Excess natural-cause mortality in US counties and its association with reported COVID-19 deaths.

In the United States, estimates of excess deaths attributable to the COVID-19 pandemic have consistently surpassed reported COVID-19 death counts. Excess deaths reported to non-COVID-19 natural causes may represent unrecognized COVID-19 deaths, deaths caused by pandemic health care interruptions, and/or deaths from the pandemic's socioeconomic impacts. The geographic and temporal distribution of these deaths may help to evaluate which explanation is most plausible. We developed a Bayesian hierarchical model to produce monthly estimates of excess natural-cause mortality for US counties over the first 30 mo of the pandemic. From March 2020 through August 2022, 1,194,610 excess natural-cause deaths occurred nationally [90% PI (Posterior Interval): 1,046,000 to 1,340,204]. A total of 162,886 of these excess natural-cause deaths (90% PI: 14,276 to 308,480) were not reported to COVID-19. Overall, 15.8 excess deaths were reported to non-COVID-19 natural causes for every 100 reported COVID-19 deaths. This number was greater in nonmetropolitan counties (36.0 deaths), the West (Rocky Mountain states: 31.6 deaths; Pacific states: 25.5 deaths), and the South (East South Central states: 26.0 deaths; South Atlantic states: 25.0 deaths; West South Central states: 24.2 deaths). In contrast, reported COVID-19 death counts surpassed estimates of excess natural-cause deaths in metropolitan counties in the New England and Middle Atlantic states. Increases in reported COVID-19 deaths correlated temporally with increases in excess deaths reported to non-COVID-19 natural causes in the same and/or prior month. This suggests that many excess deaths reported to non-COVID-19 natural causes during the first 30 mo of the pandemic in the United States were unrecognized COVID-19 deaths.

Affordable Health Insurance Options for Small Business and Low-Wage Workers Remains Elusive: Experience With New Health Reimbursement Arrangements in New Jersey.

Low-wage workers and those employed by small businesses are least likely to be offered health insurance coverage and they are over-represented among the uninsured. Two new forms of health reimbursement arrangements (HRAs) that allow employers to help fund individual market coverage for workers have been touted as breakthrough strategies to help fill this gap. Despite several years of experience and low adoption, little is known about employer understanding of or views about these HRA options. Consistent with other evidence, only 11.8% of New Jersey employers we surveyed offer or plan to offer either of the HRA options. Few respondents (18.5%) report familiarity with either option. Even among businesses that offer or plan to offer this form of HRA, under half (47.6%) say that they are familiar with them. Other reasons cited for not offering these options include broker advice and complexity. While more investigation is needed, these findings suggest that new strategies should be explored to fill the gap in health insurance for low-wage and small business employees.

COVID-19 and All-Cause Mortality by Race, Ethnicity, and Age Across Five Periods of the Pandemic in the United States.

Racial/ethnic and age disparities in COVID-19 and all-cause mortality during 2020 are well documented, but less is known about their evolution over time. We examine changes in age-specific mortality across five pandemic periods in the United States from March 2020 to December 2022 among four racial/ethnic groups (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Asian) for ages 35+. We fit Gompertz models to all-cause and COVID-19 death rates by 5-year age groups and construct age-specific racial/ethnic mortality ratios across an Initial peak (Mar-Aug 2020), Winter peak (Nov 2020-Feb 2021), Delta peak (Aug-Oct 2021), Omicron peak (Nov 2021-Feb 2022), and Endemic period (Mar-Dec 2022). We then compare to all-cause patterns observed in 2019. The steep age gradients in COVID-19 mortality in the Initial and Winter peak shifted during the Delta peak, with substantial increases in mortality at working ages, before gradually returning to an older age pattern in the subsequent periods. We find a disproportionate COVID-19 mortality burden on racial and ethnic minority populations early in the pandemic, which led to an increase in all-cause mortality disparities and a temporary elimination of the Hispanic mortality advantage at certain age groups. Mortality disparities narrowed over time, with racial/ethnic all-cause inequalities during the Endemic period generally returning to pre-pandemic levels. Black and Hispanic populations, however, faced a younger age gradient in all-cause mortality in the Endemic period relative to 2019, with younger Hispanic and Black adults in a slightly disadvantageous position and older Black adults in a slightly advantageous position, relative to before the pandemic.

