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College of
Health Sciences

Center for Community Environment and Health (CCEH)

Geisinger’s Research Institute and the Johns Hopkins Bloomberg School of Public Health formed the Center for Community Environment and Health (CCEH, formerly the Environmental Health Institute) in 2007. 


 The CCEH’s mission is to understand how social, socioeconomic, built and natural environments, and climate change impact human health in central and northeast Pennsylvania. This knowledge can be integrated into interventions in healthcare settings to improve our community health and to understand how to develop and promote healthy and sustainable communities.

We seek to understand how the context of the communities in which patients live affects their health and healthcare, including how: 

  • Community circumstances affect health: Many diseases have lifestyle factors—such as diet, physical activity, and stress—that are influenced by the communities in which we live.
  • Community circumstances enable or constrain the influence of healthcare: For example, diabetes care provided by the health system may be less effective in communities that constrain our ability to eat healthy or walk more.
  • Community context can be integrated into clinical care decisions: Geisinger researchers are embedded in Geisinger clinic settings, creating a laboratory for evaluating and implementing innovative strategies for integrating community context into clinical care.
  • Pennsylvania’s many old and emerging environmental conditions might affect health: These include, for example, abandoned coal mines; Marcellus shale development; large-scale animal feeding operations; automobile dependent, non-walkable community designs; and habitat that supports ticks and insects that can transmit vector-borne diseases.

Contact our team

Interested in our research?

Annemarie Hirsch:
Brian S. Schwartz:

Interested in learning more about a study?

Dione Mercer:



Brian S. Schwartz, MD, MS

Brian Schwartz

Co-founder, Co-Director

Professor, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health

Professor, Department of Population Health Sciences, Geisinger

Annemarie G. Hirsch, PhD, MPH

Annemarie Hirsch


Associate professor, Department of Population Health Sciences, Geisinger

Adjunct faculty, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health

Melissa N. Poulsen, PhD, MPH

Melissa Poulsen


Assistant professor, Department of Population Health Sciences, Geisinger


  • Annemarie Hirsch, PhD, MPH, Director
  • Brian S. Schwartz, MD, MS, Co-founder, Co-Director

Support staff

  • Dione Mercer, Administrative Director
  • Joseph DeWalle, Geographic Information System Analyst
  • Cara Nordberg, Biostatistical Analyst II
  • Jake Mowery, Project Manager II
  • Amy Poissant, Project Coordinator
  • Meghann Reeder, Senior Research Assistant

Areas of research

Unconventional natural gas development

The CCEH has conducted several studies regarding the potential public health impacts of unconventional natural gas development (UNGD) in the Marcellus shale, and how these may influence such health issues as asthma, cardiovascular disease, pregnancy outcomes, mental health and such symptoms as headache, fatigue, and nasal and sinus symptoms.

UNGD can influence air, surface water, and ground water quality, and we have conducted studies to assess the health impacts of each of these sources and routes of exposure. In our first study, the NIH-funded “Marcellus Shale Development, Respiratory and Reproductive Outcomes in Pennsylvania,” we used well and infrastructure data to estimate exposures to all aspects of Marcellus shale development in Pennsylvania. These exposure estimates were used to evaluate whether asthma control and pregnancy outcomes were affected by UNGD by studying 35,000 asthma patients and over 10,000 pregnancies in the Geisinger system from 2005-2013.

Prior Grant Program

The Environmental Health Institute developed a regional Marcellus Impact Pilot Program and made five awards totaling $100,000 to principal investigators from six different institutions that provided research opportunities for nine students and resulted in multiple publications.

Awards were made to Dr. Steven Rier (Bloomsburg University with United States Geological Survey partners), Dr. Lisa Bailey-Davis (Geisinger), Dr. Jonathan Niles (Susquehanna University) with Dr. Chris Grant (Juniata College), Dr. Melvin Zimmerman and Dr. Peter Petokas (Lycoming College), and Dr. Md. Khalequzzaman (Lock Haven University).


