Associations of furan exposure with the prevalence and mortality in asthma: A prospective cohort study

Associations of furan exposure with the prevalence and mortality in asthma: A prospective cohort study | 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 Research Article Associations of furan exposure with the prevalence and mortality in asthma: A prospective cohort study Shuwen Zhang, Kunlu Shen, Bingqing Sun, Bowen Liu, Chunxiao Li, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4867643/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Few studies have explored the role of furan exposure plays in aggravating asthma. Objective To access the relationship of furan exposure to asthma. Methods This is a prospective cohort study, involving 7,047 adults over 20 years old from the National Health and Nutrition Examination Survey 2007–2012. Blood furan levels were employed to quantify furan exposure. Multivariate survey-weighted regressions were utilized to analyze the associations between furan exposure, the prevalence of asthma. Mediation analyses for furan exposure and asthma prevalence were conducted. Multiple Cox regression was employed to evaluate the association between furan exposure and asthma prognosis. Results Asthmatics have higher blood furan levels than non-asthmatics ( P < 0.001). After adjusting for covariates, log10-transformed blood furan levels (LBFL) were independently associated with an increased risk of asthma prevalence (adjusted odds ratio [aOR] = 2.40, 95% confidence interval [CI] = 1.21–4.78, P = 0.014). There was a significant positive linear relationship between LBFL and risk of asthma ( P for linear = 0.0003). In mediation analyses, FEV 1 was identified as mediators in the above relationships, with mediated proportions of 32.73%. Longitudinally, multiple Cox regression analysis demonstrated that LBFL were positively correlated with respiratory mortality in asthma (HR = 27.88, 95% CI = 4.19-185.69, P < 0.0001). Conclusions Exposure to furan revealed a positive association with greater odds of asthma, and lung function was identified as an important mediator. An elevated LBFL also is associated with an increased health care use, worse HQL, and prognosis of asthma. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Asthma is a chronic inflammatory respiratory disease marked by airway hyperresponsiveness and remodeling, leading to dyspnea and wheezing. 1 . The multifaceted risk factors associated with asthma encompass environmental variables such as air pollution 2 , occupational dust 3 , smoking 4 , and environmental chemicals exposure 5 . Great deal of research revealed that exposure to environmental chemicals associated with the rising frequency of asthma, exacerbation and increased healthcare use caused by asthma 6 – 8 . Thus, it is imperative to investigate the relationship between environmental pollutants and asthma in order to support public health and environmental protection policies so lowering the burden of asthma. Furan (C4H4O) is a volatile and carcinogenic heterocyclic compound in various thermally processed foods, such as cooking, baking, canning, and sterilization at 150 to 200°C 9 . Previous studies have reported that furan can penetrate biofilms. For instance, the intestine and lungs and be rapidly absorbed and extensively metabolized 10 . Furan can enter the human body through ingestion and inhalation when preparing food 10 . Tǎbǎran et al. found that lung club cells of mice exposed to furan showed necrosis with airway denudation, regeneration and partial repair 11 . Meanwhile, a recent study has showed that the link between blood furan and chronic obstructive pulmonary disease (COPD) is mediated by inflammation 12 . To date, the relationship between furan and asthma has never been investigated. In this study, we aimed to explore the association between furan exposure, prevalence and mortality in asthma among adults. Furthermore, we investigated whether furan exposure is associated with lung function, participants-reported health outcomes, and participants-reported health-related quality of life (HQL). Method Study design and participants NHANES is a population-based survey carried out annually by the National Center for Health Statistics (NCHS) since 1999, a division of the Centers for Disease Control and Prevention (CDC). The NHANES included interviews, physical exams, and laboratory tests. The study protocol received approval from the NCHS Research Ethics Board, and all participants gave their written consent. Details of NHANES has been documented elsewhere ( https://www.cdc.gov/nchs/nhanes/index.htm ) 13,14 . Ultimately, we obtained the data from the NHANES 2007–2012. These cycles were chosen because participants underwent the spirometry test in these waves. The total sample size of the NHANES 2007–2012 was 30,442. Individuals under 18 years old (n = 12,729), those missing data for asthma (n = 17), and those without data for blood furan (n = 10,649) were excluded after merging databases. Thus, 7,047 individuals satisfied the inclusion criteria for final analysis (Fig. 1 ). Exposure Definitions Serum blood furan levels were measured