Dispensaries and Medical Marijuana Certifications and Indications: Unveiling the Geographic Connections in Pennsylvania, USA

Introduction: Pennsylvania opened its first medical marijuana (MMJ) dispensary in 2018. Qualifying conditions include six conditions determined to have no or insufficient evidence to support or refute MMJ effectiveness. We conducted a study to describe MMJ dispensary access in Pennsylvania and to determine whether dispensary proximity was associated with MMJ certifications and community demographics. Methods: Using data from the Pennsylvania Department of Health, we geocoded MMJ dispensary locations and linked them to US Census Bureau data. We created dispensary access measures from the population-weighted centroid of Zip Code Tabulation Areas (ZCTAs): distance to nearest dispensary and density of dispensaries within a 15-min drive. We evaluated associations between dispensary access and the proportion of adults who received MMJ certification and the proportion of certifications for low evidence conditions (amyotrophic lateral sclerosis, epilepsy, glaucoma, Huntington’s disease, opioid use disorder, and Parkinson’s disease) using negative binomial modeling, adjusting for community features. To evaluate associations racial and ethnic composition of communities and distance to nearest dispensary, we used logistic regression to estimate the odds ratios (OR) and 95% confidence intervals (CI), adjusting for median income. Results: Distance and density of MMJ dispensaries were associated with the proportion of the ZCTA population certified and the proportion of certifications for insufficient evidence conditions. Compared to ZCTAs with no dispensary within 15 min, the proportion of adults certified increased by up to 31% and the proportion of certifications for insufficient evidence decreased by up to 22% for ZCTAs with two dispensaries. From 2018 to 2021, the odds of being within five miles of a dispensary was up to 20 times higher in ZCTAs with the highest proportions of individuals who were not White (2019: OR: 20.14, CI: 10.7–37.8) and more than double in ZCTAs with the highest proportion of Hispanic individuals (2018: OR: 2.81, CI: 1.51–5.24), compared to ZCTAs with the lowest proportions. Conclusions: Greater dispensary access was associated with the proportions of certified residents and certifications for low evidence conditions. Whether these patterns are due to differences in accessibility or demand is unknown. Associations between community demographics and dispensary proximity may indicate MMJ access differences

Association of Greenness with Blood Pressure among Individuals with Type 2 Diabetes across Rural to Urban Community Types in Pennsylvania, USA

Greenness may impact blood pressure (BP), though evidence is limited among individuals with type 2 diabetes (T2D), for whom BP management is critical. We evaluated associations of residential greenness with BP among individuals with T2D in geographically diverse communities in Pennsylvania. To address variation in greenness type, we evaluated modification of associations by percent forest. We obtained systolic (SBP) and diastolic (DBP) BP measurements from medical records of 9593 individuals following diabetes diagnosis. Proximate greenness was estimated within 1250-m buffers surrounding individuals’ residences using the normalized difference vegetation index (NDVI) prior to blood pressure measurement. Percent forest was calculated using the U.S. National Land Cover Database. Linear mixed models with robust standard errors accounted for spatial clustering; models were stratified by community type (townships/boroughs/cities). In townships, the greenest communities, an interquartile range increase in NDVI was associated with reductions in SBP of 0.87 mmHg (95% CI: −1.43, −0.30) and in DBP of 0.41 mmHg (95% CI: −0.78, −0.05). No significant associations were observed in boroughs or cities. Evidence for modification by percent forest was weak. Findings suggest a threshold effect whereby high greenness may be necessary to influence BP in this population and support a slight beneficial impact of greenness on cardiovascular disease risk

Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network

Introduction Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved.Methods and analysis The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0–17 years only (component A), three centres conduct surveillance in young adults aged 18–44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression.Ethics and dissemination The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA