On the use of ZIP codes and ZIP code tabulation areas (ZCTAs) for the spatial analysis of epidemiological data

The association of area deprivation and state child health with respiratory outcomes of pediatric patients with cystic fibrosis in the United States

BACKGROUND

Differences in socioenvironmental exposures influence overall child health, but their association with pediatric cystic fibrosis (CF) outcomes is less clear. This observational study investigated the relationship between area-level socioeconomic deprivation, state child health, and CF respiratory outcomes in a national cohort.

METHODS

We assessed relationships between the 2015 area deprivation index, a composite measure of socioeconomic disadvantage; the 2016 child health index, a state-specific measure of overall child health; and CF respiratory outcomes in the 2016 CF Foundation Patient Registry.

RESULTS

The sample included 9934 individuals with CF, aged 6-18 years. In multiple regression analysis adjusted for demographic and clinical covariates, those residing in the worst tertile for area deprivation had 2.8% lower percent predicted forced expiratory volume in 1 s (ppFEV₁ ; 95% confidence interval [CI]: -4.1 to -1.5), 1.2 more intravenous (IV) treatment nights (CI: 0.1-2.4), and 20% higher odds of ≥2 pulmonary exacerbations (odds ratio [OR]: 1.2, CI: 1.0-1.5) than best-tertile counterparts. Children with CF in states at the worst tertile for child health had 2.3% lower ppFEV₁ (CI: -4.5 to -0.2), 2.2 more IV treatment nights (CI: 0.5-3.6), and 40% higher odds of ≥2 exacerbations (OR: 1.4, CI: 1.1-1.8) than best-tertile counterparts. State child health accounted for the association between area deprivation and multiple exacerbations and more IV treatment nights.

CONCLUSIONS

Both area socioeconomic characteristics and state child health play a role in pediatric CF outcomes. The residual association of the state child health with CF outcomes after controlling for area deprivation reflects the ability of state programs to mitigate the effect of poverty.

Neighborhood characteristics associated with COVID-19 burden-the modifying effect of age

BACKGROUND

Neighborhood characteristics have been linked to community incidence of COVID-19, but the modifying effect of age has not been examined.

OBJECTIVE

We adapted a neighborhood-wide analysis study (NWAS) design to systematically examine associations between neighborhood characteristics and COVID-19 incidence among different age groups.

METHODS

The number of daily cumulative cases of COVID-19 by zip code area in Illinois has been made publicly available by the Illinois Department of Public Health. The number of COVID-19 cases was reported for eight age groups (under 20, 20-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80+). We reviewed this data published from May 23 through June 17, 2020 with complete data for all eight age groups and linked the data to neighborhood characteristics measured by the American Community Survey (ACS). Geographic age-specific cumulative incidence (cases per 1000 people) of COVID-19 was calculated by dividing the number of daily cumulative cases by the population of the same age group at each zip code area. The association between individual characteristics and COVID-19 incidence was examined using Poisson regression models.

RESULTS

At the zip code level, neighborhood socioeconomic status was a more important risk factor of COVID-19 incidence in children and working-age adults than in seniors. Social demographics and housing conditions were important risk factors of COVID-19 incidence in older age groups. We additionally observed significant associations between transportation-related variables and COVID-19 incidences in multiple age groups.

SIGNIFICANCE

We concluded that age modified the association between neighborhood characteristics and COVID-19 incidence.

Social determinants of health and coronavirus disease 2019 in pregnancy

Background

The social and physical environments in which people live affect the emergence, prevalence, and severity of both infectious and noninfectious diseases. There are limited data on how such social determinants of health, including neighborhood socioeconomic conditions, affect the risk of severe acute respiratory syndrome coronavirus 2 infection and severity of coronavirus disease 2019 during pregnancy.

Objective

Our objective was to determine how social determinants of health are associated with severe acute respiratory syndrome coronavirus 2 infection and the severity of coronavirus disease 2019 illness in hospitalized pregnant patients in New York during the global coronavirus disease 2019 pandemic.

Study Design

This cross-sectional study evaluated all pregnant patients who delivered and had polymerase chain reaction testing for severe acute respiratory syndrome coronavirus 2 between March 15, 2020, and June 15, 2020, at 7 hospitals within Northwell Health, the largest academic health system in New York. During the study period, universal severe acute respiratory syndrome coronavirus 2 testing protocols were implemented at all sites. Polymerase chain reaction testing was performed using nasopharyngeal swabs. Patients were excluded if the following variables were not available: polymerase chain reaction results, race, ethnicity, or zone improvement plan (ZIP) code of residence. Clinical data were obtained from the enterprise electronic health record system. For each patient, ZIP code was used as a proxy for neighborhood. Socioeconomic characteristics were determined by linking to ZIP code data from the United States Census Bureau's American Community Survey and the Internal Revenue Service's Statistics of Income Division. Specific variables of interest included mean persons per household, median household income, percent unemployment, and percent with less than high school education. Medical records were manually reviewed for all subjects with positive polymerase chain reaction test results to correctly identify symptomatic patients and then classify those subjects using the National Institutes of Health severity of illness categories. Classification was based on the highest severity of illness throughout gestation and not necessarily at the time of presentation for delivery.

Results

A total of 4873 patients were included in the study. The polymerase chain reaction test positivity rate was 11% (n=544). Among this group, 359 patients (66%) were asymptomatic or presymptomatic, 115 (21%) had mild or moderate coronavirus disease 2019, and 70 (13%) had severe or critical coronavirus disease 2019. On multiple logistic regression modeling, pregnant patients who had a positive test result for severe acute respiratory syndrome coronavirus 2 were more likely to be younger or of higher parity, belong to minoritized racial and ethnic groups, have public health insurance, have limited English proficiency, and reside in low-income neighborhoods with less educational attainment. On ordinal logit regression modeling, obesity, income and education were associated with coronavirus disease 2019 severity.

Conclusion

Social and physical determinants of health play a role in determining the risk of infection. The severity of coronavirus disease 2019 illness was not associated with race or ethnicity but was associated with maternal obesity and neighborhood level characteristics such as educational attainment and household income.

Trends in spatial access to colonoscopy in South Carolina, 2000-2014

BACKGROUND

Colonoscopy use has increased since Medicare began covering screening for average-risk persons. Our objective was to describe changes in spatial access to colonoscopy in South Carolina (SC) between 2000 and 2014.

METHODS

Using data from the SC Ambulatory Surgery Database, we created annual ZIP Code Tabulation Area (ZCTA) spatial accessibility scores. We assessed changes in accessibility, colonoscopy supply, and potential demand, overall and by metropolitan designation. Spatial clustering was also explored.

RESULTS

Spatial accessibility decreased across both small rural and metropolitan ZCTAs but was significantly higher in metropolitan areas during the first part of the study period . The proportion of persons with no access to colonoscopy within 30 min increased over time but was consistently higher in small rural areas. Clusters of low accessibility grew over time.

CONCLUSIONS

The supply of colonoscopy facilities decreased relative to the potential demand, and clusters of low access increased, indicating a contraction of services.

A Clinician's Guide to Polycultural Psychiatry

Patients and families each present unique microcultures, mixing and blending numerous broadly conceptualized cultural identity groups. Within individuals and families, cultural identities are experienced and enacted as complex matrices of intersecting identities that, to varying degrees, complement, assimilate, accommodate, or clash. In these patterns, individuals' relationships to cultures are not necessarily categorically distinct ("multicultural"). Instead, they are often "polycultural," defined as partial and plural; rather than interpreting different cultural traditions as separate and independent, they are, within the lives of individuals and families, better understood as systems that interact with and influence one another.Cultural identity groups extend beyond those traditionally considered by transcultural psychiatry-that is, beyond ethnic, racial, and language groups. They encompass (in alphabetical order) educational, ethnic, extended family, gender-oriented, generational, geographic, language and dialect, organizational, physical or psychiatric disability, political, professional, racial, religious, sect, social class, and vocational identity groups, among others. Simplistic assumptions and generalities about identity groups risk cultural stereotyping that may negatively bias clinical assessments. Therefore, practitioners striving for cultural sensitivity need to adopt nuanced strategies for approaching broad polycultural identity questions in clinical practice. Accordingly, this article suggests frameworks and strategies for (1) assessing and confronting one's own cultural preconceptions and prejudices, and (2) developing etic (objective quantitative data) and emic (insiders' experiential worldviews) perspectives pertinent to clinical anthropathology. Both etic and emic perspectives are necessary for polyculturally nuanced, respectful, comprehensive inquiries pertinent to patients' and family's health beliefs, psychiatric difficulties, and health practices. Supplementary material from the DSM-5 section on cultural formulation is adapted and discussed, along with the implications of polycultural psychiatry for education and training in psychiatry.

Maternal proximity to Central Appalachia surface mining and birth outcomes

Supplemental Digital Content is available in the text.

Maternal residency in Central Appalachia counties with coal production has been previously associated with increased rates of low birth weight (LBW). To refine the relationship between surface mining and birth outcomes, this study employs finer spatiotemporal estimates of exposure.

