Determinants of Physical Activity in America: A First Characterization of Physical Activity Profile Using the National Health and Nutrition Examination Survey (NHANES)

Kao, Ming-Chih J.; Jarosz, Renata; Goldin, Michael; Patel, Amy; Smuck, Matthew

doi:10.1016/j.pmrj.2014.03.004

Cited by 20 publications

(25 citation statements)

References 21 publications

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“…25 However, minority race/ethnicity was negatively associated with self-reported leisure time physical activity 20 and a “weekend warrior” pattern based on self-reported data. 4,15,24 …”

Section: Discussionmentioning

confidence: 99%

“…Measures of physical activity and sedentary behavior have progressed from simple dichotomy (active vs. inactive) to self-reported frequency and duration, and more recently to accelerometer-based measures. 3,4 Typically, accelerometer output is summarized as total time in sedentary behavior, light, moderate, and vigorous physical activity over the course of the monitoring period (usually assessed per week). 4 However, in addition to the cumulative amount, the manner in which physical activity and sedentary behavior are accumulated may be important.…”

Section: Introductionmentioning

confidence: 99%

“…3,4 Typically, accelerometer output is summarized as total time in sedentary behavior, light, moderate, and vigorous physical activity over the course of the monitoring period (usually assessed per week). 4 However, in addition to the cumulative amount, the manner in which physical activity and sedentary behavior are accumulated may be important. 5,6 For example, the health benefits of physical activity may differ for engaging in some physical activity every day compared to longer bouts of physical activity only on weekends.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Correlates of US adult physical activity and sedentary behavior patterns

Jones¹,

Wen²,

Herring³

et al. 2016

Journal of Science and Medicine in Sport

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Objectives Physical activity and sedentary behavior patterns may be differentially associated with socio-demographic and health measures. We explored correlates of day-to-day patterns over a week in accelerometer measured physical activity and sedentary behavior to inform intervention development. Design Cross-sectional study Methods National Health and Nutrition Examination Survey (NHANES) adult participants (≥20 years) in 2003–2006 wore an accelerometer for 1 week. Accelerometer data from 7236 participants were used to derive latent classes describing day-to-day patterns over a week of physical activity and sedentary behavior. Correlates of each pattern were identified using multinomial logistic regression from 21 potential variables grouped into four domains: socio-demographic, acculturation, cardiovascular, and health history. Results Older age, female sex, higher body mass index, and history of chronic disease were consistently associated with lower odds of being in a more active compared to the least active class. In contrast, being employed, speaking Spanish at home, and having better self-rated health were associated with higher odds of being in a more active compared to the least active class. Conclusions Correlates of physical activity and sedentary behavior patterns were identified from all domains (socio-demographic, acculturation, cardiovascular, and health history). Most correlates that were positively associated with physical activity were negatively associated with sedentary behavior. Better understanding of the correlates of physical activity and sedentary behavior patterns can inform interventions to promote physical activity and reduce sedentary behavior.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Correlates of US adult physical activity and sedentary behavior patterns

Jones¹,

Wen²,

Herring³

et al. 2016

Journal of Science and Medicine in Sport

View full text Add to dashboard Cite

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“…Also, the greater intervention benefit in those reporting lower annual incomes is significant because lower socioeconomic status is associated with less physical activity and participation in physical activity behavior change interventions [21, 39]. Further research to replicate this finding and identify potential key intervention components responsible for this benefit is warranted.…”

Section: Discussionmentioning

confidence: 99%

Effects of a multicomponent physical activity behavior change intervention on breast cancer survivor health status outcomes in a randomized controlled trial

