Introduction

Consistent evidence suggests that Body Mass Index (BMI) is similar among friends [1–3]. There are three proposed mechanisms for how this greater similarity among friends arises. First, BMI may affect who one chooses to befriend [3–6]. Second, once friendships have developed, shared beliefs and activities might create convergences as behaviors increasingly mimic each other [3, 6]. Third, an indirect effect of shared environments or unobserved characteristics may result in similar BMIs [7, 8]. Determining how these three mechanisms contribute to observed similarities in BMI is challenging due to complex processes of friendship formation and change [7]. These mechanisms may co-occur and should thus be evaluated in light of one another.

The current study aims to determine if peer influence on BMI occurs among college roommates. In this study we examine how the BMI trajectory of first-year college students living on campus is associated with the baseline BMI of their roommate. College roommates are unique as they share a physical residence and inevitably spend some time together, but are not necessarily friends. While this current study does not propose specific mechanisms as to why peer influence on BMI occurs, it does present methods for ruling out two common confounders of social network studies—peer selection and environmental effects–and hence isolates influence as a mechanism.

College marks an important time and context to study peer influence on BMI for several reasons. Entering university is associated with weight increases [9] and US college populations are presenting with higher mean body weights than in the past [10]. First-year college students are at the start of the emerging adulthood period and typically have a much higher degree of autonomy than prior to starting college [11]. High school students are more likely to have an adult aware of their behaviors than college students [12]. While youth who have not yet started college may spend large amounts of time with peers, the ability to make decisions on weight-related behaviors (e.g., food choices, alcohol use, sleep patterns) while still living in their natal household may be limited [13–16]. It is suggested that high school students’ eat around four meals with their family each week [17]. In comparison, college students living away from home are limited in how many family meals they can share [18]. This difference in shared family meals suggests that, with the likely exception of lunch, adolescents will be less a part of their friends’ meals than are college students who live together. Moreover, as students transition from high school to college they tend to make less healthful choices, such as engaging in less physical activity, consuming less fruits and vegetables, and consuming more alcohol than when in high school [19, 20]. College students typically have less structured classroom time than adolescents in high school [21], resulting in greater flexibility in choosing what they do, and when, where, and how often they do it, than adolescents in high school. This provides the opportunity for learning not just behaviors, but how others organize their life and the priority various behaviors are given. Thus, we expect increasing opportunities for social learning as individuals move away from home for the first time.

While prior studies have identified a role for peer influence in many health and well-being outcomes [3, 6, 22–28], it can be difficult to disentangle peer influence from peer selection and environmental effects. We take two approaches to rule out these competing explanations. First, if college roommates are more similar than non-roommates, similarities in BMI trajectory may be due to pre-existing similarities that affected roommate choice, rather than peer influence. We overcome this confound by studying a sample of roommates who were randomly assigned. This strategy effectively rules out peer selection as the mechanism for any BMI similarities. Second is another main confounder of peer influence: shared environment. Roommates may be similar to each other due to spending time in the same environment. To test if roommate influence was due to a shared environment, we repeat our analysis, but with participants randomly paired to other participants who reside on the same (or nearby) floor. If we find evidence of similarity among randomly assigned floormates, then this suggests shared environment is responsible. But, if peer influence is not found when examining these pseudo-roommates then there is little evidence for a shared environment effect.

We study how roommates affect one another’s BMI trajectories using a sample of first-year college students living with randomly-assigned roommates in multi-story dormitories. Data were collected at four time points across an academic year, allowing us to test for change in BMI as our outcome. Unlike most prior studies that use self-reports of weight, we measure BMI. Self-reported weight tends to be under-reported at higher weights, and over-reported at lower weights [29, 30]. By using measured BMI these reporting errors are removed. The design of our study (i.e., random assignment) precludes selection as a source of similarity in BMI among roommate pairs, whereas our floormate analysis evaluates shared environment, allowing us to offer an innovative analysis of peer influence among college students. Moreover, by focusing on college roommates, and not high-school friends, we offer a test of peer influence occurring later in the life course and within a relatively underexplored type of relationship.

