Association Between Alcohol Consumption and Blood Pressure Levels Among HIV Sero-Positive and Sero-Negative Cohorts: A Secondary Analysis of the Vukuzazzi Study.

BACKGROUND: The effect of hypertension is aggravated by lifestyle factors such as alcohol consumption. This study sought to determine the association between alcohol consumption and the level of blood pressures among HIV seronegative and seropositive cohorts. METHODS: This secondary analysis was performed on a cross-sectional survey data of 17 922 participants during the period between 2018 and 2020. A questionnaire was used to obtain participants' alcohol consumption history, which was categorized into non-alcohol consumers, non-heavy alcohol consumers, and heavy alcohol consumers. A linear regression model was used to establish relationships among participants with raised blood pressure (BP ≥ 140/90 mmHg). RESULTS: Out of the total participants, 3553 (19.82%) were hypertensives. Almost 13% of the hypertensives (n = 458; 12.89%) were undiagnosed, and 12.44 % (442) had uncontrolled hypertension. About 14.52% of the hypertensives (3553) were not on any antihypertensive medication. Male non-consumers of alcohol had the highest systolic and diastolic BP; uncontrolled systolic BP (165.53 ± 20.87 mmHg), uncontrolled diastolic BP (102.28 ± 19.21mmHg). Adjusted for covariates, moderate alcohol consumption was associated with HTN among participants who were HIV seropositive [unadjusted (RR = 1.772, P = .006, 95% CI (1.178-2.665)], [RR = 1.772, P = .005, 95% CI (1.187-2.64)]. [unadjusted RR = 1.876, P = .036, 95% CI (1.043-3.378)], adjusted RR = 1.876, P = .041, 95% CI (1.024-3.437). Both moderate and heavy alcohol consumption were significantly related to hypertension among HIV sero-negative [unadjusted model, moderate consumption RR = 1.534 P = .003, 95% CI (1.152-2.044)], [adjusted model, moderate alcohol consumption RR = 1.535, P = .006, 95% CI (1.132-2.080)], [unadjusted model, heavy alcohol consumption, RR = 2.480, P = .030, 95% CI (1.091-5.638)], [adjusted model RR = 2.480, P = .034, 95% CI (1.072-5.738)]. CONCLUSION: Alcohol consumption is significantly related to increase BP regardless of HIV infection.

Increased endothelial biomarkers are associated with HIV antiretroviral therapy and C-reactive protein among a African rural population in Limpopo Province, South Africa.

In Sub-Saharan Africa (SSA) endothelial dysfunction (ED) and chronic inflammation in the HIV-positive adults population who are on highly active antiretroviral therapy (HAART) are not fully explored. We determined the effect of HAART on chronic inflammation and ED among HAART-exposed adults in a rural setting. Weight and height were measured to quantify the body mass index (BMI). Lipid and Glucose levels were determined. C-reactive protein (CRP), L-selectin, soluble intercellular adhesion molecule (sICAM-1), and soluble vascular cell adhesion molecule (sVCAM-1) in serum samples were tested. The majority of the HAART-exposed group were on treatment for <5 years. Soluble intercellular adhesion molecules, sVCAM-1, L-selectin and CRP were elevated in the HIV-infected groups as compared to the control group. The multivariate analysis showed that HIV infection (HAART-naïve) associated with increased sICAM-1 (ß = 0.350; 95% CI: 0.035-0.664, p = 0.029) and L-selectin (ß = 0.236; 95% CI: 0.038-0.434, p = 0.019) but not sVCAM-1 (ß = 0.009; 95% CI: 0.252-0.270, p = 0.468). The HAART-exposed group is associated with sVCAM-1 (ß = 0.250; 95% CI: 0.015-0.486, p = 0.037) but not with sICAM-1- (ß = 0.253; 95% CI: -0.083-0.590, p = 0.14) and L-selectin (ß = 0.119; 95% CI: -0.016-0.253, p = 0.084). sVCAM-1 was associated with decreased alcohol consumption (ß = -0.245; 95% CI: -0.469-0.021, p = 0.032) while L-selectin was associated with decreased total cholesterol (ß = -0.061; 95% CI: -0.124-0.002, p = 0.05) and increased CRP (ß = 0.015; 95% CI: 0.009-0.022, p < 0.001). Increased endothelial biomarkers were associated with HIV disease and HAART in a rural black adult population of African descent after controlling for CVD risk factors. Inflammation (as measured with CRP) may play an important role in endothelial activation. Further studies are needed to explore the association between endothelial dysfunction and inflammation especially among the HIV-positive population on HAART in similar settings.

Diagnostic accuracy of tri-ponderal mass index and body mass index in estimating overweight and obesity in South African children.

