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.

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.

Risk factors for Lyme disease stage and manifestation using electronic health records.

BACKGROUND: Little is known about risk factors for early (e.g., erythema migrans) and disseminated Lyme disease manifestations, such as arthritis, neurological complications, and carditis. No study has used both diagnoses and free text to classify Lyme disease by disease stage and manifestation. METHODS: We identified Lyme disease cases in 2012-2016 in the electronic health record (EHR) of a large, integrated health system in Pennsylvania. We developed a rule-based text-matching algorithm using regular expressions to extract clinical data from free text. Lyme disease cases were then classified by stage and manifestation using data from both diagnoses and free text. Among cases classified by stage, we evaluated individual, community, and health care variables as predictors of disseminated stage (vs. early) disease using Poisson regression models with robust errors. Final models adjusted for sociodemographic factors, receipt of Medical Assistance (i.e., Medicaid, a proxy for low socioeconomic status), primary care contact, setting of diagnosis, season of diagnosis, and urban/rural status. RESULTS: Among 7310 cases of Lyme disease, we classified 62% by stage. Overall, 23% were classified using both diagnoses and text, 26% were classified using diagnoses only, and 13% were classified using text only. Among the staged diagnoses (n = 4530), 30% were disseminated stage (762 arthritis, 426 neurological manifestations, 76 carditis, 95 secondary erythema migrans, and 76 other manifestations). In adjusted models, we found that persons on Medical Assistance at least 50% of time under observation, compared to never users, had a higher risk (risk ratio [95% confidence interval]) of disseminated Lyme disease (1.20 [1.05, 1.37]). Primary care contact (0.59 [0.54, 0.64]) and diagnosis in the urgent care (0.22 [0.17, 0.29]), compared to the outpatient setting, were associated with lower risk of disseminated Lyme disease. CONCLUSIONS: The associations between insurance payor, primary care status, and diagnostic setting with disseminated Lyme disease suggest that lower socioeconomic status and less health care access could be linked with disseminated stage Lyme disease. Intervening on these factors could reduce the individual and health care burden of disseminated Lyme disease. Our findings demonstrate the value of both diagnostic and narrative text data to identify Lyme disease manifestations in the EHR.

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.

Chronic arsenic exposure and risk of carotid artery disease: The Strong Heart Study.

BACKGROUND: Inorganic arsenic exposure from naturally contaminated groundwater is related to vascular disease. No prospective studies have evaluated the association between arsenic and carotid atherosclerosis at low-moderate levels. We examined the association of long-term, low-moderate inorganic arsenic exposure with carotid arterial disease. METHODS: American Indians, 45-74 years old, in Arizona, Oklahoma, and North and South Dakota had arsenic concentrations (sum of inorganic and methylated species, µg/g urine creatinine) measured from baseline urine samples (1989-1991). Carotid artery ultrasound was performed in 1998-1999. Vascular disease was assessed by the carotid intima media thickness (CIMT), the presence of atherosclerotic plaque in the carotid, and by the number of segments containing plaque (plaque score). RESULTS: 2402 participants (mean age 55.3 years, 63.1% female, mean body mass index 31.0kg/m2, diabetes 45.7%, hypertension 34.2%) had a median (interquintile range) urine arsenic concentration of 9.2 (5.00, 17.06) µg/g creatinine. The mean CIMT was 0.75mm. 64.7% had carotid artery plaque (3% with >50% stenosis). In fully adjusted models comparing participants in the 80th vs. 20th percentile in arsenic concentrations, the mean difference in CIMT was 0.01 (95% confidence interval (95%CI): 0.00, 0.02) mm, the relative risk of plaque presence was 1.04 (95%CI: 0.99, 1.09), and the geometric mean ratio of plaque score was 1.05 (95%CI: 1.01, 1.09). CONCLUSIONS: Urine arsenic was positively associated with CIMT and increased plaque score later in life although the association was small. The relationship between urinary arsenic and the presence of plaque was not statistically significant when adjusted for other risk factors. Arsenic exposure may play a role in increasing the severity of carotid vascular disease.

Associations of four indexes of social determinants of health and two community typologies with new onset type 2 diabetes across a diverse geography in Pennsylvania.

Evaluation of geographic disparities in type 2 diabetes (T2D) onset requires multidimensional approaches at a relevant spatial scale to characterize community types and features that could influence this health outcome. Using Geisinger electronic health records (2008-2016), we conducted a nested case-control study of new onset T2D in a 37-county area of Pennsylvania. The study included 15,888 incident T2D cases and 79,435 controls without diabetes, frequency-matched 1:5 on age, sex, and year of diagnosis or encounter. We characterized patients' residential census tracts by four dimensions of social determinants of health (SDOH) and into a 7-category SDOH census tract typology previously generated for the entire United States by dimension reduction techniques. Finally, because the SDOH census tract typology classified 83% of the study region's census tracts into two heterogeneous categories, termed rural affordable-like and suburban affluent-like, to further delineate geographies relevant to T2D, we subdivided these two typology categories by administrative community types (U.S. Census Bureau minor civil divisions of township, borough, city). We used generalized estimating equations to examine associations of 1) four SDOH indexes, 2) SDOH census tract typology, and 3) modified typology, with odds of new onset T2D, controlling for individual-level confounding variables. Two SDOH dimensions, higher socioeconomic advantage and higher mobility (tracts with fewer seniors and disabled adults) were independently associated with lower odds of T2D. Compared to rural affordable-like as the reference group, residence in tracts categorized as extreme poverty (odds ratio [95% confidence interval] = 1.11 [1.02, 1.21]) or multilingual working (1.07 [1.03, 1.23]) were associated with higher odds of new onset T2D. Suburban affluent-like was associated with lower odds of T2D (0.92 [0.87, 0.97]). With the modified typology, the strongest association (1.37 [1.15, 1.63]) was observed in cities in the suburban affluent-like category (vs. rural affordable-like-township), followed by cities in the rural affordable-like category (1.20 [1.05, 1.36]). We conclude that in evaluating geographic disparities in T2D onset, it is beneficial to conduct simultaneous evaluation of SDOH in multiple dimensions. Associations with the modified typology showed the importance of incorporating governmentally, behaviorally, and experientially relevant community definitions when evaluating geographic health disparities.

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.