Research on the association between SEP and statin adherence has mainly defined adherence through measures that reduce longitudinal medication-taking behavior into a single number, 12,13 such as the proportion of days covered (PDC). 7,9 Although this simplification is appealing, it leads to loss of information on medication-taking patterns over time. Group-based trajectory modeling (GBTM) 15 offers an alternative method for summarizing longitudinal data on medication Background-Previous research shows that low socioeconomic position (SEP; especially low income) is associated with statin nonadherence. We investigated the relationship between SEP and statin adherence in a country with universal coverage using group-based trajectory modeling in addition to the proportion of days covered. Methods and Results-Using data from Finnish healthcare registers, we identified 116 846 individuals, aged 45 to 75 years, who initiated statin therapy for primary prevention of cardiovascular disease. We measured adherence as proportion of days covered over an 18-month period since initiation and identified different adherence patterns based on monthly adherence with group-based trajectory modeling. When adjusted for age, marital status, residential area, clinical characteristics, and copayment, low SEP was associated with statin nonadherence (proportion of days covered <80%) among men (eg, lowest versus highest income quintile: odds ratio, 1.41; 95% confidence interval, 1.32-1.50; basic versus higher-degree education: odds ratio, 1.18; 95% confidence interval, 1.13-1.24; unemployment versus employment: odds ratio, 1.17; 95% confidence interval, 1.10-1.25). Among women, the corresponding associations were different (P<0.001 for sex-byincome quintile, sex-by-education level, and sex-by-labor market status interactions) and mainly nonsignificant. Results based on adherence trajectories showed that men in low SEP were likely to belong to trajectories presenting a fast decline in adherence. Conclusions-Low SEP was associated with overall and rapidly increasing statin nonadherence among men. Conversely, in women, associations between SEP and nonadherence were weak and inconsistent. adherence. GBTM accounts for the dynamic nature of adherence and identifies long-term patterns of the repeatedly measured adherence and groups of individuals with similar patterns. 16,17 Statin adherence trajectories have also been shown to predict cardiovascular events. 18Despite the universal healthcare, socioeconomic disparities in CVD have been documented also in Finland: lower SEP has been associated with higher CVD morbidity and mortality, lower use of statins, and lower revascularization rates. 3,[19][20][21] The aim of our study was to determine the association of SEP with nonadherence and adherence trajectories in Finnish patients initiating statin therapy for primary prevention of CVD. To refine the estimation of the effect of SEP on statin nonadherence, we measured adherence as 18-month adherence trajectories in addition to a conventional dichot...
Background Knee osteoarthritis (OA) worsens health-related quality of life (HRQoL) but the symptom pathway varies from person to person. We aimed to identify groups of people with knee OA or at its increased risk whose HRQoL changed similarly. Our secondary aim was to evaluate if patient-related characteristics, incidence of knee replacement (KR) and prevalence of pain medication use differed between the identified HRQoL trajectory groups. Methods Eight-year follow-up data of 3053 persons with mild knee OA or at increased risk were obtained from the public Osteoarthritis Initiative (OAI) database. Group-based trajectory modeling was used to identify patterns of experiencing a decrease of ≥10 points (Minimal Important Change, MIC) in the Quality of Life subscale of the Knee injury and Osteoarthritis Outcome Score compared to baseline. Multinomial logistic regression, Cox regression and generalized estimating equation models were used to study secondary aims. Results Four HRQoL trajectory groups were identified. Persons in the ‘no change’ group (62.9%) experienced no worsening in HRQoL. ‘Rapidly’ (9.5%) and ‘slowly’ worsening (17.1%) groups displayed an increasing probability of experiencing the MIC in HRQoL. The fourth group (10.4%) had ‘improving’ HRQoL. Female gender, higher body mass index, smoking, knee pain, and lower income at baseline were associated with belonging to the ‘rapidly worsening’ group. People in ‘rapidly’ (hazard ratio (HR) 6.2, 95% confidence interval (CI) 3.6–10.7) and ‘slowly’ worsening (HR 3.4, 95% CI 2.0–5.9) groups had an increased risk of requiring knee replacement. Pain medication was more rarely used in the ‘no change’ than in the other groups. Conclusions HRQoL worsening was associated with several risk factors; surgical and pharmacological interventions were more common in the poorer HRQoL trajectory groups indicating that HRQoL does reflect the need for OA treatment. These findings may have implications for targeting interventions to specific knee OA patient groups.
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