Bayesian analysis of non-communicable diseases risk factors: a focus on the lower-educated population in Bangladesh.

Abstract

Background: This study investigates non-communicable disease (NCD) risk factors, specifically hypertension and diabetes, among Bangladeshi adults with lower educational attainment. With an increasing global burden of NCDs, understanding the dynamics in lower-educated populations becomes crucial for targeted interventions and achieving Sustainable Development Goal 3.4-curtailing premature mortality from non-communicable diseases by one-third by 2030 through prevention and treatment.

Methods: Utilizing data from the Bangladesh Demographic and Health Survey (2017-2018), a two-stage stratified sampling design identified 7287 lower-educated individuals. Bayesian logistic regression was applied for risk factor analysis.

Results: The prevalence of hypertension and diabetes among lower-educated people was 31% and 9.3%, respectively. NCD prevalence (37.3%) underscored a significant health burden. Factors such as gender, age, wealth status, working status, residence and region showed significant associations with NCDs. Bayesian analysis revealed that females were 1.30 times more likely to develop NCDs, while older age groups demonstrated 4.30 times greater likelihood. Employed individuals exhibited a 43% lower risk. Wealthier households showed higher NCD likelihood and residence in the central region was associated with an 11% lower risk.

Conclusions: This study highlights the high risk of developing NCDs among lower-educated females, particularly those ≥35 y of age in Bangladesh. Therefore, targeted interventions for this group are critical to reducing NCD risks, supporting national health objectives and advancing progress toward the Sustainable Development Goals.