Emerging Adulthood, Emergent Health Lifestyles: Sociodemographic Determinants of Trajectories of Smoking, Binge Drinking, Obesity, and Sedentary Behavior

Daw, Jonathan; Margolis, Rachel; Wright, Laura

doi:10.1177/0022146517702421

Cited by 98 publications

(102 citation statements)

References 55 publications

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“…Drawing on the same example, 25% of Jefferson and 29% Sunshine students changed their sleep status (either from getting enough to not enough or from not enough to enough) between the waves. These behavioral and lifestyle changes are consistent with prior literature (Daw et al 2017). Importantly, the contextual composition of the classes remained relatively robust to these underlying individual changes.…”

Section: Figure 2 Class-conditional Response Probabilities From Lcasupporting

confidence: 88%

“…Descriptively, our LCA-identified health lifestyles showed similar patterns to previous work using Add Health (Burdette et al 2017, Daw et al 2017, Lawrence et al 2017. The nature of our classes (healthy, unhealthy, mixed) and the composition of our mixed classes were somewhat similar to Burdette et al (2017).…”

Section: Discussionsupporting

confidence: 75%

“…Our analyses proceeded in two primary steps which separately estimate health lifestyles, then model network dynamics for those health lifestyles. First, we used Latent Class Analysis (LCA, McCutcheon 1987, Vermut andMagidson 2002) to estimate health lifestyles using various health behavior inputs (Daw et al 2017, Lawrence et al 2017. We selected health indicators representing the broad range of behavioral domains previously identified as key to defining health lifestyles among adolescents (Burdette et al 2017, Cockerham 2005, Daw et al 2017, Mollborn et al 2014a).…”

Section: Identifying Health Lifestyles With Lcamentioning

confidence: 99%

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Peer Network Processes in Adolescents' Health Lifestyles

Adams¹,

Lawrence²,

Goode³

et al. 2020

Preprint

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Group-based lifestyles offer individuals a lens for making behavioral decisions. But how do lifestyles arise and change? We propose that friendship networks shape lifestyles, while simultaneously being a product of lifestyles. Combining theories of health lifestylesinterrelated health behaviors arising from group-based identities-with network and behavior change, we examined influence and selection processes between friendship networks and health lifestyles. We analyzed two high schools with longitudinal, complete friendship network data from the National Longitudinal Study of Adolescent to Adult Health. Latent class analyses characterized each school's predominant health lifestyles based on several health behavior domains. School-specific stochastic actor-based models (SABMs) evaluated the bidirectional relationship between friendship networks and health lifestyles. Predominant lifestyles remained stable within schools over time, even as individuals transitioned between lifestyles. In both schools, friends displayed more similarity in health lifestyles than other peers, and this similarity resulted primarily from selection, but also from influence processes. Friends exhibit remarkable similarity on a range of characteristics. Research demonstrates this "network assortativity" on characteristics ranging from specific health behaviors like smoking (Haas and Schefer 2014), physical activity (de la Haye, et al. 2011), or alcohol and other substance use (Kirke 2004); to attitudes including political (Bond et al. 2012), and religious beliefs (adams, Schaefer, and Ettekal 2020); to statuses that animate key aspects of sociological research-gender (Kandel 1978), race (Moody 2001), and occupational roles (Chen and Volker 2016). Beyond documenting the ubiquity of these patterns, network research aims to theoretically and empirically disentangle the causal processes responsible for observed assortativity (McPherson, Smith-Lovin, and Cook 2001). Frequently, this entails separating processes of peer influence (people adopting the behaviors of their friends) from homophilous selection (choosing friends with similar behaviors; Steglich, Snijders, and Pearson 2010).Here, we raise a new question regarding the basis of network assortativity: What is the nature of the characteristics that matter for how should we conceptualize the characteristics that provide the basis of network influence and selection? Network scholarship has largely focused on accounting for network similarity one attribute at a time. For example, how do our peers influence our smoking behavior? Do I interact more frequently with others who share my own musical preferences? Focusing on modeling the link between networks and single characteristics simplifies methodological strategies (e.g., it is easier to collect data that focus on a single domain at a time, statistical frameworks are more parsimonious, etc.). However, many of the mechanisms underpinning social influence may work equally well for bundles of behaviors as for individual behaviors.Our focus on how...

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Section: Figure 2 Class-conditional Response Probabilities From Lcasupporting

confidence: 88%

Section: Discussionsupporting

confidence: 75%

Section: Identifying Health Lifestyles With Lcamentioning

confidence: 99%

See 1 more Smart Citation

Peer Network Processes in Adolescents' Health Lifestyles

Adams¹,

Lawrence²,

Goode³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…The proportion of obese students reporting ever smoked increased from 28.76% at age 11 to 40.79% at age 16. This trend is consistent with the literature indicating that the initiation of smoking most commonly occurs among youth between the ages of 10 to 13 years (30). The relationship between ever smoked and obesity increased from age 11 to age 12, yet slightly decreased from 12 to 13, only to precipitously increase again from age 13 to 14.…”

supporting

confidence: 91%

Stratified Multilevel Logistic Regression Modeling for Risk Factors of Adolescent Obesity in Tennessee

Zheng¹,

Strasser²,

Holt³

et al. 2018

Int J High Risk Behav Addict

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“…This nascent literature suggests that U.S. children, adolescents, and adults exhibit coherent patterns of behavior, consistent with their conceptualization as health lifestyles. To our knowledge, though, only one study has examined health lifestyles as they develop from adolescence to young adulthood, but this study limited behaviors to smoking, drinking, obesity, and physical activity (Daw et al, 2017). Thus, to our knowledge, we are the first study to examine health lifestyles as they unfold across the transition to adulthood while considering a broad range of behaviors in which individuals engage.…”

Section: Introductionmentioning

confidence: 99%

Health lifestyles across the transition to adulthood: Implications for health

Lawrence

Mollborn

Hummer

2017

Social Science & Medicine

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Research has long established the importance of individual health behaviors such as cigarette smoking for adult morbidity and mortality. However, we know little about how health behaviors cluster into health lifestyles among adolescents and young adults in the United States, or in turn, how such health lifestyles are associated with young adult health outcomes. This study establishes health lifestyles as distinct group phenomena at three developmental time points in a single cohort: late adolescence (ages 15–17), early adulthood (ages 20–24), and young adulthood (ages 26–31). We then identify the associations between these health lifestyles and young adult health outcomes. We use the National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative sample of U.S. adolescents followed into adulthood, and latent class analysis and regression models. We uncover diverse health lifestyles among adolescents, early adults, and young adults; however, few individuals engaged in a consistently salubrious lifestyle at any developmental stage. People with less healthy lifestyles also tended to exhibit poorer health in young adulthood. Our results showed that young adult health lifestyles were significantly associated with young adult cardiovascular risk. Moreover, health lifestyles in each of the three developmental stages were associated with young adult self-rated health, and accounting for lifestyles in later stages explained some of these associations. Overall, this study suggests a portrait of problematic health lifestyles among a nationally representative cohort of young Americans, with associated patterns of relatively poor physical health among those with poor health lifestyles.

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Emerging Adulthood, Emergent Health Lifestyles: Sociodemographic Determinants of Trajectories of Smoking, Binge Drinking, Obesity, and Sedentary Behavior

Cited by 98 publications

References 55 publications

Peer Network Processes in Adolescents' Health Lifestyles

Peer Network Processes in Adolescents' Health Lifestyles

Stratified Multilevel Logistic Regression Modeling for Risk Factors of Adolescent Obesity in Tennessee

Health lifestyles across the transition to adulthood: Implications for health

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