Variation in Provider Identification of Obesity by Individual- and Neighborhood-Level Characteristics among an Insured Population

Objective. The purpose of this study was to examine whether neighborhood- and individual-level characteristics affect providers' likelihood of providing an obesity diagnosis code in their obese patients' claims. Methods. Logistic regressions were performed with obesity diagnosis code serving as the outcome variable and neighborhood characteristics and member characteristics serving as the independent variables (N = 16,151 obese plan members). Results. Only 7.7 percent of obese plan members had an obesity diagnosis code listed in their claims. Members living in neighborhoods with the largest proportions of Blacks were 29 percent less likely to receive an obesity diagnosis (P < .05). The odds of having an obesity diagnosis code were greater among members who were female, aged 44 or below, hypertensive, dyslipidemic, BMI ≥ 35 kg/m2, had a larger number of provider visits, or who lived in an urban area (all P < .05). Conclusions. Most health care providers do not include an obesity diagnosis code in their obese patients' claims. Rates of obesity identification were strongly related to individual characteristics and somewhat associated with neighborhood characteristics

Measurement of Weight in Clinical Trials: Is One Day Enough?

Background. Weight is typically measured on a single day in research studies. This practice assumes negligible day-to-day weight variability, although little evidence exists to support this assumption. We compared the precision of measuring weight on one versus two days among control participants in the Weight Loss Maintenance trial. Methods. Trained staff measured weight on two separate days at baseline, 12 months, and 30 months (2004–2007). We calculated the standard deviation (SD) of mean weight change from baseline to the 12- and 30-month visits using (a) the first and (b) both daily weights from each visit and conducted a variance components analysis (2009). Results. Of the 316 participants with follow-up measurements, mean (SD) age was 55.8 (8.5) years, BMI was 30.8 (4.5) kg/m2, 64% were women, 36% were black, and 50% were obese. At 12 months, the SD of mean weight change was 5.1 versus 5.0 kg using one versus two days of weight measurements (P = .76), while at 30 months the corresponding SDs were 6.3 and 6.3 kg (P = .98). We observed similar findings within subgroups of BMI, sex, and race. Day-to-day variability within individuals accounted for <1% of variability in weight. Conclusions. Measurement of weight on two separate days has no advantage over measurement on a single day in studies with well-standardized weight measurement protocols

Impact of bariatric surgery on hypertensive disorders in pregnancy: retrospective analysis of insurance claims data

Objective To determine whether women who had a delivery after bariatric surgery have lower rates of hypertensive disorders in pregnancy compared with women who had a delivery before bariatric surgery

Early Response to Preventive Strategies in the Diabetes Prevention Program

BACKGROUND Recommendations for diabetes prevention in patients with prediabetes include lifestyle modification and metformin. However, the significance of early weight loss and glucose measurements when monitoring response to these proven interventions is unknown. OBJECTIVE To quantify the relationship between early measures of weight and glucose and subsequent diabetes in patients undergoing diabetes prevention interventions. DESIGN Analysis of results from a randomized controlled trial in 27 academic medical centers in the United States. PARTICIPANTS/INTERVENTIONS 3,041 adults with hyperglycemia randomized to lifestyle (n = 1,018), metformin (n = 1,036), or placebo (n = 987) with complete follow-up in The Diabetes Prevention Program. MAIN MEASURES Independent variables were weight loss at 6 and 12 months; fasting glucose (FG) at 6 months; hemoglobin A1c (HbA1c) at 6 months; and post-load glucose at 12 months. The main outcome was time to diabetes diagnosis. KEY RESULTS After 6 months, 604 participants developed diabetes in the lifestyle (n = 140), metformin (n = 206), and placebo (n = 258) arms over 2.7 years. In the lifestyle arm, 6-month weight loss predicted decreased diabetes risk in a graded fashion: adjusted HR (95 % CI) 0.65 (0.35–1.22), 0.62 (0.33–1.18), 0.46 (0.24–0.87), 0.34 (0.18–0.64), and 0.15 (0.07–0.30) for 0–60 % lower diabetes risk across arms. We found a significant interaction between 6-month weight loss and FG in the lifestyle arm (P = 0.038). CONCLUSION Weight and glucose at 6 and 12 months strongly predict lower subsequent diabetes risk with a lifestyle intervention; lower FG predicts lower risk even with substantial weight loss. Early reduction in glycemia is a stronger predictor of future diabetes risk than weight loss for metformin. We offer the first evidence to guide clinicians in making interval management decisions for high-risk patients undertaking measures to prevent diabetes

Electronic Health Record-Based Recruitment and Retention and Mobile Health App Usage: Multisite Cohort Study.