Effects of Hurricane Michael on Access to Care for Pregnant Women and Associated Pregnancy Outcomes

Background: Disasters are associated with worse perinatal outcomes, perhaps due to inadequate prenatal care (PNC). Methods: Using 2017-2019 Florida vital statistics, we compared PNC use before and after Hurricane Michael. We categorized counties as most affected (Area A) or less affected (Area B and C). We examined whether Michael's effects on perinatal outcomes varied by maternity care availability and used the Baron and Kenny method to assess whether delayed PNC initiation mediated perinatal outcomes. Log-binomial regression and semi-parametric linear regression were used, controlling for maternal and ZIP code tabulation area characteristics. Results: Compared to the one-year period pre-Michael, the week of the first PNC was later in all areas in the one-year period post-Michael, with the largest change in Area A (adjusted difference 0.112, 95% CI: 0.055-0.169), where women were less likely to receive PNC overall (aRR = 0.994, 95% CI = 0.990-0.998) and more likely to have inadequate PNC (aRR = 1.193, 95% CI = 1.127-1.264). Michael's effects on perinatal outcomes did not vary significantly by maternity care availability within Area A. Delayed PNC initiation appeared to mediate an increased risk in small for gestational age (SGA) births after Michael. Conclusion: Women in Area A initiated PNC later and had a higher likelihood of inadequate PNC. Delayed PNC initiation may partially explain increased risk of SGA.

Rapid Emergence of SARS-CoV-2 in the Greater New York Metropolitan Area: Geolocation, Demographics, Positivity Rates, and Hospitalization for 46 793 Persons Tested by Northwell Health

BACKGROUND

In March 2020, the greater New York metropolitan area became an epicenter for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The initial evolution of case incidence has not been well characterized.

METHODS

Northwell Health Laboratories tested 46 793 persons for SARS-CoV-2 from 4 March through 10 April. The primary outcome measure was a positive reverse transcription-polymerase chain reaction test for SARS-CoV-2. The secondary outcomes included patient age, sex, and race, if stated; dates the specimen was obtained and the test result; clinical practice site sources; geolocation of patient residence; and hospitalization.

RESULTS

From 8 March through 10 April, a total of 26 735 of 46 793 persons (57.1%) tested positive for SARS-CoV-2. Males of each race were disproportionally more affected than females above age 25, with a progressive male predominance as age increased. Of the positive persons, 7292 were hospitalized directly upon presentation; an additional 882 persons tested positive in an ambulatory setting before subsequent hospitalization, a median of 4.8 days later. Total hospitalization rate was thus 8174 persons (30.6% of positive persons). There was a broad range (>10-fold) in the cumulative number of positive cases across individual zip codes following documented first caseincidence. Test positivity was greater for persons living in zip codes with lower annual household income.

CONCLUSIONS

Our data reveal that SARS-CoV-2 incidence emerged rapidly and almost simultaneously across a broad demographic population in the region. These findings support the premise that SARS-CoV-2 infection was widely distributed prior to virus testing availability.

A case-crossover study of short-term air pollution exposure and the risk of stillbirth in California, 1999-2009

BACKGROUND

Associations between ambient air pollution and stillbirth have recently been explored, but most studies have focused on long-term (trimester or gestational averages) rather than short-term (within one week) air pollution exposures.

OBJECTIVE

To evaluate whether short-term exposures to criteria air pollutants are associated with increased risk of stillbirth.

METHODS

Using air pollution and fetal death certificate data from 1999 to 2009, we assessed associations between acute prenatal air pollution exposure and stillbirth in California. In a time-stratified case-crossover study, we analyzed single day and/or cumulative average days (up to a 6 day lag) of exposure to fine (PM_2.5) and coarse particles (PM_10-2.5), ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO) for mothers estimated to reside within 10 km of a pollution monitor based on reported zip code. We also examined potential confounding by apparent temperature or co-pollutants, and effect modification by maternal demographic factors, fetal sex, gestational age, and cause of stillbirth.

RESULTS

Stillbirth cases in the primary analyses ranged between 1,203 and 13,018, depending on the pollutant. For an IQR increase in SO₂ (lag 4), O₃ (lag 4), and PM_10-2.5 (lag 2), we found a 2.8% (95% confidence interval (CI) 0.2%, 5.5%), 5.8% (95% CI 1.6%, 10.1%), and 6.1% (95% CI 0.1%, 12.4%) increase in the odds of stillbirth, respectively. Additional adjustment by apparent temperature had little effect on the SO₂ association but slightly attenuated O₃ (adjusted % change: 4.2% (95% CI -0.2%, 8.9%) and PM_10-2.5 (5.7% (95% CI -1.1%, 13.0%)) associations, while other co-pollutants had minimal impact. Associations were observed specifically for stillbirths from obstetric complications and in women with higher educational attainment.

CONCLUSIONS

This study provides evidence for associations between prenatal short-term air pollution exposure, specifically SO₂, O_3, and PM_10-2.5, and stillbirth in California and warrants replication of findings in other settings.

Geographic Association Between Incidence of Acute Appendicitis and Socioeconomic Status

Importance

Some studies based on proportions of patients with perforated appendicitis (PA) among all patients with acute appendicitis (AA) have found an association between socioeconomic status (SES) and risk of perforation. A potential limitation is their use of proportions, which assumes that incidence of AA is evenly distributed across populations at risk. This assumption may be invalid, and SES may have a more complex association with both AA and PA.

Objective

To generate population-based incidences of AA and PA and to examine geographic patterns of incidence alongside geographic patterns of SES.

Design, Setting, and Participants

Retrospective study of data from Washington's Comprehensive Hospital Abstract Reporting System and the 2010 US census. Geographic methods were used to identify patterns of age- and sex-standardized incidence in Washington State between 2008 and 2012. The study included all patients discharged with International Classification of Diseases, Ninth Revision codes for AA or PA. Data were analyzed between November 2016 and December 2018.

Exposures

Location of primary residence.

Main Outcomes and Measures

Age- and sex-standardized incidence for AA and PA was generated for each census tract (CT). Global spatial autocorrelation was examined using Moran index (0.0 = completely random incidence; 1.0 = fully dependent on location). Clusters of low-incidence CTs (cold spots) and high-incidence CTs (hot spots) were identified for AA. Census-based SES data were aggregated for hot spots and cold spots and then compared.

Results

Statewide, over the 5-year study period, there were 35 730 patients with AA (including 9780 cases of PA), of whom 16 574 were women (46.4%). Median age of the cohort was 29 years (IQR, 16-48 years). Statewide incidence of AA and PA was 106 and 29 per 100 000 person-years (PY), respectively. Crude incidence was higher within the male population and peaked at age 10 to 19 years. Age- and sex-standardized incidence of AA demonstrated significant positive spatial autocorrelation (Moran index, 0.30; P < .001), but autocorrelation for PA was only half as strong (0.16; P < .001). Median incidence of AA was 118.1 per 100 000 PY among hot spots vs 86.2 per 100 000 PY among cold spots (P < .001). Socioeconomic status was higher in cold spots vs hot spots: mean proportion of college-educated adults was 56% vs 26% (P < .001), and mean per capita income was $44 691 vs $30 027 (P < .001).

Conclusions and Relevance

Age- and sex-standardized incidence of appendicitis is not randomly distributed across geographic subunits, and geographic clustering of AA is twice as strong as PA. Socioeconomic advantages, such as higher income and secondary education, are strongly associated with lower incidence of AA. These findings challenge conventional views that AA occurs randomly and has no predisposing characteristics beyond age/sex. Socioeconomic status, and likely other geographically circumscribed factors, are associated with incidence of AA.

Cardiovascular disease risk and the time to insulin initiation for Medicaid enrollees with type 2 diabetes

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No CVD benefits gains from early insulin initiation in young T2D individuals.

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CVD possibly pre-exists or concurrent to insulin initiation or first-line therapy.

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Young T2D individuals needs additional management of hypertension and dyslipidemia.

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CVD risk before insulin initiation is examined by innovative methods in large cohort.

Aims

We evaluated the relationship between the timing of insulin initiation and cardiovascular diseases (CVD) risk in Pennsylvania Medicaid enrollees with type 2 diabetes (T2D).

Methods

We included 17,873 enrollees (age 47.4 ± 10.3 years; range 18–64 years) initially treated with non-insulin glucose-lowering agents (GLAs) in 2008–2016. Based on clinical guidelines, we identified early (N = 1,158; 6%; insulin initiation ≤ 6 months after first-line GLAs), in-time (N = 569; 3%; 6–12 months), delayed (N = 2,761; 15%; >12 months), and non-insulin users (N = 13,385; 75%). The Prentice-Williams-Peterson (PWP) models with inverse probability weighting estimated CVD risk across the four groups and the change in risk after insulin initiation.

Results

Regardless of time to insulin initiation, insulin users had higher CVD risks after first-line GLAs than non-insulin users (aHR: early: 2.0 [1.5–2.5], in-time: 1.8 [1.2–2.6], delayed: 1.9 [1.6–2.3]). However, we found only a borderline increase in CVD risk after insulin initiation vs. before in early (aHR: 1.4 [1.1–1.8]) and delayed users (aHR: 1.3 [1.0–1.7]), and no increase in in-time users (aHR: 1.3 [0.9–2.0]).

