The contextual influence of coal abandoned mine lands in communities and type 2 diabetes in Pennsylvania

Health and Mental Health Disparities Between National Identity Groups in Wales

Despite close links with ethnic identity and other health-relevant identities, there is surprisingly little work on national identity in the context of population health. National identity is particularly important in multi-national states, where national identity is contested and where different nationalities often reflect both distinct ethnic groups and competing civic visions of national boundaries. The present study examines health disparities between national identity groups in Wales, a constituent nation of the UK. Using data from the National Survey for Wales (n = 23,303), latent class analysis was used to identify national identity groups in Wales. Generalised linear mixed-effects models were then fitted to the data to identity disparities between groups in terms of self-reported general and mental health, both unconditionally and conditionally on several socio-demographic and geographic variables. Analyses identified five groups: Anglophone Welsh, British, Cymry Cymraeg (Welsh-speaking Welsh), English and Ethnically Diverse. Striking health disparities were found, with the Cymry Cymraeg and Ethnically Diverse groups reporting better health than the other groups, especially the Anglophone Welsh and the English. These disparities could not be accounted for by differences in demographic, socio-economic or geographic factors.

Mapping the Morbidity Risk Associated with Coal Mining in Queensland, Australia

The populations in the vicinity of surface coal mining activities have a higher risk of morbidity due to diseases, such as cardiovascular, respiratory and hypertensive diseases, as well as cancer and diabetes mellitus. Despite the large and historical volume of coal production in Queensland, the main Australian coal mining state, there is little research on the association of coal mining exposures with morbidity in non-occupational populations in this region. This study explored the association of coal production (Gross Raw Output—GRO) with hospitalisations due to six disease groups in Queensland using a Bayesian spatial hierarchical analysis and considering the spatial distribution of the Local Government Areas (LGAs). There is a positive association of GRO with hospitalisations due to circulatory diseases (1.022, 99% CI: 1.002–1.043) and respiratory diseases (1.031, 95% CI: 1.001–1.062) for the whole of Queensland. A higher risk of circulatory, respiratory and chronic lower respiratory diseases is found in LGAs in northwest and central Queensland; and a higher risk of hypertensive diseases, diabetes mellitus and lung cancer is found in LGAs in north, west, and north and southeast Queensland, respectively. These findings can be used to support public health strategies to protect communities at risk. Further research is needed to identify the causal links between coal mining and morbidity in non-occupational populations in Queensland.

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.

Unconventional Natural Gas Development and Hospitalization for Heart Failure in Pennsylvania

BACKGROUND

Growing literature linking unconventional natural gas development (UNGD) to adverse health has implicated air pollution and stress pathways. Persons with heart failure (HF) are susceptible to these stressors.

OBJECTIVES

This study sought to evaluate associations between UNGD activity and hospitalization among HF patients, stratified by both ejection fraction (EF) status (reduced [HFrEF], preserved [HFpEF], not classifiable) and HF severity.

METHODS

We evaluated the odds of hospitalization among patients with HF seen at Geisinger from 2008 to 2015 using electronic health records. We assigned metrics of UNGD activity by phase (pad preparation, drilling, stimulation, and production) 30 days before hospitalization or a frequency-matched control selection date. We assigned phenotype status using a validated algorithm.

RESULTS

We identified 9,054 patients with HF with 5,839 hospitalizations (mean age 71.1 ± 12.7 years; 47.7% female). Comparing 4th to 1st quartiles, adjusted odds ratios (95% confidence interval) for hospitalization were 1.70 (1.35 to 2.13), 0.97 (0.75 to 1.27), 1.80 (1.35 to 2.40), and 1.62 (1.07 to 2.45) for pad preparation, drilling, stimulation, and production metrics, respectively. We did not find effect modification by HFrEF or HFpEF status. Associations of most UNGD metrics with hospitalization were stronger among those with more severe HF at baseline.

