Prevalence and factors associated with metabolic syndrome in an urban population of adults living with HIV in Nairobi, Kenya

Introduction: Metabolic syndrome affects 20-25% of the adult population globally. It predisposes to cardiovascular disease and Type 2 diabetes. Studies in other countries suggest a high prevalence of metabolic syndrome among HIV-infected patients but no studies have been reported in Kenya. The objective of this study was to assess the prevalence and factors associated with metabolic syndrome in adult HIV-infected patients in an urban population in Nairobi, Kenya. Methods: in a cross-sectional study design, conducted at Riruta Health Centre in 2016, 360 adults infected with HIV were recruited. A structured questionnaire was used to collect data on socio-demography. Blood was collected by finger prick for fasting glucose and venous sampling for lipid profile. Results: Using the harmonized Joint Scientific Statement criteria, metabolic syndrome was present in 19.2%. The prevalence was higher among females than males (20.7% vs. 16.0%). Obesity (AOR = 5.37, P < 0.001), lack of formal education (AOR = 5.20, P = 0.002) and family history of hypertension (AOR = 2.06, P = 0.029) were associated with increased odds of metabolic syndrome while physical activity (AOR = 0.28, P = 0.001) was associated with decreased odds. Conclusion: Metabolic syndrome is prevalent in this study population. Obesity, lack of formal education, family history of hypertension, and physical inactivity are associated with metabolic syndrome. Screening for risk factors, promotion of healthy lifestyle, and nutrition counselling should be offered routinely in HIV care and treatment clinics

Where Are the Newly Diagnosed HIV Positives in Kenya? Time to Consider Geo-Spatially Guided Targeting at a Finer Scale to Reach the “First 90”

Background: The UNAIDS 90-90-90 Fast-Track targets provide a framework for assessing coverage of HIV testing services (HTS) and awareness of HIV status – the “first 90.” In Kenya, the bulk of HIV testing targets are aligned to the five highest HIV-burden counties. However, we do not know if most of the new HIV diagnoses are in these five highest-burden counties or elsewhere. Methods: We analyzed facility-level HTS data in Kenya from 1 October 2015 to 30 September 2016 to assess the spatial distribution of newly diagnosed HIV-positives. We used the Moran's Index (Moran's I) to assess global and local spatial auto-correlation of newly diagnosed HIV-positive tests and Kulldorff spatial scan statistics to detect hotspots of newly diagnosed HIV-positive tests. For aggregated data, we used Kruskal-Wallis equality-of-populations non-parametric rank test to compare absolute numbers across classes. Results: Out of 4,021 HTS sites, 3,969 (98.7%) had geocodes available. Most facilities (3,034, 76.4%), were not spatially autocorrelated for the number of newly diagnosed HIV-positives. For the rest, clustering occurred as follows; 438 (11.0%) were HH, 66 (1.7%) HL, 275 (6.9%) LH, and 156 (3.9%) LL. Of the HH sites, 301 (68.7%) were in high HIV-burden counties. Over half of 123 clusters with a significantly high number of newly diagnosed HIV-infected persons, 73(59.3%) were not in the five highest HIV-burden counties. Clusters with a high number of newly diagnosed persons had twice the number of positives per 1,000,000 tests than clusters with lower numbers (29,856 vs. 14,172). Conclusions: Although high HIV-burden counties contain clusters of sites with a high number of newly diagnosed HIV-infected persons, we detected many such clusters in low-burden counties as well. To expand HTS where most needed and reach the “first 90” targets, geospatial analyses and mapping make it easier to identify and describe localized epidemic patterns in a spatially dispersed epidemic like Kenya's, and consequently, reorient and prioritize HTS strategies.publishedVersio

An empiric tool to identify Kenyans living with HIV who will have unsuppressed viremia 18 months following treatment initiation to guide differentiated care models

