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This book is a detailed, empirical investigation into the question of whether academic social research can compete with the commercial sector, with its new technologies and big data, in order to classify, profile, and understand us.

Postal codes are often the only geographic identifier available to match subjects in a health dataset to census geography. This paper describes the characteristics of postal codes reported by the Canadian population on the census and, as an indicator of geocoding accuracy, the proportion that are linked to a single dissemination area (DA). Postal codes reported on the 2016 Census questionnaire were matched to a combination of the Postal Code Conversion File (PCCF) and the Postal Code Conversion File Plus (PCCF+ version 7B) (reference date November 2018) to calculate population-weighted counts and the number of matches to DAs by province or territory, delivery mode type (DMT), population centre or rural area size, and census metropolitan area. The number of single matches to census tracts (CTs), census subdivisions (CSDs) and census divisions (CDs) was also calculated. In Canada, 72.6% of the population reported postal codes that matched to a single DA. This proportion was higher in urban cores (87.1%) and among postal codes for an urban street address (DMT=A) (85.3%) or apartment building (DMT=B) (95.3%), and was lower in rural areas (26.2% to 38.1%) and among rural postal codes (13.9%). In comparison, 89.3% and 95.4% of the population reported postal codes matching to a single CSD or CD, respectively, while 92.1% of the population that live within CT boundaries were matched to a single CT. Matching postal codes to census geography is relatively accurate and frequently one to one in urban centres. In rural areas and for some types of postal code DMTs, alternative approaches to using the PCCF and PCCF+ for attaching census geography might be explored.

Introduction: Exocrine pancreatic insufficiency (EPI) is a debilitating consequence for many chronic pancreatitis (CP) patients resulting in multiple nutritional deficiencies & clinical symptoms. Overall prevalence of EPI in CP is estimated to be approximately 35-50%. Pancreatic enzyme replacement therapy (PERT) is the mainstay of EPI treatment. The National Pancreas Foundation (NPF) has accredited 39 specialty pancreas centers (NPF-C) since 2015 at institutions nationwide to designate interdisciplinary referral centers for patients with pancreatic diseases. The aim of this study is to assess the effect of NPF-C on PERT prescriptions (PERT-Rx) for EPI in CP patients using a nationwide claims database. Methods: We performed a retrospective analysis of a national claims database (Symphony) of over 250 million patients in the US to identify an aggregated cohort of CP patients & further identify those CP patients with at least 3 PERT-Rx across manufacturers for 2017. CP patients & PERT-Rx were mapped using physician prescriber zip code. CP patients & PERT-Rx were stratified by zip code into 3 groups: NPF-C zip codes, zip codes within a 50 mile radius of an NPF-C, & zip codes over 50 miles from an NPF-C. Rates of PERT-Rx in CP patients in NPF-C zip codes were compared to the local surrounding 50 mile radius area zip codes & to zip codes over 50 miles to assess the effect of NPF-C on PERT-Rx using chi-square & ANOVA analyses (GraphPad Prism 7). Results: There were 163724 CP patients identified nationwide in 2017, of which 25927 had PERT-Rx (Overall treatment 15.8%). 1458 of 6376 (22.9%) CP patients treated for EPI in NPF-C zip codes received PERT-Rx, compared to 6733 of 44680 (15.1%) in the 50 mile radius surrounding NPF-C (chi-square p<0.0001) (Figure 1). PERT-Rx rates in NPF-C zip codes were significantly higher than in geographically near & remote locations (ANOVA p<0.0001). Rates of PERT-Rx in zip codes within 50 miles of NPF-C were numerically similar to those over 50 miles. Conclusion: Substantial gaps in the treatment of EPI in CP patients exist nationwide. Rates of PERT-Rx in CP patients were significantly higher in NPF-C zip codes compared to the surrounding areas & zip codes over 50 miles. The presence of pancreatic specialty centers may improve EPI care in CP. Additional interventions are needed to bridge these gaps & prevent the clinical sequelae of untreated EPI.

