The European Union Emissions Trading System might yield large co-benefits from pollution reduction.

Mitigating greenhouse gas emissions and reducing air pollution represent two pressing and interwoven environmental challenges. While international carbon markets, such as the European Union emissions trading system (EU ETS), have demonstrated their effectiveness in curbing carbon emissions (CO[Formula: see text]), their indirect impact on hazardous co-pollutants remains understudied. This study investigates how key toxic air pollutants-sulfur dioxide (SO[Formula: see text]), fine particulate matter (PM[Formula: see text]), and nitrogen oxides (NO[Formula: see text])-evolved after the introduction of the EU ETS with a comparative analysis of regulated and unregulated sectors. Leveraging the generalized synthetic control method, we offer an ex post analysis of how the EU ETS and concurrent emission standards may have jointly generated sizable pollution reductions in regulated sectors between 2005 and 2021. We provide an aggregate assessment that these pollution reductions could translate into large health co-benefits, potentially in the hundreds of billions of Euros, even when bounding the effect of emission standards. These order-of-magnitude estimates underscore key implications for policy appraisal and motivate further microlevel research around the health co-benefits of carbon abatement.

Climate and health benefits of a transition from gas to electric cooking.

Household electrification is thought to be an important part of a carbon-neutral future and could also have additional benefits to adopting households such as improved air quality. However, the effectiveness of specific electrification policies in reducing total emissions and boosting household livelihoods remains a crucial open question in both developed and developing countries. We investigated a transition of more than 750,000 households from gas to electric cookstoves-one of the most popular residential electrification strategies-in Ecuador following a program that promoted induction stoves and assessed its impacts on electricity consumption, greenhouse gas emissions, and health. We estimate that the program resulted in a 5% increase in total residential electricity consumption between 2015 and 2021. By offsetting a commensurate amount of cooking gas combustion, we find that the program likely reduced national greenhouse gas emissions, thanks in part to the country's electricity grid being 80% hydropower in later parts of the time period. Increased induction stove uptake was also associated with declines in all-cause and respiratory-related hospitalizations nationwide. These findings suggest that, when the electricity grid is largely powered by renewables, gas-to-induction cooking transitions represent a promising way of amplifying the health and climate cobenefits of net-carbon-zero policies.

Mediating pathways between neighborhood disadvantage and cardiovascular risk: Quasi-experimental evidence from a Danish refugee dispersal policy.

Research has documented that neighborhood disadvantage is associated with increased cardiovascular disease risk, but it is unclear which mechanistic pathways mediate this association across the life course. Leveraging a natural experiment in which refugees to Denmark were quasi-randomly assigned to neighborhoods across the country during 1986-1998 and using 30 years of follow-up data from population and health registers, we assessed whether and how individual-level poverty, unstable employment, and poor mental health mediate the relation between neighborhood disadvantage and the risk of hypertension, hyperlipidemia, and type 2 diabetes among Danish refugees (N= 40,811). Linear probability models using the discrete time-survival framework showed that neighborhood disadvantage was associated with increased risk of hypertension (0.05 percentage points [pp] per year [95%CI -0.00, 0.10]); hyperlipidemia (0.03 pp per year [95%CI -0.01, 0.07]), and diabetes (0.01 pp per year (95%CI -0.02, 0.03)). The Baron-Kenny product-of-coefficients method for counterfactual mediation analysis indicated that cumulative income mediated 6%-28% of the disadvantage effect on these outcomes. We find limited evidence of mediation by unstable employment and poor mental health. This study informs our theoretical understanding of the pathways linking neighborhood disadvantage with cardiovascular disease risk and identifies income security as a promising point of intervention in future research.

Impact of removing donation service area and region from pancreas allocation.

