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Child fostering in a changing climate: evidence from sub-Saharan Africa

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Abstract

An extensive social science literature has examined the effects of climate change on human migration. Prior studies have focused largely on the out-migration of working age adults or entire households, with less attention to migration and other forms of geographic mobility among other age groups, including youth. In this study, we focus on the implications of climate variability for the movement of children by examining the association between climate exposures and the in- and out-fostering of children in sub-Saharan Africa. We link high-resolution temperature and precipitation records to data from the Demographic and Health Surveys for 23 sub-Saharan African countries. We fit a series of regression models to measure the overall associations between climate exposures and each outcome and then evaluate whether these associations are moderated by socioeconomic status, the number of children in the household, and the prevalence of fostering in each country. Precipitation is positively associated with in-fostering overall, and these effects are especially strong among households that already have at least one child and in countries where child fostering is common. We find no overall relationship between either temperature or precipitation exposures and out-fostering, but we do detect significant effects among households with many children and those with more educated heads. In sum, our findings suggest that climate variability can influence child mobility, albeit in complex and in some cases context-specific ways. Given the socioeconomic and health implications of fostering, these results underline another pathway through which climate exposures can affect children’s well-being. More broadly, this study shows that new attention to the links between climate variability, child fostering, and other understudied forms of spatial mobility is needed to fully understand the effects of climate change on human populations.

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Notes

  1. While it is possible that fostering may occur within very small geographic areas (e.g., within a village or neighborhood), we assume that a change in guardianship involves a move across a non-trivial distance in most cases.

  2. Temperature and precipitation anomalies capture short-term climate variability (i.e., short-term deviations from long-term climate averages), which is distinct from climate change (i.e., long-term shifts in the temperature and precipitation distributions). Despite these differences, it is currently standard practice among population-environment scholars to measure the demographic impacts of climate variability and (implicitly or explicitly) use those estimates to inform expectations about the likely effects of future climate change (e.g., Bohra-Mishra et al., 2014; Davenport et al., 2017; Thiede & Strube, 2020).

  3. Importantly, however, Mueller et al. (2020a) also find evidence of displacing effects in their study. For example, stresses associated with precipitation deficits increase out-migration in Botswana and Kenya.

  4. One other exception is a recent simulation of the links between rainfall and return migration in Thailand by Entwisle and colleagues (2020). This analysis highlighted the economic demands that returning migrants may place on receiving households.

  5. Relatedly, in some situations, children may be fostered in anticipation of future shocks (Kielland, 2016).

  6. For example, while all households are at risk of in-fostering, out-fostering can only occur among households with children.

  7. The motivations for this sequence of interaction models were determined before the analysis, drawing on prior demographic research and considering what DHS data could be used appropriately. As described below, we do not include moderators (or controls) that could have been plausibly affected by the focal climate exposure terms.

  8. The household sample weight is variable hv005 in the original DHS files, and is used as recommended by the DHS program. According to DHS documentation, “The household weight…for a particular household is the inverse of its household selection probability multiplied by the inverse of the household response rate in the stratum” (Croft et al., 2018: 1.31).

  9. We exclude 18,102 households with a large number (9+) of children to avoid outliers that we expect may reflect measurement error in many cases.

  10. Information on who the child resides with (e.g., other parent, relatives, and others) is only available for some DHS surveys and is therefore not used in the analysis.

  11. This assumption is important to our analysis and merits at least two points of elaboration. First, we are making assumptions about the initial decision to in- or out-foster a child, which is distinct from questions about the duration of fostering. The latter is important but cannot be analyzed precisely using our data—a limitation we discuss more in the concluding section. Second, previous research does not provide clear guidance about the presence and length of potentially lagged effects. We therefore tested the robustness of our findings in a supplementary model that included additional controls for temperature and precipitation anomalies in each of the five years prior to the survey (Models 9–12 and 17–20). Our main conclusions about the effects of temperature and precipitation in year t−1 did not change after controlling for conditions in these earlier years.

  12. This measurement strategy does not capture intra-annual variation in temperature and precipitation, differences in which may be masked by annual averages. This limitation could be substantively meaningful in some situations. For example, a location that experienced alternating periods of much-above and much-below average temperatures or precipitation could have the same annual anomaly as a location that experienced average conditions consistently.

  13. We use the term province to describe all first-level sub-national administrative units.

  14. We henceforth refer to the number of children in the household for brevity. We do not measure the number of children born to non-surveyed women in the household (i.e., older women without birth histories) because of challenges measuring non-resident children.

