Costs of Public Health Screening of Children for Presymptomatic Type 1 Diabetes in Bavaria, Germany.

OBJECTIVE: We sought to evaluate costs associated with public health screening for presymptomatic type 1 diabetes in 90,632 children as part of the Fr1da study in Bavaria and in forecasts for standard care. RESEARCH DESIGN AND METHODS: We report on resource use and direct costs for screening-related procedures in the Fr1da study coordination center and laboratory and in participating pediatric practices and local diabetes clinics. Data were obtained from Fr1da study documents, an online survey among pediatricians, and interviews and records of Fr1da staff members. Data were analyzed with tree models that mimic procedures during the screening process. Cost estimates are presented as they were observed in the Fr1da study and as they can be expected in standard care for various scenarios. RESULTS: The costs per child screened in the Fr1da study were €28.17 (95% CI 19.96; 39.63) and the costs per child diagnosed with presymptomatic type 1 diabetes were €9,117 (6,460; 12,827). Assuming a prevalence of presymptomatic type 1 diabetes of 0.31%, as in the Fr1da study, the estimated costs in standard care in Germany would be €21.73 (16.76; 28.19) per screened child and €7,035 (5,426; 9,124) per diagnosed child. Of the projected screening costs, €12.25 would be the costs in the medical practice, €9.34 for coordination and laboratory, and €0.14 for local diabetes clinics. CONCLUSIONS: This study provides information for the planning and implementation of screening tests for presymptomatic type 1 diabetes in the general public and for the analysis of the cost-effectiveness of targeted prevention strategies.

Simulation Modeling for the Economic Evaluation of Population-Based Dietary Policies: A Systematic Scoping Review.

Simulation modeling can be useful to estimate the long-term health and economic impacts of population-based dietary policies. We conducted a systematic scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guideline to map and critically appraise economic evaluations of population-based dietary policies using simulation models. We searched Medline, Embase, and EconLit for studies published in English after 2005. Modeling studies were mapped based on model type, dietary policy, and nutritional target, and modeled risk factor-outcome pathways were analyzed. We included 56 studies comprising 136 model applications evaluating dietary policies in 21 countries. The policies most often assessed were reformulation (34/136), taxation (27/136), and labeling (20/136); the most common targets were salt/sodium (60/136), sugar-sweetened beverages (31/136), and fruit and vegetables (15/136). Model types included Markov-type (35/56), microsimulation (11/56), and comparative risk assessment (7/56) models. Overall, the key diet-related risk factors and health outcomes were modeled, but only 1 study included overall diet quality as a risk factor. Information about validation was only reported in 19 of 56 studies and few studies (14/56) analyzed the equity impacts of policies. Commonly included cost components were health sector (52/56) and public sector implementation costs (35/56), as opposed to private sector (18/56), lost productivity (11/56), and informal care costs (3/56). Most dietary policies (103/136) were evaluated as cost-saving independent of the applied costing perspective. An analysis of the main limitations reported by authors revealed that model validity, uncertainty of dietary effect estimates, and long-term intervention assumptions necessitate a careful interpretation of results. In conclusion, simulation modeling is widely applied in the economic evaluation of population-based dietary policies but rarely takes dietary complexity and the equity dimensions of policies into account. To increase relevance for policymakers and support diet-related disease prevention, economic effects beyond the health sector should be considered, and transparent conduct and reporting of model validation should be improved.

Utility Decrements Associated With Diabetes and Related Complications: Estimates From a Population-Based Study in Germany.

OBJECTIVES: Health utility decrement estimates for diabetes and complications are needed for parametrization of simulation models that aim to assess the cost-utility of diabetes prevention and care strategies. This study estimates health utility decrements associated with diabetes and cardiovascular and microvascular complications from a population-based German study. METHODS: Data were obtained from the population based cross-sectional KORA (Cooperative Health Research in the Augsburg Region) health questionnaire 2016 and comprised n = 1072 individuals with type 2 diabetes and n = 7879 individuals without diabetes. Health utility was assessed through the EQ-5D-5L. We used linear regression models with interaction terms between type 2 diabetes and different cardiovascular and microvascular complications while adjusting for demographic and socio-economic factors and other comorbidities. RESULTS: Type 2 diabetes (ß = -0.028, standard error [SE] = 0.014), stroke (ß = -0.070, SE = 0.010), cardiac arrhythmia (ß = -0.031, SE = 0.006), heart failure (ß = -0.073, SE = 0.009), coronary heart disease (ß = -0.028, SE = 0.010), myocardial infarction (ß = -0.020, SE = 0.011, estimates of main effect), and neuropathy (ß = -0.067, SE = 0.020), diabetic foot (ß = -0.042, SE = 0.030), nephropathy (ß = -0.032, SE = 0.025), and blindness (ß = -0.094, SE = 0.056, estimates of interaction terms) were negatively associated with health utility. The interaction term for diabetes x stroke (ß = -0.052, SE = 0.021) showed that the utility decrement for stroke is significantly larger in people with type 2 diabetes than in people without diabetes. CONCLUSIONS: Diabetes, cardiovascular, and microvascular conditions are associated with significant health utility decrements. Utility decrements for some conditions differ between people with and without type 2 diabetes. These results are of high relevance for the parametrization of decision analytic simulation models and applied health economic evaluations in the field of prevention and management of type 2 diabetes in Germany.

Status quo bias and health behavior: findings from a cross-sectional study.

