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. Author manuscript; available in PMC: 2023 Feb 1.
Published in final edited form as: Prev Med. 2022 Jan 21;155:106967. doi: 10.1016/j.ypmed.2022.106967

Using apps to self-monitor diet and physical activity is linked to greater use of disordered eating behaviors among emerging adults

Samantha L Hahn a,b, Vivienne M Hazzard a,b,c, Katie A Loth d, Nicole Larson a, Laura Klein a, Dianne Neumark-Sztainer a
PMCID: PMC8832499  NIHMSID: NIHMS1774008  PMID: 35065981

Abstract

Use of weight-related self-monitoring (WRSM) apps is common among emerging adults, as are weight and shape concerns. The present study aimed to examine (1) whether emerging adult use of dietary-focused (e.g., MyFitnessPal) and physical activity-focused (e.g., Fitbit) WRSM apps was associated with weight-control and muscle-building behaviors, including commonly recommended/conventional behaviors and disordered behaviors and (2) whether prior use of weight-control and muscle-building behaviors in adolescence might explain such relationships. Data were collected as part of the EAT (Eating and Activity over Time) 2010–2018 study (n=1,446) and analyzed using gender-stratified logistic regression models adjusted for demographic characteristics and body mass index. Among women and men, physical activity- and dietary-focused app use were associated with greater adjusted prevalence of disordered weight-control behaviors (e.g., fasting, purging), and disordered muscle-building behaviors (e.g., using steroids). Physical activity- and dietary-focused app use were also associated with a higher adjusted prevalence of commonly recommended weight-control and conventional muscle-building behaviors (e.g., exercising, changing eating habits), but only among those who were also engaging in disordered behaviors. The observed associations remained statistically significant in models that further adjusted for adolescent use of the respective behaviors. Findings suggest that emerging adults who use physical activity- and dietary-focused WRSM apps are more likely to engage in disordered weight-control and muscle-building behaviors and that these associations are not explained by engagement in these behaviors during adolescence. Future research is needed to examine if there are aspects of WRSM apps that could be modified to reduce potential harm.

Keywords: Disordered eating, emerging adults, self-monitoring, weight-control, muscle-building, epidemiology, prevention

INTRODUCTION

Emerging adulthood often involves elevated weight and shape concerns and changes in eating patterns.1–3 In an effort to control their eating, weight, and/or shape, many emerging adults turn to weight-related self-monitoring (WRSM) smartphone applications or other technologies (apps). Popular WRSM apps, particularly physical activity- and dietary-focused apps such as FitBit and MyFitnessPal have accrued millions of users,4–7 and emerging adults represent the age group most likely to use WRSM apps.8,9 While WRSM apps reach millions of emerging adults looking to control their weight and shape each month, it is unknown what specific types of weight and shape control behaviors are being used by WRSM app users of the general emerging adult population.

Much of the research on WRSM app use has focused on populations seeking the support of a clinician to help them lose weight. Clinicians often recommend WRSM apps to assist patients in achieving their goals surrounding commonly recommended weight-control behaviors, such as increasing physical activity or eating more fruits and vegetables.10,11 In fact, clinical weight loss trials have shown that WRSM does lead to improvements in physical activity and dietary intake, and that WRSM apps lead to better adherence of self-monitoring than traditional forms of WRSM (e.g., pen and paper logs).12,13 However, little is known about how WRSM apps affect weight- and shape-control behaviors outside of clinical weight-loss interventions, which often include other components known to affect behavior change (e.g., social support, education).

Since WRSM apps are likely used outside of structured weight-loss interventions, it is important to understand whether individuals in the general population who use WRSM apps are also more likely to engage in commonly recommended weight-management behaviors, such as exercising and eating more fruits and vegetables. The limited research conducted outside of clinical weight-loss samples has focused on college students and shown that WRSM is associated with better dietary intake14,15 and higher motivation for exercise.16 However, it is unknown if these relationships hold true in more socioeconomically and racially/ethnically diverse samples of emerging adults. Additionally, existing studies have not examined the relationships between WRSM apps and dietary and activity behaviors performed explicitly for weight management. Examining weight-related health behaviors in the context of their motivations is important, as engaging in health behaviors for weight-related versus non-weight-related reasons can impact health-related outcomes.17