Abstract Social capital—the strength of an individual’s social network and community—has been identified as a potential determinant of outcomes ranging from education to health 1–8 . However, efforts to understand what types of social capital matter for these outcomes have been hindered by a lack of social network data. Here, in the first of a pair of papers 9 , we use data on 21 billion friendships from Facebook to study social capital. We measure and analyse three types of social capital by ZIP (postal) code in the United States: (1) connectedness between different types of people, such as those with low versus high socioeconomic status (SES); (2) social cohesion, such as the extent of cliques in friendship networks; and (3) civic engagement, such as rates of volunteering. These measures vary substantially across areas, but are not highly correlated with each other. We demonstrate the importance of distinguishing these forms of social capital by analysing their associations with economic mobility across areas. The share of high-SES friends among individuals with low SES—which we term economic connectedness—is among the strongest predictors of upward income mobility identified to date 10,11 . Other social capital measures are not strongly associated with economic mobility. If children with low-SES parents were to grow up in counties with economic connectedness comparable to that of the average child with high-SES parents, their incomes in adulthood would increase by 20% on average. Differences in economic connectedness can explain well-known relationships between upward income mobility and racial segregation, poverty rates, and inequality 12–14 . To support further research and policy interventions, we publicly release privacy-protected statistics on social capital by ZIP code at https://www.socialcapital.org .

OBJECTIVES : Postal codes are often the only available geographic identifiers in many sources of health data in Canada. In order to conduct geographic analyses, postal codes are routinely geocoded to census geography to link to ecological data. Despite common use of this method, the extent of geographic misclassification errors is poorly understood. We estimated misclassification errors in the geocoding of postal codes to assign census geography in Nova Scotia, Canada. METHODS : We examined differences between counts and match rates for postal-code geocoded and actual locations of buildings in Nova Scotia at two census administrative area levels: dissemination areas (DAs) and census subdivisions (CSDs). Actual locations were based on the data collected by the provincial government containing actual latitude/longitude of buildings. Variation in misclassification by rurality, using Statistics Canada’s classification, was also assessed. RESULTS : Outside two urban areas (Halifax Metro and Sydney) which had <10% differences in counts, many DAs had >30% differences. Match rates showed similar patterns, with the vast majority of non-urban DAs having <40% match rates. Even in major urban areas, 10% of DAs had large misclassification errors. Misclassification errors at the CSD level were still too great to estimate counts or rates without further area aggregation. CONCLUSION : Routine use of postal code geocoding should be replaced with geocoding of location information using additional identifiers such as civic addresses or latitude and longitude. If data holders did this in-house before providing data to researchers, the accuracy and capacity of geographic analysis would be enhanced while protecting confidentiality.

Despite overall improvements in access to care, geographic disparities still exist.

Until treatment and vaccine for coronavirus disease-2019 (COVID-19) becomes widely available, other methods of reducing infection rates should be explored. This study used a retrospective, observational analysis of deidentified tests performed at a national clinical laboratory to determine if circulating 25-hydroxyvitamin D (25(OH)D) levels are associated with severe acute respiratory disease coronavirus 2 (SARS-CoV-2) positivity rates. Over 190,000 patients from all 50 states with SARS-CoV-2 results performed mid-March through mid-June, 2020 and matching 25(OH)D results from the preceding 12 months were included. Residential zip code data was required to match with US Census data and perform analyses of race/ethnicity proportions and latitude. A total of 191,779 patients were included (median age, 54 years [interquartile range 40.4-64.7]; 68% female. The SARS-CoV-2 positivity rate was 9.3% (95% C.I. 9.2-9.5%) and the mean seasonally adjusted 25(OH)D was 31.7 (SD 11.7). The SARS-CoV-2 positivity rate was higher in the 39,190 patients with \"deficient\" 25(OH)D values (<20 ng/mL) (12.5%, 95% C.I. 12.2-12.8%) than in the 27,870 patients with \"adequate\" values (30-34 ng/mL) (8.1%, 95% C.I. 7.8-8.4%) and the 12,321 patients with values ≥55 ng/mL (5.9%, 95% C.I. 5.5-6.4%). The association between 25(OH)D levels and SARS-CoV-2 positivity was best fitted by the weighted second-order polynomial regression, which indicated strong correlation in the total population (R2 = 0.96) and in analyses stratified by all studied demographic factors. The association between lower SARS-CoV-2 positivity rates and higher circulating 25(OH)D levels remained significant in a multivariable logistic model adjusting for all included demographic factors (adjusted odds ratio 0.984 per ng/mL increment, 95% C.I. 0.983-0.986; p<0.001). SARS-CoV-2 positivity is strongly and inversely associated with circulating 25(OH)D levels, a relationship that persists across latitudes, races/ethnicities, both sexes, and age ranges. Our findings provide impetus to explore the role of vitamin D supplementation in reducing the risk for SARS-CoV-2 infection and COVID-19 disease.

