scholarly journals Two schizophrenia imaging signatures and their associations with cognition, psychopathology, and genetics in the general population

2022 ◽  
Author(s):  
Ganesh B Chand ◽  
Pankhuri Singhal ◽  
Dominic B Dwyer ◽  
Junhao Wen ◽  
Guray Erus ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Gray Matter Volume ◽  
Control Sample ◽  
Population Level ◽  
Population Based ◽  
Risk Scores ◽  
Support Vector ◽  
Cross Sectional ◽  
Polygenic Risk ◽  
Independent Population

The prevalence and significance of schizophrenia-related phenotypes at the population-level are debated in the literature. Here we assess whether two recently reported neuroanatomical signatures of schizophrenia, signature 1 with widespread reduction of gray matter volume, and signature 2 with increased striatal volume, could be replicated in an independent schizophrenia sample, and investigate whether expression of these signatures can be detected at the population-level and how they relate to cognition, psychosis spectrum symptoms, and schizophrenia genetic risk. This cross-sectional study used an independent schizophrenia-control sample (n=347; age 16-57 years) for replication of imaging signatures, and then examined two independent population-level datasets: Philadelphia Neurodevelopmental Cohort [PNC; n=359 typically developing (TD) and psychosis-spectrum symptoms (PS) youth] and UK Biobank (UKBB; n=836; age 44-50 years) adults. We quantified signature expression using support-vector machine learning, and compared cognition, psychopathology, and polygenic risk between signatures. Two neuroanatomical signatures of schizophrenia were replicated. Signature 1 but not signature 2 was significantly more common in youth with PS than TD youth, whereas signature 2 frequency was similar. In both youth and adults, signature 1 had worse cognitive performance than signature 2. Compared to adults with neither signature, adults expressing signature 1 had elevated schizophrenia polygenic risk scores, but this was not seen for signature 2. We successfully replicate two neuroanatomical signatures of schizophrenia, and describe their prevalence in population-based samples of youth and adults. We further demonstrate distinct relationships of these signatures with psychosis symptoms, cognition, and genetic risk, potentially reflecting underlying neurobiological vulnerability.

scholarly journals Exploring Various Polygenic Risk Scores for Skin Cancer in the Phenomes of the Michigan Genomics Initiative and the UK Biobank with a Visual Catalog:PRSWeb

2018 ◽  
Author(s):  
Lars G. Fritsche ◽  
Lauren J. Beesley ◽  
Peter VandeHaar ◽  
Robert B. Peng ◽  
Maxwell Salvatore ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Cell Carcinoma ◽  
Genetic Risk ◽  
Population Based ◽  
Risk Scores ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Cancer Subtypes ◽  
Construction Methods ◽  
The Uk

AbstractPolygenic risk scores (PRS) are designed to serve as a single summary measure, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The construction of a PRS often depends on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. In this paper, we consider several choices for constructing a PRS using summary data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict outcomes derived from electronic health records (EHR). Weexamine the three most common skin cancer subtypes in the USA: basal cellcarcinoma, cutaneous squamous cell carcinoma, and melanoma. The genetic risk profiles of subtypes may consist of both shared and unique elements and we construct PRS to understand the common versus distinct etiology. This study is conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate their association with secondary traits. PheWAS results are then replicated using population-based UK Biobank data. We develop an accompanying visual catalog calledPRSwebthat provides detailed PheWAS results and allows users to directly compare different PRS construction methods. The results of this study can provide guidance regarding PRS construction in future PRS-PheWAS studies using EHR data involving disease subtypes.Author summaryIn the study of genetically complex diseases, polygenic risk scores synthesize information from multiple genetic risk factors to provide insight into a patient’s risk of developing a disease based on his/her genetic profile. These risk scores can be explored in conjunction with health and disease information available in the electronic medical records. They may be associated with diseases that may be related to or precursors of the underlying disease of interest. Limited work is available guiding risk score construction when the goal is to identify associations across the medical phenome. In this paper, we compare different polygenic risk score construction methods in terms of their relationships with the medical phenome. We further propose methods for using these risk scores to decouple the shared and unique genetic profiles of related diseases and to explore related diseases’ shared and unique secondary associations. Leveraging and harnessing the rich data resources of the Michigan Genomics Initiative, a biorepository effort at Michigan Medicine, and the larger population-based UK Biobank study, we investigated the performance of genetic risk profiling methods for the three most common types of skin cancer: melanoma, basal cell carcinoma and squamous cell carcinoma.

