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Does government expenditure reduce inequalities in infant mortality rates in low- and middle-income countries?: A time-series, ecological analysis of 48 countries from 1993 to 2013

Published online by Cambridge University Press:  27 June 2018

Peter Baker Open the ORCID record for Peter Baker [Opens in a new window] ,
Thomas Hone ,
Aaron Reeves ,
Mauricio Avendano  and
Christopher Millett
Peter Baker
Affiliation:
Public Health Consultant and Honorary Clinical Fellow, The Department of Primary Care & Public Health, Imperial College London, London, UK
Thomas Hone
Affiliation:
Research Fellow, The Department of Primary Care & Public Health, Imperial College London, London, UK
Aaron Reeves
Affiliation:
Associate Professor, Department of Social Policy and Intervention, University of Oxford, Oxford, UKAssociate Professorial Research Fellow, International Inequalities Institute, London School of Economics and Political Science, London, UK
Mauricio Avendano
Affiliation:
Reader in Global Ageing, Department of Social Science, Health and Medicine, King’s College London, London, UK
Christopher Millett
Affiliation:
Professor of Public Health, The Department of Primary Care & Public Health, Imperial College London, London, UK
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Abstract

Inequalities in infant mortality rates (IMRs) are rising in some low- and middle-income countries (LMICs) and decreasing in others, but the explanation for these divergent trends is unclear. We investigate whether government expenditures and redistribution are associated with reductions in inequalities in IMRs. We estimated country-level fixed-effects panel regressions for 48 LMICs (142 country observations). Slope and Relative Indices of Inequality in IMRs (SII and RII) were calculated from Demographic and Health Surveys between 1993 and 2013. RII and SII were regressed on government expenditure (total, health and non-health) and redistribution, controlling for gross domestic product (GDP), private health expenditures, a democracy indicator, country fixed effects and time. Mean SII and RII was 39.12 and 0.69, respectively. In multivariate models, a 1 percentage point increase in total government expenditure (% of GDP) was associated with a decrease in SII of −2.468 [95% confidence intervals (CIs): −4.190, −0.746] and RII of −0.026 (95% CIs: −0.048, −0.004). Lower inequalities were associated with higher non-health government expenditure, but not higher government health expenditure. Associations with inequalities were non-significant for GDP, government redistribution, and private health expenditure. Understanding how non-health government expenditure reduces inequalities in IMR, and why health expenditures may not, will accelerate progress towards the Sustainable Development Goals.

Type
Articles
Information
Health Economics, Policy and Law , Volume 14 , Special Issue 2: SPECIAL ISSUE: Frontiers of Health Policy Research , April 2019 , pp. 249 - 273
Copyright
© Cambridge University Press 2018 

