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Availability of medical cannabis services by racial, social, and geographic characteristics of neighborhoods in New York: a cross-sectional study

Abstract

Background

Within the United States (US), because racial/ethnic disparities in cannabis arrests continue, and cannabis legalization is expanding, understanding disparities in availability of legal cannabis services is important. Few studies report mixed findings regarding disparities in availability of legal cannabis services; none examined New York. We examined disparities in availability of medical cannabis services in New York. We hypothesized that New York census tracts with few Black or Hispanic residents, high incomes, high education levels, and greater urbanicity would have more medical cannabis services.

Methods

In this cross-sectional study, we used data from the 2018 US Census Bureau 5-year American Community Survey and New York Medical Marijuana Program. Main exposures were census tract characteristics, including urban–rural classification, percentage of Black and Hispanic residents, percentage of residents with bachelor’s degrees or higher, and median household income. Main outcomes were presence of at least one medical cannabis certifying provider and dispensary in each census tract. To compare census tracts’ characteristics with (vs. without) certifying providers and dispensaries, we used chi-square tests and t-tests. To examine characteristics independently associated with (vs. without) certifying providers, we used multivariable logistic regression.

Results

Of 4858 New York census tracts, 1073 (22.1%) had medical cannabis certifying providers and 37 (0.8%) had dispensaries. Compared to urban census tracts, suburban census tracts were 62% less likely to have at least one certifying provider (aOR = 0.38; 95% CI = 0.25–0.57). For every 10% increase in the proportion of Black residents, a census tract was 5% less likely to have at least one certifying provider (aOR = 0.95; 95% CI = 0.92–0.99). For every 10% increase in the proportion of residents with bachelor’s degrees or higher, a census tract was 30% more likely to have at least one certifying provider (aOR = 1.30; 95% CI = 1.21–1.38). Census tracts with (vs. without) dispensaries were more likely to have a higher percentage of residents with bachelor’s degrees or higher (43.7% vs. 34.1%, p < 0.005).

Conclusions

In New York, medical cannabis services are least available in neighborhoods with Black residents and most available in urban neighborhoods with highly educated residents. Benefits of legal cannabis must be shared by communities disproportionately harmed by illegal cannabis.

Peer Review reports

Background

As advances in medical treatment emerge, the inequitable distribution of these medical advances among Americans can exacerbate health disparities [1]. Although cannabis has been used for medicinal purposes for centuries, in the United States (US), the legal use of medical cannabis is a relatively new phenomenon [2]. Currently, the District of Columbia and 17 states, including New York, have legalized adult-use recreational cannabis, and the District of Columbia and 36 states have legalized medical cannabis [3]. In states where recreational cannabis use remains criminalized, the benefits of access to medical cannabis, including availability (i.e. geographic location) and affordability (i.e. direct cost of the service for patients), may extend beyond medical benefits.

In the US, the harms of cannabis criminalization have disproportionately impacted Black and Hispanic people [4, 5]. Across the US and New York, the arrest rates for cannabis possession are 3.6 and 2.6 times higher for Black people than White people, respectively [4]. In several counties in New York, the arrest rates are over 15 times higher for Black people than White people [4]. Arrest rates for cannabis possession are similarly higher in communities with lower income and levels of education [6]. New York law did not distinguish between medical and recreational cannabis use until the enactment of medical cannabis. Because legal medical cannabis should allow individuals to use medical cannabis without risk of criminal sanction, access to medical cannabis certification within Black and Hispanic communities could reduce the harm of cannabis criminalization for these populations, particularly for those with an indication for medical cannabis who may otherwise obtain cannabis from the illicit market. Therefore, if medical cannabis is less available within Black and Hispanic communities, then the impact of medical cannabis policies on racial inequities may be reduced.

US federal and state policies related to cannabis differ substantially, impacting how people legally access cannabis. At the federal level, cannabis remains classified as a Schedule 1 substance with “no currently accepted medical use and a high potential for abuse” [7]. This classification, which includes substances like heroin, has important clinical implications. Because no insurance company covers medical cannabis products, patients must pay out of pocket with cash. In addition, medical providers cannot prescribe medical cannabis products, but instead certify patients for medical cannabis. Certification for medical cannabis by a medical provider is a necessary first step to obtaining medical cannabis products. In many states, including New York, a certified patient can access medical cannabis at a limited number of approved dispensaries.