Understanding potential risk factors for disordered eating is important since disordered eating is associated with numerous negative outcomes, including decreased educational attainment,18,19 increased psychological distress,20 and increased likelihood of developing full syndrome eating disorders.21 It has been hypothesized that WRSM could lead to increased use of disordered behaviors aimed at weight/shape-control, 22,23 and there is evidence that WRSM app use leads to increased criticism, shame, or obsession with eating and weight that ultimately leads to disordered eating for some users.24 Prior research using online forums found that many users felt that their thoughts around meeting goals set by the apps are obsessive and felt shame when they did not meet specified goals.24 Research conducted among those with eating disorders found that many reported believing that using WRSM apps led to the development of their eating disorder.25,26 Cross-sectional associations between WRSM app use and disordered eating have also been observed among college students.22,27 However, the lack of longitudinal studies examining the relationships between WRSM app use and disordered eating limits our ability to understand if preexisting disordered eating helps explain the relationship between WRSM app use and disordered eating.

In addition, the existing literature examining relationships between WRSM app use and disordered eating has focused largely on disordered weight-control behaviors such as fasting and purging. Another concerning behavior of interest is disordered muscle-building behaviors, such as use of steroids, protein powders, and other muscle-building substances. Disordered muscle-building behaviors are common and have severe health consequences.28 Prior research has demonstrated that the relationships between WRSM and disordered eating differ by gender.27,29 Because muscle-building behaviors, including disordered muscle-building behaviors, are more common among men than women,30 there is a need for more examination of muscle-building behaviors in studies of men who use apps to monitor their weight-related behaviors.

WRSM apps are often promoted as healthy weight-management tools. However, prior research has demonstrated that many individuals who use recommended weight-control or conventional muscle-building behaviors are also using disordered forms of those behaviors.31 Therefore, it is important to disentangle the relationships between WRSM app use and the use of commonly recommended/conventional weight-control and muscle-building behaviors. Understanding the directionality of the relationship between WRSM and weight-control and muscle-building behaviors could impact future public health and clinical recommendations for WRSM. The objective of this study was to examine how WRSM app use is associated with a broad range of weight-control and muscle-building behaviors, in a diverse population-based sample of emerging adults. We hypothesized that WRSM app use would be associated with greater use of both recommended/conventional and disordered weight-control and muscle-building behaviors. However, we hypothesized that WRSM app use would be associated with lower likelihood of engaging in only commonly recommended behaviors and not disordered behaviors. We also hypothesized that dietary-focused app use would be more strongly associated with weight-control behaviors and physical activity-focused apps use would be more strongly associated with muscle-building behaviors. Further, we hypothesized that relationships would remain statistically significant after adjusting for adolescent use of the respective weight-control and muscle-building behaviors.

METHODS

Study Design and Sample Characteristics

Data were collected as part of EAT 2010–2018 (Eating and Activity over Time), a longitudinal population-based study (n=1,568) of eating and weight-related health among a diverse sample of young people from the Minneapolis/St. Paul, Minnesota area. Participants were recruited into the EAT 2010 study as middle and senior high school students from 20 local urban public schools during the 2009–2010 academic year (mean age=14.4±2.0 years) and completed follow-up (EAT 2018) surveys as emerging adults (mean age=22.0±2.0 years) eight years later. At EAT 2010, participants completed classroom surveys and had anthropometric measurements taken by trained staff. Participants were later invited to complete the EAT 2018 survey online or return a paper copy by mail. The analytic sample for the present study draws from the EAT 2010–2018 sample (n=1,568) and includes those who reported the same gender at both time points and were not missing data for analytic covariates (n=1,446). The University of Minnesota’s Institutional Review Board Human Subjects Committee approved all study protocols.