CONCLUSIONS

Three of 4 phases of UNGD activity were associated with hospitalization for HF in a large sample of patients with HF in an area of active UNGD, with similar findings by HFrEF versus HFpEF status. Older patients with HF seem particularly vulnerable to adverse health impacts from UNGD activity.

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 .

Using human epidemiological analyses to support the assessment of the impacts of coal mining on health

The potential impacts of coal mining on health have been addressed by the application of impact assessment methodologies that use the results of qualitative and quantitative analyses to support their conclusions and recommendations. Although human epidemiological analyses can provide the most relevant measures of risk of health outcomes in populations exposed to coal mining by-products, this kind of studies are seldom implemented as part of the impact assessment methods. To review the use of human epidemiological analyses in the methods used to assess the impacts of coal mining, a systematic search in the peer review literature was implemented following the PRISMA protocol. A synthesis analysis identified the methods and the measures used in the selected publications to develop a thematic review and discussion. The major methodological approaches to assess the impacts of coal mining are environmental impact assessment (EIA), health impact assessment (HIA), social impact assessment (SIA) and environmental health impact assessment (EHIA). The measures used to assess the impacts of coal mining on health were classified as the estimates from non-human-based studies such as health risk assessment (HRA) and the measures of risk from human epidemiological analyses. The inclusion of human epidemiological estimates of the populations exposed, especially the general populations in the vicinity of the mining activities, is seldom found in impact assessment applications for coal mining. These methods rather incorporate HRA measures or other sources of evidence such as qualitative analyses and surveys. The implementation of impact assessment methods without estimates of the risk of health outcomes relevant to the potentially exposed populations affects their reliability to address the environmental and health impacts of coal mining. This is particularly important for EIA applications because these are incorporated in regulatory frameworks globally. The effective characterization of the impacts of coal mining on health requires quantitative estimates of the risk, including the risk measures from epidemiological analyses of relevant human health data.

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.

Neighborhood Environments and Diabetes Risk and Control

PURPOSE OF REVIEW

The objective of this review is to highlight the evidence on the association between contextual characteristics of residential environments and type 2 diabetes, to provide an overview of the methodological challenges and to outline potential topics for future research in this field.

RECENT FINDINGS

The link between neighborhood socioeconomic status or deprivation and diabetes prevalence, incidence, and control is robust and has been replicated in numerous settings, including in experimental and quasi-experimental studies. The association between characteristics of the built environment that affect physical activity, other aspects of the built environment, and diabetes risk is robust. There is also evidence for an association between food environments and diabetes risk, but some conflicting results have emerged in this area. While the evidence base on the association of neighborhood socioeconomic status and built and physical environments and diabetes is large and robust, challenges remain related to confounding due to neighborhood selection. Moreover, we also outline five paths forward for future research on the role of neighborhood environments on diabetes.

Mortality and morbidity in populations in the vicinity of coal mining: a systematic review

BACKGROUND

Evidence of the association of coal mining with health outcomes such as increased mortality and morbidity in the general population has been provided by epidemiological studies in the last 25 years. Given the diverse sources of data included to investigate different health outcomes in the exposed populations, the International Classification of Diseases (ICD) can be used as a single classification standard to compare the findings of studies conducted in different socioeconomic and geographic contexts. The ICD classifies diagnoses of diseases and other disorders as codes organized by categories and chapters.

OBJECTIVES

Identify the ICD codes found in studies of morbidity and/or mortality in populations resident or in proximity of coal mining and assess the methods of these studies conducting a systematic review.

METHODS

A systematic database search of PubMed, EMBASE and Scopus following the PRISMA protocol was conducted to assess epidemiological studies from 1990 to 2016. The health outcomes were mapped to ICD codes and classified by studies of morbidity and/or mortality, and the categories and chapters of the ICD.

RESULTS

Twenty-eight epidemiological studies with ecological design from the USA, Europe and China were included. The exposed populations had increased risk of mortality and/or morbidity by 78 ICD diagnosis categories and 9 groups of ICD categories in 10 chapters of the ICD: Neoplasms, diseases of the circulatory, respiratory and genitourinary systems, metabolic diseases, diseases of the eye and the skin, perinatal conditions, congenital and chromosomal abnormalities, and external causes of morbidity. Exposed populations had non-increased risk of 9 ICD diagnosis categories of diseases of the genitourinary system, and prostate cancer.