Monthly excess mortality across counties in the United States during the COVID-19 pandemic, March 2020 to February 2022.

Excess mortality is the difference between expected and observed mortality in a given period and has emerged as a leading measure of the COVID-19 pandemic's mortality impact. Spatially and temporally granular estimates of excess mortality are needed to understand which areas have been most impacted by the pandemic, evaluate exacerbating factors, and inform response efforts. We estimated all-cause excess mortality for the United States from March 2020 through February 2022 by county and month using a Bayesian hierarchical model trained on data from 2015 to 2019. An estimated 1,179,024 excess deaths occurred during the first 2 years of the pandemic (first: 634,830; second: 544,194). Overall, excess mortality decreased in large metropolitan counties but increased in nonmetropolitan counties. Despite the initial concentration of mortality in large metropolitan Northeastern counties, nonmetropolitan Southern counties had the highest cumulative relative excess mortality by July 2021. These results highlight the need for investments in rural health as the pandemic's rural impact grows.

COVID-19 Mortality by Race and Ethnicity in US Metropolitan and Nonmetropolitan Areas, March 2020 to February 2022.

Importance: Prior research has established that Hispanic and non-Hispanic Black residents in the US experienced substantially higher COVID-19 mortality rates in 2020 than non-Hispanic White residents owing to structural racism. In 2021, these disparities decreased. Objective: To assess to what extent national decreases in racial and ethnic disparities in COVID-19 mortality between the initial pandemic wave and subsequent Omicron wave reflect reductions in mortality vs other factors, such as the pandemic's changing geography. Design, Setting, and Participants: This cross-sectional study was conducted using data from the US Centers for Disease Control and Prevention for COVID-19 deaths from March 1, 2020, through February 28, 2022, among adults aged 25 years and older residing in the US. Deaths were examined by race and ethnicity across metropolitan and nonmetropolitan areas, and the national decrease in racial and ethnic disparities between initial and Omicron waves was decomposed. Data were analyzed from June 2021 through March 2023. Exposures: Metropolitan vs nonmetropolitan areas and race and ethnicity. Main Outcomes and Measures: Age-standardized death rates. Results: There were death certificates for 977 018 US adults aged 25 years and older (mean [SD] age, 73.6 [14.6] years; 435 943 female [44.6%]; 156 948 Hispanic [16.1%], 140 513 non-Hispanic Black [14.4%], and 629 578 non-Hispanic White [64.4%]) that included a mention of COVID-19. The proportion of COVID-19 deaths among adults residing in nonmetropolitan areas increased from 5944 of 110 526 deaths (5.4%) during the initial wave to a peak of 40 360 of 172 515 deaths (23.4%) during the Delta wave; the proportion was 45 183 of 210 554 deaths (21.5%) during the Omicron wave. The national disparity in age-standardized COVID-19 death rates per 100 000 person-years for non-Hispanic Black compared with non-Hispanic White adults decreased from 339 to 45 deaths from the initial to Omicron wave, or by 293 deaths. After standardizing for age and racial and ethnic differences by metropolitan vs nonmetropolitan residence, increases in death rates among non-Hispanic White adults explained 120 deaths/100 000 person-years of the decrease (40.7%); 58 deaths/100 000 person-years in the decrease (19.6%) were explained by shifts in mortality to nonmetropolitan areas, where a disproportionate share of non-Hispanic White adults reside. The remaining 116 deaths/100 000 person-years in the decrease (39.6%) were explained by decreases in death rates in non-Hispanic Black adults. Conclusions and Relevance: This study found that most of the national decrease in racial and ethnic disparities in COVID-19 mortality between the initial and Omicron waves was explained by increased mortality among non-Hispanic White adults and changes in the geographic spread of the pandemic. These findings suggest that despite media reports of a decline in disparities, there is a continued need to prioritize racial health equity in the pandemic response.

