Browsing by Author "Chikowore, Tinashe"

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Nutrition of ageing black South African women and correlates with anthropometry and cardiometabolic outcomes
(University of the Witwatersrand, Johannesburg, 2023-09) Kankwende, Caroline Belinda Tsitsi; Gradidge, Philippe; Norris, Shane; Chikowore, Tinashe
Background: Obesity is most prevalent among black women who reside in urban areas in South Africa yet the nutrient patterns of this cohort of women has never been investigated, nor have correlates of body composition indices such as adiposity and body mass index (BMI). These body composition indices are important to analyse as they have been shown to be positively associated with hypertension which is prevalent in this cohort of women. Aim: There were three main goals: 1) To determine the baseline nutrient patterns of middle-aged black South African women residing in Soweto and correlates to body composition indices 2) To evaluate the longitudinal association of nutrient patterns with adiposity in a cohort of middle-aged black South African women over a period of 5.5- years 3) To elucidate the longitudinal associations of nutrient patterns and blood pressure and to explore whether this is an indirect effect mediated by body mass index (BMI) using structural equation modelling Methods: A longitudinal study of children and their families, originally called the Birth to Twenty Plus (Bt20+) cohort and now referred to as the Middle-aged Soweto Cohort (MASC), was used to as the original dataset for this thesis. This study also drew on another embedded study, the Study of Women Entering and in Endocrine Transition (SWEET) study of older women transitioning through menopause. Data on (i) dietary information; (ii) body composition and anthropometry measurements; (iii) blood pressure; (iv) lifestyle behaviours (physical activity, tobacco use, and alcohol use); (v) psychosocial factors; (vi) socioeconomic status; and (vii) educational status were used. A total of 498 Women aged between 40 and 60 years old were included in the study. Principle component analysis (PCA) was applied on the dietary data both at baseline and at 5- years follow-up. This was conducted to extract nutrient patterns from 25 nutrients derived from the food frequency questionnaire (FFQ) and the resulting nutrient patterns are detailed in results chapter 3 (nutrient patterns derived from the baseline FFQ) and results chapter 4 (comparison between both baseline and follow-up nutrient patterns from the FFQ). Simple and complex body composition were recorded for each participant with complex body measurements taken using (DXA). Chapter 3 details the results of the 3 baseline nutrient patterns and correlates with body composition parameters. Using generalized estimating equations, associations between both baseline and 5- years follow-up nutrient patterns and adiposity were evaluated. The results are discussed in results chapter 4. Lastly, the results chapter 5 examined associations between both baseline and follow-up nutrient patterns and blood pressure were examined and furthermore, investigated whether BMI mediates the relationship between repeated measures of nutrient patterns and blood pressure. Results: The majority of the research participants (88%) were classified as individuals having obese status defined by their BMI. The fat mass index (FMI), lean mass index (LMI), gynoid fat, hip and waist circumference, and visceral and subcutaneous adipose tissue (VAT and SAT respectively) measurements were all substantially larger in the group with predominantly individuals having overweight and obese classification compared to woman in the lean group (p <0.001). Protein consumption was greater in the group with individuals having overweight/obese classification, while fat and carbohydrate consumption were matched. At baseline, the "Plant driven nutrient pattern," characterized by higher factor loadings of plant protein, starch, and B vitamins, explained 25% of the total nutritional variance; the "Animal protein driven nutrient pattern," characterized by animal protein and saturated fat, explained 23% of the variance; and the third pattern was the "Vitamin C, sugar and potassium driven nutrient pattern," which had higher factor loadings of vitamin C, sugar and potassium. At baseline, increased consumption of the animal protein driven nutrient pattern resulted in a 1.19 kg/m2 (p = 0.002) increase in BMI, 10.17 cm2 for VAT, 24.43 cm2 for SAT, 0.01 (p = 0.009) increase for VAT/SAT ratio, 0.69 kg/m2 (p = 0.005) increase for FMI, and 0.48 kg/m2 (p = 0.002) increase for LMI. Furthermore at baseline, statistically significant associations were found for the animal protein driven nutrient pattern with all body composition indicators. Subcutaneous adipose tissue increased in the presence of a plant-driven nutrition pattern (p = 0.045). At 5-year follow-up, although the value of the factor loadings of the individual nutrients changed between baseline and follow-up, the nutrients with the highest loadings for each principal component (PC) did not change therefore the overall nutrient patterns remained the same. Only DXA-derived measurements of fat mass, FMI, VAT, and gynoid fat mass (FM) increased with time, while lean mass considerably reduced. Repeated measures of the animal protein driven nutrient pattern was associated with significant increases in FMI, LMI and VAT and repeated measures of the vitamin C, sugar, and potassium driven nutrient pattern was significantly associated with an increase in FMI and LMI. For the purposes of this study, repeated measures of animal-driven nutrient patterns were shown to be significantly related with repeated measures of systolic blood pressure (SBP) only. When structural equation modelling (SEM) was applied, only significant relationships were observed between age and SBP. This relationship was not mediated by BMI but may involve other factors that were not included in this analysis. Conclusions: This thesis explored the nutrient patterns linked to obesity and cardiometabolic complications, namely blood pressure, in a cohort of black middle-aged African females. It has been previously demonstrated that this cohort has been has a high prevalence of obesity. According to literature reviews, programs focusing on nutritional and behavioural changes could aid African women in their fight against the obesity and hypertension epidemic that we are facing today. The animal-driven nutrient pattern was found to be substantially associated with increases in body fat in this cohort at baseline. At 5-year follow-up, the nutrient patterns remained the same and repeated measurements of the vitamin C, sugar, and potassium-driven nutrient pattern were associated with significant increases in FMI and LMI and the animal-driven nutrient pattern remained significantly associated with LMI, FMI and VAT, a measure of visceral obesity which is a major risk factor for cardiometabolic conditions. This is problematic in a population that consists predominantly of individuals that are classified as having an obese and overweight status. As a result of a higher BMI, a greater likelihood of developing cardiometabolic multimorbidity exists which is defined as the co-occurrence of two or three cardiometabolic conditions. This may result in reduced quality of life and an increased burden on the already overstretched healthcare system in South Africa. Furthermore, this study found that only the animal protein driven nutrient pattern had a significant relationship with SBP which was significant. When SEM was applied, BMI did not mediate the relationship between blood pressure and any of the nutrient patterns. No other noteworthy direct relationships between blood pressure and the other nutrient patterns were found. Researchers can apply the findings of this study to improve nutritional policies and guidelines aimed at combating not just obesity, but high blood pressure among black women in Sub-Saharan Africa. It is necessary to conduct further extensive research to verify these findings.
Relationship of diet and physical activity with genetic susceptibility to obesity: a longitudinal analysis in adults in South Africa
(University of the Witwatersrand, Johannesburg, 2024) Muti, Monica; Chikowore, Tinashe; Ware, Lisa
Background Obesity-related disease conditions are a major public health concern in South Africa, exerting a healthcare cost of between ZAR 30 million and ZAR 36 million, the bulk of which is due to hypertension and type 2 diabetes. Moreover, evidence reveals that women in South Africa have higher BMI compared to men, yet men exhibit less insulin sensitivity and reduced beta cell function as well as stronger associations of adiposity with type 2 diabetes compared to women. The mechanisms underlying these sex differences are not known. BMI is highly polygenic in nature; however, genetic prediction of BMI has mostly been conducted using data from European ancestry populations that have poor predictive capacity in African ancestry populations. Moreover, the relationship of polygenic risks and proteomic profiles with regards to susceptibility to obesity and related cardiometabolic traits is yet to be explored in African populations. It has also been reported that using variants associated with the statistical variance of quantitative traits (vQTLs) like BMI aids in the depiction of components of BMI genetic susceptibility, which interacts with environmental factors such as diet and exercise. However, such studies are limited in continental Africans. Aim This thesis, sought to determine the interplay of diet and physical activity with BMI genetic susceptibility. The specific objectives were: 1. To determine the association of physical activity with BMI in middle-aged black South African men and women. 