using a protocol outlined in a previously published study 15 . In brief, the approach detects specific volatile organic compounds (VOCs) in whole blood at low parts-per-trillion levels. Since non-occupationally exposed individuals have blood VOC concentrations within this range, this method is useful for measuring levels. Laboratory measurements were carried out using centralized quality assurance and control techniques. The minimum detectable concentration of blood furan was 0.0250 (unit: ng/mL). Log10 transformations were carried out where required to achieve a normal data distribution of blood furan level. In addition, participants were assigned into two groups according to the median of log10-transformed blood furan levels (LBFL): LBFL ≤ -1.752 ng/mL is assigned to furan Low group while LBFL > -1.752 ng/mL is assigned to furan High group. Primary outcome There are two primary outcomes in this study: the prevalence of asthma and respiratory mortality in asthma. Prevalence of asthma Asthma is defined by a self-reported positive answer to the questionnaire: “Has a doctor or other health professional ever told you that you had asthma?”. Respiratory mortality in asthma Another primary outcome was respiratory mortality in asthmatics, including chronic lower respiratory diseases (J40 - J47), influenza and pneumonia (J10 - J18). The information about mortality status and cause of death was obtained by NHANES-linked National Death Index (NDI) on December 31, 2019. Secondary outcome The secondary outcomes of this study were lung function (absolute value of FEV 1 [L], FEV 1 % predicted, absolute value of FVC[L], FVC % predicted, obstructive, and restrictive spirometry pattern) and participants-reported health outcomes, including asthma-related health outcomes (asthma attack, emergency room [ER] visits for asthma), respiratory symptoms (wheezing, phlegm production, dry cough, and exertional dyspnea), and participants-reported health-related quality of life (HQL) (days when physical health was poor, days when mental health was poor, inactive days because of poor health). Lung function Lung function was assessed in participants ranging in age from 6 to 79 years. Detailed information about spirometry protocol and procedure is described elsewhere 16 . Spirometry testing was performed at the NHANES Mobile Examination Center following a standardized protocol, measuring forced expiratory volume in the first second (FEV 1 ) and forced vital capacity (FVC). Predicted spirometry values were determined using normative reference equations from NHANES III data 17 . Percent (%) predicted FEV 1 , FVC, and FEV 1 /FVC were calculated using Global Lung Initiative equations based on the participant’s age, gender, height, and race/ethnicity 17 . Detailed information on spirometry administration is available in the NHANES spirometry procedures manual 18 . Moreover, obstructive spirometry was determined as FEV 1 /FVC < 0.70, whereas restrictive spirometry was characterized as FVC < 80% of predicted and FEV 1 /FVC ≥ 0.70 19 . Asthma-related health outcomes Asthma-related health outcomes included asthma attack and ER visits for asthma in the past year. An asthma attack was identified by answering “yes” to the question. Detailed questions are described in Luyster FS et al ’s study 20 . Respiratory symptoms Respiratory symptoms consisted of wheezing, phlegm production, cough, and exertional dyspnea. Respiratory symptoms listed above were identified by answering “yes” to the question. Specific questions are described in Wu et al ’s study 14 . HQL HQL was assessed by questions about mental health and physical health in the past 30 days. Specific questions are described in Luyster FS et al ’s study 20 . Demographic and Clinical Data The data of demographic and clinical on study participants was collected using questionnaires and laboratory tests, consisting of age, gender (male/female), race/ethnicity, educational attainment, marital status, poverty-income ratio (PIR) level, body mass index (BMI), serum cotinine (ng/ml), alcohol drinking, chronic disease (cancer/malignancy, coronary heart disease, diabetes mellitus, and hypertension) and count of white blood cell (WBC) count. Race/ethnicity was classified by Mexican American, other Hispanic, non-Hispanic black and white, and others race. Educational attainment was categorized as college or more, high school, middle school or lower. Marital status was classified as married/partnered, divorced/separated, or widowed/single. The PIR was ranged from 0 to 5, calculated based on guidelines and adjusted for family size, year, and state. A value of zero means no income and five means income at least five times the federal poverty level. As a metabolite of nicotine, serum cotinine is utilized to measure recent engagement in tobacco use 21 . Alcohol drinking was defined as how many drinks did you have over the past 12 months on average annually, which classified as ≥ 4 drinks/day, 1–3 drinks/day, and never drinking. Chronic disease included bronchitis, emphysema, cancer/malignancy, coronary heart disease, diabetes mellitus, and hypertension defined as self-reported physician diagnosis. Statistical