Modelling personal temperature exposure using household and outdoor temperature and questionnaire data: implications for epidemiological studies

Modelling personal temperature exposure using household and outdoor temperature and questionnaire data: implications for epidemiological studies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Modelling personal temperature exposure using household and outdoor temperature and questionnaire data: implications for epidemiological studies Xi Xia, Ka Hung Chan, Yue Niu, Cong Liu, Yitong Guo, Kin-Fai Ho, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4547455/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract The reliance of outdoor exposure data in epidemiological studies on temperature entails important uncertainties from personal exposure misclassification. We analysed ~88,000 concurrent person-hours of measured personal, household (kitchen and living room), and outdoor temperatures collected in the summer (MAY-SEP 2017) and winter (NOV 2017-JAN 2018) in rural and urban China. The temperatures across microenvironments were strongly correlated (Spearman’s ρ: 0.86-0.92) in summer. In winter, personal temperature was strongly related to household temperatures (ρ: 0.74-0.79) but poorly related to outdoor temperature (ρ: 0.30). Random forest (RF) algorithm identified household and outdoor temperatures and study date as top predictors of personal temperature exposure for both seasons, and heating-related factors were important in winter. Multivariable linear regression and RF models incorporating questionnaire and device data performed satisfactorily in predicting personal exposure in both seasons (R2summer: 0.92; R2winter: 0.68-0.70). Using generalised additive mixed effect models, we found consistent U-shaped associations between measured and predicted personal temperature exposures and heart rate (lowest at ~14.5ºC), but a weak positive linear association with outdoor temperature. Personal and outdoor temperatures differ substantially in winter, but prediction models incorporating household and outdoor temperatures and questionnaire data performed satisfactorily. Exposure misclassification from using outdoor temperature may produce inappropriate epidemiological findings. Health sciences/Risk factors Earth and environmental sciences/Environmental sciences climate change epidemiology heart rate temperature wearables Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Full Text Additional Declarations The authors declare no competing interests. Supplementary Files CKBAirTempSupplementaryappendix2Jun2024.pdf Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4547455","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":321229800,"identity":"019d6ebd-ba61-4436-8af0-064bce46650a","order_by":0,"name":"Xi Xia","email":"","orcid":"","institution":"Xi’an Jiaotong University Health Science Center","correspondingAuthor":false,"prefix":"","firstName":"Xi","middleName":"","lastName":"Xia","suffix":""},{"id":321229799,"identity":"164c9acc-6d8a-4d28-bed0-8e394f135011","order_by":1,"name":"Ka Hung Chan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYBACCQYeCMOAgYHxAQMbQwKSFGEtzAYka2GTIEqLZPvZY9IFvxjkzdnPHqsuKLuTx8DeY8Dwo4YhcWYDdi3SPHlp0jP7GAx39uSl3Z5x7lkxA8+xBMaeYwyJs3HYIseQYybN28OQYHAgx+w2b9vhxAaJ5AMMvA0MifNwaeF/A9Vy/o1ZMURLYgPjXzxapCWAtvD8AGq5kWPGDLOFGWQLLodJznhjbM3bIGG44cYbY2mec88S24B+OSxzTMIYl/clzucY3ub5YyNvAGR85im7k9jP3mP48E2NjeyMAzisAQHGNngcHABGDYjEGSsw8AfOwmfyKBgFo2AUjFQAAD1oVgxNtqVjAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-3700-502X","institution":"University of Oxford","correspondingAuthor":true,"prefix":"","firstName":"Ka","middleName":"Hung","lastName":"Chan","suffix":""},{"id":321229801,"identity":"7d23d7ba-9222-4bed-9aa6-b458692755bf","order_by":2,"name":"Yue Niu","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Niu","suffix":""},{"id":321229802,"identity":"4a4a3d23-27dd-434a-b130-4aff052aa559","order_by":3,"name":"Cong Liu","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Cong","middleName":"","lastName":"Liu","suffix":""},{"id":321229803,"identity":"951001e8-4946-4795-afbe-f7e08b8db337","order_by":4,"name":"Yitong Guo","email":"","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Yitong","middleName":"","lastName":"Guo","suffix":""},{"id":321229804,"identity":"f56ecb71-f015-46c0-bf39-40bd10d8921c","order_by":5,"name":"Kin-Fai Ho","email":"","orcid":"https://orcid.org/0000-0001-7464-3437","institution":"The Chinese University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Kin-Fai","middleName":"","lastName":"Ho","suffix":""},{"id":321229805,"identity":"3cd60e9c-0850-4b4e-9b5d-babf690b8067","order_by":6,"name":"Steve Hung-Lam Yim","email":"","orcid":"","institution":"Nanyang Technological University","correspondingAuthor":false,"prefix":"","firstName":"Steve","middleName":"Hung-Lam","lastName":"Yim","suffix":""},{"id":321229806,"identity":"351184af-ca33-4529-9da0-42a4072a9da5","order_by":7,"name":"Baihan Wang","email":"","orcid":"","institution":"University of Oxford","correspondingAuthor":false,"prefix":"","firstName":"Baihan","middleName":"","lastName":"Wang","suffix":""},{"id":321229807,"identity":"beddcf95-6652-4615-8c4e-4da9e6ab782b","order_by":8,"name":"Aiden Doherty","email":"","orcid":"","institution":"University of Oxford","correspondingAuthor":false,"prefix":"","firstName":"Aiden","middleName":"","lastName":"Doherty","suffix":""},{"id":321229808,"identity":"893052cb-cbc1-4475-99e5-22de35887425","order_by":9,"name":"Daniel Avery","email":"","orcid":"https://orcid.org/0000-0002-9823-9575","institution":"University of