2. To develop a highly predictive genetic risk score for BMI and test its longitudinal predictive ability in middle-aged black South African men and women. 3. To determine gene x lifestyle (GXE) interactions that influence BMI in Black South African adult men and women. Methods Data from 11853 adult men and women in the African-Wits-INDEPTH partnership for Genomic studies (AWI-Gen) Cohort was used to fulfil objective 1. To fulfil objectives 2 and 3, data from 5921 AWI-Gen cohort participants in the three South African (SA) sites and a sub-study of AWI-Gen focusing on the factors influencing the risk of type 2 diabetes mellitus among middle-aged black South African men and women (GSK) was used. For objective 1, a sex-stratified meta-analysis of cross-sectional data from the study participants was used to assess the association of physical activity with BMI. The PRS-CSx method was used to develop a multi-ancestry PRS for BMI and evaluate its longitudinal prediction of severe obesity to meet objective 2. For objective 3, the Levene’s test, implemented in the OCSA Package, was used to determine candidate gene-interacting variants that exhibited trait variance heterogeneity in the study population. Detailed methods are in the relevant sections for each objective. Results Meeting the recommended weekly physical activity levels of at least 150 minutes was associated with a BMI that was 0.80kg/m2 lower in men (95% CI = -1.14; -0.47) and 0.68kg/m2 lower in women (95% Ci = -1.03; -0.33). Sex and site-specific differences were also observed in domains of physical activity with an inverse relationship between transport-related physical activity and BMI being observed among men in Agincourt (beta = -1.15 kg/m2, 95% CI = -2.26; -0.04) and Nanoro (beta = -0.79 kg/m2, 95%CI = -1.25; -0.33). Work related physical activity was associated with lower BMI in Navrongo men (beta = -0.76 kg/m2, 95% CI=-1.25; -0.27) and Nanoro women (beta = -0.90 kg/m2, 95%CI = -1.44; -0.36). The multi-ancestry PRS demonstrated superior predictive ability, explaining approximately 1.9% of variance in BMI compared to 0.7% and 1.2% explained by two scores developed using single ancestry methods. In addition, over a period of ten years, the multi-ancestry PRS was associated with repeated measures of BMI (β = 1.51 p = < 0.001) and there was significant longitudinal PRS * sex interaction (Pinteraction = 0.029), prompting subsequent sex-stratified analysis. In the combined analysis of men and women, being in the top 20% of the PRS distribution (top 20) was associated with three times greater hazard of severe obesity (hazard ratio = 2.98, 95% CI = 1.75 - 5.07, p = 5.33e-05) compared to being in the bottom 20% of the PRS distribution (bottom 20). This observation was shown to be driven by women, where being a woman in the top 20 was associated with 3.5 greater hazard of severe obesity (hazard ratio 3.48, 95% CI = 1.96 – 6.16, p = 1.94e-05) compared to being in the bottom 20 while the associations were not significant in men (hazard ratio = 1.13, 95% CI = 0.24 – 5.37, p = 0.878). Comparison of the associations of dysglycaemia with PRS, BMI and the proteomic score revealed no apparent sex differences in the association between BMI PRS and dysglycaemia for most of the glycaemic markers except for Matsuda Index though men exhibited lower insulin sensitivity compared to women. The proteomic score predicted higher insulin resistance in women than in men. Gene x lifestyle interaction analysis revealed novel interactions between three genetic variants with diet and lifestyle factors. The effect of the rs557505940 variant on BMI was accentuated by higher fruit intake (betainteraction = 0.03, Pinteraction = 0.04) in the combined analysis of men and women while higher SES, carbohydrate intake and self- reported physical activity attenuated the effect of rs527747185 (betainteraction = -0.349, Pinteraction = 0.037), rs3016751 (betainteraction = -0.056, Pinteraction = 0.035) and rs188275749 (betainteraction = -0.048, Pinteraction = 0.0001) respectively on BMI in men. Conclusions Sex and geographical differences exist in associations between domains of physical activity and BMI. In addition, genetic risk better predicts incident severe obesity in women than in men while proteomic profiles have a weak correlation with PRS and show heterogenous associations with dysglycaemia, fat distribution, nutrient patterns and physical activity between men and women. Novel GXE interactions were also observed. These results underscore the need for further inquiry into the sex differences in genetic risk and environmental factors associated with BMI. Furthermore, a precision approach to obesity prevention and control, paying attention to the sex differences and contextual factors may be more efficient.