BACKGROUND: Status quo bias (SQB) has often been referred to as an important tool for improving public health. However, very few studies were able to link SQB with health behavior. METHODS: Analysis were based on data from the population-based KORA S4 study (1999-2001, n = 2309). We operationalized SQB through two questions. The first asked whether participants switched their health insurance for financial benefits since this was enabled in 1996. Those who did were assigned a 'very low SQB' (n = 213). Participants who did not switch were asked a second hypothetical question regarding switching costs. We assigned 'low SQB' to those who indicated low switching costs (n = 1035), 'high SQB' to those who indicated high switching costs (n = 588), and 'very high SQB' to those who indicated infinite switching costs (n = 473). We tested the association between SQB and physical activity, diet, smoking, alcohol consumption, the sum of health behaviors, and body mass index (BMI) using logistic, Poisson and ordinary least square regression models, respectively. Models were adjusted for age, sex, education, income, satisfaction with current health insurance and morbidity. RESULTS: SQB was associated with a higher rate of physical inactivity [OR = 1.22, 95% CI (1.11; 1.35)], a higher sum of unhealthy lifestyle factors [IRR = 1.05, 95% CI (1.01; 1.10)] and a higher BMI [ß = 0.30, 95% CI (0.08; 0.51)]. CONCLUSION: A high SQB was associated with unfavorable health behavior and higher BMI. Targeting SQB might be a promising strategy for promoting healthy behavior.

Direct healthcare costs associated with device assessed and self-reported physical activity: results from a cross-sectional population-based study.

BACKGROUND: Physical inactivity (PIA) is an important risk factor for many chronic conditions and therefore might increase healthcare utilization and costs. This study aimed to analyze the association of PIA using device assessed and self-reported physical activity (PA) data with direct healthcare costs. METHODS: Cross-sectional data was retrieved from the population based KORA FF4 study (Cooperative Health Research in the Region of Augsburg) that was conducted in southern Germany from 2013 to 2014 (n = 2279). Self-reported PA was assessed with two questions regarding sports related PA in summer and winter and categorized into "high activity", "moderate activity", "low activity" and "no activity". In a subsample (n = 477), PA was assessed with accelerometers and participants were categorized into activity quartiles ("very high", "high", "low" and "very low") according to their mean minutes per day spent in light intensity, or in moderate-vigorous PA (MVPA). Self-reported healthcare utilization was used to estimate direct healthcare costs. We regressed direct healthcare costs on PA using a two-part gamma regression, adjusted for age, sex and socio-demographic variables. Additional models, including and excluding potential additional confounders and effect mediators were used to check the robustness of the results. RESULTS: Annual direct healthcare costs of individuals who reported no sports PA did not differ from those who reported high sports PA [+€189, 95% CI: -188, 598]. In the subsample with accelerometer data, participants with very low MVPA had significantly higher annual costs than participants with very high MVPA [+€986, 95% CI: 15, 1982]. CONCLUSION: Device assessed but not self-reported PIA was associated with higher direct healthcare costs. The magnitude and significance of the association depended on the choice of covariates in the regression models. Larger studies with device assessed PA and longitudinal design are needed to be able to better quantify the impact of PIA on direct healthcare costs.

Applying the health action process approach to bicycle helmet use and evaluating a social marketing campaign.

BACKGROUND: Bicycle injuries are of concern in Canada. Since helmet use was mandated in 1996 in the province of British Columbia, Canada, use has increased and head injuries have decreased. Despite the law, many cyclists do not wear a helmet. Health action process approach (HAPA) model explains intention and behaviour with self-efficacy, risk perception, outcome expectancies and planning constructs. The present study examines the impact of a social marketing campaign on HAPA constructs in the context of bicycle helmet use. METHOD: A questionnaire was administered to identify factors determining helmet use. Intention to obey the law, and perceived risk of being caught if not obeying the law were included as additional constructs. Path analysis was used to extract the strongest influences on intention and behaviour. The social marketing campaign was evaluated through t-test comparisons after propensity score matching and generalised linear modelling (GLM) were applied to adjust for the same covariates. RESULTS: 400 cyclists aged 25-54 years completed the questionnaire. Self-efficacy and Intention were most predictive of intention to wear a helmet, which, moderated by planning, strongly predicted behaviour. Perceived risk and outcome expectancies had no significant impact on intention. GLM showed that exposure to the campaign was significantly associated with higher values in self-efficacy, intention and bicycle helmet use. CONCLUSION: Self-efficacy and planning are important points of action for promoting helmet use. Social marketing campaigns that remind people of appropriate preventive action have an impact on behaviour.

Costs and health-related quality of life in Alpha-1-Antitrypsin Deficient COPD patients.

BACKGROUND: Alpha-1-Antitrypsin Deficiency (AATD) is an economically unexplored genetic disease. METHODS: Direct and indirect costs (based on self-reported information on healthcare utilization) and health-related quality of life (HRQL, as assessed by SGRQ, CAT, and EQ-5D-3 L) were compared between 131 AATD patients (106 with, 25 without augmentation therapy (AT)) and 2,049 COPD patients without AATD participating in the COSYCONET COPD cohort. The medication costs of AT were excluded from all analyses to reveal differences associated with morbidity profiles. The association of AATD (with/without AT) with costs or HRQL was examined using generalized linear regression modelling (GLM) adjusting for age, sex, GOLD grade, BMI, smoking status, education and comorbidities. RESULTS: Adjusted mean direct annual costs were €6,099 in AATD patients without AT, €7,117 in AATD patients with AT (excluding costs for AT), and €7,460 in COPD patients without AATD. AATD with AT was significantly associated with higher outpatient (+273%) but lower inpatient (-35%) and medication costs (-10%, disregarding AT) compared with COPD patients without AATD. There were no significant differences between groups regarding indirect costs and HRQL. CONCLUSION: Apart from AT costs, AATD patients tended to have lower, though not significant, overall costs and similar HRQL compared to COPD patients without AATD. AT was not associated with lower costs or higher HRQL. TRIAL REGISTRATION: NCT01245933.