Place, poverty and prescriptions: a cross-sectional study using Area Deprivation Index to assess opioid use and drug-poisoning mortality in the USA from 2012 to 2017

Kurani, Shaheen; McCoy, Rozalina G.; Inselman, Jonathan; Jeffery, Molly Moore; Chawla, Sumit; Rutten, Lila J. Finney; Giblon, Rachel; Shah, Nilay D.

doi:10.1136/bmjopen-2019-035376

Cited by 42 publications

(36 citation statements)

References 35 publications

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“…Red diamonds depict major cites (Albuquerque in Bernalillo County, Las Cruces in Dona Ana County, Rio Rancho in Sandoval County, and Santa Fe in Santa Fe County). ADI scores were developed by Mayo Clinic researchers ( 10 ), and are derived from 17 indicators that served as surrogates for income, employment, housing, and education.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, we considered 443,814 non-Hispanic AI/AN and non-Hispanic White women aged 15 years or older at risk for breast cancer. These data were extended to include county-level Area Deprivation Index (ADI) scores developed by Mayo Clinic researchers ( 10 ), which were measured from 17 indicators that served as a surrogate for income, employment, housing, and education.…”

Section: Methodsmentioning

confidence: 99%

“…By using Surveillance, Epidemiology, and End Results (SEER) (9) program data from 2005 through 2014, we applied Bayesian disease mapping to address 3 study-specific questions to quantify potential inequities in 10-year breast cancer incidence in New Mexico:…”

Section: Introductionmentioning

confidence: 99%

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Quantification of Potential Inequities in Breast Cancer Incidence in New Mexico Through Bayesian Disease Mapping

et al. 2021

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What is already known on this topic? Breast cancer incidence among non-Hispanic American Indian and Alaska Native (AI/AN) women has been quantified in large geographic regions of the United States, showing substantial regional variation in incidence inequities among non-Hispanic AI/AN populations. What is added by this report? We found substantial evidence in New Mexico of an overall reduction in breast cancer incidence among at-risk non-Hispanic AI/AN women compared with non-Hispanic White women in certain counties in the state. What are the implications for public health practice? Our findings can facilitate targeted statewide and county-level cancer control interventions to mitigate such disparities.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Quantification of Potential Inequities in Breast Cancer Incidence in New Mexico Through Bayesian Disease Mapping

et al. 2021

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“…This conflicting and limited evidence emphasizes the necessity for further studies evaluating patient knowledge of opioids in orthopaedic surgery. Our findings may reflect that patients of lower socioeconomic measures and from more disadvantaged geographic regions are more frequently exposed to opioid prescription, chronic consumption, and related overdose in their communities [ 38 – 41 ]. This exposure, in turn, may translate to greater knowledge regarding opioids.…”

Section: Discussionmentioning

confidence: 99%

Patient understanding regarding opioid use in an orthopaedic trauma surgery population: a survey study

Dunham

Enumah

et al. 2021

J Orthop Surg Res

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Background Prior studies have assessed provider knowledge and factors associated with opioid misuse; similar studies evaluating patient knowledge are lacking. The purpose of this study was to assess the degree of understanding regarding opioid use in orthopaedic trauma patients. We also sought to determine the demographic factors and clinical and personal experiences associated with level of understanding. Methods One hundred and sixty-six adult orthopaedic trauma surgery patients across two clinical sites of an academic institution participated in an internet-based survey (2352 invited, 7.1% response rate). Demographic, clinical, and personal experience variables, as well as perceptions surrounding opioid use were collected. Relationships between patient characteristics and opioid perceptions were identified using univariate and multivariable logistic regressions. Alpha = 0.05. Results Excellent recognition (> 85% correct) of common opioids, side effects, withdrawal symptoms, and disposal methods was demonstrated by 29%, 10%, 30%, and 2.4% of patients; poor recognition (< 55%) by 11%, 56%, 33%, and 52% of patients, respectively. Compared with white patients, non-white patients had 7.8 times greater odds (95% confidence interval [CI] 1.9–31) of perceiving addiction discrepancy (p = 0.004). Employed patients with higher education levels were less likely to have excellent understanding of side effects (adjusted odds ratio [aOR] 0.06, 95% CI 0.006–0.56; p = 0.01) and to understand that dependence can occur within 2 weeks (aOR 0.28, 95% CI 0.09–0.86; p = 0.03) than unemployed patients. Patients in the second least disadvantaged ADI quartile were more knowledgeable about side effects (aOR 8.8, 95% CI 1.7–46) and withdrawal symptoms (aOR 2.7, 95% CI 1.0–7.2; p = 0.046) than those in the least disadvantaged quartile. Patients who knew someone who was dependent or overdosed on opioids were less likely to perceive addiction discrepancy (aOR 0.24, 95% CI 0.07–0.76; p = 0.02) as well as more likely to have excellent knowledge of withdrawal symptoms (aOR 2.6, 95% CI 1.1–6.5, p = 0.03) and to understand that dependence can develop within 2 weeks (aOR 3.8, 95% CI 1.5–9.8, p = 0.005). Conclusions Level of understanding regarding opioid use is low among orthopaedic trauma surgery patients. Clinical and personal experiences with opioids, in addition to demographics, should be emphasized in the clinical history.