Conclusions

We observed no gains in CVD benefits from insulin initiation in the early stages of pharmacotherapy possibly because CVD developed before insulin initiation. Additional management of hypertension and dyslipidemia may be important to reduce CVD risk in this young and middle-aged T2D cohort.

The effect of distance from cancer facility on advanced clinical stage at diagnosis in patients with cervical cancer

PURPOSE/OBJECTIVES

In the United States, cervical cancer remains a significant cause of morbidity and mortality. The effect of distance has a complicated relationship with disease characteristics and outcomes in other cancers. The purpose of this study is to investigate the relationship between distance from cancer facility on clinical stage at diagnosis in women with cervical cancer.

MATERIALS/METHODS

Data were obtained from the National Cancer Database which include patient demographics, disease characteristics, and treatment details. Persons diagnosed with cervical cancer from 2004 to 2015 were included. Subjects were excluded if they had missing information, variant histology, or lived >1,000 miles from their facility resulting in 51,413 persons. Disease was classified as localized (stage 1a-2a) or advanced (stage 2b-4b). Univariate comparisons were performed using analysis of variance and chi-square test. Multivariable logistic regression was used to investigate the effect of distance quartiles on advanced stage while adjusting for other significant variables.

RESULTS

Mean age was 51.0 years, 16.9% of women were black, 14.7% were Hispanic, 45.0% had private insurance, and 10.7% were uninsured. Overall, 50.9% of women presented with advanced disease. In multivariable analysis, greater distance demonstrated a stepwise risk reduction of advanced disease where those in the farthest quartile had odds ratio of 0.73 (p<0.001) relative to the closest. Additionally, age, race, income, and insurance status significantly affected risk of advanced disease.

CONCLUSIONS

Distance from cancer facility resulted in lower risk of advanced stage disease at diagnosis. Additional research could elucidate the nuanced relationship between distance, disease characteristics and outcomes in cervical cancer.

A Bayesian spatio-temporal analysis of neighborhood pediatric asthma emergency department visit disparities

Asthma disparities have complex, neighborhood-level drivers that are not well understood. Consequently, identifying particular contextual factors that contribute to disparities is a public health goal. We study pediatric asthma emergency department (ED) visit disparities and neighborhood factors associated with them in South Carolina (SC) census tracts from 1999 to 2015. Leveraging a Bayesian framework, we identify risk clusters, spatially-varying relationships, and risk percentile-specific associations. Clusters of high risk occur in both rural and urban census tracts with high probability, with neighborhood-specific associations suggesting unique risk factors for each locale. Bayesian methods can help clarify the neighborhood drivers of health disparities.

Mental health status in veterans residing in rural versus non-rural areas: results from the veterans' health study

BACKGROUND

The majority of Veterans Affair (VA) hospitals are in urban areas. We examined whether veterans residing in rural areas have lower mental health service use and poorer mental health status.

METHODS

Veterans with at least 1 warzone deployment in central and northeastern Pennsylvania were randomly selected for an interview. Mental health status, including PTSD, major depression, alcohol abuse and mental health global severity, were assessed using structured interviews. Psychiatric service use was based on self-reported utilization in the past 12 months. Results were compared between veterans residing in rural and non-rural areas. Data were also analyzed using multivariate logistic regression to minimize the influence by confounding factors.

RESULTS

A total of 1730 subjects (55% of the eligible veterans) responded to the survey and 1692 of them had complete geocode information. Those that did not have this information (n = 38), were excluded from some analyses. Veterans residing in rural areas were older, more often of the white race, married, and experienced fewer stressful events. In comparison to those residing in non-rural areas, veterans residing in rural areas had lower global mental health severity scores; they also had fewer mental health visits. In multivariate logistic regression, rural residence was associated with lower service use, but not with PTSD, major depression, alcohol abuse, and global mental health severity score after adjusting confounding factors (e.g., age, gender, marital status and education).

CONCLUSIONS

Rural residence is associated with lower mental health service use, but not with poor mental health in veterans with former warzone deployment, suggesting rural residence is possibly protective.

Association between private drinking water wells and the incidence of Campylobacteriosis in Maryland: An ecological analysis using Foodborne Diseases Active Surveillance Network (FoodNet) data (2007-2016)

Campylobacter is a leading cause of bacterial foodborne illness in the United States. Campylobacter infections have most often been associated with food-related risk factors, such as the consumption of poultry and raw milk. Socioeconomic, agricultural and environmental factors, including drinking water source, can also influence the risk of campylobacteriosis. Approximately 19% of Maryland residents rely on private wells as their sole source of water. Given that the federal Safe Drinking Water Act does not regulate the water quality of private wells, these could be important non-foodborne transmission pathways for Campylobacter. To address this issue, data on the number of culture-confirmed cases of Campylobacter infection in Maryland between 2007 and 2016 were obtained from the Foodborne Diseases Active Surveillance Network. Cases were linked by zip code with data from the Maryland well permits registry, the 2010 U.S. Census, the 2016 American Community Survey, and the USDA Agricultural Census. Campylobacteriosis incidence rates and well prevalence were calculated by zip code. Negative binomial regression models were then constructed to evaluate the association between the prevalence of private wells, presence/absence of animal feeding operations and the incidence of campylobacteriosis across the physiographic provinces in Maryland. From 2007 to 2016, a total of 5746 cases of campylobacteriosis were reported in Maryland, and annual incidence rates ranged from 6.65 to 11.59 per 100,000 people. In our statewide analysis, a significant positive association was observed between well prevalence and increased campylobacteriosis incidence at the zip code level (Incidence Rate Ratio (IRR) = 1.35, 95% Confidence Interval (CI) = 1.11, 1.63). A significant positive association was also observed between well prevalence and increased campylobacteriosis incidence in the Appalachian and Coastal provinces of Maryland (IRR = 2.94, 95% CI = 1.11, 7.76 and IRR = 1.70, 95% CI = 1.25, 2.31, respectively). The presence of broiler chicken operations, increasing median age and percentage of residents living in poverty were also significantly associated with campylobacteriosis incidence at the zip code level in some physiographic provinces in Maryland. To our knowledge, these are the first US data to demonstrate an association between prevalence of private wells and campylobacteriosis incidence at the zip code level.

Toward Detecting Infection Incidence in People With Type 1 Diabetes Using Self-Recorded Data (Part 1): A Novel Framework for a Personalized Digital Infectious Disease Detection System

BACKGROUND

Type 1 diabetes is a chronic condition of blood glucose metabolic disorder caused by a lack of insulin secretion from pancreas cells. In people with type 1 diabetes, hyperglycemia often occurs upon infection incidences. Despite the fact that patients increasingly gather data about themselves, there are no solid findings that uncover the effect of infection incidences on key parameters of blood glucose dynamics to support the effort toward developing a digital infectious disease detection system.

OBJECTIVE

The study aims to retrospectively analyze the effect of infection incidence and pinpoint optimal parameters that can effectively be used as input variables for developing an infection detection algorithm and to provide a general framework regarding how a digital infectious disease detection system can be designed and developed using self-recorded data from people with type 1 diabetes as a secondary source of information.

METHODS

We retrospectively analyzed high precision self-recorded data of 10 patient-years captured within the longitudinal records of three people with type 1 diabetes. Obtaining such a rich and large data set from a large number of participants is extremely expensive and difficult to acquire, if not impossible. The data set incorporates blood glucose, insulin, carbohydrate, and self-reported events of infections. We investigated the temporal evolution and probability distribution of the key blood glucose parameters within a specified timeframe (weekly, daily, and hourly).

RESULTS

Our analysis demonstrated that upon infection incidence, there is a dramatic shift in the operating point of the individual blood glucose dynamics in all the timeframes (weekly, daily, and hourly), which clearly violates the usual norm of blood glucose dynamics. During regular or normal situations, higher insulin and reduced carbohydrate intake usually results in lower blood glucose levels. However, in all infection cases as opposed to the regular or normal days, blood glucose levels were elevated for a prolonged period despite higher insulin and reduced carbohydrates intake. For instance, compared with the preinfection and postinfection weeks, on average, blood glucose levels were elevated by 6.1% and 16%, insulin (bolus) was increased by 42% and 39.3%, and carbohydrate consumption was reduced by 19% and 28.1%, respectively.

CONCLUSIONS

We presented the effect of infection incidence on key parameters of blood glucose dynamics along with the necessary framework to exploit the information for realizing a digital infectious disease detection system. The results demonstrated that compared with regular or normal days, infection incidence substantially alters the norm of blood glucose dynamics, which are quite significant changes that could possibly be detected through personalized modeling, for example, prediction models and anomaly detection algorithms. Generally, we foresee that these findings can benefit the efforts toward building next generation digital infectious disease detection systems and provoke further thoughts in this challenging field.

