Relation between dietary pattern analysis (principal component analysis) and body mass index: a 5-year follow-up study in a Belgian military population. Issue 1 (23rd February 2015) - Mullie, Patrick; Clarys, P
Abstract : Introduction: Increasing body mass index (BMI) has been related to many chronic diseases. Knowledge of nutritional determinants of BMI increase may be important to detect persons at risk. Methods: A longitudinal prospective study design was used in 805 Belgian soldiers. Daily nutrition was recorded with a validated food-frequency questionnaire. Weight and height were recorded from medical military data and principal component analysis was used to detect dietary patterns. Results: During the 5 years follow-up, mean BMI increased from 25.8 (±3.3) kg/m 2 to 27.1 (±3.6) kg/m 2 (p<0.05). Consequently, the prevalence of being overweight and obesity increased from 46.2% and 9.6% to 51.6% and 19.9% (p<0.05), respectively. Mean (SD) weight gain differed between the BMI categories at baseline with a respective weight gain of 3.8 (±3.1) kg for normal weight at baseline, 4.2 (±3.2) kg for overweight and 5.1 (±3.4) kg for obesity (p for trend <0.05). Three dietary patterns were detected by principal component analysis: Meat, Sweet and Healthy dietary pattern. In energy-unadjusted and adjusted linear regressions, no dietary pattern was associated with BMI increase. Conclusions: No specific dietary pattern was related to BMI increase. Prevention of obesity should focus on total energy intake at all BMI categories.