CONCLUSIONS

There is consistent evidence of the association of coal mining with a wide spectrum of diseases in populations resident or in proximity of the mining activities. The methods of the studies included in this review can be integrated with individual-level and longitudinal studies to provide further evidence of the exposure pathways linked to increased risk in the exposed populations.

Using electronic health record data for environmental and place based population health research: a systematic review

PURPOSE

We conducted a systematic review of literature published on January 2000-May 2017 that spatially linked electronic health record (EHR) data with environmental information for population health research.

METHODS

We abstracted information on the environmental and health outcome variables and the methods and data sources used.

RESULTS

The automated search yielded 669 articles; 128 articles are included in the full review. The number of articles increased by publication year; the majority (80%) were from the United States, and the mean sample size was approximately 160,000. Most articles used cross-sectional (44%) or longitudinal (40%) designs. Common outcomes were health care utilization (32%), cardiometabolic conditions/obesity (23%), and asthma/respiratory conditions (10%). Common environmental variables were sociodemographic measures (42%), proximity to medical facilities (15%), and built environment and land use (13%). The most common spatial identifiers were administrative units (59%), such as census tracts. Residential addresses were also commonly used to assign point locations, or to calculate distances or buffer areas.

CONCLUSIONS

Future research should include more detailed descriptions of methods used to geocode addresses, focus on a broader array of health outcomes, and describe linkage methods. Studies should also explore using longitudinal residential address histories to evaluate associations between time-varying environmental variables and health outcomes.

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 (HbA1c).

RESEARCH DESIGN AND METHODS

We identified patients with type 2 diabetes who had an HbA1c ≥7.5% (58 mmol/mol) and subsequent HbA1c 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 HbA1c change over 6 and 24 months, controlling for demographics, HbA1c, BMI, and time with evidence of type 2 diabetes. We evaluated whether community domains modified associations of TI with HbA1c change using cross product terms.

RESULTS

There were 15,308 patients with 69,818 elevated HbA1c measures. The average reduction in HbA1c 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 HbA1c in townships with the best food availability (versus worst). HbA1c 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 HbA1c 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 HbA1c 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 HbA1c change and blunted TI effectiveness.

Nasal and sinus symptoms and chronic rhinosinusitis in a population-based sample

BACKGROUND

The objective of this study was to describe the first US-based study to use the European Position Paper on Rhinosinusitis (EPOS) criteria to study the prevalence of chronic rhinosinusitis (CRS) in a general-population sample.

METHODS

A CRS symptom questionnaire was mailed to 23 700 primary care patients from Geisinger Clinic, a health system serving 45 counties in Pennsylvania. CRS cases were categorized into four unique subgroups based on EPOS symptoms: obstruction and discharge with no smell loss or pain/pressure; smell loss without pain/pressure; facial pain and/or pressure without smell loss; and both smell loss and pain/pressure. All cases were required to have nasal obstruction or discharge. Logistic regression was used to evaluate potential factors associated with CRS subgroups.

RESULTS

We found that 11.9% of patients met criteria for CRS. Prevalence peaked at 15.9% between ages 50 and 59 years and then dropped to 6.8% after age 69. The odds of CRS was higher among patients who were white, younger, smokers, had a history of Medical Assistance, and had other diseases. When CRS subgroups were modeled separately, these associations were no longer significant for some CRS subgroups. Comorbid diseases were most strongly associated with CRS cases who reported smell loss and facial pain and/or pressure and had the weakest associations with CRS cases who did not report these symptoms.

CONCLUSIONS

CRS is a highly prevalent and heterogeneous condition. Differences in risk factors and health outcomes across symptom subgroups may be indicative of differences in etiology that have implications for disease management.