PI/s and Institution/s

Project Title

Dr. Steven Rier, Bloomsburg University (with United States Geological Survey Partners)

Developing biofilm markers for monitoring the impacts of unconventional oil and gas development on stream ecosystems

Dr. Lisa Baily-Davis and Dr. Melissa Poulsen, Geisinger

Pennsylvania farmers' perception of agricultural impacts from unconventional natural gas development in the Marcellus shale

Dr. Jonathan Niles, Susquehanna University, and Dr. Chris Grant, Juniata College

Assessing potential impacts of unconventional natural gas extractions and mercury concentrations on trophic food webs of unassessed headwater streams

Dr. Melvin Zimmerman and Dr. Peter Petokas, Lycoming College

An assessment of eastern hellbender population trajectories and water quality as determinants of watershed health

Dr. Md. Khalequzzaman, Lock Haven University

Determination of the sources of turbidity in waterways in the Marcellus shale gas drilling region



  • Gorski-Steiner I, Bandeen-Roche K, Volk HE, O’Dell S, Schwartz BS. The association of unconventional natural gas development with diagnosis and treatment of internalizing disorders among adolescents in Pennsylvania using electronic health records. Environmental Research 2022; 212: 113167.
  • McAlexander TP, Bandeen-Roche K, Buckley JP, Pollak J, Michos ED, McEvoy JW, Schwartz BS. Unconventional natural gas development and hospitalization for heart failure in Pennsylvania. Journal of the American College of Cardiology 2020; 76: 2862-74. Recognized as “Editor-in-Chief’s Top Picks from 2020” in JACC 2021; 77: 943-4. (JACC impact factor = 20.5).
  • Casey JA, Goin DE, Rudolph KE, Schwartz BS, Mercer D, Elser H, Eisen EA, Morello-Frosch R. Unconventional natural gas development and adverse birth outcomes in Pennsylvania: The potential mediating role of antenatal anxiety and depression. Environmental Research 2019; 177: 108598,11 pages.
  • Casey JA, Wilcox HC, Hirsch AG, Pollak J, Schwartz BS. Associations of unconventional natural gas development with depression symptoms and disordered sleep in Pennsylvania. Scientific Reports 2018; 8: 11375, 10 pages.  
  • Poulsen MN, Bailey-Davis L, DeWalle J, Mowery J, Schwartz BS. Agricultural implications of unconventional natural gas development: divergent perceptions of sustainable and conventional farmers. Culture, Agriculture, Food, and Environment 2018, 40: 24-35.
  • Koehler K, Casey JA, Ellis HJ, Manthos D, Bandeen-Roche K, Platt R, Schwartz BS. Exposure assessment using secondary data sources in unconventional natural gas development and health studies. Environ Sci Technol 2018, 52(10), 6061-6069
  • Chen See JR, Ulrich N, Nwanosike H, McLimans CJ, Tokarev V, Wright JR, Campa MF, Grant CJ, Hazen TC, Niles JM, Resslert D, Lamandella R. Bacterial biomarkers of Marcellus shale activity in Pennsylvania. Frontiers in Microbiology 2018; 9: 1697.
  • Tustin AW, Hirsch AG, Rasmussen SG, Casey JA, Bandeen-Roche K, Schwartz BS. Associations between unconventional natural gas development and nasal and sinus, migraine headache and fatigue symptoms in Pennsylvania. Environ Health Perspect 2017; 125: 189-97.
  • Rasmussen SG, Ogburn EL, McCormack M, Casey JA, Bandeen-Roche K, Mercer, DG, Schwartz BS. Association between unconventional natural gas development in the Marcellus shale and asthma exacerbations. JAMA Intern Med 2016; 176: 1334-43.
  • Casey JA, Savitz DA, Rasmussen SG, Ogburn EL, Pollak J, Mercer DG, Schwartz BS. Unconventional Natural Gas Development and Birth Outcomes in Pennsylvania, USA. Epidemiology 2016; 27: 163-72.
  • Casey JA, Ogburn EL, Rasmussen SG, Irving JK, Pollak J, Locke PA, Schwartz BS. Predictors of indoor radon concentrations in Pennsylvania, 1989-2013. Environ Health Perspect 2015; 123: 1130-7.
  • Graham J, Irving J, Tang X, Sellers S, Crisp J, Horwitz D, Muehlenbachs L, Krupnick A, Carey D. Increased traffic accident rates associated with shale gas drilling in Pennsylvania. Accident Analysis & Prevention 2015; 74: 203-309. 
Chronic rhinosinusitis

We have been studying the epidemiology of chronic rhinosinusitis (CRS) in Geisinger's patients since 2013. This is a chronic condition with a significant patient and population disease burden.

The CCEH at Geisinger is collaborating with Northwestern University and the Johns Hopkins Bloomberg School of Public Health on the second of two program project grants (P01) awarded by the NIH (competitive renewal). The collaborative group, collectively known as the Chronic Rhinosinusitis Integrative Studies Program (CRISP), is the only P01 recipient in the United States studying this common but poorly understood disease.