To our knowledge, no previous study has examined whether and the degree to which disparities in availability of medical cannabis services exist in New York. We examined how neighborhood racial, social, and geographic characteristics differed by locations in which certifying providers and medical cannabis dispensaries were present in New York. Specifically, we compared racial and ethnic composition, income, education, and urbanicity of New York census tracts by presence of certifying providers and medical cannabis dispensaries. Informed by evidence of inequities by race, ethnicity, income, and geography for other medical innovations [1, 8], we hypothesized that New York census tracts with 1) few Black or Hispanic residents, 2) high incomes, 3) high education levels and 4) greater urbanicity would be most likely to have certifying providers and medical cannabis dispensaries.

Methods

Setting

The cross-sectional study was conducted out of the Albert Einstein College of Medicine (Bronx, New York), and its institutional review board approved this study (IRB# 2020–11913). All methods were carried out in accordance with relevant guidelines and regulations.

The New York Medical Marijuana Program was implemented in January 2017. As of June 16, 2020, 116,518 patients were enrolled in the program, and 2267 certifying providers and 38 medical cannabis dispensaries were listed on the program website [9]. To become a certifying provider, physicians, nurse practitioners, or physician assistants must complete a 4-h online educational course on cannabinoids and register with the New York State Department of Health. Within the program, 10 registered organizations are responsible for manufacturing and dispensing medical cannabis products, and each is permitted to have up to four dispensaries. Although New York legalized adult-use recreational cannabis on March 31, 2021, implementation of the policy is not yet in effect.

Study population

Of the 4918 census tracts in New York, 17 had a population of zero and 43 were missing rural–urban data codes. Therefore, we excluded these 60 census tracts and included a total of 4858 census tracts in analyses.

Study variables

Dependent variables

The main dependent variable was the presence of at least one certifying provider’s address in each census tract (yes/no). Because the majority of census tracts had no certifying provider, we defined this variable based on the presence of any certifying provider in each census tract instead of the number of certifying providers in each census tract. To create this variable, we first abstracted names and addresses of all 2267 certifying providers who were listed on the New York Medical Marijuana Program website as of June 16, 2020. These 2267 certifying providers had 2310 addresses; 2225 providers had one address, 41 had two addresses, and 1 had three addresses. Forty-three providers had addresses only outside of New York, and 2224 had at least one address in New York. If applicable, we included certifying providers with multiple addresses in multiple census tracts.

We then obtained the legal boundaries of New York census tracts from the 2019 US Census Bureau TIGER/Line Shapefiles [10]. To geocode and map certifying providers’ addresses, we used Esri ArcPro 2.2 and ArcGIS online geocoding service to complete a process that we have employed previously in accordance with best practices [11,12,13,14]. During batch geocoding (assigning latitude and longitude to a database of addresses), 2262 of 2310 address were successfully matched to a location. The remaining 48 addresses were initially matched during batch geocoding to a polygon location (i.e. center point of postal code or municipality), had a tied highest match score, or had a match score of less than 80. All 48 of these addresses were then successfully matched during hand review using Google Maps. Of the 2310 addresses, 44 were outside of New York. Thus, we mapped the 2266 unique New York geocoded addresses of certifying providers over the New York census tract boundaries to assign each certifying provider’s address to a specific census tract.

Our other dependent variable was the presence of at least one medical cannabis dispensary in each census tract (yes/no). We used a similar approach as described above, but used addresses of the 38 medical cannabis dispensaries (rather than certifying providers) obtained from the New York Medical Marijuana Program website. During batch geocoding, 37 of 38 dispensaries’ addresses were successfully located, and one address was successfully located upon hand review.

Independent variables

Key independent variables included urban–rural classification, racial and ethnic composition, and education and income levels for each census tract.

