An Unexpectedly Complex Architecture for Skin Pigmentation in Africans.

Approximately 15 genes have been directly associated with skin pigmentation variation in humans, leading to its characterization as a relatively simple trait. However, by assembling a global survey of quantitative skin pigmentation phenotypes, we demonstrate that pigmentation is more complex than previously assumed, with genetic architecture varying by latitude. We investigate polygenicity in the KhoeSan populations indigenous to southern Africa who have considerably lighter skin than equatorial Africans. We demonstrate that skin pigmentation is highly heritable, but known pigmentation loci explain only a small fraction of the variance. Rather, baseline skin pigmentation is a complex, polygenic trait in the KhoeSan. Despite this, we identify canonical and non-canonical skin pigmentation loci, including near SLC24A5, TYRP1, SMARCA2/VLDLR, and SNX13, using a genome-wide association approach complemented by targeted resequencing. By considering diverse, under-studied African populations, we show how the architecture of skin pigmentation can vary across humans subject to different local evolutionary pressures.

Genomics of disease risk in globally diverse populations.

Risk of disease is multifactorial and can be shaped by socio-economic, demographic, cultural, environmental and genetic factors. Our understanding of the genetic determinants of disease risk has greatly advanced with the advent of genome-wide association studies (GWAS), which detect associations between genetic variants and complex traits or diseases by comparing populations of cases and controls. However, much of this discovery has occurred through GWAS of individuals of European ancestry, with limited representation of other populations, including from Africa, The Americas, Asia and Oceania. Population demography, genetic drift and adaptation to environments over thousands of years have led globally to the diversification of populations. This global genomic diversity can provide new opportunities for discovery and translation into therapies, as well as a better understanding of population disease risk. Large-scale multi-ethnic and representative biobanks and population health resources provide unprecedented opportunities to understand the genetic determinants of disease on a global scale.

Author Correction: Genomics of disease risk in globally diverse populations.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genetic loci implicated in meta-analysis of body shape in Africans.

BACKGROUND AND AIMS: Obesity is one of the leading causes of non-communicable diseases (NCD). Thus, NCD risk varies in obese individuals based on the location of their fat depots; while subcutaneous adiposity is protective, visceral adiposity increases NCD risk. Although, previously anthropometric traits have been used to quantify body shape in low-income settings, there is no consensus on how it should be assessed. Hence, there is a growing interest to evaluate body shape derived from the principal component analysis (PCA) of anthropometric traits; however, this is yet to be explored in individuals of African ancestry whose body shape is different from those of Europeans. We set out to capture body shape in its multidimensional structure and examine the association between genetic variants and body shape in individuals of African ancestry. METHOD AND RESULTS: We performed a genome-wide association study (GWAS) for body shape derived from PCA analysis of anthropometric traits in the Ugandan General Population Cohort (GPC, n = 6407) and the South African Zulu Cohort (SZC, n = 2595), followed by a GWAS meta-analysis to assess the genetic variants associated with body shape. We identified variants in FGF12, GRM8, TLX1NB and TRAP1 to be associated with body shape. These genes were different from the genes been associated with BMI, height, weight, WC and waist-hip ration in continental Africans. Notably, we also observed that a standard deviation change in body shape was associated with an increase in blood pressure and blood lipids. CONCLUSION: Variants associated with body shape, as a composite variable might be different for those of individual anthropometric traits. Larger studies are required to further explore these phenomena.

Prevalence and predictors of vitamin D deficiency in young African children.