During the first phase of funding (CRISP1), our project studied the epidemiology, genetics and pathobiology of CRS.

The CCEH provided the first US-based estimates of the prevalence of CRS symptoms and sinus inflammation in general population samples. We generated new evidence regarding sinonasal symptom patterns over time and on how these symptoms, measured by questionnaire and EHR data, can be leveraged to understand the natural history of the disease through both subjective and objective information. We also identified social and environmental influences on CRS and found sex differences in both nasal and sinus symptoms and patterns of sinonasal computed tomography (CT) scan findings.


During CRISP2, our project was designed to determine the long-term consequences of CRS and to develop a more refined understanding of the CRS pathophysiology that could inform more tailored treatment strategies.

We have provided the clearest evidence to date that CRS is an independent risk factor for new-onset diagnoses of asthma, bronchiectasis and chronic obstructive pulmonary disease. We have further demonstrated that transitions to these pulmonary diseases are more likely in persons with worse CRS symptom burden. We are currently collecting nasal lavage fluid samples and sinus CT scans from individuals with evidence of CRS to evaluate if CRS endotypes are associated with phenotype, natural history, and clinical outcomes.


  • Schwartz BS, Pollak JS, Bandeen-Roche K, Hirsch AG, Lehmann AE, Kern RC, Tan BK, Kato A, Schleimer RP, Peters AT. Longitudinal evaluation of sinus inflammation and chronic rhinosinusitis in relation to new onset asthma using electronic health records. Allergy. 2023. doi: 10.1111/all.15771.
  • Hirsch AG, Schwartz BS, Nordberg C, Tan BK, Schleimer RP, Kern TC, Peters AT, Bandeen-Roche K, Lehmann AE. Risk of new onset and prevalent disease in chronic rhinosinusitis: a prospective cohort study. International Forum of Allergy & Rhinology. 2023. https//
  • Al-Sayouri, SA, Pollak JS, Peters A, Hirsch AG, Kern R, Tan B, Schleimer RP, Schwartz, BS. Schwartz B. Strong and consistent associations of precedent chronic rhinosinusitis with risk of non-cystic fibrosis bronchiectasis. Journal of Allergy and Clinical Immunology. 2022 Sep; 150(3): 701-708.e4.
  • Soliai M, Sundaresan AS, Morin A, Hirsch AG, Stanhope C, Kuiper J, Schwartz BS, Ober C, Pinto JM. Two-state genome-wide association study of chronic rhinosinusitis and disease sub-phenotypes highlights mucosal immunity contributing to risk. International Forum of Allergy & Rhinology. 2021; 11: 814-817.
  • Kuiper J, Hirsch AG, Bandeen-Roche Karen, Sundaresan AS, Schleimer RP, Kern R, Tan B, Schwartz BS. A new approach to categorization of radiologic inflammation in chronic rhinosinusitis. PLOS ONE. 2020. 15(6): e0235432.
  • Kuiper J, Bandeen-Roche, Hirsch AG, Sundaresan AS, Schleimer RP, Kern R, Tan B, Schwartz BS. Workplace indirect cost impacts of nasal and sinus symptoms and related conditions. Journal of Occupation and Environmental Medicine. 2019; 61(8): e333.
  • Cole M, Bandeen-Roche K, Hirsch AG, Kuiper JR, Sundaresan AS, Kern RC, Tan BK, Schleimer RP, Schwartz BS. Longitudinal evaluation of clustering of sinonasal and related symptoms using exploratory factor analysis. Allergy 2018; May 5.
  • Kuiper JR, Hirsch AG, Bandeen-Roche K, Sundaresan AS, Tan BK, Schleimer RP, Kern RC, Stewart WF, Schwartz BS. Prevalence and risk factors for acute exacerbations of nasal and sinus symptoms: A population-based, longitudinal cohort study in Pennsylvania. Allergy 2018, Jun;73(6):1244-53.
  • Sundaresan AS, Hirsch AG, Young AJ, Tan BK, Schleimer RP, Kern RC, Kennedy TL, Greene JS, Stewart WF, Bandeen-Roche K, Schwartz BS. Longitudinal evaluation of chronic rhinosinusitis symptoms in a population-based sample. J Allergy Clin Immunol Pract 2017, Jul 1;6(4):1327-35.
  • Stevens WW, Peters AT, Hirsch AG, Nordberg CM, Schwartz BS, Mercer DG, Mahdavinia M, Grammer LC, Hulse KE, Kern RC, Avila P, Schleimer RP. Clinical characteristics of patients with chronic rhinosinusitis with nasal polyps, asthma and aspirin-exacerbated respiratory disease. J Allergy Clin Immunol Pract 2017; 5: 1061-1070.
  • Hirsch AG, Stewart WF, Sundaresan AS, Young AJ, Kennedy TL, Greene JS, Feng W, Tan BK, Schleimer RP, Kern RC, Lidder A, Schwartz BS. Nasal and sinus symptoms and chronic rhinosinusitis in a population-based sample. Allergy 2017; 72: 274-281.
  • Hirsch AG, Yan XS, Sundaresan AS, Tan BK, Schleimer RP, Kern RC, Kennedy TL, Greene JS, Schwartz BS. Five‐year risk of incident disease following a diagnosis of chronic rhinosinusitis. Allergy 2015; 70: 1613-21.
  • Sundaresan A, Hirsch AG, Storm M, Tan BK, Kennedy TL, Greene JS, Schwartz BS. Occupational and environmental risk factors for chronic rhinosinusitis: a systematic review. Int Forum Allerg Rhino 2015; 5: 996-1003.
  • Ference EH, Stubbs V, Lidder AK, Chandra RK, Conley D, Avila PC, Hirsch AG, Min JY, Shintani Smith S, Kern RC, Tan BK. Measurement and comparison of health utility assessments in chronic rhinosinusitis. International forum of allergy & rhinology 2015; 5: 929-936.
  • Lam K, Hirsch AG, Tan BK. The association of premorbid diseases with chronic rhinosinusitis with and without polyps. Current opinion in otolaryngology & head and neck surgery. 2014; 22: 231.
  • Tan BK, Chandra RK, Pollak J, Kato A Conley DB, Peters AT, Grammer LC, Avila PC, Kern RC, Stewart WF, Schwartz BS. Incidence and associated premorbid diagnosis of patients with chronic rhinosinusitis. J Allergy Clinical Immunology 2013; 131: 1350-60.
  • Tan BK, Kern RB, Schleimer RP, Schwartz BS. Chronic rhinosinusitis - the unrecognized epidemic [editorial]. AJRCCM 2013; 188: 1275-7.