BACKGROUND: To address the obesity epidemic, there is a need for novel paradigms, including those that address the timing of eating and sleep in relation to circadian rhythms. Electronic health records (EHRs) are an efficient way to identify potentially eligible participants for health research studies. Mobile health (mHealth) apps offer available and convenient data collection of health behaviors, such as timing of eating and sleep. OBJECTIVE: The aim of this descriptive analysis was to report on recruitment, retention, and app use from a 6-month cohort study using a mobile app called Daily24. METHODS: Using an EHR query, adult patients from three health care systems in the PaTH clinical research network were identified as potentially eligible, invited electronically to participate, and instructed to download and use the Daily24 mobile app, which focuses on eating and sleep timing. Online surveys were completed at baseline and 4 months. We described app use and identified predictors of app use, defined as 1 or more days of use, versus nonuse and usage categories (ie, immediate, consistent, and sustained) using multivariate regression analyses. RESULTS: Of 70,661 patients who were sent research invitations, 1021 (1.44%) completed electronic consent forms and online baseline surveys; 4 withdrew, leaving a total of 1017 participants in the analytic sample. A total of 53.79% (n=547) of the participants were app users and, of those, 75.3% (n=412), 50.1% (n=274), and 25.4% (n=139) were immediate, consistent, and sustained users, respectively. Median app use was 28 (IQR 7-75) days over 6 months. Younger age, White race, higher educational level, higher income, having no children younger than 18 years, and having used 1 to 5 health apps significantly predicted app use (vs nonuse) in adjusted models. Older age and lower BMI predicted early, consistent, and sustained use. About half (532/1017, 52.31%) of the participants completed the 4-month online surveys. A total of 33.5% (183/547), 29.3% (157/536), and 27.1% (143/527) of app users were still using the app for at least 2 days per month during months 4, 5, and 6 of the study, respectively. CONCLUSIONS: EHR recruitment offers an efficient (ie, high reach, low touch, and minimal participant burden) approach to recruiting participants from health care settings into mHealth research. Efforts to recruit and retain less engaged subgroups are needed to collect more generalizable data. Additionally, future app iterations should include more evidence-based features to increase participant use

Arsenic Exposure and Type 2 Diabetes: A Systematic Review of the Experimental and Epidemiologic Evidence

Chronic arsenic exposure has been suggested to contribute to diabetes development. We performed a systematic review of the experimental and epidemiologic evidence on the association of arsenic and type 2 diabetes. We identified 19 in vitro studies of arsenic and glucose metabolism. Five studies reported that arsenic interfered with transcription factors involved in insulin-related gene expression: upstream factor 1 in pancreatic β-cells and peroxisome proliferative-activated receptor γ in preadipocytes. Other in vitro studies assessed the effect of arsenic on glucose uptake, typically using very high concentrations of arsenite or arsenate. These studies provide limited insight on potential mechanisms. We identified 10 in vivo studies in animals. These studies showed inconsistent effects of arsenic on glucose metabolism. Finally, we identified 19 epidemiologic studies (6 in high-arsenic areas in Taiwan and Bangladesh, 9 in occupational populations, and 4 in other populations). In studies from Taiwan and Bangladesh, the pooled relative risk estimate for diabetes comparing extreme arsenic exposure categories was 2.52 (95% confidence interval, 1.69–3.75), although methodologic problems limit the interpretation of the association. The evidence from occupational studies and from general populations other than Taiwan or Bangladesh was inconsistent. In summary, the current available evidence is inadequate to establish a causal role of arsenic in diabetes. Because arsenic exposure is widespread and diabetes prevalence is reaching epidemic proportions, experimental studies using arsenic concentrations relevant to human exposure and prospective epidemiologic studies measuring arsenic biomarkers and appropriately assessing diabetes should be a research priority

Association of Eating and Sleeping Intervals With Weight Change Over Time: The Daily24 Cohort.

