ImportanceScreening for lung cancer with low-dose computed tomography (LDCT) has been shown to reduce lung cancer mortality in trials that included relatively younger, healthier, and predominantly White populations. The comorbidity profiles among patients undergoing lung cancer screening in practice settings are poorly understood.ObjectiveTo evaluate the comorbidity profiles of patients in the Personalized Lung Cancer Screening (PLuS) cohort as a clinical setting vs the National Lung Screening Trial (NLST) participants in a clinical trial setting.Design, Setting, and ParticipantsThis multicenter cohort study was conducted across 3 health care systems in California, Florida, and South Carolina and included patients who underwent LDCT lung cancer screening between 2016 and 2021. Data were analyzed between January 1, 2016, and December 31, 2021.ExposuresReceipt of the LDCT scan identified through Current Procedural Terminology and Healthcare Common Procedure Coding System codes.Main Outcomes and MeasuresDetailed comorbidity data, measures of pulmonary function, and study data abstracted from electronic health records and institutional, Surveillance, Epidemiology, and End Results (SEER), and state registries were compared with self-reported comorbid conditions of participants in the LDCT arm of the NLST.ResultsThe PLuS cohort (n = 31 795) included 49.0% participants aged 65 years or older vs 26.6% in the NLST cohort (n = 26 723); 23.3% were individuals of racial and ethnic minority groups in the PLuS cohort compared with 8.5% in the NLST. The prevalence of comorbidity was substantially higher in the PLuS cohort than the NLST group, particularly chronic obstructive pulmonary disease (32.7% vs 17.5%), diabetes (24.6% vs 9.7%), and heart disease (15.9% vs 12.9%). Among those in the PLuS cohort, 19.3% had a Charlson Comorbidity Index score of 4 or higher, 18.0% had a frailty index greater than 0.20, 16.9% had a forced expiratory volume in 1 second (FEV-1) lower than 50% of predicted, and almost 5% had an ejection fraction lower than 40%. The prevalence of multimorbidity and frailty was especially high among those in the 75 years or older age group.Conclusions and RelevanceThis study found that the PLuS cohort members were older, had greater illness severity, and more racially and ethnically diverse than the NLST participants. Older patients and those with consequential comorbidity likely had different risk-benefit profiles, which may have affected screening outcomes. The high prevalence of multimorbidity, frailty, and impaired cardiopulmonary function in the PLuS cohort suggests that the balance of benefits and harms observed in the NLST group may not translate to the clinical setting.

ImportanceResearch shows that Tobacco 21 (T21) policies with a minimum legal access age for tobacco products of 21 years reduce smoking, yet their impact varies across US states due to differences in smoking behaviors, mortality rates, and policy coverage.ObjectiveTo quantify potential reductions in smoking-attributable mortality associated with Tobacco 21 policies for each of the 50 states and Washington, DC.Design, Setting, and ParticipantsThe Cancer Intervention Surveillance and Modeling Network (CISNET) Tobacco Control Policy Model of smoking was used with detailed state-specific data on smoking initiation, smoking cessation and mortality rates as they vary by age, gender, and birth cohort for 50 US states and the District of Columbia. This was integrated with comprehensive data on T21 policy coverage at the local and state levels from 2005 to 2024, and then T21 policy effects from quasi-experimental studies were applied to simulate each state’s experience of T21 policies, quantifying potential mortality reductions from 2005 to 2100.ExposuresCigarette smoking.Main Outcomes and MeasuresEstimated smoking-attributable deaths averted and life-years gained compared with a baseline scenario.ResultsEarly statewide T21 adoption in California, combined with its large population, was associated with more than 27 000 premature deaths averted through 2100, whereas statewide implementation in Kentucky was associated with 15 000 averted premature deaths. In Massachusetts, T21 policies were associated with 8000 averted premature deaths, largely attributed to municipal T21 policies covering most residents. Wisconsin—lacking state or local policies—requires enforcement of federal T21 to prevent up to 10 000 premature deaths. Across the country, comprehensive enforcement of federal, state, and local T21 laws were associated with up to 526 000 premature deaths averted and 13.3 million life-years gained by 2100. Enforcement of only state and local policies was associated with 442 000 premature deaths averted.Conclusions and RelevanceThis study found that early adoption and implementation of T21 policies maximizes potential premature mortality reductions. However, the strength of T21 policies and enforcement varies widely across states. Enforcement of the federal T21 law is critical in the 8 states without state-level T21 cigarette policies of their own.

This cross-sectional study compares the small molecule generic drug markets of a group of high-income countries with similar pharmaceutical regulatory environments.