For more than a decade, the CCEH has studied the role of the community environment and diabetes onset and control. We have used longitudinal EHR data, questionnaires, community data and biomarkers to study associations of social, built and natural environments, and community type, in relation to type 2 diabetes onset, control and complications in central and northeastern Pennsylvania.

Specifically, we have linked residential address and clinical data from the EHR to commercial and publicly available data on our communities to measure the food, physical activity, land use, and social environments; blue space, green space, and community greenness; urbanicity and community type; and chronic environmental contamination in relation to type 2 diabetes onset, glucose control, blood pressure, and kidney function among individuals with type 2 diabetes. Some of these studies have also included type 1 diabetes.

The CCEH is a member of two diabetes networks funded by the Centers for Disease Control and Prevention.

  • The Diabetes LEAD (Location, Environmental Attributes, and Disparities) Network. This collaborative network includes Geisinger, Johns Hopkins University, New York University School of Medicine, Drexel University, and the University of Alabama at Birmingham. The primary goal of the network is to identify the contributions of modifiable community factors on risk of type 2 diabetes. Additional information about The Diabetes LEAD Network can be found here:
  • The Assessing the Burden of Diabetes by Type in Children, Adolescents, and Young Adults (DiCAYA) Network, a collaboration of eight US-based centers and a coordinating center funded to modernize diabetes surveillance efforts to capitalize on large-volume, electronic health record data streams to provide accurate, timely, cost-effective, granular, and representative indicators of diabetes prevalence and incidence among children, adolescents, and younger adults. Additional information about the DiCAYA Network can be found here:


