Objectives The link between obesity/overweight and life-threatening illnesses is well established. The objective of this study was to investigate the relationship between body mass index (BMI) and health-related quality of life (HRQoL), and any differences between men and women, in the general population of England. Methods HRQoL data (from EQ-5D responses of 14,416 individuals aged C18 in the 2003 Health Survey for England) were used, and linear regression analyses were conducted to examine the relationship between BMI and HRQoL. Results A significant association between BMI and HRQoL was found after controlling for factors such as gender, age, and obesity-related comorbidities. The maximum HRQoL was reached at a BMI of 26.0 in men and 24.5 in women, demonstrating that BMI is negatively associated with HRQoL for both underweight and obese individuals. At higher BMI values, men reported higher HRQoL than women; at lower BMI values, HRQoL was lower in men than women. Conclusions There is a significant association between BMI and HRQoL in men and women in the general population. Nearly all aspects of HRQoL are adversely affected by elevated BMI.

ObjectivesObesity is a known risk factor for type 2 diabetes (T2D). We conducted a case–control study to assess the association between body mass index (BMI) and the risk of being diagnosed with T2D in the United States.MethodsWe selected adults (≥ 18 years old) who were diagnosed with T2D (defined by ICD-9-CM diagnosis codes or use of anti-diabetic medications) between January 2004 and October 2011 (“cases”) from an electronic health records database provided by an integrated health system in the Middle Atlantic region. Twice as many individuals enrolled in the health system without a T2D diagnosis during the study period (“controls”) were selected based on age, sex, history of cardiac comorbidities or hyperinflammatory state (defined by C-reactive protein and erythrocyte sedimentation rate), and use of psychiatric or beta blocker medications. BMI was measured during one year prior to the first observed T2D diagnosis (for cases) or a randomly assigned date (for controls); individuals with no BMI measure or BMI < 18.5 kg/m2 were excluded. We assessed the impact of increased BMI (overweight: 25–29.9 kg/m2; Obesity Class I: 30–34.9 kg/m2; Obesity Class II: 35–39.9 kg/m2; Obesity Class III: ≥40 kg/m2), relative to normal BMI (18.5–24.9 kg/m2), on a T2D diagnosis using odds ratios (OR) and relative risks (RR) estimated from multiple logistic regression results.ResultsWe included 12,179 cases (mean age: 55, 43% male) and 25,177 controls (mean age: 56, 45% male). We found a positive association between BMI and the risk of a T2D diagnosis. The strength of this association increased with BMI category (RR [95% confidence interval]: overweight, 1.5 [1.4–1.6]; Obesity Class I, 2.5 [2.3–2.6]; Obesity Class II, 3.6 [3.4–3.8]; Obesity Class III, 5.1 [4.7–5.5]).ConclusionsBMI is strongly and independently associated with the risk of being diagnosed with T2D. The incremental association of BMI category on the risk of T2D is stronger for people with a higher BMI relative to people with a lower BMI.

IntroductionAdherence to diabetes medication has been linked to improved glycemic levels and lower costs, but previous research on adherence has typically involved oral antidiabetic medication or insulin. This study examines how adherence and persistence to once-daily liraglutide impact glycemic control and economic outcomes in a real-world population of adult type 2 diabetes (T2D) patients.MethodsA retrospective cohort study using administrative claims data from July 2009 through September 2013. Patients aged ≥18 years with T2D treated with liraglutide were identified (index date = first liraglutide prescription). Adherence was based on the proportion of days covered (PDC); with PDC ≥0.80 classified as adherent. Non-persistent patients were those with a gap in therapy of >90 days. Lab results for glycated hemoglobin (A1C) were used to identify whether patients achieved target levels of <7.0% and ≤ 6.5%, or experienced a reduction of ≥1.0% in A1C from pre-index (baseline) to post-index (follow-up). Logistic regression was used to estimate the likelihood of achieving the A1C goals, adjusted for baseline characteristics. Diabetes-related medical, pharmacy, and total costs were modeled and estimated for the adherence and persistence cohorts.ResultsA total of 1321 patients were identified. The mean PDC was 0.59 and 34% of patients were classified as adherent, while 60% were persistent over 12 months of follow-up. Adherent and persistent patients were more likely to achieve each of the A1C goals than their non-adherent and non-persistent counterparts after adjusting for patient characteristics. Adherence and persistence were associated with higher adjusted diabetes-related pharmacy and total healthcare costs during follow-up; whereas persistent patients had significantly lower diabetes-related medical costs than non-persistent patients.ConclusionsAdherence and persistence to liraglutide are associated with improved A1C outcomes. Persistent patients showed significantly lower medical costs versus those discontinuing liraglutide. Total healthcare costs were higher for adherent and persistent cohorts driven by higher pharmacy costs.Electronic supplementary materialThe online version of this article (doi:10.1007/s12325-015-0199-z) contains supplementary material, which is available to authorized users.