This secondary analysis of a cluster randomized clinical trial examined a guideline-based care model for patients with low back pain, specifically whether physicians switched from opioids to low-risk or high-risk nonopioid pain medicines.

ImportanceMenopausal hormone therapy (MHT) is the treatment of choice for symptoms of menopause. However, its adoption is hindered by the risk-benefit trade-off in relation to acute and chronic diseases.ObjectiveTo evaluate trends in and correlates of MHT use among postmenopausal women in the US from 1999 to March 2020.Design, Setting, and ParticipantsThis serial cross-sectional analysis of MHT use used data from the nationally representative National Health and Nutrition Examination Survey (NHANES). Participants included noninstitutionalized US postmenopausal women from 10 NHANES study cycles (1999-2000 to 2017-March 2020 [pre–COVID-19 pandemic]). Data were analyzed from December 2023 to April 2024.ExposuresNHANES study cycle.Main Outcomes and MeasuresPrevalence of MHT use was extracted from the prescription medication data collected during NHANES household interviews. MHT formulations were determined by hormone type.ResultsData on 13 048 US postmenopausal women (47.1% ≥65 years old) were analyzed. From 1999 to 2020, the prevalence of MHT use decreased among women of all age groups, from 26.9% (95% CI, 22.6%-31.7%) in 1999 to 4.7% (95% CI, 3.4%-6.5%) in 2020. Until 2002, MHT use was highest among women aged 52 to 65 years, but since 2005, MHT use has been highest among women younger than 52 years. MHT use decreased by 23.5% (95% CI, 11.4%-35.6%), 31.4% (95% CI, 23.4%-39.5%), and 10.6% (95% CI, 6.3%-14.8%) for women younger than 52 years, 52 years to younger than 65 years, and 65 years and older, respectively. Prevalence of MHT use decreased from 13.8% (95% CI, 8.5%-21.7%) to 2.6% (95% CI, 1.5%-4.6%) for Hispanic women, 11.9% (95% CI, 8.5%-16.3%) to 0.5% (95% CI, 0.2%-1.1%) for non-Hispanic Black women, and 31.4% (95% CI, 27.1%-36.1%) to 5.8% (95% CI, 4.1%-8.2%) for non-Hispanic White women. Non-Hispanic White women consistently had the highest prevalence of MHT use. Estrogen-only formulation accounted for more than 50% of the MHT for most study periods. The prevalence of MHT use varied by family income-to-poverty ratio, health insurance coverage in all racial and ethnic groups, weight, and smoking status among non-Hispanic White women, as well as by education attainment among non-Hispanic Black and Hispanic women.Conclusions and RelevanceResults of this cross-sectional study show that over the past 2 decades, MHT use declined among US postmenopausal women of all age and racial and ethnic groups. Women of racial and ethnic minority groups had lower prevalence of MHT use compared to non-Hispanic White women.

ImportanceSponsorship of promotional events for health professionals is a key facet of marketing campaigns for pharmaceuticals and medical devices; however, there appears to be limited transparency regarding the scope and scale of this spending.ObjectiveTo develop a novel method for describing the scope and quantifying the spending by US pharmaceutical and medical companies on industry-sponsored promotional events for particular products.Design and SettingThis was a cross-sectional study using records from the Centers for Medicare & Medicaid’s Open Payments database on payments made to prescribing clinicians from January 1 to December 21, 2022.Main Outcomes and MeasuresAn event-centric approach was used to define sponsored events as groupings of payment records with matching variables. Events were characterized by value (coffee, lunch, dinner, or banquet) and number of attendees (small vs large). To test the method, the number of and total spending for each type of event across professional groups were calculated and used to identify the top 10 products related to dinner events. To validate the method, we extracted all event details advertised on the websites of 4 state-level nurse practitioner associations that regularly hosted industry-sponsored dinner events during 2022 and compared these with events identified in the Open Payments database.ResultsA total of 1 154 806 events sponsored by pharmaceutical and medical device companies were identified for 2022. Of these, 1 151 351 (99.7%) had fewer than 20 attendees, and 922 214 (80.0%) were considered to be a lunch ($10-$30 per person). Seven companies sponsored 16 031 dinners for the top 10 products. Of the 227 sponsored in-person dinner events hosted by the 4 state-level nurse practitioner associations, 168 (74.0%) matched events constructed from the Open Payments dataset.Conclusions and RelevanceThese findings indicate that an event-centric analysis of Open Payments data is a valid method to understand the scope and quantify spending by pharmaceutical and medical device companies on industry-sponsored promotional events attended by prescribers. Expanding and enforcing the reporting requirements to cover all payments to all registered health professionals would improve the accuracy of estimates of the true extent of all sponsored events and their impact on clinical practice.