analysis Categorical variables are reported as frequencies and proportions, whereas continuous variables are expressed as means ± standard deviation (SD) or median (Quartiles [Q] 1, 3) based on the data distribution. The difference between two groups for each variable was analyzed appropriately using t-test or Mann Whitney U test for continuous variables and χ 2 tests for categorical variables. To explore the link between LBFL and asthma prevalence, we conducted an RCS analysis to evaluated the dose-response association. Multiple logistic regression analyses were used to assess this association, taking into account various covariates. Initially, we employed a crude model without adjusting any covariates. Next, we developed Model I, which adjusted for age, gender, ethnicity, marital status, and educational attainment. Finally, Model II comprised the same variables as Model I, with additional adjustments for BMI, PIR, serum cotinine levels, alcohol drinking in the past year, and diabetes mellitus. In addition, we performed mediation analyses to determine if inflammation or lung function (represented by FEV 1 ) mediated the relationship between LBFL and asthma prevalence, adjusting for confounders. In brief, mediation analysis was conducted using the R package "mediation" (version 4.5.0) with 1,000 simulations 22 . We estimated the average direct effect (ADE), average causal mediation effect (ACME), and average total effect using a model-based inference approach. The proportion of the exposure's effect on the outcome that was mediated was calculated by dividing the ACME by the total effect (ACME + ADE) 22,23 . Additionally, we conducted stratified analyses to explore potential moderating effects of age, BMI, gender, ethnicity, marital status, and educational attainment. Multiple Cox regression analyses were implemented to calculate adjusted hazard ratios (HRs) and 95% CIs for furan exposure and respiratory mortality in patients with asthma. Initially, the crude model was employed. Subsequently, Model I included adjustments for age, PIR, marital status, educational attainment, while Model II adjusted for the same variables as Model I and for serum cotinine, past-year alcohol drinking, coronary heart disease, and hypertension. All statistical analyses were conducted according to the CDS guidelines ( https://wwwn.cdc.gov/nchs/nhanes/tutorials/default.aspx ). The statistical analyses included sample weights to account for the complex multi-stage stratified survey design used in NHANES. All statistical analyses were executed using R (version 4.3.1). Statistical significance was assessed at a two-sided P value < 0.05. Results Baseline characteristics of participants A total of 7,047 participants were enrolled in the present study from the NHANES data from 2007 to 2012. Of the study participants, 951 participants diagnosed as asthma and 6,096 participants without asthma. Table 1 listed the sociodemographic and clinical characteristics of the subjects grouped by asthma. As presented in Table 1 , asthmatics were more likely to be younger, more female, lower PIR, higher BMI, high serum cotinine, worse lung function, and more diabetes mellitus compared with participants without asthma (all P 0.05). With respect to blood furan level, there is a significant increased LBFL for asthma patients (21.96% vs. 14.37%, P < 0.001) compare with participants without asthma. Table 1 Demographics and clinical characteristics of participants group by asthma. Variable All (n = 7047) Healthy controls (n = 6096) Asthma (n = 951) P -value Age 46.00(33.00,59.00) 46.00(34.00,59.00) 44.00(30.00,57.00) < 0.001 Gender < 0.001 Female 3576(51.64) 3007(50.27) 569(60.12) Male 3471(48.36) 3089(49.73) 382(39.88) Ethnicity < 0.0001 Mexican American 1123(8.43) 1045(9.11) 78(4.25) Non-Hispanic Black 1445(10.96) 1213(10.58) 232(13.32) Non-Hispanic White 3083(67.56) 2627(67.17) 456(69.96) Other Hispanic 767(5.79) 660(5.76) 107(6.01) Other Race - Including Multi-Racial 629(7.25) 551(7.38) 78(6.46) Educational attainment 0.7 College or more 3482(58.65) 2973(58.48) 509(60.36) High school 1581(22.42) 1368(22.59) 213(21.62) Middle school or lower 1975(18.78) 1746(18.94) 229(18.01) Marital status 0.001 Divorced 745(10.19) 618(9.92) 127(11.87) Living with partner 542(7.88) 460(7.80) 82(8.34) Married 3663(55.63) 3235(56.77) 428(48.68) Never married 1239(18.04) 1032(17.15) 207(23.54) Separated 258(2.64) 220(2.60) 38(2.93) Widowed 596(5.59) 528(5.75) 68(4.64) BMI 27.50(24.01,32.00) 27.31(23.94,31.69) 28.59(24.47,33.98) 0.001 PIR 2.91(1.43,5.00) 2.95(1.48,5.00) 2.33(1.20,4.67) 0.01 Serum cotinine 0.04(0.01,4.98) 0.04(0.01, 2.65) 0.06(0.02,88.50) 0.01 Past-year alcohol drinking 0.92 ≥ 4 drinks/day 1049(15.68) 912(19.05) 137(19.64) 1–3 drinks/day 2800(45.89) 2420(56.03) 380(55.81) Never 1762(20.37) 1532(24.92) 230(24.55) Spirometry FEV 1 (L) 3.18(2.57,3.84) 3.21(2.61,3.87) 3.03(2.31,3.56) < 0.0001 FEV 1 % predicted 98.11(88.51,107.04) 98.78(90.08,107.60) 92.51(80.34,102.76) < 0.0001 FVC (L) 4.05(3.33,4.87) 4.06(3.36,4.91) 3.92(3.18,4.64) 0.003 FVC% predicted 101.24(92.16,110.26) 101.67(92.87,110.68) 98.57(88.03,107.73) < 0.0001 FEV 1 /FVC 