Background

Numerous studies have shown that friends' BMI converges over time [3, 6, 22], and researchers have proposed several explanations for this convergence based on peer influence. One set of explanations focuses on what is spreading when influence occurs. Studies have suggested that convergence on BMI occurs indirectly because of peer influence on weight-related behaviors [31, 32]. For example, convergence of physical activity [3, 6], screen time [6, 25], disordered eating [23], food choices [24, 25], alcohol consumption [26], weight control behaviors [27], and sleep patterns [28] has been observed among friends. While these studies all showed peer influence on weight-related behaviors, only Simpkins tested if peer influence on weight-related behaviors was responsible for similarity in BMI among peers. Simpkins et al. examined if convergence of physical activity levels explained the convergence of BMI among adolescents, after controlling for selection effects [3]. While Simpkins reported peer influence for both BMI and physical activity, there was no evidence the similarity in BMI was due to the similarity in physical activity [3]. Another study examining peer influence among college students suggested that while friends tend to have similar meal consumption patterns, fruit and vegetable intake, alcohol intake, sleep behaviors, and stress levels, only dining hall use and stress levels were also associated with BMI change; hence, only dining hall use and stress levels had the potential to explain why friends BMI tends to be similar [33]. Alternatively, it may be the case that norms, not behaviors, spread through social networks and these lead to convergence in weight [1, 34]. For instance, friends may influence the perception of what a 'socially acceptable' weight is, indirectly resulting in weight change [32].

The second set of social influence theories focus on the question of how influence on weight occurs. This is important because the processes related to influence may play out differently depending upon the type of relationship in question or life cycle stage. Much research on peer influence has focused on friendship or other affective relationships and proposed that processes such as social learning [35] are responsible. For instance, prior studies suggest that learning from media figures may result in children spending more time exercising [36], learning from coworkers may be associated with smoking behaviors and BMI [37], and family and friend support may be associated with physical activity levels [38].

Peer influence via social learning requires that individuals observe others’ behaviors that are salient to the outcome. In regards to weight-related behaviors, the capacity to observe others can differ markedly for friends vs. roommates. Namely, roommates may see the kinds of food each other brings to the room and observe workout, eating, and sleeping schedules. Additionally, given the shared living space, roommates may observe each other during periods when withdrawal from friendship networks is expected to occur, such as periods of depression [39]. For students who tend to avoid social situations, such as students with social anxiety [40], the extent of roommate observation may be higher than other peer observation. If a friendship develops then roommates may also shop and eat together. While friends may observe and participate in some of these activities, friends who do not live together do not have the capacity to directly monitor one another’s behavior at the same intensity as do roommates. Even if a friendship per se does not develop among roommates, they still have greater access to one another’s “backstage” selves, compared to the “frontstage” selves that individuals present to their friends and acquaintances [41].

Peer influence via social learning also requires that individuals remember, and later reproduce, others’ behaviors [42]. Compared to friends, roommates may be optimally placed to learn behaviors from each other. Roommates may spend much of their time together while engaged in routine activities (e.g., morning and evening routines) which can be highly repetitive. The repetitiveness of roommates interactions may result in behaviors which would typically go unnoticed being remembered, and reproduced. In comparison, if friends engage in a wider variety of shared activities it may be harder to notice, remember, and reproduce each other’s behaviors.

In contrast to social influence explanations, friends may have similar weight because people tend to select friends who are already similar to themselves (i.e., homophilous selection) [3–6]. Friendships may form on the basis of body size, with homophily arising directly via selection into friendships based on similar weight status. Homophilous selection may also occur at a genetic level, with people who have similar biological characteristics more likely to become friends [43, 44]. Given that some people may be more susceptible to obesity than others due to genetics [45, 46], such selection could result in similarity in BMI among friends.

Friends may also have similar BMIs due to not being selected into friendships by others with a higher or lower BMI. Systematic studies show discrimination against individuals with very high BMI [47]. The stigma of obesity may decrease friendship opportunities for individuals who are overweight/obese [4, 5]. As a consequence, individuals categorized as overweight or obese may turn to one another for friendship, resulting in similarities in BMI among friendship groups. Similarly, friendship discrimination may occur among those who are underweight [22].

