Spatial Distribution and Factors Associated With Risky Health Behavior Among Adult Males Aged 15-59 Years in Ethiopia: Generalized Structural Equation Modeling

BackgroundAlcohol drinking and tobacco smoking are the largest preventable causes of death and important risk factors for a number of non-communicable diseases and cause premature death and many socioeconomic consequences. Therefore, the present study is aimed to assess the spatial distribution of risky health behavior and its associated factors among adult males in Ethiopia. MethodsAll men (12,688) within the age range of 15-59 years were included in the final analysis. The distribution of risky health behavior across the country was observed by using ArcGIS software. In SaTScan software, the Bernoulli model was fitted by Kulldorff methods to identify the purely spatial clusters of risky health behavior. Generalized Structural Equation Model (GSEM) was used to determine factors associated with risky health behavior (regular alcohol drinking and tobacco smoking). ResultsRisky health behavior had spatial variation across the country. The primary clusters were located in Tigray, Amhara, and north-eastern Benishangul national regional states. Spatial scan statistics identified 118 primary clusters [Log-Likelihood ratio (LLR) = 524.8, p < 0.001]. Residence, frequency of listening to a radio, occupation, and frequency of watching television were significantly associated with drinking alcohol, whereas wealth index was associated with tobacco smoking. Age, region, educational status, marital status, and religion had association with both domains of risky health behavior. ConclusionRisky health behavior had spatial variation across the country. Bans on advertising and promotion of alcohol and tobacco on national press media should be strengthened. Aggressive health education efforts should be directed toward this high-risk population (Tigray, Amhara, and north-eastern Benishangul regional states). Improving risky health behavior is an important approach to reducing health disparities and promoting a more cost-effective utilization of scarce resources in the public health sector.