Early substance use disorders and subsequent NEET-not in education, employment or training-a national cohort study.

BACKGROUND: Substance use problems have been associated with poor labour market outcomes. This study investigated whether substance use disorders (SUD) in emerging adulthood increase the likelihood of later being not in employment, education or training (NEET). METHODS: A national cohort study of 23 5295 males and 227 792 females born between 1981 and 1987. SUD was assessed between ages 17 and 24 years. Logistic regression models were used to estimate the odds ratios (ORs) of NEET, between ages 25-34. Sibling-comparison analysis was performed to account for potential shared genetic and environmental factors. RESULTS: Having been diagnosed with a SUD was associated with the likelihood of being NEET among males [OR = 1.37, 95% confidence interval (CI), 1.25-1.49] and females (1.19, 1.13-1.27) after adjusting for domicile, origin, psychiatric diagnosis and parental psychiatric diagnosis. Early SUD was also associated with a gradual increase in the ORs of accumulation of years being NEET. This was more evident among females. In the sibling-comparison analysis, we found a higher OR of NEET among same-sex sibling males 1.39 (1.06-1.82) and females 1.28 (0.99-1.66) with SUD. These risks were fully attenuated when another psychiatric diagnosis was adjusted for. CONCLUSION: Early SUD was associated with an increased likelihood of being NEET in both males and females. Neither origin, domicile, psychiatric diagnoses nor parental psychiatric diagnoses did fully explain the association. The combination of unmeasured familial factors and having other psychiatric disorders largely explained these associations.

Characterization of data-driven clusters in diabetes-free adults and their utility for risk stratification of type 2 diabetes.

BACKGROUND: The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The aim of this study was to derive characteristic phenotypes using cluster analysis of common risk factors and to assess their utility to stratify the risk of type 2 diabetes. METHODS: Data on 7317 diabetes-free adults from Sweden were used in the main analysis and on 2332 diabetes-free adults from Mexico for external validation. Clusters were based on sex, family history of diabetes, educational attainment, fasting blood glucose and insulin levels, estimated insulin resistance and ß-cell function, systolic and diastolic blood pressure, and BMI. The risk of type 2 diabetes was assessed using Cox proportional hazards models. The predictive accuracy and long-term stability of the clusters were then compared to different definitions of prediabetes. RESULTS: Six risk phenotypes were identified independently in both cohorts: very low-risk (VLR), low-risk low ß-cell function (LRLB), low-risk high ß-cell function (LRHB), high-risk high blood pressure (HRHBP), high-risk ß-cell failure (HRBF), and high-risk insulin-resistant (HRIR). Compared to the LRHB cluster, the VLR and LRLB clusters showed a lower risk, while the HRHBP, HRBF, and HRIR clusters showed a higher risk of developing type 2 diabetes. The high-risk clusters, as a group, had a better predictive accuracy than prediabetes and adequate stability after 20 years. CONCLUSIONS: Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. These results could be used to develop more precise public health interventions.

Long-term air pollution exposure and Parkinson's disease mortality in a large pooled European cohort: An ELAPSE study.

BACKGROUND: The link between exposure to ambient air pollution and mortality from cardiorespiratory diseases is well established, while evidence on neurodegenerative disorders including Parkinson's Disease (PD) remains limited. OBJECTIVE: We examined the association between long-term exposure to ambient air pollution and PD mortality in seven European cohorts. METHODS: Within the project 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE), we pooled data from seven cohorts among six European countries. Annual mean residential concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and ozone (O3), as well as 8 PM2.5 components (copper, iron, potassium, nickel, sulphur, silicon, vanadium, zinc), for 2010 were estimated using Europe-wide hybrid land use regression models. PD mortality was defined as underlying cause of death being either PD, secondary Parkinsonism, or dementia in PD. We applied Cox proportional hazard models to investigate the associations between air pollution and PD mortality, adjusting for potential confounders. RESULTS: Of 271,720 cohort participants, 381 died from PD during 19.7 years of follow-up. In single-pollutant analyses, we observed positive associations between PD mortality and PM2.5 (hazard ratio per 5 µg/m3: 1.25; 95% confidence interval: 1.01-1.55), NO2 (1.13; 0.95-1.34 per 10 µg/m3), and BC (1.12; 0.94-1.34 per 0.5 × 10-5m-1), and a negative association with O3 (0.74; 0.58-0.94 per 10 µg/m3). Associations of PM2.5, NO2, and BC with PD mortality were linear without apparent lower thresholds. In two-pollutant models, associations with PM2.5 remained robust when adjusted for NO2 (1.24; 0.95-1.62) or BC (1.28; 0.96-1.71), whereas associations with NO2 or BC attenuated to null. O3 associations remained negative, but no longer statistically significant in models with PM2.5. We detected suggestive positive associations with the potassium component of PM2.5. CONCLUSION: Long-term exposure to PM2.5, at levels well below current EU air pollution limit values, may contribute to PD mortality.

