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

INTRODUCTION

Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved.

METHODS AND ANALYSIS

The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0-17 years only (component A), three centres conduct surveillance in young adults aged 18-44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression.

ETHICS AND DISSEMINATION

The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.

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

Introduction

Pennsylvania opened its first medical marijuana (MMJ) dispensary in 2018. Qualifying conditions include six conditions determined to have no or insufficient evidence to support or refute MMJ effectiveness. We conducted a study to describe MMJ dispensary access in Pennsylvania and to determine whether dispensary proximity was associated with MMJ certifications and community demographics.

Methods

Using data from the Pennsylvania Department of Health, we geocoded MMJ dispensary locations and linked them to US Census Bureau data. We created dispensary access measures from the population-weighted centroid of Zip Code Tabulation Areas (ZCTAs): distance to nearest dispensary and density of dispensaries within a 15-min drive. We evaluated associations between dispensary access and the proportion of adults who received MMJ certification and the proportion of certifications for low evidence conditions (amyotrophic lateral sclerosis, epilepsy, glaucoma, Huntington's disease, opioid use disorder, and Parkinson's disease) using negative binomial modeling, adjusting for community features. To evaluate associations racial and ethnic composition of communities and distance to nearest dispensary, we used logistic regression to estimate the odds ratios (OR) and 95% confidence intervals (CI), adjusting for median income.

Results

Distance and density of MMJ dispensaries were associated with the proportion of the ZCTA population certified and the proportion of certifications for insufficient evidence conditions. Compared to ZCTAs with no dispensary within 15 min, the proportion of adults certified increased by up to 31% and the proportion of certifications for insufficient evidence decreased by up to 22% for ZCTAs with two dispensaries. From 2018 to 2021, the odds of being within five miles of a dispensary was up to 20 times higher in ZCTAs with the highest proportions of individuals who were not White (2019: OR: 20.14, CI: 10.7-37.8) and more than double in ZCTAs with the highest proportion of Hispanic individuals (2018: OR: 2.81, CI: 1.51-5.24), compared to ZCTAs with the lowest proportions.

Conclusions

Greater dispensary access was associated with the proportions of certified residents and certifications for low evidence conditions. Whether these patterns are due to differences in accessibility or demand is unknown. Associations between community demographics and dispensary proximity may indicate MMJ access differences.

Age and sex differences in the association between neighborhood socioeconomic environment and incident diabetes: Results from the diabetes location, environmental attributes and disparities (LEAD) network

Objective

Worse neighborhood socioeconomic environment (NSEE) may contribute to an increased risk of type 2 diabetes (T2D). We examined whether the relationship between NSEE and T2D differs by sex and age in three study populations.

Research design and methods

We conducted a harmonized analysis using data from three independent longitudinal study samples in the US: 1) the Veteran Administration Diabetes Risk (VADR) cohort, 2) the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, and 3) a case-control study of Geisinger electronic health records in Pennsylvania. We measured NSEE with a z-score sum of six census tract indicators within strata of community type (higher density urban, lower density urban, suburban/small town, and rural). Community type-stratified models evaluated the likelihood of new diagnoses of T2D in each study sample using restricted cubic splines and quartiles of NSEE.

Results

Across study samples, worse NSEE was associated with higher risk of T2D. We observed significant effect modification by sex and age, though evidence of effect modification varied by site and community type. Largely, stronger associations between worse NSEE and diabetes risk were found among women relative to men and among those less than age 45 in the VADR cohort. Similar modification by age group results were observed in the Geisinger sample in small town/suburban communities only and similar modification by sex was observed in REGARDS in lower density urban communities.

Conclusions

The impact of NSEE on T2D risk may differ for males and females and by age group within different community types.

Sinus inflammation and chronic rhinosinusitis are associated with a diagnosis of new onset asthma in the following year

BACKGROUND

Chronic rhinosinusitis (CRS) and asthma commonly co-occur. No studies have leveraged large samples needed to formally address whether preexisting CRS is associated with new onset asthma over time.

METHODS

We evaluated whether prevalent CRS [identified in two ways: validated text algorithm applied to sinus computerized tomography (CT) scan or two diagnoses] was associated with new onset adult asthma in the following year. We used electronic health record data from Geisinger from 2008 to 2019. For each year we removed persons with any evidence of asthma through the end of the year, then identified those with new diagnosis of asthma in the following year. Complementary log-log regression was used to adjust for confounding variables (e.g., sociodemographic, contact with the health system, comorbidities), and hazard ratios (HRs) and 95% confidence intervals (CI) were calculated.

RESULTS

A total of 35,441 persons were diagnosed with new onset asthma and were compared to 890,956 persons who did not develop asthma. Persons with new onset asthma tended to be female (69.6%) and younger (mean [SD] age 45.9 [17.0] years). Both CRS definitions were associated (HR, 95% CI) with new onset asthma, with 2.21 (1.93, 2.54) and 1.48 (1.38, 1.59) for CRS based on sinus CT scan and two diagnoses, respectively. New onset asthma was uncommonly observed in persons with a history of sinus surgery.

CONCLUSION

Prevalent CRS identified with two complementary approaches was associated with a diagnosis of new onset asthma in the following year. The findings may have clinical implications for the prevention of asthma.

Risk of new-onset and prevalent disease in chronic rhinosinusitis: A prospective cohort study

BACKGROUND

Chronic rhinosinusitis (CRS) is accompanied by burdensome comorbid conditions. Understanding the relative timing of the onset of these conditions could inform disease prevention, detection, and management.

OBJECTIVE

To evaluate the association between CRS and new-onset and prevalent asthma, noncystic fibrosis bronchiectasis (NCFBE), chronic obstructive pulmonary disease (COPD), gastroesophageal reflux disease (GERD), and obstructive sleep apnea (OSA).

METHODS

We conducted a prospective cohort study among primary care patients using a detailed medical and symptom questionnaire in 2014 and again in 2020. We used questionnaire and electronic health record (EHR) data to determine CRS status: CRSSE (moderate to severe symptoms with EHR evidence), CRSE (limited symptoms with EHR evidence), CRSS (moderate to severe symptoms without EHR evidence), CRSneg (limited symptoms and no EHR evidence; reference). We evaluated the association between CRS status and new-onset and prevalent disease using logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

There were 7847 and 4445 respondents to the 2014 and 2020 questionnaires, respectively. CRSSE (vs CRSneg ) was associated with increased odds of new-onset asthma (OR, 1.74 [CI, 1.09-2.77), NCFBE (OR, 1.87 [CI, 1.12-3.13]), COPD (OR, 1.73 [CI, 1.14-2.68]), GERD (OR, 1.95 [CI, 1.61-2.35]), and OSA (OR, 1.91 [CI, 1.39-2.62]). Similarly, increased odds were observed for associations with the prevalence of these conditions.

CONCLUSION

The findings from the study support further exploration of CRS as a target for the prevention and detection of asthma, NCFBE, COPD, GERD, and OSA.

Mediation of an association between neighborhood socioeconomic environment and type 2 diabetes through the leisure-time physical activity environment in an analysis of three independent samples

INTRODUCTION

Inequitable access to leisure-time physical activity (LTPA) resources may explain geographic disparities in type 2 diabetes (T2D). We evaluated whether the neighborhood socioeconomic environment (NSEE) affects T2D through the LTPA environment.

RESEARCH DESIGN AND METHODS

We conducted analyses in three study samples: the national Veterans Administration Diabetes Risk (VADR) cohort comprising electronic health records (EHR) of 4.1 million T2D-free veterans, the national prospective cohort REasons for Geographic and Racial Differences in Stroke (REGARDS) (11 208 T2D free), and a case-control study of Geisinger EHR in Pennsylvania (15 888 T2D cases). New-onset T2D was defined using diagnoses, laboratory and medication data. We harmonized neighborhood-level variables, including exposure, confounders, and effect modifiers. We measured NSEE with a summary index of six census tract indicators. The LTPA environment was measured by physical activity (PA) facility (gyms and other commercial facilities) density within street network buffers and population-weighted distance to parks. We estimated natural direct and indirect effects for each mediator stratified by community type.

RESULTS

The magnitudes of the indirect effects were generally small, and the direction of the indirect effects differed by community type and study sample. The most consistent findings were for mediation via PA facility density in rural communities, where we observed positive indirect effects (differences in T2D incidence rates (95% CI) comparing the highest versus lowest quartiles of NSEE, multiplied by 100) of 1.53 (0.25, 3.05) in REGARDS and 0.0066 (0.0038, 0.0099) in VADR. No mediation was evident in Geisinger.

