Social Ecological Model Interpretation of Multilevel Determinants of Severe Adverse Outcomes among Low Birth Weight Neonates in a Kenyan County Referral Hospital

Background. Adverse outcomes among low-birth-weight (LBW) neonates in low-resource settings are shaped by determinants that operate at several levels simultaneously, from neonatal biology to the organisation of the health system. Analysing these determinants in isolation obscures how they interact. This paper reframes the findings of a mixed-methods study of LBW neonates admitted to a Kenyan county referral hospital through the Social-Ecological Model (SEM), to show how individual, interpersonal, community, institutional and policy-level factors together shape the risk of a severe adverse outcome. Methods. This is an interpretive secondary synthesis of an existing mixed-methods cross-sectional study (169 LBW neonates and nine key-informant interviews with newborn-unit providers) conducted at Kericho County Referral Hospital. No new data were collected and no new models were fitted. Each quantitative determinant and qualitative theme reported in the parent papers was mapped to one of the five SEM levels using a determinant-by-level matrix, and quantitative and qualitative evidence were triangulated in a joint display. Detailed statistics are cited from the empirical papers rather than recomputed. Results. A severe adverse outcome occurred in 136 of 169 neonates (80.5%). Determinants were distributed across every ecological level. At the individual level, prematurity (85.8%), very low birth weight (18.3%), lower birth weight (adjusted odds ratio [AOR] 0.997 per gram) and maternal pregnancy-induced hypertension (25.4%; AOR 18.49) were the strongest and most consistent contributors. Interpersonal and community determinants — delayed care-seeking, transport problems (32.5%) and long distances (34.3%) — shaped the pre-hospital pathway. Institutional determinants (warm-chain care 92.9%; drug and feed shortages 58.6%; staffing pressure) and policy-level referral coordination (referred/outborn 49.1%; crude odds ratio 2.25) dominated provider accounts. Qualitative and quantitative strands converged on prematurity, low birth weight, maternal hypertension, supply shortages and referral gaps as priority targets, while staffing, infection prevention and bedside monitoring emerged as strong provider concerns not captured by measured variables. Conclusions. Viewed through the SEM, severe adverse outcomes among LBW neonates are not attributable to any single level but emerge from interacting individual, household, community, facility and system factors. The framework identifies where evidence is strong and where measurement gaps remain, and argues for multilevel interventions that pair biological risk stratification with strengthened referral systems, thermal-care capacity, reliable supplies and adequate neonatal nursing staffing.