Trajectories of NEET (Not in Education, Employment, and Training) in emerging adulthood, and later drug use disorder - a national cohort study.

BACKGROUND: Being not in education, employment, or training (NEET) has been associated with poor health outcomes. This study aimed to investigate the association between NEET during emerging adulthood and later drug use disorder (DUD) among males and females. METHOD: A national cohort comprising 383,116 Swedish males and 362,002 females born between 1984 and 1990. NEET exposure was assessed annually between the ages 17 and 24 years, and follow-up for DUD between ages 25-33. Trajectories of NEET were estimated using group-based trajectory analysis. Cox regression analysis was used to estimate hazard ratios (HR) of DUD. Sibling-comparison model was performed to account for potential shared genetic and environmental factors. RESULTS: Four trajectories of NEET were identified: "constant low", "transient peak", "late increase", and "constant high". Compared with the "constant low", all other trajectories were associated with increased HRs of DUD. HR was highest among males and females in the "late increase trajectory"; HR = 4.10 (3.79-4.44, 95% CI) and HR = 3.73 (3.29-4.24, 95% CI), after adjusting for domicile, origin, birth year, psychiatric diagnoses, and parental psychiatric diagnoses. This association was reduced to about a twofold increased risk in the sibling comparison analysis. CONCLUSION: Being NEET during emerging adulthood was associated with later DUD for both males and females. Neither origin, psychiatric diagnoses, parental psychiatric diagnoses, nor shared familial factors did fully explain the association. Males and females belonging to the late increase NEET trajectory had about a twofold increased risk of DUD.

Using Distributed Lag Non-Linear Models to Estimate Exposure Lag-Response Associations between Long-Term Air Pollution Exposure and Incidence of Cardiovascular Disease.

Long-term air pollution exposure increases the risk for cardiovascular disease, but little is known about the temporal relationships between exposure and health outcomes. This study aims to estimate the exposure-lag response between air pollution exposure and risk for ischemic heart disease (IHD) and stroke incidence by applying distributed lag non-linear models (DLNMs). Annual mean concentrations of particles with aerodynamic diameter less than 2.5 µm (PM2.5) and black carbon (BC) were estimated for participants in five Swedish cohorts using dispersion models. Simultaneous estimates of exposure lags 1-10 years using DLNMs were compared with separate year specific (single lag) estimates and estimates for lag 1-5- and 6-10-years using moving average exposure. The DLNM estimated no exposure lag-response between PM2.5 total, BC, and IHD. However, for PM2.5 from local sources, a 20% risk increase per 1 µg/m3 for 1-year lag was estimated. A risk increase for stroke was suggested in relation to lags 2-4-year PM2.5 and BC, and also lags 8-9-years BC. No associations were shown in single lag models. Increased risk estimates for stroke in relation to lag 1-5- and 6-10-years BC moving averages were observed. Estimates generally supported a greater contribution to increased risk from exposure windows closer in time to incident IHD and incident stroke.

Life-course trajectories of weight and their impact on the incidence of type 2 diabetes.

Although exposure to overweight and obesity at different ages is associated to a higher risk of type 2 diabetes, the effect of different patterns of exposure through life remains unclear. We aimed to characterize life-course trajectories of weight categories and estimate their impact on the incidence of type 2 diabetes. We categorized the weight of 7203 participants as lean, normal or overweight at five time-points from ages 7-55 using retrospective data. Participants were followed for an average of 19 years for the development of type 2 diabetes. We used latent class analysis to describe distinctive trajectories and estimated the risk ratio, absolute risk difference and population attributable fraction (PAF) associated to different trajectories using Poisson regression. We found five distinctive life-course trajectories. Using the stable-normal weight trajectory as reference, the stable overweight, lean increasing weight, overweight from early adulthood and overweight from late adulthood trajectories were associated to higher risk of type 2 diabetes. The estimated risk ratios and absolute risk differences were statistically significant for all trajectories, except for the risk ratio of the lean increasing trajectory group among men. Of the 981 incident cases of type 2 diabetes, 47.4% among women and 42.9% among men were attributable to exposure to any life-course trajectory different from stable normal weight. Most of the risk was attributable to trajectories including overweight or obesity at any point of life (36.8% of the cases among women and 36.7% among men). The overweight from early adulthood trajectory had the highest impact (PAF: 23.2% for woman and 28.5% for men). We described five distinctive life-course trajectories of weight that were associated to increased risk of type 2 diabetes over 19 years of follow-up. The variability of the effect of exposure to overweight and obesity on the risk of developing type 2 diabetes was largely explained by exposure to the different life-course trajectories of weight.

