Life expectancy nexus mortality in 14 selected SADC countries with trend analysis

Abstract Background This study provides a dimensional analysis of the nexus between life expectancy and mortality-related indicators across 14 Southern African Development Community (SADC) countries over a 13-year historical period (2010–2022). Objective The objective is to analyse the historical impacts of health and economic indicators on life expectancy and to forecast regional development trends up to 2027. Methodology The study utilizes a panel dataset of 14 nations, providing a robust sample size for longitudinal analysis. Methodologically, the research employs a Generalized Method of Moments (GMM) to account for endogeneity and a machine learning Random Forest model to capture non-linear predictive dynamics. Model diagnostics, including VIF and serial correlation tests (Arellano–Bond), confirm the validity of the estimators, while the Hausman test justifies the preference for a Fixed Effects (FE) model to address country-specific unobserved heterogeneity. Results Empirical findings reveal that infant mortality (IM), under-5 mortality, and HIV prevalence are the most significant negative predictors of life expectancy, with the Random Forest model confirming these as the dominant determinants (variable importance = 0.541 for IM). The GMM estimation highlights a diminishing marginal return on government health expenditure (GHE) and an accelerating positive impact of GDP on longevity. Projections from 2023 to 2027 suggest continued regional growth, yet stark disparities persist: Mauritius is forecasted to maintain the highest life expectancy (74.44 years), while Lesotho and the DRC are projected to remain at the lower end (approx. 61–63 years). Policy recommendations To improve life expectancy across the region, policy recommendations must shift from a singular focus on economic output to targeted interventions in maternal/child health and HIV control. SADC member states should institutionalize aggressive Maternal and Child Health (MCH) programs prioritizing sustainable funding for prenatal care, neonatal intensive care units, and universal immunization as the primary lever for rapid health improvements. Given the strong negative association between HIV prevalence and life expectancy in our analysis, interventions that effectively reduce HIV prevalence may be associated with improved life expectancy outcomes. Furthermore, SADC should implement coordinated, cross-border health protocols and establish a formal Health Technology Transfer Fund to replicate successful primary healthcare models in lower-performing nations. Finally, national governments should transition from input-based to outcome-based health budgeting, ensuring financial resources are directed toward frontline services rather than administrative overhead. Novelty The novelty of this study is grounded in its methodological innovation, predictive precision, and policy operationalization. First, it departs from conventional linear analysis by integrating Generalized Method of Moments (GMM) with non-linear machine learning architectures (Random Forest), allowing for a more accurate capture of the complex, threshold-dependent relationships between health and economic indicators than traditional OLS models can achieve. Second, the study provides granular, country-specific projections for 14 SADC nations through 2027, moving beyond aggregate regional averages to offer actionable, nation-specific health trajectories that account for unique local heterogeneities. Third, by demonstrating that life expectancy gains in the region are currently “decoupled” from GDP growth, the study introduces an outcome-based policy framework that explicitly identifies infant mortality and viral load suppression as the primary levers for regional health convergence, challenging the assumption that macro-economic growth automatically resolves mortality crises.