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Background: Despite weekly iron-folic acid (WIFA) supplementation, the prevalence of anaemia among Indonesian adolescent girls remains high. This suggests that factors beyond micronutrient deficiency, such as anthropometric and haemodynamic status, may influence haemoglobin levels. This study aimed to analyze the effect of anthropometric measurements (weight, height, waist circumference, MUAC) and blood pressure on haemoglobin (Hb) levels among students in stunting-prone areas.
Methods: This analytical observational study with a longitudinal component (baseline-endline) embedded within an intervention framework was conducted at four high schools in Cianjur (January–December 2025). A total of 112 adolescent girls were allocated to the intervention (n=57) and control (n=55) groups. Baseline homogeneity between groups was assessed using the Mann-Whitney U test. Intra-group and inter-group changes in haemoglobin levels were analyzed using the Wilcoxon signed-rank and Mann-Whitney U tests, respectively. Spearman’s rank correlation was executed to examine crude bivariate relationships between haemoglobin and anthropometric/haemodynamic parameters. To identify the independent predictors of haemoglobin without data transformation, multivariate analysis was performed via General Linear Regression with a robust bootstrapping approach (2,000 resamples), while multicollinearity was monitored using the Variance Inflation Factor (VIF).
Results: The multiple linear regression model was statistically significant (p=0.036), explaining 13.2% of the variance in haemoglobin levels (R2=0.132). This indicates that other unobserved factors heavily complement body dimensions and blood pressure in driving haemoglobin levels. The bootstrap parameter estimates revealed that systolic (p=0.011) and diastolic (p=0.025) blood pressure were significant independent predictors. In contrast, anthropometric indices, including body weight (p=0.208), MUAC (p=0.474), height (p=0.358) and waist circumference (p=0.077) did not show a significant independent influence on haemoglobin levels.
Conclusion: Haemodynamic parameters are significant predictors of haemoglobin levels in adolescents within stunting-prone areas, whereas weight, MUAC, height, and waist circumference lack an independent influence. However, the overall model indicates that these parameters collectively contributed to the haemoglobin variance. Integrated monitoring of Hb, blood pressure, and anthropometry is crucial for early detection and comprehensive anaemia management to optimize health outcomes in adolescents.