  • Schwartz BS, Kolak M, Pollak JS, Poulsen MN, Bandeen-Roche K, Moon KA, DeWalle J, Siegel KR, Mercado CI, Imperatore G, Hirsch AG. Associations of four indices of social determinants of health and census tract typology with new onset type 2 diabetes across a diverse geography in Pennsylvania. PLOS ONE. 2022:
  • Hirsch AG, Nordberg CM, Bandeen-Roche K, Pollak J, Poulsen MN, Moon KA, Schwartz BS. Urban-rural differences in health care utilization and COVID-19 outcomes in patients with Type 2 diabetes. Preventing Chronic Disease. 2022; 19: 220015. DOI:
  • Thorpe LE, Adhikari A,  Lopez P,  Kanchi R,  McClure LA, Hirsch AG, Howell CR,  Zhu A,  Alemi F, Rummo P, Ogburn EL, Algur Y, Nordberg CM, Poulsen MN, Long L,  Carson  AP,  DeSilva SA, Meeker M, Schwartz BS, Lee DC, Siegel KR, Imperatore G,  Elbel B. Neighborhood socioeconomic environment and risk of type 2 diabetes: Associations and mediation through food environment pathways in three independent study samples. Diabetes Care. 2022 Apr; 45(4): 798-810.
  • Hirsch AG, Nordberg CM, Chang A, Poulsen MN, Moon KA, Siegel KR, Rolka DB, Schwartz BS. Association of community socioeconomic deprivation with evidence of reduced kidney function at time of type 2 diabetes diagnosis. Social Science & Medicine: Population Health. 2021; 15:
  • Poulsen MN, Schwartz BS, DeWalle J, Nordberg C, Pollak JS, Silva J, Mercado CI, Rolka DB, Siegel KR, Imperatore G, Hirsch AG. Proximity to freshwater blue space and type 2 diabetes: the importance of historical and economic context. Landscape and Urban Planning. 2021; 209: 104060.
  • Poulsen MN, Schwartz BS, Nordberg C, DeWalle J, Pollak J, Imperatore G, Mercado CI, Siegel KR, Hirsch AG. Association of greenness with blood pressure among individuals with type 2 diabetes across rural and urban community types in Pennsylvania, USA. International Journal of Environmental Research and Public Health. 2021; 18: 614.
  • Schwartz BS, Pollak JS, Poulsen MN, Bandeen-Roche K, Moon KA, DeWalle J, Siegel KR, Mercado CI, Imperatore Giuseppina, Hirsch AG. Association of community types and features with risk of new onset type 2 diabetes across diverse geography in Pennsylvania. BMJ Open. 2021; 11: e043528. doi:10.1136/bmjopen-2020-043528.
  • Hirsch AG, Carson AP, Lee NL, McAlexander T, Mercado C, Siegel K, Black NC, Elbel B, Long DL, Lopez P, McClure LA, Poulsen MN, Schwartz BS, Thorpe LE. The Diabetes Location, Environmental Attributes, and Disparities Network: Protocol for Nested Case Control and Cohort Studies, Rationale, and Baseline Characteristics. JMIR Res Protoc. 2020; 9(10): e21377. doi: 10.2196/21377.
  • Feldman J, Lee D, Lopez P, Rummo P, Hirsch A, Carson A, McClure L, Elbel B, Thorpe LE. Assessing county-level determinants of individual-level diabetes status in the United States (2003 – 2012): A random-effects within-between analysis of repeated cross-sectional data. Health & Place. 2020; 63: 102324.
  • Hirsch AG, Durden TE, Nordberg C, Berger A, Schwartz BS. Associations of four community factors with longitudinal change in hemoglobin A1c levels in patients with type 2 diabetes. Diabetes Care 2018; 41: 461-8.
  • Wood GC, Horwitz D, Still CD, Mirshahi T, Benotti P, Parikh M, Hirsch AG. Performance of the DiaRem score for predicting diabetes remission in two health systems following bariatric surgery procedures in Hispanic and non-Hispanic white patients. Obesity Surgery 2018; 28: 61-68.
  • Lent MR, Benotti PN, Mirshahi T, Gerhard G, Strodel WE, Petrick AT, Gabrielsen JD, Rolston DD, Still CD, Hirsch AG, Zubair F, Cook A, Carey DJ, Wood GC. All-cause and specific-cause mortality risk following Roux-en-Y gastric bypass in patients with and without diabetes. Diabetes Care 2017; 40: 1379-1385.
  • Benotti P, Wood GC, Carey D, Mehra V, Mirshahi T, Lent M, Petrick A, Still C, Gerhard G, Hirsch AG. Gastric bypass surgery produces a durable reduction in cardiovascular disease risk factors and reduces the long-term risks of congestive heart failure. JAHA 2017; 6: e005126.
  • Wood GC, Mirshahi T, Still CD, Hirsch AG. Association of DiaRem score with cure of type 2 diabetes following bariatric surgery. JAMA Surgery 2016; 15: 779-781.
  • Liu AY, Curriero FC, Glass TA, Stewart WF, Schwartz BS. The contextual influence of coal abandoned mine lands in communities and type 2 diabetes in Pennsylvania. Health & Place 2013; 22: 115-122.
  • Schoenthaler AM, Schwartz BS, Wood C, Stewart WF. Patient and physician factors associated with adherence to diabetes medications. Diabetes Educator 2012; 38: 397-408.
Lyme Disease

Geisinger serves a region that is highly endemic for Lyme disease. The CCEH has studied the epidemiology of Lyme disease and its clinical manifestations with funding from the Centers for Disease Control and Prevention, the Pennsylvania Department of Health, and the Steven & Alexandra Cohen Foundation.

