Pickett KE (2006). Income inequality and population health: a review and explanation of the evidence. Soc Sci Med. 62 (7):1768-84.




DOI: https://doi.org/10.24203/ajhss.v5i3.4820

Refbacks

  • There are currently no refbacks.


Copyright (c) 2017 Asian Journal of Humanities and Social Studies

Creative Commons License
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.