Applying group-based trajectory modeling to understand under-five mortality trends and determinants in low-and lower-middle income countries
Abstract Background Reducing under-five mortality is a global health priority. Countries need specific data on which interventions have the most potential to lead to improvements to inform their programs and policies. Methods Group-based trajectory modeling was applied to identify distinct trajector...
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2025-05-01
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| Series: | Population Health Metrics |
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| Online Access: | https://doi.org/10.1186/s12963-025-00381-1 |
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| author | Kavita Singh Gustavo Angeles H. Luz McNaughton Reyes Elizabeth Simmons Alison Swiatlo William Weiss |
| author_facet | Kavita Singh Gustavo Angeles H. Luz McNaughton Reyes Elizabeth Simmons Alison Swiatlo William Weiss |
| author_sort | Kavita Singh |
| collection | DOAJ |
| description | Abstract Background Reducing under-five mortality is a global health priority. Countries need specific data on which interventions have the most potential to lead to improvements to inform their programs and policies. Methods Group-based trajectory modeling was applied to identify distinct trajectories of under-five mortality from 2000 to 2019 in 78 low and lower-middle income countries. Both health and non-health variables were studied as time-stable covariates of trajectory group membership and as time-varying covariates of mortality rates within groups. Results We identified four distinct groups that were primarily distinguished based on trajectory level rather than shape–low mortality, medium mortality, medium–high mortality and high mortality. All four groups had under-five trajectories that declined over time with the highest mortality group having the largest declines. We conducted two sets of bivariate analyses. The first analysis was conducted to understand what factors distinguished the different groups from one another (time stable covariate analysis), and the second analysis was done to understand what factors were significant within a group (time vaying covariate analysis). Results indicated that five factors were associated with all three comparisons of being in the low, medium and medium high groups compared to the highest mortality group. These factors were fertility rate, % of population with an improved water source, female secondary school enrollment rate, diphtheria, pertussis, tetanus dose 3 (DPT3) coverage and % of gross domestic product (GDP) on health expenditures. Results of the modeling of the within group analysis with time-varying factors indicated that higher fertility rates and higher out-of-pocket expenditures were significantly associated with greater mortality rates for all four groups. High DPT3 coverage, greater political stability, high coverage of births in a health facility and a greater % GDP on health expenditures were significantly associated with reduced under-five mortality for all four groups. Conclusion Findings from our study revealed the importance of considering both health and non-health factors in understanding trajectories of under-five mortality. In particular the fertility rate and % of GDP on health expenditures were signicant for all three comparisons of the trajectory group membership analysis (time-stable covariates) and were significant for all four groups in the within group analysis (time varying covariates). Other factors were significant for some comparisons and groups. Focusing on a number of key factors relevant to their group could help countries to further improve the health of young children. |
| format | Article |
| id | doaj-art-b91deb235e30432aaa13fd8d141bf0db |
| institution | DOAJ |
| issn | 1478-7954 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
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| series | Population Health Metrics |
| spelling | doaj-art-b91deb235e30432aaa13fd8d141bf0db2025-08-20T03:16:51ZengBMCPopulation Health Metrics1478-79542025-05-0123111210.1186/s12963-025-00381-1Applying group-based trajectory modeling to understand under-five mortality trends and determinants in low-and lower-middle income countriesKavita Singh0Gustavo Angeles1H. Luz McNaughton Reyes2Elizabeth Simmons3Alison Swiatlo4William Weiss5Department of Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina at Chapel HillDepartment of Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina at Chapel HillDepartment of Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina at Chapel HillDepartment of Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina at Chapel HillDepartment of Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina at Chapel HillData for Impact (D4I), Carolina Population Center, University of North Carolina at Chapel HillAbstract Background Reducing under-five mortality is a global health priority. Countries need specific data on which interventions have the most potential to lead to improvements to inform their programs and policies. Methods Group-based trajectory modeling was applied to identify distinct trajectories of under-five mortality from 2000 to 2019 in 78 low and lower-middle income countries. Both health and non-health variables were studied as time-stable covariates of trajectory group membership and as time-varying covariates of mortality rates within groups. Results We identified four distinct groups that were primarily distinguished based on trajectory level rather than shape–low mortality, medium mortality, medium–high mortality and high mortality. All four groups had under-five trajectories that declined over time with the highest mortality group having the largest declines. We conducted two sets of bivariate analyses. The first analysis was conducted to understand what factors distinguished the different groups from one another (time stable covariate analysis), and the second analysis was done to understand what factors were significant within a group (time vaying covariate analysis). Results indicated that five factors were associated with all three comparisons of being in the low, medium and medium high groups compared to the highest mortality group. These factors were fertility rate, % of population with an improved water source, female secondary school enrollment rate, diphtheria, pertussis, tetanus dose 3 (DPT3) coverage and % of gross domestic product (GDP) on health expenditures. Results of the modeling of the within group analysis with time-varying factors indicated that higher fertility rates and higher out-of-pocket expenditures were significantly associated with greater mortality rates for all four groups. High DPT3 coverage, greater political stability, high coverage of births in a health facility and a greater % GDP on health expenditures were significantly associated with reduced under-five mortality for all four groups. Conclusion Findings from our study revealed the importance of considering both health and non-health factors in understanding trajectories of under-five mortality. In particular the fertility rate and % of GDP on health expenditures were signicant for all three comparisons of the trajectory group membership analysis (time-stable covariates) and were significant for all four groups in the within group analysis (time varying covariates). Other factors were significant for some comparisons and groups. Focusing on a number of key factors relevant to their group could help countries to further improve the health of young children.https://doi.org/10.1186/s12963-025-00381-1Group-based trajectory modelingUnder-five mortalityLow and middle income countries |
| spellingShingle | Kavita Singh Gustavo Angeles H. Luz McNaughton Reyes Elizabeth Simmons Alison Swiatlo William Weiss Applying group-based trajectory modeling to understand under-five mortality trends and determinants in low-and lower-middle income countries Population Health Metrics Group-based trajectory modeling Under-five mortality Low and middle income countries |
| title | Applying group-based trajectory modeling to understand under-five mortality trends and determinants in low-and lower-middle income countries |
| title_full | Applying group-based trajectory modeling to understand under-five mortality trends and determinants in low-and lower-middle income countries |
| title_fullStr | Applying group-based trajectory modeling to understand under-five mortality trends and determinants in low-and lower-middle income countries |
| title_full_unstemmed | Applying group-based trajectory modeling to understand under-five mortality trends and determinants in low-and lower-middle income countries |
| title_short | Applying group-based trajectory modeling to understand under-five mortality trends and determinants in low-and lower-middle income countries |
| title_sort | applying group based trajectory modeling to understand under five mortality trends and determinants in low and lower middle income countries |
| topic | Group-based trajectory modeling Under-five mortality Low and middle income countries |
| url | https://doi.org/10.1186/s12963-025-00381-1 |
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