The third explanation for weight similarities among friends is shared environment. Geographic location has been associated with friendships, with those living closer together more likely to be friends [48]. Similarities in BMI have been observed with people living in the same zip code [49] and county [50]. Thus, both friendships and BMI are spatially clustered. As a consequence, friends’ BMI may converge because living in close geographic proximity provides common opportunities for physical activity and food consumption. Aspects of the environment that might lead to converging BMI include built environments (e.g. parks, walkable neighborhoods) that encourage or discourage physical activity [51–53] and the availability of different kinds of food outlets [54, 55]. Thus, when friends reside in the same environment, their BMI may converge over time due to exposure to a common environment rather than any direct influence between friends. This possibility is particularly salient for roommates who share a residence during the academic year.

Given the aforementioned issues, concern has been raised about whether it is influence via friendship ties or other mechanisms that explain the BMI convergence observed in social network studies [7, 8]. Causal inference regarding peer influence is complicated by the fact that homophily based on BMI among friends can arise through multiple mechanisms. To overcome this concern, one approach has been to statistically control for selection into friendships when examining BMI change such as by using stochastic actor-oriented models (SAOMs) to simultaneously examine selection and influence. Following this approach, researchers have found influence on BMI among high-school students [3, 6] and university students (Bruening et al. 2018) while controlling for selection into friendships based on similarity in BMI. Together, these studies offer compelling evidence for peer influence, but nonetheless, make the strong assumption that all confounding environmental factors are specified in the model.

A second approach to overcoming concerns about selection has been to use an experimental design. By randomly assigning individuals to a relationship, selection effects are effectively removed. This is important given that peer selection is a major confounder in observational studies of peer influence—it is difficult to fully control for all of the variables (some unobservable) which may result in peers choosing to be friends or not. When participants are randomly assigned to each other, relevant confounders and omitted variables that might exert influence on friend selection are eliminated and the only mechanisms that can systematically create similarities among them are peer influence and environmental effects. It is not often that researchers can randomly assign people to long-term relationships. However, the random assignment of first-year student roommates practiced by some universities offers a suitable natural experiment. Research using randomized first-year college student roommates has shown roommates influence each other’s verbal SAT scores [56], and grade point average [57]. To our knowledge, only two studies have examined the association of randomly assigned roommate BMI and participant BMI change. The first study, conducted among female students at a private Midwestern university, found no effects of roommate BMI on participant BMI trajectories, and a negative association between a participant's weight change and their roommate's weight (i.e. they concluded that first-year students randomly assigned to a heavier roommate, gained less weight over the academic year) [58]. The second study included males and females from a large private and a large public university; this revealed a positive association between participant’s weight change and their roommate’s weight for females, but not males [59]. It is unclear why these studies produced mixed findings. One reason may be due to the calculation of BMI using self-reported weight and height which can lead to measurement error [29] and make it more difficult to detect the effects of peer influence. Additionally, some of the students in one of the studies had more than one roommate, which may complicate roommate influence [59].

Given findings contrary to predictions derived from the broader literature on friendship and BMI change, a more detailed study is warranted. We replicate the quasi-experimental approach in prior studies, but with several improvements. We recruit a more diverse student population, have better follow-up over the course of the year (i.e., up to four observations per participant), only include participants with roommates in the study, and only include roommates in double occupancy rooms (there were no triple- or quad- occupancy rooms available). We also measure anthropometrics directly, rather than relying on self-reports of height and weight to calculate BMI. Given a prior roommate study examining weight change found peer influence for females but not males [59], we include both males and females. Sex differences in several weight-related factors exist. For instance, normal weight women are more likely to believe they are overweight than normal weight men [60], and women are more likely to engage in weight loss than men [60, 61]. There are indications that peer influence may be sex-specific [59, 62–65]. Lastly, we develop an analytic method to rule out shared environment as a competing explanation, resulting in an even stronger study design than used previously.