Our prior research in 38 Pennsylvania counties from 2006–14 used EHR data (diagnosis codes, serologic testing orders and medication orders) to identify over 9500 Lyme disease cases and estimated annual incidence rates that were 4.25 to 7.43 times higher than those using surveillance data, like the large discrepancies in estimates found using a range of methods.

We found that within 4–52 weeks after Lyme disease diagnosis, 20.8% of cases with a diagnosis code and treatment also had a diagnosis of malaise or fatigue, pain or cognitive difficulties that were not present in the prior 26 weeks. We have also used EHR data to identify Lyme disease stage and manifestation.

Our results highlighted the utility of EHR data for epidemiologic research on Lyme disease for case-finding, surveillance, risk factor evaluation and characterization of post-treatment Lyme disease syndrome.

In additional studies, we linked patient data to community landscape and remote sensing data. In one study, we found that landscape composition and forest configuration, measured community-wide and within residential buffers, were associated with individual risk of Lyme disease.

We also linked individual data to daily weather data to create cumulative metrics hypothesized to promote (warm and humid) or inhibit (hot and dry) tick development or host-seeking during specific periods. Exposure-effect 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 (hot and dry days decreased risk).

In primary data collection studies, we conducted qualitative interviews with patients with confirmed Lyme disease by disease stage to identify themes regarding reasons for delayed treatment. We then completed a questionnaire-based study mailed to 5,314 patients with a Lyme disease diagnosis or blood test followed by an antibiotic order and concluded that one-third of patients reported delayed treatment.

We identified several factors related to treatment delays, including insurance status, presence of rash, season of diagnosis, the first medical provider contacted about the symptoms, and earlier diagnosis of chronic fatigue syndrome.


  • Moon K, Pollak J, Poulsen M, Heaney C, Hirsch AG, Schwartz B. Risk factors for Lyme disease stage and manifestation using electronic health records. BMC Infectious Disease. 2022; 1–13.
  • Heaney C, Moon K, Ostfeld R, Pollak J, Poulsen M, Hirsch AG, DeWalle J, Aucott J, Schwartz BS. Relations of per-residential temperature and humidity in tick-life-cycle relevant periods with human Lyme disease risk in Pennsylvania, USA. Science of the Total Environment. 2021 Nov 15; 795:148697.
  • Hirsch AG, Poulsen MN, Nordberg C, Moon KA, Rebman A, Aucott J, Heaney CD, Schwartz BS. Risk factors and outcomes of treatment delays in Lyme disease: a population-based retrospective cohort study. Frontiers in Medicine. November 2020.
  • Moon KA, Pollak J, Poulsen MN, Hirsch AG, DeWalle J, Heaney CD, Aucott JN, Schwartz BS. Peridomestic and community-wide landscape risk factors for Lyme disease across a range of community contexts in Pennsylvania. Environmental Research. 2019; 178: 108649.
  • Moon KA, Pollak J, Hirsch AG, Aucott JN, Nordberg C, Heaney CD, Schwartz BS. Epidemiology of Lyme disease in Pennsylvania 2006–2014 using electronic health records. Ticks and Tick-borne Diseases. 2018 Oct 26.
  • Hirsch AG, Herman RJ, Rebman A, Moon KA, Aucott J, Heaney C, Schwartz BS. Obstacles to diagnosis and treatment of Lyme disease in the USA: a qualitative study. BMJ Open. 2018 Jun 1;8(6):e021367.
Childhood obesity

Childhood obesity can put children at risk of poor health outcomes. Our research has leveraged the geographically diverse region served by Geisinger—including many rural areas—to examine how community environments can contribute to, or protect, children from excessive weight gain.

The CCEH also collaborates with Geisinger’s Center for Obesity & Metabolic Research to evaluate whether community features such as community socioeconomic deprivation, rurality, perception of neighborhood and food access modify the effectiveness of interventions to address obesity in children.

Past projects

Our prior research in childhood obesity was funded by the Robert Wood Johnson Foundation and the National Institutes of Health as part of the Johns Hopkins systems-oriented childhood obesity center.

The CCEH evaluated the relation of community features (including the food, land use, physical activity and social environments) and interventions of the health system (including use of certain medications that were hypothesized to be weight-promoting) with body mass index by studying more than 160,000 children with a Geisinger primary care provider.

