Obesity

Kim DD, Basu A.
Value in Health. 2016;19(5):602-613.

BACKGROUND

The prevalence of adult obesity exceeds 30% in the United States, posing a significant public health concern as well as a substantial financial burden. Although the impact of obesity on medical spending is undeniably significant, the estimated magnitude of the cost of obesity has varied considerably, perhaps driven by different study methodologies.

OBJECTIVES

To document variations in study design and methodology in existing literature and to understand the impact of those variations on the estimated costs of obesity.

METHODS

We conducted a systematic review of the twelve recently published articles that reported costs of obesity and performed a meta-analysis to generate a pooled estimate across those studies. Also, we performed an original analysis to understand the impact of different age groups, statistical models, and confounder adjustment on the magnitude of estimated costs using the nationally representative Medical Expenditure Panel Surveys from 2008-2010.

RESULTS

We found significant variations among cost estimates in the existing literature. The meta-analysis found that the annual medical spending attributable to an obese individual was $1901 ($1239-$2582) in 2014 USD, accounting for $149.4 billion at the national level. The two most significant drivers of variability in the cost estimates were age groups and adjustment for obesity-related comorbid conditions.

CONCLUSIONS

It would be important to acknowledge variations in the magnitude of the medical cost of obesity driven by different study design and methodology. Researchers and policy-makers need to be cautious on determining appropriate cost estimates according to their scientific and political questions.

Leung MYM, Carlsson NP, Colditz GA, Chang S.
Value in Health. 2017;20(1):77-84.

BACKGROUND

Diabetes is one of the most prevalent and costly chronic diseases in the United States.

OBJECTIVES

To analyze the risk of developing diabetes and the annual cost of diabetes for a US general population.

METHODS

Data from the Medical Expenditure Panel Survey, 2008 to 2012, were used to analyze 1) probabilities of developing diabetes and 2) annual total health care expenditures for diabetics. The age-, sex-, race-, and body mass index (BMI)-specific risks of developing diabetes were estimated by fitting an exponential survival function to age at first diabetes diagnosis. Annual health care expenditures were estimated using a generalized linear model with log-link and gamma variance function. Complex sampling designs in the Medical Expenditure Panel Survey were adjusted for. All dollar values are presented in 2012 US dollars.

RESULTS

We observed a more than 6 times increase in diabetes risks for class III obese (BMI ≥ 40 kg/m) individuals incurred an annual marginal cost of $628 and $756, respectively. The annual health care expenditure differentials between those with and without diabetes of age 50 years were the highest for individuals with class II ($12,907) and class III ($9,703) obesity.

CONCLUSIONS

This article highlights the importance of obesity on diabetes burden. Our results suggested that obesity, in particular, class II and class III (i.e., BMI ≥ 35 kg/m) obesity, is associated with a substantial increase in the risk of developing diabetes and imposes a large economic burden.

Gulliford MC, Charlton J, Prevost T, Booth H, Fildes A, Ashworth M, Littlejohns P, Reddy M, Khan O, Rudisill C.
Value in Health. 2017;20(1):85-92.

OBJECTIVES

To estimate costs and outcomes of increasing access to bariatric surgery in obese adults and in population subgroups of age, sex, deprivation, comorbidity, and obesity category.

METHODS

A cohort study was conducted using primary care electronic health records, with linked hospital utilization data, for 3,045 participants who underwent bariatric surgery and 247,537 participants who did not undergo bariatric surgery. Epidemiological analyses informed a probabilistic Markov model to compare bariatric surgery, including equal proportions with adjustable gastric banding, gastric bypass, and sleeve gastrectomy, with standard nonsurgical management of obesity. Outcomes were quality-adjusted life-years (QALYs) and net monetary benefits at a threshold of £30,000 per QALY.