3.00(2.11,3.85) 3.07(2.20,3.90) 2.57(1.72,3.46) < 0.0001 Cancer 0.08 No 6403(90.78) 5555(91.26) 848(88.78) Yes 638(9.07) 537(8.74) 101(11.22) Coronary heart disease 0.45 No 6764(96.93) 5851(97.17) 913(97.63) Yes 252(2.76) 219(2.83) 33(2.37) Diabetes mellitus < 0.001 Borderline 141(1.93) 122(2.01) 19(1.41) No 6019(89.20) 5253(89.74) 766(86.08) Yes 883(8.84) 717(8.25) 166(12.51) HBP 0.06 No 4564(69.83) 3999(70.50) 565(66.08) Yes 2475(30.09) 2090(29.50) 385(33.92) LBFL -1.752 ng/mL 1044(15.43) 840(14.37) 204(21.96) Abbreviation: BMI, body mass index; PIR, poverty-income ratio; FEV 1 , forced expiratory volume in 1 s; FVC, forced vital capacity; HBP, high blood pressure; LBFL, Log10-transformed blood furan levels. In addition, 6003 (85.2%) participants were divided into the furan High group and 1044 (14.8%) were divided into the furan Low group as depicted in Table E1. The patients in the furan High group were younger, had an elevated proportion were male, lower BMI, PIR, higher serum cotinine, worse lung function including FEV 1 , FEV 1 % predicted, FVC, FVC% predicted, and FEV 1 /FVC, and more participants with asthma (all P < 0.05). Primary Outcomes Furan exposure and asthma prevalence Compared to the furan Low group, participants in the furan High group showed a higher risk of asthma in all models (crude model: odds ratio [OR] = 1.68, 95% CI = 1.31–2.15, P < 0.001; model 1: adjusted OR [aOR] = 1.57 95% CI = 1.20–2.06, P = 0.002; model 2: aOR = 1.75, 95% CI = 1.14–2.68, P = 0.012, respectively) (Table 2 ). In addition, LBFL as continuous variable also suggested a positive association with the prevalence of asthma (crude model: OR = 1.99, 95% CI = 1.39–2.85, P < 0.001; model 1: aOR = 1.86 95% CI = 1.25–2.78, P = 0.003; model 2: aOR = 2.40, 95% CI = 1.21–4.78, P = 0.014) (Table 2 ). Table 2 Weighted univariate and multivariate logistic regression analysis of LBFL for the risk of asthma Crude Model Model 1 Model 2 OR (95% CI) P -value OR (95% CI) P -value OR (95% CI) P -value Log10-transformed blood furan 1.99(1.39,2.85) -1.752 ng/mL) 1.68(1.31,2.15) < 0.001 1.57(1.20,2.06) 0.002 1.75(1.14,2.68) 0.012 Abbreviation: OR, odds ratio; CI, confidence interval; LBFL, Log10-transformed blood furan levels. Crude model lacked adjustments for covariates. Model 1 adjusted for age, gender, ethnicity, marital status, educational attainment. Model 2 adjusted for age, gender, ethnicity, marital status, educational attainment, BMI, PIR, serum cotinine, past-year alcohol drinking, and diabetes mellitus. Moreover, the RCS model exhibited that LBFL were linearly related to the prevalence of asthma adjusting for age, gender, BMI, ethnicity, marital status, educational attainment, PIR, serum cotinine, past-year alcohol drinking, and diabetes mellitus ( P for overall = 0.0003; P for non-linear = 0.1311) (Fig. 2 ). And ROC analysis showed that the area under roc curve (AUC) value in the fully adjusted model was 0.655 ( P < 0.05) (Fig. 3 ). Subgroup analyses of factors impacting the association of asthma prevalence with furan exposure Furthermore, subgroup analysis was employed to further investigate the association between furan exposure and the prevalence of asthma stratified by age, gender, BMI, ethnicity, marital status, and educational attainment in Fig. 4 (Detail data as shown in Table E2). In subgroups analysis, a statistically significant link between exposure to furan and asthma prevalence was only observed in the less than 60 years age group, in those with a BMI between 25-29.9 kg/m 2 , in females, in those were non-Hispanic white and other Hispanic, in married, and in those with middle school or low and college or more (all P 0.05). Mediation analysis of lung function involved in the effects of furan on asthma Furthermore, we analyzed the associations of LBFL with inflammatory cells and lung function in adults. There was a substantial positive correlation between LBFL and lymphocytes (β = 0.346, 95% CI = 0.207–0.485, P < 0.0001), neutrophils (β = 1.005, 95% CI = 0.559–1.451, P < 0.0001), and FEV 1 (β = -0.351, 95% CI = -0.500 - -0.202, P 0.05). Additionally, asthma exhibited a positive association with eosinophils and FEV 1 (β = 0.041, 95% CI = 0.025–0.056, P < 0.0001; β = -0.222, 95% CI = -0.293 - -0.151, P 0.05). As Fig. 5 displayed, mediation analyses indicated that the absolute value of FEV 1 partially mediated the association between furan exposure and asthma prevalence, with mediated proportions of 30.93% ( P < 0.05), as depicted in Fig. 5 . Furan exposure and respiratory mortality of asthma Two patients were eliminated due to lack of follow-up among the 951 asthmatic patients (Fig. 1 ). Additionally, 18 patients died from respiratory illnesses, giving weighted respiratory mortality of 1.90%. Table 3 illustrates the positive correlation found in both models between LBFL and respiratory mortality of asthma. Table 3 shows that LBFL and respiratory mortality in asthma patients were positively correlated, with the Cox regression analysis controlling for age, PIR, marital status, educational attainment, serum cotinine, past-year alcohol drinking, coronary heart disease, and hypertension (hazard ratio [HR] = 27.88, 