Spatial characteristics of men who have sex with men and transgender women attending HIV voluntary counselling and testing in Bangkok, Thailand, 2005-2015

Spatiotemporal analyses can support Human Immuno-deficiency Virus (HIV) prevention programmes by identifying locations of at-risk populations in space and time, and their proximity to HIV testing and prevention services. We assessed residential proximity to HIV testing venues for Men who have Sex with Men (MSM) and Transgender Women (TGW) attending Voluntary Counselling and Testing (VCT) at a large urban MSM clinic in Bangkok, Thailand in the period 2005-2015. We mapped clientprovided spatial data and HIV testing venues, calculating distance from residence to venues for VCT clients between i) September 2005-December 2009; ii) January 2010-September 2013; and iii) October 2013-May 2015. We assessed spatial characteristics across times, evaluating autocorrelation of HIV prevalence and visit density using Moran's I. Among 8,758 first-time VCT clients reporting geographic information from 2005-2015 (by period: 2737, 3917, 2104), 1329 (15.2%) lived in postal codes ≤5 km from the clinic. Over time, the proportion living in areas covered by Bangkok postal codes ≤2 km from any MSM HIV testing venue increased from 12.6% to 41.0% (p<0.01). The proportion living ≤5 km from the clinic decreased from 16.6% to 13.0% (p<0.01). HIV prevalence and clinic visit density demonstrated statistically significant non-random spatial patterning. Significant non-random patterning of prevalent infection and client visits highlighted Bangkok's urban HIV epidemic, clinic proximity to clients, and geographic reach. Clients lived closer to testing venues, yet farther from the urban MSM clinic, over time. Spatiotemporal characteristics of VCT clients can help assess service accessibility and guide targeted prevention planning.

Health-Predictive Social-Environmental Stressors and Social Buffers Are Place Based: A Multilevel Example From San Bernardino Communities

Significant evidence demonstrates the powerful effects social determinants have on health-related perceptions, behaviors, and health outcomes. However, these factors are often studied out of context, despite the acknowledgement that social determinants of health are place based. This research aimed to demonstrate that health-related perceptions are dependent on where one lives. Via a community-based participatory study, participants were randomly selected from 3 residential regions varying distances from a freight railyard (nearest n = 300, middle n = 338, farthest n = 327), all mostly low-income, predominately Latino areas. Interview-administered surveys with adults were collected by bilingual trained community members (87% response) in English/Spanish. Adjusted-logistic regression models assessed residential region as a predictor of stressors (perceptions of community safety, community noise disturbance, health care access, food insecurity) and buffers (3 neighborhood cohesion variables), after adjusting for household income, race/ethnicity, gender, and age. Each region experienced a unique amalgam of stressors and buffers. In general, the region closest to the railyard experienced more stressors (odds ratio [OR] = 1.58; 95% CI 1.12-2.20) and less buffers (OR = 0.69; 95% CI 0.49-0.96) than the region furthest from the railyard. More than half of participants in each region reported 2 or more stressors and 2 or more buffers. In this seemingly homogenous study population, place remained important in spite of traditionally used socioeconomic factors, such as household income and race/ethnicity. Social determinants of health should be studied with regard to their environmental context, which will require interdisciplinary collaboration to improve multilevel research methods. Including the study of social buffers will also promote sustainable, positive change to reduce health disparities.

Fatal police shootings of civilians, by rurality

In the United States, firearm homicides disproportionately occur in urban areas. We examine whether the same is true for fatal police shootings. We use data on fatal police shootings from Washington Post's "Fatal Force Database" (2015-2017). Using Census population estimates, we examine rates of fatal police shootings, stratified by race/ethnicity (White, Black, Hispanic), across urban and rural areas using five different classification schemes. Two classification schemes-from the National Center for Health Statistics and the US Department of Agriculture-use counties as the basic unit. Three classification schemes-from the National Center for Education Statistics, the US Census Bureau, and the website "FiveThirtyEight" use zip codes. There were just under 1000 fatal police shootings per year from 2015 to 2017, a rate of 0.31 per 100,000 population. Black victimization rates were more than twice those for Whites, with Hispanic victimization rates in between. Across all classification schemes there was little difference in rates of fatal police shootings between urban and rural areas, with suburbs having somewhat lower rates. Among Whites, rates of fatal police shooting victimization were higher in rural areas compared to urban areas, while among Blacks the rates were higher in more urban areas. Our results suggest that efforts to reduce police shootings of civilians should include rural and suburban as well as urban areas.

A geographic identifier assignment algorithm with Bayesian variable selection to identify neighborhood factors associated with emergency department visit disparities for asthma

BACKGROUND

Ecologic health studies often rely on outcomes from health service utilization data that are limited by relatively coarse spatial resolutions and missing geographic information, particularly neighborhood level identifiers. When fine-scale geographic data are missing, the ramifications and strategies for addressing them are not well researched or developed. This study illustrates a novel spatio-temporal framework that combines a geographic identifier assignment (i.e., geographic imputation) algorithm with predictive Bayesian variable selection to identify neighborhood factors associated with disparities in emergency department (ED) visits for asthma.

METHODS

ED visit records with missing fine-scale spatial identifiers (~ 20%) were geocoded using information from known, coarser, misaligned spatial units using an innovative geographic identifier assignment algorithm. We then employed systematic variable selection in a spatio-temporal Bayesian hierarchical model (BHM) predictive framework within the NIMBLE package in R. Our novel methodology is illustrated in an ecologic case study aimed at identifying neighborhood-level predictors of asthma ED visits in South Carolina, United States, from 1999 to 2015. The health outcome was annual ED visit counts in small areas (i.e., census tracts) with primary diagnoses of asthma (ICD9 codes 493.XX) among children ages 5 to 19 years.

RESULTS

We maintained 96% of ED visit records for this analysis. When the algorithm used areal proportions as probabilities for assignment, which addressed differential missingness of census tract identifiers in rural areas, variable selection consistently identified significant neighborhood-level predictors of asthma ED visit risk including pharmacy proximity, average household size, and carbon monoxide interactions. Contrasted with common solutions of removing geographically incomplete records or scaling up analyses, our methodology identified critical differences in parameters estimated, predictors selected, and inferences. We posit that the differences were attributable to improved data resolution, resulting in greater power and less bias. Importantly, without this methodology, we would have inaccurately identified predictors of risk for asthma ED visits, particularly in rural areas.

CONCLUSIONS

Our approach innovatively addressed several issues in ecologic health studies, including missing small-area geographic information, multiple correlated neighborhood covariates, and multiscale unmeasured confounding factors. Our methodology could be widely applied to other small-area studies, useful to a range of researchers throughout the world.

Lessons Learned From the Environmental Public Health Tracking Sub-County Data Pilot Project

OBJECTIVE

Small area data are key to better understanding the complex relationships between environmental health, health outcomes, and risk factors at a local level. In 2014, the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program (Tracking Program) conducted the Sub-County Data Pilot Project with grantees to consider integration of sub-county data into the National Environmental Public Health Tracking Network (Tracking Network).

DESIGN

The Tracking Program and grantees developed sub-county-level data for several data sets during this pilot project, working to standardize processes for submitting data and creating required geographies. Grantees documented challenges they encountered during the pilot project and documented decisions.

RESULTS

This article covers the challenges revealed during the project. It includes insights into geocoding, aggregation, population estimates, and data stability and provides recommendations for moving forward.

CONCLUSION

National standards for generating, analyzing, and sharing sub-county data should be established to build a system of sub-county data that allow for comparison of outcomes, geographies, and time. Increasing the availability and accessibility of small area data will not only enhance the Tracking Network's capabilities but also contribute to an improved understanding of environmental health and informed decision making at a local level.

Health and Environmental Justice Implications of Retiring Two Coal-Fired Power Plants in the Southern Front Range Region of Colorado

Despite improvements in air quality over the past 50 years, ambient air pollution remains an important public health issue in the United States. In particular, emissions from coal-fired power plants still have a substantial impact on both nearby and regional populations. Of particular concern is the potential for this impact to fall disproportionately on low-income communities and communities of color. We conducted a quantitative health impact assessment to estimate the health benefits of the proposed decommissioning of two coal-fired electricity generating stations in the Southern Front Range region of Colorado. We estimated changes in exposures to fine particulate matter and ozone using the Community Multiscale Air Quality model and predicted avoided health impacts and related economic values. We also quantitatively assessed the distribution of these benefits by population-level socioeconomic status. Across the study area, decommissioning the power plants would result in 2 (95% CI: 1-3) avoided premature deaths each year due to reduced PM2.5 exposures and greater reductions in hospitalizations and other morbidities. Health benefits resulting from the modeled shutdowns were greatest in areas with lower educational attainment and other economic indicators. Our results suggest that decommissioning these power plants and replacing them with zero-emissions sources could have broad public health benefits for residents of Colorado, with larger benefits for those that are socially disadvantaged. Our results also suggested that researchers and decision makers need to consider the unique demographics of their study areas to ensure that important opportunities to reduce health disparities associated with point-source pollution.

Medication Burden for Patients With Bacterial Keratitis

PURPOSE

To understand medication use and patient burden for treatment of bacterial keratitis (BK).

