Mobile COVID-19 Screening Units: Heat Stress and Kidney Function Among Health Care Workers

Abstract

During the COVID-19 pandemic, mobile COVID-19 testing units were commonly used in many countries. Because health care workers (HCWs) were required to wear personal protective equipment (PPE) and work outdoors, heat stress became an emerging occupational hazard.1Bose-O'Reilly S. Daanen H. Deering K. et al.COVID-19 and heat waves: New challenges for healthcare systems.Environ Res. 2021; 198111153https://doi.org/10.1016/j.envres.2021.111153Crossref PubMed Scopus (15) Google Scholar This study aimed to assess incident kidney injury in HCWs from heat stress in mobile COVID-19 testing units. We applied a repeated measurement design to measure pre- and postshift kidney function and physiological changes in HCWs. The Research Ethics Committee of National Taiwan University approved the research protocol (No. 202106HN031). All participants provided written informed consent before the study. The study participants were recruited from a mobile COVID-19 screening unit in Taipei, Taiwan, that had been working on the screening bus for 3 months after the outbreak. We measured temperature and relative humidity inside the PPE by a Kestrel DROP D3 Temperature, Humidity & Pressure Logger (Nielsen-Kellerman Company)2Bailey E. Fuhrmann C. Runkle J. et al.Wearable sensors for personal temperature exposure assessments: a comparative study.Environ Res. 2020; 180108858https://doi.org/10.1016/j.envres.2019.108858Crossref PubMed Scopus (18) Google Scholar and calculated the heat index for each work shift (Figs S1-S2; Item S1).3Lee J.-S. Byun H.-R. Kim D.-W. Development of accumulated heat stress index based on time-weighted function.Theor Appl Climatol. 2016; 124: 541-554https://doi.org/10.1007/s00704-015-1434-xCrossref Scopus (12) Google Scholar Physicians conducted face-to-face interviews and confirmed the medical history. We collected fingertip blood samples to measure whole blood creatinine and calculated the estimated glomerular filtration rate (eGFR) using the 2009 CKD-EPI creatinine equation.4Levey A.S. Stevens L.A. Schmid C.H. et al.A new equation to estimate glomerular filtration rate.Ann Intern Med. 2009; 150: 604-612https://doi.org/10.7326/0003-4819-150-9-200905050-00006Crossref PubMed Scopus (15959) Google Scholar We used 1 eGFR prior to work and 1 eGFR after work to calculate the cross-shift eGFR change (ΔeGFR; postshift value less preshift value). Incident kidney injury was defined as whole blood creatinine increase of >0.3 mg/dL or 1.5-fold.5Glaser J. Hansson E. Weiss I. et al.Preventing kidney injury among sugarcane workers: promising evidence from enhanced workplace interventions.Occup Environ Med. 2020; 77: 527-534https://doi.org/10.1136/oemed-2020-106406Crossref PubMed Scopus (30) Google Scholar Proteinuria was defined as protein excretion >30 mg/dL by dipstick. We also calculated the kinetic GFR (kGFR) to estimate incident kidney injury (Item S1).6Chen S. Retooling the creatinine clearance equation to estimate kinetic GFR when the plasma creatinine is changing acutely.J Am Soc Nephrol. 2013; 24: 877-888https://doi.org/10.1681/ASN.2012070653Crossref PubMed Scopus (139) Google Scholar We used a medical-grade infrared ear thermometer (RA600; Rossmax) to measure change in core body temperature. All participants sat for 5 minutes before their BP was taken while they were in a sitting position. We measured body weight while the participants were in a base layer of clothing. Postshift dehydration was defined as >1.5% body weight loss. We used a structured questionnaire to obtain occupational risk factors, including whether electrolytes were added to the drinking water, a habit of drinking sugary beverages, and whether drinking water was avoided before wearing PPE to prevent the desire to void. Paired sample t tests were used to test pre-and postshift measurements. We recruited 50 HCWs (44 nurses and 6 bus drivers) from a mobile COVID-19 testing unit between September and October 2021. After exclusion of 5 participants to standardize blood collection procedures, 45 HCWs (39 nurses and 6 bus drivers) were included in the final analysis. In the nurses, there was a significant increase in core body temperature (P < 0.001) and nominal decreases in body weight (P = 0.05), systolic BP (P = 0.3), and diastolic BP (P = 0.2). Nine nurses (23%) developed incident kidney injury and 4 nurses (11%) developed proteinuria. Nurses had a significantly lower kGFR than bus drivers (P = 0.001) (Table 1). We observed a significant cross-shift eGFR decline in the nurses (P < 0.001) but not in the bus drivers (P = 0.9) (Fig 1). During the study period (September and October 2021), the environmental temperature was 29.3 ± 2.3 °C, with an ambient heat index of 35.0 ± 3.8 °C. The personal heat index was 46.8 ± 6.1 °C for nurse members and 48.4 ± 4.9 °C for nurse leaders (Fig S1). Large amounts of sweat and limited evaporation significantly increased humidity within the PPE, leading to