CONCLUSIONS

PA facility density and distance to parks did not substantially mediate the relation between NSEE and T2D. Our heterogeneous results suggest that approaches to reduce T2D through changes to the LTPA environment require local tailoring.

Association between Gentrification and Health and Healthcare Utilization

There is tremendous interest in understanding how neighborhoods impact health by linking extant social and environmental drivers of health (SDOH) data with electronic health record (EHR) data. Studies quantifying such associations often use static neighborhood measures. Little research examines the impact of gentrification-a measure of neighborhood change-on the health of long-term neighborhood residents using EHR data, which may have a more generalizable population than traditional approaches. We quantified associations between gentrification and health and healthcare utilization by linking longitudinal socioeconomic data from the American Community Survey with EHR data across two health systems accessed by long-term residents of Durham County, NC, from 2007 to 2017. Census block group-level neighborhoods were eligible to be gentrified if they had low socioeconomic status relative to the county average. Gentrification was defined using socioeconomic data from 2006 to 2010 and 2011-2015, with the Steinmetz-Wood definition. Multivariable logistic and Poisson regression models estimated associations between gentrification and development of health indicators (cardiovascular disease, hypertension, diabetes, obesity, asthma, depression) or healthcare encounters (emergency department [ED], inpatient, or outpatient). Sensitivity analyses examined two alternative gentrification measures. Of the 99 block groups within the city of Durham, 28 were eligible (N = 10,807; median age = 42; 83% Black; 55% female) and 5 gentrified. Individuals in gentrifying neighborhoods had lower odds of obesity (odds ratio [OR] = 0.89; 95% confidence interval [CI]: 0.81-0.99), higher odds of an ED encounter (OR = 1.10; 95% CI: 1.01-1.20), and lower risk for outpatient encounters (incidence rate ratio = 0.93; 95% CI: 0.87-1.00) compared with non-gentrifying neighborhoods. The association between gentrification and health and healthcare utilization was sensitive to gentrification definition.

Assessing Measurement Invariance of a Land Use Environment Construct Across Levels of Urbanicity

Variation in the land use environment (LUE) impacts the continuum of walkability to car dependency, which has been shown to have effects on health outcomes. Existing objective measures of the LUE do not consider whether the measurement of the construct varies across different types of communities along the rural/urban spectrum. To help meet the goals of the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, we developed a national, census tract-level LUE measure which evaluates the road network and land development. We tested for measurement invariance by LEAD community type (higher density urban, lower density urban, suburban/small town, and rural) using multiple group confirmatory factor analysis. We determined that metric invariance does not exist; thus, measurement of the LUE does vary across community type with average block length, average block size, and percent developed land driving most shared variability in rural tracts and with intersection density, street connectivity, household density, and commercial establishment density driving most shared variability in higher density urban tracts. As a result, epidemiologic studies need to consider community type when assessing the LUE to minimize place-based confounding.

Strong and consistent associations of precedent chronic rhinosinusitis with risk of non-cystic fibrosis bronchiectasis

BACKGROUND

Chronic rhinosinusitis (CRS) and bronchiectasis commonly co-occur, but most prior studies were not designed to evaluate temporality and causality.

OBJECTIVES

In a sample representing the general population in 37 counties in Pennsylvania, and thus the full spectrum of sinonasal and relevant lung diseases, we aimed to evaluate the temporality and strength of associations of CRS with non-cystic fibrosis bronchiectasis.

METHODS

We completed case-control analyses for each of 3 primary bronchiectasis case finding methods. We used electronic health records to identify CRS and bronchiectasis with diagnoses, procedure orders, and/or specific text in sinus or chest computerized tomography scan radiology reports. The controls never had any indication of bronchiectasis and were frequency-matched to the 3 bronchiectasis groups on the basis of age, sex, and encounter year. There were 5,329 unique persons with bronchiectasis and 33,363 without bronchiectasis in the 3 analyses. Important co-occurring conditions were identified with diagnoses, medication orders, and encounter types. Logistic regression was used to evaluate associations (odds ratios [ORs] and 95% CIs) of CRS with bronchiectasis while adjusting for confounding variables.

RESULTS

In adjusted analyses, CRS was consistently and strongly associated with all 3 bronchiectasis definitions. The strongest associations for CRS (ORs and 95% CIs) were those that were based on the text of sinus computerized tomography scan reports; the associations were generally stronger for CRS without nasal polyps (eg, OR = 4.46 [95% CI = 2.09-9.51] for diagnosis-based bronchiectasis). On average, CRS was identified more than 6 years before bronchiectasis.

CONCLUSION

Precedent CRS was strongly and consistently associated with increased risk of bronchiectasis.

Urban-Rural Differences in Health Care Utilization and COVID-19 Outcomes in Patients With Type 2 Diabetes

Introduction

Two studies in Pennsylvania aimed to determine whether community type and community socioeconomic deprivation (CSD) 1) modified associations between type 2 diabetes (hereinafter, diabetes) and COVID-19 hospitalization outcomes, and 2) influenced health care utilization among individuals with diabetes during the COVID-19 pandemic.

Methods

The hospitalization study evaluated a retrospective cohort of patients hospitalized with COVID-19 through 2020 for COVID-19 outcomes: death, intensive care unit (ICU) admission, mechanical ventilation, elevated D-dimer, and elevated troponin level. We used adjusted logistic regression models, adding interaction terms to evaluate effect modification by community type (township, borough, or city census tract) and CSD. The utilization study included patients with diabetes and a clinical encounter between 2017 and 2020. Autoregressive integrated moving average time-series models evaluated changes in weekly rates of emergency department and outpatient visits, hemoglobin A_1c (HbA_1c) laboratory tests, and antihyperglycemic medication orders from 2018 to 2020.

Results

In the hospitalization study, of 2,751 patients hospitalized for COVID-19, 1,020 had diabetes, which was associated with ICU admission and elevated troponin. Associations did not differ by community type or CSD. In the utilization study, among 93,401 patients with diabetes, utilization measures decreased in March 2020. Utilization increased in July, and then began to stabilize or decline through the end of 2020. Changes in HbA_1c tests and medication order trends during the pandemic differed by community type and CSD.

Conclusion

Diabetes was associated with selected outcomes among individuals hospitalized for COVID-19, but these did not differ by community features. Utilization trajectories among individuals with diabetes during the pandemic were influenced by community type and CSD and could be used to identify individuals at risk of gaps in diabetes care.

Neighborhood Socioeconomic Environment and Risk of Type 2 Diabetes: Associations and Mediation Through Food Environment Pathways in Three Independent Study Samples

OBJECTIVE

We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: 1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); 2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and 3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of 1) fast-food restaurants and 2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural.

RESULTS

Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways.

CONCLUSIONS

Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways.

Relations of peri-residential temperature and humidity in tick-life-cycle-relevant time periods with human Lyme disease risk in Pennsylvania, USA

How weather affects tick development and behavior and human Lyme disease remains poorly understood. We evaluated relations of temperature and humidity during critical periods for the tick lifecycle with human Lyme disease. We used electronic health records from 479,344 primary care patients in 38 Pennsylvania counties in 2006-2014. Lyme disease cases (n = 9657) were frequency-matched (5:1) by year, age, and sex. Using daily weather data at ~4 km² resolution, we created cumulative metrics hypothesized to promote (warm and humid) or inhibit (hot and dry) tick development or host-seeking during nymph development (March 1-May 31), nymph activity (May 1-July 30), and prior year larva activity (Aug 1-Sept 30). We estimated odds ratios (ORs) of Lyme disease by quartiles of each weather variable, adjusting for demographic, clinical, and other weather variables. Exposure-response patterns were observed for higher cumulative same-year temperature, humidity, and hot and dry days (nymph-relevant), and prior year hot and dry days (larva-relevant), with same-year hot and dry days showing the strongest association (4th vs. 1st quartile OR = 0.40; 95% confidence interval [CI] = 0.36, 0.43). Changing temperature and humidity could increase or decrease human Lyme disease risk.

Association of community socioeconomic deprivation with evidence of reduced kidney function at time of type 2 diabetes diagnosis

BACKGROUND

While there are known individual-level risk factors for kidney disease at time of type 2 diabetes diagnosis, little is known regarding the role of community context. We evaluated the association of community socioeconomic deprivation (CSD) and community type with estimated glomerular filtration rate (eGFR) when type 2 diabetes is diagnosed.

