To estimate the impact of antiretroviral therapy (ART) on labor productivity and income using detailed employment data from two large tea plantations in western Kenya for HIV-infected tea pluckers who initiated ART.Longitudinal study using primary data on key employment outcomes for a group of HIV-infected workers receiving antiretroviral therapy (ART) and workers in the general workforce.We used nearest-neighbor matching methods to estimate the impacts of HIV/AIDS and ART among 237 HIV-positive pluckers on ART (index group) over a 4-year period (2 years pre-ART and post-ART) on 4 monthly employment outcomes - days plucking tea, total kilograms (kgs) harvested, total days working, and total labor income. Outcomes for the index group were compared with those for a matched reference group from the general workforce.We observed a rapid deterioration in all four outcomes for HIV-infected individuals in the period before ART initiation and then a rapid improvement after treatment initiation. By 18-24 months after treatment initiation, the index group harvested 8% (men) and 19% (women) less tea than reference individuals. The index group earned 6% (men) and 9% (women) less income from labor than reference individuals. Women's income would have dropped further if they had not been able to offset their decline in tea plucking by spending more time on nonplucking assignments.HIV-infected workers experienced long-term income reductions before and after initiating ART. The implications of such long-term impacts in low-income countries have not been adequately addressed.
Background Multimorbidity poses an increasing challenge to health care systems in Sub-Saharan Africa. We studied the extent of multimorbidity and patterns of comorbidity among women aged 40 years or older in a peri-urban area of Dar es Salaam, Tanzania. Methods We assessed 15 chronic conditions in 1528 women who participated in a cross-sectional survey that was conducted within the Dar es Salaam Urban Cohort Study (DUCS) from June 2017 to July 2018. Diagnoses of chronic conditions were based on body measurements, weight, blood testing, screening instruments, and self-report. Results The five most prevalent chronic conditions and most common comorbidities were hypertension (49.8%, 95% CI 47.2 to 52.3), obesity (39.9%, 95% CI 37.3 to 42.4), anemia (36.9%, 95% CI 33.3 to 40.5), signs of depression (32.5%, 95% CI 30.2 to 34.9), and diabetes (30.9%, 95% CI 27.6 to 34.2). The estimated prevalence of multimorbidity (2+ chronic conditions) was 73.8% (95% CI 71.2 to 76.3). Women aged 70 years or older were 4.1 (95% CI 1.5 to 10.9) times mores likely to be affected by multimorbidity and had 0.7 (95% CI 0.3 to 1.2) more chronic conditions than women aged 40 to 44 years. Worse childhood health, being widowed, not working, and higher food insecurity in the household were also associated with a higher multimorbidity risk and level. Conclusion A high prevalence of multimorbidity in the general population of middle-aged and elderly women suggests substantial need for multimorbidity care in Tanzania. Comorbidity patterns can guide multimorbidity screening and help identify health care and prevention needs.
Background Depression is a global mental health challenge. We assessed the prevalence of depressive symptoms and their association with age, chronic conditions, and health status among middle-aged and elderly people in peri-urban Dar es Salaam, Tanzania. Methods Depressive symptoms were measured in 2,220 adults aged over 40 years from two wards of Dar es Salaam using the ten-item version of the Center of Epidemiologic Studies Depression Scale (CES-D-10) and a cut-off score of 10 or higher. The associations of depressive symptoms with age, 13 common chronic conditions, multimorbidity, self-rated health and any limitation in six activities of daily living were examined in univariable and multivariable logistic regressions. Results The estimated prevalence of depressive symptoms was 30.7% (95% CI 28.5–32.9). In univariable regressions, belonging to age groups 45–49 years (OR 1.35 [95% CI 1.04–1.75]) and over 70 years (OR 2.35 [95% CI 1.66–3.33]), chronic conditions, including ischemic heart disease (OR 3.43 [95% CI 2.64–4.46]), tuberculosis (OR 2.42 [95% CI 1.64–3.57]), signs of cognitive problems (OR 1.90 [95% CI 1.35–2.67]), stroke (OR 1.56 [95% CI 1.05–2.32]) and anemia (OR 1.32 [95% CI 1.01–1.71]) and limitations in activities of daily living (OR 1.35 [95% CI 1.07–1.70]) increased the odds of depressive symptoms. Reporting good or very good health was associated with lower odds of depressive symptoms (OR 0.48 [95% CI 0.35–0.66]). Ischemic heart disease and tuberculosis remained independent predictors of depressive symptoms in multivariable regressions. Conclusion Depressive symptoms affected almost one in three people aged over 40 years. Their prevalence differed across age groups and was moderated by chronic conditions, health status and socioeconomic factors.