  15. We do not include controls (e.g., household wealth) or moderators that are measured at the time of the survey and potentially influenced by the focal climate exposures and fostering decisions. Such variables constitute poor control variables (Angrist & Pischke, 2009). We also note that the DHS collects relatively limited information on household social and economic dynamics (e.g., excluding detailed income or consumption records), which is appropriate given its focus on demographic and health outcomes but imposes some limitations on our analysis. We ran an additional robustness check controlling for at least one woman in the household working in agriculture (Models 13-16 and 21-24). Results from these analyses were consistent with our main findings.

  16. We take the average across all years of data for countries with multiple surveys in the analytic sample.

  17. We are likewise unable to detect climate effects on very short-term fostering arrangements that occurred between the exposure period and the DHS interview.

References

  • Akresh, R. (2009). Flexibility of household structure child fostering decisions in Burkina Faso. Journal of Human Resources, 44(4), 976–997.

    Article  Google Scholar 

  • Alber, E. (2018). Transfer of belonging. Brill.

  • Andriano, L., & Monden, C. W. (2019). The causal effect of maternal education on child mortality: Evidence from a quasi-experiment in Malawi and Uganda. Demography, 56(5), 1765–1790.

    Article  Google Scholar 

  • Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton University Press.

    Book  Google Scholar 

  • Archambault, C., & de Laat, J. (2010). Social mobility in children’s mobility? An investigation into child circulation among the Maasai of Kenya. Children and migration: At the crossroads of resiliency and vulnerability, 187–206.

  • Archambault, C. S., de Laat, J., & Zulu, E. M. (2012). Urban services and child migration to the slums of Nairobi. World Development, 40(9), 1854–1869.

    Article  Google Scholar 

  • Bachan, L. (2014). Anticipatory child fostering and household economic security in Malawi. Demographic Research, 30, 1157–1188. https://doi.org/10.4054/DemRes.2014.30.40

    Article  Google Scholar 

  • Baker, R. E., & Anttila-Hughes, J. (2020). Characterizing the contribution of high temperatures to child undernourishment in Sub-Saharan Africa. Scientific Reports, 10(1), 1–10.

    Article  Google Scholar 

  • Beck, S., Vreyer, P. D., Lambert, S., Marazyan, K., & Safir, A. (2015). Child fostering in Senegal. Journal of Comparative Family Studies, 46(1), 57–73. https://doi.org/10.3138/jcfs.46.1.57

    Article  Google Scholar 

  • Beegle, K., Dehejia, R. H., & Gatti, R. (2006). Child labor and agricultural shocks. Journal of Development Economics, 81(1), 80–96. https://doi.org/10.1016/j.jdeveco.2005.05.003

    Article  Google Scholar 

  • Behrman, J. A. (2019). Polygynous unions and intimate partner violence in Nigeria: An examination of the role of selection. Journal of Marriage and Family, 81(4), 905–919.

    Article  Google Scholar 

  • Biddlecom, A. E., Axinn, W. G., & Barber, J. S. (2005). Environmental effects on family size preferences and subsequent reproductive behavior in Nepal. Population and Environment, 26(3), 183–206.

    Article  Google Scholar 

  • Bilsborrow, R. E. (1987). Population pressures and agricultural development in developing countries: A conceptual framework and recent evidence. World Development, 15(2), 183–203.

    Article  Google Scholar 

  • Black, R., Bennett, S. R., Thomas, S. M., & Beddington, J. R. (2011). Migration as adaptation. Nature, 478(7370), 447–449.

    Article  Google Scholar 

  • Bledsoe, C. (1990). “No success without struggle”: Social mobility and hardship for foster children in Sierra Leone. Man, 25(1), 70–88. https://doi.org/10.2307/2804110

    Article  Google Scholar 

  • Bledsoe, C. H., Ewbank, D. C., & Isiugo-Abanihe, U. C. (1988). The effect of child fostering on feeding practices and access to health services in rural Sierra Leone. Social Science & Medicine, 27(6), 627–636.

    Article  Google Scholar 

  • Bohra-Mishra, P., Oppenheimer, M., & Hsiang, S. M. (2014). Nonlinear permanent migration response to climatic variations but minimal response to disasters. Proceedings of the National Academy of Sciences, 111(27), 9780–9785.