METHODS

This was a retrospective cohort study of 13,144 adults with newly diagnosed type 2 diabetes in Pennsylvania. The outcome was the closest eGFR measurement within one year prior to and two weeks after type 2 diabetes diagnosis, calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi) equation. We used adjusted multinomial regression models to estimate associations of CSD (quartile 1, least deprivation) and community type (township, borough, city) with eGFR and used adjusted generalized estimating equation models to evaluate whether community features were associated with the absence of diabetes screening in the years prior to type 2 diabetes diagnosis.

RESULTS

Of the participants, 1279 (9.7%) had hyperfiltration and 1377 (10.5%) had reduced eGFR. Women were less likely to have hyperfiltration and more likely to have reduced eGFR. Black (versus White) race was positively associated with hyperfiltration when the eGFR calculation was corrected for race but inversely associated without the correction. Medical Assistance (ever versus never) was positively associated with reduced eGFR. Higher CSD and living in a city were each positively associated (odds ratio [95% confidence interval]) with reduced eGFR (CSD quartiles 3 and 4 versus quartile 1, 1.23 [1.04, 1.46], 1.32 [1.11, 1.58], respectively; city versus township, 1.38 [1.15, 1.65]). These features were also positively associated with the absence of a type 2 diabetes screening measure.

CONCLUSIONS

In a population-based sample, more than twenty percent had hyperfiltration or reduced eGFR at time of type 2 diabetes diagnosis. Individual- and community-level factors were associated with these outcomes.

Proximity to freshwater blue space and type 2 diabetes onset: the importance of historical and economic context

Salutogenic effects of living near aquatic areas (blue space) remain underexplored, particularly in non-coastal and non-urban areas. We evaluated associations of residential proximity to inland freshwater blue space with new onset type 2 diabetes (T2D) in central and northeast Pennsylvania, USA, using medical records to conduct a nested case-control study. T2D cases (n=15,888) were identified from diabetes diagnoses, medication orders, and laboratory test results and frequency-matched on age, sex, and encounter year to diabetes-free controls (n=79,435). We calculated distance from individual residences to the nearest lake, river, tributary, or large stream, and residence within the 100-year floodplain. Logistic regression models adjusted for community socioeconomic deprivation and other confounding variables and stratified by community type (townships [rural/suburban], boroughs [small towns], city census tracts). Compared to individuals living ≥1.25 miles from blue space, those within 0.25 miles had 8% and 17% higher odds of T2D onset in townships and boroughs, respectively. Among city residents, T2D odds were 38-39% higher for those living 0.25 to <0.75 miles from blue space. Residing within the floodplain was associated with 16% and 14% higher T2D odds in townships and boroughs. A post-hoc analysis demonstrated patterns of lower residential property values with nearer distance to the region's predominant waterbody, suggesting unmeasured confounding by socioeconomic disadvantage. This may explain our unexpected findings of higher T2D odds with closer proximity to blue space. Our findings highlight the importance of historic and economic context and interrelated factors such as flood risk and lack of waterfront development in blue space research.

Association of community types and features in a case-control analysis of new onset type 2 diabetes across a diverse geography in Pennsylvania

OBJECTIVES

To evaluate associations of community types and features with new onset type 2 diabetes in diverse communities. Understanding the location and scale of geographic disparities can lead to community-level interventions.

DESIGN

Nested case-control study within the open dynamic cohort of health system patients.

SETTING

Large, integrated health system in 37 counties in central and northeastern Pennsylvania, USA.

PARTICIPANTS AND ANALYSIS

We used electronic health records to identify persons with new-onset type 2 diabetes from 2008 to 2016 (n=15 888). Persons with diabetes were age, sex and year matched (1:5) to persons without diabetes (n=79 435). We used generalised estimating equations to control for individual-level confounding variables, accounting for clustering of persons within communities. Communities were defined as (1) townships, boroughs and city census tracts; (2) urbanised area (large metro), urban cluster (small cities and towns) and rural; (3) combination of the first two; and (4) county. Community socioeconomic deprivation and greenness were evaluated alone and in models stratified by community types.

RESULTS

Borough and city census tract residence (vs townships) were associated (OR (95% CI)) with higher odds of type 2 diabetes (1.10 (1.04 to 1.16) and 1.34 (1.25 to 1.44), respectively). Urbanised areas (vs rural) also had increased odds of type 2 diabetes (1.14 (1.08 to 1.21)). In the combined definition, the strongest associations (vs townships in rural areas) were city census tracts in urban clusters (1.41 (1.22 to 1.62)) and city census tracts in urbanised areas (1.33 (1.22 to 1.45)). Higher community socioeconomic deprivation and lower greenness were each associated with increased odds.

CONCLUSIONS

Urban residence was associated with higher odds of type 2 diabetes than for other areas. Higher community socioeconomic deprivation in city census tracts and lower greenness in all community types were also associated with type 2 diabetes.

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

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

Risk Factors and Outcomes of Treatment Delays in Lyme Disease: A Population-Based Retrospective Cohort Study

Background: Longer time between symptom onset and treatment of Lyme disease has been associated with poor outcomes. Reducing time-to-treatment requires knowledge of risks for treatment delays. We conducted a population-based study to evaluate factors associated with delayed treatment of Lyme disease and the relation between delayed treatment and post-treatment Lyme disease syndrome (PTLDS). Methods: We mailed questionnaires to 5,314 individuals with a Lyme disease diagnosis or blood test followed by an antibiotic order in the medical record of a Pennsylvania health system from 2015 to 2017. Analyses were confined to 778 respondents who reported that they were treated for Lyme disease within the past 5 years and reported a rash and/or a positive blood test for Lyme disease. Time-to-treatment was calculated as the sum of two windows before and after seeking care for Lyme disease symptoms: time to first medical contact and time under care. We used logistic regression to evaluate factors associated with delayed time-to-treatment in each time window (>14 days vs. ≤14 days) and the association between total time-to-treatment (>30 days vs. ≤30 days) and PTLDS. We used inverse probability weighting to calculate estimates for the study's source population (5,314 individuals sent questionnaires). Results: In the source population, 25% had time to first contact >14 days, 21% had time under care >14 days, and 31% had a total time-to-treatment >30 days. Being uninsured and attributing initial symptoms to something other than Lyme disease were positively associated with delayed time to first medical contact, while seeking care at an urgent care or emergency setting (vs. primary care) was negatively associated. Diagnoses between November and April, and the absence of rash were positively associated with delays. Individuals whose treatment was delayed, defined as time-to treatment >30 days had 2.26 (95% confidence interval: 1.25, 4.05) times the odds of PTLDS as those who were treated within 30 days of symptom onset. Conclusions: In a population-based study in Pennsylvania, one-third of Lyme disease patients reported delayed treatment, which was associated with PTLDS. To improve Lyme disease outcomes, prevention efforts should aim to reduce the time before and after seeking care.

The Diabetes Location, Environmental Attributes, and Disparities Network: Protocol for Nested Case Control and Cohort Studies, Rationale, and Baseline Characteristics

BACKGROUND

Diabetes prevalence and incidence vary by neighborhood socioeconomic environment (NSEE) and geographic region in the United States. Identifying modifiable community factors driving type 2 diabetes disparities is essential to inform policy interventions that reduce the risk of type 2 diabetes.

OBJECTIVE

This paper aims to describe the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, a group funded by the Centers for Disease Control and Prevention to apply harmonized epidemiologic approaches across unique and geographically expansive data to identify community factors that contribute to type 2 diabetes risk.

METHODS

The Diabetes LEAD Network is a collaboration of 3 study sites and a data coordinating center (Drexel University). The Geisinger and Johns Hopkins University study population includes 578,485 individuals receiving primary care at Geisinger, a health system serving a population representative of 37 counties in Pennsylvania. The New York University School of Medicine study population is a baseline cohort of 6,082,146 veterans who do not have diabetes and are receiving primary care through Veterans Affairs from every US county. The University of Alabama at Birmingham study population includes 11,199 participants who did not have diabetes at baseline from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a cohort study with oversampling of participants from the Stroke Belt region.

RESULTS

The Network has established a shared set of aims: evaluate mediation of the association of the NSEE with type 2 diabetes onset, evaluate effect modification of the association of NSEE with type 2 diabetes onset, assess the differential item functioning of community measures by geographic region and community type, and evaluate the impact of the spatial scale used to measure community factors. The Network has developed standardized approaches for measurement.