ImportanceModels predicting health care spending and other outcomes from administrative records are widely used to manage and pay for health care, despite well-documented deficiencies. New methods are needed that can incorporate more than 70 000 diagnoses without creating undesirable coding incentives.ObjectiveTo develop a machine learning (ML) algorithm, building on Diagnostic Item (DXI) categories and Diagnostic Cost Group (DCG) methods, that automates development of clinically credible and transparent predictive models for policymakers and clinicians.Design, Setting, and ParticipantsDXIs were organized into disease hierarchies and assigned an Appropriateness to Include (ATI) score to reflect vagueness and gameability concerns. A novel automated DCG algorithm iteratively assigned DXIs in 1 or more disease hierarchies to DCGs, identifying sets of DXIs with the largest regression coefficient as dominant; presence of a previously identified dominating DXI removed lower-ranked ones before the next iteration. The Merative MarketScan Commercial Claims and Encounters Database for commercial health insurance enrollees 64 years and younger was used. Data from January 2016 through December 2018 were randomly split 90% to 10% for model development and validation, respectively. Deidentified claims and enrollment data were delivered by Merative the following November in each calendar year and analyzed from November 2020 to January 2024.Main Outcome and MeasuresConcurrent top-coded total health care cost. Model performance was assessed using validation sample weighted least-squares regression, mean absolute errors, and mean errors for rare and common diagnoses.ResultsThis study included 35 245 586 commercial health insurance enrollees 64 years and younger (65 901 460 person-years) and relied on 19 clinicians who provided reviews in the base model. The algorithm implemented 218 clinician-specified hierarchies compared with the US Department of Health and Human Services (HHS) hierarchical condition category (HCC) model’s 64 hierarchies. The base model that dropped vague and gameable DXIs reduced the number of parameters by 80% (1624 of 3150), achieved an R2 of 0.535, and kept mean predicted spending within 12% ($3843 of $31 313) of actual spending for the 3% of people with rare diseases. In contrast, the HHS HCC model had an R2 of 0.428 and underpaid this group by 33% ($10 354 of $31 313).Conclusions and RelevanceIn this study, by automating DXI clustering within clinically specified hierarchies, this algorithm built clinically interpretable risk models in large datasets while addressing diagnostic vagueness and gameability concerns.

ImportanceWhile some have argued that cannabis legalization has helped to reduce opioid-related morbidity and mortality in the US, evidence has been mixed. Moreover, existing studies did not account for biases that could arise when policy effects vary over time or across states or when multiple policies are assessed at the same time, as in the case of recreational and medical cannabis legalization.ObjectiveTo quantify changes in opioid prescriptions and opioid overdose deaths associated with recreational and medical cannabis legalization in the US.Design, Setting, and ParticipantsThis quasiexperimental, generalized difference-in-differences analysis used annual state-level data between January 2006 and December 2020 to compare states that legalized recreational or medical cannabis vs those that did not.InterventionRecreational and medical cannabis law implementation (proxied by recreational and medical cannabis dispensary openings) between 2006 and 2020 across US states.Main Outcomes and MeasuresOpioid prescription rates per 100 persons and opioid overdose deaths per 100 000 population based on data from the US Centers for Disease Control and Prevention.ResultsBetween 2006 and 2020, 13 states legalized recreational cannabis and 23 states legalized medical cannabis. There was no statistically significant association of recreational or medical cannabis laws with opioid prescriptions or overall opioid overdose mortality across the 15-year study period, although the results also suggested a potential reduction in synthetic opioid deaths associated with recreational cannabis laws (4.9 fewer deaths per 100 000 population; 95% CI, −9.49 to −0.30; P = .04). Sensitivity analyses excluding state economic indicators, accounting for additional opioid laws and using alternative ways to code treatment dates yielded substantively similar results, suggesting the absence of statistically significant associations between cannabis laws and the outcomes of interest during the full study period.Conclusions and RelevanceThe results of this study suggest that, after accounting for biases due to possible heterogeneous effects and simultaneous assessment of recreational and medical cannabis legalization, the implementation of recreational or medical cannabis laws was not associated with opioid prescriptions or opioid mortality, with the exception of a possible reduction in synthetic opioid deaths associated with recreational cannabis law implementation.

