Characteristics of Adults Who Use Both Marijuana and E-Cigarette, or Vaping, Products

2021 ◽  
pp. 003335492110186
Author(s):  
Nathaniel M. Lewis ◽  
Michael Friedrichs ◽  
Shelly S. Wagstaff ◽  
Allyn K. Nakashima ◽  
Angela C. Dunn
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Adult Population ◽  
Poor Mental Health ◽  
Chronic Obstructive ◽  
Behavioral Risk ◽  
Chronic Obstructive Pulmonary Disorder ◽  
Dual Use ◽  
Other Substances ◽  
Referent Group

Objectives Among young people, dual use of marijuana and e-cigarette, or vaping, products (EVPs) is linked with using more inhalant substances and other substances, and poorer mental health. To understand antecedents and potential risks of dual use in adults, we analyzed a representative adult population in Utah. Methods We used data from the 2018 Utah Behavioral Risk Factor Surveillance System (n = 10 380) and multivariable logistic regression to evaluate differences in sociodemographic characteristics, comorbidities, and risk factors among adults aged ≥18 who reported currently using both EVPs (any substance) and marijuana (any intake mode), compared with a referent group of adults who used either or neither. Results Compared with the referent group, adults using EVPs and marijuana had greater odds of being aged 18-29 (adjusted odds ratio [aOR] = 12.44; 95% CI, 6.15-25.14) or 30-39 (aOR = 3.75; 95% CI, 1.73-8.12) versus ≥40, being male (aOR = 3.29; 95% CI, 1.82-5.96) versus female, reporting ≥14 days of poor mental health in previous 30 days (aOR = 2.30; 95% CI, 1.23-4.32) versus <14 days, and reporting asthma (aOR = 2.09; 95% CI, 1.02-4.31), chronic obstructive pulmonary disorder (aOR = 2.94; 95% CI, 1.19-7.93), currently smoking cigarettes (aOR = 4.56; 95% CI, 2.63-7.93), or past-year use of prescribed chronic pain medications (aOR = 2.13; 95% CI, 1.06-4.30), all versus not. Conclusions Clinicians and health promotion specialists working with adults using both EVPs and marijuana should assess risk factors and comorbidities that could contribute to dual use or associated outcomes and tailor prevention messaging accordingly.

scholarly journals Examining Predictors of Myocardial Infarction

2021 ◽  
Vol 18 (21) ◽  
pp. 11284
Author(s):  
Diane Dolezel ◽  
Alexander McLeod ◽  
Larry Fulton
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Home Ownership ◽  
Training Model ◽  
The United States ◽  
Access To Healthcare ◽  
Chronic Obstructive ◽  
Behavioral Risk ◽  
Chronic Obstructive Pulmonary Disorder ◽  
Training Set

Cardiovascular diseases are the leading cause of death in the United States. This study analyzed predictors of myocardial infarction (MI) for those aged 35 and older based on demographic, socioeconomic, geographic, behavioral, and risk factors, as well as access to healthcare variables using the Center for Disease (CDC) Control Behavioral Risk Factor Surveillance System (BRFSS) survey for the year 2019. Multiple quasibinomial models were generated on an 80% training set hierarchically and then used to forecast the 20% test set. The final training model proved somewhat capable of prediction with a weighted F1-Score = 0.898. A complete model based on statistically significant variables using the entirety of the dataset was compared to the same model built on the training set. Models demonstrated coefficient stability. Similar to previous studies, age, gender, marital status, veteran status, income, home ownership, employment status, and education level were important demographic and socioeconomic predictors. The only geographic variable that remained in the model was associated with the West North Central Census Division (in-creased risk). Statistically important behavioral and risk factors as well as comorbidities included health status, smoking, alcohol consumption frequency, cholesterol, blood pressure, diabetes, stroke, chronic obstructive pulmonary disorder (COPD), kidney disease, and arthritis. Three access to healthcare variables proved statistically significant: lack of a primary care provider (Odds Ratio, OR = 0.853, p < 0.001), cost considerations prevented some care (OR = 1.232, p < 0.001), and lack of an annual checkup (OR = 0.807, p < 0.001). The directionality of these odds ratios is congruent with a marginal effects model and implies that those without MI are more likely not to have a primary provider or annual checkup, but those with MI are more likely to have missed care due to the cost of that care. Cost of healthcare for MI patients is associated with not receiving care after accounting for all other variables.

Precarious employment, psychosocial risk factors and poor mental health: A cross-sectional mediation analysis

2021 ◽  
Vol 143 ◽  
pp. 105439
Author(s):  
Fabrizio Méndez Rivero ◽  
Eva Padrosa ◽  
Mireia Utzet ◽  
Joan Benach ◽  
Mireia Julià
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Mediation Analysis ◽  
Poor Mental Health ◽  
Psychosocial Risk Factors ◽  
Psychosocial Risk ◽  
Cross Sectional ◽  
Precarious Employment

scholarly journals Mental health and caregiving experiences of family carers supporting people with psychosis

2021 ◽  
Vol 30 ◽  
Author(s):  
J. Sin ◽  
J. Elkes ◽  
R. Batchelor ◽  
C. Henderson ◽  
S. Gillard ◽  
...  
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
General Population ◽  
Large Scale ◽  
Controlled Trial ◽  
Population Sample ◽  
Poor Mental Health ◽  
Mental Wellbeing ◽  
Family Carers ◽  
Negative Experience

Abstract Aims Family carers supporting an individual with psychosis often experience poorer mental health, however, little is known about specific risk factors among these carers. We investigated the associations between demographic, caregiving characteristics and mental health outcomes in family carers supporting an individual with psychosis and compared carers' outcomes with general population norms. Methods We analysed baseline data from the COPe-support randomised controlled trial of online psychoeducation and peer support for adult carers supporting an individual with psychosis between 2018 and 2020. We collected carers' demographic and health outcome data, including wellbeing using Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS as primary outcome), quality of life using EQ-5D-5L and caregiving experience assessed with Experience of Caregiving Inventory. We tested associations between carers' demographic and caregiving characteristics for each outcome in turn and meta-analysed carers' WEMWBS and EQ-5D-5L with Health Survey England (HSE) general population data from 2016 and 2017, respectively. Results The 407 carers of people with psychosis had a mean WEMWBS score of 42.2 (s.d. 9.21) and their overall weighted pooled WEMWBS score was 7.3 (95% confidence interval (CI) −8.6 to −6.0, p < 0.01) lower than the HSE general population sample, indicating carers have poorer mental wellbeing by more than double the minimum clinically important difference of 3 points on WEMWBS. Among all caring relationships, partners had poorer wellbeing compared to parents with lower WEMWBS score (−6.8, −16.9 to 3.3, p = 0.03). Single carers had significantly poorer wellbeing (−3.6, −5.6 to −1.5, p < 0.01) and a more negative caregiving experience than those who were cohabiting. Spending more than 35 h per week caregiving increased carers' negative experience significantly (p = 0.01). Conclusion Carers of people with psychosis have poorer mental health than non-carers. Partners, lone carers and those spending more than 35 h per week on caring were found to be most at risk of poor mental health. Based on the results, we advocate that the details of carers for individuals with psychosis should be added to the existing carers or severe mental illness registers at all general practitioner surgeries and for their wellbeing screened routinely. Future large-scale prospective studies are needed to develop a predictive model to determine risk factors, hence to aid early identification of carers' support needs. Such understandings are also useful to inform tailored intervention development.

A nationwide cross-sectional study of difficulty waking up for school among adolescents

SLEEP ◽  
2021 ◽  
Author(s):  
Yu Kinoshita ◽  
Osamu Itani ◽  
Yuichiro Otsuka ◽  
Yuuki Matsumoto ◽  
Sachi Nakagome ◽  
...  
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
High Schools ◽  
Odds Ratio ◽  
Associated Factors ◽  
Underlying Disease ◽  
Early Morning ◽  
Poor Mental Health ◽  
Cross Sectional ◽  
Waking Up