Associations between mortality from COVID-19 and other causes: A state-level analysis.

BACKGROUND: During the COVID-19 pandemic, the high death toll from COVID-19 was accompanied by a rise in mortality from other causes of death. The objective of this study was to identify the relationship between mortality from COVID-19 and changes in mortality from specific causes of death by exploiting spatial variation in these relationships across US states. METHODS: We use cause-specific mortality data from CDC Wonder and population estimates from the US Census Bureau to examine relationships at the state level between mortality from COVID-19 and changes in mortality from other causes of death. We calculate age-standardized death rates (ASDR) for three age groups, nine underlying causes of death, and all 50 states and the District of Columbia between the first full year of the pandemic (March 2020-February 2021) and the year prior (March 2019-February 2020). We then estimate the relationship between changes in cause-specific ASDR and COVID-19 ASDR using linear regression analysis weighted by the size of the state's population. RESULTS: We estimate that causes of death other than COVID-19 represent 19.6% of the total mortality burden associated with COVID-19 during the first year of the COVID-19 pandemic. At ages 25+, circulatory disease accounted for 51.3% of this burden while dementia (16.4%), other respiratory diseases (12.4%), influenza/pneumonia (8.7%) and diabetes (8.6%) also contribute. In contrast, there was an inverse association across states between COVID-19 death rates and changes in death rates from cancer. We found no state-level association between COVID-19 mortality and rising mortality from external causes. CONCLUSIONS: States with unusually high death rates from COVID-19 experienced an even larger mortality burden than implied by those rates alone. Circulatory disease served as the most important route through which COVID-19 mortality affected death rates from other causes of death. Dementia and other respiratory diseases made the second and third largest contributions. In contrast, mortality from neoplasms tended to decline in states with the highest death rates from COVID-19. Such information may help to inform state-level responses aimed at easing the full mortality burden of the COVID-19 pandemic.

Differences Between Reported COVID-19 Deaths and Estimated Excess Deaths in Counties Across the United States, March 2020 to February 2022.

Accurate and timely tracking of COVID-19 deaths is essential to a well-functioning public health surveillance system. The extent to which official COVID-19 death tallies have captured the true toll of the pandemic in the United States is unknown. In the current study, we develop a Bayesian hierarchical model to estimate monthly excess mortality in each county over the first two years of the pandemic and compare these estimates to the number of deaths officially attributed to Covid-19 on death certificates. Overall, we estimated that 268,176 excess deaths were not reported as Covid-19 deaths during the first two years of the Covid-19 pandemic, which represented 23.7% of all excess deaths that occurred. Differences between excess deaths and reported COVID-19 deaths were substantial in both the first and second year of the pandemic. Excess deaths were less likely to be reported as COVID-19 deaths in the Mountain division, in the South, and in nonmetro counties. The number of excess deaths exceeded COVID-19 deaths in all Census divisions except for the New England and Middle Atlantic divisions where there were more COVID-19 deaths than excess deaths in large metro areas and medium or small metro areas. Increases in excess deaths not assigned to COVID-19 followed similar patterns over time to increases in reported COVID-19 deaths and typically preceded or occurred concurrently with increases in reported COVID-19 deaths. Estimates from this study can be used to inform targeting of resources to areas in which the true toll of the COVID-19 pandemic has been underestimated.

Monthly excess mortality across counties in the United States during the Covid-19 pandemic, March 2020 to February 2022.