Inverse probability weighting (IPW) was used to account for attrition in all analyses as non-responders at follow-up were more likely to identify as Black, Indigenous or a person of color, male, and have parents with lower educational attainment. In longitudinal studies, IPW is the recommended methodology for handling missing data and minimizes response bias due to missing data, allowing for results to be extrapolated to the original EAT 2010 sample.32,33 Weights for IPW are the inverse estimated probability that an individual responded at both time points based on several participant characteristics collected in 2010, including ethnicity/race, socioeconomic status (SES), past year frequency of dieting, and weight status. After weighting, there were no differences between the EAT 2010 and EAT 2018 samples based on sociodemographic characteristics, dieting, or weight status (p>0.9). In the weighted analytic sample, 54% of participants were female, 28.4% identified as African American or Black, 20.3% as White, 20.0% as Asian American, 17.1% as Hispanic/Latinx, and 14.2% as mixed or other ethnicity/race. SES was based primarily on baseline parental educational attainment, with 38.9% of participants being low SES, 40.2% were of low-middle/middle SES, and 21.0% were of middle-high/high SES. The average body mass index (BMI) of the sample was 27.2 kg/m2 (standard deviation [SD]=7.0).

Measures

The EAT 2018 survey included items retained from the EAT 2010 survey, as well as additional items to address newly identified areas of interest.34–37 The EAT 2018 survey was pretested with three focus groups involving a separate sample of 29 emerging adults. Test-retest reliability of the measures in EAT 2018 were assessed in a subgroup of 112 emerging adult survey respondents.

Weight-Related Self-Monitoring (WRSM) App Use

The following open-ended question was used to assess WRSM app use, “Thinking about the mobile apps, tracker devices, and web-based programs you’ve used in the past year to help you manage your eating, activity or weight, please list up to 3 and tell us how often you currently use them.” Participants were able to write in up to 3 apps. For each app that was reported, participants were asked to rate how often they used that particular app with response options of “Never”, “Rarely”, “Sometimes”, and “Often”. Due to insufficient numbers to examine frequency of use, use was dichotomized based on any versus no use (test-retest agreement=87–94%). Written-in answers for WRSM apps were reviewed by research staff and coded based on the specific functionality of the mentioned app and codes were reviewed by a second coder. All apps which automatically tracked physical activity (i.e., wearables) or physical activity/fitness apps (i.e., for a specific workout) were classified as physical activity-focused apps. Dietary-focused apps included apps that tracked diet only or were designed to record both diet and physical activity, but did not automatically track physical activity (e.g., MyFitnessPal). Because individuals could report more than one app, physical activity-focused and dietary-focused app use were not mutually exclusive.

Weight-Control and Muscle-Building Behaviors

Disordered weight-control behaviors were assessed at both time points with the question, “Have you done any of the following things in order to lose weight or keep from gaining weight during the past year?”.38 Participants responded “yes” or “no” for the following behaviors: fasting, eating very little food, using a food substitute, skipping meals, smoking more cigarettes, taking diet pills, vomiting, abusing laxatives, and using diuretics. Use of one or more of the behaviors was the cut-point for creating a dichotomous variable to distinguish any versus no use of disordered weight-control behaviors (test-retest agreement=78%).

Recommended weight-control behaviors were assessed by asking about behaviors recommended by the Centers for Disease Control for weight management.39 At both time points, participants were asked the question, “How often have you done each of the following things in order to lose weight or keep from gaining weight during the past year?” Behaviors included exercising, eating more fruits and vegetables, eating less high-fat foods, and eating less sweets. The response options for each behavior were “never”, “rarely”, “sometimes” and “on a regular basis”. Those who reported any of the four behaviors regularly were considered to have engaged in recommended weight-control behaviors at the respective time points to be consistent with prior research (test-retest agreement=76%).31

Disordered muscle-building behaviors were assessed using an adapted question from previous studies, “Have you done any of the following things in order to increase your muscle size or tone during the past year?”40–42 The specific behaviors that were assessed at both time points included using protein powder or shakes (test-retest agreement=88.3%), steroids, another muscle-building substance, and using a pre-workout drink was assessed in 2018 only (test-retest agreement=88.3%). For each behavior, frequency responses ranged from “never” to “often” in 2010 and were assessed as yes/no in 2018. Participants who reported use of any of the assessed behaviors were considered positive for use in the dichotomized variable at each time point.

Conventional muscle-building behaviors were also assessed using the adapted question from previous studies, “Have you done any of the following things in order to increase your muscle size or tone during the past year?” 40–42 Behaviors assessed were changing eating (test-retest agreement=80.4%) and exercising more (test-retest agreement=82.7%). Use of both behaviors often was considered a positive response in 2010, and a ‘yes’ for both behaviors in 2018 was considered a positive response.

Statistical Analysis

Analyses were stratified by gender due to evidence that the relationships between WRSM and weight-control behaviors differ by gender in similarly aged samples.9,27 Univariate and bivariate statistics were calculated for all independent and dependent variables. To examine the relationships between use of WRSM apps and weight-control and muscle-building behaviors, we utilized logistic regressions adjusting for ethnicity/race, socioeconomic status, age, BMI, and educational/student status to obtain adjusted prevalence estimates of weight-control and muscle-building behaviors by each type of WRSM app use. Because of small cell sizes, we were not able to run separate regressions to independently examine those who used both forms of WRSM apps. Models were run with and without additional adjustment for adolescent use of the respective weight-control and muscle-building behavior. Because many individuals who engage in disordered weight-control behaviors also engage in recommended weight-control behaviors, we wanted to better understand whether WRSM apps were associated with only recommended/conventional behaviors. Therefore, we created a variables for both weight-control and muscle-building behaviors for which people were only considered positive if they engaged in recommended/conventional and not disordered behaviors.31 Cross-sectional models will allow us to understand whether users are more likely to use behaviors, whereas adjusting for adolescent levels of respective behaviors will begin to assist in understanding temporality of the relationships between WRSM app use and weight and muscle-related behaviors. Analyses were conducted using SAS version 9.4 and STATA 16. All results were considered statistically significant at p<.05.

RESULTS

Use of WRSM apps was common among both men and women (Table 1), but chi-square analyses comparing prevalence of WRSM app use by gender (1 degree of freedom, unweighted sample size of 1,446) showed that a higher percentage of women reported using both physical activity-focused and dietary-focused apps as compared to men. Nearly one quarter of women (23.6%) versus one sixth of men (16.5% Χ2=11.01, p<.001) used a physical activity-focused app. Dietary-focused apps were used by 12.8% of women versus 5.4% of men (Χ2=22.57, p<.001). More women (6.1%) than men (2.5%) reported using both physical activity- and dietary-focused WRSM apps (Χ2=10.62, p=.001), and fewer women (69.7%) than men (80.6%) reported using neither type of WRSM app (Χ2=22.24, p<.001). Women were also more likely than men to report using disordered weight-control behaviors (Χ2 [1, unweighted n=1,418]=13.21, p<.001), whereas men were more likely to report using disordered (Χ2 [1, unweighted n=1,411]=57.91, p<.001) and conventional muscle-building behaviors (Χ2 [1, unweighted n=1,427]=16.38, p<.001).

Table 1.

Prevalence of weight-related self-monitoring app use and weight-control and muscle-building behaviors in emerging adulthooda

Women (n=851) Men (n=595) p-value
Weight-Related Self-Monitoring App Use, % (n)
Physical Activity-Focused Apps 23.6 (206) 16.5 (102) <.001
Dietary-Focused Apps 12.8 (110) 5.4 (35) <.001
Both Physical Activity and Dietary-Focused Apps 6.1 (54) 2.5 (16) .001
Neither Physical Activity or Dietary-Focused 69.7 (589) 80.6 (474) <.001
Apps
Weight-Control and Muscle-Building Behaviors, % (n)
Weight-Control Behaviors - Disordered 57.5 (477) 47.7 (274) .003
Weight-Control Behaviors - Recommended 53.6 (448) 51.0 (294) .35
Weight-Control Behaviors - Recommended Onlyb 19.3 (162) 20.8 (119) .49
Muscle-Building Behaviors - Disordered 20.3 (169) 38.9 (225) <.001
Muscle-Building Behaviors - Conventional 37.3 (312) 51.5 (299) <.001
Muscle-Building Behaviors - Conventional Onlyc 25.2 (209) 21.1 (121) .08
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a

All statistics but n, which represents observed count, are weighted to account for attrition over time and allow for extrapolation to the original population-based sample. P-values represent results from chi-square analyses.

b

Prevalence of engaging in recommended weight-control behaviors, but not disordered weight-control behaviors.

c

Prevalence of engaging in conventional muscle-building behaviors, but not disordered muscle-building behaviors.

