Higher Energy Intake Variability as Predisposition to Obesity: Novel Approach Using Interquartile Range

• Published in: Central European journal of public health Vol. 25; no. 4; pp. 321 - 325
• Main Authors: Forejt, Martin, Derflerová Brázdová, Zuzana, Novák, Jan, Zlámal, Filip, Forbelská, Marie, Bienert, Petr, Mořkovská, Petra, Zavřelová, Miroslava, Pohořalá, Aneta, Jurášková, Miluše, Salah, Nabil, Bienertová-Vašků, Julie
• Format: Journal Article
• Language: English
• Published: Czech Republic National Institute of Public Health 01.12.2017
• Subjects: Adolescent; Adult; Aged; Anthropometry; Appetite; Body composition; Body fat; Body Mass Index; Body size; Czech Republic - epidemiology; Diet - methods; Diet - statistics & numerical data; Diet Records; Energy; Energy distribution; Energy Intake; Energy measurement; Female; Food; Hip; Human subjects; Humans; Male; Meals; Metabolism; Middle Aged; Obesity; Obesity - epidemiology; Regression analysis; Studies; Waist Circumference; Waist-Hip Ratio - statistics & numerical data; Weight control; Women; Young Adult; Czech Republic; energy intake; energy distribution; interquartile range; variability; anthropometry; obesity
• ISSN: 1210-7778; 1803-1048
• DOI: 10.21101/cejph.a4451

It is known that total energy intake and its distribution during the day influences human anthropometric characteristics. However, possible association between variability in total energy intake and obesity has thus far remained unexamined. This study was designed to establish the influence of energy intake variability of each daily meal on the anthropometric characteristics of obesity. A total of 521 individuals of Czech Caucasian origin aged 16–73 years (390 women and 131 men) were included in the study, 7-day food records were completed by all study subjects and selected anthropometric characteristics were measured. The interquartile range (IQR) of energy intake was assessed individually for each meal of the day (as a marker of energy intake variability) and subsequently correlated with body mass index (BMI), body fat percentage (%BF), waist-hip ratio (WHR), and waist circumference (cW). Four distinct models were created using multiple logistic regression analysis and backward stepwise logistic regression. The most precise results, based on the area under the curve (AUC), were observed in case of the %BF model (AUC=0.895) and cW model (AUC=0.839). According to the %BF model, age (p<0.001) and IQR-lunch (p<0.05) seem to play an important prediction role for obesity. Likewise, according to the cW model, age (p<0.001), IQR-breakfast (p<0.05) and IQR-dinner (p <0.05) predispose patients to the development of obesity. The results of our study show that higher variability in the energy intake of key daily meals may increase the likelihood of obesity development. Based on the obtained results, it is necessary to emphasize the regularity in meals intake for maintaining proper body composition.