Digital access and structural indicators of social isolation among older adults in Rwanda: a nationally representative study

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Background Social isolation and reduced social connectedness are important public health concerns among older adults and are associated with adverse health outcomes. In LMICs, digital expansion may offer new opportunities for social connection; however, evidence from sub-Saharan Africa remains limited. Methods We analyzed nationally representative data from the Rwanda Demographic and Health Survey (2019–20), including 2,081 adults aged ≥65 years. Living alone was used as a structural indicator and proxy measure of social isolation. Weighted descriptive statistics and multivariable logistic regression were used to estimate adjusted odds ratios (AORs) with 95% confidence intervals (CIs). Machine learning models (k-nearest neighbors and gradient boosting) were applied as complementary analyses to assess predictive performance and identify influential predictors. Results Overall, 9.7% of older adults lived alone and 55.4% owned a mobile phone. Mobile phone ownership was independently associated with lower odds of living alone (AOR = 0.13; 95% CI: 0.08–0.22; p < 0.001). Female sex was associated with higher odds of living alone (AOR = 1.86; 95% CI: 1.29–2.67), whereas higher wealth index was associated with lower odds. Machine-learning models demonstrated moderate discriminatory ability (AUC 0.75–0.77) but limited classification performance due to outcome imbalance. Across models, mobile phone ownership consistently emerged as the most influential predictor. Conclusion Digital access, operationalized as mobile phone ownership, was strongly associated with reduced likelihood of living alone among older adults in Rwanda. These findings suggest that digital connectivity may contribute to structural dimensions of social integration in rapidly digitizing low- and middle-income settings. Policies that promote equitable access to mobile technologies may support social connectedness and healthy aging among older populations.

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