Abstract Study Objectives To determine the prevalence of and risk-factors for difficulty waking up for school among adolescents. Methods We used a self-administered questionnaire (140 junior high schools [JHSs]; 124 senior high schools [SHSs]) selected randomly in 2012 from throughout Japan. Results Total response rate: 60.7%. Data from 38,494 JHS and 61,556 SHS students were analyzed. The prevalence of at least one instance of school tardiness/absence due to difficulty waking up over a 30-day period was 10.9(95% confidence-interval:10.5-11.3)%/2.9(2.7-3.1)% for JHS-boys and 7.7(7.3-8.1)%/2.0(1.8-2.2)% for JHS-girls. The prevalence was 15.5(15.1-15.9)%/5.6(5.3-5.9)% for SHS-boys and 14.4(14.0-14.8)%/5.9(5.6-6.2)% for SHS-girls. We used ordinal regression to identify the risk factors associated with the experience of school tardiness/absence. Factors significantly associated with school tardiness in all four groups (JHS boys/girls, SHS boys/girls) were “no-participation-in-club-activities,” “early-morning-awakening,” “feeling bad throughout a morning,” “drinking,” and “smoking.” Among associated factors, the highest odds ratio was found for monthly smoking-days (none vs. at least one-day or more) for JHS-girls at 5.30(3.57-7.85). Factors significantly associated with school absence in all four groups were “no wishing to go to university,” “no participation in club activities,” “disorders of initiating and maintaining sleep,” “long internet use,” “drinking,” “smoking,” “poor-mental-health” and “feeling bad throughout a morning.” Among associated factors, the highest odds ratio was found for monthly smoking-days (none vs. at least one-day or more) for JHS-girls at 4.60(3.45-6.15). Conclusions These results suggest that the risk factors for difficulty waking up among adolescents are sleep status, lifestyle, and mental health, which can indicate the presence of an underlying disease.

scholarly journals Lifestyle Behaviors and Mental Health of American Adults

2007 ◽  
Vol 100 (1) ◽  
pp. 294-302 ◽  
Author(s):  
Elizabeth H. Chaney ◽  
J. Don Chaney ◽  
Min Qi Wang ◽  
James M. Eddy
Keyword(s):  
Mental Health ◽  
Healthy Lifestyle ◽  
Descriptive Analysis ◽  
Experimental Studies ◽  
Poor Mental Health ◽  
Behavioral Risk ◽  
Lifestyle Behaviors ◽  
Unhealthy Lifestyle ◽  
Data Set ◽  
Health Related

The purpose of this study was to test the hypothesis that individuals reporting healthy lifestyle behaviors would also report better self-rated mental health. Logistic regression analyses were conducted utilizing SUDAAN on the Behavioral Risk Factor Surveillance Survey data set. This descriptive analysis suggests that persons reporting poor mental health were more likely to report unhealthy lifestyle behaviors. This set of findings encourages careful design of experimental studies of empirically based associations of mental health and life style, using psychometrically sound measures. Then public health programs focused on change of health-related behaviors might be more suitably devised.

scholarly journals STUDENTS’ MENTAL HEALTH RISKS REGARDING SUSCEPTIBILITY TO PEER PRESSURE

2021 ◽  
pp. 60-67
Author(s):  
Jasna Kudek Mirošević ◽  
Mirjana Radetić-Paić ◽  
Ivan Prskalo
Keyword(s):  
Mental Health ◽  
Young People ◽  
Health Behaviour ◽  
Peer Group ◽  
Adult Population ◽  
Peer Pressure ◽  
Poor Mental Health ◽  
Positive Health ◽  
Significant Difference ◽  
The University