scholarly journals Polygenic risk, lifestyle, and cardiovascular mortality: a prospective population-based UK Biobank study

2021 ◽  
Author(s):  
Jae-Seung Yun ◽  
Sang-Hyuk Jung ◽  
Manu Shivakumar ◽  
Brenda Xiao ◽  
Amit V. Khera ◽  
...  
Keyword(s):  
Cardiovascular Mortality ◽  
Genetic Risk ◽  
Risk Groups ◽  
Population Based ◽  
Risk Scores ◽  
Uk Biobank ◽  
Lifestyle Behavior ◽  
Polygenic Risk ◽  
High Genetic Risk ◽  
Very High

AbstractOBJECTIVETo assess the prognostic ability of polygenic risk scores (PRSs) for coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) for cardiovascular (CV) mortality, independent of traditional risk factors, and further investigate the additive effect between lifestyle behavior and PRS on CV mortality.DESIGNProspective population-based cohort study.SETTINGUK Biobank.PARTICIPANTSA total 377,909 unrelated participants of white British descent were included in the analyses from the UK Biobank cohort.MAIN OUTCOME MEASURESGenome-wide PRSs were constructed using >6 million genetic variants. We stratified patients into four PRS risk groups: low (0 to 19th percentile), intermediate (20 to 79th percentile), high (80 to 98th percentile), and very high (99th percentile). We defined a favorable and unfavorable lifestyle with four modifiable lifestyle components, including smoking, obesity, physical activity, and diet. Cox proportional hazard models were used to analyze the relationship between PRS and CV mortality with stratification by age, sex, disease status, and lifestyle behavior.RESULTSOf 377,909 UK Biobank participants having European ancestry, 3,210 (0.8%) died due to CV disease during a median follow-up of 8.9 years. CV mortality risk was significantly associated with CAD PRS (low vs. very high genetic risk groups, CAD PRS hazard ratio [HR] 2.61 [2.02 to 3.36]) and T2DM PRS (HR 2.08 [1.58 to 2.73]), respectively. These relationships remained significant even after adjustment for a comprehensive range of demographic and clinical factors. In the very high genetic risk group, adherence to an unfavorable lifestyle was further associated with a substantially increased risk of CV mortality (favorable versus unfavorable lifestyle with very high genetic risk for CAD PRS, HR 8.31 [5.12 to 13.49]; T2DM PRS, HR 5.84 [3.39 to 10.04]). Across all genetic risk groups, 32.1% of CV mortality was attributable to lifestyle behavior (population attributable fraction [PAF] 32.1% [95% CI 28.8 to 35.3%]) and 14.1% was attributable to smoking (PAF 14.1% [95% CI 12.4 to 15.7%]). There was no evidence of significant interaction between PRSs and age, sex, or lifestyle behavior in predicting the risk of CV mortality.CONCLUSIONPRSs for CAD or T2DM and lifestyle behaviors are independent predictive factors for future CV mortality in the white, middle-aged population. PRS-based risk assessment could be useful to identify individuals who need intensive behavioral or therapeutic interventions to reduce the risk of CV mortality.Summary BoxWhat is already known on this topicPolygenic risk scores quantify the inherited risk conferred by the cumulative impact of common variants into a quantitative risk estimate.Previous studies primarily targeted the ability of polygenic risk scores to predict a specific disease, and only a few studies have investigated the association between genetic risk scores and cardiovascular mortality.The majority of previous analyses calculated polygenic risk scores from only a small number of genetic variants or adjusted for only a few risk factors, and no studies have examined whether the association of polygenic risk score with cardiovascular mortality differs by lifestyle behavior.What this study addsGenetic risk and lifestyle are independent predictive factors for cardiovascular mortality, even after adjustment for a comprehensive range of demographic and clinical factors.A healthy lifestyle is associated with relative risk reduction for cardiovascular mortality across all genetic risk categories, a finding that indicates the potential benefit of intensive lifestyle modification in overcoming genetic risk for cardiovascular mortality.

scholarly journals Subthreshold psychosis symptoms associated with molecular genetic risk in a population-based cohort: Findings from Generation Scotland

2019 ◽  
Author(s):  
A.R. Docherty ◽  
Andrey A. Shabalin ◽  
Daniel E. Adkins ◽  
Frank Mann ◽  
Robert F. Krueger ◽  
...  
Keyword(s):  
Sex Differences ◽  
General Population ◽  
Genetic Risk ◽  
Molecular Genetic ◽  
Population Based ◽  
Risk Scores ◽  
Factor Scores ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Genetic Risks

