Association of body mass index and osteoarthritis with healthcare expenditures and utilization.

OBJECTIVE: Osteoarthritis is highly prevalent and, on aggregate, is one of the largest contributors to US spending on hospital-based health care. This study sought to examine body mass index (BMI)-related variation in the association of osteoarthritis with healthcare utilization and expenditures. METHODS: This is a retrospective study using administrative insurance claims linked to electronic health records. Study patients were aged ≥ 18 years with ≥1 BMI measurement recorded in 2014, with the first (index) BMI ≥ 25 kg m-2. Study outcomes and covariates were measured during a 1-year evaluation period spanning 6 months before and after index. Multivariable regression analyses examined the association of BMI with osteoarthritis prevalence, and the combined associations of osteoarthritis and BMI with osteoarthritis-related medication utilization, all-cause hospitalization, and healthcare expenditures. RESULTS: A total of 256 459 patients (median age = 56 y) met study eligibility criteria; 14.8% (38 050) had osteoarthritis. In multivariable analyses, the adjusted prevalence of osteoarthritis increased with increasing BMI (12.7% in patients who were overweight [25.0-29.9 kg m-2] to 21.9% in patients with class III obesity [BMI ≥ 40 kg m-2], P < .001). Among patients with osteoarthritis, increasing BMI (from overweight to class III obesity) was associated with increased (all P < .01): utilization rates for analgesic medications (41.5-53.5%); rates of all-cause hospitalization (26.3%-32.0%); and total healthcare expenditures ($18 204-$23 372). CONCLUSION: The prevalence and economic burden of osteoarthritis grow with increasing BMI; primary prevention of weight-related osteoarthritis and secondary weight management may help to alleviate this burden.

Assessment of obesity prevalence and validity of obesity diagnoses coded in claims data for selected surgical populations: A retrospective, observational study.

In many types of surgery, obesity may influence patient selection, prognosis, and/or management. Quantifying the accuracy of the coding of obesity and other prognostic factors is important for the design and interpretation of studies of surgical outcomes based on administrative healthcare data. This study assessed the validity of obesity diagnoses recorded in insurance claims data in selected surgical populations.This was a retrospective, observational study. Deidentified electronic health record (EHR) and linked administrative claims data were obtained for US patients age ≥20 years who underwent a qualifying surgical procedure (bariatric surgery, total knee arthroplasty [TKA], cardiac ablation, or hernia repair) in 2014Q1-2017Q1 (first = index). Patients' body mass index (BMI) as coded in the claims data (error-prone measure) during the index procedure or 180d pre-index was compared with their measured BMI as recorded in the EHR (criterion standard) to estimate the sensitivity and positive predictive value (PPV) of obesity diagnosis codes.Among patients who underwent bariatric surgery (N = 1422), TKA (N = 8670), cardiac ablation (N = 167), or hernia repair (N = 5450), obesity was present in 98%, 63%, 52%, and 54%, respectively, based on measured BMI. PPVs of obesity diagnosis codes were high: 99.3%, 96.0%, 92.8%, and 94.1% in bariatric surgery, TKA, cardiac ablation, and hernia repair, respectively. The sensitivity of obesity diagnoses was: 99.8%, 46.2%, 41.3%, and 42.3% in bariatric surgery, TKA, cardiac ablation, and hernia repair, respectively. Among false-positive patients diagnosed as obese but with measured BMI <30, the proportion with a BMI ≥28 was 40.0%, 67.6%, 60.7%, and 65.8% for bariatric surgery, TKA, cardiac ablation, and hernia repair, respectively.Our data indicate that obesity is highly prevalent in many surgical populations, obesity diagnosis codes have high PPVs, but also obesity is generally undercoded in claims data. Quantifying the validity of diagnosis codes for obesity and other important prognostic factors is important for the design and interpretation of studies of surgical outcomes based on administrative data. Further research is needed to determine the extent to which undercoding of BMI and obesity can be addressed through the use of proxies that may be better documented in claims data.

The contribution of obesity to prescription opioid use in the United States.

