Health psychology and behavioral medicine · 2025
Within-week and within-year patterns in self-monitoring of dietary intake in adults with obesity participating in a behavioral weight loss program.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Ross Kathryn M, Swanson Taylor N, Arroyo Kelsey M, Shetty Armaan, Shankar Meena N, Krukowski Rebecca A
Аннотация
INTRODUCTION: Seasonal and within-week variation has been documented in relation to body weight change and self-weighing; however, less is known regarding how patterns of self-monitoring dietary intake vary over time.
METHODS: The current study conducted secondary data analysis from a larger weight management trial to examine within-week and within-year patterns of dietary self-monitoring in 446 adults with obesity (mean ± SD age = 49.5 ± 11.4 years, BMI = 35.7 ± 4.0 kg/m2) enrolled in a 16-week behavioral weight loss program (with start dates staggered throughout the year). Generalized mixed models were used to characterize within-week and within-year patterns in adherence to dietary self-monitoring and to examine potential moderators (i.e. age and gender).
RESULTS: There was significant variation in self-monitoring adherence and caloric intake across days of the week, ps < .001, with the lowest adherence and greatest intake observed on Thursdays through Sundays. Moreover, there was significant variation by calendar month, ps < .001, with the lowest adherence and highest intake in October, November, and December. Age moderated the associations between day of the week and caloric intake and between calendar month and self-monitoring adherence/caloric intake; gender moderated the associations between calendar month and self-monitoring adherence/caloric intake.
DISCUSSION: Results demonstrate differences in dietary self-monitoring adherence and caloric intake within-week and within-year, with effects moderated by age and gender. Taken together with research demonstrating that additional support may improve adherence to self-monitoring during high-risk times (e.g. holiday seasons), future research should replicate these findings and identify additional predictors of self-monitoring adherence, supporting the development of novel, individually- and contextually-adaptable interventions.
METHODS: The current study conducted secondary data analysis from a larger weight management trial to examine within-week and within-year patterns of dietary self-monitoring in 446 adults with obesity (mean ± SD age = 49.5 ± 11.4 years, BMI = 35.7 ± 4.0 kg/m2) enrolled in a 16-week behavioral weight loss program (with start dates staggered throughout the year). Generalized mixed models were used to characterize within-week and within-year patterns in adherence to dietary self-monitoring and to examine potential moderators (i.e. age and gender).
RESULTS: There was significant variation in self-monitoring adherence and caloric intake across days of the week, ps < .001, with the lowest adherence and greatest intake observed on Thursdays through Sundays. Moreover, there was significant variation by calendar month, ps < .001, with the lowest adherence and highest intake in October, November, and December. Age moderated the associations between day of the week and caloric intake and between calendar month and self-monitoring adherence/caloric intake; gender moderated the associations between calendar month and self-monitoring adherence/caloric intake.
DISCUSSION: Results demonstrate differences in dietary self-monitoring adherence and caloric intake within-week and within-year, with effects moderated by age and gender. Taken together with research demonstrating that additional support may improve adherence to self-monitoring during high-risk times (e.g. holiday seasons), future research should replicate these findings and identify additional predictors of self-monitoring adherence, supporting the development of novel, individually- and contextually-adaptable interventions.