Trajectory models summarized adherence patterns better than traditional approaches and were similarly predicted by covariates. Group-based trajectory models may facilitate targeting of interventions and may be useful to adjust for confounding by health-seeking behavior.

BackgroundAttention deficit hyperactivity disorder (ADHD) is a commonly diagnosed neuropsychiatric disorder in childhood, but the frequency of the condition is not well established in many countries. The aim of the present study was to quantify the overall prevalence of ADHD among children and adolescents in Spain by means of a systematic review and meta-analysis.MethodsPubMed/MEDLINE, IME, IBECS and TESEO were comprehensively searched. Original reports were selected if they provided data on prevalence estimates of ADHD among people under 18 years old in Spain and were cross-sectional, observational epidemiological studies. Information from included studies was systematically extracted and evaluated. Overall pooled-prevalence estimates of ADHD were calculated using random-effects models. Sources of heterogeneity were explored by means sub-groups analyses and univariate meta-regressions.ResultsFourteen epidemiological studies (13,026 subjects) were selected. The overall pooled-prevalence of ADHD was estimated at 6.8% [95% confidence interval (CI) 4.9 – 8.8%] representing 361,580 (95% CI 260,550 – 467,927) children and adolescents in the community. There was significant heterogeneity (P < 0.001), which was incompletely explained by subgroup analyses and meta-regressions.ConclusionsOur findings suggest that the prevalence of ADHD among children and adolescents in Spain is consistent with previous studies conducted in other countries and regions. This study represents a first step in estimating the national burden of ADHD that will be essential to building evidence-based programs and services.

ObjectiveTo identify adherence patterns over time and their predictors for evidence-based medications used after hospitalization for coronary heart disease (CHD).Patients and MethodsWe built a population-based retrospective cohort of all patients discharged after hospitalization for CHD from public hospitals in the Valencia region (Spain) during 2008 (n = 7462). From this initial cohort, we created 4 subcohorts with at least one prescription (filled or not) from each therapeutic group (antiplatelet, beta-blockers, ACEI/ARB, statins) within the first 3 months after discharge. Monthly adherence was defined as having ≥24 days covered out of 30, leading to a repeated binary outcome measure. We assessed the membership to trajectory groups of adherence using group-based trajectory models. We also analyzed predictors of the different adherence patterns using multinomial logistic regression.ResultsWe identified a maximum of 5 different adherence patterns: 1) Nearly-always adherent patients; 2) An early gap in adherence with a later recovery; 3) Brief gaps in medication use or occasional users; 4) A slow decline in adherence; and 5) A fast decline. These patterns represented variable proportions of patients, the descending trajectories being more frequent for the beta-blocker and ACEI/ARB cohorts (16% and 17%, respectively) than the antiplatelet and statin cohorts (10% and 8%, respectively). Predictors of poor or intermediate adherence patterns were having a main diagnosis of unstable angina or other forms of CHD vs. AMI in the index hospitalization, being born outside Spain, requiring copayment or being older.ConclusionDistinct adherence patterns over time and their predictors were identified. This may be a useful approach for targeting improvement interventions in patients with poor adherence patterns.