95% CI = 4.19–185.69, P < 0.0001). Table 3 Weighted univariate and multivariate cox regression analysis of LBFL and respiratory mortality of asthma. Crude Model Model 1 Model 2 HR (95% CI) P -value HR (95% CI) P -value HR (95% CI) P -value Log10-transformed blood furan 3.65(1.22, 10.93) 0.021 31.33(7.08, 138.74) < 0.0001 27.88(4.19, 185.69) -1.752 ng/mL) 2.52(1.02, 6.22) 0.045 15.07(5.33, 42.61) < 0.0001 33.88(16.86, 68.10) < 0.001 Abbreviation: HR, hazard ratio; CI, confidence interval; LBFL, Log10-transformed blood furan levels. Crude model lacked adjustments for covariates. Model 1 adjusted for age, PIR, marital status, educational attainment. Model 2 adjusted for age, PIR, marital status, educational attainment, serum cotinine, past-year alcohol drinking, coronary heart disease, and hypertension. Secondary outcome Lung function Compared with furan Low group, those in the furan High group had worse FEV 1 , FEV 1 % predicted, and FVC % predicted (3.08 [2.48,3.64] vs. 3.20 [2.59,3.86] L, P < 0.0001; 91.90 [81.61,101.00] vs. 98.94 [90.22,107.83] %, P < 0.0001; 99.99 [90.15,108.09] vs. 101.52 [92.73,110.49], P = 0.01; respectively) and a higher proportion of obstructive spirometry pattern (26.63% vs. 11.29%, P < 0.0001) (Table E6). But no significant difference was observed in restrictive spirometry pattern (Table E6). After multivariate adjustment, a one-unit increase in LBFL was significantly associated with 0.35 decrements in absolute value of FEV 1 (β = -0.35, 95% CI = -0.50 - -0.20. P < 0.0001), and with 10.59 decrements in percent predicted FEV 1 (β = -10.59, 95% CI = -14.56 - -6.63. P < 0.0001) after adjusting for age, gender, BMI, ethnicity, marital status, educational attainment, PIR, serum cotinine, bronchitis, emphysema, diabetes mellitus. In addition, after adjusting for all confounders in the master analytical model 2 above, a non-linear correlation was observed between furan exposure and absolute value of FEV 1 ( P for overall < 0.0001; P for non-linear = 0.0156) in Figure E1. A linear correlation was observed between furan exposure and percent predicted FEV 1 , absolute value of FVC, and percent predicted FVC ( P for overall 0.05) (Figure E1). Consequently, LBFL was associated with an elevated risk of an obstructive spirometry pattern (aOR = 5.02, 95% CI = 2.97–8.47, P < 0.0001), but not with restrictive spirometry pattern (aOR = 0.84, 95% CI = 0.45–1.56, P = 0.57) (Table 4 ). Table 4 Weighted univariate and multivariate regression models of LBFL predicting lung function and patient-reported health outcomes. Variables Crude Model Model 1 Model 2 β/OR (95% CI) P -value β/OR (95% CI) P -value β/OR (95% CI) P -value Lung function FEV 1 (L) -0.26(-0.35, -0.16) < 0.0001 -0.33(-0.43, -0.24) < 0.0001 -0.35(-0.50, -0.20) < 0.0001 FEV 1 % predicted -12.43(-14.76, -10.10) < 0.0001 -11.01(-13.61, -8.42) < 0.0001 -10.59(-14.56, -6.63) < 0.0001 FVC (L) 0.03(-0.11, 0.17) 0.67 -0.08(-0.20, 0.03) 0.14 -0.14(-0.32, 0.04) 0.13 FVC % predicted -4.16(-6.65, -1.67) 0.002 -3( -5.606, -0.393) 0.03 -3.26( -7.10, 0.59) 0.09 Obstructive 4.82(3.71, 6.26) < 0.0001 6.17(4.57, 8.32) < 0.0001 5.02(2.97, 8.47) < 0.0001 Restrictive 0.93(0.59, 1.49) 0.93 0.86(0.53,1.38) 0.86 0.84(0.45, 1.56) 0.57 Asthma-related health outcomes Asthma attack in past yr 1.84(0.90, 3.76) 0.09 2.00(0.94,4.27) 0.07 3.25(0.82, 12.80) 0.09 ER visits for asthma in past yr 1.03(0.35, 3.05) 0.96 1.02(0.31, 3.38) 0.97 2.11(0.07, 59.91) 0.65 Respiratory symptoms Wheezing 4.88(3.68, 6.47) < 0.0001 4.35(3.23,5.86) < 0.0001 4.48(2.72, 7.40) < 0.0001 Phlegm 5.37(3.52, 8.20) < 0.0001 5.67(3.67, 8.75) < 0.0001 7.16(3.09, 16.61) < 0.0001 Cough 7.47(4.75, 11.77) < 0.0001 6.60(4.24, 10.28) < 0.0001 7.73(3.58, 16.71) < 0.0001 Exertional dyspnea 2.58(1.82, 3.66) < 0.0001 2.45(1.71, 3.51) < 0.0001 2.90(1.58, 5.30) 0.001 HQL Days physical health was not good 3.18(1.86, 4.51) < 0.0001 2.85(1.51, 4.20) < 0.001 2.61(0.88, 4.33) 0.004 Days mental health was not good 4.05(2.71, 5.39) < 0.0001 3.37(2.05, 4.69) < 0.0001 2.23(0.38, 4.09) 0.020 Inactive days due to health 1.85(0.96, 2.73) < 0.001 1.61(0.74,2.48) < 0.001 1.04(-0.17, 2.26) 0.09 Abbreviation: ER, emergency room; OR, odds ratio; CI, confidence interval; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; LBFL, Log10-transformed blood furan levels; HQL, health-related quality of life. Crude model lacked adjustments for covariates. Model 1 adjusted for age, gender, ethnicity, marital status, educational attainment. Model 1 adjusted for age, gender, ethnicity, marital status, educational attainment, BMI, PIR, serum cotinine, bronchitis, emphysema, diabetes mellitus. Asthma-related health outcomes No significant difference was found in asthma attack and ER visits for asthma in past year between furan Low group and furan High group (all P > 0.05) (Table 4 and E6). Respiratory symptoms Compared with participants in the furan Low group, those in the furan High group had a higher proportion of wheezing (27.59% vs. 10.40%, P < 0.0001), phlegm (19.92% vs. 6.40%, P < 0.0001), cough (26.78% vs. 7.35%, P < 0.0001), and exertional dyspnea (44.65% vs. 28.09%, P < 0.0001) (Table E6). Similarly, LBFL was associated