    Article  Google Scholar 

  • Borderon, M., Sakdapolrak, P., Muttarak, R., Kebede, E., Pagogna, R., & Sporer, E. (2019). Migration influenced by environmental change in Africa. Demographic Research, 41, 491–544.

    Article  Google Scholar 

  • Bougma, M., LeGrand, T. K., & Kobiané, J. F. (2015). Fertility decline and child schooling in urban settings of Burkina Faso. Demography, 52(1), 281–313.

    Article  Google Scholar 

  • Boyle, E.H., King, M., & Sobek, M. (2020a) IPUMS demographic and health surveys. Version 8 . Minneapolis, MN: IPUMS and ICF. https://doi.org/10.18128/D080.V8

  • Boyle, E. H., King, M. L., Garcia, S., Culver, C., & Bourdeaux, J. (2020b). Contextual data in IPUMS DHS: Physical and social environment variables linked to the Demographic and Health Surveys. Population and Environment, 1–21.

  • Call, M., & Gray, C. (2020). Climate anomalies, land degradation, and rural out-migration in Uganda. Population and Environment, 41, 507–528.

    Article  Google Scholar 

  • Carleton, T. A., & Hsiang, S. M. (2016). Social and economic impacts of climate. Science, 353(6304),aad9837.

  • Carrico, A. R., Donato, K. M., Best, K. B., & Gilligan, J. (2020). Extreme weather and marriage among girls and women in Bangladesh. Global Environmental Change, 65, 102160.

    Article  Google Scholar 

  • Corno, L., Hildebrandt, N., & Voena, A. (2020). Age of marriage, weather shocks, and the direction of marriage payments. Econometrica, 88(3), 879–915.

    Article  Google Scholar 

  • Cotton, C. (2021). An enduring institution? Child fostering in sub‐Saharan Africa. Population and Development Review, padr.12439. https://doi.org/10.1111/padr.12439

  • Cotton, C., Clark, S., & Madhavan, S. (2022). One hand does not bring up a child. Demographic Research, 46, 865–904.

    Article  Google Scholar 

  • Croft, T. N., Marshall, A. M., Allen, C. K., Arnold, F., Assaf, S., & Balian, S. (2018). Guide to DHS statistics. Rockville: ICF, 645.

  • Davenport, F., Grace, K., Funk, C., & Shukla, S. (2017). Child health outcomes in sub-Saharan Africa: A comparison of changes in climate and socio-economic factors. Global Environmental Change, 46, 72–87.

    Article  Google Scholar 

  • Davis, K. (1963). The theory of change and response in modern demographic history. Population Index, 29(4), 345–366.

    Article  Google Scholar 

  • DeWaard, J., Hunter, L. M., Mathews, M. C., Quiñones, E. J., Riosmena, F., & Simon, D. H. (2022). Operationalizing and empirically identifying populations trapped in place by climate and environmental stressors in Mexico. Regional Environmental Change, 22(1), 29.

    Article  Google Scholar 

  • Ellis, F. (1998). Household strategies and rural livelihood diversification. The Journal of Development Studies, 35(1), 1–38.

  • Eloundou-Enyegue, P. M., & Shapiro, D. (2004). Buffering inequalities: The safety net of extended families. In Cameroon. SAGA Working Paper.

  • Entwisle, B., Verdery, A., & Williams, N. (2020). Climate change and migration: New insights from a dynamic model of out-migration and return migration. American Journal of Sociology, 125(6), 1469–1512.

    Article  Google Scholar 

  • Fortson, J. G. (2008). The gradient in sub-Saharan Africa: Socioeconomic status and HIV/AIDS. Demography, 45(2), 303–322.

    Article  Google Scholar 

  • Fussell, E., Hunter, L. M., & Gray, C. L. (2014). Measuring the environmental dimensions of human migration: The demographer’s toolkit. Global Environmental Change, 28, 182–191.

    Article  Google Scholar 

  • Gaydosh, L. (2015). Childhood risk of parental absence in Tanzania. Demography, 52(4), 1121–1146. https://doi.org/10.1007/s13524-015-0411-4

    Article  Google Scholar 

  • Goody, E. (1982). Fostering and occupational roles in West Africa. Cambridge University Press.

    Google Scholar 

  • Grace, K., Hertrich, V., Singare, D., & Husak, G. (2018). Examining rural Sahelian out-migration in the context of climate change: An analysis of the linkages between rainfall and out-migration in two Malian villages from 1981 to 2009. World Development, 109, 187–196.