Using the 2019 revised Rural–Urban Commuting Area (RUCA) codes from the US Department of Agriculture [15], we categorized census tracts into a commonly used 3-level urban–rural classification scheme [16, 17]: urban (RUCA codes 1.0, 1.1), suburban (RUCA codes 2.0, 2.1, 3.0), and rural (RUCA codes 4.0, 4.1, 4.2, 5.0, 5.1,5.2,6.0, 6.1, 7.0, 7.1, 7.2, 7.3, 7.4,8.0, 8.1, 8.2, 8.3, 8.4, 9.0,9.1, 9.2,10.0, 10.1, 10.2, 10.3, 10.4, 10.5, 10.6). Because our study did not aim to examine difference across rural communities, we collapsed the previously used 4-level scheme (urban, suburban, large rural, and small rural) into a 3-level scheme by combining large rural and small rural categories.

Using the 2018 US Census Bureau 5-year American Community Survey [18], we obtained demographic, educational and economic data for each census tract. For racial and ethnic composition, we calculated the mean percentage of Black residents (including Hispanic and non-Hispanic ethnicity), Hispanic residents (including all races). For education, we calculated the mean percentage of residents 25 years of age or older with bachelor’s degrees or higher. For income levels, we calculated the mean median household income in 2018 inflation-adjusted dollars. All variables and categories were based on those defined in the 2018 US Census Bureau 5-year American Community Survey.

Other variables

To provide descriptive data on certifying provider characteristics from the publicly available New York State Office of Professions website [19], we collected provider type (Medical Doctor [MD], Doctor of Osteopathy [DO], Nurse Practitioner [NP], Physician Assistant [PA]), and date of medical degree (available for MDs and DOs).

Data analyses

The unit of analysis was census tract. To compare characteristics of census tracts with versus without at least one certifying provider, we conducted bivariate analyses using chi-square tests for categorical variables and t-tests for continuous variables. To examine whether characteristics of census tracts were independently associated with the presence of certifying providers, we then conducted a multivariable logistic regression model in which all independent variables were included in the model. Due to missing values for independent variables, 164 observations (3.4%) were excluded from the model. Because the categories of urban–rural classification take population density into account, we did not include population density in our model. We chose urban census tracts as the reference group because it is the most frequent urban–rural classification of census tracts. We performed a Hosmer and Lemeshow goodness-of-fit test to examine model fit of the data. We also conducted a sensitivity analysis to examine if spatial autocorrelation impacted our findings. We tested for spatial autocorrelation for our main dependent variable using Moran's I. We then repeated our multivariable logistic regression by incorporating spatial autocorrelation mixed-effect structure into the model.

To compare characteristics of census tracts with versus without at least one medical cannabis dispensary, we conducted bivariate analyses using chi-square tests for categorical variables and t-tests for continuous variables. Because only 38 medical cannabis dispensaries were present in 37 of New York’s census tracts, we did not conduct multivariable analyses.

Finally, to describe characteristics of certifying providers, we ran simple frequencies of their characteristics, combining variables into clinically meaningful categories. Analyses were conducted using SAS 9.4 (Cary, NC, USA).

Results

Of the 4858 New York census tracts, 1073 (22.1%) had at least one certifying provider and 37 (0.8%) had at least one medical cannabis dispensary (Table 1, Figs. 1 and 2). Of 2224 certifying providers with New York addresses, most were physicians (60.4% MDs, 6.7% DOs) or nurse practitioners (29.5%). A majority (63.7%) of physicians received medical degrees over 20 years ago. Certifying providers’ most common specialties were family medicine (20.8%), general internal medicine (19.1%), psychiatry (12.3%), pain medicine (10.8%), neurology (8.1%), anesthesiology (4.7%), and physical medicine and rehabilitation (4.8%).