On March 15, 2021, the Organ Procurement and Transplantation Network (OPTN) replaced donation service area (DSA) and OPTN region as units of pancreas (PA) allocation with a 250 nautical mile (NM) circle with proximity points. We analyzed OPTN data for kidney-pancreas (KP) and PA candidates, transplants, and donors in the 2 years pre-policy (March 16, 2019, to March 14, 2021) and post-policy (March 15, 2021, to March 14, 2023). As expected, more transplants occurred at hospitals outside the recovering organ procurement organization's DSA post-policy (KP: 32.1% vs 57.3%, P < .001; PA: 61.6% vs 69.3%, P = .09), but the majority stayed within 250 NM (KP: 79.7% vs 85.0%, P < .001; PA: 55.4% vs 61.5%, P = .19). Median preservation time increased from 9.5 to 10.3 hours for KP (P < .001); there was little change for PA (8.5 vs 8.6 hours; P = .99). There were no statistically significant differences in 1-year posttransplant patient mortality or graft failure after implementation for KP (mortality: 3.6% vs 3.2%, P = .60; kidney graft failure: 4.9% vs 5.0%, P = .95; PA graft failure: 9.5% vs 8.9%, P = .65) or PA (mortality: 1.7% vs 2.2%, P = .72; PA graft failure: 12.2% vs 12.6%, P = .88). The removal of DSA and OPTN region from PA allocation has resulted in broader distribution with minimal impact on preservation time or posttransplant outcomes.

A Bayesian multivariate factor analysis model for causal inference using time-series observational data on mixed outcomes.

Assessing the impact of an intervention by using time-series observational data on multiple units and outcomes is a frequent problem in many fields of scientific research. Here, we propose a novel Bayesian multivariate factor analysis model for estimating intervention effects in such settings and develop an efficient Markov chain Monte Carlo algorithm to sample from the high-dimensional and nontractable posterior of interest. The proposed method is one of the few that can simultaneously deal with outcomes of mixed type (continuous, binomial, count), increase efficiency in the estimates of the causal effects by jointly modeling multiple outcomes affected by the intervention, and easily provide uncertainty quantification for all causal estimands of interest. Using the proposed approach, we evaluate the impact that Local Tracing Partnerships had on the effectiveness of England's Test and Trace programme for COVID-19.

The impact of the expanded health insurance coverage policy on healthcare spending: evidence from Korea.

BACKGROUND: South Korea's National Health Insurance (NHI) system pursues universal health coverage, but it has not been able to alleviate patients' financial burden owing to limited coverage and a high proportion of out-of-pocket expenses. In 2017, the government announced a plan to strengthen universality by providing coverage for all unincluded services, expanding coverage, and alleviating household financial burden. We aimed to evaluate the effect of "Moon Care" with a focus on changes in health expenditures following policy implementation, and to provide empirical evidence for future policies to strengthen the NHI system's universality. METHODS: Using data from the 2016 and 2018 Korea Health Panel (KHP), we established a treatment group affected by the policy and an unaffected control group; we ensured homogeneity between the groups using propensity score matching (PSM). Subsequently, we examined changes in NHI payments, non-payments, and out-of-pocket payments (OOP); we performed difference-in-differences (DID) analysis to evaluate the policy's effect. RESULTS: Following policy implementation, the control group had a higher increase than the treatment group in all categories of health expenditures, including NHI payments, non-payments, and OOP. We noted significant decreases in all three categories of health expenditures when comparing the differences before and after policy implementation, as well as between the treatment and control groups. However, we witnessed a significant decrease in the interaction term, which confirms the policy's effect, but only for non-payments. CONCLUSIONS: We observed the policy's intervention effect over time as a decrease in non-payments, on the effectivity of remunerating covered medical services. However, the policy did not work for NHI payments and OOP, suggesting that it failed to control the creation of new non-covered services as noncovered services were converted into covered ones. Thus, it is crucial to discuss the financial spending of health insurance regarding the inclusion of non-covered services in the NHI benefits package.

Physician responses to insurance benefit restrictions: The case of ophthalmology.

This study examines the impact of social insurance benefit restrictions on physician behaviour, using ophthalmologists as a case study. We examine whether ophthalmologists use their market power to alter their fees and rebates across services to compensate for potential policy-induced income losses. The results show that ophthalmologists substantially reduced their fees and rebates for services directly targeted by the benefit restriction compared to other medical specialists' fees and rebates. There is also some evidence that they increased their fees for services that were not targeted. High-fee charging ophthalmologists exhibited larger fee and rebate responses while the low-fee charging group raise their rebates to match the reference price provided by the policy environment.

The effect of social pension on health-related quality of life of the rural older people: a panel study from China.