The prevalence of obesity has grown rapidly over the past several decades and has been accompanied by an increase in the prevalence of chronic pain and prescription opioid use. Obesity, through its association with pain, may represent an important contributor to opioid use. This cross-sectional study investigated the relationship between obesity and prescription opioid use among adults aged 35 to 79 years using data from the National Health and Nutrition Examination Survey (NHANES, 2003-2016). Relative to normal weight, body mass indices in the overweight {odds ratio (OR), 1.11 (confidence interval [CI], 0.88-1.39)}, obese I (OR, 1.26 [CI, 1.01-1.57]), obese II (OR, 1.69 [CI, 1.34-2.12]), and obese III (OR, 2.33 [CI, 1.76-3.08]) categories were associated with elevated odds of prescription opioid use. The association between excess weight and opioid use was stronger for chronic opioid use than for use with a duration of less than 90 days (P-value, <0.001). We estimated that 14% (CI, 9%-19%) of prescription opioid use at the population level was attributable to obesity, suggesting there might have been 1.5 million fewer opioid users per year under the hypothetical scenario where obese individuals were instead nonobese (CI, 0.9-2.0 million users). Back pain, joint pain, and muscle/nerve pain accounted for the largest differences in self-reported reasons for prescription opioid use across obesity status. Although interpretation is limited by the cross-sectional nature of the associations, our findings suggest that the obesity epidemic may be partially responsible for the high prevalence of prescription opioid use in the United States.

Body mass index and insulin use as identifiers of high-cost patients with type 2 diabetes: A retrospective analysis of electronic health records linked to insurance claims data.

AIMS: To study the association of body mass index (BMI) and insulin use with type 2 diabetes-related healthcare expenditures (T2D-HE). MATERIALS AND METHODS: Retrospective study using de-identified electronic health records linked to insurance claims data. Study included a prevalence-based sample of overweight or obese patients with antihyperglycaemic-treated T2D. Patients had ≥1 A1c measurement in 2014 (last observed = index A1c), ≥1 BMI measurement within ±90 days of index (average BMI = baseline BMI), and continuous enrolment for 180 days before (baseline) through 395 days after index (day 30-395 = follow-up). BMI was categorized as: 25 to 29.9 kg/m2 = overweight; 30 to 34.9 kg/m2 = obese class I (OCI); 35 to 39.9 kg/m2 = OCII; ≥40 kg/m2 = OCIII. Multivariable regressions were used to examine one-year follow-up T2D-HE as a function of BMI, insulin use, an interaction term between BMI and insulin use, and patient demographics. RESULTS: Study included 13 026 patients (mean age = 63.6 years; 48.1% female; 29.5% overweight, 31.6% OCI, 20.3% OCII, 18.6% OCIII; 25.3% insulin users). Baseline insulin use rates monotonically ranged from 19.7% in overweight patients to 33.0% in OCIII patients (P < 0.001). Together, BMI and insulin use were jointly associated with one-year follow-up T2D-HE, which monotonically ranged from $5842 in overweight patients with no insulin to $17 700 OCIII insulin users, P < 0.001. Within each BMI category, insulin users' one-year T2D-HE was at least double that of non-users. Additional analyses of all-cause healthcare expenditures yielded consistent results. CONCLUSIONS: BMI and insulin use represent simple stratifiers for identifying high-cost patients. OCIII insulin users incurred the greatest annual healthcare expenditures; these patients may be an ideal group for targeted interventions.

Prevalence and Determinants of Engagement with Obesity Care in the United States.

OBJECTIVE: Medical management of obesity can result in significant weight loss and reduce the burden of obesity-related complications. This report employs a new conceptual model to quantify engagement with obesity care and associated determinants in the US adult population. METHODS: Engagement with obesity care was conceptualized as a cascade comprising 5 successive steps: perceiving oneself as overweight, desiring to lose weight, attempting weight loss, seeking care from a health care professional for obesity, and seeking care from a physician specifically. RESULTS: Among adults with obesity, 7.3% did not perceive themselves as overweight, 1.5% perceived themselves as overweight but had no desire to lose weight, 29.9% wanted to lose weight but did not try in the last year, 51.3% tried to lose weight but did not consult a health professional, and 6.4% sought help for weight loss from a health professional but not a physician, implying that 96.4% of the population with obesity had an unmet need for obesity care. CONCLUSIONS: This analysis provides new insight into the most common points along the cascade at which disengagement occurs and can inform efforts to improve uptake of obesity-related health care services.