Table 1 New York census tract characteristics by presence of medical cannabis certifying providers and dispensaries
Fig. 1
figure 1

New York census tracts with and without medical cannabis certifying providers

Fig. 2
figure 2

New York census tracts with and without medical cannabis dispensaries

In bivariate analyses, census tracts with (vs. without) at least one certifying provider were less likely to be suburban (2.6% vs. 7.7%, p < 0.001), and more likely to be urban (89.2% vs. 82.1%, p < 0.001), have a lower percentage of Black and Hispanic residents (13.6% vs. 19.6%, p < 0.001; 15.0% vs. 18.6%, p < 0.001, respectively), have a higher median household income ($99,082 vs. $80,001, p < 0.001), and have a higher percentage of residents with bachelor’s degrees or higher (43.4% vs. 31.5%, p < 0.001) (Table 1). Census tracts with (vs. without) at least one medical cannabis dispensary were more likely to have a higher percentage of residents with bachelor’s degrees or higher (43.7% vs. 34.1%, p = 0.002).

In multivariable analysis, compared to urban census tracts, suburban census tracts were 62% less likely to have at least one certifying provider (aOR = 0.38; 95% CI = 0.25–0.57) while there was no difference detected between urban and rural census tracts. For every 10% increase in the proportion of Black residents, a census tract was 5% less likely to have at least one certifying provider (aOR = 0.95; 95% CI = 0.92–0.99). For every 10% increase in the proportion of residents with bachelor’s degrees or higher, a census tract was 30% more likely to have at least one certifying provider (aOR = 1.30; 95% CI = 1.21–1.38, Table 2). For this model, the Hosmer and Lemeshow chi-square was 10.21 (p = 0.25), the Cox and Snell R-square was 0.06, and the Nagelker R-square was 0.09. In our sensitivity analysis, there was evidence of spatial autocorrelation for our primary outcome (Moran’s Index 0.03; p < 0.001). However, our model with a mixed-effect term for nearby census tracts with medical cannabis certifiers did not impact our primary findings (data not shown).

Table 2 Multivariable logistic regression model examining characteristics of New York census tracts with versus without medical cannabis certifying providers (N = 4694)

Discussion

In the New York Medical Marijuana Program, medical providers who certify individuals for medical cannabis are located in less than one quarter of census tracts, and dispensaries that provide medical cannabis products are located in less than 1% of census tracts. Certifying providers are most likely to be in census tracts with fewer Black residents (hypothesis #1) and more highly educated residents (hypothesis #3). Certifying providers are more likely to be in urban versus suburban census tracts, but we did not find evidence of a difference in availability between urban and rural census tracts (hypothesis #4). We did not find evidence that certifying provider availability was associated with census tract income (hypothesis #2). Medical cannabis dispensaries may be located in similar locations, though due to the small number of dispensaries, independent associations could not be determined.

Our finding of racial and educational disparities in availability of medical cannabis services in New York is not surprising. Findings similar to ours, in which Black patients have less access than white patients to advances in health care, have been documented repeatedly and across numerous medical conditions. Examples of well-documented racial disparities in access to advances in health care include: buprenorphine treatment for opioid use disorder [20, 21], highly active antiretroviral medication for HIV infection [22,23,24], joint replacements for arthritis [25, 26], interventions for acute myocardial infarction [27, 28], and renal transplant for end stage renal disease [29, 30]. Similarly, low educational levels have been previously associated with less access to medical, dental, and mental health care [31]. However, our finding that neighborhoods with a greater proportion of Black New Yorkers were less likely to have available medical cannabis services is particularly problematic given the historical and ongoing disproportionate rates of cannabis arrests among Black people relative to white people in New York and the US [4]. As more states legalize recreational and medical cannabis, policies that do not take into account racial disparities in the harms of cannabis criminalization may perpetuate racial disparities. Additional interventions or reparations targeted to the most harmed communities is likely to be required to reduce racial disparities associated with cannabis use in the US.