Among women, physical activity- and dietary-focused WRSM app use were associated with higher adjusted prevalence of both disordered and recommended weight-control behaviors, but not the use of only recommended weight-control behaviors (Table 2). Similarly for muscle-building behaviors, physical activity- and dietary-focused WRSM app use were associated with higher adjusted prevalence of disordered and conventional muscle-building behaviors, but not the use of only conventional muscle-building behaviors. In longitudinal analyses that adjusted for adolescent behaviors, all results remained significant with no meaningful changes in adjusted prevalences.

Table 2.

Adjusted prevalence estimates (%) of weight-control and muscle-building behaviors by weight-related self-monitoring (WRSM) app use in emerging adulthood among womena

Physical Activity-Focused
App Use 		Dietary-Focused
App Use
No Yes p No Yes p
Cross-Sectional Differences b
Weight-Control Behaviors - Disordered 54.6% 66.6% .003 55.3% 72.7% .001
Weight-Control Behaviors - Recommended 50.4% 63.8% .002 52.1% 63.8% .034
Weight-Control Behaviors - Recommended Onlyc 18.9% 20.5% .63 19.3% 18.7% .88
Muscle-Building Behaviors - Disordered 18.0% 27.3% .008 18.3% 33.0% .001
Muscle-Building Behaviors - Conventional 33.7% 48.8% < .001 34.5% 56.5% < .001
Muscle-Building Behaviors - Conventional Onlyd 23.8% 29.8% .11 24.2% 31.6% .13
Physical Activity-Focused
App Use 		Dietary-Focused
App Use
No Yes p No Yes p
Differences Adjusted for Behaviors During Adolescencee
Weight-Control Behaviors - Disordered 54.7% 66.6% .003 55.7% 71.3% .003
Weight-Control Behaviors - Recommended 51.0% 62.9% .006 52.3% 63.4% .040
Weight-Control Behaviors - Recommended Onlyc 19.1% 20.6% .65 19.5% 19.4% .99
Muscle-Building Behaviors - Disordered 17.9% 27.3% .007 18.3% 32.2% .002
Muscle-Building Behaviors - Conventional 34.1% 48.6% .001 34.9% 55.8% < .001
Muscle-Building Behaviors - Conventional Onlyd 23.8% 29.8% .11 24.2% 31.9% .11
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a

Percentage represents adjusted prevalence of disordered eating behavior by use of WRSM app use. For example, the adjusted prevalence of disordered weight control behaviors among individuals who did not use physical activity-focused apps is 54.6% compared to 66.6% for women who do use physical activity-focused app use.

b

Adjusted for age, race/ethnicity, educational/student status, socioeconomic status, and BMI.

c

Engagement in recommended weight-control behaviors, but not disordered weight-control behaviors.

d

Engagement in conventional muscle-building behaviors, but not disordered muscle-building behaviors.

e

Adjusted for age, race/ethnicity, educational/student status, socioeconomic status, BMI, and adolescent use of respective weight-control and muscle-building behavior.

Among men, cross-sectional analyses indicated that the adjusted prevalence of using disordered and recommended weight-control behaviors was higher among those who reported dietary-focused app use compared to those who did not use dietary-focused apps, but the use of only recommended weight-control behaviors was not associated with dietary-focused app use (Table 3). Further, dietary-focused app use was associated with higher adjusted prevalence of disordered and conventional muscle-building behaviors, but not the use of only conventional muscle-building behaviors. Physical activity-focused app use was also associated with higher adjusted prevalence of disordered weight-control behaviors and conventional muscle-building behaviors. Results remained relatively unchanged in longitudinal analyses adjusting for adolescent levels of the respective behaviors. However, in the longitudinal analyses the association between physical activity-focused app use and disordered muscle-building behaviors became significant (p=.04).

Table 3.