Oxford","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Avery","suffix":""},{"id":321229809,"identity":"b0ce5dff-a30d-4820-baf9-376864cc3e5c","order_by":10,"name":"Pei Pei","email":"","orcid":"","institution":"Fuwai Hospital Chinese Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Pei","middleName":"","lastName":"Pei","suffix":""},{"id":321229810,"identity":"793ed2f2-f6b8-4e4f-a148-ba724140ec8c","order_by":11,"name":"Canqing Yu","email":"","orcid":"https://orcid.org/0000-0002-0019-0014","institution":"Peking University","correspondingAuthor":false,"prefix":"","firstName":"Canqing","middleName":"","lastName":"Yu","suffix":""},{"id":321229811,"identity":"ef2b1149-2419-45d5-91a6-2c7a6ada64e5","order_by":12,"name":"Dianjianyi Sun","email":"","orcid":"https://orcid.org/0000-0003-3651-6693","institution":"School of Public Health, Peking University Health Science Center","correspondingAuthor":false,"prefix":"","firstName":"Dianjianyi","middleName":"","lastName":"Sun","suffix":""},{"id":321229812,"identity":"50570f4b-b144-4e63-bfb5-74aa1ad205ac","order_by":13,"name":"Jun Lv","email":"","orcid":"https://orcid.org/0000-0001-7916-3870","institution":"Peking University, Department of Epidemiology \u0026 Biostatistics","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Lv","suffix":""},{"id":321229813,"identity":"6a0821ef-9a7c-4ff4-9cf6-5ae722e2e2c8","order_by":14,"name":"Junshi Chen","email":"","orcid":"","institution":"China National Center for Food Safety Risk Assessment","correspondingAuthor":false,"prefix":"","firstName":"Junshi","middleName":"","lastName":"Chen","suffix":""},{"id":321229814,"identity":"1211daa9-ef3f-4732-9232-34b21ea38f4d","order_by":15,"name":"liming Li","email":"","orcid":"https://orcid.org/0000-0001-5873-7089","institution":"Peking University","correspondingAuthor":false,"prefix":"","firstName":"liming","middleName":"","lastName":"Li","suffix":""},{"id":321229815,"identity":"1a829065-de68-4ad5-bd4d-7cafbd1a2125","order_by":16,"name":"Peng Wen","email":"","orcid":"","institution":"Maiji Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Wen","suffix":""},{"id":321229816,"identity":"98441f24-d67c-455b-94c1-c7aa59c1431b","order_by":17,"name":"Shaowei Wu","email":"","orcid":"https://orcid.org/0000-0003-2680-6064","institution":"Xi'an Jiaotong University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Shaowei","middleName":"","lastName":"Wu","suffix":""},{"id":321229817,"identity":"3c2b776d-5499-4bfe-99e3-eacbcb61e309","order_by":18,"name":"Kin Bong Hubert Lam","email":"","orcid":"https://orcid.org/0000-0003-1228-3362","institution":"University of Oxford","correspondingAuthor":false,"prefix":"","firstName":"Kin","middleName":"Bong Hubert","lastName":"Lam","suffix":""},{"id":321229818,"identity":"83c3537f-a61d-44c6-8401-f6dc694a431b","order_by":19,"name":"Haidong Kan","email":"","orcid":"https://orcid.org/0000-0002-1871-8999","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Haidong","middleName":"","lastName":"Kan","suffix":""},{"id":321229819,"identity":"39d29bf4-f707-4cb8-8c16-5eda37ad5101","order_by":20,"name":"Zhengming Chen","email":"","orcid":"https://orcid.org/0000-0001-6423-105X","institution":"Uni of Oxford, Department of Population Health","correspondingAuthor":false,"prefix":"","firstName":"Zhengming","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-06-07 17:15:22","currentVersionCode":2,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4547455/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-4547455/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59955793,"identity":"cc8b07e0-11d6-44bb-ae0e-cd9de56c88fc","added_by":"auto","created_at":"2024-07-09 19:53:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":610298,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLinear regression fitting plots of measured temperature across locations by season\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShaded area around regression lines indicate 95% confidence intervals\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4547455/v2/8d00d4f55fa997df8c9064a3.png"},{"id":59955792,"identity":"ed05a4a9-2765-4442-82a9-fad135f09811","added_by":"auto","created_at":"2024-07-09 19:53:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":508395,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRanked importance of variables identified in Boruta feature selection for personal temperature exposure by season\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFeatures above the horizontal dashed line indicate meets the pre-specified criteria of important features. The direction of association was ascertained from multivariable linear regression of each feature on measured personal temperature, adjusting for age, sex, and study area where appropriate.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4547455/v2/743e83f64181e6effa8dfa99.png"},{"id":59955935,"identity":"7b6eeca3-b88f-4fcf-b999-115af7e23a72","added_by":"auto","created_at":"2024-07-09 20:01:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":293360,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLinear regression fitting plots of measured and predicted personal temperature from the final linear mixed effect and random forest models by season\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShaded area around regression lines indicate 95% confidence intervals. Abbreviations: MLR = multivariable linear regression; RF = random forest.