To our knowledge, our study is among the first to examine how location of certifying providers is associated with sociodemographic characteristics of the population they serve. In addition, our study is the first to examine medical cannabis services in New York, which has one of the most stringent medical cannabis policies in the US. In the only study that we are aware of that examined disparities in medical cannabis certification, only 14% of patients assessed for certification at nine medical cannabis clinics in California were Hispanic, while 32% of Californians were Hispanic [32]. Our study did not find a relationship between the percentage of Hispanic residents in a census tract and the availability of cannabis services. Future research is needed to confirm this negative finding and also examine how neighborhood availability of services is related to certification rates. Other studies have focused on geospatial locations of medical or recreational cannabis dispensaries, not certifying providers. While most of these studies report that dispensaries were more commonly located in neighborhoods with high levels of poverty or deprivation, or high percentages of Black or Hispanic residents [33,34,35,36,37], one study reported no relationship between locations of dispensaries and these neighborhood characteristics [38]. There are several potential reasons for the differences in findings between these studies and ours. Other studies often combined medical cannabis and recreational cannabis dispensaries, while New York has only medical cannabis dispensaries. In addition, New York has only 38 medical cannabis dispensaries, while California, Washington, and Colorado have hundreds of dispensaries [36, 39, 40]; thus, the limited number of dispensaries in New York may be strategically located in select neighborhoods. In our clinical experience, the cost of medical cannabis is New York is often unaffordable to many, which is also likely to contribute to decisions regarding locations of dispensaries. Although 36 states have legalized medical cannabis, relatively few studies, and only studies from California, Washington, and Colorado, have examined how medical cannabis policies are associated with access to medical cannabis, particularly by race and ethnicity, along with income and education. Our results are consistent with prior research showing greater availability of medical services within urban versus suburban areas [8, 41]. However, our results differ from previous research that showed less availability in rural versus urban areas [8, 13]. Our results for rural areas was unexpected, but future research should examine disparities using other measures of availability, such as drive time to services. Understanding and mitigating disparities in access to advances in health care, and specifically legal cannabis, is critical to ensuring equitable health care delivery and outcomes.

The current New York Medical Marijuana program does not include measures to encourage the adoption of medical cannabis certification among providers within communities harmed by cannabis criminalization. For medical cannabis, our results suggest incentives to provide services within such communities are needed if all potential benefits of legal medical cannabis are to be realized. One potential option is to incentivize or encourage the adoption of medical cannabis certification among providers at Federally Qualified Health Centers, which disproportionately serve under-resourced communities. States like New York could also provide financial incentives to open new practices that provide medical cannabis certification within communities harmed by cannabis criminalization. Our results also suggest New York should increase the number of medical cannabis dispensaries and incentivize their location within communities harmed by cannabis criminalization to avoid disparities in dispensary availability. Despite the shortcomings in New York’s Medical Marijuana Program, the recently passed law for legal adult-use cannabis in New York has earmarked 40% of tax revenues to be invested in communities, along with social and economic equity programs to address those disproportionally impacted by cannabis criminalization [42]. These provisions include preferences for licensing to minority-owned businesses. It will be important to evaluate whether these provisions lead to equitable availability and access to legal cannabis.

Our study has limitations. Because New York’s medical cannabis policies differ from other states in the US, our findings may not be generalizable to other states. Because we used a dichotomous outcome for availability of services, we could not assess differences in the density of certifying providers among census tracts. New York also allows medical cannabis certification and dispensary visits via telemedicine, along with delivery of medical cannabis products. While telemedicine may potentially reduce the importance of geographic proximity, adoption and availability of telemedicine may align with the same racial disparities identified within our study [43]. Because Black race and Hispanic ethnicity are defined by the 2018 US Census Bureau 5-year American Community Survey, we were unable to combine or parse out these variables to isolate individuals who may have identified as Black and Hispanic. We did not include other measures, such as cost or stigma of medical cannabis use, which are likely to impact disparities in access to medical cannabis services and products. Because this was a cross-sectional study, future research should examine how these results may change over time. While the exact proportion of medical versus recreational cannabis users within New York is unknown, the approved conditions for medical cannabis within New York are present within all racial and ethnic subpopulations and these populations have an equal right to access medical cannabis free of criminal penalty [9]. Despite these limitations, we remain confident in our robust findings on the relationship between the availability of medical cannabis and the percentage of Black residents within a neighborhood.

Conclusions

In the New York Medical Marijuana Program, certifying providers are less likely to be located in neighborhoods with high percentages of Black residents, and more likely to be located in neighborhoods that are urban and with highly educated residents. Given the historical and ongoing racial disparities in cannabis arrests across the US and New York, ensuring equitable access to legal cannabis services and products is critical and just. As legalization of cannabis continues to grow, states need to take additional measures to ensure equitable availability of and access to the benefits of cannabis legalization.

Availability of data and materials

The datasets analyzed in the study are publicly available as follows: 1) the New York State Medical Marijuana Program at https://www.health.ny.gov/regulations/medical_marijuana/, 2) New York State Office of Professions website at http://www.op.nysed.gov/opsearches.htm#nme, 3) 2018 US Census Bureau 5-year American Community Survey at https://www.census.gov/acs/www/data/data-tables-and-tools/data-profiles/2018/, and 4) 2019 US Census Bureau TIGER/Line Shapefiles at https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html. The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Institute of Medicine 2003. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: The National Academies Press. https://doi.org/10.17226/12875. http://nap.edu/12875. Accessed 26 December 2021

  2. National Academy of Sciences, Engineering, and Medicine. The Health Effects of Cannabis and Cannabinoids: The Current State of Evidence and Recommendations for Research. Washington, DC: The National Academies Press; 2017.

    Google Scholar 

  3. ProCon.org. Legal medical and recreational marijuana states. https://medicalmarijuana.procon.org/legal-medical-marijuana-states-and-dc/. Accessed 5 January 2021

  4. American Civil Liberties Union. A tale of two countries. Racially targeted arrests in the era of marijuana reform. 2020. https://www.aclu.org/report/tale-two-countries-racially-targeted-arrests-era-marijuana-reform. Accessed 22 November 22, 2020.

  5. United States Department of Justice Office of Justice Programs, Bureau of Justice Statistics. More than half of drug offenders in federal prison were serving sentences for powder or crack cocaine. 2015. https://www.bjs.gov/content/pub/press/dofp12pr.cfm. Accessed 22 November 2020.

  6. Drug Policy Alliance and the Public Science Project. Inequitable Marijuana Criminalization, COVID-19 and Socioeconomic Disparities: The Case for Community Reinvestment in New York. http://smart-ny.com/wp-content/uploads/2021/03/DPA_PSP_Marijuana_Disparities_COVID_3.16.2021.pdf. Accessed 30 January 2022.

  7. United States Drug Enforcement Administration. Drug Scheduling. https://www.dea.gov/druginfo/ds.shtml. Accessed 5 January 2021.

  8. Joudrey PJ, Edelman EJ, Wang EA. Drive Times to Opioid Treatment Programs in Urban and Rural Counties in 5 US States. JAMA. 2019;322(13):1310–2. https://doi.org/10.1001/jama.2019.12562.

    Article  PubMed  PubMed Central  Google Scholar 

  9. New York State Department of Health. New York State Medical Marijuana Program. https://www.health.ny.gov/regulations/medical_marijuana/. Accessed 16 June 2020.

  10. United States Census Bureau. TIGER/Line Shapefiles. https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html. Accessed 5 October 2021.

  11. Swift JN, Goldberg DW, Wilson, JP. Geocoding Best Practices: Review of Eight Commonly Used Geocoding Systems. Los Angeles, CA: University of Southern California GIS Research Laboratory. 2008. https://spatial.usc.edu/wp-content/uploads/2014/03/gislabtr10.pdf. Accessed 24 October 2020.

  12. Goldberg DW, Swift JN, Wilson JP. Geocoding Best Practices: Reference Data, Input Data and Feature Matching. Los Angeles, CA: University of Southern California GIS Research Laboratory. Technical Report No 8. 2008. https://spatial.usc.edu/wp-content/uploads/2014/03/gislabtr8.pdf. Accessed 24 October 2020.

  13. Joudrey PJ, Chadi N, Roy P, et al. Pharmacy-based methadone dispensing and drive time to methadone treatment in five states within the United States: A cross-sectional study. Drug Alcohol Depend. 2020;211:107968.

    Article  CAS  Google Scholar 

  14. McLafferty S, Freeman VL, Barrett RE, Luo L, Shockley A. Spatial error in geocoding physician location data from the AMA Physician Masterfile: implications for spatial accessibility analysis. Spat Spatiotemporal Epidemiol. 2012;3(1):31–8.

    Article  Google Scholar 

  15. United States Department of Agriculture. Rural-Urban Commuting Area Codes. https://www.ers.usda.gov/data-products/rural-urban-commuting-area-codes/. Accessed 24 October 2020.

  16. Hailu A, Wasserman C. Guidelines for Using Rural-Urban Classification Systems for Community Health Assessment. 2016. https://www.doh.wa.gov/Portals/1/Documents/1500/RUCAGuide.pdf. Accessed 24 October 2020.

  17. Strogatz D, Mielenz TJ, Johnson AK, et al. Importance of Driving and Potential Impact of Driving Cessation for Rural and Urban Older Adults. J Rural Health. 2020;36(1):88–93.

    Article  Google Scholar 

  18. United States Census Bureau. American Community Survey. 2019. https://www.census.gov/acs/www/data/data-tables-and-tools/data-profiles/2018/. Accessed 5 October 2021.

  19. New York State Education Department. Office of Professions. http://www.op.nysed.gov/opsearches.htm#nme. Accessed 24 October 2020.

  20. Hansen H, Siegel C, Wanderling J, DiRocco D. Buprenorphine and methadone treatment for opioid dependence by income, ethnicity and race of neighborhoods in New York City. Drug Alcohol Depend. 2016;164:14–21.

    Article  Google Scholar 

  21. Lagisetty PA, Ross R, Bohnert A, Clay M, Maust DT. Buprenorphine treatment divide by race/ethnicity and payment. JAMA Psychiat. 2019;76(9):979–81.

    Article  Google Scholar 

  22. Levine RS, Briggs NC, Kilbourne BS, et al. Black-White mortality from HIV in the United States before and after introduction of highly active antiretroviral therapy in 1996. Am J Public Health. 2007;97(10):1884–92.

    Article  Google Scholar 

  23. Beer L, Mattson CL, Bradley H, Skarbinski J. Understanding cross-sectional racial, ethnic, and gender disparities in antiretroviral use and viral suppression among HIV patients in the United States. Medicine (Baltimore). 2016;95(13):e3171.

    Article  CAS  Google Scholar 

  24. Landovitz RJ, Desmond KA, Leibowitz AA. Antiretroviral therapy: Racial disparities among publicly insured Californians with HIV. J Health Care Poor Underserved. 2017;28(1):406–29.

    Article  Google Scholar 

  25. Shahid H, Singh JA. Racial/ethnic disparity in rates and outcomes of total joint arthroplasty. Curr Rheumatol Rep. 2016;18(4):20.

    Article  Google Scholar 

  26. Amen TB, Varady NH, Rajaee S, Chen AF. Persistent racial disparities in utilization rates and perioperative metrics in total joint arthroplasty in the U.S.: A comprehensive analysis of trends from 2006 to 2015. J Bone Joint Surg Am. 2020;102(9):811–20.

    Article  Google Scholar 

  27. Rashid M, Fischman DL, Martinez SC, et al. Temporal trends and predictors of time to coronary angiography following non-ST-elevation acute coronary syndrome in the USA. Coron Artery Dis. 2019;30(3):159–70.

    Article  Google Scholar 

  28. Desai R, Singh S, Fong HK, et al. Racial and sex disparities in resource utilization and outcomes of multi-vessel percutaneous coronary interventions (a 5-year nationwide evaluation in the United States). Cardiovasc Diagn Ther. 2019;9(1):18–29.

    Article  Google Scholar 

  29. Gander JC, Zhang X, Plantinga L, et al. Racial disparities in preemptive referral for kidney transplantation in Georgia. Clin Transplant. 2018;32(9):e13380.

    Article  Google Scholar 

  30. Murphy KA, Jackson JW, Purnell TS, et al. Association of socioeconomic status and comorbidities with racial disparities during kidney transplant evaluation. Clin J Am Soc Nephrol. 2020;15(6):843–51.

    Article  Google Scholar 

  31. Burgard SA, Hawkins JM. Race/Ethnicity Educational Attainment, and Foregone Health Care in the United States in the 2007–2009 Recession. Am J Public Health. 2014;104(2):e134–40.

    Article  Google Scholar 

  32. Reinarman C, Nunberg H, Lanthier F, Heddleston T. Who are medical marijuana patients? Population characteristics from nine California assessment clinics. J Psychoactive Drugs. 2011;43(2):128–35.