Adjusted prevalence estimates (%) of weight-control and muscle-building behaviors by weight-related self-monitoring (WRSM) app use in emerging adulthood among mena

Physical Activity-Focused
App Use 		Dietary-Focused
App Use
No Yes p No Yes p
Cross-Sectional Differencesb
Weight-Control Behaviors - Disordered 45.2% 60.7% .003 45.6% 82.1% < .001
Weight-Control Behaviors - Recommended 49.4% 59.4% .07 49.6% 76.6% .003
Weight-Control Behaviors - Recommended Onlyc 22.1% 13.6% .06 21.4% 10.0% .10
Muscle-Building Behaviors - Disordered 37.4% 46.2% .09 37.4% 65.0% .002
Muscle-Building Behaviors - Conventional 47.8% 70.2% < .001 50.0% 78.4% .002
Muscle-Building Behaviors - Conventional Onlyd 19.9% 27.3% .10 21.3% 18.0% .65
Physical Activity-Focused
App Use 		Dietary-Focused
App Use
No Yes p No Yes p
Differences Adjusted for Behaviors During Adolescencee
Weight-Control Behaviors - Disordered 45.5% 59.2% .01 45.9% 80.0% < .001
Weight-Control Behaviors - Recommended 49.5% 59.8% .06 49.8% 75.6% .005
Weight-Control Behaviors - Recommended Onlyc 22.3% 14.2% .08 21.6% 11.1% .16
Muscle-Building Behaviors - Disordered 37.9% 48.7% .04 38.1% 66.4% .002
Muscle-Building Behaviors - Conventional 48.0% 70.0% < .001 50.2% 77.4% .004
Muscle-Building Behaviors - Conventional Onlyd 20.0% 27.2% .11 21.4% 18.2% .66
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a

Percentage represents adjusted prevalence of disordered eating behavior by use of WRSM app use. For example, the adjusted prevalence of disordered weight control behaviors among individuals who did not use physical activity-focused apps is 45.2% compared to 60.7% for men who do use physical activity-focused app use.

b

Adjusted for age, race/ethnicity, educational/student status, socioeconomic status, and BMI.

c

Engagement in recommended weight-control behaviors, but not disordered weight-control behaviors.

d

Engagement in conventional muscle-building behaviors, but not disordered muscle-building behaviors.

e

Adjusted for age, race/ethnicity, educational/student status, socioeconomic status, BMI, and adolescent use of respective weight-control and muscle-building behavior.

DISCUSSION

The current study examined associations between WRSM app use and weight-control and muscle-building behaviors in emerging adulthood among an ethnically/racially and socioeconomically diverse, population-based sample. Among both men and women, physical activity- and dietary-focused app use were associated with higher adjusted prevalence of disordered weight-control and disordered muscle-building behaviors but were not associated with using only recommended weight-control or conventional muscle-building behaviors. Overall, results suggest a strong association between WRSM app use and the use of disordered eating behaviors, including disordered muscle-building behaviors among emerging adults. The cross-sectional relationships between WRSM app use and disordered eating in emerging adulthood were not explained by the adolescent levels of disordered eating, thereby suggesting that disordered eating may not proceed WRSM app use.

While cross-sectional relationships between physical activity- and dietary-focused self-monitoring and disordered eating have been documented among college students,9,22,43,44 this is the first study to our knowledge to show that these relationships also exist in a racially/ethnically and socioeconomically diverse population-based sample, including 59.3% who are not currently college students. The present study is also the first to our knowledge that has adjusted for engagement in disordered eating earlier in life when examining the relationships between WRSM and disordered eating. Our results are consistent with qualitative research that indicates that individuals who are suffering with eating disorders believe WRSM apps contributed to the development of their eating disorder.25,26 Our findings also provide some evidence contrary to the belief that WRSM apps may be a symptom rather than a risk factor for eating disorders.22 Therefore, until more is known about whether, and/or the degree to which WRSM app use increases eating disorder risk, caution should be taken when promoting WRSM apps so that their use does not inadvertently cause harm. Future research is also needed to identify if there are subpopulations for whom WRSM may be more harmful, as well as identify potential protective factors.

The present study also expands on existing knowledge of the relationships between WRSM and disordered muscle-building behaviors, as our results show that both physical activity- and dietary-focused app use are strongly associated with disordered muscle-building behaviors among men and women. There may be higher adjusted prevalences of disordered muscle-building behaviors among those who use dietary-focused apps compared to those who use physical activity-focused apps because of the types of behaviors encouraged by the respective app types. Specifically, physical activity-focused apps automatically monitor and encourage behaviors associated with cardiovascular health (e.g., number of steps, heart rate) rather than muscle-building exercises. In contrast, dietary-focused apps emphasize meeting nutrient goals, and individuals may use substances (e.g., protein powders) to meet nutrient goals for muscle-building. Future research is needed to determine if there are specific functions of dietary-focused WRSM apps that encourage disordered muscle-building behaviors. For example, it may be beneficial to examine whether certain app functions (e.g., app notifications/messages, goal settings), frequency of app use, and/or motivation for app use are associated with differential risk. Findings could then be used to inform WRSM app development and to make more specific recommendations on how to use WRSM apps in a manner that minimizes risk for disordered eating and muscle-building behaviors.