A new study by the Student Borrower Protection Center finds that predatory for-profit schools are disproportionately targeting communities of color. Majority-Black zip codes are over 75 percent more likely to have a for-profit college than zip codes that are not majority Black.

IntroductionSocioeconomic status (SES) is a dynamic determinant factor that could predict the population’s wellness in many aspects. However, there is little existing literature on how socioeconomic conditions influence ischemic stroke outcomes. This study aims to determine whether SES has any correlation with the functional outcome of ischemic stroke patients undergoing mechanical thrombectomy.MethodsData was retrospectively collected using the Lyerly neurosurgery center’s prospectively maintained thrombectomy database. Patient-level data collected include stroke risk factors such as age, race, gender, comorbidities, infarct core volume, history of stroke, and tobacco usage. We measured the outcome of ischemic stroke using the modified Rankin Score (mRS) at 90-day post-procedure. SES was defined by a combination of the zip code median income data we collected from the 2019 U.S. Census Bureau’s American Community Survey (ACS) 5-year Projection and patients’ health insurance coverage. We used several multivariate analyses to plot the correlation between the outcomes and SES.ResultsAmong 508 patients collected, 234 (46%) had preferred outcome (mRS ≤ 2) and 274 (54%) had poor outcome (mRS > 2). Baseline risk factors that presented a significant correlation with poor outcome included age (p < 0.001), infarct core volume (p = 0.007), hypertension (p = 0.006), atrial fibrillation (p = 0.001), and existing history of stroke (p = 0.012). After adjusting for nuisance variables, unfavorable functional outcome (p < 0.001) was more likely to occur in patients with lower median income based on zip code. There was no association between health insurance and functional outcome (p = 0.58).ConclusionsMedian income based on zip code is a SES indicator that is potentially associated with functional outcomes of ischemic stroke patients undergoing mechanical thrombectomy. Further studies addressing this relationship are needed.Disclosures A. Nguyen: None. G. M. Cortez: None. M. Baretta: None. A. Aghaebrahim: None. E. Sauvageau: None. R. Hanel: None.

We conduct a within-county analysis using detailed ZIP code-level data to document new findings regarding the origins of the biggest financial crisis since the Great Depression. The sharp increase in mortgage defaults in 2007 is significantly amplified in subprime ZIP codes, or ZIP codes with a disproportionately large share of subprime borrowers as of 1996. Prior to the default crisis, these subprime ZIP codes experience an unprecedented relative growth in mortgage credit. The expansion in mortgage credit from 2002 to 2005 to subprime ZIP codes occurs despite sharply declining relative (and in some cases absolute) income growth in these neighborhoods. In fact, 2002 to 2005 is the only period in the past eighteen years in which income and mortgage credit growth are negatively correlated. We show that the expansion in mortgage credit to subprime ZIP codes and its dissociation from income growth is closely correlated with the increase in securitization of subprime mortgages.