Modeling Regional Trends in Caesarean Births across Ghana's Former Ten Regions over a Decade

Abstract

This study utilizes empirical modeling and statistical analysis to examine the temporal evolution of caesarean births in Ghana over the period 2008–2017. Building upon a robust linear framework augmented by an exponential component, the research probes the quasi-linear characteristics of the global caesarean birth frequency Nglob (t). The model demonstrates strong explanatory power, with a high correlation coefficient (R = 0.954208) indicating effective capture of temporal trends. A strategic procedure is applied to assess deviations from quasi-linearity, revealing a range of values. The relative deviation metric, together with a supplementary metric, supports a nuanced interpretation of these deviations. The annual periodicity observed in the relative deviation suggests that cultural factors influence caesarean birth rates. Region-specific analysis extends the investigation to ten regions, incorporating cumulative births (Ni,tot) and relative birth rates (Ni,rel) to provide broader insights into caesarean births across geographic subunits.Linear regression estimates optimal parameters, while correlation coefficients indicate the strength of the model fit. Monthly frequency rates per 100,000 inhabitants (αi) were computed to illuminate regional variations. Deviations from linearity are assessed for each region, highlighting distinct regional dynamics. The study concludes with the introduction of a reduced-frequency metric, which indicates an annual increase in caesarean births per 100,000 inhabitants. A linear model is employed to forecast future trends, supported by a high correlation coefficient (R = 0.93655). The research offers comprehensive insights into the dynamics of caesarean births in Ghana, with implications for healthcare planning, policy formulation, and ongoing monitoring of maternal health trends.