DESIGN, SETTING AND PARTICIPANTS: Ten-year horizon (2016-25) modeling study of opioid addiction epidemic and treatment that accommodated potential peer effects in opioid use initiation and supply-induced treatment demand in three Ukrainian cities: Kyiv, Mykolaiv and Lviv, comprising a simulated population of people at risk of and with OUD.
MEASUREMENTS: Incremental cost per quality-adjusted life-year gained in the simulated population.
FINDINGS: An estimated 12.2-, 2.4- and 13.4-fold OAT capacity increase over 2016 baseline capacity in Kyiv, Mykolaiv and Lviv, respectively, would be cost-effective at a willingness-to-pay of one per-capita gross domestic product (GDP) per quality-adjusted life-year gained. This result is robust to parametric and structural uncertainty. Even under the most ambitious capacity increase, OAT coverage (i.e. the proportion of people with OUD receiving OAT) over a 10-year modeling horizon would be 20, 11 and 17% in Kyiv, Mykolaiv and Lviv, respectively, owing to limited demand.
CONCLUSIONS: It is estimated that a substantial increase in opioid agonist treatment (OAT) capacity in three Ukrainian cities would be cost-effective for a wide range of willingness-to-pay thresholds. Even a very ambitious capacity increase, however, is unlikely to reach internationally recommended coverage levels. Further increases in coverage may be limited by demand and would require addressing existing structural barriers to OAT access.
METHOD: The study included 2322 community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, biomarkers, psychosocial status, disability, and cognitive function. A biopsychosocial model of cognitive function was developed to test variables' predictive power on cognitive function. Statistical analyses were performed using SPSS (version 15.0) in conjunction with Analysis of Moment Structures Graphics (AMOS 7.0).
RESULTS: The estimated theoretical model fitted the data well. Psychosocial stress and metabolic syndrome (MetS) negatively predicted cognitive function and psychosocial stress appeared as a main predictor. Socio-demographic characteristics, except gender, also had significant effects on cognitive function. However, disability failed to predict cognitive function.
CONCLUSION: Several factors together may predict cognitive function in the Malaysian elderly population, and the variance accounted for it is large enough to be considered substantial. Key factor associated with the elderly's cognitive function seems to be psychosocial well-being. Thus, psychosocial well-being should be included in the elderly assessment, apart from medical conditions, both in clinical and community setting.