Skip to main content
Top
Published in: International Journal for Equity in Health 1/2022

Open Access 01-12-2022 | Research

Comparison of household socioeconomic status classification methods and effects on risk estimation: lessons from a natural experimental study, Kisumu, Western Kenya

Authors: Vincent Were, Louise Foley, Eleanor Turner-Moss, Ebele Mogo, Pamela Wadende, Rosemary Musuva, Charles Obonyo

Published in: International Journal for Equity in Health | Issue 1/2022

Login to get access

Abstract

Introduction

Low household socioeconomic status is associated with unhealthy behaviours including poor diet and adverse health outcomes. Different methods leading to variations in SES classification has the potential to generate spurious research findings or misinform policy. In low and middle-income countries, there are additional complexities in defining household SES, a need for fieldwork to be conducted efficiently, and a dearth of information on how classification could impact estimation of disease risk.

Methods

Using cross-sectional data from 200 households in Kisumu County, Western Kenya, we compared three approaches of classifying households into low, middle, or high SES: fieldworkers (FWs), Community Health Volunteers (CHVs), and a Multiple Correspondence Analysis econometric model (MCA). We estimated the sensitivity, specificity, inter-rater reliability and misclassification of the three methods using MCA as a comparator. We applied an unadjusted generalized linear model to determine prevalence ratios to assess the association of household SES status with a self-reported diagnosis of diabetes or hypertension for one household member.

Results

Compared with MCA, FWs successfully classified 21.7% (95%CI = 14.4%-31.4%) of low SES households, 32.8% (95%CI = 23.2–44.3) of middle SES households, and no high SES households. CHVs successfully classified 22.5% (95%CI = 14.5%-33.1%) of low SES households, 32.8% (95%CI = 23.2%-44.3%) of middle SES households, and no high SES households. The level of agreement in SES classification was similar between FWs and CHVs but poor compared to MCA, particularly for high SES. None of the three methods differed in estimating the risk of hypertension or diabetes.

