Abstract P205: A National Study Examining Association Between Frequency Of Cannabis Use And Demographic, Socioeconomic, And Behavioral Risk Factors

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Abra M Jeffers ◽  
Amy Byers ◽  
Salomeh Keyhani
Keyword(s):  
Risk Factors ◽  
Socioeconomic Status ◽  
Logistic Regression ◽  
Alcohol Use ◽  
Vulnerable Populations ◽  
Ordinal Logistic Regression ◽  
Cannabis Use ◽  
Behavioral Risk Factors ◽  
Behavioral Risk ◽  
Cannabis Consumption

Background: Cannabis use is becoming increasingly common. Yet, little is known about the frequency of past month cannabis use and how it is associated with demographic, socioeconomic and behavioral risk factors. Hypothesis: Vulnerable populations will have higher frequency of cannabis use. Individuals that have lower socioeconomic status, and or other behavioral risk factors (e.g. smoking) will have higher frequency of use compared to non-users. Methods: We combined four years (2016-2019), of the Behavioral Risk Factor Surveillance Survey (BRFSS), a large national survey of adults conducted annually by the CDC. The large sample size (unweighted N = 394,285) allowed the categorization of cannabis use. We examined the distribution of use and categorized past 30 day use into four categories: non-use (0 days, 90.7%), infrequent use (1-5 days, 2.9%), frequent use (6-29 days, 3.0%) and daily use (30 days, 3.3%). The subcategorizations of cannabis use frequency were treated as an ordinal variable. Ordinal logistic regression was performed to examine the association of the frequency of cannabis use with demographics (age, gender race/ethnicity, marital status), socioeconomic (educational attainment, employment status, annual household income), and behavioral (access to legal cannabis, smoking status, e-cigarette use, alcohol use and risky alcohol use) factors. Results: A multivariate ordinal logistic regression analysis showed that being male (Adjusted Odds Ratio (AOR) = 1.51; 95% CI: 1.41, 1.61), black (AOR = 1.55; 95%CI: 1.40, 1.72), unemployed (AOR = 1.19; 95%CI: 1.11-1.29), having access to legal medical (AOR = 1.22; 95%CI: 1.12, 1.32) or recreational (AOR = 2.52; 95%CI: 2.30, 2.76) cannabis, were associated with greater frequency of cannabis consumption. In addition, smoking tobacco (AOR = 2.18; 95%CI: 2.00, 2.37), e-cigarettes use (AOR = 3.51; 95%CI: 3.08, 4.01), past month alcohol use (AOR = 1.96; 95%CI: 1.81, 2.13) and binge drinking (AOR = 1.78; 95%CI: 1.63, 1.94) were also associated with greater frequency of cannabis consumption. Being older (AOR = 0.18; 95%CI: 0.15, 0.20), Asian (AOR = 0.66; 95%CI: 0.55, 0.79), Hispanic (AOR = 0.67; 95%CI: 0.60, 0.75), married (AOR = 0.56; 95%CI: 0.52, 0.60), and higher income (AOR = 0.87; 95%CI: 0.79, 0.97) were all associated with lower frequency of cannabis use. Conclusion: The most salient factors associated with greater frequency of cannabis use had to do with low socioeconomic status, recreational access to cannabis, and use of substances such as cigarette smoking and alcohol consumption. Vulnerable populations had high odds of cannabis use, and frequent cannabis use was associated with health behaviors that increase cardiovascular risk.

scholarly journals Neighborhood Disadvantage and Ischemic Stroke

Stroke ◽  
2011 ◽  
Vol 42 (12) ◽  
pp. 3363-3368 ◽  
Author(s):  
Arleen F. Brown ◽  
Li-Jung Liang ◽  
Stefanie D. Vassar ◽  
Sharon Stein-Merkin ◽  
W.T. Longstreth ◽  
...  
Keyword(s):  
Risk Factors ◽  
Socioeconomic Status ◽  
Ischemic Stroke ◽  
Hazard Ratio ◽  
Behavioral Risk Factors ◽  
Behavioral Risk ◽  
Stroke Incidence ◽  
Biological Risk ◽  
Neighborhood Socioeconomic Status ◽  
The Relationship

Background and Purpose— Neighborhood characteristics may influence the risk of stroke and contribute to socioeconomic disparities in stroke incidence. The objectives of this study were to examine the relationship between neighborhood socioeconomic status and incident ischemic stroke and examine potential mediators of these associations. Methods— We analyzed data from 3834 whites and 785 blacks enrolled in the Cardiovascular Health Study, a multicenter, population-based, longitudinal study of adults ages ≥65 years from 4 US counties. The primary outcome was adjudicated incident ischemic stroke. Neighborhood socioeconomic status was measured using a composite of 6 census tract variables. Race-stratified multilevel Cox proportional hazard models were constructed adjusted for sociodemographic, behavioral, and biological risk factors. Results— Among whites, in models adjusted for sociodemographic characteristics, stroke hazard was significantly higher among residents of neighborhoods in the lowest compared with the highest neighborhood socioeconomic status quartile (hazard ratio, 1.32; 95% CI, 1.01–1.72) with greater attenuation of the hazard ratio after adjustment for biological risk factors (hazard ratio, 1.16; 0.88–1.52) than for behavioral risk factors (hazard ratio, 1.30; 0.99–1.70). Among blacks, we found no significant associations between neighborhood socioeconomic status and ischemic stroke. Conclusions— Higher risk of incident ischemic stroke was observed in the most disadvantaged neighborhoods among whites, but not among blacks. The relationship between neighborhood socioeconomic status and stroke among whites appears to be mediated more strongly by biological than behavioral risk factors.

Abstract P151: The Association Between Perceived Discrimination And Behavioral Risk Factors Among African Americans In The Jackson Heart Study

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Mario Sims ◽  
Ana Diez-Roux ◽  
Samsom Gebreab ◽  
DeMarc Hickson ◽  
Marino Bruce ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Socioeconomic Status ◽  
African Americans ◽  
Perceived Discrimination ◽  
Behavioral Risk Factors ◽  
Behavioral Risk ◽  
Men And Women ◽  
Heart Study ◽  
Everyday Discrimination

Objectives. Prior research has reported an association between perceived discrimination and health outcomes among African Americans, and there is growing interest in the pathways in which it gets ‘under the skin.’ One such pathway may be through the association with behavioral risk factors. Using Jackson Heart Study data, we examined whether perceived reports of discrimination were associated with behavioral risk factors among African Americans. Methods. Cross-sectional associations of perceived reports of everyday discrimination, lifetime discrimination, and burden of lifetime discrimination with smoking status, physical activity, percent calories from fat in diet, and hours of sleep were examined among 4,939 participants 20–95 years old (women=3,123; men=1,816). We estimated odds ratios (OR) of current smoking and mean differences in physical activity, fat in diet and hours of sleep with measures of discrimination and adjusted for age and socioeconomic status. Results. Men were more likely to smoke than women, and had higher physical activity scores. Women reported slightly more hours of sleep than men. Men and women reported similar percentages of calories from fat in diet. After adjustment for age and socioeconomic status, perceived everyday discrimination was associated with more smoking and a greater percentage of calories from fat in diet in men and women (OR for smoking: 1.13, 95%CI 1.00–1.28 and 1.19, 95%CI 1.05–1.34; mean difference in percent calories from fat in diet: 0.37, p<.05,0.43, p<.01, in men and women respectively). Everyday discrimination was associated with higher physical activity scores in women (0.11, p<.05) but not men. Everyday and lifetime discrimination were associated with fewer hours of sleep in men and women (everyday discrimination: −0.08, p<.05 and −0.18, p<.001, respectively; and lifetime discrimination: −0.08, p<.05, and −0.24, p<.001, respectively). Lifetime discrimination was associated with more smoking and higher physical activity scores in women only in fully-adjusted models (OR for smoking: 1.17, 95%CI 1.03–1.33; mean difference in physical activity: 0.14, p<.01), and lifetime discrimination was positively associated with percent calories from fat in diet in men only in the fully-adjusted model (0.46, p <.01). Burden of lifetime discrimination was associated with more smoking in women and fewer hours of sleep in women. Conclusions. Behavioral risk factors offer a potential mechanism through which perceived discrimination affects health in African Americans.

scholarly journals Psychological and Behavioral Predictors of Vaccine Efficacy: Considerations for COVID-19

2021 ◽  
pp. 174569162198924
Author(s):  
Annelise A. Madison ◽  
M. Rosie Shrout ◽  
Megan E. Renna ◽  
Janice K. Kiecolt-Glaser
Keyword(s):  
Risk Factors ◽  
Side Effects ◽  
Vaccine Efficacy ◽  
Psychological Factors ◽  
Behavioral Interventions ◽  
Vulnerable Groups ◽  
Behavioral Risk Factors ◽  
Behavioral Risk ◽  
Vaccine Response ◽  
The Impact

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine candidates are being evaluated, with the goal of conferring immunity on the highest percentage of people who receive the vaccine as possible. It is noteworthy that vaccine efficacy depends not only on the vaccine but also on characteristics of the vaccinated. Over the past 30 years, a series of studies has documented the impact of psychological factors on the immune system’s vaccine response. Robust evidence has demonstrated that stress, depression, loneliness, and poor health behaviors can impair the immune system’s response to vaccines, and this effect may be greatest in vulnerable groups such as the elderly. Psychological factors are also implicated in the prevalence and severity of vaccine-related side effects. These findings have generalized across many vaccine types and therefore may be relevant to the SARS-CoV-2 vaccine. In this review, we discuss these psychological and behavioral risk factors for poor vaccine responses, their relevance to the COVID-19 pandemic, as well as targeted psychological and behavioral interventions to boost vaccine efficacy and reduce side effects. Recent data suggest these psychological and behavioral risk factors are highly prevalent during the COVID-19 pandemic, but intervention research suggests that psychological and behavioral interventions can increase vaccine efficacy.

