Stroke has a high global burden, which is highest in low and middle-income countries (LMICs). Recurrent strokes contribute heavily to this burden, making secondary prevention crucial. Adopting healthy lifestyles is essential for stroke secondary prevention but remains low among individuals post-stroke. While studies in high-income countries provide valuable insights, their findings may not be directly applicable to LMICs due to cultural and contextual differences. Identifying key predictors of the adoption of healthy lifestyle behaviors in a middle-income country can target individuals who may benefit most from non-pharmacological, non-surgical stroke secondary prevention interventions and guide the development of interventions focused on these mediators.

To investigate whether sociodemographic and routinely assessed clinical risk factors for recurrent stroke variables predict the adoption of healthy lifestyle behaviors post-stroke in a middle-income country.

A cross-sectional study was conducted with approval from the Institutional Ethical Review Board. All individuals admitted to a public hospital Stroke Unit between September-2019 and February-2021 were invited to participate in a previous cohort study. Two years later, they were contacted via telephone call for this study. Those who consented were screened for cognitive and language impairments that could hinder telephone interviews by a trained researcher. Using the Stroke RiskometerTM App, four healthy lifestyle behaviors were considered dependent variables: physical activity participation, healthy eating, smoking abstinence, and safe alcohol consumption. A fifth dependent variable assessed adherence to all four behaviors. Independent predictors included sociodemographic factors (age and sex) and clinical risk factors (cardiac condition, hypertension, diabetes, body mass index, and emotional stress/depression). Binary logistic regression (a = 5%) was employed.

Among 81 participants (63 ± 14 years, 51% male), 22% engaged in physical activity = 2.5 hours/week, 68% consumed = 2 servings of fruits/vegetables daily, 88% were non-smokers, and 95% reported safe alcohol consumption. Only 16% adopted all four behaviors. Regression models for physical activity, healthy eating, and safe alcohol consumption did not identify significant predictors. The model for smoking abstinence (correct classification = 87.7%) revealed that emotional stress/depression predicted smoking (p = 0.036, B = 1.896, OR = 6.659, 95%CI = 1.137-39.013). Individuals without emotional stress/depression were more likely to be non-smokers. The model for adopting all four behaviors (correct classification = 82.7%) identified age as a significant predictor (p = 0.023, B = -0.072, OR = 0.931, 95%CI = 0.875-0.990), with older individuals less likely to adopt all healthy behaviors.

Emotional stress/depression and age were predictors of adopting healthy lifestyle behaviors post-stroke in a middle-income country, highlighting their importance in targeting secondary prevention interventions.

Smoking cessation interventions should consider additional support for individuals experiencing emotional stress/depression. Secondary prevention strategies should also target older individuals to enhance their adherence to multiple healthy behaviors. While age cannot be modified, older individuals may require intensive behavioral strategies to reduce stroke recurrence risk. The low physical activity rate (22%) aligns with findings from another study conducted in a middle-income country, emphasizing the need for targeted interventions. Despite the high smoking cessation rate, relapse remains a concern, reinforcing the need for sustained prevention efforts. Additionally, studies should incorporate feasible clinical measurements to refine these findings further.