Conclusions

FW and CHV assessments are community-driven methods for SES classification. Compared to MCA, these approaches appeared biased towards low or middle SES households and not sensitive to high household SES. The three methods did not differ in risk estimation for diabetes and hypertension. A mix of approaches and further evaluation to refine SES classification methodology is recommended.
Appendix
Available only for authorised users
Literature
1.
2.
go back to reference Allen L, Williams J, Townsend N, Mikkelsen B, Roberts N, Foster C, Wickramasinghe K. Socioeconomic status and non-communicable disease behavioural risk factors in low-income and lower-middle-income countries: a systematic review. Lancet Glob Health. 2017;5:e277–89.CrossRef Allen L, Williams J, Townsend N, Mikkelsen B, Roberts N, Foster C, Wickramasinghe K. Socioeconomic status and non-communicable disease behavioural risk factors in low-income and lower-middle-income countries: a systematic review. Lancet Glob Health. 2017;5:e277–89.CrossRef
3.
go back to reference Williams J, Allen L, Wickramasinghe K, Mikkelsen B, Roberts N, Townsend N: A systematic review of associations between non-communicable diseases and socioeconomic status within low-and lower-middle-income countries. Journal of global health 2018, 8. Williams J, Allen L, Wickramasinghe K, Mikkelsen B, Roberts N, Townsend N: A systematic review of associations between non-communicable diseases and socioeconomic status within low-and lower-middle-income countries. Journal of global health 2018, 8.
4.
go back to reference Feinstein JS: The relationship between socioeconomic status and health: a review of the literature. Milbank Q 1993:279–322. Feinstein JS: The relationship between socioeconomic status and health: a review of the literature. Milbank Q 1993:279–322.
5.
go back to reference Kington RS, Smith JP. Socioeconomic status and racial and ethnic differences in functional status associated with chronic diseases. Am J Public Health. 1997;87:805–10.CrossRef Kington RS, Smith JP. Socioeconomic status and racial and ethnic differences in functional status associated with chronic diseases. Am J Public Health. 1997;87:805–10.CrossRef
6.
go back to reference Fiechtner L, Kleinman K, Melly SJ, Sharifi M, Marshall R, Block J, Cheng ER, Taveras EM. Effects of proximity to supermarkets on a randomized trial studying interventions for obesity. Am J Public Health. 2016;106:557–62.CrossRef Fiechtner L, Kleinman K, Melly SJ, Sharifi M, Marshall R, Block J, Cheng ER, Taveras EM. Effects of proximity to supermarkets on a randomized trial studying interventions for obesity. Am J Public Health. 2016;106:557–62.CrossRef
7.
go back to reference Laraia BA, Siega-Riz AM, Kaufman JS, Jones SJ. Proximity of supermarkets is positively associated with diet quality index for pregnancy. Prev Med. 2004;39:869–75.CrossRef Laraia BA, Siega-Riz AM, Kaufman JS, Jones SJ. Proximity of supermarkets is positively associated with diet quality index for pregnancy. Prev Med. 2004;39:869–75.CrossRef
8.
go back to reference Lamichhane AP, Mayer-Davis EJ, Puett R, Bottai M, Porter DE, Liese AD. Associations of built food environment with dietary intake among youth with diabetes. J Nutr Educ Behav. 2012;44:217–24.CrossRef Lamichhane AP, Mayer-Davis EJ, Puett R, Bottai M, Porter DE, Liese AD. Associations of built food environment with dietary intake among youth with diabetes. J Nutr Educ Behav. 2012;44:217–24.CrossRef
9.
go back to reference Skidmore P, Welch A, van Sluijs E, Jones A, Harvey I, Harrison F, Griffin S, Cassidy A. Impact of neighbourhood food environment on food consumption in children aged 9–10 years in the UK SPEEDY (Sport, Physical Activity and Eating behaviour: Environmental Determinants in Young people) study. Public Health Nutr. 2010;13:1022–30.CrossRef Skidmore P, Welch A, van Sluijs E, Jones A, Harvey I, Harrison F, Griffin S, Cassidy A. Impact of neighbourhood food environment on food consumption in children aged 9–10 years in the UK SPEEDY (Sport, Physical Activity and Eating behaviour: Environmental Determinants in Young people) study. Public Health Nutr. 2010;13:1022–30.CrossRef