Obesity Progression Between Young Adulthood and Midlife and Incident Diabetes: A Retrospective Cohort Study of U.S. Adults.

OBJECTIVE: Understanding how changes in weight over the life course shape risk for diabetes is critical for the prevention of diabetes. Using data from the National Health and Nutrition Examination Survey (NHANES), we investigated the association between self-reported weight change from young adulthood to midlife and incident diabetes. RESEARCH DESIGN AND METHODS: We categorized individuals into four weight-change groups: those who remained nonobese (stable nonobese), those who moved from an obese BMI to a nonobese BMI (losing), those who moved from a nonobese BMI to an obese BMI (gaining), and those who remained obese (stable obese). Diabetes status was determined by self-report of a prior diagnosis, and age at diagnosis was used to establish time of diabetes onset. Hazard ratios (HRs) relating weight change to incident diabetes over 10 years of follow-up were calculated using Cox models adjusting for covariates. RESULTS: Those who were obese and lost weight exhibited a significantly lower risk (HR 0.33; 95% CI 0.14, 0.76) of diabetes compared with those with stable obesity. We also observed lower risk among those who were stable nonobese (HR 0.22; 95% CI 0.18, 0.28) and those in the gaining category (HR 0.70; 95% CI 0.57, 0.87). Further, there was evidence of an increased incidence of diabetes among obese individuals who lost weight compared with individuals who were stable nonobese; however, weight loss was rare, and the association was not statistically significant. If those who were obese had become nonobese during the 10-year period, we estimate that 9.1% (95% CI 5.3, 12.8) of observed diabetes cases could have been averted, and if the population had maintained a normal BMI during the period, 64.2% (95% CI 59.4, 68.3) of cases could have been averted. CONCLUSIONS: The findings from this study underscore the importance of population-level approaches to the prevention and treatment of obesity across the life course of individuals.

A novel approach to glycemic control in type 2 diabetes mellitus, partial jejunal diversion: pre-clinical to clinical pathway.

OBJECTIVE: To explore partial jejunal diversion (PJD) via a side-to-side jejuno-jejunostomy for improved glycemic control in type 2 diabetes mellitus (T2DM). PJD is an anatomy-sparing, technically simple surgery in comparison to the predominate metabolic procedures, Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG). Positive results in a rodent model prompted a human proof-of-concept study. RESEARCH DESIGN AND METHODS: Pre-clinically, 71 rats were studied in a model of metabolic dysfunction induced by a high-fat diet; 33 animals undergoing one of two lengths of PJD were compared with 18 undergoing sham, 10 RYGB and 10 jejuno-ileal bypass. Clinically, 15 adult subjects with treated but inadequately controlled T2DM (hemoglobin A1c (HbA1c) of 8.0%-11.0%), body mass index of 27.0-40.0 kg/m2, and C peptide ≥3 ng/mL were studied. Follow-up was at 2 weeks, and 3, 6, 9, and 12 months post-PJD. RESULTS: Pre-clinically, positive impacts with PJD on glucose homeostasis, cholesterol, and body composition versus sham control were demonstrated. Clinically, PJD was performed successfully without serious complications. Twelve months post-surgery, the mean (SD) reduction from baseline in HbA1c was 2.3% (1.3) (p<0.01). CONCLUSIONS: PJD may provide an anatomy sparing, low-risk, intervention for poorly controlled T2DM without significant alteration of the patient's lifestyle. The proof-of-concept study is limited by a small sample size and advanced disease, with 80% of participants on insulin and a mean time since diagnosis of over 10 years. Further study is warranted. TRIAL REGISTRATION NUMBER: NCT02283632; Pre-results.