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“…The ADI score is a composite indicator of area-based socioeconomic disadvantages in the 4 domains outside of the strictly defined health care setting: income, housing, employment, and education. Previous studies have revealed disparities in cancer screening, 20 opioid use, 21 and drug-related mortality 21 as a function of the ADI score. However, evidence is scarce on the association between area-level deprivation (as captured by a multifaceted indicator of social determinants of health, such as the ADI) and diabetes care quality.…”

Section: Introductionmentioning

confidence: 99%

Association Between Area-Level Socioeconomic Deprivation and Diabetes Care Quality in US Primary Care Practices

et al. 2021

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IMPORTANCE Diabetes management operates under a complex interrelationship between behavioral, social, and economic factors that affect a patient's ability to self-manage and access care.OBJECTIVE To examine the association between 2 complementary area-based metrics, area deprivation index (ADI) score and rurality, and optimal diabetes care. DESIGN, SETTING, AND PARTICIPANTSThis cross-sectional study analyzed the electronic health records of patients who were receiving care at any of the 75 Mayo Clinic or Mayo Clinic Health System primary care practices in Minnesota, Iowa, and Wisconsin in 2019. Participants were adults with diabetes aged 18 to 75 years. All data were abstracted and analyzed between June 1 and November 30, 2020. MAIN OUTCOMES AND MEASURESThe primary outcome was the attainment of all 5 components of the D5 metric of optimal diabetes care: glycemic control (hemoglobin A 1c <8.0%), blood pressure (BP) control (systolic BP <140 mm Hg and diastolic BP <90 mm Hg), lipid control (use of statin therapy according to recommended guidelines), aspirin use (for patients with ischemic vascular disease), and no tobacco use. The proportion of patients receiving optimal diabetes care was calculated as a function of block group-level ADI score (a composite measure of 17 US Census indicators) and zip code-level rurality (calculated using Rural-Urban Commuting Area codes). Odds of achieving the D5 metric and its components were assessed using logistic regression that was adjusted for demographic characteristics, coronary artery disease history, and primary care team specialty. RESULTS Among the 31 934 patients included in the study (mean [SD] age, 59 [11.7] years; 17 645 men [55.3%]), 13 138 (41.1%) achieved the D5 metric of optimal diabetes care. Overall, 4090 patients (12.8%) resided in the least deprived quintile (quintile 1) of block groups and 1614 (5.1%) lived in the most deprived quintile (quintile 5), while 9193 patients (28.8%) lived in rural areas and 2299 (7.2%) in highly rural areas. The odds of meeting the D5 metric were lower for individuals residing in quintile 5 vs quintile 1 block groups (odds ratio [OR], 0.72; 95% CI, 0.67-0.78). Patients residing in rural (OR, 0.84; 95% CI, 0.73-0.97) and highly rural (OR, 0.81; 95% CI, 0.72-0.91) zip codes were also less likely to attain the D5 metric compared with those in urban areas. CONCLUSIONS AND RELEVANCEThis cross-sectional study found that patients living in more deprived and rural areas were significantly less likely to attain high-quality diabetes care compared with those living in less deprived and urban areas. The results call for geographically targeted population health management efforts by health systems, public health agencies, and payers.

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Place, poverty and prescriptions: a cross-sectional study using Area Deprivation Index to assess opioid use and drug-poisoning mortality in the USA from 2012 to 2017

Cited by 42 publications

References 35 publications

Quantification of Potential Inequities in Breast Cancer Incidence in New Mexico Through Bayesian Disease Mapping

Quantification of Potential Inequities in Breast Cancer Incidence in New Mexico Through Bayesian Disease Mapping

Patient understanding regarding opioid use in an orthopaedic trauma surgery population: a survey study

Association Between Area-Level Socioeconomic Deprivation and Diabetes Care Quality in US Primary Care Practices

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