Given that adolescents and young people spend most of their time in the educational system, advancements in neurodevelopmental research emphasize the important and complex role of peers’ influence on adolescents’ behaviour, suggesting that supportive programmes led by peers have a strong potential benefit (King, & Fazel, 2019). In many cases peers are the most important source of social support, and are therefore an important target group to investigate the factors of risk, signs of poor mental health and ways to assess their health behaviour and awareness of the care which should be taken regarding their mental health, as well as the resources and prevention models. The wish is to study whether there are differences regarding the mental behaviour in certain characteristics of susceptibility to peer pressure as a risk for the mental health of students of the Faculty of Educational Sciences of the Juraj Dobrila University of Pula and students of the Faculty of Teacher Education of the University of Zagreb, Division of Petrinja (N=440). The set hypothesis states that there is a statistically significant difference among students of the faculty in Pula and those in Petrinja in their assessment of certain features of peer pressure susceptibility as a possible risk for mental health. The results obtained at the x2-test showed a statistically significant difference between certain peer pressure features among students regarding their study environment linked to hanging out with peers who consume drugs and being tempted to try them, getting involved in risky behaviours if their peers ask them to, and betting or gambling because their friends also do that. The results indicate that in smaller communities social control and conformity in the students’ behaviour is more present due to their wish to fit in a peer group as well as possible, suggesting the need for strengthening the positive health behaviour of young people during their whole education in order to secure a healthy and productive adult population.

scholarly journals Patterns of multiple lifestyle risk factors and their link to mental health in the German adult population: a cross-sectional study

BMJ Open ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. e022184 ◽  
Author(s):  
Josefine Atzendorf ◽  
Christian Apfelbacher ◽  
Elena Gomes de Matos ◽  
Ludwig Kraus ◽  
Daniela Piontek
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Adult Population ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Lifestyle Risk Factors ◽  
Unhealthy Diet ◽  
Lifestyle Risk ◽  
German Adult

ObjectivesLifestyle risk factors, such as drinking or unhealthy diet, can expotentiate detrimental health effects. Therefore, it is important to investigate multiple lifestyle risk factors instead of single ones. The study aims at: (1) identifying patterns of lifestyle risk factors within the adult general population in Germany and (2) examining associations between the extracted patterns and external factors.DesignCross-sectional study.SettingGeneral German adult population (aged 18–64 years).ParticipantsParticipants of the 2015 Epidemiological Survey of Substance Abuse (n=9204).Primary outcome measuresLifestyle risk factors (daily smoking, at-risk alcohol consumption, unhealthy diet, low physical activity, weekly use of pharmaceuticals, as well as consumption of cannabis and other illicit drugs).ResultsA latent class analysis was applied to identify patterns of lifestyle risk factors, and a multinomial logistic regression was carried out to examine associations between the extracted classes and external factors. A total of four classes were extracted which can be described as healthy lifestyle (58.5%), drinking lifestyle (24.4%), smoking lifestyle (15.4%) and a cumulate risk factors lifestyle (1.7%). Individuals who were male, at younger age and single as well as individuals with various mental health problems were more likely to show multiple lifestyle risk factors.ConclusionsHealthcare professionals should be aware of correlations between different lifestyle risk factors as well as between lifestyle risk groups and mental health. Health promotion strategies should further focus especially on younger and single men.

scholarly journals Partner alcohol use, violence and women's mental health: population-based survey in India

2010 ◽  
Vol 196 (3) ◽  
pp. 192-199 ◽  
Author(s):  
Madhabika B. Nayak ◽  
Vikram Patel ◽  
Jason C. Bond ◽  
Thomas K. Greenfield
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Alcohol Use ◽  
Mental Disorders ◽  
Partner Violence ◽  
Common Mental Disorders ◽  
Population Based ◽  
Poor Mental Health ◽  
Mediation Effects ◽  
The Relationship

BackgroundThe relationship between partner alcohol use and violence as risk factors for poor mental health in women is unclear.AimsTo describe partner-related and other psychosocial risk factors for common mental disorders in women and examine interrelationships between these factors.MethodData are reported on 821 women aged 18–49 years from a larger population study in north Goa, India. Logistic regression models evaluated the risks for women's common mental disorders and tested for mediation effects in the relationship between partner alcohol use and these disorders.ResultsExcessive partner alcohol use increased the risk for common mental disorders two- to threefold. Partner violence and alcohol-related problems each partially mediated the association between partner excessive alcohol use and these mental disorders. Women's own violence-related attitudes were also independently associated with them.ConclusionsPartner alcohol use, partner violence and women's violence-related attitudes must be addressed to prevent and treat common mental disorders in women.

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