Background With the global push towards universal access to Antiretroviral Treatment (ART), patient numbers are increasing, further straining already under-resourced healthcare systems in sub-Saharan Africa. A simple scoring tool could be useful in optimizing differentiated service delivery by identifying individuals likely to have unsuppressed viral load. Methods Using existing data of patients accessing ART at public health facilities that were extracted from the Kenya Electronic Medical Record (KenyaEMR) and standard methods of developing a clinical prediction tool; we created and validated a risk scoring tool to identify persons likely to be virally unsuppressed at 18 months post-ART initiation. Data from the KenyaEMR were cleaned, merged and reviewed for completeness. We utilized multivariate modelling to determine key predictors of viral load suppression that could be measured in clinical settings. Results We assessed clinical reports of 3,968 patients on ART who had been on ART for at least 18 months and had at least one viral load result and were ≥ 18 years old. Of these, the majority (81%) were virally suppressed 18 months post-ART initiation. The final risk score included age, sex, body mass index at HIV diagnosis, number of years of formal education, disclosure status, and duration of time between HIV diagnosis and initiating ART. The maximum risk score was 78; a risk score of ≥22 was associated with unsuppressed viral load (>1000copies/mL). The area under the curve (AUC) for the probability of the risk score to correctly predict unsuppressed viral load was 0.55 (95% CI: 0.52 to 0.56). Internal and external validation showed similar predictive ability. Conclusions Routinely collected variables in a public HIV clinic medical record predicts, with modest accuracy, individuals likely to have unsuppressed HIV viremia 18 months after they initiate ART. The use and application of this tool could improve and complement efficiency in differentiated care models for patients on ART

Rates and Predictors of Non-Adherence to Antiretroviral Therapy among HIV-Positive Individuals in Kenya: Results from the Second Kenya AIDS Indicator Survey, 2012.

Understanding the levels and associated factors of non-adherence to antiretroviral therapy (ART) is crucial in designing interventions to improve adherence and health outcomes of ART. We assessed non-adherence to ART among HIV-infected persons reporting ART use in a nationally representative survey in Kenya.The Kenya AIDS Indicator Survey 2012 was a population-based, household survey of persons aged 18 months-64 years conducted in 2012-2013. Self-reported information was collected on demographics, sexual behaviour, HIV status, and ART use. Blood was collected for HIV testing, and if HIV infected, CD4 and viral load testing. HIV-positive specimens were tested for the presence of antiretroviral (ARV) drugs using a qualitative ARV assay using liquid chromatography-tandem mass spectrometry. HIV-positive persons who reported receiving ART but did not have the ARV biomarker present were defined as being non-adherent to their ARV medication. We restricted our analysis to HIV-infected persons aged 15-64 years who reported receiving ART and had laboratory-confirmed results from ARV testing. Multivariate logistic regression was used to identify variables associated with non-adherence.A total of 648 (5.6%; CI 4.9-6.3) tested HIV-positive of whom 559 (86.3%) had sufficient volume of blood to be tested for ARV drugs. Of those, 271 (47.7%; CI 41.8-53.6) self-reported HIV-positive status during the interview and 186 (69.1%; CI 62.2-76.0) of those reported taking ART. The ARV biomarker was absent in 18 of 186 individuals (9.4%; CI 4.9-13.8) who thus were defined as being non-adherent to ART. Non-adherence was associated with being aged 15-29 years (AOR 8.39; CI 2.26-31.22, p = 0.002) compared to aged 30-64 years, rural residence (AOR 5.87; CI 1.39-25.61, p = 0.016) compared with urban residence and taking recreational drugs in the past 30 days (AOR 5.89; CI 1.30-26.70, p = 0.022).Overall, less than 10% of Kenyans aged 15-64 years on ART were not adhering to their HIV medication, highlighting the success of the Kenyan national ART program. Our findings, however, point to the need for targeted interventions particularly for young persons, those in rural areas to improve adherence outcomes, as well as delivery of treatment programs that include psychosocial support as a preventative measure to minimize substance abuse and the risk of treatment failure

Modes of HIV transmission among adolescents and young adults aged 10–24 years in Kenya

