Premium
Predicting Metabolic Syndrome Risk Factors Using Different Anthropometric Indices Of Obesity In A Farm Worker Population, Western Cape South Africa
Author(s) -
Nell Theo A,
Kruger Maritza J
Publication year - 2016
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.30.1_supplement.1293.5
Subject(s) - metabolic syndrome , medicine , waist , anthropometry , obesity , body mass index , population , epidemiology , diabetes mellitus , endocrinology , environmental health
Anthropometric assessments can be used in epidemiological field studies to assess health status. The prevalence of both the metabolic syndrome(MetS) and obesity are on the increase in the South African population, thus increasing the risk of developing lifestyle related diseases including diabetes, cardiovascular disease, and cancer. The farm worker population in the Western Cape Province are also now included in this increased prevalence. Using anthropometrical indices, such as body mass index (BMI), waist circumference (WC), and waist to hip ratio (W:H) in epidemiological field studies, could possibly increase the risk prediction of the metabolic syndrome as well as obesity. This cross‐sectional study included both men and women (total n= 188; n= 147 women and n=41 men) which revealed a total metabolic syndrome prevalence of 42.6%. The women in this sample had a 46% prevalence compared to the men (29%). We then wanted to distinguish the association between anthropometrical indices and the metabolic syndrome risk factors for both genders, irrespective of their metabolic status. We reported that the women showed significant correlations for all the metabolic syndrome risk factors with the following anthropometrical indices; BMI, WC and W:H. This was not seen for the men where BMI, WC and W:H only significantly correlated with high density lipoprotein cholesterol(HDL‐c), glucose (Gluc), triglycerides (TG), and diastolic blood pressure (DBP). Since the women seemed to have a higher risk for the metabolic syndrome we further subdivided only the women into either the metabolic syndrome (IDF criteria) versus non‐metabolic syndrome groups. In the metabolic syndrome group, W:H was only significantly correlated with TG (r=0.32; p=0.007) and Gluc (r=0.39;p=0.001), whilst, BMI was significantly correlated with systolic blood pressure(SBP) (r=0.39; p=0.001) and DBP (r=0.31; p=0.001). Waist circumference was only significantly correlated with SBP (r=0.35; p=0.003). For the non‐metabolic syndrome group, only W:H significantly correlated with TG (r=0.43; p=0.000). The BMI, WC and W:H may be better predictors of the metabolic syndrome in the female group, however, when this group were subdivided this was no longer evident. Here, the W:H and BMI indices were better predictors of only certain risk factors. Support or Funding Information This study was funded by the Cancer Association of South Africa (CANSA)