AbstractImportanceSubthreshold psychosis symptoms in the general population may be associated with genetic risk for schizophrenia. In this analysis, empirically-derived symptom factor scores led to a detection of significant and robust polygenic signal.ObjectiveThis study sought to optimize genetic association with data-driven symptom factor scores, accounting for cohort factor structure and sex differences.DesignEFA-derived symptom factor scores were regressed onto PRS for schizophrenia in models accounting for age and genetic ancestry principal components. Follow-up examination of symptom factor score associations with other related genetic risks included ADHD, autism, bipolar disorder, major depression, and neuroticism.ParticipantsThis study examined the newly expanded symptom dataset from the Northern European ancestry cohort, Generation Scotland: Scottish Family Health Study (N = 9,105 individuals 18-65 years of age) comprising common variant and subthreshold psychosis symptom data. A total of 5,391 females and 3,713 males with age M[SD] = 45.2 [13] were included in the final analyses.Main Outcome and MeasureSubthreshold psychosis symptoms were measured using the Schizotypal Personality Questionnaire-Brief (SPQ-B). Primary phenotypic factor scores and genome-wide polygenic risk scores (PRS) reflected weighted sum scores and were examined as continuous measures. Polygenic risk scores were calculated from genome-wide association summary statistics using 7,358,674 imputed common genetic variants passing quality control.ResultsIn males, symptom factor scores were positively associated with polygenic risk for schizophrenia alone and implicated primarily interpersonal/negative symptoms. In females, symptom factor scores were positively associated with polygenic risks for ADHD and autism but not schizophrenia. Scores were robustly associated with genetic risk for neuroticism across both males and females.Conclusions and RelevanceThis study detected a significant association of subthreshold psychosis symptoms with genetic risk for schizophrenia and neuroticism in a population-based sample. Furthermore, important sex differences suggest a need for better understanding of schizophrenia risk assessment in females.Key PointsQuestionWhat molecular genetic risks are associated with subthreshold psychosis symptoms in the general population?FindingsIn a large population-based cohort (N = 9,084), significant associations of polygenic risks with symptoms were observed. Symptoms were associated with genetic risk for schizophrenia in males, for ADHD and autism spectrum disorder in females, and for neuroticism across both males and females.MeaningAssociations of genetic risk with symptoms in the general population are highly significant and suggest important sex differences.

scholarly journals Modeling Hearing Loss Progression and Asymmetry in the Older Old: A National Population-Based Survey

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 214-215
Author(s):  
Rahul Sharma ◽  
Anil Lalwani ◽  
Justin Golub
Keyword(s):  
Hearing Loss ◽  
Pure Tone ◽  
Population Level ◽  
Population Based ◽  
National Database ◽  
Cross Sectional ◽  
Adult Lifespan ◽  
Pure Tone Average ◽  
Age Related ◽  
Public Datasets

Abstract The progression and asymmetry of age-related hearing loss has not been well characterized in those 80 years of age and older because public datasets mask upper extremes of age to protect anonymity. We aimed to model the progression and asymmetry of hearing loss in the older old using a representative, national database. This was a cross-sectional, multicentered US epidemiologic analysis using the National Health and Nutrition Examination Study (NHANES) 2005-2006, 2009-2010, and 2011-2012 cycles. Subjects included non-institutionalized, civilian adults 80 years and older (n=621). Federal security clearance was granted to access publicly-restricted age data. Outcome measures included pure-tone average air conduction thresholds and the 4-frequency pure tone average (PTA). 621 subjects were 80 years old or older (mean=84.2 years, range=80-104 years), representing 10,600,197 Americans. Hearing loss exhibited constant acceleration across the adult lifespan at a rate of 0.0052 dB/year2 (95% CI = 0.0049, 0.0055). Compounded over a lifetime, the velocity of hearing loss would increase five-fold, from 0.2 dB loss/year at age 20 to 1 dB loss/year at age 100. This model predicted mean PTA within 2 dB of accuracy for most ages between 20 and 100 years. There was no change in the asymmetry of hearing loss with increasing age over 80 years (linear regression coefficient of asymmetry over age=0.07 (95% CI=-0.01, 0.24). In conclusion, hearing loss steadily and predictably accelerates across the adult lifespan to at least age 100, becoming near-universal. These population-level statistics will guide treatment and policy recommendations for hearing health in the older old.