We reported associations between the built and social environment and body mass index in children and adolescents. We also found novel associations of antibiotics, medications for attention deficit hyperactivity disorder, and medications for anxiety and depression, with weight gain in adolescents.

From this cohort of children, we recruited youth ages 10 to 15 years and their parents (dyads) sampled from communities geographically distributed across the Geisinger service area that represented a range of obesogenic and obeso-protective environments. Our team conducted home visits with 408 participating dyads and collected behavioral and demographic data through self-administered questionnaires and anthropometric measures of both the youth and a parent.

We found that youth from food insecure households, compared to food secure households, had a higher mean body mass index and lower mean healthy home food availability. We also used these data to compare direct observation of built environment features with the use of secondary data to characterize such features in their associations with youth physical activity and sedentary behavior across heterogeneous geographies.


  • Bailey-Davis L, Moore AM, Poulsen M, Dzewaltowski DA, Cumming S. Comparing enhancements to well-child visits in the prevention of obesity: ENCIRCLE cluster-randomized controlled trial. BMC Public Health. 22(10: 1 – 13).
  • Poulsen MN, Glass TA, Pollak J, Bandeen-Roche K, Hirsch AG, Bailey-Davis L, Schwartz BS. Associations of multidimensional socioeconomic and built environment factors with body mass index trajectories among youth in geographically heterogeneous communities. Preventive Medicine Reports. 2019; 15: 100939.
  • Poulsen M, Bailey-Davis L, Pollak J, Hirsch AG, Schwartz BS. Household food insecurity and home food availability in relation to youth diet, body mass index, and adiposity. Journal of the Academy of Nutrition and Dietetics. 2019; 119(10): 1666 – 1675.
  • Poulsen MN, Knapp EA, Hirsch AG, Bailey-Davis L, Pollak J, Schwartz BS. Comparing objective measures of the built environment in their associations with youth physical activity and sedentary behavior across heterogeneous geographies. Health & Place 2018; 49: 30-38.
  • Poulsen MN, Pollak J, Bailey-Davis L, Hirsch AG, Glass TA, Schwartz BS. Associations of prenatal and childhood antibiotic use with child body mass index at age three years. Obesity 2017; 25: 438-444.
  • Dunstan J, Bressler JP, Moran TH, Pollak JS, Hirsch AG, Bailey-Davis L, Glass TA, Schwartz BS. 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. Clinical Epigenetics 2017; 9: 29.
  • Bailey-Davis L, Poulsen MN, Hirsch AG, Pollak J, Glass TA, Schwartz BS. Home food rules in relation to youth eating behaviors, body mass index, waist circumference, and percent body fat. J Adolescent Health 2017; 60: 270-276.
  • Schwartz BS, Pollak J, Bailey-Davis L, Hirsch AG, Cosgrove SE, Nau C, Kress A, Glass TA, Bandeen-Roche K. Antibiotic use and childhood body mass index trajectory. Internat J Obesity, 2016; 40: 615-21.
  • Schwartz BS, Glass TA, Pollak J, Hirsch AG, Bailey-Davis L, Bandeen-Roche K. Depression, its co-morbidities and treatment, and childhood body mass index trajectories. Obesity, 2016; 24: 2585-2592.
  • Nau C, Ellis H, Huang H, Schwartz BS, Hirsch A, Bailey-Davis L, Kress AM, Pollak J, Glass TA. Exploring the forest instead of the trees: An innovative method for defining obesogenic and obesoprotective environments. Health & Place, 2015; 35: 136-46.
  • Nau C, Schwartz BS, Bandeen-Roche K, Liu A, Pollak J, Hirsch A, Bailey-Davis L, Glass TA. Community socioeconomic deprivation and obesity trajectories in children using electronic health records. Obesity 2015; 23: 207-12.
  • Schwartz BS, Bailey-Davis L, Bandeen-Roche K, Pollak J, Hirsch AG, Nau C, Liu AY, Glass TA. Attention deficit disorder, stimulant use, and childhood body mass index trajectory. Pediatrics 2014; 133: 688-76.
  • Schwartz BS, Stewart WF, Godby S, Pollak J, DeWalle J, Larson SL, Mercer DG, Glass TA. Body mass index and the built and social environments in children and adolescents using electronic health records. Am J Prev Med 2011; 41: e17-28.
  • Feng J, Glass TA, Curriero FC, Stewart WF, Schwartz BS. The built environment and obesity: a systematic review of the epidemiologic evidence. Health & Place 2010; 16: 175-90.
Industrial farm animal production

Communities living near animal feeding operations may face increased risk of certain health problems. These large, densely-packed livestock operations are a source of zoonotic pathogens that can spread through the environment to local communities, including through the use of animal manure to fertilize crop fields. They have also been shown to be a source of air pollution. 