with higher odds of wheezing (aOR = 4.48, 95% CI = 2.72–7.40, P < 0.0001), phlegm (aOR = 7.16, 95% CI = 3.09–16.61, P < 0.0001), cough (aOR = 7.73, 95% CI = 3.58–16.71, P < 0.0001), and exertional dyspnea (aOR = 2.90, 95% CI = 1.58–5.30, P < 0.0001) in the past 12 months, adjusting for age, gender, BMI, ethnicity, marital status, educational attainment, PIR, serum cotinine, bronchitis, emphysema, diabetes mellitus. HQL Participants in the furan High group had worse HQL including days when physical health was poor, days when mental health was poor, and inactive days due to poor health (5.60 ± 0.39 vs. 3.23 ± 0.12, P < 0.0001; 6.87 ± 0.46 vs. 3.64 ± 0.10, P < 0.0001; 3.13 ± 0.33 vs. 1.60 ± 0.09, P < 0.0001; respectively), as compared to participants in the furan Low group. Furthermore, LBFL was also associated with more days with poor physical or poor mental health but not of inactive days due to poor health during after adjusted for age, gender, BMI, ethnicity, marital status, educational attainment, PIR, serum cotinine, bronchitis, emphysema, and diabetes mellitus (Table 4 ). Discussion To our knowledge, we’re first to sought to examine systematic relationship between furan exposure, asthma prevalence, and asthma-related respiratory mortality in this prospective cohort study. We found that a higher LBFL was associated with greater odds of the prevalence and mortality of asthma. Lung function, particularly FEV 1 , was identified as a mediator in the relationship between LBFL and asthma prevalence. Additionally, our results indicated that elevated LBFL were associated with worse lung function, increased risk of respiratory symptoms, and lower risk of self-reported HQL after adjusting for covariates. The results indicated that furan as a common environmental pollution may be a notable risk factor for asthma, which highlights the importance of considering environmental exposures in public health and deepens our understanding of the factors contributing to asthma. Accurately identifying environmental chemical exposure is crucial for understanding its potential impact on lung health 5 . Furan, a volatile organic compound as a potential human carcinogen 24 . It is common to found in heat-processed foods through heat treatment methods 25 . Therefore, individuals are at risk of furan toxicity. This is particularly alarming due to the widespread presence of furan in the environment, highlighting its potential role as a public health hazard. There are some issues that could explain the adverse effects of furan on respiratory health. A previous investigation indicated that bronchiolar club cell enlargement, cytoplasmic vacuolation, and necrosis along with airway denudation and an inflammatory response consisting of bronchiolar wall infiltration by low numbers of many neutrophils and lymphocytes when breathing furan 11 . According to Bas et al.'s study, pro-inflammatory cells moved into the bronchioles and alveolar gaps of the rat lungs, indicating that the oral furan administration had harmed the histoarchitectural structures of the lungs 26 . Furan exposure may cause lung dysfunction through inflammation, altered histoarchitectural characteristics, genomic instability or damage, and loss of redox equilibrium. 27 . All these studies demonstrated that furan was consumed orally or inhaled causing lung damage through various pathological mechanisms. The exact mechanism of the effect of furan exposure on the lungs of asthmatic patients and mouse models of asthma need further exploration in the future. Lung function measurement forms a crucial part of the clinical assessment and management of patients with asthma. Individuals exposed to higher levels of furan exhibited notably lower FEV 1 , FEV 1 % predicted and FVC and FEV 1 /FVC, indicative of impaired lung function. Inconsistent with our study, Ahman M et al. found that workers exposed to furan resin sand showed a decrease in FVC and total lung capacity but no fall in any other lung-function variable 28 . There are two main reasons for the disparity about lung function between the two studies: the difference of enrolled population and the study design of two studies. Hence, further studies required to verify that one possible mechanism for furan-related asthma could be represented by FEV1. Understanding this pathway is crucial for developing targeted interventions aimed at preserving lung function and mitigating the adverse effects on environmental pollutants. We found that LBFL was positively associated with participants-reported health outcomes including HQL, and respiratory symptom burden. These respiratory symptom burden not only reflect underlying respiratory dysfunction but also significantly impact daily living and overall well-being. The worse HQL indicating that the adverse effects of furan extend beyond clinical measures to affect subjective health perceptions and daily functioning. Although Sun et al. ’s study found that LBFL was associated with respiratory disease mortality in COPD patients 12 . Nonetheless, no other studies have investigated the effect of furan exposure on the risk of respiratory disease mortality in participants with asthma. In