CONCLUSIONS

The Network will provide insight into the community factors driving geographical disparities in type 2 diabetes risk and disseminate findings to stakeholders, providing guidance on policies to ameliorate geographic disparities in type 2 diabetes in the United States.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/21377.

A new approach to categorization of radiologic inflammation in chronic rhinosinusitis

Chronic rhinosinusitis (CRS) is a prevalent condition. Clinical diagnosis requires subjective evidence (i.e. symptoms) and objective evidence of inflammation (e.g. sinus computed tomography [CT]). Few studies have assessed differences in common CT scoring approaches for CRS, the Lund-Mackay (LM) system and its modified version (mLM); none in a general population sample. The aims of this study were to answer the following: (1) Is mLM superior to LM? (2) Should nasal cavity opacification be included in scoring? (3) How should location-specific scores be utilized? (4) If location-specific scores are summed, what should be the cutoff? (5) Are associations of opacification with symptoms observed when using different measurement approaches? We scored sinus CTs using LM and mLM from 526 subjects selected from a larger CRS study. Exploratory factor analysis (EFA) assessed similarity of mLM and LM. Latent class analysis (LCA) identified subgroups of sinus opacification patterns. Factors associated with group membership and relations with nasal and sinus symptoms (NSS) guided clinical relevance. EFA suggested no differences between LM and mLM, or after addition of nasal cavity opacification. LCA identified three opacification groups: no/mild, localized, and diffuse. Males were 2.7x more likely to have diffuse opacification than females, as were those with asthma or hay fever. A LM cutoff of 3 had similar performance to the currently used 4. Diffuse opacification was associated with nasal blockage and smell loss. Differing patterns of opacification may be clinically relevant, improving measurement of objective evidence in studies of CRS and sinus diseases.

Radiologic sinus inflammation and symptoms of chronic rhinosinusitis in a population-based sample

BACKGROUND

Chronic rhinosinusitis (CRS) epidemiology has been largely studied using symptom-based case definitions, without assessment of objective sinus findings.

OBJECTIVE

To describe radiologic sinus opacification and the prevalence of CRS, defined by the co-occurrence of symptoms and sinus opacification, in a general population-based sample.

METHODS

We collected questionnaires and sinus CT scans from 646 participants selected from a source population of 200 769 primary care patients. Symptom status (CRS_S ) was based on guideline criteria, and objective radiologic inflammation (CRS_O ) was based on the Lund-Mackay (L-M) score using multiple L-M thresholds for positivity. Participants with symptoms and radiologic inflammation were classified as CRS_S+O . We performed negative binomial regression to assess factors associated with L-M score and logistic regression to evaluate factors associated with CRS_S+O . Using weighted analysis, we calculated estimates for the source population.

RESULTS

The proportion of women with L-M scores ≥ 3, 4, or 6 (CRS_O ) was 11.1%, 9.9%, and 5.7%, respectively, and 16.1%, 14.6%, and 8.7% among men. The respective proportion with CRS_S+O was 1.7%, 1.6%, and 0.45% among women and 8.8%, 7.5%, and 3.6% among men. Men had higher odds of CRS_S+O compared to women. A greater proportion of men (vs women) had any opacification in the frontal, anterior ethmoid, and sphenoid sinuses.

CONCLUSION

In a general population-based sample in Pennsylvania, sinus opacification was more common among men than in women and opacification occurred in different locations by sex. Male sex, migraine headache, and prior sinus surgery were associated with higher odds of CRS_S+O .

Assessing county-level determinants of diabetes in the United States (2003-2012)

Using data from the United States Behavioral Risk Factor Surveillance System (2003-2012; N = 3,397,124 adults), we estimated associations between prevalent diabetes and four county-level exposures (fast food restaurant density, convenience store density, unemployment, active commuting). All associations confirmed our a priori hypotheses in conventional multilevel analyses that pooled across years. In contrast, using a random-effects within-between model, we found weak, ambiguous evidence that within-county changes in exposures were associated with within-county change in odds of diabetes. Decomposition revealed that the pooled associations were largely driven by time-invariant, between-county factors that may be more susceptible to confounding versus within-county associations.

Peridomestic and community-wide landscape risk factors for Lyme disease across a range of community contexts in Pennsylvania

Land use and forest fragmentation are thought to be major drivers of Lyme disease incidence and its geographic distribution. We examined the association between landscape composition and configuration and Lyme disease in a population-based case control study in the Geisinger health system in Pennsylvania. Lyme disease cases (n = 9657) were identified using a combination of diagnosis codes, laboratory codes, and antibiotic orders from electronic health records (EHRs). Controls (5:1) were randomly selected and frequency matched on year, age, and sex. We measured six landscape variables based on prior literature, derived from the National Land Cover Database and MODIS satellite imagery: greenness (normalized difference vegetation index), percent forest, percent herbaceous, forest edge density, percent forest-herbaceous edge, and mean forest patch size. We assigned landscape variables within two spatial contexts (community and ½-mile [805 m] Euclidian residential buffer). In models stratified by community type, landscape variables were modeled as tertiles and flexible splines and associations were adjusted for demographic and clinical covariates. In general, we observed positive associations between landscape metrics and Lyme disease, except for percent herbaceous, where associations differed by community type. For example, compared to the lowest tertile, individuals with highest tertile of greenness in residential buffers had higher odds of Lyme disease (odds ratio: 95% confidence interval [CI]) in townships (1.73: 1.55, 1.93), boroughs (1.70: 1.40, 2.07), and cities (3.71: 1.74, 7.92). Similarly, corresponding odds ratios (95% CI) for forest edge density were 1.34 (1.22, 1.47), 1.56 (1.33, 1.82), and 1.90 (1.13, 3.18). Associations were generally higher in residential buffers, compared to community, and in cities, compared to boroughs or townships. Our results reinforce the importance of peridomestic landscape in Lyme disease risk, particularly measures that reflect human interaction with tick habitat. Linkage of EHR data to public data on residential and community context may lead to new health system-based approaches for improving Lyme disease diagnosis, treatment, and prevention.

Associations of multidimensional socioeconomic and built environment factors with body mass index trajectories among youth in geographically heterogeneous communities

Understanding contextual influences on obesity requires comparison of heterogeneous communities and concurrent assessment of multiple contextual domains. We used a theoretically-based measurement model to assess multidimensional socioeconomic and built environment factors theorized to influence childhood obesity across a diverse geography ranging from rural to urban. Confirmatory factor analysis specified four factors—community socioeconomic deprivation (CSED), food outlet abundance (FOOD), fitness and recreational assets (FIT), and utilitarian physical activity favorability (UTIL)—which were assigned to communities (townships, boroughs, city census tracts) in 37 Pennsylvania counties. Using electronic health records from 2001 to 2012 from 163,820 youth aged 3–18 years from 1288 communities, we conducted multilevel linear regression analyses with factor quartiles and their cross products with age, age², and age³ to test whether community factors impacted body mass index (BMI) growth trajectories. Models controlled for sex, age, race/ethnicity, and Medical Assistance. Factor scores were lowest in townships, indicating less deprivation, fewer food and physical activity outlets, and lower utilitarian physical activity favorability. BMI at average age was lower in townships versus boroughs (beta [SE]) (0.217 [0.027], P < 0.001) and cities (0.378 [0.036], P < 0.001), as was BMI growth over time. Factor distributions across community types lacked overlap, requiring stratified analyses to avoid extrapolation. In townships, FOOD, UTIL, and FIT were inversely associated with BMI trajectories. Across community types, youth in the lowest (versus higher) CSED quartiles had lower BMI at average age and slower BMI growth, signifying the importance of community deprivation to the obesogenicity of environments.

•

Diverse geographies must be compared to understand contextual influences on obesity.

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Youth body mass index trajectories differed by community type in Pennsylvania.

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Food and physical activity environments were related to trajectories in townships.

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Socioeconomic deprivation was associated with trajectories in all community types.

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Community socioeconomic deprivation appears central to obesogenic environments.

Household Food Insecurity and Home Food Availability in Relation to Youth Diet, Body Mass Index, and Adiposity

BACKGROUND

Food security status is related to food types available in the home, which may shape youth dietary patterns, with implications for obesity.

OBJECTIVE

Investigate whether household food insecurity and home food availability (HFA) are associated with youth fruit and vegetable (F/V) consumption and anthropometric outcomes.

