Mette Hammer

The association of body mass index and health-related quality of life in the general population: data from the 2003 Health Survey of England

ObjectivesThe 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.MethodsHRQoL data (from EQ-5D responses of 14,416 individuals aged ≥18 in the 2003 Health Survey for England) were used, and linear regression analyses were conducted to examine the relationship between BMI and HRQoL.ResultsA 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.ConclusionsThere 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.

Costs of managing severe hypoglycaemia in three European countries

Abstract Objectives: To assess the costs of severe hypoglycaemic events (SHEs) in diabetes patients in Germany, Spain and the UK. Methods: Healthcare resource use was measured by surveying 639 patients aged ≥16 years, receiving insulin for type 1 (n=319) or type 2 diabetes (n=320), who experienced ≥1 SHE in the preceding year. Patients were grouped by location of SHE treatment: group 1, community (family/domestic); group 2, community (healthcare professional); group 3, hospital. Costs were calculated from published unit costs applied to estimated resource use. Costs per SHE were derived from patient numbers per subgroup. Weighted average costs were derived using a prevalence database. Results: Hospital treatment was a major cost in all countries. In Germany and Spain, costs per SHE for type 1 patients differed from those for type 2 patients in each group. Average SHE treatment costs were higher for patients with type 2 diabetes (Germany, €533; Spain, €691; UK, €537) than type 1 diabetes patients (€441, €577 and €236, respectively). Telephone calls, visits to doctors, blood glucose monitoring and patient education contributed substantially to costs for non-hospitalised patients. Conclusions: 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.

Understanding and assessing the impact of treatment in diabetes: the Treatment-Related Impact Measures for Diabetes and Devices (TRIM-Diabetes and TRIM-Diabetes Device)

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.

A comparison of preferences for two GLP-1 products – liraglutide and exenatide – for the treatment of type 2 diabetes

Abstract Objective: To use time trade-off (TTO) to compare patient preferences for profiles of two glucagon-like peptide (GLP-1) products for the treatment of type 2 diabetes (liraglutide and exenatide) that vary on four key attributes – efficacy (as measured by hemoglobin A1C), incidence of nausea, incidence of hypoglycemia, and dosing frequency (QD vs. BID) – and measure the contribution of those attributes to preferences. Methods: A total of 382 people with T2DM were recruited to participate in an internet-based survey consisting of a series of health-related questions, a conjoint exercise and a set of time trade-off items. In the conjoint exercise, respondents were presented with eight pairs of hypothetical GLP-1 profiles, and completed a time-tradeoff exercise for each pair. Results: The product profile representing liraglutide was preferred by 96% of respondents and resulted in significantly higher health utilities (0.038) than the product profile representing exenatide (0.978 vs. 0.94, p < 0.05). Estimated preference scores from the conjoint analysis revealed that efficacy measured by hemoglobin A1C is the most important attribute, followed by nausea, hypoglycemia, and dosing schedule. Limitations: On-line participants may not represent ‘typical’ type 2 diabetes patients, and brief product profiles represented results from clinical trials, not clinical practice Conclusion: 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.

Reporting error in weight and its implications for bias in economic models

Most research on the economic consequences of obesity uses data on self-reported weight, which contains reporting error that has the potential to bias coefficient estimates in economic models. The purpose of this paper is to measure the extent and characteristics of reporting error in weight, and to examine its impact on regression coefficients in models of the healthcare consequences of obesity. We analyze data from the National Health and Nutrition Examination Survey (NHANES) for 2003-2010, which includes both self-reports and measurements of weight and height. We find that reporting error in weight is non-classical: underweight respondents tend to overreport, and overweight and obese respondents tend to underreport, their weight, with underreporting increasing in measured weight. This error results in roughly 1 out of 7 obese individuals being misclassified as non-obese. Reporting error is also correlated with other common regressors in economic models, such as education. Although it is a common misconception that reporting error always causes attenuation bias, comparisons of models that use self-reported and measured weight confirm that reporting error can cause upward bias in coefficient estimates. For example, use of self-reports leads to overestimates of the probability that an obese man uses a prescription drug, has a healthcare visit, or has a hospital admission. These findings underscore that models of the consequences of obesity should use measurements of weight, when available, and that social science datasets should measure weight rather than simply ask subjects to report their weight.