The Effect of Smartphone Apps Versus Supervised Exercise on Physical Activity, Cardiorespiratory Fitness, and Body Composition Among Individuals With Mild-to-Moderate Mobility Disability: Randomized Controlled Trial.

BACKGROUND: Adequate levels of physical activity (PA) and good cardiorespiratory fitness (CRF) are associated with profound health benefits for individuals with mobility disability (MD). Despite the vast amount of research published in the field of PA interventions, little attention has been given to individuals with MD. OBJECTIVE: The aim of this study was to examine the efficacy of an app-based versus a supervised exercise and health coaching program to support adults with MD to increase levels of PA, CRF, and improve body composition. METHODS: Participants with self-perceived MD, aged 18 to 45 years, were included in this 12-week parallel-group randomized controlled trial and allocated at random to an app-based intervention, using commercially available apps-the Swedish Military training app (FMTK), the Acupedo walking app, and the LogMyFood food photography app-or a supervised exercise and health coaching intervention, including 1 weekly supervised exercise session and healthy lifestyle coaching. The primary outcome was the level of moderate-to-vigorous PA (MVPA) measured with accelerometers. Secondary outcomes included CRF measured by a submaximal test performed on a stationary bicycle and body composition measured by bioelectrical impedance. All outcomes were measured at baseline, 6 weeks, and 12 weeks. Linear mixed-effect models were used to assess the between-group differences, as well as the within-group changes through time, in each intervention group. RESULTS: A total of 110 participants with MD were randomized to an app-based intervention (n=55) or a supervised exercise and health intervention (n=55). The mean age of participants was 34.9 years (SD 6.1), and 81.8% (90/110) of the participants were women. CRF showed a moderate increase in both groups after 12 weeks-1.07 (95% CI -0.14 to 2.27) mL/kg/min increase in the app-based group and 1.76 (95% CI 0.70 to 2.83) mLkg/min increase in the supervised exercise group. However, the intention-to-treat analysis showed no significant differences between the groups in MVPA or CRF after 12 weeks. Waist circumference was significantly lower in the app-based intervention group. CONCLUSIONS: Commercially available apps increased levels of CRF and improved body composition over 12 weeks to the same extent as supervised exercise sessions, showing that both are equally effective. However, neither the app-based intervention nor the supervised exercise intervention increased MVPA. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN): 22387524; http://isrctn.com/ISRCTN22387524.

Childhood adversities, negative life events and outcomes of non-pharmacological treatments for depression in primary care: A secondary analysis of a randomized controlled trial.

Non-pharmacological treatments for depression are effective and available in primary care, but useful prognostic factors are lacking. Childhood adversities (CA) and negative recent life events (RLE) increase the risk and severity of depression, though their effect on treatment outcomes remains understudied. Using a sample of 737 adult participants of a multicenter randomized controlled trial receiving physical exercise, internet based cognitive-behavioral therapy or treatment as usual, alone or in combination with antidepressants, this prospective study aimed to determine the impact of CA, RLE and their interaction as predictors of outcomes of non-pharmacological treatments for mild-moderate depression in primary care. Outcomes were depression severity (MADRS score) and response to treatment (≥50% reduction in MADRS score) after three months. Linear regression and modified Poisson regression were used, interaction was assessed with a product term (CA*RLE) and epidemiological measures of interaction. The number of CA and RLE were associated with higher depression severity at follow-up (CA: ß = 0.79, 95% CI: 0.14 to 1.44 and RLE: ß = 0.52, 95% CI: 0.14 to 0.72) and showed a trend towards lower rates of response to treatment (RR = 0.94, 95% CI: 0.86 to 1.03; and RLE: RR = 0.95, 95% CI: 0.90 to 0.99). Interaction between CA and RLE was not significant for depression severity (ß = 0.10, 95% CI: -2.12 to 0.41) nor for response to treatment (RERI = -0.05, 95% CI = -0.33 to 0.24). CA and RLE are associated with worse outcomes of non-pharmacological treatments in primary care. Further studies to identify predictors of outcomes of non-pharmaological treatments for depression are needed.