the study, those in the furan High had a higher risk of respiratory disease mortality in participants with asthma compared with the furan Low in individuals with asthma, which suggests that a reduction in LBFL may reduce the risk of respiratory disease mortality in participants with asthma. This study has several limitations. First, our study cannot demonstrate causal relationships between furan exposure and the prevalence of asthma. Further longitudinal studies are necessary to establish causality and monitor changes in lung function and asthma prevalence over time in relation to furan exposure. Second, the diagnosis of asthma depends on self-reported rather than a more reliable and accurate method such as lung function testing, which may lead to recall bias. Third, although we adjusted potential risk factors, the existence of unknown confounders cannot be completely eliminated, and some important covariates, such as medication use (OCS and ICS/LABA), asthma control level, or multi-pollutant adjustment. Conclusion In conclusion, this study indicated a positive link of furan exposure with the prevalence and respiratory mortality of asthma. FEV 1 served as a mediator in this relationship underscores the potential of furan to contribute to the asthma burden through direct respiratory impairment. This implies that reducing environmental exposure to furan could potentially decrease asthma prevalence and respiratory mortality, thereby improving overall respiratory health. The evidence provided by this study underscores the need for a comprehensive approach to addressing environmental pollutants like furan and their impact on respiratory health. Abbreviations ACME: average causal mediation effect ADE: average direct effect aOR: adjusted odds ratio BMI: body mass index CDC: Centers for Disease Control and Prevention CI: confidence interval ER: emergency room FEV 1 : forced expiratory volume in 1 s FVC: forced vital capacity HBP: high blood pressure HQL: health-related quality of life LBFL: log10-transformed blood furan levels NCHS: National Center for Health Statistics NHANES: National Health and Nutrition Examination Survey OR: odds ratio PIR: poverty-income ratio Q: Quartiles RCS: restricted cubic spline SD: standard deviation VOCs: volatile organic compounds WBC: white blood cell Declarations Ethics approval and consent to participate The study protocol received approval from the NCHS Research Ethics Board, and was performed in accordance with the Declaration of Helsinki. All participants gave their written consent. Details of NHANES has been documented elsewhere (https://www.cdc.gov/nchs/nhanes/index.htm). Consent for publication Not applicable. Availability of data and materials Publicly available datasets were analyzed in this study. These data can be found here: https://www.cdc.gov/nchs/nhanes/. The code used for these analyses are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no conflicts of interest to disclose. Funding This work was supported by the National Natural Science Foundation of China (8217010602). Author’s contributions Jiangtao Lin and Shuwen Zhang, conceived the study, performed the data interpretation and manuscript revision, and took accountability for all aspects of the work. Shuwen Zhang planned the work, carried out the data analysis, interpretation and drafted the manuscript. Kunlu Shen, Bingqing Sun and Bowen Liu offered the help of statistical analysis. Chunxiao Li, Xin Hou, Min Xiang, Mengqi Zhou and Jiangtao Lin interpreted the results and contributed to the manuscript revision. All authors approved the final manuscript. Acknowledgements The authors are grateful to all volunteers who participated in this study. The graphic abstract was made with assets from Freepik.com (www.freepik.com). References Global Initiative for Asthma. Global strategy for asthma management and prevention. 2023. Accessed January 1 2024. Avaliable at: https://ginasthma.org/wp-content/uploads/2023/07/GINA-2023-Full-report-23_07_06-WMS.pdf Zheng XY, Ding H, Jiang LN, et al. Association between Air Pollutants and Asthma Emergency Room Visits and Hospital Admissions in Time Series Studies: A Systematic Review and Meta-Analysis. PLoS ONE. 2015;10(9):e0138146. Bakke P, Eide GE, Hanoa R, Gulsvik A. Occupational dust or gas exposure and prevalences of respiratory symptoms and asthma in a general population. Eur Respir J. 1991;4(3):273–8. Osborne ML, Pedula KL, O'Hollaren M, et al. Assessing future need for acute care in adult asthmatics: the Profile of Asthma Risk Study: a prospective health maintenance organization-based study. Chest. 2007;132(4):1151–61. Mattila T, Santonen T, Andersen HR et al. Scoping Review-The Association between Asthma and Environmental Chemicals. Int J Environ Res Public Health 2021;18(3). Humblet O, Diaz-Ramirez LG, Balmes JR, Pinney SM, Hiatt RA. Perfluoroalkyl chemicals and asthma among children 12–19 years of age: NHANES (1999–2008). Environ Health Perspect. 2014;122(10):1129–33. Podlecka D, Gromadzińska J, Mikołajewska K, Fijałkowska B, Stelmach I, Jerzynska J. Longitudinal effect of phthalates exposure on allergic diseases in children. Ann Allergy Asthma Immunol. 