10.
go back to reference Powell LM, Auld MC, Chaloupka FJ, O’Malley PM, Johnston LD. Associations between access to food stores and adolescent body mass index. Am J Prev Med. 2007;33:S301–7.CrossRef Powell LM, Auld MC, Chaloupka FJ, O’Malley PM, Johnston LD. Associations between access to food stores and adolescent body mass index. Am J Prev Med. 2007;33:S301–7.CrossRef
11.
go back to reference Sim LJ, Parker L, Kumanyika SK. Bridging the evidence gap in obesity prevention: a framework to inform decision making. 2010. Sim LJ, Parker L, Kumanyika SK. Bridging the evidence gap in obesity prevention: a framework to inform decision making. 2010.
12.
go back to reference Niessen LW, Mohan D, Akuoku JK, Mirelman AJ, Ahmed S, Koehlmoos TP, Trujillo A, Khan J, Peters DH. Tackling socio-economic inequalities and non-communicable diseases in low-income and middle-income countries under the Sustainable Development agenda. Lancet. 2018;391:2036–46.CrossRef Niessen LW, Mohan D, Akuoku JK, Mirelman AJ, Ahmed S, Koehlmoos TP, Trujillo A, Khan J, Peters DH. Tackling socio-economic inequalities and non-communicable diseases in low-income and middle-income countries under the Sustainable Development agenda. Lancet. 2018;391:2036–46.CrossRef
13.
go back to reference Howe LD, Galobardes B, Matijasevich A, Gordon D, Johnston D, Onwujekwe O, Patel R, Webb EA, Lawlor DA, Hargreaves JR. Measuring socio-economic position for epidemiological studies in low-and middle-income countries: a methods of measurement in epidemiology paper. Int J Epidemiol. 2012;41:871–86.CrossRef Howe LD, Galobardes B, Matijasevich A, Gordon D, Johnston D, Onwujekwe O, Patel R, Webb EA, Lawlor DA, Hargreaves JR. Measuring socio-economic position for epidemiological studies in low-and middle-income countries: a methods of measurement in epidemiology paper. Int J Epidemiol. 2012;41:871–86.CrossRef
14.
go back to reference Onwujekwe O, Hanson K, Fox-Rushby J. Some indicators of socio-economic status may not be reliable and the use of indices with these data could worsen equity. Health Econ. 2006;15:639–44.CrossRef Onwujekwe O, Hanson K, Fox-Rushby J. Some indicators of socio-economic status may not be reliable and the use of indices with these data could worsen equity. Health Econ. 2006;15:639–44.CrossRef
15.
go back to reference Baena A, Garcés-Palacio IC, Grisales H. The effect of misclassification error on risk estimation in case-control studies. Rev Bras Epidemiol. 2015;18:341–56.CrossRef Baena A, Garcés-Palacio IC, Grisales H. The effect of misclassification error on risk estimation in case-control studies. Rev Bras Epidemiol. 2015;18:341–56.CrossRef
16.
go back to reference dos Santos Silva I: Cancer epidemiology: principles and methods. IARC; 1999. dos Santos Silva I: Cancer epidemiology: principles and methods. IARC; 1999.
17.
go back to reference Were V, Buff AM, Desai M, Kariuki S, Samuels A, Ter Kuile FO, Phillips-Howard PA, Kachur SP, Niessen L. Socioeconomic health inequality in malaria indicators in rural western Kenya: evidence from a household malaria survey on burden and care-seeking behaviour. Malar J. 2018;17:1–10.CrossRef Were V, Buff AM, Desai M, Kariuki S, Samuels A, Ter Kuile FO, Phillips-Howard PA, Kachur SP, Niessen L. Socioeconomic health inequality in malaria indicators in rural western Kenya: evidence from a household malaria survey on burden and care-seeking behaviour. Malar J. 2018;17:1–10.CrossRef
18.
go back to reference Rutstein SO, Johnson K. The DHS wealth index. DHS comparative reports no. 6. Calverton: ORC Macro; 2004. Rutstein SO, Johnson K. The DHS wealth index. DHS comparative reports no. 6. Calverton: ORC Macro; 2004.
19.
