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The effects of cash transfers on adult and child mortality in low- and middle-income countries

Nature volume 618, pages 575–582 (2023)Cite this article

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Abstract

Poverty is an important social determinant of health that is associated with increased risk of death1,2,3,4,5. Cash transfer programmes provide non-contributory monetary transfers to individuals or households, with or without behavioural conditions such as children’s school attendance6,7. Over recent decades, cash transfer programmes have emerged as central components of poverty reduction strategies of many governments in low- and middle-income countries6,7. The effects of these programmes on adult and child mortality rates remains an important gap in the literature, however, with existing evidence limited to a few specific conditional cash transfer programmes, primarily in Latin America8,9,10,11,12,13,14. Here we evaluated the effects of large-scale, government-led cash transfer programmes on all-cause adult and child mortality using individual-level longitudinal mortality datasets from many low- and middle-income countries. We found that cash transfer programmes were associated with significant reductions in mortality among children under five years of age and women. Secondary heterogeneity analyses suggested similar effects for conditional and unconditional programmes, and larger effects for programmes that covered a larger share of the population and provided larger transfer amounts, and in countries with lower health expenditures, lower baseline life expectancy, and higher perceived regulatory quality. Our findings support the use of anti-poverty programmes such as cash transfers, which many countries have introduced or expanded during the COVID-19 pandemic, to improve population health.

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Fig. 1: Study timeline.
Fig. 2: The effects of cash transfer programmes on all-cause mortality.
Fig. 3: The effects of cash transfer programmes on all-cause mortality over time.

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Data availability

The analysed data can be requested from the DHS Program website (individual recode datasets from the included countries from https://www.dhsprogram.com/Data/) or are publicly available from the World Bank (GDP per capita, total health expenditures per capita, life expectancies at birth, and Worldwide Governance Indicators datasets from https://data.worldbank.org/data-catalog/) or PEPFAR (PEPFAR Operating Unit Budgets by Financial Classifications FY04-FY20 dataset from https://data.pepfar.gov/financial). The cash transfer programme dataset is available in the Supplementary Information.

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Acknowledgements

A.R. was supported by the National Institute of Mental Health of the National Institutes of Health under Award Number K23MH131464.

Author information

Authors and Affiliations

  1. Division of Infectious Diseases, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Aaron Richterman

  2. Partners in Health, Mirebalais, Haiti

    Christophe Millien

  3. Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia, PA, USA

    Elizabeth F. Bair & Harsha Thirumurthy

  4. Partners in Health, Kono, Sierra Leone

    Gregory Jerome

  5. Partners in Health, Neno, Malawi

    Jean Christophe Dimitri Suffrin

  6. Departments of Economics and Sociology, University of Pennsylvania, Philadelphia, PA, USA

    Jere R. Behrman

  7. Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA

    Jere R. Behrman & Harsha Thirumurthy

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Contributions

The study was conceptualized by A.R., H.T., C.M., G.J., J.C.D.S. and J.R.B. Methodology design was led by A.R., H.T., E.F.B. and J.R.B., and the data curation and formal analyses were conducted by A.R. under the supervision of H.T. Figures were created by A.R. The first draft of the manuscript was written by A.R. and all authors provided critical inputs into the final draft.

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Correspondence to Aaron Richterman.

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The authors declare no competing interests.

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Nature thanks Till Bärnighausen, Davide Rasella and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Country inclusion flow diagram.

Flow Diagram showing selection of intervention (N = 16) and comparison (N = 21) countries during our study period of 2000–2019, and reasons for exclusion (red boxes).

Extended Data Fig. 2 Temporal plots of the effects of cash transfer programs on mortality for children aged 5 to 17 years.

