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  • BURDEN  (1)
  • COMORBIDITY  (1)
  • 1
    Keywords: DISEASE ; RISK-FACTORS ; REGION ; OVERWEIGHT ; WAIST CIRCUMFERENCE ; BURDEN ; ILLNESS RATING-SCALE ; SEVERE OBESITY ; CARE COSTS ; AUGSBURG
    Abstract: Methods: this cross-sectional analysis used data of n = 3,108 individuals aged 58-82 from a population-based prospective cohort study. Body mass index (BMI) and waist-to-height ratio (WHtR) were calculated based on clinical examinations. Health service use was measured by a questionnaire for a 3-month period. Corresponding costs were calculated applying a societal perspective. Results: 21.8% of the sample were normal weight, 43.0% overweight, 25.5% obese class 1 and 9.6% obese class a parts per thousand yen2 according to BMI. In 42.6%, WHtR was a parts per thousand yen0.6. For normal weight, overweight, obese class 1 and obese class a parts per thousand yen2 individuals, mean costs (3-month period) of outpatient care were 384a,not sign, 435a,not sign, 475a,not sign and 525a,not sign (P 〈 0.001), mean costs of inpatient care were 284a,not sign, 408a,not sign, 333a,not sign and 652a,not sign (P = 0.070) and mean total costs 716a,not sign, 891a,not sign, 852a,not sign and 1,244a,not sign (P = 0.013). For individuals with WHtR 〈 0.6 versus a parts per thousand yen0.6, outpatient costs were 401a,not sign versus 499a,not sign (P 〈 0.001), inpatient costs 315a,not sign versus 480a,not sign (P = 0.016) and total costs 755a,not sign versus 1,041a,not sign (P 〈 0.001). Multiple regression analyses controlling for sociodemographic variables showed a significant effect of obesity on costs of outpatient care (class 1: +72a,not sign; class a parts per thousand yen2: +153a,not sign) and total costs (class a parts per thousand yen2: +361a,not sign) while the effect of overweight was not significant. WHtR a parts per thousand yen0.6 significantly increased outpatient costs by +79a,not sign and total costs by +189a,not sign. Conclusions: excess weight is associated with increased service use and cost in elderly individuals, in particular in obese class a parts per thousand yen2 individuals.
    Type of Publication: Journal article published
    PubMed ID: 25829392
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  • 2
    Keywords: POPULATION ; COMORBIDITY ; ACCESS ; MENTAL-HEALTH ; MULTIPLE CHRONIC CONDITIONS ; FULLY CONDITIONAL SPECIFICATION ; ILLNESS RATING-SCALE ; SOCIAL-FACTORS ; MEDICAL-CARE ; MULTIMORBIDITY
    Abstract: Background: To analyze the association of health care costs with predisposing, enabling, and need factors, as defined by Andersen's behavioral model of health care utilization, in the German elderly population. Methods: Using a cross-sectional design, cost data of 3,124 participants aged 57-84 years in the 8 year follow up of the ESTHER cohort study were analyzed. Health care utilization in a 3-month period was assessed retrospectively through an interview conducted by trained study physicians at respondents' homes. Unit costs were applied to calculate health care costs from the societal perspective. Socio-demographic and health-related variables were categorized as predisposing, enabling, or need factors as defined by the Andersen model. Multimorbidity was measured by the Cumulative Illness Rating Scale for Geriatrics (CIRS-G). Mental health status was measured by the SF-12 mental component summary (MCS) score. Sector-specific costs were analyzed by means of multiple Tobit regression models. Results: Mean total costs per respondent were 889 [sic] for the 3-month period. The CIRS-G score and the SF-12 MCS score representing the need factor in the Andersen model were consistently associated with total, inpatient, outpatient and nursing costs. Among the predisposing factors, age was positively associated with outpatient costs, nursing costs, and total costs, and the BMI was associated with outpatient costs. Conclusions: Multimorbidity and mental health status, both reflecting the need factor in the Andersen model, were the dominant predictors of health care costs. Predisposing and enabling factors had comparatively little impact on health care costs, possibly due to the characteristics of the German social health insurance system. Overall, the variables used in the Andersen model explained only little of the total variance in health care costs.
    Type of Publication: Journal article published
    PubMed ID: 24524754
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