ImportanceSugar-sweetened beverage (SSB) taxes are promoted as key policies to reduce cardiometabolic diseases and other conditions, but comprehensive analyses of SSB taxes in the US have been difficult because of the absence of sufficiently large data samples and methods limitations.ObjectiveTo estimate changes in SSB prices and purchases following SSB taxes in 5 large US cities.Design, Setting, and ParticipantsIn this cross-sectional study with an augmented synthetic control analysis, changes in prices and purchases of SSBs were estimated following SSB tax implementation in Boulder, Colorado; Philadelphia, Pennsylvania; Oakland, California; Seattle, Washington; and San Francisco, California. Changes in SSB prices (in US dollars) and purchases (volume in ounces) in these cities in the 2 years following tax implementation were estimated and compared with control groups constructed from other cities. Changes in adjacent, untaxed areas were assessed to detect any increase in cross-border purchases. Data used for this analysis spanned from January 1, 2012, to February 29, 2020, and were analyzed between June 1, 2022, and September 29, 2023.Main Outcomes and MeasuresThe main outcomes were the changes in SSB prices and volume purchased.ResultsUsing nutritional information, 5500 unique universal product codes were classified as SSBs, according to tax designations. The sample included 26 338 stores—496 located in treated localities, 1340 in bordering localities, and 24 502 in the donor pool. Prices of SSBs increased by an average of 33.1% (95% CI, 14.0% to 52.2%; P < .001) during the 2 years following tax implementation, corresponding to an average price increase of 1.3¢ per oz and a 92% tax pass-through rate from distributors to consumers. SSB purchases declined in total volume by an average of 33.0% (95% CI, −2.2% to −63.8%; P = .04) following tax implementation, corresponding to a −1.00 price elasticity of demand. The observed price increase and corresponding volume decrease immediately followed tax implementation, and both outcomes were sustained in the months thereafter. No evidence of increased cross-border purchases following tax implementation was found.Conclusions and RelevanceIn this cross-sectional study, SSB taxes led to substantial, consistent declines in SSB purchases across 5 taxed cities following price increases associated with those taxes. Scaling SSB taxes nationally could yield substantial public health benefits.

ImportancePresident Biden recently prioritized the fight against smoking as key to reducing cancer mortality.ObjectiveTo assess trends in smoking and illuminate the association between smoking and reducing deaths due to cancer.Design, Setting, and ParticipantsThis cross-sectional study used responses to National Health Interview Surveys from January 1, 2011, to December 31, 2022, to characterize trends in current smoking for key sociodemographic groups among US adults.ExposuresAge (18-24, 25-39, 40-64, and ≥65 years), family income (<200%, 200%-399%, and ≥400% of the federal poverty level [FPL]), educational level (less than high school, high school degree or General Educational Development, some college, and college degree or above), and race and ethnicity (Black, Hispanic, White, and other).Main Outcomes and MeasuresWeighted current smoking prevalence with 95% CIs by analysis group from 2011 to 2022. Average annual percentage change (AAPC) in smoking prevalence by analysis group is calculated using Joinpoint regression.ResultsData from 353 555 adults surveyed by the National Health Interview Surveys from 2011 to 2022 were included (12.6% Black, 15.0% Hispanic, 65.2% White, and 7.3% other race or ethnicity). Overall, smoking prevalence decreased among adults aged 18 to 24 years from 19.2% (95% CI, 17.5%-20.9%) in 2011 to 4.9% (95% CI, 3.7%-6.0%) in 2022 at an AAPC of −11.3% (95% CI, −13.2% to −9.4%), while it remained roughly constant among adults 65 years or older at 8.7% (95% CI, 7.9%-9.5%) in 2011 and 9.4% (95% CI, 8.7%-10.2%) in 2022 (AAPC, −0.1% [95% CI, −0.8% to 0.7%]). Among adults 65 years or older, smoking prevalence increased from 13.0% (95% CI, 11.2%-14.7%) in 2011 to 15.8% (95% CI, 14.1%-17.6%) for those with income less than 200% FPL (AAPC, 1.1% [95% CI, 0.1%-2.1%]) and remained roughly constant with no significant change for those of higher income. Similar age patterns are seen across educational level and racial and ethnic groups.Conclusions and RelevanceThis cross-sectional study found that smoking prevalence decreased from 2011 to 2022 in all age groups except adults 65 years or older, with faster decreases among younger than older adults. These findings suggest that the greatest gains in terms of reducing smoking-attributable morbidity and mortality could be achieved by focusing on individuals with low socioeconomic status, as this population has the highest smoking rates and the worst health prospects.

This Viewpoint discusses how the International Classification of Diseases, 11th Revision (ICD-11), made available in January 2022, will affect the US health care system.

