ObjectivesStudies in clinical settings showed a potential relationship between socioeconomic status (SES) and lifestyle factors with COVID-19, but it is still unknown whether this holds in the general population. In this study, we investigated the associations of SES with self-reported, tested and diagnosed COVID-19 status in the general population.Design, setting, participants and outcome measuresParticipants were 49 474 men and women (46±12 years) residing in the Northern Netherlands from the Lifelines cohort study. SES indicators and lifestyle factors (i.e., smoking status, physical activity, alcohol intake, diet quality, sleep time and TV watching time) were assessed by questionnaire from the Lifelines Biobank. Self-reported, tested and diagnosed COVID-19 status was obtained from the Lifelines COVID-19 questionnaire.ResultsThere were 4711 participants who self-reported having had a COVID-19 infection, 2883 participants tested for COVID-19, and 123 positive cases were diagnosed in this study population. After adjustment for age, sex, lifestyle factors, body mass index and ethnicity, we found that participants with low education or low income were less likely to self-report a COVID-19 infection (OR [95% CI]: low education 0.78 [0.71 to 0.86]; low income 0.86 [0.79 to 0.93]) and be tested for COVID-19 (OR [95% CI]: low education 0.58 [0.52 to 0.66]; low income 0.86 [0.78 to 0.95]) compared with high education or high income groups, respectively.ConclusionOur findings suggest that the low SES group was the most vulnerable population to self-reported and tested COVID-19 status in the general population.

Objectives. This study aimed to assess the cost-effectiveness of treatments for attention-deficit/hyperactivity disorder (ADHD) in children through prevention of serious delinquent behavior. Cost-effectiveness was assessed in net-monetary benefit (NMB). Methods. To evaluate the three major forms of ADHD treatment (medication management, behavioral treatment, and the combination thereof) relative to community-delivered treatment (control condition), we used data from 448 children, aged 7 to 10, who participated in the National Institute of Mental Health’s Multimodal Treatment Study of Children with ADHD. We developed a three-state continuous-time Markov model (no delinquency, minor to moderate delinquency, serious delinquency) to extrapolate the results 10 years beyond the 14-month trial period at a 3% discount rate. Serious delinquency was considered an absorbing state to enable assessment in life-years (LYs) of serious delinquent behavior prevented. The willingness-to-pay (WTP) threshold was set equal to the annual cost associated with serious delinquency in children with ADHD of $12,370. Results. Modeled and observed outcomes matched closely with a mean difference of 6.9% in LYs of serious delinquent behavior prevented. The economic evaluation revealed a NMB of $95,449, $88,553, $90,536 and $98,660 for medication management, behavioral treatment, combined treatment, and routine community care, respectively. Estimates remained stable after linearly increasing the WTP threshold between $0 and $50,000 in the deterministic sensitivity analyses. Conclusions. This study assessed the cost-effectiveness of treatments for ADHD in children using continuous-time Markov modeling. We show that treatment evaluation in broader societal outcomes is essential for policy makers, as the three major forms of ADHD treatment turned out to be inferior to the control condition.

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