scholarly journals Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity

2021 ◽  
pp. 1-12
Author(s):  
Simon Schmitt ◽  
Tina Meller ◽  
Frederike Stein ◽  
Katharina Brosch ◽  
Kai Ringwald ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Mental Disorders ◽  
Cortical Thickness ◽  
Genetic Risk ◽  
Right Hemisphere ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Grey Matter Volume ◽  
Polygenic Risk ◽  
Risk For Depression

Abstract Background MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. Methods We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. Results The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. Conclusions Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

scholarly journals Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Joshua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Prediction Accuracy ◽  
Genetic Risk Score ◽  
Low Risk ◽  
Risk Scores ◽  
Sample Mean ◽  
Polygenic Risk ◽  
Reliable Identification

AbstractPolygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals’ scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals’ scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.

scholarly journals Independent and combined associations between fast-food outlet exposure and genetic risk for obesity: a population-based, cross-sectional study in the UK

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Thomas Burgoine ◽  
Pablo Monsivais ◽  
Stephen J. Sharp ◽  
Nita G. Forouhi ◽  
Nicholas J. Wareham
Keyword(s):  
Genetic Risk ◽  
Fast Food ◽  
Genetic Risk Score ◽  
Population Based ◽  
Overweight And Obesity ◽  
Nucleotide Polymorphisms ◽  
Food Outlet ◽  
Cross Sectional ◽  
Fast Food Outlet ◽  
Common Genetic Variants

Abstract Background Characteristics of the built environment, such as neighbourhood fast-food outlet exposure, are increasingly recognised as risk factors for unhealthy diet and obesity. Obesity also has a genetic component, with common genetic variants explaining a substantial proportion of population-level obesity susceptibility. However, it is not known whether and to what extent associations between fast-food outlet exposure and body weight are modified by genetic predisposition to obesity. Methods We used data from the Fenland Study, a population-based sample of 12,435 UK adults (mean age 48.6 years). We derived a genetic risk score associated with BMI (BMI-GRS) from 96 BMI-associated single nucleotide polymorphisms. Neighbourhood fast-food exposure was defined as quartiles of counts of outlets around the home address. We used multivariable regression models to estimate the associations of each exposure, independently and in combination, with measured BMI, overweight and obesity, and investigated interactions. Results We found independent associations between BMI-GRS and risk of overweight (RR = 1.34, 95% CI 1.23–1.47) and obesity (RR = 1.73, 95% CI 1.55–1.93), and between fast-food outlet exposure and risk of obesity (highest vs lowest quartile RR = 1.58, 95% CI 1.21–2.05). There was no evidence of an interaction of fast-food outlet exposure and genetic risk on BMI (P = 0.09), risk of overweight (P = 0.51), or risk of obesity (P = 0.27). The combination of higher BMI-GRS and highest fast-food outlet exposure was associated with 2.70 (95% CI 1.99–3.66) times greater risk of obesity. Conclusions Our study demonstrated independent associations of both genetic obesity risk and neighbourhood fast-food outlet exposure with adiposity. These important drivers of the obesity epidemic have to date been studied in isolation. Neighbourhood fast-food outlet exposure remains a potential target of policy intervention to prevent obesity and promote the public’s health.

scholarly journals Association of Conventional Cardiovascular Risk Factors with Carotid Atherosclerosis Prevalence in General Population

2018 ◽  
Vol 14 (4) ◽  
pp. 552-557
Author(s):  
V. S. Kaveshnikov ◽  
V. N. Serebryakova ◽  
I. A. Trubacheva ◽  
S. A. Shalnova
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Carotid Atherosclerosis ◽  
Population Level ◽  
Educational Status ◽  
Population Based ◽  
High Density Lipoproteins ◽  
Ultrasound Screening ◽  
Cross Sectional ◽  
Working Age