ImportancePost–COVID-19 condition (PCC), also known as long COVID, encompasses the range of symptoms and sequelae that affect many people with prior SARS-CoV-2 infection. Understanding the functional, health, and economic effects of PCC is important in determining how health care systems may optimally deliver care to individuals with PCC.ObservationsA rapid review of the literature showed that PCC and the effects of hospitalization for severe and critical illness may limit a person’s ability to perform day-to-day activities and employment, increase their risk of incident health conditions and use of primary and short-term health care services, and have a negative association with household financial stability. Care pathways that integrate primary care, rehabilitation services, and specialized assessment clinics are being developed to support the health care needs of people with PCC. However, comparative studies to determine optimal care models based on their effectiveness and costs remain limited. The effects of PCC are likely to have large-scale associations with health systems and economies and will require substantial investment in research, clinical care, and health policy to mitigate these effects.Conclusions and RelevanceAn accurate understanding of additional health care and economic needs at the individual and health system levels is critical to informing health care resource and policy planning, including identification of optimal care pathways to support people affected by PCC.

This Viewpoint discusses how the COVID-19 pandemic has spotlighted the critical role of unpaid family caregiving.

ImportanceThe US Food and Drug Administration (FDA) has expansive regulatory flexibility regarding the quality and quantity of evidence it deems sufficient to approve new drugs, which has been increasingly used to grant approval based on less certain evidence of benefit. However, the FDA’s regulatory flexibility with respect to standards for approval has not been matched by sufficient stringency in its exercise of postmarket safeguards, including the FDA’s authority and willingness to require confirmation of benefit through postmarket efficacy studies or to withdraw approval when benefit is not confirmed.ObjectiveTo identify and evaluate opportunities for the FDA to extend its authority to require postmarket efficacy studies and use expedited withdrawal procedures for drugs approved despite substantial residual uncertainty outside the accelerated approval pathway.EvidenceThe FDA’s current approaches to regulatory flexibility with respect to standards for drug approval; examples of shortcomings in the postmarket period; existing statutes and regulations governing the scope of the FDA’s authority to impose and enforce postmarket study requirements; and recent legislative reform and agency action regarding the accelerated approval pathway.FindingsDrawing on the broad language of the federal Food, Drug, and Cosmetic Act, the FDA could independently extend its core accelerated approval authorities—required postmarket efficacy studies and expedited withdrawal procedures—to any drug approved with substantial residual uncertainty regarding benefit, such as those supported by a single pivotal trial. To avoid exacerbating existing problems that have become evident during the past 3 decades of experience using the accelerated approval pathway, however, the FDA must ensure that postmarket studies are well designed and completed quickly, while compelling expedited withdrawal when needed.Conclusions and RelevanceUnder current FDA approaches to drug approval, patients, clinicians, and payers may be left with little confidence about a drug’s benefit not only when it first enters the market but also for an extended period thereafter. If policy makers continue to favor earlier market access over evidentiary certainty, flexible approvals must be matched by more expansive use of postmarket safeguards, an approach possible within the FDA’s existing legal authorities.

ImportanceFew interventions are proven to reduce total health care costs, and addressing cost-related nonadherence has the potential to do so.ObjectiveTo determine the effect of eliminating out-of-pocket medication fees on total health care costs.Design, Setting, and ParticipantsThis secondary analysis of a multicenter randomized clinical trial using a prespecified outcome took place across 9 primary care sites in Ontario, Canada (6 in Toronto and 3 in rural areas), where health care services are generally publicly funded. Adult patients (≥18 years old) reporting cost-related nonadherence to medicines in the past 12 months were recruited between June 1, 2016, and April 28, 2017, and followed up until April 28, 2020. Data analysis was completed in 2021.InterventionsAccess to a comprehensive list of 128 medicines commonly prescribed in ambulatory care with no out-of-pocket costs for 3 years vs usual medicine access.Main Outcome and MeasuresTotal publicly funded health care costs over 3 years, including costs of hospitalizations. Health care costs were determined using administrative data from Ontario’s single-payer health care system, and all costs are reported in Canadian dollars with adjustments for inflation.ResultsA total of 747 participants from 9 primary care sites were included in the analysis (mean [SD] age, 51 [14] years; 421 [56.4%] female). Free medicine distribution was associated with a lower median total health care spending over 3 years of $1641 (95% CI, $454-$2792; P = .006). Mean total spending was $4465 (95% CI, −$944 to $9874) lower over the 3-year period.Conclusions and RelevanceIn this secondary analysis of a randomized clinical trial, eliminating out-of-pocket medication expenses for patients with cost-related nonadherence in primary care was associated with lower health care spending over 3 years. These findings suggest that eliminating out-of-pocket medication costs for patients could reduce overall costs of health care.Trial RegistrationClinicalTrials.gov Identifier: NCT02744963

