Mobility, mental well-being and Neighborhood walkability among older adults in Nigeria: an urban perspective

尼日利亚老年人的行动能力、心理健康和社区步行友好性:城市视角

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Abstract

BACKGROUND: The rapid urbanization and demographic shifts experienced globally have significant implications for the well-being of older adults, particularly in low and middle income countries like Nigeria. As individuals age, understanding the impact of environmental characteristics on mobility and mental well-being becomes crucial for optimal health. Walkable neighborhoods have the potential to enhance mobility, social engagement, and well-being among older adults. This study explored the neighborhood characteristics and its relationship with mobility and mental well-being of older adults in Nigeria. It also identified the policy implications of the findings for urban planning and public health interventions. METHODS: This cross-sectional study involved 162 older adults residing in Enugu urban area between August 2023 and April 2024. The Neighborhood Environment Walkability Scale, Life Space Questionnaire and Warwick-Edinburgh Mental Well-being Scale assessed the neighborhood characteristics, mobility and mental well-being respectively. Correlation and multiple regression analysis were employed. RESULTS: Significant relationships were observed between mobility and residential density (r= -0.223, p = 0.004), connectivity (r = 0.266, p = 0.001) aesthetics (r = 0.212, p = 0.007), and safety from traffic (r = 0.214, p = 0.006). The regression analysis with mobility as the dependent variable showed a good model fit and was significant [F = 7.389, p < 0.001, adjusted R(2) = 0.28, R(2) = 0.33]. The predictors/independent variables in the model accounted for 33% of the variance in mobility. Durbin Watson's score was 2.066 indicating independence of observations in the model. Variance Inflation factor values were less than 10 while Tolerance values were greater than 0.20 indicating no multicollinearity in the model. Key predictors of mobility were residential density, land use mix, connectivity, aesthetics, safety from traffic, environmental description and child safety. The stepwise regression identified five significant predictors: connectivity, residential density, aesthetics, child safety, and traffic safety. These explained 27.5% of the variance in mobility scores (R² = 0.275, p < 0.001). While explaining slightly less variance than the full model, it offered a more interpretable structure. Interestingly, there was no significant relationship between neighborhood characteristics and mental well-being (p > 0.05), and none of these characteristics emerged as significant predictors of mental well-being. CONCLUSIONS: Urban planners, policymakers, and healthcare professionals should collaborate to create age-friendly environments that prioritize mobility and well-being for older adults. The insights from this study can inform policy recommendations and guidelines aimed at enhancing the overall quality of life for older adults, reducing the incidence of isolation, anxiety, and depression, and promoting healthier, more vibrant communities. CLINICAL TRIAL NUMBER: Not applicable.

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