BACKGROUND: Children living in sub-Saharan Africa have a high burden of rickets and infectious diseases, conditions that are linked to vitamin D deficiency. However, data on the vitamin D status of young African children and its environmental and genetic predictors are limited. We aimed to examine the prevalence and predictors of vitamin D deficiency in young African children. METHODS: We measured 25-hydroxyvitamin D (25(OH)D) and typed the single nucleotide polymorphisms, rs4588 and rs7041, in the GC gene encoding the vitamin D binding protein (DBP) in 4509 children aged 0-8 years living in Kenya, Uganda, Burkina Faso, The Gambia and South Africa. We evaluated associations between vitamin D status and country, age, sex, season, anthropometric indices, inflammation, malaria and DBP haplotypes in regression analyses. RESULTS: Median age was 23.9 months (interquartile range [IQR] 12.3, 35.9). Prevalence of vitamin D deficiency using 25(OH)D cut-offs of < 30 nmol/L and < 50 nmol/L was 0.6% (95% CI 0.4, 0.9) and 7.8% (95% CI 7.0, 8.5), respectively. Overall median 25(OH)D level was 77.6 nmol/L (IQR 63.6, 94.2). 25(OH)D levels were lower in South Africa, in older children, during winter or the long rains, and in those with afebrile malaria, and higher in children with inflammation. 25(OH)D levels did not vary by stunting, wasting or underweight in adjusted regression models. The distribution of Gc variants was Gc1f 83.3%, Gc1s 8.5% and Gc2 8.2% overall and varied by country. Individuals carrying the Gc2 variant had lower median 25(OH)D levels (72.4 nmol/L (IQR 59.4, 86.5) than those carrying the Gc1f (77.3 nmol/L (IQR 63.5, 92.8)) or Gc1s (78.9 nmol/L (IQR 63.8, 95.5)) variants. CONCLUSIONS: Approximately 0.6% and 7.8% of young African children were vitamin D deficient as defined by 25(OH)D levels < 30 nmol/L and < 50 nmol/L, respectively. Latitude, age, season, and prevalence of inflammation and malaria should be considered in strategies to assess and manage vitamin D deficiency in young children living in Africa.

HIV infection and anaemia do not affect HbA1c for the detection of diabetes in black South Africans: Evidence from the Durban Diabetes Study.

OBJECTIVE: South Africa has a high burden of HIV infection and anaemia. These conditions may cause HbA1c to over- or underestimate glycaemia; however, this has not been comprehensively investigated in African populations. We assessed the association of anaemia, HIV infection and antiretroviral therapy (ART) with HbA1c , and implications for the detection and diagnosis of diabetes, in a black South African population. RESEARCH DESIGN AND METHODS: In this population-based cross-sectional study in eThekwini municipality (Durban), South Africa, we assessed HbA1c and conducted oral glucose tolerance tests (OGTTs), HIV diagnostic tests and full blood count measurements among 1067 participants without a history of diabetes diagnosis. Linear regression was used to examine differences in HbA1c by anaemia (comparator: no anaemia), or HIV and ART (comparator: no HIV) status. HbA1c -based diabetes prevalence was compared with OGTT-based prevalence among individuals with anaemia and with untreated and ART-treated HIV. RESULTS: In adjusted analyses, normocytic and microcytic anaemia were associated with higher HbA1c compared with no anaemia, whereas macrocytic anaemia and ART-treated HIV were associated with lower HbA1c compared with no anaemia and no HIV, respectively. However, magnitudes of association were small (range: ß  = -3.4 mmol/mol or -0.31%, p < 0.001 [macrocytic anaemia] to ß = 2.1 mmol/mol or 0.19%, p < 0.001 [microcytic anaemia]). There was no significant difference in diabetes prevalence based on HbA1c or OGTT among individuals with anaemia (2.9% vs. 3.3%, p = 0.69), untreated HIV (1.6% vs. 1.6% p = 1.00) or ART-treated HIV (2.9% vs. 1.2%, p = 0.08). CONCLUSIONS: Our results suggest that anaemia and HIV status appear unlikely to materially affect the utility of HbA1c for diabetes detection and diagnosis in this population. Further studies are needed to examine these associations in sub-Saharan African populations.

The African Genome Variation Project shapes medical genetics in Africa.

Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa.

Long reads: their purpose and place.

In recent years long-read technologies have moved from being a niche and specialist field to a point of relative maturity likely to feature frequently in the genomic landscape. Analogous to next generation sequencing, the cost of sequencing using long-read technologies has materially dropped whilst the instrument throughput continues to increase. Together these changes present the prospect of sequencing large numbers of individuals with the aim of fully characterizing genomes at high resolution. In this article, we will endeavour to present an introduction to long-read technologies showing: what long reads are; how they are distinct from short reads; why long reads are useful and how they are being used. We will highlight the recent developments in this field, and the applications and potential of these technologies in medical research, and clinical diagnostics and therapeutics.

Sociodemographic inequities associated with participation in leisure-time physical activity in sub-Saharan Africa: an individual participant data meta-analysis.