ImportanceBuprenorphine is an effective and cost-effective medication to treat opioid use disorder (OUD), but is not readily available to many people with OUD in the US. The current cost-effectiveness literature does not consider interventions that concurrently increase buprenorphine initiation, duration, and capacity.ObjectiveTo conduct a cost-effectiveness analysis and compare interventions associated with increased buprenorphine treatment initiation, duration, and capacity.Design and SettingThis study modeled the effects of 5 interventions individually and in combination using SOURCE, a recent system dynamics model of prescription opioid and illicit opioid use, treatment, and remission, calibrated to US data from 1999 to 2020. The analysis was run during a 12-year time horizon from 2021 to 2032, with lifetime follow-up. A probabilistic sensitivity analysis on intervention effectiveness and costs was conducted. Analyses were performed from April 2021 through March 2023. Modeled participants included people with opioid misuse and OUD in the US.InterventionsInterventions included emergency department buprenorphine initiation, contingency management, psychotherapy, telehealth, and expansion of hub-and-spoke narcotic treatment programs, individually and in combination.Main Outcomes and MeasuresTotal national opioid overdose deaths, quality-adjusted life years (QALYs) gained, and costs from the societal and health care perspective.ResultsProjections showed that contingency management expansion would avert 3530 opioid overdose deaths over 12 years, more than any other single-intervention strategy. Interventions that increased buprenorphine treatment duration initially were associated with an increased number of opioid overdose deaths in the absence of expanded treatment capacity. With an incremental cost- effectiveness ratio of $19 381 per QALY gained (2021 USD), the strategy that expanded contingency management, hub-and-spoke training, emergency department initiation, and telehealth was the preferred strategy for any willingness-to-pay threshold from $20 000 to $200 000/QALY gained, as it was associated with increased treatment duration and capacity simultaneously.Conclusion and RelevanceThis modeling analysis simulated the effects of implementing several intervention strategies across the buprenorphine cascade of care and found that strategies that were concurrently associated with increased buprenorphine treatment initiation, duration, and capacity were cost-effective.

ImportanceCanada legalized cannabis in October 2018 but initially prohibited the sale of edibles (eg, prepackaged candies). Starting in January 2020, some provinces permitted the sale of commercial cannabis edibles. The association of legalizing cannabis edibles with unintentional pediatric poisonings is uncertain.ObjectiveTo evaluate changes in proportions of all-cause hospitalizations for poisoning due to cannabis in children during 3 legalization policy periods in Canada’s 4 most populous provinces (including 3.4 million children aged 0-9 years).Design, Setting, and ParticipantsThis repeated cross-sectional study included all hospitalizations in children aged 0 to 9 years in Ontario, Alberta, British Columbia, and Quebec between January 1, 2015, and September 30, 2021.ExposuresPrelegalization (January 2015 to September 2018); period 1, in which dried flower only was legalized in all provinces (October 2018 to December 2019); and period 2, in which edibles were legalized in 3 provinces (exposed provinces) and restricted in 1 province (control province) (January 2020 to September 2021).Main Outcomes and MeasuresThe primary outcome was the proportion of hospitalizations due to cannabis poisoning out of all-cause poisoning hospitalizations. Data analysis was performed using descriptive statistics and Poisson regression models.ResultsDuring the 7-year study period, there were 581 pediatric hospitalizations for cannabis poisoning (313 [53.9%] boys; 268 [46.1%] girls; mean [SD] age, 3.6 [2.5] years) and 4406 hospitalizations for all-cause poisonings. Of all-cause poisoning hospitalizations, the rate per 1000 due to cannabis poisoning before legalization was 57.42 in the exposed provinces and 38.50 in the control province. During period 1, the rate per 1000 poisoning hospitalizations increased to 149.71 in the exposed provinces (incidence rate ratio [IRR], 2.55; 95% CI, 1.88-3.46) and to 117.52 in the control province (IRR, 3.05; 95% CI, 1.82-5.11). During period 2, the rate per 1000 poisoning hospitalizations due to cannabis more than doubled to 318.04 in the exposed provinces (IRR, 2.16; 95% CI, 1.68-2.80) but remained similar at 137.93 in the control province (IRR, 1.18; 95% CI, 0.71-1.97).Conclusions and RelevanceThis cross-sectional study found that following cannabis legalization, provinces that permitted edible cannabis sales experienced much larger increases in hospitalizations for unintentional pediatric poisonings than the province that prohibited cannabis edibles. In provinces with legal edibles, approximately one-third of pediatric hospitalizations for poisonings were due to cannabis. These findings suggest that restricting the sale of legal commercial edibles may be key to preventing pediatric poisonings after recreational cannabis legalization.

This Viewpoint discusses Canada’s experience and response to COVID-19 pandemic–related events during the fourth through seventh waves.

