Predictors of diagnosed cardiovascular diseases and their spatial heterogeneity in Lagos State, Nigeria

Abstract

Cardiovascular diseases (CVDs) persist as the foremost global cause of death despite persistent efforts to comprehend the risk factors associated with them. Low- and middle-income countries (LMICs) are disproportionately affected, bearing a high burden of CVD morbidity and mortality. Nevertheless, the intricate socio-spatial landscape that could yield new insights into CVD incidence within LMICs like Nigeria has not received sufficient attention. This study aimed to determine the predictors of CVDs in a megacity in one of the LMICs and investigate their spatial heterogeneity. The study acquired and appropriately geocoded hospital records of patients clinically diagnosed with CVDs between 2008 and 2018 from a tertiary healthcare facility. Stepwise regression and geographically weighted regression were employed to identify predictors of CVDs and investigate their patterns. The study’s findings revealed that gender emerged as the primary predictor of diagnosed CVDs. Consequently, the study underscores the importance of focusing on the female population in efforts to control and prevent CVDs while advocating for the formulation and implementation of spatially sensitive policies and interventions.

Keywords

• diagnosed cvd
• geographically weighted regression
• spatial heterogeneity