SHBG, free testosterone, and Type 2 Diabetes risk in middle-aged African men: a longitudinal study
(Oxford University Press, 2024) Norris, Shane; Seipone, Ikanyeng D.; Mendham, Amy E.; Storbeck, Karl-Heinz; Oestlund, Imken; Kufe, Clement N.; Chikowore, Tinashe; Masemola, Maphoko; Crowther, Nigel J.; Kengne, Andre Pascal; Olsson, Tommy; Brown, Todd; Micklesfield, Lisa K.; Goedecke, Julia H.
Objectives: To investigate longitudinal changes in SHBG and free testosterone (free T) levels among Black middle-aged African men, with and without coexistent HIV, and explore associations with incident dysglycaemia and measures of glucose metabolism. Design: This longitudinal study enrolled 407 Black South African middle-aged men, comprising primarily 322 men living without HIV (MLWOH) and 85 men living with HIV (MLWH), with normal fasting glucose at enrollment. Follow-up assessments were conducted after 3.1 ± 1.5 years. Methods: At baseline and follow-up, SHBG, albumin, and total testosterone were measured and free T was calculated. An oral glucose tolerance test at follow-up determined dysglycaemia (impaired fasting glucose, impaired glucose tolerance, type 2 diabetes) and glucose metabolism parameters including insulin sensitivity (Matsuda index), insulin resistance (homeostasis model assessment of insulin resistance), and beta(β)- cell function (disposition index). The primary analysis focussed on MLWOH, with a subanalysis on MLWH to explore whether associations in MLWOH differed from MLWH. Results: The prevalence of dysglycaemia at follow-up was 17% (n = 55) in MLWOH. Higher baseline SHBG was associated with a lower risk of incident dysglycaemia (odds ratio 0.966; 95% confidence interval 0.945-0.987) and positively associated with insulin sensitivity (β = 0.124, P < .001) and β-cell function (β = 0.194, P = .001) at follow-up. Free T did not predict dysglycaemia. In MLWH, dysglycaemia prevalence at follow-up was 12% (n = 10). Neither baseline SHBG nor free T were associated with incident dysglycaemia and glucose metabolism parameters in MLWH. Conclusion: SHBG levels predict the development of dysglycaemia in middle-aged African men but do not exhibit the same predictive value in MLWH.
Variability of polygenic prediction for body mass index in Africa
(BioMed Central (BMC), 2024) Norris, Shane A.; Chikowore, Tinashe; Läll, Kristi; Micklesfield, Lisa K.; Lombard, Zane; Goedecke, Julia H.; Fatumo, Segun; Magi, Reedik; Ramsay, Michele; Franks, Paul W.; Pare, Guillaume; Morris, Andrew P.
Background: Polygenic prediction studies in continental Africans are scarce. Africa’s genetic and environmental diversity pose a challenge that limits the generalizability of polygenic risk scores (PRS) for body mass index (BMI) within the continent. Studies to understand the factors that affect PRS variability within Africa are required. Methods: Using the first multi-ancestry genome-wide association study (GWAS) meta-analysis for BMI involving continental Africans, we derived a multi-ancestry PRS and compared its performance to a European ancestry-specific PRS in continental Africans (AWI-Gen study) and a European cohort (Estonian Biobank). We then evaluated the factors affecting the performance of the PRS in Africans which included fine-mapping resolution, allele frequencies, linkage disequilibrium patterns, and PRS-environment interactions. Results: Polygenic prediction of BMI in continental Africans is poor compared to that in European ancestry individuals. However, we show that the multi-ancestry PRS is more predictive than the European ancestry-specific PRS due to its improved fine-mapping resolution. We noted regional variation in polygenic prediction across Africa’s East, South, and West regions, which was driven by a complex interplay of the PRS with environmental factors, such as physical activity, smoking, alcohol intake, and socioeconomic status. Conclusions: Our findings highlight the role of gene-environment interactions in PRS prediction variability in Africa. PRS methods that correct for these interactions, coupled with the increased representation of Africans in GWAS, may improve PRS prediction in Africa.