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.

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.