The US has experienced increasing socioeconomic inequalities and stagnating life expectancy. Past studies have not disentangled 2 mechanisms thought to underlie socioeconomic inequalities in health, differential exposure and differential vulnerability, that have different policy implications.To evaluate the extent to which the association between socioeconomic status (SES) and all-cause mortality can be decomposed into a direct effect of SES, indirect effects through lifestyle factors (differential exposure), and joint effects of SES with lifestyle factors (differential vulnerability).This nationwide, population-based cohort study used the cross-sectional US National Health Interview Survey linked to the National Death Index. Civilian, noninstitutionalized US adults aged 25 to 84 years were included from the 1997 to 2014 National Health Interview Survey and were followed up until December 31, 2015. Data were analyzed from May 1 to October 31, 2021. A causal mediation model using an additive hazard and marginal structural approach was used.Both SES (operationalized as educational attainment) and lifestyle risk factors (smoking, alcohol use, obesity, and physical inactivity) were assessed using self-reported questionnaires.Time to all-cause mortality.Participants included 415 764 adults (mean [SD] age, 49.4 [15.8] years; 55% women; 64% non-Hispanic White), of whom 45% had low educational attainment and 27% had high educational attainment. Participants were followed up for a mean (SD) of 8.8 (5.2) years during which 49 096 deaths (12%) were observed. Low educational attainment (compared with high) was associated with 83.6 (men; 95% CI, 81.8-85.5) and 54.8 (women; 95% CI, 53.4-56.2) additional deaths per 10 000 person-years, of which 66% (men) and 80% (women) were explained by lifestyle factors. Inequalities in mortality were primarily a result of greater exposure and clustering of unhealthy lifestyle factors among low SES groups; with some exceptions among women, little evidence of differential vulnerability was identified.In this cohort study, differential exposure to lifestyle risk factors was an important mediator of socioeconomic inequalities in mortality. Public health interventions are needed, particularly among low SES groups, to address smoking, physical inactivity, alcohol use, and the socioenvironmental contexts within which these risk factors develop.

Importance Persons with dementia and Parkinson disease (PD) are vulnerable to disruptions in health care and services. Objective To examine changes in health service use among community-dwelling persons with dementia, persons with PD, and older adults without neurodegenerative disease during the first wave of the COVID-19 pandemic. Design, Setting, and Participants Repeated cross-sectional analysis using population-based administrative data among community-dwelling persons with dementia, persons with PD, and adults 65 years and older at the start of each week from March 1 through the week of September 20, 2020 (pandemic period), and March 3 through the week of September 22, 2019 (historical period), in Ontario, Canada. Exposures COVID-19 pandemic as of March 1, 2020. Main Outcomes and Measures Main outcomes were weekly rates of emergency department visits, hospitalizations, nursing home admissions, home care, virtual and in-person physician visits, and all-cause mortality. Poisson regression models were used to calculate weekly rate ratios (RRs) with 95% CIs comparing pandemic weeks with historical levels. Results Among those living in the community as of March 1, 2020, persons with dementia (n = 131 466; mean [SD] age, 80.1 [10.1] years) were older than persons with PD (n = 30 606; 73.7 [10.2] years) and older adults (n = 2 363 742; 74.0 [7.1] years). While all services experienced declines, the largest drops occurred in nursing home admissions (RR for dementia: 0.10; 95% CI, 0.07-0.15; RR for PD: 0.03; 95% CI, 0.00-0.21; RR for older adults: 0.11; 95% CI, 0.06-0.18) and emergency department visits (RR for dementia: 0.45; 95% CI, 0.41-0.48; RR for PD: 0.40; 95% CI, 0.34-0.48; RR for older adults: 0.45; 95% CI, 0.44-0.47). After the first wave, most services returned to historical levels except physician visits, which remained elevated (RR for dementia: 1.07; 95% CI, 1.05-1.09; RR for PD: 1.10, 95% CI, 1.06-1.13) and shifted toward virtual visits. Older adults continued to experience lower hospitalizations. All-cause mortality was elevated across cohorts. Conclusions and Relevance In this population-based repeated cross-sectional study in Ontario, Canada, those with dementia, those with PD, and older adults sought hospital care far less than usual, were not admitted to nursing homes, and experienced excess mortality during the first wave of the pandemic. Most services returned to historical levels, but virtual physician visits remained a feature of care. While issues of equity and quality of care are still emerging among persons with neurodegenerative diseases, policies to support virtual care are necessary.

