Using gender-based analyses to understand physical inactivity among women in Yellowstone County, Montana

Duin, Diane K.; Golbeck, Amanda L.; Keippel, April Ennis; Ciemins, Elizabeth L.; Hanson, Hillary; Neary, Tracy; Fink, Heather

doi:10.1016/j.evalprogplan.2014.12.006

Cited by 13 publications

(13 citation statements)

References 8 publications

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“…Girls may smoke as an indication and an expression of independence, while for boys smoking may be just another risk‐taking behaviour confirming their masculinity and these differentiations may be pertinent to the determinants of all health risk behaviours (Duin et al . , Núñez et al . ).…”

Section: Discussionmentioning

confidence: 99%

Gender differences in the prevalence and clustering of multiple health risk behaviours in young adults

Kritsotakis

Psarrou

Vassilaki

et al. 2016

Journal of Advanced Nursing

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Section: Discussionmentioning

confidence: 99%

Gender differences in the prevalence and clustering of multiple health risk behaviours in young adults

Kritsotakis

Psarrou

Vassilaki

et al. 2016

Journal of Advanced Nursing

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“…The fact of not having a partner was associated with physical inactivity. Indeed, previous studies demonstrate that having a marital life and having family support are essential to the practice of physical activities (Duin et al, 2015; Escobar-Viera, Jones, Schumacher, & Hall, 2014).…”

Section: Discussionmentioning

confidence: 99%

Prevalence of Physical Inactivity and Associated Factors Among Older Caregivers of Older Adults

et al. 2018

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“…In addition, the lack of exercise and sedentary behavior both play a fundamental role in the process of weight gain [ 13 , 19 ]. However, gender roles influenced by genetic and social factors place some women in the position of family caregiver, leaving little time or energy for exercise [ 51 ]. The American College of Sports Medicine and the American Diabetes Association hold the joint statement that physical activity and regular exercise can assist with the management of blood glucose levels [ 52 ].…”

Section: Discussionmentioning

confidence: 99%

Identifying Patterns of Lifestyle Behaviors among People with Type 2 Diabetes in Tianjin, China: A Latent Class Analysis

et al. 2017

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IntroductionLifestyle behaviors are essential elements of diabetes care. The aims of this study were to identify distinct subgroups of people with type 2 diabetes based on personal levels of lifestyle behaviors and explore the different characteristics across these subgroups.MethodsIn 2015 and 2016, 1504 outpatients with a diagnosis of type 2 diabetes were selected via two-stage simple random sampling from 10 municipal district hospitals in Tianjin. Participants accepted an invitation by experienced physicians to complete a questionnaire containing demographic and lifestyle content. Clinical data were collected by reviewing medical records. Latent class analysis was applied to identify patterns of lifestyle behaviors. Multinomial logistic regression was used to investigate the characteristics of the subgroups.ResultsThe final model yielded a four-class solution: the healthy behavioral group, unhealthy diet and less activity group, smoking and drinking group, and sedentary and extremely inactive group. Further analysis found that variables, including age, sex, general/central obesity, treatment modalities, glycemic control, diabetes duration, and diabetes-related complications and comorbidities, were disproportionately distributed across the four latent classes (P < 0.05). Participants in the unhealthy diet and less activity group were more likely to have a longer duration of diabetes, poor glycemic control and more diabetes-related diseases relative to the other three latent classes.ConclusionsIdentification and characterization of subgroups based on lifestyle behaviors in individuals with type 2 diabetes can help health care providers to shift to targeted intervention strategies.Electronic supplementary materialThe online version of this article (doi:10.1007/s13300-017-0327-7) contains supplementary material, which is available to authorized users.

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Using gender-based analyses to understand physical inactivity among women in Yellowstone County, Montana

Cited by 13 publications

References 8 publications

Gender differences in the prevalence and clustering of multiple health risk behaviours in young adults

Gender differences in the prevalence and clustering of multiple health risk behaviours in young adults

Prevalence of Physical Inactivity and Associated Factors Among Older Caregivers of Older Adults

Identifying Patterns of Lifestyle Behaviors among People with Type 2 Diabetes in Tianjin, China: A Latent Class Analysis

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