METHODS

A retrospective study was conducted examining medical records of adult patients with BK in an academic cornea practice. Data collected included medications used in the treatment of BK, dosing of medications, and the number and total duration of clinical encounters. Costs of medications were estimated using the average wholesale pharmacy price. Linear regression analysis was used to investigate associations of medication use with patient demographics and corneal culture results and reported with beta estimates (β) and 95% confidence intervals (95% CIs).

RESULTS

Forty-eight patients with BK (56% female) were studied. Patients were treated for a median of 54 days with 10 visits, 5 unique medications, 587 drops, and 7 prescriptions. The estimated median medication cost was $933 (interquartile range: $457-$1422) US dollars. Positive bacterial growth was significantly associated with more visits (β: 6.16, 95% CI: 1.75-10.6, P = 0.007), more days of treatment (β: 86.8, 95% CI: 10.8-163, P = 0.026), more prescribed medications (β: 2.86, 95% CI: 1.04-4.67, P = 0.003), and more doses of medications (β: 796, 95% CI: 818-1412, P = 0.012) compared with patients who did not undergo corneal scraping. Patients were prescribed 132 more drops of medication for every 10 years of older age (β: 132, 95% CI: 18.2-246, P = 0.024). Sex and income were not associated with medication burden or treatment length.

CONCLUSIONS

Older patients and those with positive cultures incur the most medication burden in treatment of BK. Providers should be aware of medication usage and cost burden as it may affect compliance with treatment.

GIScience and cancer: State of the art and trends for cancer surveillance and epidemiology

Maps are well recognized as an effective means of presenting and communicating health data, such as cancer incidence and mortality rates. These data can be linked to geographic features like counties or census tracts and their associated attributes for mapping and analysis. Such visualization and analysis provide insights regarding the geographic distribution of cancer and can be important for advancing effective cancer prevention and control programs. Applying a spatial approach allows users to identify location-based patterns and trends related to risk factors, health outcomes, and population health. Geographic information science (GIScience) is the discipline that applies Geographic Information Systems (GIS) and other spatial concepts and methods in research. This review explores the current state and evolution of GIScience in cancer research by addressing fundamental topics and issues regarding spatial data and analysis that need to be considered. GIScience, along with its health-specific application in the spatial epidemiology of cancer, incorporates multiple geographic perspectives pertaining to the individual, the health care infrastructure, and the environment. Challenges addressing these perspectives and the synergies among them can be explored through GIScience methods and associated technologies as integral parts of epidemiologic research, analysis efforts, and solutions. The authors suggest GIScience is a powerful tool for cancer research, bringing additional context to cancer data analysis and potentially informing decision-making and policy, ultimately aimed at reducing the burden of cancer.

Impact Of Risk Adjustment For Socioeconomic Status On Medicare Advantage Plan Quality Rankings

Sociodemographically disadvantaged patients have worse outcomes on some quality measures that inform Medicare Advantage plan ratings. Performance measurement that does not adjust for sociodemographic factors may penalize plans that disproportionately serve disadvantaged populations. We assessed the impact of adjusting for socioeconomic and demographic factors (sex, race/ethnicity, dual eligibility, disability, rurality, and neighborhood disadvantage) on Medicare Advantage plan rankings for blood pressure, diabetes, and cholesterol control. After adjustment, 20.3 percent, 19.5 percent, and 11.4 percent of Medicare Advantage plans improved by one or more quintiles in rank on the diabetes, cholesterol, and blood pressure measures, respectively. Plans that improved in ranking after adjustment enrolled higher proportions of disadvantaged enrollees. Adjusting quality measures for socioeconomic factors is important for equitable payment and quality reporting. Our study suggests that plans serving disadvantaged populations would have improved relative rankings for three important outcome measures if socioeconomic factors were included in risk-adjustment models.

Opioid overdose deaths and potentially inappropriate opioid prescribing practices (PIP): A spatial epidemiological study

INTRODUCTION

Opioid overdose deaths quintupled in Massachusetts between 2000 and 2016. Potentially inappropriate opioid prescribing practices (PIP) are associated with increases in overdoses. The purpose of this study was to conduct spatial epidemiological analyses of novel comprehensively linked data to identify overdose and PIP hotspots.

METHODS

Sixteen administrative datasets, including prescription monitoring, medical claims, vital statistics, and medical examiner data, covering >98% of Massachusetts residents between 2011-2015, were linked in 2017 to better investigate the opioid epidemic. PIP was defined by six measures: ≥100 morphine milligram equivalents (MMEs), co-prescription of benzodiazepines and opioids, cash purchases of opioid prescriptions, opioid prescriptions without a recorded pain diagnosis, and opioid prescriptions through multiple prescribers or pharmacies. Using spatial autocorrelation and cluster analyses, overdose and PIP hotspots were identified among 538 ZIP codes.

RESULTS

More than half of the adult population (n = 3,143,817, ages 18 and older) were prescribed opioids. Nearly all ZIP codes showed increasing rates of overdose over time. Overdose clusters were identified in Worcester, Northampton, Lee/Tyringham, Wareham/Bourne, Lynn, and Revere/Chelsea (Getis-Ord Gi*; p < 0.05). Large PIP clusters for ≥100 MMEs and prescription without pain diagnosis were identified in Western Massachusetts; and smaller clusters for multiple prescribers in Nantucket, Berkshire, and Hampden Counties (p < 0.05). Co-prescriptions and cash payment clusters were localized and nearly identical (p < 0.05). Overlap in PIP and overdose clusters was identified in Cape Cod and Berkshire County. However, we also found contradictory patterns in overdose and PIP hotspots.

CONCLUSIONS

Overdose and PIP hotspots were identified, as well as regions where the two overlapped, and where they diverged. Results indicate that PIP clustering alone does not explain overdose clustering patterns. Our findings can inform public health policy decisions at the local level, which include a focus on PIP and misuse of heroin and fentanyl that aim to curb opioid overdoses.

Misalignment Between ZIP Codes and Municipal Boundaries: A Problem for Public Health

While useful for mail delivery, ZIP Codes are flawed as a geographic metric for public health research. This paper quantifies the magnitude of potential error inherent in using ZIP Codes as a unit of analysis in the state of Michigan. ZIP Codes are intersected with municipality boundaries in ArcGIS to determine the degree of misclassification. Results showed that 49 percent of the population had their municipality misclassified by their ZIP Code. This creates potentially huge errors when ZIP Code is the only geographic identifier, because actual exposure may vary from the exposure to which an individual is assigned based on ZIP Code. The Flint, Michigan, Water Crisis is a prime example of this error and the need to consider finer units of analysis whenever possible. Collaboration with experts in geographic information science is therefore essential for any public health research project where location is a factor.

Are We Serving the Most At-Risk Communities? Examining the Reach of a South Carolina Home Visiting Program

In addition to individual-level characteristics, characteristics of the social and physical environments in which individuals reside may adversely impact health outcomes. Careful attention to the role of "place" can result in programs that successfully deliver services to those most at risk. This retrospective, cross-sectional study used geocoded residential addresses from 3090 households enrolled in a South Carolina (SC) home visiting program, 2013-2016, and corresponding years of data for maternal and child health outcomes obtained from vital records data. ZIP Code Tabulation Areas (ZCTAs) served as the primary geographic unit of analysis. ZCTAS with high volumes of birth or adverse maternal and child health outcomes for any of 10 indicators were flagged. Distribution of enrolled households across highest-risk ZCTAs was calculated. Of 379 ZCTAS with reported data, 152 had 8 or more risk flags. Of the 152 highest-risk ZCTAs, 33 also had high birth volumes. Fifty-seven of the 152 highest-risk ZCTAs had no enrollees; seven of the 33 highest-risk/highest-volume ZCTAS had no enrollees. Service delivery gaps existed despite a statewide, county-level needs assessment conducted prior to program implementation. This study suggests methods to identify service areas of need, as an ongoing effort toward program improvement.

Use of Fine-scale Geospatial Units and Population Data to Evaluate Access to Emergency Care

Introduction

Time to facility is a crucial element in emergency medicine (EM). Fine-scale geospatial units such as census block groups (CBG) and publicly available population datasets offer a low-cost and accurate approach to modeling geographic access to and utilization of emergency departments (ED). These methods are relevant to the emergency physician in evaluating patient utilization patterns, emergency medical services protocols, and opportunities for improved patient outcomes and cost utilization. We describe the practical application of geographic information system (GIS) and fine-scale analysis for EM using Ohio ED access as a case study.

Methods

Ohio ED locations (n=198), CBGs (n=9,238) and 2015 United States Census five-year American Community Survey (ACS) socioeconomic data were collected July—August 2016. We estimated drive time and distance between population-weighted CBGs and nearest ED using ArcGIS and 2010 CBG shapefiles. We examined drive times vs. ACS characteristics using multinomial regression and mapping.

Results

We categorized CBGs by centroid-ED travel time in minutes: <10 (73.4%; n=6,774), 10–30 (25.1%; n=2,315), and >30 (1.5%; n=141). CBGs with increased median age, Hispanic and non-Hispanic Black population, and college graduation rates had significantly decreased travel time. CBGs with increased low-income populations (adjusted odds ratio [AOR] [1.03], 95% confidence interval [CI] [1.01–1.04]) and vacant housing (AOR [1.06], 95% CI [1.05–1.08]) had increased odds of >30 minute travel time.