Our research group has examined several health outcomes related to animal feeding operations, including concentrated animal feeding operations (CAFOs) and concentrated animal operations (CAOs) in Pennsylvania. 

The incidence of methicillin-resistant Staphylococcus aureus (MRSA) in the region had increased dramatically over the decade before we commenced our work, with over 4,000 cases during this period. During this time, community-associated infections (CA-MRSA) surpassed healthcare-associated infections (HA-MRSA) in incidence. 

Our research group made several interesting and novel observations, studying swine and dairy/veal operations, which were summarized in peer-reviewed publications. We found: 

  1. The incidence of CA-MRSA increased by over 30 percent per year while that of HA-MRSA increased by five percent per year;
  2. CA-MRSA cases exceeded HA-MRSA cases;
  3. Aspects of both the farms on which animals were raised and the crop fields to which manure was applied were associated with increased risk of MRSA infection; and
  4. Certain molecular subtypes not previously associated with these animal operations were associated with human MRSA infections.

We continued this work by evaluating these operations in relation to other health impacts. Additionally, with funding from the Fisher Center Discovery Program in the Johns Hopkins School of Medicine, we investigated other disease risks associated with living near large, densely populated poultry operations.

Considering poultry carry zoonotic bacteria (for example, Campylobacter, E. coli, Salmonella) that can cause gastroenteritis in humans, one study assessed whether closer residential proximity to more and larger poultry operations was associated with diarrheal illness, taking weather-related variables like precipitation into account. 

As a source of air pollution, animal feeding operations can also compromise the respiratory health of individuals living near them, potentially increasing the risk of pneumonia. Thus, in other studies, we examined whether proximity to poultry operations was related to diagnosis with community-acquired pneumonia and asthma exacerbations.


  • Poulsen MN, Pollak J, Sills DL, Casey JA, Nachman KE, Cosgrove SE, Stewart D, Schwartz BS. High-density poultry operations and community-acquired pneumonia in Pennsylvania. Environmental Epidemiology 2018.
  • Poulsen MN, Pollak J, Sills DL, Casey JA, Rasmussen SG, Nachman KE, Cosgrove SE, Stewart D, Schwartz BS. Residential proximity to high-density poultry operations associated with campylobacteriosis and infectious diarrhea. International Journal of Hygiene and Environmental Health, 2018; 221: 323-333.
  • Rasmussen SG, Casey JA, Bandeen-Roche K, Schwartz BS. Proximity to industrial food animal production and asthma exacerbations in Pennsylvania, 2005-2012. Int J Environ Res Public Health 2017; 14: E362.
  • Casey JA, Shopsin B, Cosgrove SE, Curriero FC, Nachman KE, Rose H, Schwartz BS. Molecular characterization of MRSA infection and association with high-density livestock production in Pennsylvania, USA. Environ Health Perspect 2014; 122: 464-70.
  • Casey JA and Schwartz BS. Swine livestock production as a risk factor for community associated MRSA in Pennsylvania. Alliance for the Prudent Use of Antibiotics (APUA) newsletter, 2013; 31: 9-12.
  • Casey JA, Curriero FC, Cosgrove SE, Nachman KE, Schwartz BS. High-density livestock operations, crop field application of manure, and risk of community-associated methicillin-resistant Staphylococcus aureus infection in Pennsylvania. JAMA Intern Med 2013; 173: 1980-90.
  • Casey JA, Stewart WF, Cosgrove SE, Pollak J, Schwartz BS. A population-based study of the epidemiology and clinical features of methicillin-resistant Staphylococcus aureus infection in Pennsylvania 2001-2010. Epidemiology & Infection 2013; 141: 1166-79.
Substance use disorders

Contextual factors, such as socioeconomic decline and social cohesion, have long been understood to increase risk for substance use disorders, but are among the least studied influences on substance misuse.

With funding from the National Institute on Drug Abuse, researchers in the CCEH are leveraging longitudinal electronic health record data; community data on socioeconomic, social, and natural environments; and questionnaires to investigate the community conditions that contribute to opioid misuse, drive geographic variations in opioid use disorder (OUD), and differentially impact retention in medication treatment for OUD in Pennsylvania.

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