go back to reference Chakraborty NM, Fry K, Behl R, Longfield K. Simplified asset indices to measure wealth and equity in health programs: a reliability and validity analysis using survey data from 16 countries. Global Health: Science and Practice. 2016;4:141–54. Chakraborty NM, Fry K, Behl R, Longfield K. Simplified asset indices to measure wealth and equity in health programs: a reliability and validity analysis using survey data from 16 countries. Global Health: Science and Practice. 2016;4:141–54.
20.
go back to reference Jehu-Appiah C, Aryeetey G, Spaan E, Agyepong I, Baltussen R. Efficiency, equity and feasibility of strategies to identify the poor: an application to premium exemptions under National Health Insurance in Ghana. Health Policy. 2010;95:166–73.CrossRef Jehu-Appiah C, Aryeetey G, Spaan E, Agyepong I, Baltussen R. Efficiency, equity and feasibility of strategies to identify the poor: an application to premium exemptions under National Health Insurance in Ghana. Health Policy. 2010;95:166–73.CrossRef
21.
go back to reference Foley L, Francis O, Musuva R, Mogo ER, Turner-Moss E, Wadende P, Were V, Obonyo C. Impacts of a New Supermarket on Dietary Behavior and the Local Foodscape in Kisumu, Kenya: Protocol for a Mixed Methods. Natural Experimental Study JMIR Research Protocols. 2020;9:e17814.CrossRef Foley L, Francis O, Musuva R, Mogo ER, Turner-Moss E, Wadende P, Were V, Obonyo C. Impacts of a New Supermarket on Dietary Behavior and the Local Foodscape in Kisumu, Kenya: Protocol for a Mixed Methods. Natural Experimental Study JMIR Research Protocols. 2020;9:e17814.CrossRef
22.
go back to reference Statistics KNBo: 2019 Kenya Population and Housing Census Volume I: Population by County and Sub-County. 2019. Statistics KNBo: 2019 Kenya Population and Housing Census Volume I: Population by County and Sub-County. 2019.
23.
go back to reference Svoronos T, Mjungu P, Dhadialla R, Luk R, Zue C, Jackson J, Lesh N: CommCare: Automated quality improvement to strengthen community-based health. Weston: D-Tree International 2010. Svoronos T, Mjungu P, Dhadialla R, Luk R, Zue C, Jackson J, Lesh N: CommCare: Automated quality improvement to strengthen community-based health. Weston: D-Tree International 2010.
25.
go back to reference Olayo R, Wafula C, Aseyo E, Loum C, Kaseje D. A quasi-experimental assessment of the effectiveness of the Community Health Strategy on health outcomes in Kenya. BMC Health Serv Res. 2014;14:S3.CrossRef Olayo R, Wafula C, Aseyo E, Loum C, Kaseje D. A quasi-experimental assessment of the effectiveness of the Community Health Strategy on health outcomes in Kenya. BMC Health Serv Res. 2014;14:S3.CrossRef
26.
go back to reference Sonko ST, Jaiteh M, Jafali J, Jarju LB, D’Alessandro U, Camara A, Komma-Bah M, Saho A. Does socio-economic status explain the differentials in malaria parasite prevalence? Evidence from The Gambia Malaria Journal. 2014;13:449.CrossRef Sonko ST, Jaiteh M, Jafali J, Jarju LB, D’Alessandro U, Camara A, Komma-Bah M, Saho A. Does socio-economic status explain the differentials in malaria parasite prevalence? Evidence from The Gambia Malaria Journal. 2014;13:449.CrossRef
27.
go back to reference Tiwari S, Kumar A. Updation of the scale to measure socio-economic status in urban & rural communities in India. Indian J Med Res. 2012;135:432.PubMedPubMedCentral Tiwari S, Kumar A. Updation of the scale to measure socio-economic status in urban & rural communities in India. Indian J Med Res. 2012;135:432.PubMedPubMedCentral
28.
go back to reference Woods ER, Lin YG, Middleman A, Beckford P, Chase L, DuRant RH. The associations of suicide attempts in adolescents. Pediatrics. 1997;99:791–6.CrossRef Woods ER, Lin YG, Middleman A, Beckford P, Chase L, DuRant RH. The associations of suicide attempts in adolescents. Pediatrics. 1997;99:791–6.CrossRef
29.
go back to reference Bakibinga P, Kamande E, Omuya M, Ziraba AK, Kyobutungi C. The role of a decision-support smartphone application in enhancing community health volunteers’ effectiveness to improve maternal and newborn outcomes in Nairobi, Kenya: quasi-experimental research protocol. BMJ open. 2017;7:e014896.CrossRef Bakibinga P, Kamande E, Omuya M, Ziraba AK, Kyobutungi C. The role of a decision-support smartphone application in enhancing community health volunteers’ effectiveness to improve maternal and newborn outcomes in Nairobi, Kenya: quasi-experimental research protocol. BMJ open. 2017;7:e014896.CrossRef
