Methods for conducting trends analysis: roadmap for comparing outcomes from three national HIV Population-based household surveys in Kenya (2007, 2012, and 2018).

BACKGROUND: For assessing the HIV epidemic in Kenya, a series of independent HIV indicator household-based surveys of similar design can be used to investigate the trends in key indicators relevant to HIV prevention and control and to describe geographic and sociodemographic disparities, assess the impact of interventions, and develop strategies. We developed methods and tools to facilitate a robust analysis of trends across three national household-based surveys conducted in Kenya in 2007, 2012, and 2018. METHODS: We used data from the 2007 and 2012 Kenya AIDS Indicator surveys (KAIS 2007 and KAIS 2012) and the 2018 Kenya Population-based HIV Impact Assessment (KENPHIA 2018). To assess the design and other variables of interest from each study, variables were recoded to ensure that they had equivalent meanings across the three surveys. After assessing weighting procedures for comparability, we used the KAIS 2012 nonresponse weighting procedure to revise normalized KENPHIA weights. Analyses were restricted to geographic areas covered by all three surveys. The revised analysis files were then merged into a single file for pooled analysis. We assessed distributions of age, sex, household wealth, and urban/rural status to identify unexpected changes between surveys. To demonstrate how a trend analysis can be carried out, we used continuous, binary, and time-to-event variables as examples. Specifically, temporal trends in age at first sex and having received an HIV test in the last 12 months were used to demonstrate the proposed analytical approach. These were assessed with respondent-specific variables (age, sex, level of education, and marital status) and household variables (place of residence and wealth index). All analyses were conducted in SAS 9.4, but analysis files were created in Stata and R format to support additional analyses. RESULTS: This study demonstrates trends in selected indicators to illustrate the approach that can be used in similar settings. The incidence of early sexual debut decreased from 11.63 (95% CI: 10.95-12.34) per 1,000 person-years at risk in 2007 to 10.45 (95% CI: 9.75-11.2) per 1,000 person-years at risk in 2012 and to 9.58 (95% CI: 9.08-10.1) per 1,000 person-years at risk in 2018. HIV-testing rates increased from 12.6% (95% CI: 11.6%-13.6%) in 2007 to 56.1% (95% CI: 54.6%-57.6%) in 2012 but decreased slightly to 55.6% [95% CI: 54.6%-56.6%) in 2018. The decrease in incidence of early sexual debut could be convincingly demonstrated between 2007 and 2012 but not between 2012 and 2018. Similarly, there was virtually no difference between HIV Testing rates in 2012 and 2018. CONCLUSIONS: Our approach can be used to support trend comparisons for variables in HIV surveys in low-income settings. Independent national household surveys can be assessed for comparability, adjusted as appropriate, and used to estimate trends in key indicators. Analyzing trends over time can not only provide insights into Kenya's progress toward HIV epidemic control but also identify gaps.

Combating Climate Change in the Kenyan Tea Industry.

Climate change triggered by global warming poses a major threat to agricultural systems globally. This phenomenon is characterized by emergence of pests and diseases, extreme weather events, such as prolonged drought, high intensity rains, hailstones and frosts, which are becoming more frequent ultimately impacting negatively to agricultural production including rain-fed tea cultivation. Kenya is predominantly an agricultural based economy, with the tea sector generating about 26% of the total export earnings and about 4% gross domestic product (GDP). In the recent years, however, the country has witnessed unstable trends in tea production associated with climate driven stresses. Toward mitigation and adaptation of climate change, multiple approaches for impact assessment, intensity prediction and adaptation have been advanced in the Kenyan tea sub-sector. Further, pressure on tea breeders to release improved climate-compatible cultivars for the rapidly deteriorating environment has resulted in the adoption of a multi-targeted approach seeking to understand the complex molecular regulatory networks associated with biotic and abiotic stresses adaptation and tolerance in tea. Genetic modeling, a powerful tool that assists in breeding process, has also been adopted for selection of tea cultivars for optimal performance under varying climatic conditions. A range of physiological and biochemical responses known to counteract the effects of environmental stresses in most plants that include lowering the rates of cellular growth and net photosynthesis, stomatal closure, and the accumulation of organic solutes such as sugar alcohols, or osmolytes have been used to support breeding programs through screening of new tea cultivars suitable for changing environment. This review describes simulation models combined with high resolution climate change scenarios required to quantify the relative importance of climate change on tea production. In addition, both biodiversity and ecosystem based approaches are described as a part of an overall adaptation strategy to mitigate adverse effects of climate change on tea in Kenya and gaps highlighted for urgent investigations.

Prevalence of metabolic syndrome among an urban population in Kenya.

OBJECTIVE: Developing countries are undergoing an epidemiologic transition accompanied by increasing burden of cardiovascular disease (CVD) linked to urbanization and lifestyle modifications. Metabolic syndrome is a cluster of CVD risk factors whose extent in Kenya remains unknown. The aim of this study was to determine the prevalence of metabolic syndrome and factors associated with its occurrence among an urban population in Kenya. RESEARCH DESIGN AND METHODS: This was a household cross-sectional survey comprising 539 adults (aged ≥18 years) living in Nairobi, drawn from 30 clusters across five socioeconomic classes. Measurements included waist circumference, HDL cholesterol, triacylglycerides (TAGs), fasting glucose, and blood pressure. RESULTS: The prevalence of metabolic syndrome was 34.6% and was higher in women than in men (40.2 vs. 29%; P < 0.001). The most frequently observed features were raised blood pressure, a higher waist circumference, and low HDL cholesterol (men: 96.2, 80.8, and 80%; women: 89.8, 97.2, and 96.3%, respectively), whereas raised fasting glucose and TAGs were observed less frequently (men: 26.9 and 63.3%; women: 26.9 and 30.6%, respectively). The main factors associated with the presence of metabolic syndrome were increasing age, socioeconomic status, and education. CONCLUSIONS: Metabolic syndrome is prevalent in this urban population, especially among women, but the incidence of individual factors suggests that poor glycemic control is not the major contributor. Longitudinal studies are required to establish true causes of metabolic syndrome in Kenya. The Kenyan government needs to create awareness, develop prevention strategies, and strengthen the health care system to accommodate screening and management of CVDs.