BACKGROUND: Social pensions, social assistance systems for older people in rural areas, have been put into place in many nations and have positively impacted health. The long-term health consequences of social pension programs in China are uncertain. The aim of this study is to evaluate the long-term health consequences of the new rural social pension (NRSP) for the rural older people in China. METHODS: Based on the 2011 and 2018 China Health and Retirement Longitudinal Study, we compared the scores on eight Health-Related Quality of Life (HRQoL) subscales of the rural older people before and after participation in the NRSP. The propensity score matching and difference-in-difference methods were used in data analysis. We also conducted a heterogeneity analysis for subgroups with different characteristics and pension enrolment times. RESULTS: The NRSP significantly enhanced scores on physical functioning, role-physical, and self-rated mental health of old rural participants by 1.90 (p < 0.01), 2.05 (p < 0.01), and 2.93 (p < 0.05), respectively. After excluding newly enrolled individuals, the beneficial health effects of the NRSP remained significant. There were no significant changes due to NRSP in the other five scores on the HRQoL subscale of the rural older people. The NRSP had more health benefits for older people in underdeveloped areas without formal schooling. CONCLUSIONS: The NRSP reduced health disparities and had long-term benefits on the physical and mental health of the rural older people. We suggest continuously expanding the NRSP throughout rural China and further improving the social support system to enhance the overall quality of life of the rural older people. Comparable social pension programs aimed at underprivileged groups could also be conducted in other low- or middle-income nations.

Abortion Legal Reform and Neonatal Mortality in Mozambique.

INTRODUCTION: Abortion law reforms have been hypothesized to influence reproductive, maternal, and neonatal health services and health outcomes, as well as social inequalities in health. In 2014, Mozambique legalized abortion in specific circumstances. However, due to challenges implementing the law, there is concern that it may have negatively influenced neonatal outcomes. METHODS: Using a difference-in-differences design, we used birth history data collected via the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) between 2004 and 2018 to assemble a panel of 476 939 live births across 17 countries including Mozambique. We estimated the effect of the abortion reform on neonatal mortality by comparing Mozambique to a series of control countries that did not change their abortion policies. We also conducted stratified analyses to examine heterogeneity in effect estimates by household wealth, educational attainment, and rural/urban residence. RESULTS: The reform was associated with an additional 5.6 (95% CI = 1.3, 9.9) neonatal deaths per 1,000 live birth. There was evidence of a differential effect of the reform, with a negative effect of the reform on neonatal outcomes for socially disadvantaged women, including those with no schooling, in poorer households, and living in rural areas. DISCUSSION: Given the delay in implementation, our analyses suggest that abortion reform in Mozambique was associated with an initial increase in neonatal mortality particularly among socially disadvantaged women. This may be due to the delay in effective implementation, including the dissemination of clear guidelines and expansion of safe abortion services. Longer-term follow-up is needed to assess the impact of the reform after 2018, when services were expanded. Abortion legal reform without adequate implementation and enforcement is unlikely to be sufficient to improve abortion access and health outcomes.

Confidence intervals for policy evaluation in adaptive experiments.

Adaptive experimental designs can dramatically improve efficiency in randomized trials. But with adaptively collected data, common estimators based on sample means and inverse propensity-weighted means can be biased or heavy-tailed. This poses statistical challenges, in particular when the experimenter would like to test hypotheses about parameters that were not targeted by the data-collection mechanism. In this paper, we present a class of test statistics that can handle these challenges. Our approach is to adaptively reweight the terms of an augmented inverse propensity-weighting estimator to control the contribution of each term to the estimator's variance. This scheme reduces overall variance and yields an asymptotically normal test statistic. We validate the accuracy of the resulting estimates and their CIs in numerical experiments and show that our methods compare favorably to existing alternatives in terms of mean squared error, coverage, and CI size.

Associations of U.S. state-level COVID-19 policies intensity with cannabis sharing behaviors in 2020.

BACKGROUND: Cannabis use before the COVID-19 pandemic for many involved sharing prepared cannabis for inhalation, practices that were less prevalent during the pandemic. State-level COVID-19 containment policies may have influenced this decrease. This study examined the extent to which the intensity of state-level COVID-19 policies were associated with individual-level cannabis sharing. Findings have the potential to guide harm reduction policies for future respiratory pandemics and seasonal respiratory virus waves. METHODS: This study used cross-sectional individual-level data from the COVID-19 Cannabis Study, an anonymous U.S.-based web survey on cannabis use disseminated during the early phase of the pandemic (Full sample N = 1,883). We combined individual-level data with state-level policy data from Kaiser Family Foundation's State COVID-19 Data and Policy Actions for three time-points from June to August 2020 that overlapped with the survey period. Cannabis sharing was dichotomized as any versus no sharing. We adapted a previously published coding framework to score the intensity of COVID-19 policies implemented in each U.S. state and averaged the policy score across the time period. We then used Poisson regression models to quantify the associations of the average state-level COVID-19 policy score with cannabis sharing during the pandemic. RESULTS: Participants (n = 925) reporting using inhalation as a mode for cannabis use were included in this analysis. Most respondents were male (64.1%), non-Hispanic White (54.3%), with a mean age of 33.7 years (SD 8.8). A large proportion (74.9%) reported sharing cannabis during the pandemic. Those who shared cannabis more commonly lived in states with a lower average policy score (16.7, IQR 12.3-21.5) compared to those who did not share (18.6, IQR 15.3-25.3). In adjusted models, the prevalence ratio of any cannabis sharing per every 5-unit increase in the average COVID-19 policy score was 0.97 (95% CI 0.93, 1.01). CONCLUSIONS: Fewer individuals shared cannabis in states with more intense COVID-19 containment policies compared to those in states with less intense policies. Individuals who use cannabis may be willing to make changes to their behavior and may further benefit from specific and directed public health messaging to avoid sharing during respiratory infection outbreaks.

Farmland protection and fertilization intensity: Empirical evidence from preservation policy of Heilongjiang's black soil.

The preservation of cultivated land quality stands as a vital prerequisite for ensuring food security and sustainability. In the black soil area of northeast China, a large amount of fertilizer was used to stabilize grain production in its early stages, which damaged soil structure and polluted the ecological environment. Based on the panel data of fertilization intensity of 48 districts and counties in Heilongjiang Province from 2010 to 2020, this study takes the implementation of the "Three-Year Action Plan for the Protection of Black Soil Farmland in Heilongjiang Province for the (2018-2020)" (TYAP) policy as a natural experiment, and uses the difference-in-differences (DiD) method to identify the causal effect of the policy on the local fertilization intensity. The results of the empirical study showed that the implementation of the TYAP policy significantly reduced the fertilization intensity of the black soil cultivated land implemented by the policy during the implementation period, which resulted in a decrease of 11.97% on average compared with the areas without the policy implementation. Several robustness tests provided additional confirmation of the aforementioned findings. This study further revealed that the policy mitigated fertilization intensity by fostering advancements in agricultural mechanization.

Research alignment in the U.S. national park system: Impact of transformative science policy on the supply and demand for scientific knowledge for protected area management.

The US National Park System encompasses diverse environmental and tourism management regimes, together governed by the 1916 Organic Act and its dual mandate of conservation and provision of public enjoyment. However, with the introduction of transformative science policy in the 2000's, the mission scope has since expanded to promote overarching science-based objectives. Yet despite this paradigm shift instituting "science for parks, parks for science", there is scant research exploring the impact of the National Park Science Policy on the provision of knowledge. We address this gap by developing a spatiotemporal framework for evaluating research alignment, here operationalized via quantifiable measures of supply and demand for scientific knowledge. Specifically, we apply a machine learning algorithm (Latent Dirichlet analysis) to a comprehensive park-specific text corpus (combining official needs statements -i.e. demand- and scientific research metadata -i.e. supply-) to define a joint topic space, which thereby facilitates quantifying the direction and degree of alignment at multiple levels. Results indicate an overall robust degree of research alignment, with misaligned topics tending to be over-researched (as opposed to over-demanded), which may be favorable to many parks, but is inefficient from the park system perspective. Results further indicate that the transformative science policy exacerbated the misalignment in mandated research domains. In light of these results, we argue for improved decision support mechanisms to achieve more timely alignment of research efforts towards distinctive park needs, thereby fostering convergent knowledge co-production and leveraging the full value of National Parks as living laboratories.

The impact of "Aging with Medical and Caregiving" on family caregiving-Evidence from China's pilot cities for integrating medical and caregiving.

Easing the pressure on family caregiving and addressing the shortage of manpower for family caregiving are significant challenges that China faces in responding to its aging population. This study utilizes data from the 2015 and 2020 China Health and Retirement Longitudinal Study (CHARLS) and employs a Difference-in-Difference method to investigate the impact of pilot policies that integration of medical and caregiving for aging individuals. The findings reveal that these pilot programs are successful in reducing the amount of time spent on family caregiving and the financial burden placed on families, effectively relieving the pressure associated with family caregiving. However, the effects of these programs differ depending on the level of disability, household registration, and the geographical location of the participants. Further analysis suggests that these pilot programs achieve these positive outcomes by increasing government investment in health and wellness funds and providing in-family medical and caregiving services.