    Article  Google Scholar 

  33. Morrison C, Gruenewald PJ, Freisthler B, Ponicki WR, Remer LG. The economic geography of medical cannabis dispensaries in California. Int J Drug Policy. 2014;25(3):508–15.

    Article  Google Scholar 

  34. Tabb LP, Fillmore C, Melly S. Location, location, location: Assessing the spatial patterning between marijuana licenses, alcohol outlets and neighborhood characteristics within Washington state. Drug Alcohol Depend. 2018;185:214–8.

    Article  Google Scholar 

  35. Shi Y, Meseck K, Jankowska MM. Availability of medical and recreational marijuana stores and neighborhood characteristics in Colorado. J Addict. 2016;2016:7193740.

    Article  Google Scholar 

  36. Thomas C, Freisthler B. Examining the locations of medical marijuana dispensaries in Los Angeles. Drug Alcohol Rev. 2016;35(3):334–7.

    Article  Google Scholar 

  37. Amiri S, Monsivais P, McDonell MG, Amram O. Availability of licensed cannabis businesses in relation to area deprivation in Washington state: A spatiotemporal analysis of cannabis business presence between 2014 and 2017. Drug Alcohol Rev. 2019;38(7):790–7.

    Article  Google Scholar 

  38. Boggess LN, Pérez DM, Cope K, Root C, Stretesky PB. Do medical marijuana centers behave like locally undesirable land uses? Implications for the geography of health and environmental justice. Urban Geogr. 2014;35(3):315–36.

    Article  Google Scholar 

  39. Colorado Department of Revenue Specialized Business Group. MED Licensed Facilities. https://www.colorado.gov/pacific/enforcement/med-licensed-facilities. Accessed 12 December 2020

  40. Washington State Department of Health. Marijuana Retail Stores with Medical Endorsement List – Updated October 2020. https://www.doh.wa.gov/Portals/1/Documents/Pubs/608017.pdf. Accessed 12 December 2020.

  41. Iloglu S, Joudrey PJ, Wang EA, Thornhill TA 4th, Gonsalves G. Expanding access to methadone treatment in Ohio through federally qualified health centers and a chain pharmacy: A geospatial modeling analysis. Drug Alcohol Depend. 2021 Mar;1(220):108534.

    Article  Google Scholar 

  42. Governor Cuomo signs legislation legalizing adult-use cannabis. https://www.governor.ny.gov/news/governor-cuomo-signs-legislation-legalizing-adult-use-cannabis. Accessed 1 May 2021.

  43. Chunara R, Zhao Y, Chen J, et al. Telemedicine and Healthcare Disparities: A cohort study in a large healthcare system in New York City during COVID-19. J Am Med Inform Assoc. 2021;28(1):33–41.

    Article  Google Scholar 

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Acknowledgements

Not applicable.

Funding

Dr. Cunningham received funding support from the National Institute on Drug Abuse (K24DA036955, R01DA044171) and the National Institute on Allergies and Infectious Diseases (P30AI124414). The funders had no role in the design or conduct of the study; data collection, analyses, or interpretation; manuscript preparation or submission.

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COC,CZ, and PJJ had full access to all the data in the study and take full responsibility for the integrity of the data and the accuracy of the analyses. COC and PJJ conceptualized and designed the study, and supervised the conduct of the study. MH and MW extracted data. COC and JPP drafted the manuscript. CZ conducted statistical analyses. All authors critically reviewed, revised, and approved the final manuscript.

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Correspondence to Chinazo O. Cunningham.

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This study was approved by the Albert Einstein College of Medicine Institutional Review Board. Because the study included only publicly available data, consent to participate was not required. All methods were carried out in accordance with relevant guidelines and regulations.

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The authors declare that they have no competing interests.

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Cunningham, C.O., Zhang, C., Hollins, M. et al. Availability of medical cannabis services by racial, social, and geographic characteristics of neighborhoods in New York: a cross-sectional study. BMC Public Health 22, 671 (2022). https://doi.org/10.1186/s12889-022-13076-1

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