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4547455/v2/a7158b78bd0fe56e1bf982e5.png"},{"id":59956161,"identity":"ff1bcd67-061e-47c8-9cec-45388bb630e2","added_by":"auto","created_at":"2024-07-09 20:09:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":407669,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBland-Altman plots of measured and predicted personal temperature from the final linear mixed effect and random forest models by season\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRegression lines and 95% confidence intervals (shaded area) were obtained from linear regression of the difference between measured and predicted personal temperature on the average of the two. Grey horizontal dashed lines represent the upper and lower limits of agreement (± 1.96SD). Abbreviations: MLR = multivariable linear regression; RF = random forest.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4547455/v2/959bbba18d6a8452e88124c1.png"},{"id":59955797,"identity":"ed3d2eb9-b6d7-4794-b580-edf791abaa01","added_by":"auto","created_at":"2024-07-09 19:53:53","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":343828,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExposure-response functions between measured and predicted temperature and heart rate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChange of hear rate (beat-per-minute) was derived from generalized additive mixed models adjusting for age, sex, region, education, occupation, income, temporal trend, and natural cubic splines with 3 df for fine particulate matter and relative humiditiy. Dashed lines around the exposure-response curve represent 95% confidence intervals. Vertical purple dashed lines indicate the point of lowest heart rate and the corresponding temperature in plots A, D, and F. The indicated range of bpm refers to the difference between the highest mean heart rate estimate from the high temperature end compared to the point of lowest mean heart rate of the exposure-response function. Black vertical lines at the bottom indicate the distribution of exposure data across the temperature range on the x-axis.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4547455/v2/5e512010446b1bd0a6623ae5.png"},{"id":59956697,"identity":"7bb746b6-57c7-43fe-9a47-efb107d423ab","added_by":"auto","created_at":"2024-07-09 20:26:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2626599,"visible":true,"origin":"","legend":"","description":"","filename":"CKBAirTempManuscript25June2024.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4547455/v2_covered_8d66a778-7ac7-4b23-9122-e596e4f6eab0.pdf"},{"id":59955937,"identity":"32253d66-7086-4fb0-86e7-bfa8f187504c","added_by":"auto","created_at":"2024-07-09 20:01:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1588517,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"CKBAirTempSupplementaryappendix2Jun2024.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4547455/v2/34811b26efdfb9498598f6be.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"Modelling personal temperature exposure using household and outdoor temperature and questionnaire data: implications for epidemiological studies","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"climate change, epidemiology, heart rate, temperature, wearables ","lastPublishedDoi":"10.21203/rs.3.rs-4547455/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4547455/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The reliance of outdoor exposure data in epidemiological studies on temperature entails important uncertainties from personal exposure misclassification. We analysed ~88,000 concurrent person-hours of measured personal, household (kitchen and living room), and outdoor temperatures collected in the summer (MAY-SEP 2017) and winter (NOV 2017-JAN 2018) in rural and urban China. The temperatures across microenvironments were strongly correlated (Spearman’s ρ: 0.86-0.92) in summer. In winter, personal temperature was strongly related to household temperatures (ρ: 0.74-0.79) but poorly related to outdoor temperature (ρ: 0.30). Random forest (RF) algorithm identified household and outdoor temperatures and study date as top predictors of personal temperature exposure for both seasons, and heating-related factors were important in winter. Multivariable linear regression and RF models incorporating questionnaire and device data performed satisfactorily in predicting personal exposure in both seasons (R2summer: 0.92; R2winter: 0.68-0.70). Using generalised additive mixed effect models, we found consistent U-shaped associations between measured and predicted personal temperature exposures and heart rate (lowest at ~14.5ºC), but a weak positive linear association with outdoor temperature. Personal and outdoor temperatures differ substantially in winter, but prediction models incorporating household and outdoor temperatures and questionnaire data performed satisfactorily. Exposure misclassification from using outdoor temperature may produce inappropriate epidemiological findings.","manuscriptTitle":"Modelling personal temperature exposure using household and outdoor temperature and questionnaire data: implications for epidemiological studies","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2024-07-09 19:53:48","doi":"10.21203/rs.3.rs-4547455/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2024-07-01 13:07:05","doi":"10.21203/rs.3.rs-4547455/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"517e01e4-b6cd-4596-87e5-0a7804ce36fe","owner":[],"postedDate":"July 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":33959968,"name":"Health sciences/Risk factors"},{"id":33959969,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2024-07-01T13:07:05+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-09 19:53:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-4547455","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4547455","identity":"rs-4547455","version":["v2"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}