Management of severe hypoglycaemia: cultural similarities, differences and resource consumption in three European countries

Abstract Background: To investigate the characteristics of people with insulin-treated diabetes, who have experienced severe hypoglycaemic events (SHEs), in Germany, Spain or UK. Methods: Patients with type 1 (n=319) or insulin-treated type 2 diabetes (n=320) who had experienced ≥1 SHE in the preceding year were enrolled. Their median age was 53 years (range, 16–94 years). Data were collected using a questionnaire administered by an experienced interviewer. Results: The median number of reported SHEs was 2–3 in 12 months. Most events (69%) occurred at home, usually during the day or evening (74%) and most commonly due to insufficient food consumption (45%). In patients whose hypoglycaemia awareness was tested, 68% had normal awareness. Patients requiring emergency healthcare treatment frequently had impaired hypoglycaemia awareness, and developed hypoglycaemic coma more often. Hospital treatment was usually provided in an emergency department (72–94%). The duration of stay was longest in Germany. Following a SHE, patients receiving professional treatment were more likely to: consult their physician, test their blood glucose more often, adjust insulin dose and receive self-management training. Conclusions: This survey of diabetes patients aged 16–94 years showed that SHEs represent a substantial burden on national healthcare systems in Germany, UK and Spain. The pattern of occurrence and treatment was similar in all three countries, despite differences in cultures and healthcare systems.

Impact of obesity and type 2 diabetes on health-related quality of life in the general population in England.

Background Weight gain can contribute towards the development of type 2 diabetes (T2D), and some treatments for T2D can lead to weight gain. The aim of this study was to determine whether having T2D and also being obese had a greater or lesser impact on health-related quality of life (HRQoL) than having either of the two conditions alone. Methods The 2003 dataset of the Health Survey for England (HSE) was analyzed using multiple regression analyses to examine the influence of obesity and T2D on HRQoL, and to determine whether there was any interaction between these two disutilities. Results T2D reduced HRQoL by 0.029 points, and obesity reduced HRQoL by 0.027 points. There was no significant interaction effect between T2D and obesity, suggesting that the effect of having both T2D and being obese is simply additive and results in a reduction in HRQoL of 0.056. Conclusions Based on analysis of HSE 2003 data, people with either T2D or obesity experience significant reduction in HRQoL and people with both conditions have a reduction in HRQoL equal to the sum of the two independent effects. The effect of obesity on HRQoL in people with T2D should be considered when selecting a therapy.

Prevalence and healthcare costs of obesity-related comorbidities: evidence from an electronic medical records system in the United States

Abstract Objective: This study estimated the economic burden of obesity-related comorbidities (ORCs) in the US, at both the person and population levels. Methods: The Geisinger Health System provided electronic medical records and claims between January 2004 and May 2013 for a sample of 153,561 adults (50% males and 97% white). Adults with < 2 years of data, who were underweight (body mass index (BMI) < 18.5 kg/m2), or had diseases causing major weight change (e.g., malignancy) during the study period (i.e., continuous enrollment in health plans) were excluded. A total of 21 chronic conditions, with established association with obesity in the literature, were identified by diagnosis codes and/or lab test results. The total healthcare costs were measured in each year. The association between annual costs and ORCs was assessed by a regression, which jointly considered all the ORCs. The per-person incremental costs of a single comorbidity, without any of the other ORCs, were calculated. The population-level economic burden was the product of each ORC’s incremental costs and the annual prevalence of the ORC among 100,000 individuals. The prevalence of ORCs was stratified by obesity status to estimate the economic burden among 100,000 individuals with obesity and among those without. Results: This study identified 56,895 adults (mean age = 47 years; mean BMI = 29.6 kg/m2). The annual prevalence of ORCs ranged from 0.5% for pulmonary embolism (PE) to 41.8% for dyslipidemia. The per-person annual incremental costs of a single ORC ranged from

Results of a model analysis of the cost-effectiveness of liraglutide versus exenatide added to metformin, glimepiride, or both for the treatment of type 2 diabetes in the United States.

120 for angina to

Development and validation of the Treatment Related Impact Measure of Weight (TRIM-Weight)

1665 for PE. Hypertensive diseases (HTND), dyslipidemia, and osteoarthritis were the three most expensive ORCs at the population level; each responsible for ≥