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OBJECTIVES: Given the increasing prevalence of obesity and need for effective interventions, there is a growing interest in understanding how an individuals body image can inform obesity prevention and management. This studys objective was to examine the use of silhouette showcards to measure body size perception compared with measured body mass index, and assess body size dissatisfaction, in three different African-origin populations spanning the epidemiological transition. An ancillary objective was to investigate associations between body size perception and dissatisfaction with diabetes and hypertension. SETTING: Research visits were completed in local research clinics in respective countries. PARTICIPANTS: Seven hundred and fifty-one African-origin participants from the USA and the Republic of Seychelles (both high-income countries), and Ghana (low/middle-income country). PRIMARY AND SECONDARY OUTCOME MEASURES: Silhouette showcards were used to measure perceived body size and body size dissatisfaction. Objectively measured body size was measured using a scale and stadiometer. Diabetes was defined as fasting blood glucose ≥126 mg/dL and hypertension was defined as ≥130 mm Hg/80 mm Hg. RESULTS: Most women and men from the USA and Seychelles had Perceived minus Actual weight status Discrepancy scores less than 0, meaning they underestimated their actual body size. Similarly, most overweight or obese men and women also underestimated their body size, while normal weight men and women were accurately able to estimate their body size. Finally, participants with diabetes were able to accurately estimate their body size and similarly desired a smaller body size. CONCLUSIONS: This study highlights that overweight and obese women and men from countries spanning the epidemiological transition were unable to accurately perceive their actual body size. Understanding peoples perception of their body size is critical to implementing successful obesity prevention programmes across the epidemiological transition.

The relationship between microbiota, short chain fatty acids (SCFAs), and obesity remains enigmatic. We employ amplicon sequencing and targeted metabolomics in a large (n = 1904) African origin cohort from Ghana, South Africa, Jamaica, Seychelles, and the US. Microbiota diversity and fecal SCFAs are greatest in Ghanaians, and lowest in Americans, representing each end of the urbanization spectrum. Obesity is significantly associated with a reduction in SCFA concentration, microbial diversity, and SCFA synthesizing bacteria, with country of origin being the strongest explanatory factor. Diabetes, glucose state, hypertension, obesity, and sex can be accurately predicted from the global microbiota, but when analyzed at the level of country, predictive accuracy is only universally maintained for sex. Diabetes, glucose, and hypertension are only predictive in certain low-income countries. Our findings suggest that adiposity-related microbiota differences differ between low-to-middle-income compared to high-income countries. Further investigation is needed to determine the factors driving this association.

Sleep disorders are increasingly being characterized in modern society as contributing to a host of serious medical problems, including obesity and metabolic syndrome. Changes to the microbial community in the human gut have been reportedly associated with many of these cardiometabolic outcomes. In this study, we investigated the impact of sleep length on the gut microbiota in a large cohort of 655 participants of African descent, aged 25-45, from Ghana, South Africa (SA), Jamaica, and the United States (US). The sleep duration was self-reported via a questionnaire. Participants were classified into 3 sleep groups: short (

Traditional obesity-related public health messaging often includes physical activity (PA) recommendations. However, at the population level, the data are conflicting, especially when comparing different self-reported vs measured techniques across different settings and populations. We measured the association between moderate-to-vigorous intensity PA (MVPA) and prospective weight change across five African-origin populations and the extent to which MVPA attenuated weight change over time. At baseline, 2,500 adults (median age: 37y) were recruited into the Modelling the Epidemiologic Transition Study (METS), from Ghana, South Africa, Jamaica, Seychelles, and US. 2000 participants were followed up 8 years later, with 851 participants having complete 7-day accelerometry to measure MVPA at both time points. Generalised estimating equations were used to explore the longitudinal association between weight and MVPA adjusted for several confounders. The obesity prevalence at baseline was 27.5% which increased to 38.0% at follow-up. Baseline MVPA varied from 7 (IQR: 4, 16) min/day in US women to 52 (IQR: 36, 78) min/day in South African men, and similarly at follow-up ranged from 8 min/day to 41 min/day among the same participant groups. While overall, engaging in higher MVPA levels was associated with a lower body weight, such that every additional 30 min of MVPA equalled a 600g lower body weight (p = 0.04), the interaction between time and MVPA was not statistically significant (p = 0.18). Therefore, regardless of the amount of MVPA at any time point, body weight increased over time. Despite the association between MVPA and weight, our results suggest that objectively measured longitudinal MVPA was not associated with the change in 8-year weight in African-origin adults. Our research confirms that while PA is a critical determinant of cardiovascular health, it alone may not be enough to stem the rising obesity burden., Competing Interests: Competing interests The authors declare that they have no competing interests, or financial competing interests to declare.