Association Between Unconventional Natural Gas Development in the Marcellus Shale and Asthma Exacerbations

IMPORTANCE

Asthma is common and can be exacerbated by air pollution and stress. Unconventional natural gas development (UNGD) has community and environmental impacts. In Pennsylvania, UNGD began in 2005, and by 2012, 6253 wells had been drilled. There are no prior studies of UNGD and objective respiratory outcomes.

OBJECTIVE

To evaluate associations between UNGD and asthma exacerbations.

DESIGN

A nested case-control study comparing patients with asthma with and without exacerbations from 2005 through 2012 treated at the Geisinger Clinic, which provides primary care services to over 400 000 patients in Pennsylvania. Patients with asthma aged 5 to 90 years (n = 35 508) were identified in electronic health records; those with exacerbations were frequency matched on age, sex, and year of event to those without.

EXPOSURES

On the day before each patient's index date (cases, date of event or medication order; controls, contact date), we estimated activity metrics for 4 UNGD phases (pad preparation, drilling, stimulation [hydraulic fracturing, or "fracking"], and production) using distance from the patient's home to the well, well characteristics, and the dates and durations of phases.

MAIN OUTCOMES AND MEASURES

We identified and defined asthma exacerbations as mild (new oral corticosteroid medication order), moderate (emergency department encounter), or severe (hospitalization).

RESULTS

We identified 20 749 mild, 1870 moderate, and 4782 severe asthma exacerbations, and frequency matched these to 18 693, 9350, and 14 104 control index dates, respectively. In 3-level adjusted models, there was an association between the highest group of the activity metric for each UNGD phase compared with the lowest group for 11 of 12 UNGD-outcome pairs: odds ratios (ORs) ranged from 1.5 (95% CI, 1.2-1.7) for the association of the pad metric with severe exacerbations to 4.4 (95% CI, 3.8-5.2) for the association of the production metric with mild exacerbations. Six of the 12 UNGD-outcome associations had increasing ORs across quartiles. Our findings were robust to increasing levels of covariate control and in sensitivity analyses that included evaluation of some possible sources of unmeasured confounding.

CONCLUSIONS AND RELEVANCE

Residential UNGD activity metrics were statistically associated with increased risk of mild, moderate, and severe asthma exacerbations. Whether these associations are causal awaits further investigation, including more detailed exposure assessment.

Greenness and Birth Outcomes in a Range of Pennsylvania Communities

Living in communities with more vegetation during pregnancy has been associated with higher birth weights, but fewer studies have evaluated other birth outcomes, and only one has been conducted in the Eastern United States, in regions with a broad range, including high levels, of greenness. We evaluated associations between prenatal residential greenness and birth outcomes (term birth weight, small for gestational age, preterm birth, and low 5 min Apgar score) across a range of community types using electronic health record data from 2006–2013 from the Geisinger Health System in Pennsylvania. We assigned greenness based on mother’s geocoded address using the normalized difference vegetation index from satellite imagery. We used propensity scores to restrict the study population to comparable groups among those living in green vs. less-green areas. Analyses were adjusted for demographic, clinical, and environmental covariates, and stratified by community type (city, borough, and township). In cities, higher greenness (tertiles 2–3 vs. 1) was protective for both preterm (OR = 0.78, 95% CI: 0.61–0.99) and small for gestational age birth (OR = 0.73, 95% CI: 0.58–0.97), but not birth weight or Apgar score. We did not observe associations between greenness and birth outcomes in adjusted models in boroughs or townships. These results add to the evidence that greener cities might be healthier cities.

Using Electronic Health Records for Population Health Research: A Review of Methods and Applications

The use and functionality of electronic health records (EHRs) have increased rapidly in the past decade. Although the primary purpose of EHRs is clinical, researchers have used them to conduct epidemiologic investigations, ranging from cross-sectional studies within a given hospital to longitudinal studies on geographically distributed patients. Herein, we describe EHRs, examine their use in population health research, and compare them with traditional epidemiologic methods. We describe diverse research applications that benefit from the large sample sizes and generalizable patient populations afforded by EHRs. These have included reevaluation of prior findings, a range of diseases and subgroups, environmental and social epidemiology, stigmatized conditions, predictive modeling, and evaluation of natural experiments. Although studies using primary data collection methods may have more reliable data and better population retention, EHR-based studies are less expensive and require less time to complete. Future EHR epidemiology with enhanced collection of social/behavior measures, linkage with vital records, and integration of emerging technologies such as personal sensing could improve clinical care and population health.

