Forecasting preterm birth in Kazakhstan through 2050: a cohort-component demographic modeling study.

Preterm birth rates in Kazakhstan are projected to stabilize at around 30,000-33,000 cases annually by 2050, highlighting the need for long-term planning in maternal and neonatal health services.

Summary and findings

This study estimated long-term trends in preterm birth in Kazakhstan through 2050 using a cohort-component demographic modeling approach. The analysis utilized national demographic and birth data from 2009 to 2023. The projected annual number of preterm births is expected to stabilize at approximately 30,000-33,000 cases by 2050.

Abstract

Background Preterm birth remains a major global health challenge, particularly in countries undergoing demographic transition such as Kazakhstan. Objective To estimate long-term trends in preterm birth in Kazakhstan through 2050 using a cohort-component demographic modeling approach. Methods National demographic and birth data for 2009-2023 were analyzed. A cohort-component model was used to project the population of women aged 15-49 years, accounting for aging, survival, and migration. Future live births and preterm births were estimated under three combined scenarios (optimistic, baseline, and pessimistic), reflecting alternative assumptions regarding fertility and preterm birth proportions. Model performance was evaluated using out-of-sample validation for 2019-2023. Results Between 2013 and 2023, the annual number of preterm births ranged from approximately 21,000 to 27,000 cases, with an increase in the proportion observed after 2020. Under the baseline scenario, preterm births are projected to stabilize at approximately 30,000-33,000 cases annually by 2050. Predicted values closely matched observed data, with a mean absolute error of 4 cases and a root mean square error of 4.5 cases. Conclusions Preterm birth is expected to remain a sustained public health burden in Kazakhstan through 2050. The projected trends are consistent with demographic changes in the size and age structure of women of reproductive age and should be interpreted as population-level associations rather than direct causal effects. These findings underscore the need for long-term planning of maternal and neonatal health services.

Key findings

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Limitations

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Elsewhere in the HCG (Human Chorionic Gonadotropin) corpus