Understanding how HIV is acquired can inform interventions to prevent infection. We constructed a risk profile of 10-24 year olds participating in the 2012 Kenya AIDS Indicator Survey and classified them as perinatally infected if their biological mother was infected with HIV or had died, or if their father was infected with HIV or had died (for those lacking mother's data). The remaining were classified as sexually infected if they had sex, and the remaining as parenterally infected if they had a blood transfusion. Overall, 84 (1.6%) of the 5298 10-24 year olds tested HIV positive; 9 (11%) were aged 10-14 and 75 (89%) 15-24 years. Five (56%) 10-14 year olds met criteria for perinatal infection; 4 (44%) did not meet perinatal, sexual or parenteral transmission criteria and parental HIV status was not established. Of the 75 HIV-infected, 15 to 24 year olds, 5 (7%) met perinatal transmission, 63 (84%) sexual and 2 (3%) parenteral criteria; 5 (7%) were unclassified. Perinatal transmission likely accounted for 56% and sexual transmission for 84% of infections among 10-14 year olds and 15-24 year olds, respectively. Although our definitions may have introduced some uncertainty, and with the number of infected participants being small, our findings suggest that mixed modes of HIV transmission exist among adolescents and young people

Progress in Reversing the HIV Epidemic through Intensified Access to Antiretroviral Therapy: Results from a Nationally Representative Population-Based Survey in Kenya, 2012.

BACKGROUND:In 2014, the Joint United Nations Programme on HIV/AIDS (UNAIDS) called for 90% of persons living with HIV (PLHIV) to know their status, 90% of these to be on antiretroviral therapy (ART), and 90% of these to be virally suppressed by 2020 (90-90-90). It is not clear whether planned ART scale-up in countries whose eligibility criteria for ART initiation are based on recommendations from the 2013 World Health Organization treatment guidelines will be sufficient to meet UNAIDS' new global targets. MATERIALS AND METHODS:Using data from a nationally representative population-based household survey of persons in Kenya we compared coverage and unmet need associated with HIV diagnosis, ART, and viral suppression among PLHIV aged 15-64 years in 2012 based on criteria outlined in the 2014 national ART guidelines and UNAIDS' 90-90-90 goals. Estimates were weighted to account for sampling probability and nonresponse. RESULTS:Eight in ten PLHIV aged 15-64 years needed ART based on treatment eligibility. Need for treatment based on the national treatment policy was 97.4% of treatment need based on UNAIDS' 90-90-90 goals, requiring an excess of 24,000 PLHIV to access treatment beyond those eligible for ART to achieve UNAIDS' 90-90-90 treatment target. The gap in treatment coverage was high, ranging from 43.1% nationally to 52.3% in Nyanza among treatment-eligible PLHIV and 44.6% nationally to 52.4% in Nyanza among all PLHIV. CONCLUSION:Maintaining the current pace of ART scale-up in Kenya will result in thousands of PLHIV unreached, many with high viral load and at-risk of transmitting infection to others. Careful strategies for reaching 90-90-90 will be instrumental in determining whether intensified access to treatment can be achieved to reach all who require ART

Equity of antiretroviral treatment use in high HIV burden countries: Analyses of data from nationally-representative surveys in Kenya and South Africa.

OBJECTIVE:To assess changes and equity in antiretroviral therapy (ART) use in Kenya and South Africa. METHODS:We analysed national population-based household surveys conducted in Kenya and South Africa between 2007 and 2012 for factors associated with lack of ART use among people living with HIV (PLHIV) aged 15-64 years. We considered ART use to be inequitable if significant differences in use were found between groups of PLHIV (e.g. by sex). FINDINGS:ART use among PLHIV increased from 29.3% (95% confidence interval [CI]: 22.8-35.8) to 42.5% (95%CI: 37.4-47.7) from 2007 to 2012 in Kenya and 17.4% (95%CI: 14.2-20.9) to 30.3% (95%CI: 27.2-33.6) from 2008 to 2012 in South Africa. In 2012, factors independently associated with lack of ART use among adult Kenyan PLHIV were rural residency (adjusted odds ratio [aOR] 1.98, 95%CI: 1.23-3.18), younger age (15-24 years: aOR 4.25, 95%CI: 1.7-10.63, and 25-34 years: aOR 5.16, 95%CI: 2.73-9.74 versus 50-64 years), nondisclosure of HIV status to most recent sex partner (aOR 2.41, 95%CI: 1.27-4.57) and recent recreational drug use (aOR 2.50, 95%CI: 1.09-5.77). Among South African PLHIV in 2012, lack of ART use was significantly associated with younger age (15-24 years: aOR 4.23, 95%CI: 2.56-6.70, and 25-34 years: aOR 2.84, 95%CI: 1.73-4.67, versus 50-64 years), employment status (aOR 1.61, 95%CI: 1.16-2.23 in students versus unemployed), and recent recreational drug use (aOR 4.56, 95%CI: 1.79-11.57). CONCLUSION:Although we found substantial increases in ART use in both countries over time, we identified areas needing improvement including among rural Kenyans, students in South Africa, and among young people and drug users in both countries