Methods

Results

A total of 150 participants residing in 75 shared rooms met inclusion criteria 1 to 5 (Fig 1). There were 32 participants (16 shared rooms) excluded from the analysis as they did not meet the sixth inclusion criteria (no evidence of prior friendship), indicating that their roommate assignment may not have been random. An additional 14 participants (7 shared rooms) were removed from the analyses as these participants did not remain roommates throughout the academic year, potentially limiting influence effects (inclusion criteria seven). There was no evidence that the remaining 104 participants (81% female, 45% non-Hispanic White; Table 1) residing in 52 shared rooms, were friends prior to meeting each other on campus or changed roommates during the year. The majority (73%; 76/104) of the 104 participants reported their roommate as a friend, and stated that they met their roommate on campus. The remaining 27% (28/104) of participants did not nominate their roommate as a friend; how these roommates met is unknown. Compared to the students who were not included in the roommate analysis, the 104 students included in the roommate analysis were more likely to be female (P = 0.001) and from campus A (P<0.001), which reflects the higher participation rates of females and students from campus A (Table 1). No difference by race/ethnicity (P = 0.570), Pell Grant status (0.064), or BMI (0.414) was observed between the students who were included, or excluded from the roommate analysis. Participants with missing socio-demographic data, and participants without a measured baseline and Spring BMI, were omitted from the analysis. No imputation procedures were completed. Monte Carlo permutation results showed that the roommates were no more similar than floormates by Pell Grant status (P = 0.576), weight status (P = 0.460), or baseline BMI (P = 0.060). However, roommates were more likely to both be non-Hispanic White than floormates were (P = 0.048). The correlation of participant and roommate baseline BMI was 0.11, while the correlation of participant and floormate baseline BMI ranged between -0.17 and 0.38 (Fig 2). There were 70 students in the roommate analysis with complete data, 25 students with missing data at one time point, and 9 students with missing data at two time points. Two students had an unknown BMI at T2, 5 students had an unknown BMI at T3, and 18 students had an unknown BMI at T4. An additional 6 students had unknown BMI for T2 and T4, and 3 students had an unknown BMI for T3 and T4. No differences in gender (P = 1.000), race/ethnicity (P = 0.634), Pell Grant status (P = 0.198), or BMI (P = 0.468) between the students in the roommate analysis with complete versus incomplete data were found.

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Fig 1. Flow chart of total study population and final analytical sample.

https://doi.org/10.1371/journal.pone.0242681.g001

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Fig 2. Correlation of participant and roommate, and participant and floormate, BMI at Time 1.

https://doi.org/10.1371/journal.pone.0242681.g002

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Table 1. Key demographics of the first-year college students’ who were included, and excluded, from the roommate analysis.

https://doi.org/10.1371/journal.pone.0242681.t001

The linear mixed model showed student baseline BMI strongly predicted their BMI in later waves (β = 0.98, 95% CI = 0.93, 1.02; Table 2). Consistent with roommate influence, roommate baseline BMI significantly modified participant’s BMI trajectory over the school year (T2-T4), as indicated by a significant interaction between time and roommate BMI (β = 0.06; 95% CI = 0.02, 0.10). The model suggests that a participant with a baseline BMI of 25, and with a roommate with BMI of 20 would be expected to decrease 0.04 kg/m² between T2 and T4, while a participant with a baseline BMI of 25 and with a roommate with BMI of 30 would be expected to increase 0.53 kg/m² between T2 and T4 (Fig 3). These changes in BMI correspond to a 1.75m (5'7") participant with a T1 BMI of 25 losing 0.1 kg (0.2 lb), or gaining 1.6 kg (3.6 lb), between T2 and T4.

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Fig 3. Predicted BMI trajectory over the academic year for a non-Hispanic White female participant whose baseline BMI was 25 by roommate BMI.

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Table 2. The association of participant BMI change at a large southwestern university over the 2015–2016 academic year and roommate baseline BMI (n = 104).

https://doi.org/10.1371/journal.pone.0242681.t002

When time interactions for campus and sex were included in the model, the results did not change; time interactions for campus and sex were not significant (P = 0.224 and P = 0.401; S1 Table). Further, when residence hall, rather than campus, was included as a predictor in the models the results were consistent (S2 Table).