Effects of a disincentive policy on behavioral changes by South Korean medical institutions that do not submit official nursing grade data.

AIM: This study aimed to determine whether the policy of imposing deductions on medical institutions in South Korea led to increased submission of nursing grade data. BACKGROUND: In Korea, medical institutions are required to report data on their nursing workforce; however, many institutions did not comply with this regulation, making it difficult to gauge their level of nurse staffing. Therefore, in 2020, a nursing fee deduction policy was introduced that penalizes medical institutions financially for failing to submit nursing workforce data. METHODS: We prospectively collected data on the characteristics, nursing grade, and data submission status of 1,200 hospitals in South Korea from 2015 to 2021. We analyzed the submission rate of data related to nursing grades according to the characteristics of the medical institutions and evaluated the effect of policy change on data submission status using multiple logistic regression. FINDINGS: The submission rate of data increased from 50.2% in 2015 to 93.3% in 2021, and 39.3% of medical institutions that had not previously submitted data did so after the policy was introduced. The submission rate of medical institutions unaffected by the policy also increased after its introduction. Compared with 2015, the likelihood of medical institutions submitting data increased by 23.69 times in 2020 and 20.47 times in 2021. CONCLUSION: The appropriate use of disincentive policies, such as financial deductions for medical institutions showing inappropriate behavior, was found to be effective in inducing desirable changes in the behavior of medical institutions. IMPLICATIONS FOR NURSING AND HEALTH POLICY: Properly planned and implemented policies can contribute to improved quality of medical services and patient safety through effective administrative control.

Impact of a regulatory target and external factors on the waste efficiency of Italian municipalities.

Due to increasing consumption and urbanisation, urban waste management and recycling are a primary concern in Italy. Italian waste collection underwent significant reform with the introduction of a sorted collection target of 65% of total collected waste in Legislative Decree No. 152/2006. In this article, we analyse the effect of this regulatory target on the efficiency of waste collection in 275 Italian municipalities in the years 2016-2019. We estimate the coefficients of the cost efficiencies of the sorted and unsorted waste without assuming functional forms for the efficient frontier or the distribution of efficiency. Our findings suggest that municipalities that met the 65% sorted waste target demonstrated higher efficiency as costs increased, whereas those that failed to meet the target demonstrated higher inefficiency as costs increased. Strong effects emerged for population and urban economic development on the success of waste collection, whereas only marginal effects were observed for population density and city size. To improve the situation of municipalities that are not meeting the 65% target, we propose several policy measures, including 'neighbourhood solidarity'.

Invited Commentary: Use of Epidemiologic Methods to Guide Comprehensive and Equitable Approaches to Policy.

Despite a dramatic reduction in the prevalence of commercial cigarette smoking in the United States, children are still commonly exposed to secondhand smoke (SHS), which is a cause of various pediatric health problems. Further, SHS exposure is patterned by race and class, exacting an inequitable toll on children from families with lesser social and economic advantage. In this issue of the Journal, Titus et al. (Am J Epidemiol. 2023;192(1):25-33) use natural experiment evaluation methods (difference-in-differences) to test whether the recently implemented US Department of Housing and Urban Development policy that forbade smoking in and around New York City Housing Authority buildings affected child respiratory health. The results from their work remind us that policies do not always impact outcomes as we might expect. Given that policy is one of the most potent tools for population health promotion, this work underlines the need for epidemiologists to engage in policy evaluation at all stages of the policy life cycle, in order to discover comprehensive approaches to policy development and implementation that prioritize equity and address structural racism.

Impact of Changes to Concealed-Carry Weapons Laws on Fatal and Nonfatal Violent Crime, 1980-2019.

