Correlates of weight-related self-monitoring application use during emerging adulthood in a population-based sample

Hahn, Samantha L.; Hazzard, Vivienne M.; Larson, Nicole; Klein, Laura Cousino; Loth, Katie A.; Neumark‐Sztainer, Dianne

doi:10.1007/s40519-021-01349-4

Cited by 10 publications

(12 citation statements)

References 44 publications

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“…Among our more important results and reflective of Hahn, Hazzard, Larson, et al (2022) who reported that unhealthy weight-control behaviors predicted food and PA tracking in emerging adulthood, those with an eating disorder in this study were more likely to engage in self-monitoring behaviors. Because NDIT did not measure tracking behaviors prior to cycle 24, it is unclear whether tracking was a relatively new or a long-standing behavior at age 34.…”

Section: Discussionsupporting

confidence: 59%

“…Aligned with ( Hahn, Hazzard, Larson, et al, 2022 ; Hahn, Hazzard, Loth, et al, 2022 ; Hahn, Sonneville, et al, 2021 ), this study suggests that PA tracking is more prevalent than food tracking—37% of participants reported PA tracking, 14% reported food and 10.0% reported both. The predictors of tracking identified (i.e., diagnosis of an eating disorder, several weight-related indicators, PA, eating behaviors, body-related embarrassment, PA behavior regulation, sex, education, income, employment) are consistent with both previous research and theoretical tenets.…”

Section: Discussionmentioning

confidence: 65%

“…Briefly, in cross-sectional studies, correlates of both food and PA tracking reported to date for young adults include female sex, higher body mass index (BMI) ( Hahn, Sonneville, et al, 2021 ), unhealthy weight-control behaviors (i.e., fasting, using food substitutes, taking diet pills, purging), conventional weight-control behaviors, (i.e., increasing fruit and vegetable consumption, eating fewer high-fat foods and sweets), and conventional muscle-building behaviors (i.e., changes to eating or exercise to promote muscle growth; Hahn, Hazzard, Loth, et al, 2022 ). In a recent longitudinal study focused on weight- and muscle-related measures and behaviors, Hahn, Hazzard, Larson, et al (2022) identified predictors of food and PA tracking in a sample of college-age adults. After adjusting for sociodemographic variables, BMI ≥ 85th percentile during adolescence predicted food and PA tracking 8 years later.…”

Section: Introductionmentioning

confidence: 99%

“…After adjusting for sociodemographic variables, BMI ≥ 85th percentile during adolescence predicted food and PA tracking 8 years later. In further modeling that also adjusted for BMI, body dissatisfaction, unhealthy muscle-building behaviors (i.e., described by the authors of the study as use of protein powders, steroids, or other muscle-building substances), and conventional muscle-building behaviors in adolescence predicted both forms of tracking ( Hahn, Hazzard, Larson, et al, 2022 ). Apart from Hahn, Hazzard, Larson, et al (2022) , no other longitudinal studies have identified predictors of food and PA tracking behavior.…”

Section: Introductionmentioning

confidence: 99%

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Predictors of Food and Physical Activity Tracking Among Young Adults

et al. 2023

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Background: Monitoring food intake and physical activity (PA) using tracking applications may support behavior change. However, few longitudinal studies identify the characteristics of young adults who track their behavior, findings that could be useful in designing tracking-related interventions. Our objective was to identify predictors of past-year food and PA tracking among young adults. Methods: Data were available for 676 young adults participating in the ongoing longitudinal Nicotine Dependence in Teens Study. Potential predictors were measured in 2017–2020 at age 31, and past-year food and PA tracking were measured in 2021–2022 at age 34. Each potential predictor was studied in a separate multivariable logistic regression model controlling for age, sex, and educational attainment. Results: One third (37%) of participants reported past-year PA tracking; 14% reported past-year food, and 10% reported both. Nine and 11 of 41 potential predictors were associated with food and PA tracking, respectively. Compensatory behaviors after overeating, trying to lose weight, self-report overweight, reporting a wide variety of exercise behaviors, and pressure to lose weight predicted both food and PA tracking. Conclusion: Food and PA tracking are relatively common among young adults. If the associations observed herein between compensatory behavior after overeating and tracking (among other observed associations) are replicated and found to be causal, caution may need to be exercised in making “blanket” recommendations to track food intake and/or PA to all young adults seeking behavior change.