Antibiotic use and childhood body mass index trajectory

BACKGROUND/OBJECTIVES

Antibiotics are commonly prescribed for children. Use of antibiotics early in life has been linked to weight gain but there are no large-scale, population-based, longitudinal studies of the full age range among mainly healthy children.

SUBJECTS/METHODS

We used electronic health record data on 163 820 children aged 3-18 years and mixed effects linear regression to model associations of antibiotic orders with growth curve trajectories of annual body mass index (BMI) controlling for confounders. Models evaluated three kinds of antibiotic associations-reversible (time-varying indicator for an order in year before each BMI), persistent (time-varying cumulative orders up to BMIj) and progressive (cumulative orders up to prior BMI (BMIj-1))-and whether these varied by age.

RESULTS

Among 142 824 children under care in the prior year, a reversible association was observed and this short-term BMI gain was modified by age (P<0.001); effect size peaked in mid-teen years. A persistent association was observed and this association was stronger with increasing age (P<0.001). The addition of the progressive association among children with at least three BMIs (n=79 752) revealed that higher cumulative orders were associated with progressive weight gain; this did not vary by age. Among children with an antibiotic order in the prior year and at least seven lifetime orders, antibiotics (all classes combined) were associated with an average weight gain of approximately 1.4 kg at age 15 years. When antibiotic classes were evaluated separately, the largest weight gain at 15 years was associated with macrolide use.

CONCLUSIONS

We found evidence of reversible, persistent and progressive effects of antibiotic use on BMI trajectories, with different effects by age, among mainly healthy children. The results suggest that antibiotic use may influence weight gain throughout childhood and not just during the earliest years as has been the primary focus of most prior studies.

Exploring the forest instead of the trees: An innovative method for defining obesogenic and obesoprotective environments

Past research has assessed the association of single community characteristics with obesity, ignoring the spatial co-occurrence of multiple community-level risk factors. We used conditional random forests (CRF), a non-parametric machine learning approach to identify the combination of community features that are most important for the prediction of obesogenic and obesoprotective environments for children. After examining 44 community characteristics, we identified 13 features of the social, food, and physical activity environment that in combination correctly classified 67% of communities as obesoprotective or obesogenic using mean BMI-z as a surrogate. Social environment characteristics emerged as most important classifiers and might provide leverage for intervention. CRF allows consideration of the neighborhood as a system of risk factors.

Community socioeconomic deprivation and obesity trajectories in children using electronic health records

OBJECTIVES

Longitudinal studies of the role of community context in childhood obesity are lacking. The objective of this study was to examine associations of community socio economic deprivation (CSD) with trajectories of change in body mass index (BMI) in childhood and adolescence.

METHODS

Data came from electronic health records on 163,473 children aged 3-18 residing in 1,288 communities in Pennsylvania whose weight and height were measured longitudinally. CSD at the year of birth was measured using six US Census variables and modeled in quartiles. Trajectories of BMI within CSD quartiles were estimated using random effects growth-curve models accounting for differences by age, sex, and race/ethnicity as well as correcting for non-constant residual variance across age groups.

RESULTS

CSD was associated with higher BMI at average age (10.7 years) and with more rapid growth of BMI over time. Children born in communities with greater CSD had steeper increases of BMI at younger ages. Those born into the poorest communities displayed sustained accelerated BMI growth. CSD remained associated with BMI trajectories after adjustment for a measure of household socio economic deprivation.

CONCLUSIONS

Higher CSD may be associated with more obesogenic growth trajectories in early life. Findings suggest that individual-level interventions that ignore the effect of community context on obesity-related behaviors may be less efficient.