BACKGROUND: Prevalence of obesity in youths has drastically increased in both industrialised and non-industrialised countries, and this transition resulted in an increased prevalence of chronic diseases. AIM: The study aimed to comparatively examine prevalence of overweight and obesity status based on tri-ponderal mass index and body mass index in estimating body fat levels in South African children. SETTING: The study was conducted in Limpopo and Mpumalanga provinces of South Africa. METHODS: A cross-sectional survey of 1361 (boys: n = 678; girls: n = 683) children aged 9-13 years was undertaken. The children's age and sex-related measurements of body weight, waist-to-height ratio, waist-to-hip ratio, triceps skinfold, subscapular skinfolds and sum of skinfold were taken using the International Society for Advancement of Kinanthropometry protocol. TMI and BMI calculations classified children according to weight and age categories. Descriptive statistics, Spearman's correlations and multiple linear regression analyses were set at ≤ 0.05. RESULTS: Obesity classifications on TMI and BMI among children were as follows: Boys: 7.3%, 2.6%; 2.2%, 0.7%; Girls: 4.0%, 1.0%; 1.8%, 0.6%. Body weight, WHtR, WHpR, TSKF, SSKF and ΣSKF significantly correlated with TMI (r = 0.40, p 0.001; r = 0.73, p 0.001; r = -0.09, p 0.001; r = 0.50, p 0.001; r = 0.51, p 0.001 and r = 0.52, p 0.001) and BMI (r = 0.81, p 0.001; r = 0.59, p 0.001; r = -0.22, p 0.001; r = 0.63, p 0.001; r = 0.67, p 0.001 and r = 0.66, p 0.001). Regression analysis revealed that body weight, WHtR, WHpR, TSKF, SSKF and ΣSKF accounted for 65% and 85% of variance in children's TMI (R2 = 0.647, F[6 1354] = 413.977, p 0.001) and BMI (R2 = 0.851, F[6 1354] = 1288.218, p 0.001). CONCLUSION: TMI revealed strikingly higher incidence of overweight and obesity in South African boys and girls than BMI. Future studies are needed to clarify sensitivity of TMI over BMI in quantifying obesity prevalence in children and adolescents.

Diagnostic comparison of Centers for Disease Control and Prevention and International Obesity Task Force criteria for obesity classification in South African children.

BACKGROUND: This study was designed to estimate overweight and obesity in school children by using contrasting definitions recommended by the Centers for Disease Control and Prevention (CDC) and the International Obesity Task Force (IOTF). METHOD: The sample size consisted of 1361 learners (n = 678 boys; n = 683 girls) aged 9-13 years who were randomly selected from Mpumalanga and Limpopo provinces of South Africa. A cross-sectional and descriptive design was used to measure the children's anthropometric characteristics. Based on height and weight measurements, the children's body mass index (BMI) was calculated and used to classify them as underweight, overweight and obese. Percentage body fat was calculated from the sum of two skinfolds (i.e. triceps and subscapular). Age-specific BMI, percentage body fat and sum of skinfolds were examined for the boys and girls. RESULTS: A higher prevalence of overweight and obesity was found in boys and girls when the CDC BMI categories were used. In contrast, the IOTF BMI classifications indicated a strong prevalence of underweight among the children. CONCLUSION: In contrast to the IOTF index that yielded a greater occurrence of underweight among South African children, the CDC criteria indicated a higher prevalence of obesity and overweight among the same children. Future large-scale surveillance studies are needed to determine the appropriateness of different definitions in order to establish a more reliable indicator for estimating overweight and obesity in South African children.

Low levels of physical activity in female adolescents cause overweight and obesity: are our schools failing our children?

The increasing prevalence of overweight and obesity among female adolescents is a global health problem. In developing countries such as South Africa, this increase is often associated with urbanisation and the adoption of a Western lifestyle. Two aspects of the Western lifestyle that contribute to the development of overweight and obesity are a decrease in physical activity levels and an increase in the consumption of energy-dense food, high in fats and refined sugar. Information on the prevalence of increased body fatness in populations in transition is scarce, but necessary for effective planning and intervention. Current indications are that there is a trend towards unhealthy behaviour among high-school girls, globally and in South Africa. Schools can play an important role in the prevention of overweight and obesity among schoolgirls. It is recommended that school governing bodies institute remedial action to prevent weight gain in children, especially girls.

Diagnostic accuracy of tri-ponderal mass index and body mass index in estimating overweight and obesity in South African children

Background: Prevalence of obesity in youths has drastically increased in both industrialised and non-industrialised countries, and this transition resulted in an increased prevalence of chronic diseases. Aim: The study aimed to comparatively examine prevalence of overweight and obesity status based on tri-ponderal mass index and body mass index in estimating body fat levels in South African children. Setting: The study was conducted in Limpopo and Mpumalanga provinces of South Africa. Methods: A cross-sectional survey of 1361 (boys: n = 678; girls: n = 683) children aged 9­13 years was undertaken. The children's age and sex-related measurements of body weight, waist-to-height ratio, waist-to-hip ratio, triceps skinfold, subscapular skinfolds and sum of skinfold were taken using the International Society for Advancement of Kinanthropometry protocol. TMI and BMI calculations classified children according to weight and age categories. Descriptive statistics, Spearman's correlations and multiple linear regression analyses were set at ≤ 0.05. Results: Obesity classifications on TMI and BMI among children were as follows: Boys: 7.3%, 2.6%; 2.2%, 0.7%; Girls: 4.0%, 1.0%; 1.8%, 0.6%. Body weight, WHtR, WHpR, TSKF, SSKF and Σ SKF significantly correlated with TMI (r = 0.40, p < 0.001; r = 0.73, p < 0.001; r = -0.09, p < 0.001; r = 0.50, p < 0.001; r = 0.51, p < 0.001 and r = 0.52, p< 0.001) and BMI (r = 0.81, p < 0.001; r = 0.59, p < 0.001; r = -0.22, p < 0.001; r = 0.63, p < 0.001; r = 0.67, p < 0.001 and r = 0.66, p < 0.001). Regression analysis revealed that body weight, WHtR, WHpR, TSKF, SSKF and Σ SKF accounted for 65% and 85% of variance in children's TMI (R 2 = 0.647, F[6 1354] = 413.977, p < 0.001) and BMI (R 2 = 0.851, F[6 1354] = 1288.218, p< 0.001). Conclusion: TMI revealed strikingly higher incidence of overweight and obesity in South African boys and girls than BMI. Future studies are needed to clarify sensitivity of TMI over BMI in quantifying obesity prevalence in children and adolescents