University campuses represent an opportunity to advance the understanding of how the built environment influences health. We used de-identified billing codes from a private university clinic serving undergraduate students for academic years 2008 through 2012 linked to students’ residential history and demographic information. We used a two-stage, hierarchical regression model to study the differences in the reported prevalence of diagnostic groups by dorm and the association between building characteristics and disease incidence rates. We found significant differences in the prevalence of mental health (MH), upper respiratory infections (URI) and substance abuse between freshmen and upperclassmen. In addition, we found systematic differences in the relative rates of URI and MH diagnoses across dorms. Among upperclasmen dorms, the only mechanically ventilated building had a lower rate of allergy cases. An increase in available dorm space of 100 ft2 per student was associated to a decrease in 10.8 URI cases per 100 students per academic year (p < 0.01). Construction age was also associated with lower incidence rate of MH (1.1 fewer diagnoses/100 students-academic year for every 25-year increment in building age, p = 0.04). These results suggest the potential for the use of electronic health records (EHR) to identify differential health issues faced by students depending on the housing characteristics and on the stages of their academic career.
Subscribe to Journal
Get full journal access for 1 year
only $19.83 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Percentage of undergraduates receiving financial aid, by type and source of aid and selected student characteristics: 2015–16. The Condition of Education—Postsecondary Education—Postsecondary Students—Undergraduate Enrollment—Indicator. Institute of Education Sciences; 2019. https://nces.ed.gov/programs/coe/indicator_cha.asp.
Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62:593–602.
Schug TT, Janesick A, Blumberg B, Heindel JJ. Endocrine disrupting chemicals and disease susceptibility. J Steroid Biochem Mol Biol. 2011;127:204–15.
Jaques N, Taylor S, Azaria A, Ghandeharioun A, Sano A, Picard R. Predicting students’ happiness from physiology, phone, mobility, and behavioral data. In: Proceeding of the 2015 International Conference on Affective Computing and Intelligent Interaction (ACII). IEEE; 2015. p. 222–8.
Zimmerman DJ. Peer effects in academic outcomes: evidence from a natural experiment. Rev Econ Stat. 2003;85:9–23.
Thomsen J, Eikemo TA. Aspects of student housing satisfaction: a quantitative study. J Hous Built Environ. 2010;25:273–93.
Eisenberg D, Golberstein E, Whitlock JL. Peer effects on risky behaviors: new evidence from college roommate assignments. J Health Econ. 2014;33:126–38.
Sundell J, Levin H, Nazaroff WW, Cain WS, Fisk WJ, Grimsrud DT, et al. Ventilation rates and health: multidisciplinary review of the scientific literature. Indoor Air. 2011;21:191–204.
Jaakkola MS, Quansah R, Hugg TT, Heikkinen SA, Jaakkola JJ. Association of indoor dampness and molds with rhinitis risk: a systematic review and meta-analysis. J Allergy Clin Immunol. 2013;132:1099–110.
Mendell MJ, Mirer AG, Cheung K, Tong M, Douwes J. Respiratory and allergic health effects of dampness, mold, and dampness-related agents: a review of the epidemiologic evidence. Environ Health Perspect. 2011;119:748–56.
Van Bommel WJ, Van den Beld GJ. Lighting for work: a review of visual and biological effects. Lighting Res Technol. 2004;36:255–66.
Basner M, Babisch W, Davis A, Brink M, Clark C, Janssen S, et al. Auditory and non-auditory effects of noise on health. lancet. 2014;383:1325–32.
Seppanen O, Fisk WJ, Faulkner D. Control of temperature for health and productivity inoffices. LBNL-55448. ASHRAE transactions;2004. 111.
Turner JC, Keller A. College health surveillance network: epidemiology and health care utilization of college students at US 4-year universities. J Am Coll Health. 2015;63:530–8.
Sherman MH, Logue JM, Singer BC. Infiltration effects on residential pollutant concentrations for continuous and intermittent mechanical ventilation approaches. HvacR Res. 2011;17:159–73.
Laboratory-Confirmed Influenza Hospitalizations. FluView. Center for Disease Control; 2015. http://gis.cdc.gov/grasp/fluview/FluHospChars.html.
Chang SS, Stuckler D, Yip P, Gunnell D. Impact of 2008 global economic crisis on suicide: time trend study in 54 countries. Bmj. 2013;347:f5239.
Lipson SK, Lattie EG, Eisenberg D. Increased rates of mental health service utilization by US college students: 10-year population-level trends (2007–2017). Psychiatr Serv. 2018;70:60–63.
Ham LS, Hope DA. College students and problematic drinking: a review of the literature. Clin Psychol Rev. 2003;23:719–59.
Prokhorov AV, Warneke C, Moor Cd, Emmons KM, Jones MM, Rosenblum C, et al. Self-reported health status, health vulnerability, and smoking behavior in college students: Implications for intervention. Nicotine Tob Res. 2003;5:545–52.
Blake K, Kellerson RL, Simic A. Measuring overcrowding in housing. U.S. Department of Housing and Urban Development, Office of Policy Development and Research. Econometrica Inc., ICF International; 2007.
Rudnick SN, Milton DK. Risk of indoor airborne infection transmission estimated from carbon dioxide concentration. Indoor Air. 2003;13:237–45.
Boone SA, Gerba CP. The occurrence of influenza A virus on household and day care center fomites. J Infect. 2005;51:103–9.
Thomas Y, Vogel G, Wunderli W, Suter P, Witschi M, Koch D, et al. Survival of influenza virus on banknotes. Appl Environ Microbiol. 2008;74:3002–7.
Noakes CJ, Beggs CB, Sleigh PA, Kerr KG. Modelling the transmission of airborne infections in enclosed spaces. Epidemiol Infect. 2006;134:1082–91.
Sun Y, Wang Z, Zhang Y, Sundell J. In China, students in crowded dormitories with a low ventilation rate have more common colds: evidence for airborne transmission. PloS one. 2011;6:e27140.
Spengler JD, Jaakkola JJ, Parise H, Katsnelson BA, Privalova LI, Kosheleva AA. Housing characteristics and children’s respiratory health in the Russian Federation. Am J Public Health. 2004;94:657–62.
United Nations Economic Commission for Europe. Country profiles on the housing sector. Russian Federation. Geneva, Switzerland: United Nations; 2004
Baum A, Valins S. Architecture, social interation, and crowding. Trans NY Acad Sci. 1974;36:793–9.
We thank the division of medical records at the university health services that compiled the clinical datasets for our study. This study was sponsored by the National Science Foundation EFRI-1038264 award. Partial sponsorship was also received from the Akira Yamaguchi Endowment and the Mexican National Council of Science and Technology (CONACYT). FD was supported by grant R01 ES024332.
Conflict of interest
The authors declare that they have no conflict of interest.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Cedeno Laurent, J.G., Allen, J.G., McNeely, E. et al. Influence of the residential environment on undergraduate students’ health. J Expo Sci Environ Epidemiol 30, 320–327 (2020). https://doi.org/10.1038/s41370-019-0196-4
- Undergraduate student health
- Electronic health records
- Indoor environmental quality
- College students
- Mental health
- Respiratory infections