Anthropometric Status, Menstrual Health, and Psychosocial Correlates Among 4251 Adolescent Girls in Kazakhstan: A School-Based Cross-Sectional Study

Background/Objectives: Menstrual health in adolescence is influenced by nutritional, developmental, and psychosocial factors, yet integrated school-based evidence from Central Asia is limited. We assessed recorded anthropometric, menstrual/reproductive, and psychosocial indicators among adolescent girls in southern Kazakhstan and evaluated factors associated with a prespecified composite menstrual/reproductive outcome. Methods: We conducted a cross-sectional secondary analysis of a non-public school health screening database containing 5197 participant records from 2025. After removal of 946 exact duplicate copies, 4251 unique records of girls aged 12–18 years remained. We present prevalence estimates with Wilson 95% confidence intervals (CIs). We estimated adjusted prevalence ratios (aPRs) using modified Poisson regression with robust standard errors clustered by recorded school field. Results: Mean age was 15.03 ± 1.23 years and mean BMI was 20.36 ± 3.36 kg/m2. The source form used fixed adult BMI categories; these are reported descriptively and are not interpreted as pediatric nutritional diagnoses. At least one non-reference menstrual or reproductive indicator was recorded in 24.1% of participants; severe menstrual pain and stress were each recorded in 6.9%. Stress was associated with any menstrual/reproductive abnormality (aPR 2.05, 95% CI 1.65–2.54) and with severe menstrual pain (aPR 3.27, 95% CI 2.39–4.46). Unsatisfactory nutrition was also associated with the composite outcome (aPR 1.64, 95% CI 1.35–2.00). Conclusions: Recorded menstrual/reproductive concerns were frequent in this screened sample, and stress showed consistent associations with menstrual outcomes. Because anthropometric categories were based on adult cut points and several screening items were not validated instruments, interpret the findings as descriptive and hypothesis-generating rather than as population prevalence or causal estimates.