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References

Adato, M. and Bassett, L. (2009), ‘Social protection to support vulnerable children and families: the potential of cash transfers to protect education, health and nutrition’, AIDS Care, 21: 60–75.Google Scholar
Amouzou, A., Kozuki, N. and Gwatkin, D. R. (2014), ‘Where is the gap?: The contribution of disparities within developing countries to global inequalities in under-five mortality’, BMC Public Health, 14: 1–5.Google Scholar
Ataguba, J. E.-O., Day, C. and McIntyre, D. (2015), ‘Explaining the role of the social determinants of health on health inequality in South Africa’, Global Health Action, 8: 28865. https://doi.org/10.3402/gha.v8.28865.Google Scholar
Conley, D. and Springer, K. W. (2001), ‘Welfare state and infant mortality’, American Journal of Sociology, 107: 768–807.Google Scholar
Dahlgren, G. and Whitehead, M. (2006), European Strategies for Tackling Social Inequities in Health: Levelling up Part 2. Studies on Social and Economic Determinants of Population Health. Copenhagen, Denmark: World Health Organization.Google Scholar
Hart, J. T. (1971), ‘INVERSE CARE LAW’, Lancet, 297(7696): 405–412.Google Scholar
Houweling, T. A., Kunst, A. E., Huisman, M. and Mackenbach, J. P. (2007), ‘Using relative and absolute measures for monitoring health inequalities: experiences from cross-national analyses on maternal and child health’, International Journal for Equity in Health, 6: 15.Google Scholar
Houweling, T. A. J. and Kunst, A. E. (2010), ‘Socio-economic inequalities in childhood mortality in low- and middle-income countries: a review of the international evidence’, British Medical Bulletin, 93: 7–26.Google Scholar
Khan, M. S., Guan, B. Y., Audimulam, J., Cervero Liceras, F., Coker, R. J. and Yoong, J. (2016), ‘Economic interventions to improve population health: a scoping study of systematic reviews’, BMC Public Health, 16: 528.Google Scholar
Kruk, M. E., Prescott, M. R., de Pinho, H. and Galea, S. (2011), ‘Equity and the child health millennium development goal: the role of pro-poor health policies’, Journal of Epidemiology and Community Health, 65: 327–333.Google Scholar
Liu, L., Oza, S., Hogan, D., Chu, Y., Perin, J., Zhu, J., Lawn, J. E., Cousens, S., Mathers, C. and Black, R. E. (2016), ‘Global, regional, and national causes of under-5 mortality in 2000 – 15: an updated systematic analysis with implications for the sustainable development goals’, Lancet, 6736: 2275–2286.Google Scholar
Mackenbach, J. P., Hu, Y. and Looman, C. W. N. (2013), ‘Democratization and life expectancy in Europe, 1960-2008’, Social Science & Medicine, 93: 166–175.Google Scholar
McKinnon, B., Harper, S. and Kaufman, J. S. (2016), ‘Do socioeconomic inequalities in neonatal mortality reflect inequalities in coverage of maternal health services? Evidence from 48 low- and middle-income countries’, Maternal and Child Health Journal, 20: 434–446.Google Scholar
McKinnon, B., Harper, S., Kaufman, J. S. and Bergevin, Y. (2014), ‘Socioeconomic inequality in neonatal mortality in countries of low and middle income: a multicountry analysis’, Lancet Global Health, 2: 165–173.Google Scholar
McLean, G., Guthrie, B., Mercer, S. W. and Watt, G. C. (2015), ‘General practice funding underpins the persistence of the inverse care law: cross-sectional study in Scotland’, British Journal of General Practice, 65: e799–e805.Google Scholar
Mosley, W. H. and Chen, L. C. (1984), ‘An analytical framework for the study of child survival in developing countries’, Population and Development Review, 10: 25–45.Google Scholar
Munck, G. L. and Verkuilen, J. (2002), ‘Conceptualizing and measuring democracy: evaluating alternative indices’, Comparative Political Studies, 35: 5–34.Google Scholar
O’Donnell, O., van Doorslaer, E., van, Wagstaff, A. and Lindelow, M. (2008), Analyzing Health Equity Using Household Survey Data: A Guide to Techniques and their Implementation, Washington, DC: World Bank.Google Scholar
Ross, M. (2006), ‘Is democracy good for the poor?’, American Journal of Political Science, 50: 860–874.Google Scholar
Sartorius, B. and Sartorius, K. (2014), ‘Global infant mortality trends and attributable determinants – an ecological study using data from 192 countries for the period 1990–2011’, Population Health Metrics, 12: 29.Google Scholar
Sogaard, J. (1992), ‘Econometric critique of the economic-change model of mortality’, Social Science & Medicine, 34: 947–957.Google Scholar
Solt, F. (2016), ‘The standardized world income inequality database’, Social Science Quarterly, 97(5): 1267–1281.Google Scholar
Spaan, E., Mathijssen, J., Tromp, N., McBain, F., ten Have, A. and Baltussen, R. (2012), ‘The impact of health insurance in Africa and Asia: a systematic review’, Bulletin of the World Health Organization, 90: 685–692.Google Scholar
StataCorp (2015), Stata Statistical Software: Release 14.1, College Station, TX.Google Scholar
Stuckler, D., Basu, S., Suhrcke, M., Coutts, A. and McKee, M. (2009), ‘The public health effect of economic crises and alternative policy responses in Europe: an empirical analysis’, Lancet, 374: 315–323.Google Scholar
Truesdale, B. C. and Jencks, C. (2016), ‘The health effects of income inequality: averages and disparities’, Annual Review of Public Health, 37: 413–430.Google Scholar
Victora, C. G., Requejo, J. H., Barros, A. J. D., Berman, P., Bhutta, Z., Boerma, T., Chopra, M., De Francisco, A., Daelmans, B., Hazel, E., Lawn, J., Maliqi, B., Newby, H. and Bryce, J. (2016), ‘Countdown to 2015: a decade of tracking progress for maternal, newborn, and child survival’, Lancet, 387: 2049–2059.Google Scholar
Wagstaff, A. (1985), ‘Time-series analysis of the relationship between unemployment and mortality - a survey of econometric critiques and replications of Brenner studies’, Social Science & Medicine, 21: 985–996.Google Scholar
Wagstaff, A. (2015), ‘Commentary: value judgments in health inequality measurement’, Epidemiology, 26: 670–672.Google Scholar
Wagstaff, A., Bredenkamp, C. and Buisman, L. R. (2014), ‘Progress on global health goals: are the poor being left behind?’, World Bank Research Observer, 29: 137–162.Google Scholar
Wagstaff, A., Paci, P. and van Doorslaer, E. (1991), ‘On the measurement of inequalities in health’, Social Science & Medicine, 33: 545–557.Google Scholar
Wooldridge, J. M. (2003), Introductory Econometrics: A Modern Approach, Mason, OH: South-Western College Publishing.Google Scholar
Wooldridge, J. M. (2010), Econometric Analysis of Cross Section and Panel Data, Cambridge, MA: MIT Press.Google Scholar
World Bank (2016), World Development Indicators, http://databank.worldbank.org/data/home.aspx [29 November 2016].Google Scholar
World Bank (2015), Database of Political Institutions, http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/0,,contentMDK:20649465~pagePK:64214825~piPK:64214943~theSitePK:469382,00.html [14 November 2017].Google Scholar
World Health Organization (WHO) (2008), Closing the Gap in a Generation: Health Equity Through Action on the Social Determinants of Health: Commission on Social Determinants of Health, Geneva: World Health Organization.Google Scholar
World Health Organization (WHO) (2013), Handbook on Health Inequality Monitoring with a Special Focus on Low- and Middle-Income Countries, Geneva: World Health Organization.Google Scholar
World Health Organization (WHO) (2016), Global Health Observatory: Health Equity Monitor, http://www.who.int/gho/database/en/ [29 November 2016].Google Scholar
You, D., Hug, L., Ejdemyr, S., Idele, P., Hogan, D., Mathers, C., Gerland, P., New, J. R. and Alkema, L. (2015), ‘Global, regional, and national levels and trends in under-5 mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation’, Lancet, 386: 2275–2286. https://doi.org/10.1016/S0140-6736(15)00120-8.Google Scholar
Young, C. and Holsteen, K. (2015), Model Uncertainty and Robustness: A Computational Framework for Multimodel Analysis, Sociological Methods & Research. https://doi.org/10.1177/0049124115610347.Google Scholar
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