Background: Physical activity (PA) is an important preventive factor of non-communicable diseases (NCDs), particularly cardiovascular disease, yet progress towards reducing physical inactivity in populations is slow. Population-levels of PA are most often estimated using self-report questionnaires in population surveys, such as the Global PA Questionnaire (GPAQ), which may not accurately reflect objectively measured PA, such as accelerometers. The aim of the current study was to compare self-report vs objectively measured PA across 5 African-origin populations., Methods: Approximately 2,000 African-origin men and women (35-55 yrs) were enrolled in a prospective cohort study to explore the relationship between lifestyle and cardiometabolic health. Participants were from Ghana, South Africa (SA), Jamaica, Seychelles, and the United States (US). Data collection included objective PA (accelerometer) and self-reported PA (GPAQ). WHO defines "sufficiently active" as performing >150 minutes of moderate intensity PA per week, or >600 MET*min/week (metabolic equivalent of task in minutes/week). Logistic regression was used to determine the proportion of participants that were physically active by accelerometry, among those who were found as sufficiently active based on GPAQ., Results: 1,161 participants had complete self-reported PA and accelerometery data. Overall, 23.5% were classified as sufficiently active by both PA measures, while 38.2% of those classified as sufficiently active based on self-reported PA did not meet the criteria using objective monitoring (sensitivity of GPAQ: 74%, specificity: 44%). Among participants who were classified as sufficiently active according to the questionnaire (n=717), participants from Ghana (OR=3.2, p<0.01), SA (OR=5.3, p<0.01), Jamaica (OR=2.3, p=0.01), and Seychelles (OR=1.9, p=0.03) were more likely to be similarly classified as sufficiently active based on accelerometry, compared to those from the US, and men (OR=2.9, p<0.01) more likely than women. Finally, obese participants had 0.4 times lower adjusted odds to be similarly classified as sufficiently active using objective measures compared to non-obese participants (p<0.01)., Conclusion: Our findings further underscore difficulties in interpreting self-reported PA, which may furthermore vary across different settings and socio-economic settings. Given the importance of PA interventions for reducing the NCD burden, future research should explore tailored approaches to better understand self-report PA accuracy and to better assess the dose-response between PA and cardiometabolic risk., Competing Interests: Competing interests The authors declare that they have no competing interests, or financial competing interests to declare.

Exposure to toxic metals impacts obesity and type 2 diabetes (T2DM) risk. Yet, the underlying mechanisms remain largely unknown. Gut microbiota has been strongly associated with progression of cardiometabolic risk. To determine whether high metal exposures and gut dysbiosis interact to promote metabolic dysregulation and cardiometabolic risk, we assessed relationships between these factors. We analyzed cross-sectional associations between arsenic, lead, mercury, cadmium, and cardiometabolic health markers in 178 randomly selected African-origin adults (52% female, 51% obese, mean age=43.0±6.4 years) from Ghana, South Africa, Seychelles, Jamaica, and USA. Metal levels were dichotomized to high or low at the median level of each metal. We analyzed associations between gut microbiome taxa, metal levels, clinical measures (BMI, fasting blood glucose, and blood pressure) and diagnoses (hypertension, obesity, and diabetes status). High vs. low lead and arsenic exposures had a significant effect on beta diversity (p <0.05). 71 taxa were associated with high lead levels: 30 with elevated BMI, 22 with T2DM, and 23 with elevated fasting blood glucose (p<0.05). 115 taxa were associated with high arsenic levels: 32 with elevated BMI, 33 with T2DM, and 26 with elevated blood glucose (p<0.05). Of the taxa associated with high lead and arsenic exposure and either elevated BMI or fasting blood glucose, porphyrin metabolism was the most enriched metabolic pathway. These data collectively provide the first findings in a human study that the gut microbiome may drive the association between lead and arsenic exposure and obesity and T2DM risk., Competing Interests: Competing Interests. No potential conflicts of interest relevant to this article were reported.

The relationship between the gut microbiota, short chain fatty acid (SCFA) metabolism, and obesity remains unclear due to conflicting reports from studies with limited statistical power. Additionally, this association has rarely been explored in large scale diverse populations. Here, we investigated associations between fecal microbial composition, predicted metabolic potential, SCFA concentrations, and obesity in a large ( N = 1,934) adult cohort of African-origin spanning the epidemiologic transition, from Ghana, South Africa, Jamaica, Seychelles, and the United States (US). The greatest gut microbiota diversity and total fecal SCFA concentration was found in the Ghanaian population, while the lowest levels were found in the US population, respectively representing the lowest and the highest end of the epidemiologic transition spectrum. Country-specific bacterial taxa and predicted-functional pathways were observed, including an increased prevalence of Prevotella , Butyrivibrio , Weisella and Romboutsia in Ghana and South Africa, while Bacteroides and Parabacteroides were enriched in Jamaican and the US populations. Importantly, 'VANISH' taxa, including Butyricicoccus and Succinivibrio , were significantly enriched in the Ghanaian cohort, reflecting the participants' traditional lifestyles. Obesity was significantly associated with lower SCFA concentrations, a decrease in microbial richness, and dissimilarities in community composition, and reduction in the proportion of SCFA synthesizing bacteria including Oscillospira , Christensenella , Eubacterium , Alistipes , Clostridium and Odoribacter . Further, the predicted proportions of genes in the lipopolysaccharide (LPS) synthesis pathway were enriched in obese individuals, while genes associated with butyrate synthesis via the dominant pyruvate pathway were significantly reduced in obese individuals. Using machine learning, we identified features predictive of metabolic state and country of origin. Country of origin could accurately be predicted by the fecal microbiota (AUC = 0.97), whereas obesity could not be predicted as accurately (AUC = 0.65). Participant sex (AUC = 0.75), diabetes status (AUC = 0.63), hypertensive status (AUC = 0.65), and glucose status (AUC = 0.66) could all be predicted with different success. Interestingly, within country, the predictive accuracy of the microbiota for obesity was inversely correlated to the epidemiological transition, being greatest in Ghana (AUC = 0.57). Collectively, our findings reveal profound variation in the gut microbiota, inferred functional pathways, and SCFA synthesis as a function of country of origin. While obesity could be predicted accurately from the microbiota, the variation in accuracy in parallel with the epidemiological transition suggests that differences in the microbiota between obesity and non-obesity may be larger in low-to-middle countries compared to high-income countries. Further examination of independent study populations using multi-omic approaches will be necessary to determine the factors that drive this association.