Attention deficit disorder, stimulant use, and childhood body mass index trajectory

BACKGROUND

Childhood attention-deficit/hyperactivity disorder (ADHD) has been associated with childhood and adult obesity, and stimulant use with delayed childhood growth, but the independent influences are unclear. No longitudinal studies have examined associations of ADHD diagnosis and stimulant use on BMI trajectories throughout childhood and adolescence.

METHODS

We used longitudinal electronic health record data from the Geisinger Health System on 163,820 children ages 3 to 18 years in Pennsylvania. Random effects linear regression models were used to model BMI trajectories with increasing age in relation to ADHD diagnosis, age at first stimulant use, and stimulant use duration, while controlling for confounding variables.

RESULTS

Mean (SD) age at first BMI was 8.9 (5.0) years, and children provided a mean (SD) of 3.2 (2.4) annual BMI measurements. On average, BMI trajectories showed a curvilinear relation with age. There were consistent associations of unmedicated ADHD with higher BMIs during childhood compared with those without ADHD or stimulants. Younger age at first stimulant use and longer duration of stimulant use were each associated with slower BMI growth earlier in childhood but a more rapid rebound to higher BMIs in late adolescence.

CONCLUSIONS

The study provides the first longitudinal evidence that ADHD during childhood not treated with stimulants was associated with higher childhood BMIs. In contrast, ADHD treated with stimulants was associated with slower early BMI growth but a rebound later in adolescence to levels above children without a history of ADHD or stimulant use. The findings have important clinical and neurobiological implications.

High-density livestock operations, crop field application of manure, and risk of community-associated methicillin-resistant Staphylococcus aureus infection in Pennsylvania

IMPORTANCE

Nearly 80% of antibiotics in the United States are sold for use in livestock feeds. The manure produced by these animals contains antibiotic-resistant bacteria, resistance genes, and antibiotics and is subsequently applied to crop fields, where it may put community members at risk for antibiotic-resistant infections.

OBJECTIVE

To assess the association between individual exposure to swine and dairy/veal industrial agriculture and risk of methicillin-resistant Staphylococcus aureus (MRSA) infection.

DESIGN, SETTING, AND PARTICIPANTS

A population-based, nested case-control study of primary care patients from a single health care system in Pennsylvania from 2005 to 2010. Incident MRSA cases were identified using electronic health records, classified as community-associated MRSA or health care-associated MRSA, and frequency matched to randomly selected controls and patients with skin and soft-tissue infection. Nutrient management plans were used to create 2 exposure variables: seasonal crop field manure application and number of livestock animals at the operation. In a substudy, we collected 200 isolates from patients stratified by location of diagnosis and proximity to livestock operations.

MAIN OUTCOMES AND MEASURES

Community-associated MRSA, health care-associated MRSA, and skin and soft-tissue infection status (with no history of MRSA) compared with controls.

RESULTS

From a total population of 446,480 patients, 1539 community-associated MRSA, 1335 health care-associated MRSA, 2895 skin and soft-tissue infection cases, and 2914 controls were included. After adjustment for MRSA risk factors, the highest quartile of swine crop field exposure was significantly associated with community-associated MRSA, health care-associated MRSA, and skin and soft-tissue infection case status (adjusted odds ratios, 1.38 [95% CI, 1.13-1.69], 1.30 [95% CI, 1.05-1.61], and 1.37 [95% CI, 1.18-1.60], respectively); and there was a trend of increasing odds across quartiles for each outcome (P ≤ .01 for trend in all comparisons). There were similar but weaker associations of swine operations with community-associated MRSA and skin and soft-tissue infection. Molecular testing of 200 isolates identified 31 unique spa types, none of which corresponded to CC398 (clonal complex 398), but some have been previously found in swine.

CONCLUSIONS AND RELEVANCE

Proximity to swine manure application to crop fields and livestock operations each was associated with MRSA and skin and soft-tissue infection. These findings contribute to the growing concern about the potential public health impacts of high-density livestock production.