RESULTS

In a UK population of 250,000 adults, there may be 7,163 people with morbid obesity including 1,406 with diabetes. The immediate cost of 1,000 bariatric surgical procedures is £9.16 million, with incremental discounted lifetime health care costs of £15.26 million (95% confidence interval £15.18–£15.36 million). Patient-years with diabetes mellitus will decrease by 8,320 (range 8,123–8,502). Incremental QALYs will increase by 2,142 (range 2,032–2,256). The estimated cost per QALY gained is £7,129 (range £6,775–£7,506). Net monetary benefits will be £49.02 million (range £45.72–£52.41 million). Estimates are similar for subgroups of age, sex, and deprivation. Bariatric surgery remains cost-effective if the procedure is twice as costly, or if intervention effect declines over time.

CONCLUSIONS

Diverse obese individuals may benefit from bariatric surgery at acceptable cost. Bariatric surgery is not cost-saving, but increased health care costs are exceeded by health benefits to obese individuals.

Singh GC V, Suhrcke M, Hardeman W, Sutton S, Wilson ECF.
Value in Health. 2018;21(1):18-26.

BACKGROUND

Our analysis suggests that the use of pedometer BIs is the most cost-effective strategy to promote physical activity in primary care, and that there is potential value in further research into the cost-effectiveness of brief (i.e., 5 minutes) pedometer interventions in this setting.

OBJECTIVES

To estimate the cost-effectiveness of BIs to promote physical activity in primary care and to guide future research priorities using value of information analysis.

METHODS

A decision model was used to compare the cost-effectiveness of three classes of BIs that have been used, or could be used, to promote physical activity in primary care: 1) pedometer interventions, 2) advice/counseling on physical activity, and (3) action planning interventions. Published risk equations and data from the available literature or routine data sources were used to inform model parameters. Uncertainty was investigated with probabilistic sensitivity analysis, and value of information analysis was conducted to estimate the value of undertaking further research.

RESULTS

In the base-case, pedometer interventions yielded the highest expected net benefit at a willingness to pay of £20,000 per quality-adjusted life-year. There was, however, a great deal of decision uncertainty: the expected value of perfect information surrounding the decision problem for the National Health Service Health Check population was estimated at £1.85 billion.

CONCLUSIONS

Our analysis suggests that the use of pedometer BIs is the most cost-effective strategy to promote physical activity in primary care, and that there is potential value in further research into the cost-effectiveness of brief (i.e., 5 minutes) pedometer interventions in this setting.

Jia H, Zack MM, Gottesman II, Thompson WW.
Value in Health. 2018;21(3):364-371.

OBJECTIVES

To examine associations between four health behaviors (smoking, physical inactivity, heavy alcohol drinking, and obesity) and three health indices (health-related quality of life, life expectancy, and quality-adjusted life expectancy (QALE)) among US adults with depression.

METHODS

Data were obtained from the 2006, 2008, and 2010 Behavioral Risk Factor Surveillance System data. The EuroQol five-dimensional questionnaire (EQ-5D) health preference scores were estimated on the basis of extrapolations from the Centers for Disease Control and Prevention’s healthy days measures. Depression scores were estimated using the eight-item Patient Health Questionnaire. Life expectancy estimates were obtained from US life tables, and QALE was estimated from a weighted combination of the EQ-5D scores and the life expectancy estimates. Outcomes were summarized by depression status for the four health behaviors (smoking, physical inactivity, heavy alcohol drinking, and obesity).

RESULTS

For depressed adults, current smokers and the physically inactive had significantly lower EQ-5D scores (0.040 and 0.171, respectively), shorter life expectancy (12.9 and 10.8 years, respectively), and substantially less QALE (8.6 and 10.9 years, respectively). For nondepressed adults, estimated effects were similar but smaller. Heavy alcohol drinking among depressed adults, paradoxically, was associated with higher EQ-5D scores but shorter life expectancy. Obesity was strongly associated with lower EQ-5D scores but only weakly associated with shorter life expectancy.

CONCLUSIONS

Among depressed adults, physical inactivity and smoking were strongly associated with lower EQ-5D scores, life expectancy, and QALE, whereas obesity and heavy drinking were only weakly associated with these indices. These results suggest that reducing physical inactivity and smoking would improve health more among depressed adults.