Conclusion

Use of fine-scale geographic analysis and population data can be used to evaluate geographic accessibility and utilization of EDs. Methods described offer guidance to approaching questions of geographic accessibility and have numerous ED and pre-hospital applications.

Consumer credit scores as a novel tool for identifying health in urban U.S. neighborhoods

PURPOSE

Credit scores may operate as a socioeconomic indicator of health: they represent cumulative financial history that directly influences ability to access financial and nonfinancial resources related to health. Yet, little is known about the relationship of credit score and health or to traditional measures of socioeconomic position (SEP). Our objectives were to (1) evaluate the association between area-level credit score and individual self-rated health and (2) compare credit score to traditional markers of area-level SEP in predicting self-rated health.

METHODS

Equifax estimates of average household credit score in 2015 among nine-digit zip code regions were combined with a representative survey of 2083 residents of Philadelphia to estimate the correlation with income, housing value, education, and occupational status and then predict the odds of self-rated health for credit score and each SEP measure.

RESULTS

Credit score was moderately correlated with SEP markers (r = -0.78 to 0.49). After adjusting for area- and individual-level SEP and demographic factors, each SD increase in credit score is associated with 26% greater odds of better self-rated health (odds ratio = 1.26, 95% confidence interval: 1.09-1.46). Credit score had a larger effect size than other SEP markers.

CONCLUSIONS

Credit score may be a useful complement to traditional measures of SEP in assessing health outcomes.

Socioeconomic and geographical disparities in prescription and illicit opioid-related overdose deaths in Orange County, California, from 2010-2014

Background: Reports indicate a geographic effect of socioeconomic inequalities on the occurrence of opioid-related fatal overdoses. This study aims to (1) estimate the rates of opioid-related overdoses, (2) estimate the association of benzodiazepine co-ingestion with opioid-related deaths, (3) estimate associations between socioeconomic indicators and opioid-related deaths, and (4) map the distribution of fatal overdoses, in Orange County (OC), California. Methods: An ecologic study was conducted of all opioid- related deaths (1205 total) from 2010 to 2014 obtained from the OC Coroner Division database (1065 OC residents, 55 nonresidents, 85 OC homeless) (analyzed 2016-2017). Rates of opioid overdose, benzodiazepine co-ingestion prevalence, and associations with socioeconomic status (SES; education, poverty, median income) using ZIP code analysis in the residential and homeless communities were calculated. Results: Of 1205 deaths, 904 involved prescription-type opioids, 223 involved heroin, 39 involved both, and 39 not stated; 973 were classified unintentional overdoses, 180 suicides, and 52 undetermined; 49% of cases involved benzodiazepines. Prescription-type opioid and heroin death rates for residents were 5.4/ 100,000 person-years (95% confidence interval [CI]: 5.0-5.8) and 1.2/100,000 person-years (95% CI: 1.0-1.4), respectively. Males, age group 45-54, and Caucasian race had the highest rate (13.6/100,000) of opioid mortality. The highest death rates were seen in homeless adults, at 136/100,000 person-years for prescription-type opioids (95% CI: 99.0-185.5) and 156/100,000 person-years for heroin (95% CI: 116.8-209.5). Conclusions: The burden of prescription-type opioid-related deaths in OC affects all demographics and levels of SES; there is a disproportionately high rate of opioid-related deaths in the OC homeless population.

Descriptive Epidemiology for Community-wide Naloxone Administration by Police Officers and Firefighters Responding to Opioid Overdose

Recently implemented New York State policy allows police and fire to administer intranasal naloxone when responding to opioid overdoses. This work describes the geographic distribution of naloxone administration (NlxnA) by police and fire when responding to opioid overdoses in Erie County, NY, an area of approximately 920,000 people including the City of Buffalo. Data are from opioid overdose reports (N = 800) filed with the Erie County Department of Health (July 2014-June 2016) by police/fire and include the overdose ZIP code, reported drug(s) used, and NlxnA. ZIP code data were geocoded and mapped to examine spatial patterns of NlxnA. The highest NlxnA rates (range: 0.01-84.3 per 10,000 population) were concentrated within the city and first-ring suburbs. Within 3 min 27.3% responded to NlxnA and 81.6% survived the overdose. The average individual was male (70.3%) and 31.4 years old (SD = 10.3). Further work is needed to better understand NlxnA and overdose, including exploring how the neighborhood environment creates a context for drug use, and how this context influences naloxone use and overdose experiences.

Temporal Analysis of Factors Associated with EAT-10 in Outpatients with Oropharyngeal Dysphagia from a Tertiary Care Clinic

Self-perception of disease is increasingly recognized as a determinant of health. The Eating Assessment Tool-10 (EAT-10) is a functional health status questionnaire that measures the symptomatic severity of dysphagia from the patient's perspective. The objective of this work was to identify factors (demographics, clinical variables, swallowing physiology, health-related quality of life) associated with longitudinal change in EAT-10 scores in outpatients with oropharyngeal dysphagia at a multi-disciplinary, tertiary care clinic. All patients with swallowing concerns that were included in the UW Madison Voice and Swallowing Outcomes database from 12/2012 to 04/2015 were invited to complete EAT-10 and a general health-related quality of life survey (SF-12v2) at their initial evaluation and six months later. Forty-two patients were included in analysis (n = 42). Weaning from a gastrostomy tube was significantly associated with EAT-10 improvement. Approximately 70% of the sample had mild dysphagia, and floor effects were observed for all EAT-10 items in this sample subset. Mean SF-12v2 Physical Component Summary score was substantially lower than that of the general population. Significant, weak-moderate correlations were found between EAT-10 and SF-12v2 scores for all comparisons except for Physical Health Composite at six months (rs = = 0.24 to - 0.43). Weaning from a feeding tube appears to meaningfully improve self-perceived symptoms of dysphagia. Given the floor effects observed, validity of EAT-10 for patients with mild dysphagia should be examined. Future research should address contributors to self-perceived symptom change across the range of dysphagia severity.

Patient portals and broadband internet inequality

Background

Patient portals have shown potential for increasing health care quality and efficiency. Internet access and other factors influencing patient portal use could worsen health disparities.

Methods

Observational study of adults with 1 or more visits to the outpatient clinics of an urban public health care system from 2012 to 2015. We used mixed effects logistic regression to evaluate the association between broadband internet access and (1) patient portal initiation (whether a patient logged in at least 1 time) and (2) messaging, controlling for demographic and neighborhood characteristics.

Results

There were 243 248 adults with 1 or more visits during 2012-2015 and 70 835 (29.1%) initiated portal use. Portal initiation was 34.1% for whites, 23.4% for blacks, and 23.8% for Hispanics, and was lower for Medicaid (26.5%), Medicare (23.4%), and uninsured patients (17.4%) than commercially insured patients (39.3%). In multivariate analysis, both initiation of portal use (odds ratio [OR] = 1.24 per quintile, 95% confidence interval [CI], 1.23-1.24, P  < .0001) and sending messages to providers (OR = 1.15, 95%CI, 1.09-1.14, P  < .0001) were associated with neighborhood broadband internet access.

Conclusions

The majority of adults with outpatient visits to a large urban health care system did not use the patient portal, and initiation of use was lower for racial and ethnic minorities, persons of lower socioeconomic status, and those without neighborhood broadband internet access. These results suggest the emergence of a digital divide in patient portal use. Given the scale of investment in patient portals and other internet-dependent health information technologies, efforts are urgently needed to address this growing inequality.

Social Ecological Correlates of Family-Level Interpersonal and Environmental Microaggressions Toward Sexual and Gender Minority Adolescents

Microaggressions are associated with mental and behavioral health problems and are common experiences for sexual and gender minority adolescents (SGMA). Little is known about the social ecological correlates of family-level interpersonal and environmental microaggressions for SGMA. Utilizing a national sample of SGMA (N = 1,177), this study (a) identified the frequencies of family-level interpersonal and environmental microaggressions by participant demographics and (b) examined individual-, family-, and structural-level factors associated with interpersonal and environmental microaggressions. Outness to parents, a transgender or genderqueer identity, and higher levels of gender role non-conformity were associated with higher frequencies of interpersonal microaggressions. Higher levels of family-level child maltreatment and religiosity were associated with higher frequencies of interpersonal and environmental microaggressions. State-level non-discrimination protections were associated with lower frequencies of environmental microaggressions. Suggestions for increased individual-level support for gender non-binary adolescents as well as family targeted preventive strategies are discussed. Areas for future research are highlighted.

A multivariate analysis of CalEnviroScreen: comparing environmental and socioeconomic stressors versus chronic disease

BACKGROUND

The health-risk assessment paradigm is shifting from single stressor evaluation towards cumulative assessments of multiple stressors. Recent efforts to develop broad-scale public health hazard datasets provide an opportunity to develop and evaluate multiple exposure hazards in combination.