30.
go back to reference Flaming A, Canty M, Javetski G, Lesh N. The CommCare evidence base for frontline workers. 2015. Flaming A, Canty M, Javetski G, Lesh N. The CommCare evidence base for frontline workers. 2015.
31.
go back to reference Alaba O, Chola L. Socioeconomic inequalities in adult obesity prevalence in South Africa: a decomposition analysis. Int J Environ Res Public Health. 2014;11:3387–406.CrossRef Alaba O, Chola L. Socioeconomic inequalities in adult obesity prevalence in South Africa: a decomposition analysis. Int J Environ Res Public Health. 2014;11:3387–406.CrossRef
32.
go back to reference Abdi H, Valentin D. Multiple correspondence analysis. Encyclopedia Meas Stat. 2007;2:651–7. Abdi H, Valentin D. Multiple correspondence analysis. Encyclopedia Meas Stat. 2007;2:651–7.
33.
go back to reference Cohen J. Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit. Psychol Bull. 1968;70:213.CrossRef Cohen J. Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit. Psychol Bull. 1968;70:213.CrossRef
34.
go back to reference Srinivas S, Satyavaraprasad K, Ramdas R, Krishna C, Tajuddin T, Rao RP. Prevalence of prehypertension in adult population of rural Andhra Pradesh. Asian J Biomed Pharm Sci. 2013;3:45. Srinivas S, Satyavaraprasad K, Ramdas R, Krishna C, Tajuddin T, Rao RP. Prevalence of prehypertension in adult population of rural Andhra Pradesh. Asian J Biomed Pharm Sci. 2013;3:45.
36.
go back to reference Gorski PC. Perceiving the problem of poverty and schooling: Deconstructing the class stereotypes that mis-shape education practice and policy. Equity & Excell Educ. 2012;45:302–19.CrossRef Gorski PC. Perceiving the problem of poverty and schooling: Deconstructing the class stereotypes that mis-shape education practice and policy. Equity & Excell Educ. 2012;45:302–19.CrossRef
37.
go back to reference Kabudula CW, Houle B, Collinson MA, Kahn K, Tollman S, Clark S. Assessing changes in household socioeconomic status in rural South Africa, 2001–2013: a distributional analysis using household asset indicators. Soc Indic Res. 2017;133:1047–73.CrossRef Kabudula CW, Houle B, Collinson MA, Kahn K, Tollman S, Clark S. Assessing changes in household socioeconomic status in rural South Africa, 2001–2013: a distributional analysis using household asset indicators. Soc Indic Res. 2017;133:1047–73.CrossRef
38.
go back to reference Case A, Lubotsky D, Paxson C. Economic status and health in childhood: The origins of the gradient. Am Econ Rev. 2002;92:1308–34.CrossRef Case A, Lubotsky D, Paxson C. Economic status and health in childhood: The origins of the gradient. Am Econ Rev. 2002;92:1308–34.CrossRef
39.
go back to reference Were V, Buff AM, Desai M, Kariuki S, Samuels A, Ter Kuile FO, Phillips-Howard PA, Kachur SP, Niessen L. Socioeconomic health inequality in malaria indicators in rural western Kenya: evidence from a household malaria survey on burden and care-seeking behaviour. Malar J. 2018;17:166.CrossRef Were V, Buff AM, Desai M, Kariuki S, Samuels A, Ter Kuile FO, Phillips-Howard PA, Kachur SP, Niessen L. Socioeconomic health inequality in malaria indicators in rural western Kenya: evidence from a household malaria survey on burden and care-seeking behaviour. Malar J. 2018;17:166.CrossRef
Metadata
Title
Comparison of household socioeconomic status classification methods and effects on risk estimation: lessons from a natural experimental study, Kisumu, Western Kenya
Authors
Vincent Were
Louise Foley
Eleanor Turner-Moss
Ebele Mogo
Pamela Wadende
Rosemary Musuva
Charles Obonyo
Publication date
01-12-2022
Publisher
BioMed Central
Published in
International Journal for Equity in Health / Issue 1/2022
Electronic ISSN: 1475-9276
DOI
https://doi.org/10.1186/s12939-022-01652-1

Other articles of this Issue 1/2022

International Journal for Equity in Health 1/2022 Go to the issue