Excess mortality is the difference between expected and observed mortality in a given period and has emerged as a leading measure of the overall impact of the Covid-19 pandemic that is not biased by differences in testing or cause-of-death assignment. Spatially and temporally granular estimates of excess mortality are needed to understand which areas have been most impacted by the pandemic, evaluate exacerbating and mitigating factors, and inform response efforts, including allocating resources to affected communities. We estimated all-cause excess mortality for the United States from March 2020 through February 2022 by county and month using a Bayesian hierarchical model trained on data from 2015 to 2019. An estimated 1,159,580 excess deaths occurred during the first two years of the pandemic (first: 620,872; second: 538,708). Overall, excess mortality decreased in large metropolitan counties, but increased in nonmetro counties, between the first and second years of the pandemic. Despite the initial concentration of mortality in large metropolitan Northeast counties, beginning in February 2021, nonmetro South counties had the highest cumulative relative excess mortality. These results highlight the need for investments in rural health as the pandemic's disproportionate impact on rural areas continues to grow.

The role of context in shaping the relationship between physical health and suicide over the life course.

U.S. suicide rates are at a thirty-year high while physical health, as measured by life expectancy and pain, has declined, particularly for those without a college degree. We investigate how these patterns may be related by exploring the role of physical health problems in suicide deaths using 2019 data from the National Violent Death Reporting System. We estimate multilevel logistic regression models to examine (1) how individual risk factors are associated with the likelihood of a physical health circumstance underlying a suicide over the life course and (2) how context - the socioeconomic, health and policy environment of the state in which a decedent resides - may play a role. Physical health circumstances were present in about 20% of all suicides and in over half of suicide deaths for the older population in 2019. A gender crossover effect exists, in which women are more likely to have a physical health problem contribute to a suicide prior to age 60, but men surpass women after age 60 in that probability. Net of individual characteristics, we find significant variation across states in the likelihood of physical health circumstances. For all age groups, physical health circumstances are more likely in states that are less densely populated with weaker gun control laws and higher suicide rates. Among decedents younger than 65, the likelihood is elevated in states with limited health care access. This study highlights the critical interaction between physical and mental well-being, the ways in which that interaction may be experienced differently by gender, and the important role of social safety nets in prevention.

The effect of Medicaid expansion on Medicaid participation, payer mix, and labor supply in primary care.

Evidence of increased health care utilization associated with the Medicaid expansion suggests that clinicians increased capacity to meet demand. However, little is known about the mechanism underlying this response. Using a novel source of all-payer data, we quantified clinicians' response to the Medicaid expansion - examining whether and how they changed their Medicaid participation decisions, payer mix, and overall labor supply. Primary care clinicians in expansion states provided an average of 49 additional appointments per year (a 21% relative increase) for patients insured by Medicaid, compared to clinicians in non-expansion states - with new-patient visits representing half (25 appointments) of this overall increase. Clinicians did not increase their labor supply to accommodate these additional appointments. They instead offset the 1.7 percentage point average increase in Medicaid payer mix with an equivalent reduction in commercial payer mix. However, this reduction in commercial patient share represented only a 2.8% relative decrease, with commercially insured patients still comprising the majority of the average clinician's patient panel. Subsample analyses revealed a larger increase in care for Medicaid patients among clinicians with high Medicaid participation preceding the eligibility expansion.

COVID-19 and excess mortality in the United States: A county-level analysis.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) excess deaths refer to increases in mortality over what would normally have been expected in the absence of the COVID-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to COVID-19. In this study, we take advantage of county-level variation in COVID-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to COVID-19 varies across subsets of counties defined by sociodemographic and health characteristics. METHODS AND FINDINGS: In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct COVID-19 and all-cause mortality occurring in US counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a 10-week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more COVID-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black, and 59.6% non-Hispanic White. A total of 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and COVID-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to COVID-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than COVID-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to COVID-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of COVID-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to COVID-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics. CONCLUSIONS: In this study, we found that direct COVID-19 death counts in the US in 2020 substantially underestimated total excess mortality attributable to COVID-19. Racial and socioeconomic inequities in COVID-19 mortality also increased when excess deaths not assigned to COVID-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

Assessing the Impact of the Covid-19 Pandemic on US Mortality: A County-Level Analysis.