METHODS

We performed a multivariate study of the spatial relationship between 12 indicators of environmental hazard, 5 indicators of socioeconomic hardship, and 3 health outcomes. Indicators were obtained from CalEnviroScreen (version 3.0), a publicly available environmental justice screening tool developed by the State of California Environmental Protection Agency. The indicators were compared to the total rate of hospitalization for 14 ICD-9 disease categories (a measure of disease burden) at the zip code tabulation area population level. We performed principal component analysis to visualize and reduce the CalEnviroScreen data and spatial autoregression to evaluate associations with disease burden.

RESULTS

CalEnviroScreen was strongly associated with the first principal component (PC) from a principal component analysis (PCA) of all 20 variables (Spearman ρ = 0.95). In a PCA of the 12 environmental variables, two PC axes explained 43% of variance, with the first axis indicating industrial activity and air pollution, and the second associated with ground-level ozone, drinking water contamination and PM_2.5. Mass of pesticides used in agriculture was poorly or negatively correlated with all other environmental indicators, and with the CalEnviroScreen calculation method, suggesting a limited ability of the method to capture agricultural exposures. In a PCA of the 5 socioeconomic variables, the first PC explained 66% of variance, representing overall socioeconomic hardship. In simultaneous autoregressive models, the first environmental and socioeconomic PCs were both significantly associated with the disease burden measure, but more model variation was explained by the socioeconomic PCs.

CONCLUSIONS

This study supports the use of CalEnviroScreen for its intended purpose of screening California regions for areas with high environmental exposure and population vulnerability. Study results further suggest a hypothesis that, compared to environmental pollutant exposure, socioeconomic status has greater impact on overall burden of disease.

A generic method for improving the spatial interoperability of medical and ecological databases

BACKGROUND

The availability of big data in healthcare and the intensive development of data reuse and georeferencing have opened up perspectives for health spatial analysis. However, fine-scale spatial studies of ecological and medical databases are limited by the change of support problem and thus a lack of spatial unit interoperability. The use of spatial disaggregation methods to solve this problem introduces errors into the spatial estimations. Here, we present a generic, two-step method for merging medical and ecological databases that avoids the use of spatial disaggregation methods, while maximizing the spatial resolution.

METHODS

Firstly, a mapping table is created after one or more transition matrices have been defined. The latter link the spatial units of the original databases to the spatial units of the final database. Secondly, the mapping table is validated by (1) comparing the covariates contained in the two original databases, and (2) checking the spatial validity with a spatial continuity criterion and a spatial resolution index.

RESULTS

We used our novel method to merge a medical database (the French national diagnosis-related group database, containing 5644 spatial units) with an ecological database (produced by the French National Institute of Statistics and Economic Studies, and containing with 36,594 spatial units). The mapping table yielded 5632 final spatial units. The mapping table's validity was evaluated by comparing the number of births in the medical database and the ecological databases in each final spatial unit. The median [interquartile range] relative difference was 2.3% [0; 5.7]. The spatial continuity criterion was low (2.4%), and the spatial resolution index was greater than for most French administrative areas.

CONCLUSIONS

Our innovative approach improves interoperability between medical and ecological databases and facilitates fine-scale spatial analyses. We have shown that disaggregation models and large aggregation techniques are not necessarily the best ways to tackle the change of support problem.

An analysis of the process and results of manual geocode correction

Geocoding is the science and process of assigning geographical coordinates (i.e. latitude, longitude) to a postal address. The quality of the geocode can vary dramatically depending on several variables, including incorrect input address data, missing address components, and spelling mistakes. A dataset with a considerable number of geocoding inaccuracies can potentially result in an imprecise analysis and invalid conclusions. There has been little quantitative analysis of the amount of effort (i.e. time) to perform geocoding correction, and how such correction could improve geocode quality type. This study used a low-cost and easy to implement method to improve geocode quality type of an input database (i.e. addresses to be matched) through the processes of manual geocode intervention, and it assessed the amount of effort to manually correct inaccurate geocodes, reported the resulting match rate improvement between the original and the corrected geocodes, and documented the corresponding spatial shift by geocode quality type resulting from the corrections. Findings demonstrated that manual intervention of geocoding resulted in a 90% improvement of geocode quality type, took 42 hours to process, and the spatial shift ranged from 0.02 to 151,368 m. This study provides evidence to inform research teams considering the application of manual geocoding intervention that it is a low-cost and relatively easy process to execute.

Geographic Access to Specialty Mental Health Care Across High- and Low-Income US Communities

Importance

With the future of the Affordable Care Act and Medicaid program unclear, it is critical to examine the geographic availability of specialty mental health treatment resources that serve low-income populations across local communities.

Objectives

To examine the geographic availability of community-based specialty mental health treatment resources and how these resources are distributed by community socioeconomic status.

Design, Setting, and Participants

Measures of the availability of specialty mental health treatment resources were derived using national data for 31 836 zip code tabulation areas from 2013 to 2015. Analyses examined the association between community socioeconomic status (assessed by median household income quartiles) and resource availability using logistic regressions. Models controlled for zip code tabulation area-level demographic characteristics and state indicators.

Main Outcomes and Measures

Dichotomous indicators for whether a zip code tabulation area had any (1) outpatient mental health treatment facility (more than nine-tenths of which offer payment arrangements for low-income populations), (2) office-based practice of mental health specialist physician(s), (3) office-based practice of nonphysician mental health professionals (eg, therapists), and (4) mental health facility or office-based practice (ie, any community-based resource).

Results

Of the 31 836 zip code tabulation areas in the study, more than four-tenths (3382 of 7959 [42.5%]) of communities in the highest income quartile (mean income, $81 207) had any community-based mental health treatment resource vs 23.1% of communities (1841 of 7959) in the lowest income quartile (mean income, $30 534) (adjusted odds ratio, 1.74; 95% CI, 1.50-2.03). When examining the distribution of mental health professionals, 25.3% of the communities (2014 of 7959) in the highest income quartile had a mental health specialist physician practice vs 8.0% (637 of 7959) of those in the lowest income quartile (adjusted odds ratio, 3.04; 95% CI, 2.53-3.66). Similarly, 35.1% of the communities (2792 of 7959) in the highest income quartile had a nonphysician mental health professional practice vs 12.9% (1029 of 7959) of those in the lowest income quartile (adjusted odds ratio, 2.77; 95%, 2.35-3.26). In contrast, outpatient mental health treatment facilities were less likely to be located in the communities in the highest vs lowest income quartiles (12.9% [1025 of 7959] vs 16.5% [1317 of 7959]; adjusted odds ratio, 0.43; 95% CI, 0.37-0.51). More than seven-tenths of the lowest income communities with any resource (71.5% [1317 of 1841]) had an outpatient mental health treatment facility.

Conclusions and Relevance

Mental health treatment facilities are more likely to be located in poorer communities, whereas office-based practices of mental health professionals are more likely to be located in higher-income communities. These findings indicate that mental health treatment facilities constitute the backbone of the specialty mental health treatment infrastructure in low-income communities. Policies are needed to support and expand available resources for this critical infrastructure.

Not Near Enough: Racial and Ethnic Disparities in Access to Nearby Behavioral Health Care and Primary Care

BACKGROUND

Racial, ethnic, and geographical health disparities have been widely documented in the United States. However, little attention has been directed towards disparities associated with integrated behavioral health and primary care services.

METHODS

Access to behavioral health professionals among primary care physicians was examined using multinomial logistic regression analyses with 2010 National Plan and Provider Enumeration System, American Medical Association Physician Masterfile, and American Community Survey data.

RESULTS

Primary care providers practicing in neighborhoods with higher percentages of African Americans and Hispanics were less likely to have geographically proximate behavioral health professionals. Primary care providers in rural areas were less likely to have geographically proximate behavioral health professionals.

CONCLUSION

Neighborhood-level factors are associated with access to nearby behavioral health and primary care. Additional behavioral health professionals are needed in racial/ethnic minority neighborhoods and rural areas to provide access to behavioral health services, and to progress toward more integrated primary care.

Neurodevelopmental Delay Diagnosis Rates Are Increased in a Region with Aerial Pesticide Application

A number of studies have implicated pesticides in childhood developmental delay (DD) and autism spectrum disorder (ASD). The influence of the route of pesticide exposure on neurodevelopmental delay is not well defined. To study this factor, we examined ASD/DD diagnoses rates in an area near our regional medical center that employs yearly aerial pyrethroid pesticide applications to combat mosquito-borne encephalitis. The aim of this study was to determine if areas with aerial pesticide exposure had higher rates of ASD/DD diagnoses. This regional study identified higher rates of ASD/DD diagnoses in an area with aerial pesticides application. Zip codes with aerial pyrethroid exposure were 37% more likely to have higher rates of ASD/DD (adjusted RR = 1.37, 95% CI = 1.06-1.78, p = 0.02). A Poisson regression model controlling for regional characteristics (poverty, pesticide use, population density, and distance to medical center), subject characteristics (race and sex), and local birth characteristics (prematurity, low birthweight, and birth rates) identified a significant relationship between aerial pesticide use and ASD/DD rates. The relationship between pesticide application and human neurodevelopment deserves additional study to develop safe and effective methods of mosquito prevention, particularly as communities develop plans for Zika virus control.