Importance Starting in 2022, the US Food and Drug Administration (FDA) plans to require all cigarette packages in the US to display graphic health warnings depicting health harms associated with smoking. The FDA originally planned to implement such warnings in 2012, but tobacco industry litigation delayed the effort. Objective To assess the estimated population health outcomes associated with a policy requiring graphic health warnings on cigarette packages in the US and with a 10-year delay in implementation. Design, Setting, and Participants This decision analytical model used simulation modeling of smoking prevalence and smoking-attributable mortality in the US from 2012 to 2100, using the Cancer Intervention and Surveillance Modeling Network smoking population model. The study was conducted from October 2020 to July 2021. Main Outcomes and Measures The primary outcomes were annual adult smoking prevalence, smoking-attributable deaths averted, and life-years gained vs the baseline scenario. A baseline scenario assuming no graphic health warnings was compared with expected outcomes of implementing graphic health warnings in 2022 vs 2012. Policy effects were considered under varying assumptions of the association of the policy with smoking initiation and cessation, ranging from most conservative to most optimistic. A maximum smoking reduction scenario in which all smoking would stop by the end of 2022 was evaluated. Results In the baseline scenario, an estimated 13.2 million smoking-attributable deaths would have occurred from 2012 to 2100. Under a maximum smoking-reduction scenario, 5.5 million of these deaths would be averted. Implementation of graphic health warnings from 2022 to 2100 would be associated with 539 000 (range, 275 000-794 000) smoking-attributable deaths averted and 7.9 million (range, 4.0-11.6 million) life-years gained, representing less than 10% of the 5.5 million estimated smoking-attributable deaths averted and 81.8 million life-years gained in the maximum smoking-reduction scenario. Implementation from 2012 to 2100 would be associated with 33.2% (range, 32.9%-33.5%) more deaths averted (718 000; range, 365 000 to 1.1 million) and 42.7% (range, 42.3%-43.1%) more life-years gained (11.2 million; range, 5.7-16.6 million) compared with implementation in 2022. Conclusions and Relevance This decision analytical model estimated that FDA cigarette graphic health warnings, if implemented in 2022, would be associated with public health benefits. The model also estimated that more smoking-attributable deaths would have been averted if the policy had been implemented in 2012. Industry litigation and delays to implementing tobacco regulations may have been harmful for public health.

This cross-sectional study compares rates of emergency department visits and hospitalizations for assault and maltreatment by age category and sex in Ontario, Canada, before vs during the COVID-10 pandemic.

Importance Hospitalized medical patients cared for by female physicians may have decreased mortality rates compared with patients of male physicians. However, this association has yet to be assessed outside of the US, and little is known about factors that may explain this difference. Objective To determine whether mortality, other hospital outcomes, and processes of care differed between the patients cared for by female and male physicians. Design, Setting, and Participants This retrospective cross-sectional study included patients admitted to general medical wards at 7 hospitals in Ontario, Canada, between April 1, 2010, and October 31, 2017. The association of physician gender with patient outcomes was examined while adjusting for hospital fixed effects, patient characteristics, physician characteristics, and processes of care. All patients were admitted to a general internal medicine service through the emergency department and were cared for by a general internist or family physician-hospitalist. Patients were excluded if length of stay was greater than 30 days or if the attending physician cared for less than 100 hospitalized general medicine patients over the study period. Statistical analyses were performed from October 15, 2020, to May 8, 2021. Main Outcomes and Measures In-hospital mortality, length of stay, intensive care unit admission, 30-day readmissions, and process-of-care measures (blood tests, medications, imaging, endoscopy, and interventional radiology services). Results A total of 171 625 hospitalized patients with a median age of 73 years (interquartile range, 56-84 years) were included (84 221 men [49.1%], 87 402 women [50.9%], and 2 patients with unspecified sex). Patients were cared for by 172 attending physicians (54 female physicians [31.4%] and 118 male physicians [68.6%]). In fully adjusted models, female physicians ordered more imaging tests, including computed tomography (adjusted difference, −1.70%; 95% CI, −2.78% to −0.61%;P= .002), magnetic resonance imaging (−0.88%; 95% CI, −1.37% to −0.38%;P= .001), and ultrasonography (−1.90%; 95% CI, −3.21% to −0.59%;P= .005). Patients treated by female physicians had lower in-hospital mortality (2256 of 46 772 patients [4.8%] vs 6452 of 124 853 patients [5.2%]). This difference persisted after adjustment for patient characteristics but was no longer statistically different after adjustment for other physician characteristics (adjusted difference, 0.29%; 95% CI, −0.08% to 0.65%;P = .12). The difference was similar after further adjustment for processes of care. Conclusions and Relevance In this cross-sectional study of patients admitted to general medical units in Canada, patients cared for by female physicians had lower mortality rates than those treated by male physicians, adjusting for patient characteristics. This finding was nonsignificant after adjustment for other physician characteristics.