Material and methods. In the cross-sectional population-based study of general unorganized population of Tomsk aged 25-64 years ultrasound screening examination of the carotid arteries was done for detection of atherosclerotic plaques (plaque). As potential plaque determinants the following factors were studied: age, gender, smoking, low and high density lipoproteins (LDL-C and HDL-C), triglycerides, arterial hypertension, body mass index (BMI), low educational status (LES), high-sensitive C-reactive protein, glucose, diabetes mellitus, antihypertensive and hypolipidemic therapy. Study of relationships was carried out with logistic regression analysis. The error probability of less than 5% was considered statistically significant.Results. In the crude analysis most of the determinants under study showed statistically significant relationship with plaque presence. After adjustment for age and sex, LDL-C, smoking and LES were associated with CAS prevalence. In multivariable regression analysis 9 risk factors appeared to be independently associated with plaque presence, wherein age, male sex, LDL-C, BMI and HDL-C were the most significant. In the participants of 50 years and older the smoking effect was the next in significance after LDL-C.Conclusion. The results obtained focus attention on the comparative value of the major atherogenic risk factors and suggest that currently effective and timely control of LDL-C is of primary importance for prevention of carotid atherosclerosis in the general working-age population. As well the findings of the study evidence that at the population level smoking is still one of the leading atherogenic risk factors.

scholarly journals Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank

PLoS Medicine ◽  
2021 ◽  
Vol 18 (10) ◽  
pp. e1003782
Author(s):  
Michael Wainberg ◽  
Samuel E. Jones ◽  
Lindsay Melhuish Beaupre ◽  
Sean L. Hill ◽  
Daniel Felsky ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Sleep Duration ◽  
Sleep Efficiency ◽  
Risk Scores ◽  
Psychiatric Diagnoses ◽  
Uk Biobank ◽  
Major Depressive ◽  
Cross Sectional ◽  
Polygenic Risk ◽  
The Uk

Background Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort. Methods and findings In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures—bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration—were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = −0.11 (95% confidence interval −0.13 to −0.10, p = 3 × 10−56, FDR = 6 × 10−55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry. Conclusions In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.

scholarly journals Use, awareness and willingness to self-test for HIV: An analysis of cross-sectional population-based surveys in Malawi and Zimbabwe

2020 ◽  
Author(s):  
Cheryl Case Johnson ◽  
Melissa Neuman ◽  
Peter MacPherson ◽  
Augustine Choko ◽  
Caitlin Quinn ◽  
...  
Keyword(s):  
Sexual Risk ◽  
Large Scale ◽  
Scale Up ◽  
Population Level ◽  
Sociodemographic Factors ◽  
Population Based ◽  
African Countries ◽  
Cross Sectional ◽  
Self Test ◽  
Result Analysis

Abstract Background Many southern African countries are nearing the global goal to diagnose 90% of people with HIV by 2020. In 2016, 84% and 86% of people with HIV knew their status in Malawi and Zimbabwe respectively. Despite this progress, gaps remain, particularly among men (≥25 years). We investigated awareness, use and willingness to HIV self-test (HIVST) prior to large scale implementation and explored sociodemographic associations. Methods We pooled responses from two of the first cross-sectional Demographic Health Surveys to include HIVST questions: Malawi and Zimbabwe in 2015-16. Sociodemographic factors and sexual risk behaviours associated with previously testing for HIV, and awareness, past use and future willingness to self-test were investigated using univariable and multivariable logistic regression, adjusting for the sample design and limiting analysis to participants with completed questionnaire and a valid HIV result. Analysis of willingness to self-test was restricted to Zimbabwean men, as Malawians and women were not asked this question. Results Of 31 385 individuals, the proportion never-tested was higher for men (31.2%) than women (16.5%), p<0.001. For men, having ever tested increased with age. Past use and awareness of HIVST was very low, 1.2% and 12.6% respectively. Awareness was lower among women than men (9.1% vs 15.3%, adjusted odds ratio (aOR)=1.55; 95% confidence interval [CI]: 1.37-1.75), and at younger ages, and lower education and literacy levels. Willingness to self-test among Zimbabwean men was high (84.5%), with having previously tested for HIV, high sexual risk, and being ≥25 years associated with greater willingness. Wealthier men had greater awareness of HIVST than poorer men (p<0.001). Men at higher HIV-related sexual risk, compared to men at lower HIV-related sexual risk, had the greatest willingness to self-test (aOR=3.74; 95%CI: 1.39-10.03, p<0.009).Conclusions In 2015-16 many Malawian and Zimbabwean men had never tested for HIV. Despite low awareness and minimal HIVST experience at that time, willingness to self-test was high among Zimbabwean men, especially in older men with moderate to high HIV-related sexual risk. These data provide a valuable baseline against which to investigate population-level uptake of HIVST as programmes scale-up. Programmes introducing, or planning to introduce HIVST, should consider including questions in population-based surveys.

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