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Clinical Anthropometrics and Body Composition from 3-Dimensional Optical Imaging
Published on: June 7, 2024
Association between chrononutrition behaviours, anthropometric measurements and body composition in adults with
Guey Yong Chong1,2,3, Satvinder Kaur4, Ruzita Abd Talib5,6
1Faculty of Applied Sciences, Tunku Abdul Rahman University of Management and Technology, Setapak, Malaysia.
Abstract:
Delayed eating is associated with a higher risk of overweight and obesity in the general population, but its relationship with anthropometric measurements and body composition in individuals with prediabetes remains unclear. This study investigated the association between chrononutrition behaviours, anthropometric measurements and body composition in adults with prediabetes. This prospective longitudinal study enrolled 120 participants aged 54 ±15 years, who received standard care at healthcare clinics. Socio-demographic data were collected via an interviewer-administered questionnaire. Anthropometric measurements, body composition metrics and chrononutrition behaviours (assessed with the Malay-translated Chrononutrition Profile Questionnaire) were assessed at baseline and 6 months. Multiple linear regression analyses with adjustment for confounders were conducted. A later last meal was associated with higher body weight (β: 0·68 kg, 95 % CI: 0·31, 1·04) and larger waist circumference (β: 1·38 cm, 95 % CI: 0·57, 2·19). Each hour deviation from eating beyond the 07.00-19.00 time window corresponded to an increase in body weight of 1·41 kg (95 % CI: 0·05, 2·77). Increasing frequency of nighttime snacking was associated with higher BMI (β: 1·61 kg/m2, 95 % CI: 0·43, 2·79). Delaying last meal timing (β: 0·44 %, 95 % CI: 0·14, 0·74) and deviating from solar time were associated with higher body fat percentage (β: 1·36 %, 95 % CI: 0·30, 2·42), while increasing frequency of breakfast skipping was associated with lower muscle mass (β: -0·31 kg, 95 % CI: -0·56, 0·07). These findings highlight the importance of chrononutrition behaviours in influencing anthropometric and body composition outcomes, supporting targeted interventions on meal timing in prediabetes management.
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