higher heat stress (Fig S2). Direct sunlight exposure (P = 0.03) and avoiding drinking water (P = 0.03) increased the risks for kidney function decline in univariable analysis (Table S1).Table 1Demographic Characteristics and Pre- and Postshift MeasurementsDemographic CharacteristicsNurses (n = 39)Bus drivers (n = 6)Age, y30.4 ± 6.546.0 ± 7.8Female sex35 (90%)0 (0%)Current smoker4 (10%)1 (17%)Height, cm160.9 ± 6.1176.2 ± 6.2BMI, kg/m222.9 ± 4.026.4 ± 3.3Work shift, min120.8 ± 23.2152.5 ± 30.6Fluid intake, mL641.3 ± 370.01,033.3 ± 752.8kGFR, mL/min/1.73 m218.5 ± 33.973.3 ± 51.8Pre- and Postshift MeasurementsNursesBus DriversPreshiftPostshiftPPreshiftPostshiftPAural temperature, °C36.4 ± 0.336.6 ± 0.3<0.00136.9 ± 0.436.5 ± 0.50.2Body weight, kg59.4 ± 10.559.2 ± 10.50.0582.2 ± 13.682.1 ± 13.20.9Systolic BP, mm Hg111.9 ± 11.5109.9 ± 9.40.3141.5 ± 17.7138.2 ± 19.40.6Diastolic BP, mm Hg75.9 ± 9.773.5 ± 9.20.290.0 ± 13.590.3 ± 14.70.9Creatinine, mg/dL0.8 ± 0.21.0 ± 0.2<0.0011.1 ± 0.21.1 ± 0.10.9eGFR, mL/min/1.73 m2104.6 ± 17.681.2 ± 17.8<0.00179.3 ± 9.480.0 ± 8.90.9Urine specific gravity1.012 ± 0.0091.012 ± 0.0080.91.005 ± 0.0051.007 ± 0.0030.3Proteinuria0 (0%)4 (10%)0 (0%)0 (0%)Incident kidney injury–9 (23%)–0 (0%)Values for continuous variables given as mean ± SD. Abbreviations: BP, blood pressure; BMI, body mass index. Open table in a new tab Values for continuous variables given as mean ± SD. Abbreviations: BP, blood pressure; BMI, body mass index. To our knowledge, this is the first study that provides evidence that HCWs wearing PPE and working outdoors during hot weather have a significant decline in their kidney function. Although the association of sugary beverages with ΔeGFR observed in this study was of borderline statistical significance, an effect would be consistent with the mechanism of increased vascular resistance in the kidney reported by Chapman et al.7Chapman C.L. Grigoryan T. Vargas N.T. et al.High-fructose corn syrup-sweetened soft drink consumption increases vascular resistance in the kidneys at rest and during sympathetic activation.Am J Physiol Renal Physiol. 2020; 318: F1053-F1065https://doi.org/10.1152/ajprenal.00374.2019Crossref PubMed Google Scholar There are some limitations. First, this study used aural temperature as core body temperature, which is not as accurate as rectal temperature.8Ganio M.S. Brown C.M. Casa D.J. et al.Validity and reliability of devices that assess body temperature during indoor exercise in the heat.J Athl Training. 2009; 44: 124-135https://doi.org/10.4085/1062-6050-44.2.124Crossref PubMed Scopus (125) Google Scholar Second, this study did not measure urinary biomarkers of kidney injury, which could provide better insight into the mechanisms or location of kidney injury.9Chapman C.L. Johnson B.D. Parker M.D. et al.Kidney physiology and pathophysiology during heat stress and the modification by exercise, dehydration, heat acclimation and aging.Temperature (Austin). 2021; 8: 108-159https://doi.org/10.1080/23328940.2020.1826841Crossref PubMed Scopus (13) Google Scholar We recommend that governments pay attention to the thermal hazard of kidney injury in HCWs during the COVID-19 pandemic. Data collection: T-HC, C-YL, C-JC; data analysis: T-HC, C-YL; study design: J-KWL, H-YY; study collection: W-CC. Each author contributed important intellectual content during manuscript drafting or revision and agrees to be personally accountable for the individual’s own contributions and to ensure that questions pertaining to the accuracy or integrity of any portion of the work, even one in which the author was not directly involved, are appropriately investigated and resolved, including with documentation in the literature if appropriate. This study was funded by the National Taiwan University (NTU) within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan [NTU-110L881004, NTU-111L881004] and was financially supported by the Ministry of Science and Technology, Taiwan (grant no. MOST 109-2314-B-002-166-MY3) and the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) program. The funders did not have a role in study design, data collection, analysis, reporting, or the decision to submit for publication. The authors declare that they have no relevant financial interests. We thank the COVID-19 quarantine station, Taipei City Hospital, and all participants of the Taipei mobile screening bus team. We also express our gratitude to the Rotary Club, Dr Hsu, Flybird, Chi-Hsiang, and Chingshin Academy for providing epidemic prevention materials and cooling vests for the HCWs after the study. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not reflect the views of the National Research Foundation, Singapore. Received January 20, 2022. Evaluated by 2 external peer reviewers, with direct editorial input from a Statistics/Methods Editor, an Associate Editor, and the Editor-in-Chief. Accepted in revised form May 18, 2022. Download .pdf (.38 MB) Help with pdf files Supplementary File (PDF)Figures S1-S2; Item S1; Table S1.