Increasing Depression and Substance Use Among Former Smokers in the United States, 2002-2016

Determinants of Depression in Indonesian Youth: Findings From a Community-based Survey

Objectives

This study investigated the determinants of depression in adolescents and young adults.

Methods

The present study analyzed data from the 2018 Indonesia Basic Health Survey (Riset Kesehatan Dasar; RISKESDAS). The study subjects were adolescents (15-17 years old) and young adults (18-24 years old). In total, 64 179 subjects were included. Univariable, bivariable, and multivariable logistic regression analyses were performed to determine associations between youths’ characteristics, risky behavior, chronic disease, parents’ health, and youths’ depression.

Results

The prevalence of depression was 5.1% in adolescents and 5.6% in young adults. The risk factors for depression in adolescents were being women (adjusted odds ratio [aOR], 3.53; 95% confidence interval [CI], 2.89 to 4.30; p<0.001), an ex-smoker (aOR, 2.99; 95% CI, 2.10 to 4.25; p<0.001), or a current smoker (aOR, 2.60; 95% CI, 1.97 to 3.44; p<0.001); consuming alcohol (aOR, 2.00; 95% CI, 1.33 to 3.01; p=0.001), having a chronic disease (aOR, 2.64; 95% CI, 1.41 to 4.96; p=0.002); maternal depression (aOR, 2.47; 95% CI, 1.97 to 3.09; p<0.001); and paternal depression (aOR, 2.63; 95% CI, 1.98 to 3.50; p<0.001). In young adults, the risk factors were being women (aOR, 2.23; 95% CI, 1.82 to 2.75; p<0.001) or an ex-smoker (aOR, 2.47; 95% CI, 1.67 to 3.67; p<0.001), consuming alcohol (aOR, 2.42; 95% CI, 1.89 to 3.09; p<0.001), maternal depression (aOR, 3.12; 95% CI, 2.54 to 3.84; p<0.001), and paternal depression (aOR, 2.80; 95% CI, 2.17 to 3.63; p<0.001).

Conclusions

Being women, smoking, drinking alcohol, having a chronic disease, and having a parent with depression were crucial factors associated with youth depression. Mental health screening, prevention, and treatment should involve collaboration among primary healthcare, schools, universities, professionals, and families.

Effects of morbidity on smoking cessation: a national smoking cessation program

Background

In smokers with chronic diseases, we examined the abstinence rates over 6 months and its affecting factors in the context of the Korea National Health Insurance Service (NHIS) smoking cessation program.

Methods

To identify 6-month abstinence, we extracted a sample of 15,017 participants using the multi-stage stratified cluster sampling method from the 359,047 individuals enrolled in the 2016 NHIS smoking cessation program and 1500 smokers responded to the telephone survey. From this group, 1245 individuals (48.50 ± 12.55 years; men 89.8%) were enrolled, as they had no missing information for confounding variables. We compared chronic disease distribution between participants and current smokers in the 2016 Korea National Health and Nutrition Examination Survey. We evaluated the factors affecting continuous abstinence rate (CAR) across patients with different chronic diseases: hypertension, diabetes mellitus (DM), dyslipidemia (DL), chronic obstructive pulmonary disease, and major depressive disorder (MDD).

Results

While participation of DM patients was high, the participation of DL patients was relatively low. The CAR over 6 months was 44.74%. The adjusted odds ratio (OR) for continuous abstinence over 6 months was significantly lower in the MDD group than in the no-MDD group (OR 0.43, 95% confidence interval [CI] 0.21 to 0.85). The factors of program completion (complete versus incomplete: OR 3.11, 95% CI 2.43 to 3.98), region (non-metropolitan areas versus Seoul metropolitan area: OR 1.28, 95% CI 1.01 to 1.61), and nicotine dependence (severe versus light or moderate: OR 0.64, 95% CI 0.50 to 0.83) were significantly associated with CAR.

Conclusions

The smoking cessation program was not actively recruiting smokers with chronic diseases. The CARs in each disease group were not different from those in the non-disease groups, except that the MDD group had a lower CAR over 6 months than the no-MDD group. Recruiting smokers with chronic diseases and improving their CARs depends on the careful identification of their characteristics.