Logistic Regression and the Behavioral Risk Factor Surveillance System (2013): Physical Activity in the U.S.

Background:Physical inactivity is associated with increased morbidity and mortality. This study provides prevalence estimates of inactivity by select characteristics among older adults.Methods:Respondents ≥50 years of age were selected from the 2005 Behavioral Risk Factor Surveillance System (N = 185,702).Results:Overall, 30.0% of older adults did not engage in leisure-time physical activity. Within each racial/ethnic group, the prevalence of inactivity was highest among Hispanic men (41.9%) and women (42.4%). Among men with and without disabilities, chronic disease conditions associated with inactivity were angina or coronary artery disease. Among women with disabilities, chronic disease conditions associated with inactivity were stroke and diabetes; among women without disabilities only diabetes was significantly associated with inactivity.Conclusion:Regular physical activity is an important means to maintaining independence, because it substantially reduces the risk for developing many diseases; contributes to healthy bones, muscles, and joints; and can reduce the risk for falling. Health care providers are encouraged to discuss concerns regarding physical activity with their patients.

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TRENDS IN PHYSICAL ACTIVITY PATTERNS AMONG YOUNG ADULTS. THE BEHAVIORAL RISK FACTOR SURVEILLANCE SYSTEM, 1986???1990

Medicine & Science in Sports & Exercise ◽

10.1249/00005768-199205001-00154 ◽

1992 ◽

Vol 24 (Supplement) ◽

pp. S26

Author(s):

R. K. Merrill ◽

C. J. Caspersen

Keyword(s):

Physical Activity ◽

Young Adults ◽

Risk Factor ◽

Surveillance System ◽

Activity Patterns ◽

Behavioral Risk ◽

Behavioral Risk Factor ◽

Physical Activity Patterns ◽

Behavioral Risk Factor Surveillance ◽

Risk Factor Surveillance

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Propensity Score Analysis Assessing the Burden of Non-Communicable Diseases among the Transgender Population in the United States Using the Behavioral Risk Factor Surveillance System (2017–2019)

Healthcare ◽

10.3390/healthcare9060696 ◽

2021 ◽

Vol 9 (6) ◽

pp. 696

Author(s):

Jennifer R. Pharr ◽

Kavita Batra

Keyword(s):

Logistic Regression ◽

Risk Factor ◽

Propensity Score ◽

Surveillance System ◽

Behavioral Risk ◽

Behavioral Risk Factor ◽

Cross Sectional ◽

Non Communicable Diseases ◽

Behavioral Risk Factor Surveillance ◽

Risk Factor Surveillance

Research to assess the burden of non-communicable diseases (NCDs) among the transgender population needs to be prioritized given the high prevalence of chronic conditions and associated risk factors in this group. Previous cross-sectional studies utilized unmatched samples with a significant covariate imbalance resulting in a selection bias. Therefore, this cross-sectional study attempts to assess and compare the burden of NCDs among propensity score-matched transgender and cisgender population groups. This study analyzed Behavioral Risk Factor Surveillance System data (2017–2019) using complex weighting procedures to generate nationally representative samples. Logistic regression was fit to estimate propensity scores. Transgender and cisgender groups were matched by sociodemographic variables using a 1:1 nearest neighbor matching algorithm. McNemar, univariate, and multivariate logistic regression analyses were conducted among matched cohorts using R and SPSS version 26 software. Compared with the cisgender group, the transgender group was significantly more likely to have hypertension (31.3% vs. 27.6%), hypercholesteremia (30.8% vs. 23.7%), prediabetes (17.3% vs. 10.3%), and were heavy drinkers (6.7% vs. 6.0%) and smokers (22.4% vs. 20.0%). Moreover, the transgender group was more than twice as likely to have depression (aOR: 2.70, 95% CI 2.62–2.72), stroke (aOR: 2.52 95% CI 2.50–2.55), coronary heart disease (aOR: 2.77, 95% CI 2.74–2.81), and heart attack (aOR: 2.90, 95% CI 2.87–2.94). Additionally, the transgender group was 1.2–1.7 times more likely to have metabolic and malignant disorders. Differences were also found between transgender subgroups compared with the cisgender group. This study provides a clear picture of the NCD burden among the transgender population. These findings offer an evidence base to build health equity models to reduce disparities among transgender groups.

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