Use of viral load to improve survey estimates of known HIV-positive status and antiretroviral treatment coverage.

Objective:To compare alternative methods of adjusting self-reported knowledge of HIV-positive status and antiretroviral (ARV) therapy use based on undetectable viral load (UVL) and ARV detection in blood.Design:Post hoc analysis of nationally representative household survey to compare alternative biomarker-based adjustments to population HIV indicators.Methods:We reclassified HIV-positive participants aged 15-64 years in the 2012 Kenya AIDS Indicator Survey (KAIS) who were unaware of their HIV-positive status by self-report as aware and on antiretroviral treatment if either ARVs were detected or viral load was undetectable (<550copies/ml) on dried blood spots. We compared self-report to adjustments for ARV measurement, UVL, or both.Results:Treatment coverage among all HIV-positive respondents increased from 31.8% for self-report to 42.5% [95% confidence interval (CI) 37.4-47.8] based on ARV detection alone, to 42.8% (95% CI 37.9-47.8) when ARV-adjusted, 46.2% (95% CI 41.3-51.1) when UVL-adjusted and 48.8% (95% CI 43.9-53.8) when adjusted for either ARV or UVL. Awareness of positive status increased from 46.9% for self-report to 56.2% (95% CI 50.7-61.6) when ARV-adjusted, 57.5% (95% CI 51.9-63.0) when UVL-adjusted, and 59.8% (95% CI 54.2-65.1) when adjusted for either ARV or UVL.Conclusion:Undetectable viral load, which is routinely measured in surveys, may be a useful adjunct or alternative to ARV detection for adjusting survey estimates of knowledge of HIV status and antiretroviral treatment coverage

Geometric models of a snake robot control

This thesis deals with the geometric theory of control of a robotic snake. The thesis includes required definitions of differential geometry and control theory, which are used to describe and derive the control model for a three segment robotic snake. The model is applied in the simulation environment V-REP

Use of viral load to improve survey estimates of known HIV-positive status and antiretroviral treatment coverage

Objective:To compare alternative methods of adjusting self-reported knowledge of HIV-positive status and antiretroviral (ARV) therapy use based on undetectable viral load (UVL) and ARV detection in blood.Design:Post hoc analysis of nationally representative household survey to compare alternative biomarker-based adjustments to population HIV indicators.Methods:We reclassified HIV-positive participants aged 15-64 years in the 2012 Kenya AIDS Indicator Survey (KAIS) who were unaware of their HIV-positive status by self-report as aware and on antiretroviral treatment if either ARVs were detected or viral load was undetectable (<550copies/ml) on dried blood spots. We compared self-report to adjustments for ARV measurement, UVL, or both.Results:Treatment coverage among all HIV-positive respondents increased from 31.8% for self-report to 42.5% [95% confidence interval (CI) 37.4-47.8] based on ARV detection alone, to 42.8% (95% CI 37.9-47.8) when ARV-adjusted, 46.2% (95% CI 41.3-51.1) when UVL-adjusted and 48.8% (95% CI 43.9-53.8) when adjusted for either ARV or UVL. Awareness of positive status increased from 46.9% for self-report to 56.2% (95% CI 50.7-61.6) when ARV-adjusted, 57.5% (95% CI 51.9-63.0) when UVL-adjusted, and 59.8% (95% CI 54.2-65.1) when adjusted for either ARV or UVL.Conclusion:Undetectable viral load, which is routinely measured in surveys, may be a useful adjunct or alternative to ARV detection for adjusting survey estimates of knowledge of HIV status and antiretroviral treatment coverage