BackgroundCoronavirus disease 2019 (COVID-19)-related disruptions in healthcare services and clinical outcomes have been predicted and documented. However, little is known about how antiretroviral therapy (ART) adherence disruptions caused by the COVID-19 pandemic have manifested amidst the ‘Undetectable = Untransmittable' campaign initiative. Using a patient's viral load as a proxy for medication adherence, our study aimed to determine the adherence to ART on first-line medications among adult people living with human immunodeficiency virus (PLWHIV) at the University Teaching Hospital in Lusaka, Zambia during the pandemic.MethodsThis was a hospital-based cross-sectional study. Secondary data of PLWHIV registered to receive ART from the Adult Infectious Disease Centre was extracted from the SmartCare® electronic health record system to constitute a resultant data set that this study used. The data extraction form was used to extract values of dependent (ART adherence measured by viral load detectability) and independent variables and imported them into the statistical analysis tool, STATA version 16.1 MP. Descriptive statistics of individual characteristics, testing for associations using Pearson's chi-square test, and stratified and combined multivariable logistic regression were performed.ResultsOf the 7,281 adult PLWHIV included in this study, 9.0% (95% CI 8.3–9.6%) were virally detectable. Estimates of the odds ratios of detectable viral load remained significantly higher among adult PLWHIV who were initiated on ART after the U=U campaign was launched in Zambia and were on a monthly 2.51 (1.31–9.03) or 6-monthly 4.75 (3.52–6.41) dispensing of a dolutegravir-based regimen and those on 6-monthly dispensing of an efavirenz-based regimen 4.67 (2.16–10.08) compared to their counterparts. Overall estimates showed us the same picture 4.14 (3.22–5.31), having adjusted for all other predictor variables.ConclusionWe found that a high proportion of people with detectable viral load in the study population, irrespective of medication refill interval and type of regimen, was concentrated among adult PLWHIV who started treatment during the COVID-19 epidemic waves, as compared to those who started treatment before the pandemic. This observed disparity suggests the inherent impact of the pandemic on the adherence to ART among adult PLWHIV in Lusaka, Zambia. This further illustrates how exposed program responses are to external shocks, especially in already weakened health systems, and the need to create program response buffers and resilient program-specific strategies to minimize the effect of external disruptions.
Introduction: Tobacco smoking is one of the biggest public health threats causing poverty, several illnesses and death. Previous studies found that the lower the education, the higher the risk of smoking. This study assessed the association between education attainment and smoking among participants of the Zambia Demographic Health Survey 2013-2014. Methodology: This was a population-based cross-sectional study. Secondary data was extracted from existing Zambia Demographic Health Survey 2013- 2014 data sets, from ten provinces in comparison with different variables to constitute a resultant data set which this study used. All successfully interviewed male and female participants who answered the question, “Do you currently smoke cigarettes?” or “Do you currently smoke or use any other type of tobacco?” were included. The data extraction form was used to extract values of dependent and independent variables and imported into statistical analysis tool Stata version 13. Descriptive statistics of individual characteristics, testing for associations using the Pearson’s Chi Square test and logistic regression were performed. Results: Overall there were 14773 men and 16411women with mean age of 15-19. Smoking prevalence was 9.9% overall and 20.4% in men, but 0.5% in women. The incidence of tobacco smoking is steadily increasing with increase in age among both men and women. There was a significant increase in the incidence of smoking between 20-24 and 25-29 particularly in male smokers. Higher socioeconomic status seems to have a protective effect, consequently smoking remains highest among poor individuals and lowest among the rich. Higher education groups had a decreased likelihood to smoke with an odds ratio of 0.5 overall, 0.2 in men and 0.1 in women. Conclusions: We report high and unchanging prevalence of smoking predominantly concentrated in rural adult populations with lower education attainment. This suggests past health promotion efforts that targeted whole population may not have been relevant to the most affected groups. This therefore calls for reshaping health promotion messages to target specific populations and settings with highest burden. Furthermore, this calls for additional explorative studies in order to examine reasons for smoking in lower educated groups including exploring how what has worked in reducing smoking in higher educated groups could be extrapolated to most affected low educated and rural populations.
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