BACKGROUND: Covid-19 excess deaths refer to increases in mortality over what would normally have been expected in the absence of the Covid-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to Covid-19. In this study, we take advantage of county-level variation in Covid-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to Covid-19 varies across subsets of counties defined by sociodemographic and health characteristics. METHODS AND FINDINGS: In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct Covid-19 and all-cause mortality occurring in U.S. counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a ten week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more Covid-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black and 59.6% non-Hispanic White. 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and Covid-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to Covid-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than Covid-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to Covid-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of Covid-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to Covid-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics. CONCLUSIONS: In this study, we found that direct Covid-19 death counts in the United States in 2020 substantially underestimated total excess mortality attributable to Covid-19. Racial and socioeconomic inequities in Covid-19 mortality also increased when excess deaths not assigned to Covid-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

The Secret Menu in Health Care: A Cash Market for Imaging in California.

In addition to the prices they negotiate with private health insurers, most providers also have a cash price schedule for patients who have the wherewithal to ask and are willing to pay in full when they receive a service. This is the first study that estimates the potential cost saving of allowing privately-insured consumers to observe both in-network negotiated prices and cash prices, which is of particular interest given the growing importance of high-deductible health plans and a recent executive order mandating greater price transparency. Using data from five private health insurers and 142 imaging facilities in the San Francisco Bay Area, we estimate that patients could save between 10% and 22% of their insurer's in-network price by paying cash. Potential savings are much larger (between 45% and 64% of their insurer's in-network price) if consumers observe both cash and in-network prices and select the facility in the region offering the lowest price for a particular service.

Increases in BMI and chronic pain for US adults in midlife, 1992 to 2016.

Recent unprecedented increases in mortality and morbidity during midlife are often ascribed to rising despair in the US population. An alternative and less often examined explanation is that these trends reflect, at least in part, the lagged effects of the obesity epidemic. Adults in midlife today are more likely to live with obesity and have a greater cumulative exposure to excess adiposity during their lifetime than any previous generation. Prior work has demonstrated a link between obesity and mortality risk at midlife, but the mechanisms remain unclear. Pain may represent one important pathway linking obesity to mortality trends. Pain is a debilitating condition that has increased significantly over recent decades and is associated with both morbidity and mortality, including suicide and opioid-related mortality. Evidence suggests obesity and pain may be linked, but there is little evidence of an association at the population level. In this paper, we examine to what extent increases in overweight and obesity explain the rising trends in chronic pain observed among middle-aged adults in the US from 1992 to 2016. We assess trends in both mild/moderate nonlimiting pain and severe and/or limiting pain. In doing so, we draw attention to one mechanism through which overweight/obesity may have contributed to recent population health trends. Our analysis found that increases in BMI from 1992 to 2016 may account for up to 20% of the upward trend in mild/moderate nonlimiting pain and 32% of the trend in severe and/or limiting pain for women, and 10% and 19% of the trends respectively for men.

Practice Patterns of Physicians and Nurse Practitioners in Primary Care.

BACKGROUND: Primary care practices increasingly include nurse practitioners (NPs), in addition to physicians. Little is known about how the patient mix and clinical activities of colocated physicians and NPs compare. OBJECTIVES: To describe the clinical activities of NPs, compared with physicians. RESEARCH DESIGN: We used claims and electronic health record data from athenahealth Inc., on primary care practices in 2017 and a cross-sectional analysis with practice fixed effects. SUBJECTS: Patients receiving treatment from physicians and NPs within primary care practices. MEASURES: First, we measured patient characteristics (payer, age, sex, race, chronic condition count) and visit characteristics (new patient, scheduled duration, same-day visit, after-hours visit). Second, we measured procedures performed and diagnoses recorded during each visit. Finally, we measured daily quantity (visit volume, minutes scheduled for patient care, total work relative value units billed) of care. RESULTS: Relative to physicians, NPs treated younger and healthier patients. NPs also had a larger share of patients who were female, non-White, and covered by Medicaid, commercial insurance, or no insurance. NPs scheduled longer appointments and treated more patients on a same-day or after-hours basis. On average, "overlapping" services-those performed by NPs and physicians within the same practice-represented 92% of all service volume. The small share of services performed exclusively by physicians reflected greater clinical intensity. On a daily basis, NPs provided fewer and less intense visits than physicians within the same practice. CONCLUSIONS: Our findings suggest considerable overlap between the clinical activities of colocated NPs and physicians, with some differentiation based on intensity of services provided.