Background We aim to evaluate the association between meal intervals and weight trajectory among adults from a clinical cohort. Methods and Results This is a multisite prospective cohort study of adults recruited from 3 health systems. Over the 6-month study period, 547 participants downloaded and used a mobile application to record the timing of meals and sleep for at least 1 day. We obtained information on weight and comorbidities at each outpatient visit from electronic health records for up to 10  years before until 10 months after baseline. We used mixed linear regression to model weight trajectories. Mean age was 51.1 (SD 15.0) years, and body mass index was 30.8 (SD 7.8) kg/

Low and High Birth Weights Are Risk Factors for Nonalcoholic Fatty Liver Disease in Children

OBJECTIVES: To examine the distribution of birth weight in children with nonalcoholic fatty liver disease (NAFLD) compared with the general US population, and to investigate the relationship between birth weight and severity of NAFLD. STUDY DESIGN: A multicenter, cross-sectional study of children with biopsy-proven NAFLD enrolled in the Nonalcoholic Steatohepatitis Clinical Research Network Database. Birth weight was categorized as low birth weight (LBW), normal birth weight (NBW), or high birth weight (HBW) and compared with the birth weight distribution in the general US population. The severity of liver histology was assessed by birth weight category. RESULTS: Children with NAFLD (n = 538) had overrepresentation of both LBW and HBW compared with the general US population (LBW, 9.3%; NBW, 75.8%; HBW, 14.9% vs LBW, 6.1%; NBW, 83.5%; HBW 10.5%; P < .0001). Children with HBW had significantly greater odds of having more severe steatosis (OR, 1.82, 95% CI. 1.15-2.88) and nonalcoholic steatohepatitis (OR, 2.03; 95% CI, 1.21-3.40) compared with children with NBW. In addition, children with NAFLD and LBW had significantly greater odds of having advanced fibrosis (OR, 2.23; 95% CI, 1.08-4.62). CONCLUSION: Birth weight involves maternal and in utero factors that may have long-lasting consequences. Children with both LBW and HBW may be at increased risk for developing NAFLD. Among children with NAFLD, those with LBW or HBW appear to be at increased risk for more severe disease

Pioglitazone, Vitamin E, or Placebo for Nonalcoholic Steatohepatitis

Background Nonalcoholic steatohepatitis is a common liver disease that can progress to cirrhosis. Currently, there is no established treatment for this disease. Methods We randomly assigned 247 adults with nonalcoholic steatohepatitis and without diabetes to receive pioglitazone at a dose of 30 mg daily (80 subjects), vitamin E at a dose of 800 IU daily (84 subjects), or placebo (83 subjects), for 96 weeks. The primary outcome was an improvement in histologic features of nonalcoholic steatohepatitis, as assessed with the use of a composite of standardized scores for steatosis, lobular inflammation, hepatocellular ballooning, and fibrosis. Given the two planned primary comparisons, P values of less than 0.025 were considered to indicate statistical significance. Results Vitamin E therapy, as compared with placebo, was associated with a significantly higher rate of improvement in nonalcoholic steatohepatitis (43% vs. 19%, P=0.001), but the difference in the rate of improvement with pioglitazone as compared with placebo was not significant (34% and 19%, respectively; P=0.04). Serum alanine and aspartate aminotransferase levels were reduced with vitamin E and with pioglitazone, as compared with placebo (P Conclusions Vitamin E was superior to placebo for the treatment of nonalcoholic steatohepatitis in adults without diabetes. There was no benefit of pioglitazone over placebo for the primary outcome; however, significant benefits of pioglitazone were observed for some of the secondary outcomes. (ClinicalTrials.gov number, NCT00063622.