DESIGN

Cross-sectional study. Youth and parents completed questionnaires during in-home visits (2013-2014). Research staff obtained anthropometric measures.

PARTICIPANTS/SETTING

Medical record data for 10- to 15-year-old Pennsylvania youths were used to identify 434 parent-youth dyads, with 408 evaluated after excluding missing data.

MAIN OUTCOME MEASURES

Parent-reported household food security was assessed with the six-item US Department of Agriculture Food Security Scale (dichotomized as high vs low). Healthy and obesogenic HFA scales assessed parent report of how frequently particular foods were present in the home. Youth self-reported daily average F/V consumption. Anthropometric outcomes included age- and sex-standardized z scores for body mass index (BMIz), waist circumference (WCz), and percent body fat (PBFz).

STATISTICAL ANALYSES

Associations were evaluated with multivariable linear regression adjusted for youth age, sex, and race or ethnicity, and parent age and income.

RESULTS

Compared with food secure counterparts, youth from food insecure households had higher mean (beta [standard error]) BMIz (.30 [.15]), WCz (.27 [.12]), and PBFz (.43 [.16]). Food insecure households had lower mean healthy HFA scores (-1.23 [.54]); there was no evidence obesogenic HFA differed between food secure and insecure households. Youth from lower healthy HFA or higher obesogenic HFA households reported fewer mean daily F/V servings (healthy HFA: .08 [.02]; obesogenic HFA: -.06 [.02]). Food security status was not associated with F/V consumption, nor was there evidence HFA modified associations between food insecurity and anthropometric outcomes.

CONCLUSIONS

Despite an observed association between healthy HFA and youth F/V consumption, this study did not provide evidence that HFA explained associations between food insecurity and youth anthropometric outcomes.

Associations of unconventional natural gas development with depression symptoms and disordered sleep in Pennsylvania

Environmental and community factors may influence the development or course of depression and sleep problems. We evaluated the association of unconventional natural gas development (UNGD) with depression symptoms and disordered sleep diagnoses using the Patient Health Questionnaire-8 and electronic health record data among Geisinger adult primary care patients in Pennsylvania. Participants received a retrospective metric for UNGD at their residence (very low, low, medium, and high) that incorporated dates and durations of well development, distance from patient homes to wells, and well characteristics. Analyses included 4,762 participants with no (62%), mild (23%), moderate (10%), and moderately severe or severe (5%) depression symptoms in 2014-2015 and 3,868 disordered sleep diagnoses between 2009-2015. We observed associations between living closer to more and bigger wells and depression symptoms, but not disordered sleep diagnoses in models weighted to account for sampling design and participation. High UNGD (vs. very low) was associated with depression symptoms in an adjusted negative binomial model (exponentiated coefficient = 1.18, 95% confidence interval [CI]: 1.04-1.34). High and low UNGD (vs. very low) were associated with depression symptoms (vs. none) in an adjusted multinomial logistic model. Our findings suggest that UNGD may be associated with adverse mental health in Pennsylvania.

Obstacles to diagnosis and treatment of Lyme disease in the USA: a qualitative study

OBJECTIVE

For many individuals with Lyme disease, prompt treatment leads to rapid resolution of infection. However, severe complications can occur if treatment is delayed. Our objective was to identify themes around belated diagnosis or treatment of Lyme disease using the General Model of Total Patient Delay (GMTPD).

DESIGN

We conducted a qualitative interview study using indepth telephone interviews.

SETTING

Participants were patients from a large, integrated health system in the state of Pennsylvania, USA.

PARTICIPANTS

There were 26 participants. Participants had to have a diagnosis of Lyme disease between 2014 and 2017 and a positive IgG western blot. We used a stratified purposeful sampling design to identify patients with and without late Lyme disease manifestations. To ensure variation in care experiences, we oversampled patients diagnosed outside of primary care.

OUTCOME MEASURES

We asked participants about their experience from first Lyme disease symptoms to treatment. We applied an iterative coding process to identify key themes and then synthesised codes into higher order codes representing the GMTPD stages: appraisal delay (symptom to recognition of illness); illness delay (inferring illness to deciding to seek help); behavioural delay (deciding to seek help to the act of seeking help); scheduling delay (seeking help to attending an appointment); and treatment delay (attending appointment to treatment).

RESULTS

Appraisal delay themes included symptom misattribution, intermittent symptoms and misperceptions about the necessity of a bull's-eye rash. Health insurance status was a driver of illness and behavioural delays. Scheduling delay was not noted by participants, in part, because 10 of the 26 patients went to urgent care or emergency department settings. Misdiagnoses were more common in these settings, contributing to treatment delay.

CONCLUSION

Our study identified potentially modifiable risk factors for belated treatment. Targeting these risk factors may minimise time to treatment and reduce the occurrence of preventable complications.

Prevalence, severity, and risk factors for acute exacerbations of nasal and sinus symptoms by chronic rhinosinusitis status

BACKGROUND

Nasal and sinus symptoms (NSS) are common to many health conditions, including chronic rhinosinusitis (CRS). Few studies have investigated the occurrence and severity of, and risk factors for, acute exacerbations of NSS (AENSS) by CRS status (current, past, or never met European Position Paper on Rhinosinusitis [EPOS] criteria for CRS).

METHODS

Four seasonal questionnaires were mailed to a stratified random sample of Geisinger primary care patients. Logistic regression was used to identify individual characteristics associated with AENSS occurrence and severity by CRS status (current long-term, current recent, past, never) using EPOS subjective symptoms-only (EPOSS ) CRS criteria. We operationalized 3 AENSS definitions based on prescribed antibiotics or oral corticosteroids, symptoms, and symptoms with purulence.

RESULTS

Baseline and at least 1 follow-up questionnaires were available from 4736 subjects. Self-reported NSS severity with exacerbation was worst in the current long-term CRS group. AENSS was common in all subgroups examined and generally more common among those with current EPOSS CRS. Seasonal prevalence of AENSS differed by AENSS definition and CRS status. Associations of risk factors with AENSS differed by definition, but CRS status, body mass index, asthma, hay fever, sinus surgery history, and winter season consistently predicted AENSS.

CONCLUSIONS

In this first longitudinal, population-based study of 3 AENSS definitions, NSS and AENSS were both common, sometimes severe, and differed by EPOSS CRS status. Contrasting associations of risk factors for AENSS by the different definitions suggest a need for a standardized approach to definition of AENSS.

Performance of the DiaRem Score for Predicting Diabetes Remission in Two Health Systems Following Bariatric Surgery Procedures in Hispanic and non-Hispanic White Patients

OBJECTIVE

The objective of this study was to determine whether the DiaRem, a score that predicts type 2 diabetes (T2D) remission following roux-en-y gastric bariatric surgery (RYGB), also predicts remission following laparoscopic adjustable gastric banding (LAGB) and laparoscopic sleeve gastrectomy (LSG) in white and Hispanic patients.

BACKGROUND

While bariatric surgery is highly effective in reversing insulin resistance, there are patients for whom surgery will not lead to remission. To date, there is no score for predicting remission following LAGB or LSG surgery. Additionally, there is little known about how to predict whether Hispanic patients will experience remission.

METHODS

We conducted a retrospective cohort study of white and Hispanic patients with T2D who received bariatric surgery. There were 361 white and 130 Hispanic patients among whom 328 had RYGB surgery, 107 had LSG surgery, and 56 had LAGB surgery. We used age, diabetes treatment, and hemoglobin A1c to calculate DiaRem scores. Mann-Whitney U test was used to determine the association between DiaRem scores and remission. Area under the receiver operant curve (AUC) was used to assess the ability of the DiaRem to discriminate between patients who did and did not remit.

RESULTS

The DiaRem was associated with partial remission in all surgery types for white and Hispanic patients (Mann-Whitney, p < 0.001). The DiaRem had moderate to high discriminant ability (AUC > 0.70) for all surgical and racial/ethnic groups.

CONCLUSIONS

The DiaRem distinguishes between patients likely and unlikely to experience remission, informing expectations of patients making T2D treatment decisions.

Measures of SES for Electronic Health Record-based Research

INTRODUCTION

Although infrequently recorded in electronic health records (EHRs), measures of SES are essential to describe health inequalities and account for confounding in epidemiologic research. Medical Assistance (i.e., Medicaid) is often used as a surrogate for SES, but correspondence between conventional SES and Medical Assistance has been insufficiently studied.

