OBJECTIVE: To determine the relation of skeletal body build and obesity to blood pressure and the prevalence of hypertension. DESIGN: Cross-sectional data obtained from the baseline recruitment of the EPIC-Potsdam Study, which is part of the European Prospective Investigation into Cancer and Nutrition (EPIC). SUBJECTS: A total of 10,303 subjects (4387 men, aged 40-65 y and 5916 women, aged 35-65 y) were recruited between January 1995 and July 1996. MEASUREMENTS: Anthropometric measures included body mass index (BMI), waist-hip ratio (WHR) and metrik index (MIX) as a measure of body build that is derived from the relation of chest depth and breadth to body height. Systolic and diastolic blood pressure was obtained using automatic oscillometric devices. Hypertension was defined as blood pressure > or = 160/95 mmHg or current use of antihypertensive medication. Information on lifestyle factors were obtained by personal interview. STATISTICAL ANALYSIS: Logistic regression was used to define the association of categories of BMI, WHR, and MIX and the prevalence of hypertension. Odds ratios (ORs) of being hypertensive were estimated comparing the highest to the lowest quintile, adjusting for age, smoking status, alcohol intake level, educational attainment, physical activity categories, and each of the anthropometric variables. RESULTS: The simultaneously adjusted OR of being hypertensive, comparing the highest vs the lowest category, was for BMI 2.3 (95% confidence interval (CI) = 1.6-3.2) in men and 1.8 (95% CI = 1.4-2.5) in women, for WHR 1.8 (95% CI = 1.4-2.4) in men and 1.5 (95% CI = 1.2-2.0) in women, and for MIX (largest chest size vs lowest chest size relative to body height) 2.0 (95% CI = 1.4-2.8) in men and 2.2 (95% CI = 1.6-3.1) in women. CONCLUSION: In addition to measures of overall obesity (BMI) as well as central obesity (WHR), skeletal body build (MIX) was independently associated with the prevalence of hypertension. The biological mechanism relating MIX to hypertension, however, is still unclear and needs further exploration.
OBJECTIVE: To determine the relation of skeletal body build and obesity to blood pressure and the prevalence of hypertension. DESIGN: Cross-sectional data obtained from the baseline recruitment of the EPIC-Potsdam Study, which is part of the European Prospective Investigation into Cancer and Nutrition (EPIC). SUBJECTS: A total of 10,303 subjects (4387 men, aged 40-65 y and 5916 women, aged 35-65 y) were recruited between January 1995 and July 1996. MEASUREMENTS: Anthropometric measures included body mass index (BMI), waist-hip ratio (WHR) and metrik index (MIX) as a measure of body build that is derived from the relation of chest depth and breadth to body height. Systolic and diastolic blood pressure was obtained using automatic oscillometric devices. Hypertension was defined as blood pressure > or = 160/95 mmHg or current use of antihypertensive medication. Information on lifestyle factors were obtained by personal interview. STATISTICAL ANALYSIS: Logistic regression was used to define the association of categories of BMI, WHR, and MIX and the prevalence of hypertension. Odds ratios (ORs) of being hypertensive were estimated comparing the highest to the lowest quintile, adjusting for age, smoking status, alcohol intake level, educational attainment, physical activity categories, and each of the anthropometric variables. RESULTS: The simultaneously adjusted OR of being hypertensive, comparing the highest vs the lowest category, was for BMI 2.3 (95% confidence interval (CI) = 1.6-3.2) in men and 1.8 (95% CI = 1.4-2.5) in women, for WHR 1.8 (95% CI = 1.4-2.4) in men and 1.5 (95% CI = 1.2-2.0) in women, and for MIX (largest chest size vs lowest chest size relative to body height) 2.0 (95% CI = 1.4-2.8) in men and 2.2 (95% CI = 1.6-3.1) in women. CONCLUSION: In addition to measures of overall obesity (BMI) as well as central obesity (WHR), skeletal body build (MIX) was independently associated with the prevalence of hypertension. The biological mechanism relating MIX to hypertension, however, is still unclear and needs further exploration.
Authors: Tobias Pischon; Matthias Möhlig; Kurt Hoffmann; Joachim Spranger; Cornelia Weikert; Stefan N Willich; Andreas F H Pfeiffer; Heiner Boeing Journal: Eur J Epidemiol Date: 2007-06-08 Impact factor: 8.082