When roommate weight status was included in the model instead of roommate BMI, participant BMI trajectory remained significantly predicted by roommates’ weight status (β = 0.49, 95% CI = 0.12, 0.85; S3 Table). This suggests a participant with a baseline BMI of 25 with a non-overweight/obese roommate would be expected to increase 0.03 kg/m² between T2 and T4. A participant with a baseline BMI of 25 and with an overweight/obese roommate would be expected to increase 0.51 kg/m² between T2 and T4.

When participant T1 to T4 BMI was predicted by their roommate BMI, participant BMI was significantly associated with roommate baseline BMI (β = -0.98, 95% CI = -1.03, -0.94) and the interaction between roommate baseline BMI and time was significant (ß = 0.08, 95% CI = 0.03, 0.13; S4 Table). This suggests that participants assigned to a roommate with a higher BMI had a lower initial BMI, but gained more weight between T1 and T4.

When participant weight was predicted by their roommate weight, the interaction between roommate weight and time was significant (ß = 0.04, 95% CI = 0.01, 0.07; S5 Table). This model suggests that a participant with a baseline weight of 65 would be expected to lose 0.1 kg between T2 and T4 if assigned to a roommate with a weight of 50 kg, and gain 1.1 kg between T2 and T4 if assigned to a roommate with a weight of 80 kg.

When the models were stratified by sex, roommate baseline BMI was significantly associated with the BMI trajectory of females (n = 84, ß = 0.06, 95% CI = 0.01, 0.10; S6 Table) but not males (n = 20, ß = 0.05, 95% CI = -0.06, 0.17; S7 Table). While this effect was not “significant” for males, the beta estimate of 0.05 was consistent with that found in the other models.

When examining the Fall and Spring semesters separately, the estimated effects of roommate BMI on participant BMI were a similar magnitude to the effect for the full-year analyses (Fall: n = 93, ß = 0.04, 95% CI = 0.00, 0.08, S8 Table; Spring: n = 68, ß = 0.06, 95% CI = 0.02, 0.10, S9 Table). The effect was significant for the Spring, but not for the Fall.

The final model evaluates the possibility that shared environment could have been responsible for the above findings indicative of roommate influence. When the 104 floormate pairs were examined, no association was found between participant BMI trajectory and participant baseline BMI (β = 0.01, 95% CI = 0.00, 0.02) or their floormate baseline BMI (β = -0.01, 95% CI = -0.04, 0.03; S10 Table). The near-zero, non-significant estimate for floormate BMI suggests that being on the same floor was not sufficient to produce the pattern of peer influence we observe.

Discussion

This study examined roommate influence on body mass index (BMI) change using a natural experiment of randomly assigned roommates combined with an innovative floormate analysis to rule out selection or shared environment as competing explanations. The findings suggest that first-year college students’ weight trajectories are influenced by the weight status of their randomly assigned roommate. For every 5 kg/m² greater baseline BMI of a roommate at the start of the Fall 2015 semester, a participant would be expected to gain an additional 0.3 kg/m² between the end of the Fall 2015 and the end of the Spring 2016 semesters. While the magnitude of the effect is modest, considered at the population level, these results could have significant impacts on weight patterning. These findings also suggest that the similarity observed among friends cannot be attributed solely to selection of friends based on BMI or other unmeasured variables. Controlling for clustering by campus, combined with null results in the floormate analysis, helps to rule out shared environment as an alternative explanation. Finally, as pre-existing friendships were excluded from the study, this study indicates that peer influence on BMI may occur via proximity mechanisms, rather than longer term friendship selection mechanisms.