Do race/ethnicity or socioeconomic status affect why we place ear tubes in children?

INTRODUCTION

Despite recent concerns about potential overuse of tympanostomy tube (TT) placement to treat otitis media in children, utilization of this common procedure in the U.S. has been shown to be relatively less common among minority children. It is not known if the indications for TT differ by child race/ethnicity and/or socioeconomic status (SES). Our objective is to analyze the association of patient- and neighborhood-level demographics and SES with clinical indications for TT.

METHODS

We conducted a retrospective chart review of children who underwent TT at single urban academic tertiary pediatric care center in a 6-month period (8/2013-3/2014). Children with congenital anomalies or syndromic diagnoses were excluded (50/137 children, 36.5%). Children were grouped by primary TT indication, recurrent acute otitis media (RAOM) or chronic otitis media with effusion (OME). Group characteristics were compared using t-tests and chi-square analyses, and logistic regression was performed to assess the association between demographics and TT indication.

RESULTS

87 children were included in this analysis (mean age = 2.8 years, 1-6 years). The most common indication for TT was RAOM (53%), and these children had a mean of 6 AOM episodes/year. Indications for TT varied significantly by the patient's neighborhood SES (median neighborhood income $70,969.09-RAOM vs $58, 844.95-OME, p-value = 0.009). Those undergoing TT for RAOM were less likely to live in a high-poverty neighborhood (OR = 0.36,p-value = 0.02), whereas children who underwent TT for OME were more likely to live in a high-poverty neighborhood. There was no significant difference in indication by race/ethnicity or insurance type.

CONCLUSIONS

In this population, TT indications differed by SES. Among children receiving tubes, those from high poverty areas were more likely than those from low poverty neighborhoods to receive tubes for the indication of OME as opposed to RAOM. This finding suggests that concerns for appropriate use of TT in the setting of RAOM may be specific to a more affluent population. Future prospective patient-centered research will evaluate cultural and economic influences for families pursuing TT placement, as well as factors considered by physicians who make surgical recommendations.

Comparative approaches for assessing access to alcohol outlets: exploring the utility of a gravity potential approach

Background

A growing body of research recommends controlling alcohol availability to reduce harm. Various common approaches, however, provide dramatically different pictures of the physical availability of alcohol. This limits our understanding of the distribution of alcohol access, the causes and consequences of this distribution, and how best to reduce harm. The aim of this study is to introduce both a gravity potential measure of access to alcohol outlets, comparing its strengths and weaknesses to other popular approaches, and an empirically-derived taxonomy of neighborhoods based on the type of alcohol access they exhibit.

Methods

We obtained geospatial data on Seattle, including the location of 2402 alcohol outlets, United States Census Bureau estimates on 567 block groups, and a comprehensive street network. We used exploratory spatial data analysis and employed a measure of inter-rater agreement to capture differences in our taxonomy of alcohol availability measures.

Results

Significant statistical and spatial variability exists between measures of alcohol access, and these differences have meaningful practical implications. In particular, standard measures of outlet density (e.g., spatial, per capita, roadway miles) can lead to biased estimates of physical availability that over-emphasize the influence of the control variables. Employing a gravity potential approach provides a more balanced, geographically-sensitive measure of access to alcohol outlets.

Conclusions

Accurately measuring the physical availability of alcohol is critical for understanding the causes and consequences of its distribution and for developing effective evidence-based policy to manage the alcohol outlet licensing process. A gravity potential model provides a superior measure of alcohol access, and the alcohol access-based taxonomy a helpful evidence-based heuristic for scholars and local policymakers.

Buprenorphine and methadone treatment for opioid dependence by income, ethnicity and race of neighborhoods in New York City

BACKGROUND

Geographic and demographic variation in buprenorphine and methadone treatment use in U.S. cities has not been assessed. Identifying variance in opioid maintenance is essential to improving treatment access and equity.

PURPOSE

To examine the differential uptake of buprenorphine treatment in comparison to methadone treatment between 2004 and 2013 in neighborhoods in New York City characterized by income, race and ethnicity.

METHODS

Social area (SA) analysis of residential zip codes of methadone and buprenorphine patients in NYC, which aggregated zip codes into five social areas with similar percentages of residents below poverty, identifying as Black non-Hispanic and as Hispanic, to examine whether treatment rates differed significantly among social areas over time. For each rate, mixed model analyses of variance were run with fixed effects for social area, year and the interaction of social area by year.

RESULTS

Buprenorphine treatment increased in all social areas over time with a significantly higher rate of increase in the social area with the highest income and the lowest percentage of Black, Hispanic, and low-income residents. Methadone treatment decreased slightly in all social areas until 2011 and then increased bringing rates back to 2004 levels. Treatment patterns varied by social area.

CONCLUSIONS

Buprenorphine treatment rates are increasing in all social areas, with slower uptake in moderate income mixed ethnicity areas. Methadone rates have remained stable over time. Targeted investments to promote public sector buprenorphine prescription may be necessary to reduce disparities in buprenorphine treatment and to realize its potential as a public health measure.

New spatially continuous indices of redlining and racial bias in mortgage lending: links to survival after breast cancer diagnosis and implications for health disparities research

Racial health disparities continue to be a serious problem in the United States and have been linked to contextual factors, including racial segregation. In some cases, including breast cancer survival, racial disparities appear to be worsening. Using the Home Mortgage Disclosure Act (HMDA) database, we extend current spatial analysis methodology to derive new, spatially continuous indices of (1) racial bias in mortgage lending and (2) redlining. We then examine spatial patterns of these indices and the association between these new measures and breast cancer survival among Black/African American women in the Milwaukee, Wisconsin metropolitan area. These new measures can be used to examine relationships between mortgage discrimination and patterns of disease throughout the United States.

Latino residential segregation and self-rated health among Latinos: Washington State Behavioral Risk Factor Surveillance System, 2012-2014

The relationship between Latino residential segregation and self-rated health (SRH) is unclear, but might be partially affected by social capital. We investigated the association between Latino residential segregation and SRH while also examining the roles of various social capital measures. Washington State Behavioral Risk Factor Surveillance System (2012-2014) and U.S. Census data were linked by zip code and zip code tabulation area. Multilevel logistic regression models were used to estimate odds of good or better SRH by Latino residential segregation, measured by the Gini coefficient, and controlling for sociodemographic, acculturation and social capital measures of neighborhood ties, collective socialization of children, and social control. The Latino residential segregation - SRH relationship was convex, or 'U'-shaped, such that increases in segregation among Latinos residing in lower segregation areas was associated with lower SRH while increases in segregation among Latinos residing in higher segregation areas was associated with higher SRH. The social capital measures were independently associated with SRH but had little effect on the relationship between Latino residential segregation and SRH. A convex relationship between Latino residential segregation and SRH could explain mixed findings of previous studies. Although important for SRH, social capital measures of neighborhood ties, collective socialization of children, and social control might not account for the relationship between Latino residential segregation and SRH.

Characterizing the Morbidity of Postchemotherapy Retroperitoneal Lymph Node Dissection for Testis Cancer in a National Cohort of Privately Insured Patients

OBJECTIVE

To characterize morbidity of postchemotherapy retroperitoneal lymph node dissection (PC-RPLND) for testis cancer, we analyze a contemporary national database. PC-RPLND is the standard for residual radiographic masses ≥1 cm (nonseminoma) and positron emission tomography-avid masses ≥3 cm (seminoma). Morbidity for PC-RPLND is greater than primary RPLND, which may be mitigated by performing surgery at a high-volume cancer center.

METHODS

Current Procedural Terminology and International Classification of Diseases, Ninth Edition codes identified men with testis cancer undergoing PC- or primary RPLND in MarketScan (2007-2012). Multivariable logistic regression assessed factors associated with receiving adjunctive procedures (ie, nephrectomy, vascular reconstruction), prolonged hospitalization, and 90-day readmission. Geographic variables assessed regionalization of PC-RPLND.

RESULTS

Of 559 men with claims for PC- or primary RPLND (206, 37% PC-RPLND), 19% of PC-RPLND underwent adjunctive procedures (vs 1% among RPLND, P  <  .01). For PC-RPLND, the nephrectomy rate was 10% and the vascular reconstruction rate was 8%. On multivariable analysis, PC-RPLND was associated with undergoing adjunctive procedures (odds ratio 41.9; 95% confidence interval 11.7, 150) and prolonged hospitalization (odds ratio 3.75; 95% confidence interval 1.68, 8.42) compared to primary RPLND. PC-RPLND was not associated with 90-day readmission. Up to 29% of PC-RPLNDs are performed in centers, billing just a single case through MarketScan in the 6 years studied.

CONCLUSION

PC-RPLND is associated with adjunctive procedures and longer hospitalizations. Given the morbidity of PC-RPLND in this young patient population, efforts are needed to establish quality benchmarks for, reduce the morbidity of, and to accurately discriminate risk during patient discussions prior to this complex, specialized surgery.