Background Depression is a global mental health challenge. We assessed the prevalence of depressive symptoms and their association with age, chronic conditions, and health status among middle-aged and elderly people in peri-urban Dar es Salaam, Tanzania. Methods Depressive symptoms were measured in 2,220 adults aged over 40 years from two wards of Dar es Salaam using the ten-item version of the Center of Epidemiologic Studies Depression Scale (CES-D-10) and a cut-off score of 10 or higher. The associations of depressive symptoms with age, 13 common chronic conditions, multimorbidity, self-rated health and any limitation in six activities of daily living were examined in univariable and multivariable logistic regressions. Results The estimated prevalence of depressive symptoms was 30.7% (95% CI 28.5–32.9). In univariable regressions, belonging to age groups 45–49 years (OR 1.35 [95% CI 1.04–1.75]) and over 70 years (OR 2.35 [95% CI 1.66–3.33]), chronic conditions, including ischemic heart disease (OR 3.43 [95% CI 2.64–4.46]), tuberculosis (OR 2.42 [95% CI 1.64–3.57]), signs of cognitive problems (OR 1.90 [95% CI 1.35–2.67]), stroke (OR 1.56 [95% CI 1.05–2.32]) and anemia (OR 1.32 [95% CI 1.01–1.71]) and limitations in activities of daily living (OR 1.35 [95% CI 1.07–1.70]) increased the odds of depressive symptoms. Reporting good or very good health was associated with lower odds of depressive symptoms (OR 0.48 [95% CI 0.35–0.66]). Ischemic heart disease and tuberculosis remained independent predictors of depressive symptoms in multivariable regressions. Conclusion Depressive symptoms affected almost one in three people aged over 40 years. Their prevalence differed across age groups and was moderated by chronic conditions, health status and socioeconomic factors.
Abortions are difficult to measure; yet, accurate estimates are critical in developing health programs. We implemented and tested the validity of a list experiment of lifetime abortion prevalence in Istanbul, Turkey. We complemented our findings by understanding community perspectives using in-depth interviews with key informants.
Intimate Partner Violence (IPV) has severe health consequences, though may be underreported due to stigma. In Tanzania, estimates of IPV prevalence range from 12 to >60%. List experiments, a technique of indirectly asking survey questions, may allow for more accurate prevalence estimates of sensitive topics. We examined list experiment and direct questions about experiences of physical and sexual IPV from a 2017 cross-sectional survey among 2,299 adults aged 40+ years in Dar es Salaam. List experiment prevalence estimates were determined through quantitative analysis and compared qualitatively to direct question prevalence estimates. The list experiment estimated a higher prevalence of IPV in all cases except for physical violence experienced by women. This study contributes to the estimation of IPV prevalence. If the list experiment estimates yield an unbiased estimate, findings suggest women openly report experiencing physical IPV, and IPV experienced by men is underreported and understudied.
Introduction A substantial number of patients with HIV in South Africa have failed first‐line antiretroviral therapy (ART). Although individual predictors of first‐line ART failure have been identified, few studies in resource‐limited settings have been large enough for predictive modelling. Understanding the absolute risk of first‐line failure is useful for patient monitoring and for effectively targeting limited resources for second‐line ART. We developed a predictive model to identify patients at the greatest risk of virologic failure on first‐line ART, and to estimate the proportion of patients needing second‐line ART over five years on treatment. Methods A cohort of patients aged ≥18 years from nine South African HIV clinics on first‐line ART for at least six months were included. Viral load measurements and baseline predictors were obtained from medical records. We used stepwise selection of predictors in accelerated failure‐time models to predict virologic failure on first‐line ART (two consecutive viral load levels >1000 copies/mL). Multiple imputations were used to assign missing baseline variables. The final model was selected using internal‐external cross‐validation maximizing model calibration at five years on ART, and model discrimination, measured using Harrell's C‐statistic. Model covariates were used to create a predictive score for risk group of ART failure. Results A total of 72,181 patients were included in the analysis, with an average of 21.5 months (IQR: 8.8–41.5) of follow‐up time on first‐line ART. The final predictive model had a Weibull distribution and the final predictors of virologic failure were men of all ages, young women, nevirapine use in first‐line regimen, low baseline CD4 count, high mean corpuscular volume, low haemoglobin, history of TB and missed visits during the first six months on ART. About 24.4% of patients in the highest quintile and 9.4% of patients in the lowest quintile of risk were predicted to experience treatment failure over five years on ART. Conclusions Age, sex, CD4 count and having any missed visits during the first six months on ART were the strongest predictors of ART failure. The predictive model identified patients at high risk of failure, and the predicted failure rates over five years closely reflected actual rates of failure.
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