BACKGROUND: Leisure-time physical activity (LTPA) is an important contributor to total physical activity and the focus of many interventions promoting activity in high-income populations. Little is known about LTPA in sub-Saharan Africa (SSA), and with expected declines in physical activity due to rapid urbanisation and lifestyle changes we aimed to assess the sociodemographic differences in the prevalence of LTPA in the adult populations of this region to identify potential barriers for equitable participation. METHODS: A two-step individual participant data meta-analysis was conducted using data collected in SSA through 10 population health surveys that included the Global Physical Activity Questionnaire. For each sociodemographic characteristic, the pooled adjusted prevalence and risk ratios (RRs) for participation in LTPA were calculated using the random effects method. Between-study heterogeneity was explored through meta-regression analyses and tests for interaction. RESULTS: Across the 10 populations (N = 26,022), 18.9% (95%CI: 14.3, 24.1; I2 = 99.0%) of adults (≥ 18 years) participated in LTPA. Men were more likely to participate in LTPA compared with women (RR for women: 0.43; 95%CI: 0.32, 0.60; P < 0.001; I2 = 97.5%), while age was inversely associated with participation. Higher levels of education were associated with increased LTPA participation (RR: 1.30; 95%CI: 1.09, 1.55; P = 0.004; I2 = 98.1%), with those living in rural areas or self-employed less likely to participate in LTPA. These associations remained after adjusting for time spent physically active at work or through active travel. CONCLUSIONS: In these populations, participation in LTPA was low, and strongly associated with sex, age, education, self-employment and urban residence. Identifying the potential barriers that reduce participation in these groups is necessary to enable equitable access to the health and social benefits associated with LTPA.

Genome-wide association study of type 2 diabetes in Africa.

AIMS/HYPOTHESIS: Genome-wide association studies (GWAS) for type 2 diabetes have uncovered >400 risk loci, primarily in populations of European and Asian ancestry. Here, we aimed to discover additional type 2 diabetes risk loci (including African-specific variants) and fine-map association signals by performing genetic analysis in African populations. METHODS: We conducted two type 2 diabetes genome-wide association studies in 4347 Africans from South Africa, Nigeria, Ghana and Kenya and meta-analysed both studies together. Likely causal variants were identified using fine-mapping approaches. RESULTS: The most significantly associated variants mapped to the widely replicated type 2 diabetes risk locus near TCF7L2 (p = 5.3 × 10-13). Fine-mapping of the TCF7L2 locus suggested one type 2 diabetes association signal shared between Europeans and Africans (indexed by rs7903146) and a distinct African-specific signal (indexed by rs17746147). We also detected one novel signal, rs73284431, near AGMO (p = 5.2 × 10-9, minor allele frequency [MAF] = 0.095; monomorphic in most non-African populations), distinct from previously reported signals in the region. In analyses focused on 100 published type 2 diabetes risk loci, we identified 21 with shared causal variants in African and non-African populations. CONCLUSIONS/INTERPRETATION: These results demonstrate the value of performing GWAS in Africans, provide a resource to larger consortia for further discovery and fine-mapping and indicate that additional large-scale efforts in Africa are warranted to gain further insight in to the genetic architecture of type 2 diabetes.

Sociodemographic patterns of health insurance coverage in Namibia.

