National time zone unification in Kazakhstan altered healthcare utilization and circadian re-entrainment patterns

Abstract

Abstract In March 2024, the Republic of Kazakhstan unified its administrative time to UTC + 5, creating a nationwide natural experiment across a 30-degree longitudinal gradient. This structural shift offered a rare opportunity to evaluate how abrupt temporal restructuring correlates with population-level health indicators and healthcare utilization patterns within a single jurisdiction. We integrated national clinical registry data (~ 19 million observations) with a stratified random survey ( n = 13,648) from January 2022 to March 2025. Difference-in-Differences and Interrupted Time Series models were utilized to compare 15 eastern treatment administrative units against five western controls (N_treatment = 15, N_control = 5). To address potential bias from the small number of control clusters, wild cluster bootstrap procedures (Cameron–Gelbach–Miller) were applied. Models adjusted for age, sex, residence type, chronotype, and baseline chronic disease status. During the acute phase (Months 1–6), cardiovascular consultations increased by a relative 11.4% (95% CI 9.2–13.6%, wild bootstrap p = 0.024) in unified regions compared to western controls. Survey data identified a distinct spatial gradient, where residents in eastern longitudes (82°E) reported higher odds of sleep disturbances (aOR 4.21; 95% CI 3.85–4.65) and cephalalgia. However, longitudinal monitoring through early 2025 identified a trajectory of convergence toward pre-intervention trends. Late-period clinical utilization rates showed no statistically significant deviation from modelled baseline expectations ( p = 0.38), indicating a stabilization of observable indicators. Nationwide administrative unification was associated with transient changes in healthcare utilization and self-reported health outcomes. These deviations attenuated over time, with a return to projected baselines observed within one year. The findings provide descriptive evidence of population-level health service responses while remaining limited to observational inference regarding underlying physiological mechanisms.