Obesity and Incident Prescription Opioid Use in the U.S., 2000-2015.

INTRODUCTION: Prior studies have identified associations between obesity and numerous conditions that increase risks for chronic pain. However, the impact of obesity on prescription opioid use is not well known. This study investigates the association between obesity and incidence of long-term prescription opioid use. METHODS: Fifteen panels of the Medical Expenditure Panel Survey from 2000 to 2015 were pooled to generate a sample of civilian non-institutionalized adults aged 30-84 years who were prescription opioid-naïve for approximately 9 months. Incident long-term prescription opioid use was defined as reporting use at 2 of 3 interviews during a 15-month follow-up. BMI was reported at baseline. Analyses were completed in 2019. RESULTS: Among opioid-naïve adults (n=89,629), obesity was strongly associated with incident long-term prescription opioid use. The association increased at progressively higher BMI values, with 24% elevated odds (95% CI=7%, 44%) in adults with overweight (25-29.9 kg/m2) and 158% increased odds (95% CI=106%, 224%) among adults with Class III obesity (40-49.9 kg/m2). These associations grew with higher-dosage opioids. Of the reasons for opioid use, joint pain, back pain, injury, and muscle/nerve pain contributed the most to the excess use observed among adults with obesity. At the population level, 27.0% of incident long-term prescription opioid use (95% CI=19.0%, 34.8%) was attributable to adults having a BMI above normal weight (25-49.9 kg/m2). CONCLUSIONS: These findings suggest that obesity has contributed to prescription opioid use in the U.S. Future investments in chronic pain reduction may benefit from increased integration with obesity prevention and treatment.

Association of Obesity With Prescription Opioids for Painful Conditions in Patients Seeking Primary Care in the US.

Importance: Prior studies have identified an association between obesity and prescription opioid use in the US. However, the pain conditions that are factors in this association remain unestablished. Objective: To investigate the association between obesity and pain diagnoses recorded by primary care clinicians as reasons for prescription of opioids. Design, Setting, and Participants: A cross-sectional study including 565 930 patients aged 35 to 64 years with a body mass index (BMI) measurement recorded in 2016 was conducted. Electronic health records of patients seen by primary care clinicians in the US in the multipayer athenahealth network from January 1, 2015, to December 31, 2017, were reviewed, and data were analyzed from March 1 to September 15, 2019. Main Outcomes and Measures: Any prescription of opioids in the 365 days before or after the first BMI measurement in 2016 were identified. All International Classification of Diseases, Ninth Revision, and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, claims within 7 days before each opioid prescription were captured and classified using a pain diagnosis typologic system. Weight was categorized as underweight (BMI, 18.5-19.9), normal weight (BMI, 20.0-24.9), overweight (BMI, 25.0-29.9), obese I (BMI, 30-34.9), obese II (BMI, 35.0-39.9), obese III (BMI, 40.0-49.9), and obese IV (BMI, 50.0-80.0). Results: Among 565 930 patients, 329 083 (58.1%) were women. A total of 125 093 patients (22.1%) were aged 35 to 44 years, 199 384 patients (35.2%) were 45 to 54 years, and 241 453 patients (42.7%) were 55 to 64 years. A total of 177 631 patients (31.4%) were overweight and 273 135 patients (48.2%) were obese at baseline. Over 2 years, 93 954 patients (16.6%) were prescribed opioids. The risk of receiving prescription opioids increased progressively with BMI (adjusted relative risk for overweight: 1.08; 95% CI, 1.06-1.10; obese I: 1.24; 95% CI, 1.22-1.26; obese II: 1.33; 95% CI, 1.30-1.36; obese III: 1.48; 95% CI, 1.45-1.51; and obese IV, 1.71; 95% CI, 1.65-1.77). The percentage of patients with opioid prescriptions attributable to an overweight or obese BMI was 16.2% (95% CI, 15.0%-17.4%). Prescription opioids for management of osteoarthritis (relative risk for obese vs normal weight, 1.90; 95% CI, 1.77-2.05) and other joint disorders (relative risk, 1.63; 95% CI, 1.55-1.72) both had stronger associations with obesity than the mean for any pain diagnosis (relative risk, 1.33; 95% CI, 1.31-1.36). Osteoarthritis, other joint disorders, and other back disorders comprised a combined 53.4% of the absolute difference in prescription of opioids by obesity. Conclusions and Relevance: Joint and back disorders appear to be the most important diagnoses in explaining the increased receipt of opioid prescriptions among patients with obesity. Addressing the opioid crisis will require attention to underlying sources of demand for prescription opioids, including obesity, through its associations with pain.

