The prevalence of hypertension and the relationship with body composition in Grade 1 learners in the North West Province of South Africa

Abstract

Abstractobjective. To determine the prevalence of hypertension in Grade 1 learners in the North West Province of South Africa and to investigate the association between blood pressure (BP) and body composition of these children. Methods. Data were collected by means of a stratified random sampling procedure from 816 Grade 1 learners (419 boys, 397 girls) with a mean age of 6.78±0.49 years (mean±SD), in the NW-CHILD-study. Height, weight, skinfolds (subscapular, triceps, calf) and waist circumference were measured. The international recommended cut-off values of Cole et al. (2000) for body mass index (BMI) were used. Hypertension, defined as the average of two separate BP (BP) readings, where the systolic BP and diastolic BP is >95th percentile for age, sex and height, was determined by means of an Omron 705CP-II. Results. The overall prevalence of prehypertension and hypertension was 8.5% and 24.9%, respectively. Both systolic and diastolic BP was positively associated with BMI, body fat percentage and waist circumference. Boys and girls showed a similar prevalence of hypertension. A higher percentage of black children were hypertensive compared with whites, although the difference in BP of the groups was not significant. A high percentage of children with normal weight also showed increased levels of BP. Conclusions. High prevalences of hypertension were found in Grade 1 learners in the North West Province of South Africa. Small practical significant associations existed between BP and body composition. BP screening is therefore considered important in the paediatric population. Interventions which include physical activity are recommended to reduce potential cardiovascular complications and obesity among children. Other contributing factors to high BP amongst young children should also be investigated.

Prehypertension and Hypertension among Schoolchildren in Brazzaville, Congo

“…In Africa, low prevalences of HT were reported as 4.9% in Sudan [5] and 4% in Egypt [11]. On the other hand, the rate of 10.1% hypertensive black Bantu Congolese children in this study is intermediate between those from non-Bantu Sudanese and Egyptian children [5, 11] and that of 29.4% black Bantu South African children [6]. These differences are related to standards of developing or emerging economies, overweight/obesity [17–19], and ethnic/genetic factors [3, 22].…”

Obesity in 7 - 10-year-old children in urban primary schools in Port Elizabeth

“…Truter et al [21] analysed children aged 9 -13 years (N=280) from various socioeconomic strata and indicated an overweight and obesity prevalence rate of 15.5% and 6.5%, respectively. Kemp et al [22] analysed the BMI values of 7-year-old children (N=816) from lower socioeconomic areas and reported that 7.8% of the participants were overweight and 3.8% were obese. Both of these studies used previous methods of arbitrarily defined percentile cut-offs and smaller sample sizes with variation in variables.…”

“…Both of these studies used previous methods of arbitrarily defined percentile cut-offs and smaller sample sizes with variation in variables. [21,22] The perception currently exists that rural children from impoverished environments have lower prevalence of obesity and overweight than their counterparts with higher socioeconomic status; [19] however, more scientific evidence, including studies with larger sample sizes, equivalent variables and the use of internationally accepted BMI criteria, are needed to confirm this trend in SA. The HDI [20] categorises SA as a country in transition, similar to Algeria, Egypt, China and India; therefore it is relevant to make a comparison with international studies.…”

Relationships between academic performance, SES school type and perceptual‐motor skills in first grade South African learners: NW‐CHILD study

“…A stratified random sample of schools and educational districts in the NWP of SA was used and the process is described in detail elsewhere (Kemp et al . ). The regions and schools were chosen randomly with respect to population density and SES (from Quintile 1 – schools in poorest socio‐economic areas, to Quintile 5 – schools in areas with the highest SES).…”