BackgroundThe prevalence of obesity has more than doubled in the USA in the past 30 years. Obesity is a significant risk factor for diabetes, cardiovascular disease, and other clinically significant co-morbidities. This paper estimates the medical care cost savings that can be achieved from a given amount of weight loss by people with different starting values of body mass index (BMI), for those with and without diabetes. This information is an important input into analyses of the cost effectiveness of obesity treatments and prevention programs.MethodsTwo-part models of instrumental variables were estimated using data from the Medical Expenditure Panel Survey (MEPS) for 2000–2010. Models were estimated for all adults as well as separately for those with and without diabetes. We calculated the causal impact of changes in BMI on medical care expenditures, cost savings for specific changes in BMI (5, 10, 15, and 20 %) from starting BMI levels ranging from 30 to 45 kg/m2, as well as the total excess medical care expenditures caused by obesity.ResultsIn the USA, adult obesity raised annual medical care costs by $US3,508 per obese individual, for a nationwide total of $US315.8 billion (year 2010 values). However, the relationship of medical care costs over BMI is J-shaped; costs rise exponentially in the range of class 2 and 3 obesity (BMI ≥35). The heavier the obese individual, the greater the reduction in medical care costs associated with a given percent reduction in BMI. Medical care expenditures are higher, and rise more with BMI, among individuals with diabetes than among those without diabetes.ConclusionsThe savings from a given percent reduction in BMI are greater the heavier the obese individual, and are greater for those with diabetes than for those without diabetes. The results provide health insurers, employers, government agencies, and health economists with accurate estimates of the change in medical care expenditures resulting from weight loss, which is important information for calculating the cost effectiveness of interventions to prevent and treat obesity.Electronic supplementary materialThe online version of this article (doi:10.1007/s40273-014-0230-2) contains supplementary material, which is available to authorized users.

Treatment of SHEs adds significantly to healthcare costs. Average costs were lower for type 1 than for insulin-treated type 2 diabetes, in all three countries.

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Based on the four attributes presented, patients prefer liraglutide over exenatide. Preference is based on superior efficacy and less nausea more than less hypoglycemia and once-daily dosing.

PurposeDiabetes is a debilitating illness requiring lifelong management. Treatments can be varied in terms of mode of administration as well as type of agent. Unfortunately, most patient reported outcome measures currently available to assess the impact of treatment are specific to diabetes type, treatment modality or delivery systems and are designed to be either a HRQoL or treatment satisfaction measure. To address these gaps, the Treatment Related Impact Measure-Diabetes and Device measures were developed. This paper presents the item development and validation of the TRIM Diabetes/Device.MethodsPatient interviews were conducted to collect the patient perspective and ensure high content validity. Interviews were hand coded and qualitatively analyzed to identify common themes. A conceptual model of the impact of diabetes medication was developed and preliminary items for the TRIM-Diabetes/Device were generated and cognitively debriefed. Validation data was collected via an on-line survey and analyzed according to an a priori statistical analysis plan to validate the overall score as well as each domain. Item level criteria were used to reduce the preliminary item pool. Next, factor analysis to identify structural domains was performed. Reliability and validity testing was then performed.ResultsOne hundred and five patients were interviewed in focus groups, individual interviews and for cognitive debriefing. Five hundred seven patients participated in the validation study. Factor analysis identified seven domains: Treatment Burden, Daily Life; Diabetes Management; Psychological Health; Compliance and Device Function and Bother. Internal consistency reliability coefficients of the TRIM-Diabetes/Device ranged from 0.80 and 0.94. Test-retest reliability of the TRIM-Diabetes/Device ranged from 0.71 to 0.89. All convergent and known groups validity hypotheses were met for the TRIM-Diabetes/Device total scores and sub-scales.ConclusionValidation is an ongoing and iterative process. These findings are the first step in that process and have shown that both the TRIM-Diabetes and the TRIM-Diabetes Device have acceptable psychometric properties. Future research is needed to continue the validation process and examine responsiveness and the validity of the TRIM-Diabetes/Device in a clinical trial population.