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Section: Discussionsupporting

confidence: 59%

Section: Discussionmentioning

confidence: 65%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Predictors of Food and Physical Activity Tracking Among Young Adults

et al. 2023

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“…Listed apps were reviewed by a research staff member and coded based on the purpose of the app and tracking focus; a second member of the research team then reviewed the codes to ensure accuracy. 40,41 Apps that automatically tracked physical activity (e.g., wearable devices) or were specific for physical activity/fitness were classified as physical activity-focused apps (e.g., Fitbit). Apps that tracked only diet or diet and physical activity, but with a primary focus on tracking diet (e.g., MyFitnessPal) were considered dietary-focused apps.…”

Section: Methodsmentioning

confidence: 99%

Weight-related Self-monitoring App Use Among Emerging Adults is Cross-sectionally Associated With Amount and Type of Physical Activity and Screen Time

Hahn,

Kramer-Kostecka,

Hazzard

et al. 2023

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Weight-related self-monitoring (WRSM) apps are often used by emerging adults to assist in behavior change. However, little is known about the relationship between WRSM among the general population of emerging adults and various physical activity and screen time behaviors. This paper examines associations between WRSM app use and various forms of physical activity and screen time among a population-based sample of emerging adults. Data come from EAT 2018 (N = 1,568, mean age = 22.0 ± 2.0 years), a population-based sample of emerging adults from Minneapolis/St. Paul, Minnesota. Participants reported on the types of WRSM apps used (physical activity and/or dietary focused), in addition to how much time they spent doing physical activity, whether they practiced yoga, compulsive exercise, recreational screen time, social media use, and whether they viewed dieting/weight loss materials. Linear and logistic regressions were used to assess adjusted means and prevalences of outcomes. We found that physical activity-focused WRSM app users engaged in more hours of total (8.7 vs 7.2, P < .001), and moderate-to-vigorous (5.1 vs 4.3, P = .002) physical activity compared to non-users. Similar results were found for dietary WRSM app users compared to non-users. However, WRSM app users had higher levels of compulsive exercise and were more likely to view dieting/weight loss materials ( Ps < .001). Findings suggest that although physical activity is higher among WRSM users, the types of physical activity and screen time behaviors WRSM users are engaging in may be harmful.

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Exploring longitudinal relationships between fitness tracking and disordered eating outcomes in college‐aged women

Berry,

Driscoll,

Fuller‐Tyszkiewicz

et al. 2024

Intl J Eating Disorders

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ObjectiveA growing body of research, primarily cross‐sectional, suggests a relationship between the practice of tracking one's food intake and exercise behaviors using fitness‐tracking smartphone applications (“apps”) or wearable devices (“wearables”) and disordered eating symptomatology. The aim of the present study was to explore longitudinal relationships between fitness tracking and disordered eating outcomes among college‐aged women, as well as to determine whether the individual‐level risk factors of pre‐existing eating concerns, perfectionism, and rumination about food moderated the relationship.MethodN = 68 female undergraduates used the MyFitnessPal app for 8 weeks while completing a series of self‐report measures.ResultsAt the trait level, fitness tracking frequency was positively associated with weight/shape concerns, but not with the other outcome measures. Daily levels of fitness tracking did not predict next‐day levels for any of the outcome measures. Within‐day fitness tracking at one timepoint was associated with lower reports of dietary restraint efforts at the next timepoint. None of the proposed moderators significantly interacted with the relationships over time.DiscussionThese results suggest that while those who engage in fitness tracking may experience higher weight/shape concerns as a trait, over time fitness tracking was not associated with an increase in concerns. Further work exploring whether fitness tracking may affect particular subgroups in different ways is warranted.

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Correlates of weight-related self-monitoring application use during emerging adulthood in a population-based sample

Cited by 10 publications

References 44 publications

Predictors of Food and Physical Activity Tracking Among Young Adults

Predictors of Food and Physical Activity Tracking Among Young Adults

Weight-related Self-monitoring App Use Among Emerging Adults is Cross-sectionally Associated With Amount and Type of Physical Activity and Screen Time

Exploring longitudinal relationships between fitness tracking and disordered eating outcomes in college‐aged women

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