INTRODUCTION: Health insurance has been found to increase healthcare utilisation and reduce catastrophic health expenditures in a number of countries; however, coverage is often unequally distributed among populations. The sociodemographic patterns of health insurance in Namibia are not fully understood. We aimed to assess the prevalence of health insurance, the relation between health insurance and health service utilisation and to explore the sociodemographic factors associated with health insurance in Namibia. Such findings may help to inform health policy to improve financial access to healthcare in the country. METHODS: Using data on 14,443 individuals, aged 15 to 64 years, from the 2013 Namibia Demographic and Health Survey, the association between health insurance and health service utilisation was investigated using multivariable mixed effects Poisson regression analyses, adjusted for sociodemographic covariates and regional, enumeration area and household clustering. Multivariable mixed effects Poisson regression analyses were also conducted to explore the association between key sociodemographic factors and health insurance, adjusted for covariates and clustering. Effect modification by sex, education level and wealth quintile was also explored. RESULTS: Just 17.5% of this population were insured (men: 20.2%; women: 16.2%). In fully-adjusted analyses, education was significantly positively associated with health insurance, independent of other sociodemographic factors (higher education RR: 3.98; 95% CI: 3.11-5.10; p < 0.001). Female sex (RR: 0.83; 95% CI: 0.74-0.94; p = 0.003) and wealth (highest wealth quintile RR: 13.47; 95% CI: 9.06-20.04; p < 0.001) were also independently associated with insurance. There was a complex interaction between sex, education and wealth in the context of health insurance. With increasing education level, women were more likely to be insured (p for interaction < 0.001), and education had a greater impact on the likelihood of health insurance in lower wealth quintiles. CONCLUSIONS: In this population, health insurance was associated with health service utilisation but insurance coverage was low, and was independently associated with sex, education and wealth. Education may play a key role in health insurance coverage, especially for women and the less wealthy. These findings may help to inform the targeting of strategies to improve financial protection from healthcare-associated costs in Namibia.

Linear mixed model for heritability estimation that explicitly addresses environmental variation.

The linear mixed model (LMM) is now routinely used to estimate heritability. Unfortunately, as we demonstrate, LMM estimates of heritability can be inflated when using a standard model. To help reduce this inflation, we used a more general LMM with two random effects-one based on genomic variants and one based on easily measured spatial location as a proxy for environmental effects. We investigated this approach with simulated data and with data from a Uganda cohort of 4,778 individuals for 34 phenotypes including anthropometric indices, blood factors, glycemic control, blood pressure, lipid tests, and liver function tests. For the genomic random effect, we used identity-by-descent estimates from accurately phased genome-wide data. For the environmental random effect, we constructed a covariance matrix based on a Gaussian radial basis function. Across the simulated and Ugandan data, narrow-sense heritability estimates were lower using the more general model. Thus, our approach addresses, in part, the issue of "missing heritability" in the sense that much of the heritability previously thought to be missing was fictional. Software is available at https://github.com/MicrosoftGenomics/FaST-LMM.

A cross-sectional analysis of ITN and IRS coverage in Namibia in 2013.

BACKGROUND: Achieving vector control targets is a key step towards malaria elimination. Because of variations in reporting of progress towards vector control targets in 2013, the coverage of these vector control interventions in Namibia was assessed. METHODS: Data on 9846 households, representing 41,314 people, collected in the 2013 nationally-representative Namibia Demographic and Health Survey were used to explore the coverage of two vector control methods: indoor residual spraying (IRS) and insecticide-treated nets (ITNs). Regional data on Plasmodium falciparum parasite rate in those aged 2-10 years (PfPR2-10), obtained from the Malaria Atlas Project, were used to provide information on malaria transmission intensity. Poisson regression analyses were carried out exploring the relationship between household interventions and PfPR2-10, with fully adjusted models adjusting for wealth and residence type and accounting for regional and enumeration area clustering. Additionally, the coverage as a function of government intervention zones was explored and models were compared using log-likelihood ratio tests. RESULTS: Intervention coverage was greatest in the highest transmission areas (PfPR2-10 ≥ 5%), but was still below target levels of 95% coverage in these regions, with 27.6% of households covered by IRS, 32.3% with an ITN and 49.0% with at least one intervention (ITN and/or IRS). In fully adjusted models, PfPR2-10 ≥ 5% was strongly associated with IRS (RR 14.54; 95% CI 5.56-38.02; p < 0.001), ITN ownership (RR 5.70; 95% CI 2.84-11.45; p < 0.001) and ITN and/or IRS coverage (RR 5.32; 95% CI 3.09-9.16; p < 0.001). CONCLUSIONS: The prevalence of IRS and ITN interventions in 2013 did not reflect the Namibian government intervention targets. As such, there is a need to include quantitative monitoring of such interventions to reliably inform intervention strategies for malaria elimination in Namibia.

Polymorphisms of large effect explain the majority of the host genetic contribution to variation of HIV-1 virus load.