    Article  Google Scholar 

  • Grant, M. J., & Yeatman, S. (2014). The impact of family transitions on child fostering in rural Malawi. Demography, 51(1), 205–228.

    Article  Google Scholar 

  • Gray, C., & Mueller, V. (2012). Drought and population mobility in rural Ethiopia. World Development, 40(1), 134–145.

    Article  Google Scholar 

  • Gray, C., & Wise, E. (2016). Country-specific effects of climate variability on human migration. Climatic Change, 135(3–4), 555–568.

    Article  Google Scholar 

  • Hampshire, K., Porter, G., Agblorti, S., Robson, E., Munthali, A., & Abane, A. (2015). Context matters: Fostering, orphanhood and schooling in sub-Saharan Africa. Journal of Biosocial Science, 47(02), 141–164.

    Article  Google Scholar 

  • Headey, D. D., & Ruel, M. T. (2022). Economic shocks predict increases in child wasting prevalence. Nature Communications, 13(1), 2157.

    Article  Google Scholar 

  • Heath, R., Hidrobo, M., & Roy, S. (2020). Cash transfers, polygamy, and intimate partner violence: Experimental evidence from Mali. Journal of Development Economics, 143, 102410.

    Article  Google Scholar 

  • Hedges, S., Sear, R., Todd, J., Urassa, M., & Lawson, D. W. (2019). Earning their keep? Fostering, children’s education, and work in north-western Tanzania. Demographic Research, 41, 263–292. https://doi.org/10.4054/DemRes.2019.41.10

    Article  Google Scholar 

  • Hoddinott, J., & Mekasha, T. J. (2020). Social protection, household size, and its determinants: Evidence from Ethiopia. The Journal of Development Studies, 1–20. https://doi.org/10.1080/00220388.2020.1736283

  • Hoffmann, R., Dimitrova, A., Muttarak, R., Crespo Cuaresma, J., & Peisker, J. (2020). A meta-analysis of country-level studies on environmental change and migration. Nature Climate Change, 10(10), 904–912. https://doi.org/10.1038/s41558-020-0898-6

    Article  Google Scholar 

  • Hunter, L. M., Luna, J. K., & Norton, R. M. (2015). Environmental dimensions of migration. Annual Review of Sociology, 41(1), 377–397. https://doi.org/10.1146/annurev-soc-073014-112223

    Article  Google Scholar 

  • ICF. (2023). “Methodology.” The DHS Program. http://www.dhsprogram.com. [June, 22, 2023].

  • Jensen, R. (2000). Agricultural volatility and investments in children. American Economic Review, 90(2), 399–404.

    Article  Google Scholar 

  • Kalipeni, E. (1996). Demographic response to environmental pressure in Malawi. Population and Environment, 17(4), 285–308.

    Article  Google Scholar 

  • Kielland, A. (2016). The role of risk perception in child mobility decisions in West Africa, empirical evidence from Benin. World Development, 83, 312–324. https://doi.org/10.1016/j.worlddev.2016.01.008

    Article  Google Scholar 

  • Kielland & Gaye. (2010). Climate change and the role of children in household risk management strategies in rural Senegal (Report No. 69811). World Bank. https://openknowledge.worldbank.org/server/api/core/bitstreams/edd0cd61-a9dd-5c5b-a228-97e9c2868c8a/content

  • Kielland, A., & Kebede, T. A. (2020). Drought vulnerability and child mobility in rural Senegal. Forum for Development Studies, 47(3), 427–445. https://doi.org/10.1080/08039410.2020.1739122

    Article  Google Scholar 

  • Knox, J., Hess, T., Daccache, A., & Wheeler, T. (2012). Climate change impacts on crop productivity in Africa and South Asia. Environmental Research Letters, 7(3), 034032.

    Article  Google Scholar 

  • Madhavan, S., Schatz, E., Clark, S., & Collinson, M. (2012). Child mobility, maternal status, and household composition in rural South Africa. Demography, 49(2), 699–718.

    Article  Google Scholar 

  • Massey, D. S., Axinn, W. G., & Ghimire, D. J. (2010). Environmental change and out-migration: Evidence from Nepal. Population and Environment, 32, 109–136.

    Article  Google Scholar 

  • McDaniel, A., & Zulu, E. (1996). Mothers, fathers, and children: Regional patterns in child-parent residence in sub-Saharan Africa. African Population Studies, 11(1), 1–28.

    Google Scholar 

  • Mounirou, I., & Yebou, J. (2022). Perceptions of climate risks and migration of agricultural producers in northern Benin. Society & Natural Resources, 36(2), 190–208.