Rogers

Courneya

Carter

et al. 2016

Breast Cancer Res Treat

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Purpose Little is known about the effects of physical activity behavior change interventions on health outcomes such as lower extremity dysfunction and SF-36 physical health (predictor of mortality) in breast cancer survivors. Furthermore, effect moderators are rarely reported. Therefore, we report the effects of the 3-month BEAT Cancer physical activity behavior change intervention on global health status and health indicators along with moderators of intervention outcomes. Methods Post-primary treatment breast cancer survivors (N=222) were randomized to BEAT Cancer or usual care (UC). SF-36, muscle strength, body mass index, lower extremity dysfunction (WOMAC) and life satisfaction were measured at 3 months (M3) and 6 months (M6). Results At M3, adjusted linear mixed-model analyses demonstrated statistically significant effects of BEAT Cancer versus UC on SF-36 physical health [mean between group difference (M)=2.1; 95% confidence interval (CI)=0.3 to 3.9; P=.023], SF-36 mental health (M=5.2; CI=2.8 to 7.6; P <.001), and all SF-36 subscores. Intervention benefits occurred for lower extremity physical dysfunction (M =−2.7; CI=−5.0 to −0.5; P=0.018), WOMAC total (M=−3.7; CI=−6.7 to −0.6; P=0.018), and life satisfaction (M=2.4; CI=0.9 to 3.9; P=0.001). Statistically significant effects persisted at M6 for mental health and vitality. Baseline value, income, marital status, cancer treatment, cancer stage, and months since diagnosis moderated one or more outcomes. Conclusions BEAT Cancer improves SF-36, WOMAC, and life satisfaction outcomes with improvements in vitality and mental well-being continuing 3 months post-intervention. Several moderators with potential to guide targeting individuals for optimal intervention benefit warrant further study.

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“…Both the intensity of PA and the total amount of energy spent are lower in women than in men. In addition, compared with men, woman spend a greater proportion of time engaged in sedentary and light activities and less time engaged in more strenuous (moderate and intense) PA [32,33]. Furthermore, women's blood pressure is also in uenced by estrogen levels, menstrual cycle, and fertility [34].…”

Section: Discussionmentioning

confidence: 99%

Physical Activity Trajectories During Adulthood and Incident Hypertension: A National Longitudinal Cohort Study

Cao¹,

Wang²,

Dong³

et al. 2020

Preprint

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Background We aimed to characterize the physical activity (PA) trajectories across adulthood and estimate their association with incident hypertension risk.Methods Data were obtained from the China Health and Nutrition Survey (CHNS) conducted during 2004–2011. Group-based trajectory modeling (GBTM) was used to identify distinct groups of PA trajectories. The Cox proportional hazard model was used to investigate the association between each PA trajectory group and incident hypertension.Results A total of 11,162 participants whose PA was repeatedly measured two to four times in the CHNS during 2004–2011 were included in our study. During the 5.4 years of follow-up, 3,824 incident hypertension cases were identified. Five distinct PA trajectories were identified in men: light and slight decline, light and gradual decline then sharp rise, light to medium-heavy then decline, medium-heavy and persistent decline, and heavy and sharp decline. Two distinct PA trajectories were identified in women: light and stable, and medium and gradual decline. The PA trajectory of medium-heavy and persistent decline was significantly associated with decreased risk of hypertension in men, with the hazard ratios and 95% confidence intervals being 0.80 (0.63, 0.99), 0.74 (0.59, 0.93), 0.76 (0.60, 0.96), and 0.70 (0.55, 0.88) in model 1, model 2, model 3, and model 4, respectively.Conclusions Our study identified five distinct long‐term PA trajectories in men and two distinct trajectories in women. The PA trajectory of medium-heavy PA in early adulthood (at 18–37 years) followed by persistent decline (at 38–70 years) was found to be significantly associated with a decreased risk of hypertension in later life in men.

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Determinants of Physical Activity in America: A First Characterization of Physical Activity Profile Using the National Health and Nutrition Examination Survey (NHANES)

Cited by 20 publications

References 21 publications

Correlates of US adult physical activity and sedentary behavior patterns

Correlates of US adult physical activity and sedentary behavior patterns

Effects of a multicomponent physical activity behavior change intervention on breast cancer survivor health status outcomes in a randomized controlled trial

Physical Activity Trajectories During Adulthood and Incident Hypertension: A National Longitudinal Cohort Study

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