METHODS

Geisinger Clinic EHR data from 2001 to 2014 and a 2014 questionnaire were used to create six SES measures: EHR-derived Medical Assistance and proportion of time under observation on Medical Assistance; educational attainment, income, and marital status; and area-level poverty. Analyzed in 2016-2017, associations of SES measures with obesity, hypertension, type 2 diabetes, chronic rhinosinusitis, fatigue, and migraine headache were assessed using weighted age- and sex-adjusted logistic regression.

RESULTS

Among 5,550 participants (interquartile range, 39.6-57.5 years, 65.9% female), 83% never used Medical Assistance. All SES measures were correlated (Spearman's p≤0.4). Medical Assistance was significantly associated with all six health outcomes in adjusted models. For example, the OR for prevalent type 2 diabetes associated with Medical Assistance was 1.7 (95% CI=1.3, 2.2); the OR for high school versus college graduates was 1.7 (95% CI=1.2, 2.5). Medical Assistance was an imperfect proxy for SES: associations between conventional SES measures and health were attenuated <20% after adjustment for Medical Assistance.

CONCLUSIONS

Because systematically collected SES measures are rarely available in EHRs and are unlikely to appear soon, researchers can use EHR-based Medical Assistance to describe inequalities. As SES has many domains, researchers who use Medical Assistance to evaluate the association of SES with health should expect substantial unmeasured confounding.

Associations of Four Community Factors With Longitudinal Change in Hemoglobin A1c Levels in Patients With Type 2 Diabetes

OBJECTIVE

To evaluate associations of community factors with glycated hemoglobin (HbA_1c).

RESEARCH DESIGN AND METHODS

We identified patients with type 2 diabetes who had an HbA_1c ≥7.5% (58 mmol/mol) and subsequent HbA_1c testing within 90-270 days. We used mixed-effect models to assess whether treatment intensification (TI) and community domains (community socioeconomic deprivation [CSD], food availability, fitness assets, and utilitarian physical activity favorability [quartiled]) were associated with HbA_1c change over 6 and 24 months, controlling for demographics, HbA_1c, BMI, and time with evidence of type 2 diabetes. We evaluated whether community domains modified associations of TI with HbA_1c change using cross product terms.

RESULTS

There were 15,308 patients with 69,818 elevated HbA_1c measures. The average reduction in HbA_1c over 6 months was 0.07% less in townships with a high level of CSD (third quartile versus the first). Reductions were 0.10% greater for HbA_1c in townships with the best food availability (versus worst). HbA_1c reductions were 0.17-0.19% greater in census tracts in the second and third quartiles of utilitarian physical activity favorability versus the first. The association of TI with 6-month HbA_1c change was weaker in townships and boroughs with the worst CSD (versus best) and in boroughs with the best fitness assets (versus worst). The association of TI with 24-month HbA_1c change was weaker in census tracts with the worst CSD (versus third quartile) and strongest in census tracts most favorable for utilitarian physical activity (versus worst).

CONCLUSIONS

Community domains were associated with HbA_1c change and blunted TI effectiveness.

Bariatric Surgery Patients and Their Families: Health, Physical Activity, and Social Support

BACKGROUND

This study evaluated the social environment of bariatric surgery patients in the preoperative period.

METHODS

Forty bariatric surgery patients (mean = 46.2 ± 11.2 years), 35 adult cohabitating family members (mean = 45.2 ± 12.7 years), and 15 cohabitating children (mean = 11.5 ± 3.6 years) were recruited from a large rural medical center. Adult participants (patients and family members) completed height, weight, body composition, blood draws, and physical activity assessments (accelerometry), as well as eating behavior and social support inventories before the patient underwent bariatric surgery. Child participants completed demographic, height, and weight assessment only.

RESULTS

Over 90 % of adult family members were overweight or obese (body mass index (BMI) ≥ 25 kg/m², as were 50 % of children (BMI percentile ≥ 85 %). More than one third (37.1 %) of family members met the criteria for moderate to severe insulin resistance. Physical activity measured by accelerometry was moderately correlated between the patient and adult family members (r = 0.46, p = 0.023). Bariatric surgery patients reported high levels of social support from their family members on multiple social support measures.

CONCLUSIONS

Many family members of bariatric surgery patients also lived with obesity and related comorbidities, and demonstrate high sedentary behavior. However, patients reported high levels of support from family members, including support in following a healthy diet and engaging in physical activity. Engaging families in behavior change may help bariatric surgery patients and their families to become healthier.

Comparing objective measures of the built environment in their associations with youth physical activity and sedentary behavior across heterogeneous geographies

We compared two strategies for measuring built environment features in their associations with youth physical activity and sedentary behavior across heterogeneous geographies of Pennsylvania. Physical activity environments of communities representing a rural-to-urban gradient were characterized through direct observation and spatially referenced archival data subjected to confirmatory factor analysis. Stratified regression analyses assessed associations between environmental measures and behavioral outcomes by community type. Neither strategy was consistently associated with behavior across communities. Findings highlight the importance of differentiating community type in evaluating associations of the built environment, and the challenge of measuring meaningful differences that influence youth behavior across heterogeneous geographies.

Longitudinal Evaluation of Chronic Rhinosinusitis Symptoms in a Population-Based Sample

BACKGROUND

Chronic rhinosinusitis (CRS) is a prevalent and disabling condition of the nose and sinuses. The natural history of CRS symptoms in a general population sample has not been previously studied.

OBJECTIVE

In a general population-based sample from Pennsylvania, we used 2 questionnaires mailed 6 months apart to estimate the prevalence of, and identify predictors for, stability or change in symptoms over time.

METHODS

We mailed the baseline and 6-month follow-up questionnaires to 23,700 primary care patients and 7,801 baseline responders, respectively. We categorized nasal and sinus symptoms using European Position Paper on Rhinosinusitis (EPOS) epidemiologic criteria. We defined 6 symptom groups over time on the basis of the presence of CRS symptoms at baseline and follow-up. We performed multivariable survey logistic regression controlling for confounding variables comparing persistent versus nonpersistent, recurrent versus stable past, and incident versus never.

RESULTS

There were 4,966 responders at follow-up: 558 had persistent symptoms, 190 recurrent symptoms, and 83 new symptoms meeting EPOS criteria for CRS. The prevalence of persistent symptoms was 4.8% (95% CI, 3.8-5.8), whereas the annual cumulative incidence of new symptoms was 1.9% and of recurrent symptoms was 3.2%. More severe symptoms at baseline were associated with persistence, whereas minor symptoms, allergies, and multiple treatments were associated with the development of new symptoms.

CONCLUSIONS

Less than half with nasal and sinus symptoms meeting CRS EPOS criteria in our general, regional population had symptom persistence over time, with symptom profiles at baseline and age of onset being strongly associated with stability of symptoms.

All-Cause and Specific-Cause Mortality Risk After Roux-en-Y Gastric Bypass in Patients With and Without Diabetes

OBJECTIVE

This study assessed all-cause and specific-cause mortality after Roux-en-Y gastric bypass (RYGB) and in matched control subjects, stratified by diabetes status.

RESEARCH DESIGN AND METHODS

RYGB patients were matched by age, BMI, sex, and diabetes status at time of surgery to nonsurgical control subjects using data from the electronic health record. Kaplan-Meier curves and Cox regression were used to assess differences in all-cause and specific-cause mortality between RYGB patients and control subjects with and without diabetes.

RESULTS

Of the 3,242 eligible RYGB patients enrolled from January 2004 to December 2015, control subjects were identified for 2,428 (n = 625 with diabetes and n = 1,803 without diabetes). Median postoperative follow-up was 5.8 years for patients with diabetes and 6.7 years for patients without diabetes. All-cause mortality was reduced in RYGB patients compared with control subjects only for those with diabetes at the time of surgery (adjusted hazard ratio 0.44; P < 0.0001). Mortality was not significantly improved in RYGB patients without diabetes compared with control subjects without diabetes (adjusted hazard ratio 0.84; P = 0.37). Deaths from cardiovascular diseases (P = 0.011), respiratory conditions (P = 0.017), and diabetes P = 0.011) were more frequent in control subjects with diabetes than in RYGB patients with diabetes. RYGB patients without diabetes were less likely to die of cancer (P = 0.0038) and respiratory diseases (P = 0.046) than control subjects without diabetes but were at higher risk of death from external causes (P = 0.012), including intentional self-harm (P = 0.025), than control subjects without diabetes.