    Article  Google Scholar 

  • Mueller, V., Gray, C., & Hopping, D. (2020a). Climate-induced migration and unemployment in middle-income Africa. Global Environmental Change, 65, 102183.

    Article  Google Scholar 

  • Mueller, V., Gray, C., & Kosec, K. (2014). Heat stress increases long-term human migration in rural Pakistan. Nature Climate Change, 4(3), 182–185.

    Article  Google Scholar 

  • Mueller, V., Sheriff, G., Dou, X., & Gray, C. (2020b). Temporary migration and climate variation in eastern Africa. World Development, 126, 104704.

    Article  Google Scholar 

  • Nawrotzki, R. J., & DeWaard, J. (2018). Putting trapped populations into place: Climate change and inter-district migration flows in Zambia. Regional Environmental Change, 18(2), 533–546.

    Article  Google Scholar 

  • Pickering, A. J., & Davis, J. (2012). Freshwater availability and water fetching distance affect child health in sub-Saharan Africa. Environmental Science & Technology, 46(4), 2391–2397.

    Article  Google Scholar 

  • Rigaud, K. K., de Sherbinin, A., Jones, B., Bergmann, J., Clement, V., Ober, K., & Midgley, A. (2018). Groundswell: Preparing for internal climate migration. Washington,, DC: World Bank.

  • Schlenker, W., & Lobell, D. B. (2010). Robust negative impacts of climate change on African agriculture. Environmental Research Letters, 5(1), 014010.

    Article  Google Scholar 

  • Sekhri, S., & Storeygard, A. (2014). Dowry deaths: Response to weather variability in India. Journal of Development Economics, 111, 212–223.

    Article  Google Scholar 

  • Serra, R. (2009). Child fostering in Africa: When labor and schooling motives may coexist. Journal of Development Economics, 88(1), 157–170.

    Article  Google Scholar 

  • Sheffield, J., Goteti, G., & Wood, E. F. (2006). Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate, 19(13), 3088–3111.

    Article  Google Scholar 

  • Thalheimer, L., Schwarz, M. P., & Pretis, F. (2023). Large weather and conflict effects on internal displacement in Somalia with little evidence of feedback onto conflict. Global Environmental Change, 79, 102641.

    Article  Google Scholar 

  • Thiede, B. C., Randell, H., & Gray, C. (2022). The childhood origins of climate-induced mobility and immobility. Population and Development Review, 48(3), 767–793.

    Article  Google Scholar 

  • Thiede, B. C., & Strube, J. (2020). Climate variability and child nutrition: Findings from sub-Saharan Africa. Global Environmental Change, 65, 102192.

    Article  Google Scholar 

  • Tsaneva, M. (2020). The effect of weather variability on child marriage in Bangladesh. Journal of International Development, 32(8), 1346–1359.

    Article  Google Scholar 

  • Weinreb, A., Stecklov, G., & Arslan, A. (2020). Effects of changes in rainfall and temperature on age- and sex-specific patterns of rural-urban migration in sub-Saharan Africa. Population and Environment, 42(2), 219–254. https://doi.org/10.1007/s11111-020-00359-1

    Article  Google Scholar 

  • Zimmerman, F. J. (2003). Cinderella goes to school the effects of child fostering on school enrollment in South Africa. Journal of Human Resources, 38(3), 557.

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Funding

Ronnkvist acknowledges support from the University of Wisconsin-Madison’s University Fellowship. Support for this fellowship is provided by the Graduate School, part of the Office of Vice Chancellor for Research and Graduate Education at the University of Wisconsin-Madison, with funding from the Wisconsin Alumni Research Foundation and the UW-Madison. Ronnkvist also acknowledges the support of the Center for Demography and Ecology (P2C HD047873 & T32 HD007014). Thiede acknowledges the assistance provided by the Population Research Institute at Penn State University, which is supported by an infrastructure grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (P2CHD041025). Thiede’s work was also supported by the USDA National Institute of Food and Agriculture and Multistate Research Project #PEN04623 (Accession #1013257). Barber acknowledges support from The Pennsylvania State University’s College of Agricultural Sciences undergraduate research award program.

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Ronnkvist, S.R., Thiede, B.C. & Barber, E. Child fostering in a changing climate: evidence from sub-Saharan Africa. Popul Environ 45, 29 (2023). https://doi.org/10.1007/s11111-023-00435-2

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