Interestingly, WRSM app use was only associated with recommended weight-control behaviors and conventional muscle-building behaviors for individuals who also engaged in disordered behaviors as well. Prior research has shown that forms of WRSM such as nutrition label use may be associated with healthier dietary intake and higher physical activity motivation.14,16,45 The present research suggests that among the general emerging adult population, the associations between WRSM and recommended weight-control behaviors may be driven by individuals who are also engaging in disordered weight-control or muscle-building behaviors. Future research should examine whether there are certain individual characteristics that distinguish WRSM users who engage in only recommended weight-control and conventional muscle-building behaviors from those who also engage in disordered weight-control or muscle-building behaviors.

A key strength of the study is the large population-based sample, which extends our understanding of the relationships between WRSM app use and weight-control and muscle-building behaviors among a racially/ethnically and socioeconomically diverse population-based sample of emerging adults. Further, the large sample size allowed us to examine gender-specific relationships. We were also able to examine muscle-building behaviors, which are more common among men, and less well described in the disordered eating literature. We utilized data from a longitudinal study of young people and were uniquely able to adjust for adolescent levels of weight-control and muscle-building behaviors. However, because WRSM app use was only assessed during emerging adulthood and there was an eight-year period between assessments, we were not able to fully disentangle the temporality of the relationships between WRSM app use and weight-control and muscle-building behaviors. Further, because we assessed apps used and not the content individuals tracked, we cannot be certain what specific behaviors they were monitoring on the apps. We also had to dichotomize WRSM app use due to insufficient numbers to examine frequency of use; future research should examine whether frequency of app use impacts associations. Additionally, while we were able to run analyses separately for women and men, we were unable to assess the relationships between WRSM app use and weight-control and muscle-building behaviors among gender minorities due to insufficient sample size (n=11). Results are also only applicable to emerging adults; future research is needed to understand if the same relationships exist in other populations that may be at lower risk for disordered eating, including older adults.

CONCLUSION

In a racially/ethnically and socioeconomically diverse population-based sample of emerging adults, WRSM app use was associated with higher adjusted prevalences of disordered weight-control and muscle-building behaviors. The observed associations were found to be independent of engagement in the same weight-control and muscle-building behaviors eight years earlier during adolescence. WRSM app users were not more likely than non-users to use only recommended weight-control or conventional muscle-building behaviors. Therefore, it is possible that WRSM app use increases risk for disordered eating but is unrelated to the use of recommended weight-management behaviors on their own when used by the general population of emerging adults. Public health and clinical professionals promoting WRSM apps as tools for weight management should consider all possible implications of their use by the general public, including the possibility of increasing risk for disordered eating. Future research is needed to investigate the complex temporal relationships between WRSM app use and disordered eating, and to further examine whether there are certain aspects of WRSM apps that may be particularly harmful.

Highlights.

  • Use of weight-related self-monitoring (WRSM) apps is common among emerging adults

  • WRSM app use is associated with increased likelihood of disordered eating (DE)

  • Prior DE does not explain relationships between WRSM and DE in emerging adulthood

  • WRSM app use is not related to using only recommended weight control behaviors

  • Future research needed to identify for whom WRSM may be helpful or harmful

FUNDING

This study was supported by the National Heart, Lung, and Blood Institute (Grant Numbers: R35HL139853 and R01HL127077, PI: D. Neumark-Sztainer). SLH and VMH’s time was funded by the National Institute of Mental Health (Grant Number: T32MH082761, PI: S. Crow). KAL’s time was funded by the National Institute of Child Health and Human Development (Grant Number: K23HD090324-02, PI: Katie Loth). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, and Blood Institute, the National Institute of Mental Health, the National Institute of Child Health and Human Development, or the National Institutes of Health.

ABBREVIATIONS

WRSM

Weight-related self-monitoring

Apps

smartphone applications/technologies

Footnotes

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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