CONCLUSIONS

All-cause mortality benefits of RYGB are driven predominantly by patients with diabetes at the time of surgery. RYGB patients with diabetes were less likely to die of cardiovascular diseases, diabetes, and respiratory conditions than their counterparts without RYGB.

Gastric Bypass Surgery Produces a Durable Reduction in Cardiovascular Disease Risk Factors and Reduces the Long-Term Risks of Congestive Heart Failure

Background

Obesity and its association with reduced life expectancy are well established, with cardiovascular disease as one of the major causes of fatality. Metabolic surgery is a powerful intervention for severe obesity, resulting in improvement in comorbid diseases and in cardiovascular risk factors. This study investigates the relationship between metabolic surgery and long‐term cardiovascular events.

Methods and Results

A cohort of Roux‐en‐Y gastric bypass surgery (RYGB) patients was tightly matched by age, body mass index, sex, Framingham Risk Score, smoking history, use of antihypertension medication, diabetes mellitus status, and calendar year with a concurrent cohort of nonoperated control patients. The primary study end points of major cardiovascular events (myocardial infarction, stroke, and congestive heart failure) were evaluated using Cox regression. Secondary end points of longitudinal cardiovascular risk factors were evaluated using repeated‐measures regression. The RYGB and matched controls (N=1724 in each cohort) were followed for up to 12 years after surgery (overall median of 6.3 years). Kaplan–Meier analysis revealed a statistically significant reduction in incident major composite cardiovascular events (P=0.017) and congestive heart failure (0.0077) for the RYGB cohort. Adjusted Cox regression models confirmed the reductions in severe composite cardiovascular events in the RYGB cohort (hazard ratio=0.58, 95% CI=0.42–0.82). Improvements of cardiovascular risk factors (eg, 10‐year cardiovascular risk score, total cholesterol, high‐density lipoprotein, systolic blood pressure, and diabetes mellitus) were observed within the RYGB cohort after surgery.

Conclusions

Gastric bypass is associated with a reduced risk of major cardiovascular events and the development of congestive heart failure.

The electronic health record audit file: the patient is waiting

Objective: We describe how electronic health record (EHR) audit files can be used to understand how time is spent in primary care (PC).

Materials/methods: We used audit file data from the Geisinger Clinic to quantify elements of the clinical workflow and to determine how these times vary by patient and encounter factors. We randomly selected audit file records representing 36 437 PC encounters across 26 clinic locations. Audit file data were used to estimate duration and variance of: (1) time in the waiting room, (2) nurse time with the patient, (3) time in the exam room without a nurse or physician, and (4) physician time with the patient. Multivariate modeling was used to test for differences by patient and by encounter features.

Results: On average, a PC encounter took 54.6 minutes, with 5 minutes of nurse time, 15.5 minutes of physician time, and the remaining 62% of the time spent waiting to see a clinician or check out. Older age, female sex, and chronic disease were associated with longer wait times and longer time with clinicians. Level of service and numbers of medications, procedures, and lab orders were associated with longer time with clinicians. Late check-in and same-day visits were associated with shorter wait time and clinician time.

Conclusions: This study provides insights on uses of audit file data for workflow analysis during PC encounters.

Discussion: Scalable ways to quantify clinical encounter workflow elements may provide the means to develop more efficient approaches to care and improve the patient experience.

The electronic health record audit file: the patient is waiting

OBJECTIVE

We describe how electronic health record (EHR) audit files can be used to understand how time is spent in primary care (PC).

MATERIALS/METHODS

We used audit file data from the Geisinger Clinic to quantify elements of the clinical workflow and to determine how these times vary by patient and encounter factors. We randomly selected audit file records representing 36 437 PC encounters across 26 clinic locations. Audit file data were used to estimate duration and variance of: (1) time in the waiting room, (2) nurse time with the patient, (3) time in the exam room without a nurse or physician, and (4) physician time with the patient. Multivariate modeling was used to test for differences by patient and by encounter features.

RESULTS

On average, a PC encounter took 54.6 minutes, with 5 minutes of nurse time, 15.5 minutes of physician time, and the remaining 62% of the time spent waiting to see a clinician or check out. Older age, female sex, and chronic disease were associated with longer wait times and longer time with clinicians. Level of service and numbers of medications, procedures, and lab orders were associated with longer time with clinicians. Late check-in and same-day visits were associated with shorter wait time and clinician time.

CONCLUSIONS

This study provides insights on uses of audit file data for workflow analysis during PC encounters.

DISCUSSION

Scalable ways to quantify clinical encounter workflow elements may provide the means to develop more efficient approaches to care and improve the patient experience.

Community Audit of Social, Civil, and Activity Domains in Diverse Environments (CASCADDE)

There are currently no direct observation environmental audit tools that measure diverse aspects of the obesity-related environment efficiently and reliably in a variety of geographic settings. The goal was to develop a new instrument to reliably characterize the overall properties and features of rural, suburban, and urban settings along multiple dimensions. The Community Audit of Social, Civil, and Activity Domains in Diverse Environments (CASCADDE) is an iPad-based instrument that incorporates GPS coordinates and photography and comprises 214 items yielding seven summary indices. A comprehensive spatial sampling strategy, training manual, and supporting data analysis code were also developed. Random geospatial sampling using GIS was used to capture features of the community as a whole. A single auditor collected 510 observation points in 30 communities (2013-2015). This analysis was done in 2015-2016. Correlation coefficients were used to compare items and indices to each other and to standard measures. Multilevel unconditional means models were used to calculate intraclass correlation coefficients to determine if there was significant variation between communities. Results suggest that CASCADDE measures aspects of communities not previously captured by secondary data sources. Additionally, seven summary indices capture meaningful differences between communities based on 15 observations per community. Community audit tools such as CASCADDE complement secondary data sources and have the potential to offer new insights about the mechanisms through which communities affect obesity and other health outcomes.

Associations of LEP, CRH, ICAM-1, and LINE-1 methylation, measured in saliva, with waist circumference, body mass index, and percent body fat in mid-childhood

BACKGROUND

Genetics explains a small proportion of variance in body mass index at the population level. Epigenetics, commonly measured by gene methylation, holds promise for understanding obesity risk factors and mechanisms.

METHODS

Participants were 431 adolescents aged 10-15 years. BMI z-score, waist circumference z-score, and percent body fat were measured. Saliva samples were collected and methylation of promoter regions of four candidate genes or sequences (LEP, ICAM-1, CRH, and LINE-1) were measured in 3-4 CpG sites each. Linear regression was used to identify associations of methylation with obesity-related outcomes.

RESULTS

After adjusting for age, in sex-stratified analysis, the three obesity-related outcomes were negatively associated with LEP methylation in obese boys only. There were no associations of methylation of the other genes or sequences and the obesity-related outcomes.

CONCLUSIONS

Our results are consistent with prior studies that reported sex differences in associations of obesity-related outcomes with LEP methylation, and also as would be expected in adipose tissue, the source of circulating leptin. The findings suggest that saliva might be an acceptable tissue for epigenetics studies in adolescents.

Clinical Characteristics of Patients with Chronic Rhinosinusitis with Nasal Polyps, Asthma, and Aspirin-Exacerbated Respiratory Disease

BACKGROUND

Aspirin-exacerbated respiratory disease (AERD) comprises the triad of chronic rhinosinusitis with nasal polyps (CRSwNP), asthma, and intolerance to inhibitors of the cyclooxygenase-1 (COX-1) enzyme. The prevalence of AERD remains unclear, and few studies have compared the clinical characteristics of patients with AERD to those with CRSwNP alone, asthma alone, or both CRSwNP and asthma.

OBJECTIVE

To determine the prevalence of AERD within a tertiary care setting, and to identify unique clinical features that could distinguish these patients from those with both CRSwNP and asthma or with CRSwNP alone.

METHODS

Electronic medical records of patients at Northwestern in Chicago, Illinois, were searched by computer algorithm and then manual chart review to identify 459 patients with CRSwNP alone, 412 with both CRSwNP and asthma, 171 with AERD, and 300 with asthma only. Demographic and clinical features including sex, atopy, and sinus disease severity were characterized.

RESULTS

The prevalence of AERD among patients with CRSwNP was 16%. Patients with AERD had undergone 2-fold more sinus surgeries (P < .001) and were significantly younger at the time of their first surgery (40 ± 13 years) than were patients with CRSwNP (43 ± 14 years; P < .05). Atopy was significantly more prevalent in patients with AERD (84%) or asthma (85%) than in patients with CRSwNP (66%, P < .05). More patients with AERD (13%) had corticosteroid-dependent disease than patients with both CRSwNP and asthma (4%, P < .01) or asthma (1%, P < .001).

