METHODS: Systematic literature searches in accordance with PRISMA guidelines found 51 eligible studies that met inclusion criteria. Eight studies utilized both Waves 1 and 2 NESARC data, and selection of sample sizes varied from 185 to 43,093 individuals, consistent with specified research objectives of each study.
RESULTS: The prevalence of lifetime pathological gambling was 0.42% (0.64% among men, 0.23% among women), while past-year prevalence was 0.16%. Pathological gambling rates were generally higher in populations with substance-use disorders and other psychiatric diagnoses. Rates of adverse childhood experiences and suicidal attempts were higher among individuals with problem or pathological gambling. Early-onset gamblers were more likely to be male, be never married, have incomes below $70,000, belong to younger cohorts and have Cluster B personality disorders, but less likely to be diagnosed with mood disorders. While pathological gambling was related to obesity, increased stress, and poorer physical health among general age groups, recreational gambling was linked with improved physical and mental functioning in older adults.
CONCLUSIONS: The NESARC has provided important information on the correlates of pathological gambling and subdiagnostic patterns of gambling behaviors. Additional studies should examine these relationships in the current gambling environment and longitudinally with aims of implementing policies to improve the public health.
METHODS: To fill this gap, electronic databases including PubMed, Scopus, Science Direct, Sagepub, CINAHL, Psychology, and Behavioral Sciences Collection were searched for relevant studies. A total of 16 studies were included in the systematic review.
RESULTS: The analyses showed that the prevalence of depression, anxiety, and stress ranged from 14.3% to 81.7%, 8.0% to 81.7%, and 0.9% to 56.5% respectively. Adult populations demonstrated the highest prevalence of depression, whereas university students reported the highest prevalence of anxiety and stress. Several factors were associated with mental health conditions including age, gender, family income, and perception of COVID-19.
CONCLUSION: Differentials in mental health screening practices call for standardised screening practices. Mental health intervention should be targeted at high-risk populations with effective risk communication.
METHODS: The study included individuals from the Northern Finland Birth Cohort 1966 (NFBC1966) who had available data for adiposity measures (body mass index and waist-to-hip ratio), alexithymia (measured by the 20-Item Toronto Alexithymia Scale: TAS-20), depressive symptoms (measured by the 13-item depression subscale of Hopkins Symptom Checklist: HSCL-13) at age of 31 years (n = 4773) and 46 years (n = 4431). Pearson's (r) correlation, and multiple linear regression were used to investigate the relationships between alexithymia, depressive symptoms, and adiposity measures. The potential mediating role of depressive symptoms was examined via Hayes' procedure (PROCESS).
RESULTS: Positive correlations were confirmed between adiposity measures (BMI and WHR) and the TAS-20 score (and its subscale), but not between obesity and HSCL-13 score. The strongest correlation was between the DIF (difficulty identifying feelings) subscale of the TAS-20 and HSCL-13 at both time points (31 y: r(3013) = 0.41, p