{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T13:58:42Z","timestamp":1780063122484,"version":"3.54.0"},"reference-count":69,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,3,8]],"date-time":"2023-03-08T00:00:00Z","timestamp":1678233600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Delaware Watershed Research Fund","award":["DWRF-17-03"],"award-info":[{"award-number":["DWRF-17-03"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Good water quality safeguards public health and provides economic benefits through recreational opportunities for people in urban and suburban environments. However, expanding impervious areas and poorly managed sanitary infrastructures result in elevated concentrations of fecal indicator bacteria and waterborne pathogens in adjacent waterways and increased waterborne illness risk. Watershed characteristics, such as urban land, are often associated with impaired microbial water quality. Within the proximity of the New York\u2013New Jersey\u2013Pennsylvania metropolitan area, the Musconetcong River has been listed in the Clean Water Act\u2019s 303 (d) List of Water Quality-Limited Waters due to high concentrations of fecal indicator bacteria (FIB). In this study, we aimed to apply spatial stream network (SSN) models to associate key land use variables with E. coli as an FIB in the suburban mixed-land-use Musconetcong River watershed in the northwestern New Jersey. The SSN models explicitly account for spatial autocorrelation in stream networks and have been widely utilized to identify watershed attributes linked to deteriorated water quality indicators. Surface water samples were collected from the five mainstem and six tributary sites along the middle section of the Musconetcong River from May to October 2018. The log10 geometric means of E. coli concentrations for all sampling dates and during storm events were derived as response variables for the SSN modeling, respectively. A nonspatial model based on an ordinary least square regression and two spatial models based on Euclidean and stream distance were constructed to incorporate four upstream watershed attributes as explanatory variables, including urban, pasture, forest, and wetland. The results indicate that upstream urban land was positively and significantly associated with the log10 geometric mean concentrations of E. coli for all sampling cases and during storm events, respectively (p &lt; 0.05). Prediction of E. coli concentrations by SSN models identified potential hot spots prone to water quality deterioration. The results emphasize that anthropogenic sources were the main threats to microbial water quality in the suburban Musconetcong River watershed. The SSN modeling approaches from this study can serve as a novel microbial water quality modeling framework for other watersheds to identify key land use stressors to guide future urban and suburban water quality restoration directions in the USA and beyond.<\/jats:p>","DOI":"10.3390\/ijerph20064743","type":"journal-article","created":{"date-parts":[[2023,3,8]],"date-time":"2023-03-08T02:30:23Z","timestamp":1678242623000},"page":"4743","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Predicting Fecal Indicator Bacteria Using Spatial Stream Network Models in A Mixed-Land-Use Suburban Watershed in New Jersey, USA"],"prefix":"10.3390","volume":"20","author":[{"given":"Tsung-Ta David","family":"Hsu","sequence":"first","affiliation":[{"name":"New Jersey Center for Water Science and Technology, Montclair State University, Montclair, NJ 07043, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4470-7011","authenticated-orcid":false,"given":"Danlin","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Earth and Environmental Studies, Montclair State University, Montclair, NJ 07043, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meiyin","family":"Wu","sequence":"additional","affiliation":[{"name":"New Jersey Center for Water Science and Technology, Montclair State University, Montclair, NJ 07043, USA"},{"name":"Department of Biology, Montclair State University, Montclair, NJ 07043, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"149","DOI":"10.2166\/wh.2006.001","article-title":"Waterborne pathogens in urban watersheds","volume":"5","author":"Arnone","year":"2007","journal-title":"J. Water Health"},{"key":"ref_2","unstructured":"Schneider, I.E. (2009). The Water Environment of Cities, Springer."},{"key":"ref_3","unstructured":"USEPA (1984). Health Effects Criteria for Fresh Recreational Waters, USEPA."},{"key":"ref_4","unstructured":"USEPA (2012). Recreational Water Quality Criteria, USEPA."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/ije\/27.1.1","article-title":"Review of epidemiological studies on health effects from exposure to recreational water","volume":"27","year":"1998","journal-title":"Int. J. Epidemiol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1002\/env.535","article-title":"A model for estimating the incidence of swimming-related gastrointestinal illness as a function of water quality indicators","volume":"13","author":"Wymer","year":"2002","journal-title":"Environmetrics"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3400","DOI":"10.1007\/s11356-012-0865-5","article-title":"A recreational water quality index using chemical, physical and microbiological parameters","volume":"19","author":"Almeida","year":"2012","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Wymer, L.J., Wade, T.J., and Dufour, A.P. (2013). Equivalency of risk for a modified health endpoint: A case from recreational water epidemiology studies. BMC Public Health, 13.","DOI":"10.1186\/1471-2458-13-459"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1016\/j.jenvman.2006.12.013","article-title":"Assessing the US Clean Water Act 303(d) listing process for determining impairment of a waterbody","volume":"86","author":"Keller","year":"2008","journal-title":"J. Environ. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"987","DOI":"10.13031\/2013.21739","article-title":"Modeling bacteria fate and transport in watersheds to support TMDLs","volume":"49","author":"Benham","year":"2006","journal-title":"Trans. ASABE"},{"key":"ref_11","unstructured":"National Research Council (2001). Assessing the TMDL Approach to Water Quality Management, National Research Council."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.watres.2016.04.064","article-title":"Modeling fate and transport of fecally-derived microorganisms at the watershed scale: State of the science and future opportunities","volume":"100","author":"Cho","year":"2016","journal-title":"Water Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1317","DOI":"10.2134\/jeq2009.0392","article-title":"Assessment of Total Maximum Daily Load Implementation Strategies for Nitrate Impairment of the Raccoon River, Iowa","volume":"39","author":"Jha","year":"2010","journal-title":"J. Environ. Qual."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1623\/hysj.52.4.713","article-title":"Comparing artificial neural networks and regression models for predicting faecal coliform concentrations","volume":"52","author":"Mas","year":"2007","journal-title":"Hydrol. Sci. J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/j.watres.2016.05.024","article-title":"Modeling spatiotemporal bacterial variability with meteorological and watershed land-use characteristics","volume":"100","author":"Cha","year":"2016","journal-title":"Water Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1186\/s12302-019-0250-9","article-title":"Prediction of fecal indicator organism concentrations in rivers: The shifting role of environmental factors under varying flow conditions","volume":"31","author":"Herrig","year":"2019","journal-title":"Environ. Sci. Eur."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"136814","DOI":"10.1016\/j.scitotenv.2020.136814","article-title":"Prediction of recreational water safety using Escherichia coli as an indicator: Case study of the Passaic and Pompton rivers, New Jersey","volume":"714","author":"Rossi","year":"2020","journal-title":"Sci. Total. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.watres.2015.08.006","article-title":"Development of multiple linear regression models as predictive tools for fecal indicator concentrations in a stretch of the lower Lahn River, Germany","volume":"85","author":"Herrig","year":"2015","journal-title":"Water Res."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Acevedo, M.F. (2012). Data Analysis and Statistics for Geography, Environmental Science, and Engineering, CRC Press.","DOI":"10.1201\/b13675"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"234","DOI":"10.2307\/143141","article-title":"A Computer Movie Simulating Urban Growth in the Detroit Region","volume":"46","author":"Tobler","year":"1970","journal-title":"Econ. Geogr."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1111\/ele.12084","article-title":"Modelling dendritic ecological networks in space: An integrated network perspective","volume":"16","author":"Peterson","year":"2013","journal-title":"Ecol. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1002\/wat2.1023","article-title":"Applications of spatial statistical network models to stream data","volume":"1","author":"Isaak","year":"2014","journal-title":"WIREs Water"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3736","DOI":"10.1021\/es803236j","article-title":"Modern space\/time geostatistics using river distances: Data integration of turbidity and E. coli measurements to assess fecal contamination along the Raritan River in New Jersey","volume":"43","author":"Money","year":"2009","journal-title":"Environ. Sci. Technol."},{"key":"ref_24","unstructured":"USEPA (2011). Using Microbial Source Tracking to Support TMDL Development and Implementation, USEPA."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1139\/cjfas-2016-0247","article-title":"Scalable population estimates using spatial-stream-network (SSN) models, fish density surveys, and national geospatial database frameworks for streams","volume":"74","author":"Isaak","year":"2017","journal-title":"Can. J. Fish. Aquat. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"944","DOI":"10.1111\/1752-1688.12543","article-title":"Improving Predictive Models of In-Stream Phosphorus Concentration Based on Nationally-Available Spatial Data Coverages","volume":"53","author":"Scown","year":"2017","journal-title":"JAWRA J. Am. Water Resour. Assoc."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1080\/2150704X.2018.1475768","article-title":"River network based characterization of errors in remotely sensed rainfall products in hydrological applications","volume":"9","author":"ElSaadani","year":"2018","journal-title":"Remote Sens. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Gendaszek, A.S., Dunham, J.B., Torgersen, C.E., Hockman-Wert, D.P., Heck, M.P., Thorson, J., Mintz, J., and Allai, T. (2020). Land-Cover and Climatic Controls on Water Temperature, Flow Permanence, and Fragmentation of Great Basin Stream Networks. Water, 12.","DOI":"10.3390\/w12071962"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1007\/s10651-006-0022-8","article-title":"Spatial statistical models that use flow and stream distance","volume":"13","author":"Hoef","year":"2006","journal-title":"Environ. Ecol. Stat."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1198\/jasa.2009.ap08248","article-title":"A Moving Average Approach for Spatial Statistical Models of Stream Networks","volume":"105","author":"Hoef","year":"2010","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"297","DOI":"10.2307\/1400521","article-title":"Blackbox Kriging: Spatial Prediction without Specifying Variogram Models","volume":"1","author":"Barry","year":"1996","journal-title":"J. Agric. Biol. Environ. Stat."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"840","DOI":"10.1016\/j.scitotenv.2017.08.151","article-title":"Using spatial-stream-network models and long-term data to understand and predict dynamics of faecal contamination in a mixed land-use catchment","volume":"612","author":"Neill","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Hunt, A., Wu, M., Hsu, T.-T., Roberts-Lawler, N., Miller, J., Rossi, A., and Lee, L. (2021). Picking Up Where the TMDL Leaves Off: Using the Partnership Wild and Scenic River Framework for Collaborative River Restoration. Sustainability, 13.","DOI":"10.3390\/su13041878"},{"key":"ref_34","unstructured":"Stinnette, I., Taylor, M., Kerr, L., Pirani, R., Lipuma, S., and Lodge, J. (2018). State of the Estuary 2018, Hudson River Foundation."},{"key":"ref_35","unstructured":"New Jersey Department of Environmental Protection (2003). Total Maximum Daily Loads for Fecal Coliform to Address 28 Streams in the Northwest Water Region, New Jersey Department of Environmental Protection."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Anderson, J.R., Hardy, E.E., Roach, J.T., and Witmer, R.E. (1976). A Land Use and Land Cover Classification System for Use with Remote Sensor Data, US Government Printing Office.","DOI":"10.3133\/pp964"},{"key":"ref_37","unstructured":"Restoration, R.W. (2011). Water Quality Monitoring Data Report, Rutgers Cooperative Extension Water Resources Program."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1002\/env.995","article-title":"Spatial modelling and prediction on river networks: Up model, down model or hybrid?","volume":"21","author":"Garreta","year":"2010","journal-title":"Environmetrics"},{"key":"ref_39","first-page":"1","article-title":"SSN: An R Package for Spatial Statistical Modeling on Stream Networks","volume":"56","author":"Peterson","year":"2014","journal-title":"J. Stat. Softw."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/0166-0462(92)90038-3","article-title":"Spatial autocorrelation and neighborhood quality","volume":"22","author":"Dubin","year":"1992","journal-title":"Reg. Sci. Urban Econ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/0166-0462(95)02111-6","article-title":"Simple diagnostic tests for spatial dependence","volume":"26","author":"Anselin","year":"1996","journal-title":"Reg. Sci. Urban Econ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1016\/j.scitotenv.2016.01.026","article-title":"Monitoring and predicting the fecal indicator bacteria concentrations from agricultural, mixed land use and urban stormwater runoff","volume":"550","author":"Ventura","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_43","unstructured":"Peterson, E.E. (2017). STARS: Spatial Tools for the Analysis of River Systems version 2.0. 6\u2014A tutorial, Queensland University of Technology."},{"key":"ref_44","unstructured":"R Core Team (2016). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1093\/biomet\/52.3-4.591","article-title":"An analysis of variance test for normality (complete samples)","volume":"52","author":"Shapiro","year":"1965","journal-title":"Biometrika"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1007\/s10661-005-9156-7","article-title":"Patterns of Spatial Autocorrelation in Stream Water Chemistry","volume":"121","author":"Peterson","year":"2006","journal-title":"Environ. Monit. Assess."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1006\/jmva.1993.1034","article-title":"The Asymptotic Distribution of REML Estimators","volume":"45","author":"Cressie","year":"1993","journal-title":"J. Multivar. Anal."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.chemolab.2005.04.008","article-title":"Variance reduction in estimating classification error using sparse datasets","volume":"79","author":"Beleites","year":"2005","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"6018","DOI":"10.1002\/2015WR018349","article-title":"Spatial statistical network models for stream and river temperature in New England, USA","volume":"52","author":"Detenbeck","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1007\/s10661-018-6646-y","article-title":"Monitoring spatial and temporal variation of dissolved oxygen and water temperature in the Savannah River using a sensor network","volume":"190","author":"Post","year":"2018","journal-title":"Environ. Monit. Assess."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1016\/j.envsoft.2014.06.019","article-title":"Improving the predictive power of spatial statistical models of stream macroinvertebrates using weighted autocovariance functions","volume":"60","author":"Frieden","year":"2014","journal-title":"Environ. Model. Softw."