Abstract

Background: Poor quality of life (QoL) disrupts social functioning, fulfilment of basic needs, and is associated with depressive disorder (DD). Objective: We answered the question of whether there is a common risk factor for DD across six low- and middle-income countries (LMICs) and determined whether this risk factor can be ranked consistently as the most important predictor of DD in all six LMICs. We estimated the effect of DD on QoL for each country and meta-analyzed the results to generate a pooled effect estimate of DD on QoL in the six LMICs. Methods: We used data from the WHO Study on Global Ageing and Adult Health (SAGE). This study involved a total of 35,164 older adults aged ≥ 50 yr. in six LMICs: China, 13,408; Ghana, 4,305; India, 7,108; Mexico, 2,309; Russian Federation, 3,763; and South Africa, 3,842. We conducted an extensive literature review to select the list of 58 potential risk factors associated with DD. We used double selection Least Absolute Shrinkage and Selection Operator Poisson regression model to identify country-specific risk factors associated with DD. Weighted dominance analysis (WDA) was performed to determine the most important risk factor of DD. To estimate the effect of DD on QoL, we used inverse probability weighting Poisson regression adjustment for each country, and meta-analysis techniques for a pooled estimate of the overall effect. Results: The risk factors for DD were generally country specific. However, asthma was the most common and the most important predictor of DD across all six SAGE countries. In Ghana, the prevalence of DD among older adults who have been diagnosed with asthma or have experienced symptoms of asthma in the 12 months preceding the survey was 14 times that among those without asthma or asymptomatic of asthma [Adjusted Prevalence Ratio (aPR), 14.46, 95% confidence interval (CI): 10.47 - 19.97; p < 0.001]. Similarly, it was 14 times in South Africa (aPR, 14.6; 95% CI: 8.18 - 26.14; p < 0.00) but in Mexico, it was 4 times (aPR, 4.39; 95% CI: 3.00 - 6.42; p < 0.001) and in China (aPR, 5.99; 95% CI: 4.32 - 8.31; p < 0.001) and Russia (aPR, 5.90; 95% CI: 3.9 - 9.0; p < 0.001), it was 6 times. In India, it was 5 times (aPR=5.1; 95% CI: 4.3 - 6.0; p < 0.001. Generally, there was evidence of 8% increase in poor QoL due to the presence of DD (Pooled estimate, 0.08; 95% CI: 6.0 – 12; p < 0.001). Specifically, in China, there was evidence of 12% increase in poor QoL that could be attributed to DD (prevalence difference (PD), 0.12; 95% CI: 0.07 - 0.18; p < 0.001). In India (PD, 0.08; 95% CI: 0.04 - 0.13; p < 0.01) and Russian Federation (PD, 0.08; 95% CI: 0.01 - 0.15; p < 0.01), there was evidence of 8% increase in poor QoL. Although, there was some increase in poor QoL in Mexico, Ghana, and South Africa due to DD, the increase was not statistically significant. Conclusion: Although different factors could explain the prevalence of DD among older adults in the six LMICs, it was evident that asthma patients amongst this population were at a higher risk of DD. Clinical evaluation and potential diagnosis and treatment of DD among older adults who present with asthma could potentially enhance their QoL

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