CONCLUSIONS

AERD is common among patients with CRSwNP; even though patients with AERD have CRSwNP and asthma, the clinical course of their disease is not the same as of patients who have CRSwNP and asthma but are tolerant to COX-1 inhibitors.

Home Food Rules in Relation to Youth Eating Behaviors, Body Mass Index, Waist Circumference, and Percent Body Fat

PURPOSE

To investigate agreement and associations between parent and youth acknowledgment of home food rules, youth eating behaviors, and measures of body composition and excess weight.

METHODS

Parent-youth dyads (N = 413) completed the "rules for eating at home" scale (Active Where Survey) and reported dietary intake. Trained research staff obtained anthropometric data. Linear regression analyses separately evaluated relationships between youth and parent acknowledgment of rules and youth-reported eating behaviors and anthropometric outcomes. Food rules were evaluated as a 12-item scale and individually.

RESULTS

Score on the food rule scale was positively associated with fruit and vegetable servings by youth acknowledgment only (β = .09, p = .006), and not with anthropometric outcomes. The rule "no desserts except fruit" was positively associated with fruit and vegetable servings by youth (β = .72, p = .002) and parent (β = .53, p = .03) acknowledgment. The rules "no second helpings at meals" and "limited fast food" were positively associated with body mass index z-score by youth (β = .38, p = .002; β = .32, p = .02, respectively) and parent (β = .74, p < .001; β = .41, p = .006, respectively) acknowledgment, with similar results for waist circumference z-score and percent body fat.

CONCLUSIONS

Inverse associations between specific food rules and healthful eating behaviors but positive associations with anthropometric outcomes suggest potentially bidirectional relationships between food rule implementation and youth weight. Future studies should disentangle how food rules guide youth behavior in the context of youth weight status.

Associations of prenatal and childhood antibiotic use with child body mass index at age 3 years

OBJECTIVE

Early-life antibiotic exposure, whether through prenatal or childhood antibiotic use, may contribute to increased child body mass. Associations of prenatal and childhood antibiotic use with body mass index z-score (BMIz) were evaluated at age 3 years.

METHODS

Electronic health records were utilized from 8,793 mothers and singleton children delivered at Geisinger Clinic in Pennsylvania between 2006 and 2012. Antibiotic orders were ascertained for mothers during pregnancy and for children through their age-3 BMI measurement. Linear mixed-effects regression models evaluated associations of prenatal and childhood antibiotic use with child BMIz.

RESULTS

Prenatal antibiotic orders were not associated with child BMIz. Children in the three largest categories of lifetime antibiotic orders had higher BMIz compared with children with no orders; associations persisted when controlling for prenatal antibiotics (β [95% confidence interval]) (4-5 child orders: 0.090 [0.011 to 0.170]; 6 to 8: 0.113 [0.029 to 0.197]; ≥9: 0.175 [0.088 to 0.263]; trend P value <0.001). Two or more first-year orders were also associated with BMIz (1: 0.021 [-0.038 to 0.081]; 2: 0.088 [0.017 to 0.160]; ≥3: 0.104 [0.038 to 0.170]; trend P value < 0.001).

CONCLUSIONS

Associations of early-life and lifetime childhood antibiotic use with increased child BMI highlight antibiotic exposure as a modifiable factor for reducing population-level excess weight.

Associations between Unconventional Natural Gas Development and Nasal and Sinus, Migraine Headache, and Fatigue Symptoms in Pennsylvania

BACKGROUND

Unconventional natural gas development (UNGD) produces environmental contaminants and psychosocial stressors. Despite these concerns, few studies have evaluated the health effects of UNGD.

OBJECTIVES

We investigated associations between UNGD activity and symptoms in a cross-sectional study in Pennsylvania.

METHODS

We mailed a self-administered questionnaire to 23,700 adult patients of the Geisinger Clinic. Using standardized and validated questionnaire items, we identified respondents with chronic rhinosinusitis (CRS), migraine headache, and fatigue symptoms. We created a summary UNGD activity metric that incorporated well phase, location, total depth, daily gas production and inverse distance-squared to patient residences. We used logistic regression, weighted for sampling and response rates, to assess associations between quartiles of UNGD activity and outcomes, both alone and in combination.

RESULTS

The response rate was 33%. Of 7,785 study participants, 1,850 (24%) had current CRS symptoms, 1,765 (23%) had migraine headache, and 1,930 (25%) had higher levels of fatigue. Among individuals who met criteria for two or more outcomes, adjusted odds ratios for the highest quartile of UNGD activity compared with the lowest were [OR (95% CI)] 1.49 (0.78, 2.85) for CRS plus migraine, 1.88 (1.08, 3.25) for CRS plus fatigue, 1.95 (1.18, 3.21) for migraine plus fatigue, and 1.84 (1.08, 3.14) for all three outcomes together. Significant associations were also present in some models of single outcomes.

CONCLUSIONS

This study provides evidence that UNGD is associated with nasal and sinus, migraine headache, and fatigue symptoms in a general population representative sample. Citation: Tustin AW, Hirsch AG, Rasmussen SG, Casey JA, Bandeen-Roche K, Schwartz BS. 2017. Associations between unconventional natural gas development and nasal and sinus, migraine headache, and fatigue symptoms in Pennsylvania. Environ Health Perspect 125:189-197; http://dx.doi.org/10.1289/EHP281.

Depression, its comorbidities and treatment, and childhood body mass index trajectories

OBJECTIVE

No prior studies have evaluated depression diagnoses and cumulative antidepressant use in relation to longitudinal body mass index (BMI) trajectories in a population-representative sample.

METHODS

Electronic health record data from 105,163 children ages 8 to 18 years with 314,648 BMI values were used. Depression diagnoses were evaluated as ever versus never, cumulative number of encounters with diagnoses, and total duration of diagnoses. Antidepressants were evaluated as months of use. Associations were evaluated with diagnoses alone, antidepressants alone, and then together, adjusting for covariates.

RESULTS

A total of 6,172 (5.9%) and 10,628 (10.1%) children had a diagnosis of depression or received antidepressant treatment, respectively. At all ages, children receiving Medical Assistance (30.9%) were more likely to be treated with antidepressants. Depression diagnosis and antidepressant use were each independently and positively associated with BMI trajectories; associations were stronger with longer durations of diagnosis and treatment. Among children who received 12 or more months of antidepressants (vs. none), the mean (95% CI) weight gain at 18 years associated with antidepressant use (all classes) was 2.10 (1.76-2.45) kg.

CONCLUSIONS

Depression and antidepressant use were both independently associated with increasing BMIs over time, suggesting an important unintended consequence of healthcare to the obesity epidemic.

Early-life antibiotic use and subsequent diagnosis of food allergy and allergic diseases

BACKGROUND

Antibiotic use in early life has been linked to disruptions in the microbiome. Such changes can disturb immune system development. Differences have been observed in the microbiota of children with and without allergies, but there have been few studies on antibiotic use and allergic disease.

OBJECTIVE

We evaluated associations of early-life antibiotic use with subsequent occurrence of food allergy and other allergies in childhood using electronic health record data.

METHODS

We used longitudinal data on 30 060 children up to age 7 years from Geisinger Clinic's electronic health record to conduct a sex- and age-matched case-control study to evaluate the association between antibiotic use and milk allergy, non-milk food allergies, and other allergies. For each outcome, we estimated conditional logistic regression models adjusting for race/ethnicity, history of Medical Assistance, and mode of birth delivery. Models were repeated separately for penicillins, cephalosporins and macrolides.

RESULTS

There were 484 milk allergy cases, 598 non-milk food allergy cases and 3652 other allergy cases. Children with three or more antibiotic orders had a greater odds of milk allergy (Odds Ratio; 95% Confidence interval) (1.78; 1.28-2.48), non-milk food allergy (1.65; 1.27-2.14), and other allergies (3.07; 2.72-3.46) compared with children with no antibiotic orders. Associations were strongest at younger ages and differed by antibiotic class.

CONCLUSIONS AND CLINICAL RELEVANCE

We observed associations between antibiotic orders and allergic diseases, providing evidence of a potentially modifiable clinical practice associated with paediatric allergic disease. Differences by antibiotic class should be further explored, as this knowledge could inform paediatric treatment decisions.