In light of these findings, it is worth reflecting more deeply on the nature of peer influence within roommate relationships in particular. Although we find evidence of peer influence among roommates, the mechanisms by which roommates influence each other’s weight trajectories are not yet well understood. One prior study finds that the extent of shared activities among first-year college roommates decreases throughout the first academic year [73], which may suggest that less time is spent with roommates after more ‘desirable’ friendships are formed later in the semester. While roommates may not be first-year college students’ most desirable friends, they are required to live together. Compared to friends, roommates may be more likely to observe each other’s morning and evening routines. Peer influence via mechanisms such as sleep routines, night eating, screen time, and breakfast eating may be more relevant for roommates than friends. Students may also spend time with their roommate when doing less social activities (e.g., studying, sleeping), and spend time with friends for social activities (e.g., eating, socializing). As such, friends may see “frontstage” activities (such as alcohol intake at a party) while roommates may see the more typical “backstage” activities (such as daily alcohol intake). The mechanisms for BMI influence among roommates and friends may be different given these expected differences in shared activities among roommates and friends. Notably, even within friendships, which are far more often the focus of inquiry, the mechanisms by which friends influence each other’s weight trajectories are still unclear. Thus, additional research on the mechanisms behind peer influence among both roommates and friends is warranted, particularly with an eye toward differences in relational properties that shape which mechanisms are activated.

While this study examined students, roommates are also prevalent outside of the college context. The prevalence of a roommate living arrangement is greatest among 18–24 year-olds with some college education who are continuing their education, however roommates among adults outside this age range are also common [74, 75], including among retirees [76]. While we would anticipate peer influence among other (non-college) roommates, the lack of random assignment makes parsing out selection and influence effects more difficult for roommates in other environments. Thus, other research designs may be needed to understand influence among non-randomly assigned roommates.

Weight discrimination may also partially explain our findings. Students who experience weight discrimination may gain more weight than their counterparts for many reasons [77]. For instance, weight discrimination is associated with unhealthy weight control behaviors [78], higher caloric consumption [79], and less exercise [79]. It may be that when a participant's roommate experiences weight discrimination, the roommate and the participant engage in unhealthy weight-related behaviors. Minimizing weight discrimination and encouraging self-acceptance may be effective at minimizing weight gain for those at higher BMIs, and their roommates.

Regarding females, our findings align with Yakusheva et al. (2014), who also reported an association between participant and roommate weight among females. Our sample size for males was too small to be certain that the non-significant association for male BMI trajectory was due to a true null effect (as reported by Yakusheva et al. (2014) [59]) or not. One study which examined friendship networks (rather than roommates) found null results when testing if sex affects susceptibility to peer influence on BMI [3]. Given sex differences in weight-related behaviors, it is plausible that peer influence is indeed sex-specific in some circumstances. For instance, feeling or experiencing weight discrimination is more prevalent among females than males [80] and female college students are more likely to overestimate their BMI and try to lose weight than males [81]. The amount of weight gained over college may also differ by sex. Some studies suggest that males have a greater increase in BMI than females during the four years of college [82, 83], however other studies suggest that the extent of weight gain over the first year of college is similar among males and females [84–87]. As such it remains unclear if the effect of roommate influence on BMI is sex-specific as suggested by Yakusheva, or not. Additional research is needed in this regard, and with particular attention to relationship type (e.g., friends, roommates, and other types of relationships).

Our study documented influence among first-year university students. The overall findings from this study are consistent with a prior roommate study [59] and other social network studies related to weight [3, 6]. Given accumulating evidence that roommates influence each other's weight trajectories, interventions encouraging healthful lifestyles at the roommate level may be worth considering. It would be useful to determine how roommates influence each other's BMI trajectories over longer periods of time. In particular, universities which provide on-campus housing to students until graduation could follow randomized roommate pairs to determine if the influence effect observed during the first year of university remains until graduation. This study shows that those in close proximity, who are not necessarily friends, influence each other’s BMI change. This study showed no BMI influence among less proximate individuals (floormates), indicating a certain ‘closeness’ is necessary for influence to occur. Increased knowledge of the mechanisms by which proximate individuals influence each other would not only be helpful for preventing obesity, but could potentially be applied to develop interventions encouraging healthful behaviors for other populations who spend time in close proximity (e.g., office co-workers, active members of faith-based communities).

Conclusion

We found roommates significantly influenced each other’s weight change over time. These findings provide evidence that one’s associates have an independent and potentially important influence on weight change.

Supporting information

Acknowledgments

The authors would like to thank the devilSPARC research team for their assistance in collecting the data, and the students participating in this study.