Previous genome-wide association studies (GWAS) of HIV-1-infected populations have been underpowered to detect common variants with moderate impact on disease outcome and have not assessed the phenotypic variance explained by genome-wide additive effects. By combining the majority of available genome-wide genotyping data in HIV-infected populations, we tested for association between ∼8 million variants and viral load (HIV RNA copies per milliliter of plasma) in 6,315 individuals of European ancestry. The strongest signal of association was observed in the HLA class I region that was fully explained by independent effects mapping to five variable amino acid positions in the peptide binding grooves of the HLA-B and HLA-A proteins. We observed a second genome-wide significant association signal in the chemokine (C-C motif) receptor (CCR) gene cluster on chromosome 3. Conditional analysis showed that this signal could not be fully attributed to the known protective CCR5Δ32 allele and the risk P1 haplotype, suggesting further causal variants in this region. Heritability analysis demonstrated that common human genetic variation-mostly in the HLA and CCR5 regions-explains 25% of the variability in viral load. This study suggests that analyses in non-European populations and of variant classes not assessed by GWAS should be priorities for the field going forward.

Evaluating the Impact of Functional Genetic Variation on HIV-1 Control.

Background: Previous genetic association studies of human immunodeficiency virus-1 (HIV-1) progression have focused on common human genetic variation ascertained through genome-wide genotyping. Methods: We sought to systematically assess the full spectrum of functional variation in protein coding gene regions on HIV-1 progression through exome sequencing of 1327 individuals. Genetic variants were tested individually and in aggregate across genes and gene sets for an influence on HIV-1 viral load. Results: Multiple single variants within the major histocompatibility complex (MHC) region were observed to be strongly associated with HIV-1 outcome, consistent with the known impact of classical HLA alleles. However, no single variant or gene located outside of the MHC region was significantly associated with HIV progression. Set-based association testing focusing on genes identified as being essential for HIV replication in genome-wide small interfering RNA (siRNA) and clustered regularly interspaced short palindromic repeats (CRISPR) studies did not reveal any novel associations. Conclusions: These results suggest that exonic variants with large effect sizes are unlikely to have a major contribution to host control of HIV infection.

The Use of Different International References to Assess Child Anthropometric Status in a Malaysian Population.

OBJECTIVE: To assess the prevalence of child underweight, overweight, and obesity in a Malaysian population according to 3 international references because classification of anthropometric status may differ according to the reference used to express body mass index (BMI). STUDY DESIGN: We assessed data from 6414 children aged 6-18 years, collected by the South East Asia Community Observatory. Child underweight, overweight, and obesity were expressed according to 3 internationally used BMI references: World Health Organization 2007, International Obesity Task Force 2012, and Centers for Disease Control and Prevention 2000. We assessed agreement in classification of anthropometric status among the references using Cohen's kappa statistic and estimated underweight, overweight, and obesity prevalence according to each reference using mixed effects Poisson regression. RESULTS: There was poor to moderate agreement between references when classifying underweight, but generally good agreement when classifying overweight and obesity. Underweight, overweight, and obesity prevalence estimates generated using the 3 references were notably inconsistent. Overweight and obesity prevalence estimates were higher using the World Health Organization reference vs the other 2, and underweight prevalence was up to 8.5% higher and obesity prevalence was about 4% lower when using the International Obesity Task Force reference. CONCLUSIONS: The choice of reference to express BMI may influence conclusions about child anthropometric status and malnutrition prevalence. This has implications regarding strategies for clinical management and public health interventions.

A general approach for haplotype phasing across the full spectrum of relatedness.

Many existing cohorts contain a range of relatedness between genotyped individuals, either by design or by chance. Haplotype estimation in such cohorts is a central step in many downstream analyses. Using genotypes from six cohorts from isolated populations and two cohorts from non-isolated populations, we have investigated the performance of different phasing methods designed for nominally 'unrelated' individuals. We find that SHAPEIT2 produces much lower switch error rates in all cohorts compared to other methods, including those designed specifically for isolated populations. In particular, when large amounts of IBD sharing is present, SHAPEIT2 infers close to perfect haplotypes. Based on these results we have developed a general strategy for phasing cohorts with any level of implicit or explicit relatedness between individuals. First SHAPEIT2 is run ignoring all explicit family information. We then apply a novel HMM method (duoHMM) to combine the SHAPEIT2 haplotypes with any family information to infer the inheritance pattern of each meiosis at all sites across each chromosome. This allows the correction of switch errors, detection of recombination events and genotyping errors. We show that the method detects numbers of recombination events that align very well with expectations based on genetic maps, and that it infers far fewer spurious recombination events than Merlin. The method can also detect genotyping errors and infer recombination events in otherwise uninformative families, such as trios and duos. The detected recombination events can be used in association scans for recombination phenotypes. The method provides a simple and unified approach to haplotype estimation, that will be of interest to researchers in the fields of human, animal and plant genetics.

