Maternal Anthropometric and Obstetric Risk Factors for Small‑for‑Gestational‑Age Births in Anuradhapura District, Sri Lanka: A Retrospective Case‑Control Study

Background: Small‑for‑gestational‑age (SGA), defined as birth weight below the 10th percentile for gestational age, is a major cause of neonatal morbidity and mortality, disproportionately affecting low‑ and middle‑income countries (LMICs). The Anuradhapura district of Sri Lanka carries the highest low birth weight (LBW) prevalence nationally, yet no case‑control study has systematically characterized independent maternal risk factors for SGA in this population.

Objectives: To identify maternal anthropometric, obstetric, and antenatal risk factors independently associated with SGA births in Anuradhapura district, Sri Lanka.

Methods: A retrospective, matched case‑control study was conducted using Public Health Midwife (PHM) pregnancy records from 2014 to 2017 across two Medical Officer of Health (MOH) areas. Cases (n = 136) were SGA infants (birth weight < 10th percentile for gestational age) individually matched 1:2 to average‑for‑gestational‑age (AGA) controls (n = 272) by gestational age category. Multivariable binary logistic regression with two separate models identified independent predictors.

Findings: Five independent maternal risk factors were identified. Prepregnancy weight <50 kg (adjusted OR 2.18; 95% CI, 1.28–3.69; P = 0.004), prepregnancy BMI <18.5 kg/m² (OR 2.24; 95% CI, 1.27–3.94; P = 0.005), prepregnancy BMI ≥25 kg/m² (OR 1.95; 95% CI, 1.04–3.64; P = 0.036), maternal height ≤150 cm (OR 1.98; 95% CI, 1.14–3.45; P = 0.015), and history of a prior LBW infant (OR 3.87; 95% CI, 1.98–7.57; P < 0.001) were independently associated with SGA. Borderline associations for consanguinity, anemia, and absence of folic acid supplementation did not persist in adjusted models.

Conclusions: Both undernutrition and overweight independently elevate SGA risk, reflecting a double burden of malnutrition in this LMIC setting. A prior LBW delivery is the single strongest predictor, underscoring intergenerational risk pathways. Preconception nutritional screening and targeted antenatal interventions are essential to reduce the SGA burden in Anuradhapura and comparable settings.