Background: Regional forecasts of the population aged 6–17 years can provide demographic denominators for education and school health planning, but they do not directly estimate health-service or workforce requirements. This study aimed to forecast the population aged 6–17 years across Kazakhstan’s 20 territorial units through 2030 and to compare the historical accuracy of a focal age-shift cohort model with ARIMA and ETS benchmarks. Methods: Official aggregated population data for 2015–2025 were analyzed for 20 territorial units by region, sex, locality type, and single year of age. The cohort, ARIMA, and ETS models were evaluated on the same five expanding-window one-step targets for 2021–2025. Empirical uncertainty in cohort-transition ratios was assessed using transition-year block bootstrap resampling; coefficient sensitivity and exploratory migration-effect stress tests were also examined. Results: The cohort model had the lowest rolling-origin RMSE in 17 of 20 territories, compared with two for ETS and one for ARIMA. By 2030, the largest point-estimate increases were projected for Astana, Shymkent, Almaty city, and Mangystau Region, while the largest decline was projected for North Kazakhstan Region. Empirical uncertainty intervals supported growth in eight territories and decline in two; the direction remained uncertain in ten. Conclusion: Under the primary validation design, the cohort model had the lowest historical forecast error by RMSE in most territories. The projections quantify a demographic denominator; translating them into staffing, service, or infrastructure requirements requires additional data on morbidity, coverage, utilization, accessibility, productivity, and existing capacity.

Objective: To assess the structure and regional variation in mortality among school-aged children in Kazakhstan from 2015 to 2024, and to determine its association with dietary patterns and socio-economic factors. Materials and Methods: An ecological inter-regional analysis was conducted using official statistical data of the Republic of Kazakhstan. Mortality rates among children aged 6–17 years, the distribution of death causes according to ICD-10, indicators of consumption of major food product groups, and poverty levels were examined. Linear mixed-effects regression with a random intercept for region and fixed effects for year and covariates, and spatial description of regional trends were applied. Results: Variation in school-age mortality across regions and calendar years was evident, with external causes predominating, followed by diseases of the nervous system, neoplasms, and diseases of the circulatory and respiratory systems in the mortality structure. In the multivariable linear mixed-effects model, none of the dietary or socioeconomic predictors showed statistically significant independent associations with mortality (all p > 0.05), and the calendar year was not significant (p = 0.180). Model explanatory power was very low (marginal R² = 0.017; conditional R² = 0.020; ICC = 0.005), and residuals demonstrated significant temporal autocorrelation (p < 0.001). Conclusions: The mortality structure among school-aged children is shaped by a complex interplay of medical, social, and behavioral determinants. Dietary and socioeconomic indicators showed only weak ecological associations with mortality and did not retain independent effects after multivariable adjustment, underscoring the multifactorial nature of regional mortality patterns and the need for multisectoral action, including improved access to nutritious foods, enhanced social well-being, and strengthened health system capacity.