Population and assay thresholds for the predictive value of lipoprotein (a) for coronary artery disease: the EPIC-Norfolk Prospective Population Study.

Variable agreement exists between different lipoprotein (a) [Lp(a)] measurement methods, but their clinical relevance remains unclear. The predictive value of Lp(a) measured by two different assays [Randox and University of California, San Diego (UCSD)] was determined in 623 coronary artery disease (CAD) cases and 948 controls in a case-control study within the EPIC-Norfolk Prospective Population Study. Participants were divided into sex-specific quintiles, and by Lp(a) <50 versus ∼50 mg/dl, which represents the 80th percentile in northern European subjects. Randox and UCSD Lp(a) levels were strongly correlated; Spearman's correlation coefficients for men, women, and sexes combined were 0.905, 0.915, and 0.909, respectively (P< 0.001 for each). The >80th percentile cutoff values, however, were 36 mg/dl and 24 mg/dl for the Randox and UCSD assays, respectively. Despite this, Lp(a) levels were significantly associated with CAD risk, with odds ratios of 2.18 (1.58-3.01) and 2.35 (1.70-3.26) for people in the top versus bottom Lp(a) quintile for the Randox and UCSD assays, respectively. This study demonstrates that CAD risk is present at lower Lp(a) levels than the currently suggested optimal Lp(a) level of <50 mg/dl. Appropriate thresholds may need to be population and assay specific until Lp(a) assays are standardized and Lp(a) thresholds are evaluated broadly across all populations at risk for CVD and aortic stenosis.

Common variants in WFS1 confer risk of type 2 diabetes.

We studied genes involved in pancreatic beta cell function and survival, identifying associations between SNPs in WFS1 and diabetes risk in UK populations that we replicated in an Ashkenazi population and in additional UK studies. In a pooled analysis comprising 9,533 cases and 11,389 controls, SNPs in WFS1 were strongly associated with diabetes risk. Rare mutations in WFS1 cause Wolfram syndrome; using a gene-centric approach, we show that variation in WFS1 also predisposes to common type 2 diabetes.

Urbanicity and lifestyle risk factors for cardiometabolic diseases in rural Uganda: a cross-sectional study.

BACKGROUND: Urban living is associated with unhealthy lifestyles that can increase the risk of cardiometabolic diseases. In sub-Saharan Africa (SSA), where the majority of people live in rural areas, it is still unclear if there is a corresponding increase in unhealthy lifestyles as rural areas adopt urban characteristics. This study examines the distribution of urban characteristics across rural communities in Uganda and their associations with lifestyle risk factors for chronic diseases. METHODS AND FINDINGS: Using data collected in 2011, we examined cross-sectional associations between urbanicity and lifestyle risk factors in rural communities in Uganda, with 7,340 participants aged 13 y and above across 25 villages. Urbanicity was defined according to a multi-component scale, and Poisson regression models were used to examine associations between urbanicity and lifestyle risk factors by quartile of urbanicity. Despite all of the villages not having paved roads and running water, there was marked variation in levels of urbanicity across the villages, largely attributable to differences in economic activity, civil infrastructure, and availability of educational and healthcare services. In regression models, after adjustment for clustering and potential confounders including socioeconomic status, increasing urbanicity was associated with an increase in lifestyle risk factors such as physical inactivity (risk ratio [RR]: 1.19; 95% CI: 1.14, 1.24), low fruit and vegetable consumption (RR: 1.17; 95% CI: 1.10, 1.23), and high body mass index (RR: 1.48; 95% CI: 1.24, 1.77). CONCLUSIONS: This study indicates that even across rural communities in SSA, increasing urbanicity is associated with a higher prevalence of lifestyle risk factors for cardiometabolic diseases. This finding highlights the need to consider the health impact of urbanization in rural areas across SSA. Please see later in the article for the Editors' Summary.