Temporal plots showing the associations between cash transfer programs and mortality as a function of the year of the cash transfer period. Effect estimates are adjusted risk ratios and error bars are 95% confidence intervals. Estimates were generated using multivariable modified Poisson models with country and year fixed effects, country-level covariates (GDP per capita, PEPFAR funding budgeted, and three Worldwide Governance Indicators: Control of Corruption, Political Stability and Absence of Violence, and Voice and Accountability), and individual-level covariates (age and rural/urban setting in all models; sex, age of mother, and birth order in child analyses). We used robust standard errors clustered at the country level. The top panel shows estimates for children aged 5 to 9 years (N = 4,818,370 person-years), the bottom panel shows estimates for children aged 10 to 17 years (N = 4,824,891 person-years).

Extended Data Fig. 3 Heterogeneity analyses for adult males.

Forest plot showing subgroup analyses among adult males (N = 15,249,343 person-years), with fully adjusted risk ratios of mortality with 95% confidence intervals generated using multivariable modified Poisson models with country and year fixed effects, country-level covariates (GDP per capita, PEPFAR funding budgeted, and three Worldwide Governance Indicators: Control of Corruption, Political Stability and Absence of Violence, and Voice and Accountability), and individual-level covariates (age and rural/urban setting). We used robust standard errors clustered at the country level. Effect estimates are adjusted risk ratios and error bars are 95% confidence intervals.

Extended Data Fig. 4 Heterogeneity analyses for children aged <5.

Forest plot showing subgroup analyses among children aged <5 years (N = 6,757,284 person-years), with fully adjusted risk ratios of mortality with 95% confidence intervals generated using multivariable modified Poisson models with country and year fixed effects, country-level covariates (GDP per capita, PEPFAR funding budgeted, and three Worldwide Governance Indicators: Control of Corruption, Political Stability and Absence of Violence, and Voice and Accountability), and individual-level covariates (age and rural/urban setting). We used robust standard errors clustered at the country level. Effect estimates are adjusted risk ratios and error bars are 95% confidence intervals.

Extended Data Fig. 5 Heterogeneity analyses for children aged 5 to 9.

Forest plot showing subgroup analyses among children aged 5 to 9 years (N = 4,818,370 person-years), with fully adjusted risk ratios of mortality with 95% confidence intervals generated using multivariable modified Poisson models with country and year fixed effects, country-level covariates (GDP per capita, PEPFAR funding budgeted, and three Worldwide Governance Indicators: Control of Corruption, Political Stability and Absence of Violence, and Voice and Accountability), and individual-level covariates (age and rural/urban setting). We used robust standard errors clustered at the country level. Effect estimates are adjusted risk ratios and error bars are 95% confidence intervals.

Extended Data Fig. 6 Heterogeneity analyses for children aged 10 to 17.

Forest plot showing subgroup analyses among children aged 10 to 17 years (N = 4,824,891 person-years), with fully adjusted risk ratios of mortality with 95% confidence intervals generated using multivariable modified Poisson models with country and year fixed effects, country-level covariates (GDP per capita, PEPFAR funding budgeted, and three Worldwide Governance Indicators: Control of Corruption, Political Stability and Absence of Violence, and Voice and Accountability), and individual-level covariates (age and rural/urban setting). We used robust standard errors clustered at the country level. Effect estimates are adjusted risk ratios and error bars are 95% confidence intervals.

Extended Data Fig. 7 Country-specific effects of cash transfer programs on mortality among adult females.

Forest plot showing country-specific effects of cash transfers on mortality among adult females (N = 14,994,934 person-years). Estimates were generated using multivariable modified Poisson models with country and year fixed effects, country-level covariates (GDP per capita, PEPFAR funding budgeted, and three Worldwide Governance Indicators: Control of Corruption, Political Stability and Absence of Violence, and Voice and Accountability), and individual-level covariates (age and rural/urban setting in all moels; sex, age of mother, and birth order in child analyses). We used robust standard errors clustered at the country level.

Extended Data Table 1 Characteristics of adult mortality dataset
Full size table
Extended Data Table 2 Characteristics of the child mortality dataset
Full size table

Supplementary information

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Richterman, A., Millien, C., Bair, E.F. et al. The effects of cash transfers on adult and child mortality in low- and middle-income countries. Nature 618, 575–582 (2023). https://doi.org/10.1038/s41586-023-06116-2

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