Determinants of the neonatal mortality rate in Peru: evidence from a panel data study, 2015–2023

López-Vidal R.; Campaña-Acuña A.; Molfino-Jaramillo C.C.; Benavides-Luyo C.; Quiñones-Laveriano D.M.; Minaya-León P. · Acta Medica Peruana (2026) · DOI: 10.35663/amp.2026.431.4201

Resumen

Objectives: To estimate the association between rurality, poverty, the employed economically active population, and the COVID-19 epidemiological period—pre-pandemic, pandemic, and post-pandemic—with the regional neonatal mortality rate in Peru during 2015–2023, using a panel data analysis. Materials and methods: An analytical, observational, ecological study using region–year panel data from 25 regional governments (GORES), 2015–2023 (225 observations). The NMR was obtained from the National Single Health Information Repository (REUNIS). Explanatory variables from the National Institute of Statistics and Informatics (INEI): rural population, poverty, and employed economically active population (EAP). The study included COVID-19 periods: pre-pandemic, pandemic, and post-pandemic. Clustered, fixed-effects, and random-effects models were fitted, with Breusch–Pagan and Hausman LM tests. Given heteroscedasticity (Wald) and autocorrelation (Wooldridge), the final model was estimated using generalized least squares (GLS), p<0.05. Results: The average MMR was 9.44 ± 3.421 per 1,000 live births (range: 3.70–21.4). Regional heterogeneity persisted: Amazonian and high-Andean regions had higher rates and greater year-to-year variability, while Lima and the coastal region showed lower and more stable values. The MCG model showed that greater rurality was associated with a higher MMR (β=0.34; 95% CI: 0.26–0.42; p<0.001) and that poverty also increased the MMR (β=0.13; 95% CI: 0.11–0.15; p<0.001). The employed labor force was not inversely associated (β=−0.546; 95% CI: −0.959 to −0.133; p=0.010). Conclusion: Compared to the post-pandemic period, the pre-pandemic (β=2.63) and pandemic (β=1.52) periods showed higher MMRs (p<0.001). The regional average mortality rate in Peru is explained by structural determinants: rurality and poverty increase the risk, while higher employment reduces it; targeted policies with an equity-focused approach are needed.

Instituciones: Universidad Científica del Sur; Universidad Ricardo Palma; Universidad Señor de Sipán