The United States faces rapidly rising rates of violent crime committed with firearms. In this study, we sought to estimate the impact of changes to laws that regulate the concealed carrying of weapons (concealed-carry weapons (CCW) laws) on violent crimes committed with a firearm. We used augmented synthetic control models and random-effects meta-analyses to estimate state-specific effects and the average effect of adopting shall-issue CCW permitting laws on rates of 6 violent crimes: homicide with a gun, homicide by other means, aggravated assault with a gun, aggravated assault with a knife, robbery with a gun, and robbery with a knife. The average effects were stratified according to the presence or absence of several shall-issue permit provisions. Adoption of a shall-issue CCW law was associated with a 9.5% increase in rates of assault with a firearm during the first 10 years after law adoption and was associated with an 8.8% increase in rates of homicide by other means. When shall-issue laws allowed violent misdemeanants to acquire CCW permits, the laws were associated with higher rates of gun assaults. It is likely that adoption of shall-issue CCW laws has increased rates of nonfatal violent crime committed with firearms. Harmful effects of shall-issue laws are most clear when provisions intended to reduce risks associated with civilian gun-carrying are absent.

The impact of urban-rural medical insurance integration on medical impoverishment: evidence from China.

BACKGROUND: Financial protection is a key dimension of Universal Health Coverage (UHC), and social medical insurance is an effective measure to provide financial protection. The aim of this study is to examine the impact of urban-rural medical insurance integration on medical impoverishment in China. METHODS: We collected the time of integration policy in 337 prefecture-level cities across China, combined with the longitudinal database of China Labor-force Dynamics Survey (CLDS) from 2012-2016, and used a difference-in-differences (DID) method with multiple time periods at the city level to study the effect of urban-rural medical insurance integration on the medical impoverishment. Besides, to explore the heterogeneity of policy effects across populations, we conducted subgroup analyses based on respondents' age, household registration, and whether they were rural-urban migrants. FINDINGS: A total of 8,397 samples were included in the study. The integration policy has significantly reduced the incidence of medical impoverishment (average treatment effect on the treated (ATT) = - 0.055, p < 0.05). Subgroup analysis showed that the impacts on medical impoverishment varied by age group, and the integration policy has more effect on older people than on younger people (ATT for age 15-34 = - 0.018, p > 0.05; ATT for age 35-54 = - 0.042, p < 0.05; ATT for age 55-64 = - 0.163, p < 0.01). Moreover, the impacts also varied by household registration. The integration policy has a more significant impact on rural residents (ATT for rural = - 0.067, p < 0.05) compared to urban residents (ATT for urban = - 0.007, p > 0.05). Additionally, the policy has a bigger influence on rural-urban migrants (ATT for rural-urban migrated = - 0.086, p < 0.05) than on those who have not migrated (ATT for rural-urban unmigrated = - 0.071, p < 0.05). CONCLUSION: China's policy of integrating urban-rural medical insurance has been successful in reducing medical impoverishment, especially for older age, rural, and rural-urban migrated people. It can be speculated that the integrating policy may be adapted to other similar settings in developing countries to reduce medical impoverishment.

Early results of a natural experiment evaluating the effects of a local minimum wage policy on the diet-related health of low-wage workers, 2018-2020.

OBJECTIVE: The current study presents results of a midpoint analysis of an ongoing natural experiment evaluating the diet-related effects of the Minneapolis Minimum Wage Ordinance, which incrementally increases the minimum wage to $15/h. DESIGN: A difference-in-difference (DiD) analysis of measures collected among low-wage workers in two U.S. cities (one city with a wage increase policy and one comparison city). Measures included employment-related variables (hourly wage, hours worked and non-employment assessed by survey questions with wages verified by paystubs), BMI measured by study scales and stadiometers and diet-related mediators (food insecurity, Supplemental Nutrition Assistance Program (SNAP) participation and daily servings of fruits and vegetables, whole-grain rich foods and foods high in added sugars measured by survey questions). SETTING: Minneapolis, Minnesota and Raleigh, North Carolina. PARTICIPANTS: A cohort of 580 low-wage workers (268 in Minneapolis and 312 in Raleigh) who completed three annual study visits between 2018 and 2020. RESULTS: In DiD models adjusted for time-varying and non-time-varying confounders, there were no statistically significant differences in variables of interest in Minneapolis compared with Raleigh. Trends across both cities were evident, showing a steady increase in hourly wage, stable BMI, an overall decrease in food insecurity and non-linear trends in employment, hours worked, SNAP participation and dietary outcomes. CONCLUSION: There was no evidence of a beneficial or adverse effect of the Minimum Wage Ordinance on health-related variables during a period of economic and social change. The COVID-19 pandemic and other contextual factors likely contributed to the observed trends in both cities.