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"100773","DOI":"10.1016\/j.ecocom.2019.100773","article-title":"Testing the River Continuum Concept with geostatistical stream-network models","volume":"39","author":"Larsen","year":"2019","journal-title":"Ecol. Complex."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"7775","DOI":"10.1021\/acs.est.8b01178","article-title":"Geostatistical Prediction of Microbial Water Quality Throughout a Stream Network Using Meteorology, Land Cover, and Spatiotemporal Autocorrelation","volume":"52","author":"Holcomb","year":"2018","journal-title":"Environ. Sci. Technol."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Franklin, R.B., and Mills, A.L. (2007). The Spatial Distribution of Microbes in the Environment, Springer.","DOI":"10.1007\/978-1-4020-6216-2"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1180","DOI":"10.1016\/j.scitotenv.2017.07.104","article-title":"Combined sewer overflow events and childhood emergency department visits: A case-crossover study","volume":"607\u2013608","author":"Brokamp","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1289\/ehp.5914","article-title":"Septic system density and infectious diarrhea in a defined population of children","volume":"111","author":"Borchardt","year":"2003","journal-title":"Environ. Health Perspect."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1725","DOI":"10.1016\/S0043-1354(01)00394-3","article-title":"Faecal-indicator concentrations in waters draining lowland pastoral catchments in the UK: Relationships with land use and farming practices","volume":"36","author":"Crowther","year":"2002","journal-title":"Water Res."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1289\/ehp.8839","article-title":"Impacts of Waste from Concentrated Animal Feeding Operations on Water Quality","volume":"115","author":"Burkholder","year":"2007","journal-title":"Environ. Health Perspect."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"910","DOI":"10.1111\/jam.13689","article-title":"Impact of storm runoff on Salmonella and Escherichia coli prevalence in irrigation ponds of fresh produce farms in southern Georgia","volume":"124","author":"Harris","year":"2018","journal-title":"J. Appl. Microbiol."},{"key":"ref_60","unstructured":"Mitsch, W.J., and Gosselink, J.G. (2015). Wetlands, John Wiley & Sons."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.ecoleng.2008.05.001","article-title":"Removal of wastewater pathogen indicators in a constructed wetland in Leon, Spain","volume":"33","author":"Molleda","year":"2008","journal-title":"Ecol. Eng."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1061\/(ASCE)EE.1943-7870.0000107","article-title":"Indicator Bacteria Removal in Storm-Water Best Management Practices in Charlotte, North Carolina","volume":"135","author":"Hathaway","year":"2009","journal-title":"J. Environ. Eng."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1016\/j.ecoleng.2017.02.051","article-title":"Towards sustainable protection of public health: The role of an urban wetland as a frontline safeguard of pathogen and antibiotic resistance spread","volume":"108","author":"Hsu","year":"2017","journal-title":"Ecol. Eng."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"201","DOI":"10.3389\/fenvs.2022.836289","article-title":"Constructed Wetlands for Reclamation and Reuse of Wastewater and Urban Stormwater: A Review","volume":"10","author":"Biswal","year":"2022","journal-title":"Front. Environ. Sci."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.2105\/AJPH.91.8.1194","article-title":"The Association Between Extreme Precipitation and Waterborne Disease Outbreaks in the United States, 1948\u20131994","volume":"91","author":"Curriero","year":"2001","journal-title":"Am. J. Public Health"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1080\/09603120600641326","article-title":"A role of high impact weather events in waterborne disease outbreaks in Canada, 1975\u20132001","volume":"16","author":"Thomas","year":"2006","journal-title":"Int. J. Environ. Health Res."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1056\/NEJM199407213310304","article-title":"A Massive Outbreak in Milwaukee of Cryptosporidium Infection Transmitted through the Public Water Supply","volume":"331","author":"Hoxie","year":"1994","journal-title":"N. Engl. J. Med."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"De Roos, A.J., Kondo, M.C., Robinson, L.F., Rai, A., Ryan, M., Haas, C.N., Lojo, J., and Fagliano, J.A. (2020). Heavy precipitation, drinking water source, and acute gastrointestinal illness in Philadelphia, 2015\u20132017. PLoS ONE, 15.","DOI":"10.1371\/journal.pone.0229258"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Dupigny-Giroux, L.A., Mecray, E.L., Lemcke-Stampone, M.D., Hodgkins, G.A., Lentz, E.E., Mills, K.E., Lane, E.D., Miller, R., Hollinger, D.Y., and Solecki, W.D. (2018). Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, U.S. Global Change Research Program.","DOI":"10.7930\/NCA4.2018.CH18"}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/20\/6\/4743\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:50:30Z","timestamp":1760122230000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/20\/6\/4743"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,8]]},"references-count":69,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2023,3]]}},"alternative-id":["ijerph20064743"],"URL":"https:\/\/doi.org\/10.3390\/ijerph20064743","relation":{},"ISSN":["1660-4601"],"issn-type":[{"value":"1660-4601","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,8]]}}}