scholarly journals Effects of Behavioral Risk Factors and Social-Environmental Factors on Non-Communicable Diseases in South Korea: A National Survey Approach

2021 ◽  
Vol 18 (2) ◽  
pp. 612
Author(s):  
Nam Jeong Jeong ◽  
Eunil Park ◽  
Angel P. del Pobil
Keyword(s):  
Risk Factors ◽  
Environmental Factors ◽  
South Korea ◽  
Communicable Diseases ◽  
Behavioral Risk Factors ◽  
Behavioral Risk ◽  
Non Communicable Diseases ◽  
Path Analyses ◽  
Social Environmental ◽  
Social Environmental Factors

Non-communicable diseases (NCDs) are one of the major health threats in the world. Thus, identifying the factors that influence NCDs is crucial to monitor and manage diseases. This study investigates the effects of social-environmental and behavioral risk factors on NCDs as well as the effects of social-environmental factors on behavioral risk factors using an integrated research model. This study used a dataset from the 2017 Korea National Health and Nutrition Examination Survey. After filtering incomplete responses, 5462 valid responses remained. Items including one’s social-environmental factors (household income, education level, and region), behavioral factors (alcohol use, tobacco use, and physical activity), and NCDs histories were used for analyses. To develop a comprehensive index of each factor that allows comparison between different concepts, the researchers assigned scores to indicators of the factors and calculated a ratio of the scores. A series of path analyses were conducted to determine the extent of relationships among NCDs and risk factors. The results showed that social-environmental factors have notable effects on stroke, myocardial infarction, angina, diabetes, and gastric, liver, colon, lung, and thyroid cancers. The results indicate that the effects of social-environmental and behavioral risk factors on NCDs vary across the different types of diseases. The effects of social-environmental factors and behavioral risk factors significantly affected NCDs. However, the effect of social-environmental factors on behavioral risk factors was not supported. Furthermore, social-environmental factors and behavioral risk factors affect NCDs in a similar way. However, the effects of behavioral risk factors were smaller than those of social-environmental factors. The current research suggests taking a comprehensive view of risk factors to further understand the antecedents of NCDs in South Korea.

Abstract WP182: Trends in Acute Ischemic Stroke Hospitalizations and Risk Factors Among Young Adults: 12 Years of Nationally Representative Data

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Urvish K Patel ◽  
Priti Poojary ◽  
Vishal Jani ◽  
Mandip S Dhamoon
Keyword(s):  
Risk Factors ◽  
Older Adults ◽  
Young Adults ◽  
Ischemic Stroke ◽  
Length Of Stay ◽  
Acute Ischemic Stroke ◽  
Stroke Risk ◽  
Behavioral Risk Factors ◽  
Behavioral Risk ◽  
Stroke Risk Factors

Background: There is limited recent population-based data of trends in acute ischemic stroke (AIS) hospitalization rates among young adults (YA). Rising prevalence of stroke risk factors may increase stroke rates in YA. We hypothesized that 1) stroke hospitalizations and mortality among YA are increasing over time (2000-2011), 2) besides traditional stroke risk factors, non-traditional factors are associated with stroke in YA, 3) stroke hospitalization among YA is associated with higher mortality, length of stay (LOS), and cost. Methods: In the Nationwide Inpatient Sample database (years 2000-2011), adult hospitalizations for AIS and concurrent diagnoses were identified by ICD-9-CM codes; the analytic cohort constituted all AIS hospitalizations. We performed weighted analysis using chi-square, t-test, and Jonckheere trend test. Multivariable survey regression models evaluated interactions between age group (18-45 vs. >45 years) and traditional and non-traditional risk factors, with outcomes including mortality, LOS, and cost. Models were adjusted for race, sex, Charlson’s Comorbidity Index, primary payer, location and teaching status of hospital, and admission day. Results: Among 5220960 AIS hospitalizations, 231858 (4.4%) were YA. On trend analysis, proportion of YA amongst AIS increased from 3.6% in 2000 to 4.7% in 2011 (p<0.0001) but mortality in YA decreased from 3.7% in 2000 to 2.6% in 2011, compared to 7.1% in 2000 to 4.6% in 2011 (p<0.0001) among older adults. Non-traditional, especially behavioral, risk factors were more common among YA, and LOS and cost were higher (Table). Conclusion: There was a trend for higher proportion of YA among AIS hospitalizations, though there was a decreasing mortality trend over 10 years. Behavioral risk factors were more common among YA, and there was an increased length of stay and cost. AIS in YA may require different preventive approaches compared to AIS among older adults.

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