Trends in Prescription Analgesic Use Among Adults With Musculoskeletal Conditions in the United States, 1999-2016.

Importance: Monitoring trends in prescription analgesic use among adults with musculoskeletal conditions provides insight into how changing prescribing practices, guidelines, and policy measures may affect those who need pain management. Objective: To evaluate trends in prescription opioid use and nonopioid analgesic use among adults with functional limitations attributable to musculoskeletal conditions. Design, Setting, and Participants: This repeated cross-sectional study uses data from the National Health and Nutrition Examination Study from 1999 to 2016. Data were analyzed from January to July 2019. The participants were adults aged 30 to 79 years who reported functional limitations due to back or neck problems and/or arthritis or rheumatism. Main Outcomes and Measures: Any use of a prescription opioid or exclusive use of a prescription nonopioid analgesic. Results: In this population of 7256 adults with 1 or more functional limitations attributable to a musculoskeletal condition (4226 women [59.9%]; 3508 [74.4%] non-Hispanic white individuals; median [interquartile range] age, 63 [53-70] years), opioid use and exclusive nonopioid analgesic use exhibited approximately reciprocal patterns of change from 1999 to 2016. Opioid use increased significantly (difference in prevalence for 2015-2016 vs 1999-2000, 7.2%; 95% CI, 1.3% to 13%; P for trend = .002), and exclusive use of nonopioid analgesics decreased significantly (difference in prevalence for 2015-2016 vs 1999-2000, -13%; 95% CI, -19% to -7.5%; P for trend < .001) during this period. The increase in any opioid use was driven by long-term rather than short-term use. A crossover in the prevalence of opioid use and exclusive use of nonopioid analgesics occurred between 2003 and 2006, after which opioid use was more prevalent. Between 2013 and 2016, decreases in opioid use were observed among men (difference in prevalence for 2015-2016 vs 2013-2014, -11%; 95% CI, -21% to 1.8%) and participants with less than a high school education (difference, -15%; 95% CI, -24% to -6.1%). During this same period, exclusive nonopioid analgesic use also decreased markedly across the population (difference, -5.3%; 95% CI, -9.1% to -1.5%). Conclusions and Relevance: The substitution of opioids for nonopioid analgesics between 2003 and 2006 may have occurred as evidence emerged on the cardiovascular risks associated with nonopioid analgesics. Reductions in opioid use between 2013 and 2016 were most substantial among those with low socioeconomic status, who may encounter barriers in accessing alternatives. Despite those decreases, opioid use remained more prevalent in 2015 to 2016 than in 1999 to 2000, suggesting a potentially long tail for the opioid epidemic.