2020;125(1):84–9. Pfeffer PE, Mudway IS, Grigg J. Air Pollution and Asthma: Mechanisms of Harm and Considerations for Clinical Interventions. Chest. 2021;159(4):1346–55. Mogol BA, Gökmen V. Thermal process contaminants: acrylamide, chloropropanols and furan. Curr Opin Food Sci. 2016;7:86–92. Alizadeh M, Jalal M, Hamed K, et al. Recent Updates on Anti-Inflammatory and Antimicrobial Effects of Furan Natural Derivatives. J Inflamm Res. 2020;13:451–63. Tǎbǎran AF, O'Sullivan MG, Seabloom DE, et al. Inhaled Furan Selectively Damages Club Cells in Lungs of A/J Mice. Toxicol Pathol. 2019;47(7):842–50. Sun D, Wang Y, Wang J, Dilixiati N, Ye Q. Inflammation mediates the association between furan exposure and the prevalence and mortality of chronic obstructive pulmonary disease: National Health and Nutrition Examination Survey 2013–2018. BMC Public Health. 2024;24(1):1046. Shan Z, Rehm CD, Rogers G, et al. Trends in Dietary Carbohydrate, Protein, and Fat Intake and Diet Quality Among US Adults, 1999–2016. JAMA. 2019;322(12):1178–87. Wu TD, Fawzy A, Brigham E, et al. Association of Triglyceride-Glucose Index and Lung Health: A Population-Based Study. Chest. 2021;160(3):1026–34. Furan. Report on carcinogens: carcinogen profiles. 2011;12:205–207. Miller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry. Eur Respir J. 2005;26(2):319–38. Hankinson JL, Odencrantz JR, Fedan KB. Spirometric reference values from a sample of the general U.S. population. Am J Respir Crit Care Med. 1999;159(1):179–87. National Center for Health Statistics (U.S.). National Health and Nutrition Examination Survey, Respiratory Health Spirometry Procedures Manual. Accessed January 1 2024. https://wwwn.cdc.gov/nchs/data/nhanes/2011-2012/manuals/spirometry_procedures_manual.pdf Cirillo DJ, Agrawal Y, Cassano PA. Lipids and pulmonary function in the Third National Health and Nutrition Examination Survey. Am J Epidemiol. 2002;155(9):842–8. Luyster FS, Shi X, Baniak LM, Morris JL, Chasens ER. Associations of sleep duration with patient-reported outcomes and health care use in US adults with asthma. Ann Allergy Asthma Immunol. 2020;125(3):319–24. Zhang W, Peng SF, Chen L, Chen HM, Cheng XE, Tang YH. Association between the Oxidative Balance Score and Telomere Length from the National Health and Nutrition Examination Survey 1999–2002. Oxidative Med Cell Longev. 2022;2022:1345071. Tingley D, Yamamoto T, Hirose K, Keele L, Imai K. mediation: R Package for Causal Mediation Analysis. J Stat Softw. 2014;59(5):1–38. Imai K, Keele L, Tingley D, Yamamoto T. Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies. Am Polit Sci Rev. 2011;105(4):765–89. Batool Z, Xu D, Zhang X, et al. A review on furan: Formation, analysis, occurrence, carcinogenicity, genotoxicity and reduction methods. Crit Rev Food Sci Nutr. 2021;61(3):395–406. FDA UJhwcfgdfh. Question and Answers on the Occurrence of Furan in Food. 2004. Baş H, Pandir D. Protective Effects of Lycopene on Furan-treated Diabetic and Non-diabetic Rat Lung. Biomed Environ Sci: BES. 2016;29(2):143–7. Owumi SE, Otunla MT, Arunsi UO. A biochemical and histology experimental approach to investigate the adverse effect of chronic lead acetate and dietary furan on rat lungs. Biometals: Int J role metal ions biology Biochem Med. 2023;36(1):201–16. Ahman M, Alexandersson R, Ekholm U, Bergström B, Dahlqvist M, Ulfvarson U. Impeded lung function in moulders and coremakers handling furan resin sand. Int Arch Occup Environ Health. 1991;63(3):175–80. Additional Declarations No competing interests reported. Supplementary Files OnlineDataSupplementfuranandasthma.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version 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. 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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-4867643","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":348192580,"identity":"00be0c59-0d79-4a06-abaf-0f4d79fe83da","order_by":0,"name":"Shuwen Zhang","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuwen","middleName":"","lastName":"Zhang","suffix":""},{"id":348192581,"identity":"b54a7ceb-90ee-482e-b9c5-f651ea0fbb5b","order_by":1,"name":"Kunlu Shen","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kunlu","middleName":"","lastName":"Shen","suffix":""},{"id":348192582,"identity":"950bd851-8714-4495-bccb-1cdad0b563df","order_by":2,"name":"Bingqing Sun","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bingqing","middleName":"","lastName":"Sun","suffix":""},{"id":348192583,"identity":"3ad9b252-9d3e-4745-96b0-7651956edf93","order_by":3,"name":"Bowen Liu","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bowen","middleName":"","lastName":"Liu","suffix":""},{"id":348192584,"identity":"8ec35563-785b-46c7-a771-5f88f983d181","order_by":4,"name":"Chunxiao Li","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chunxiao","middleName":"","lastName":"Li","suffix":""},{"id":348192585,"identity":"e723c5a9-abc4-414b-a04c-294abca8ed32","order_by":5,"name":"Mengqi Zhou","email":"","orcid":"","institution":"University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Mengqi","middleName":"","lastName":"Zhou","suffix":""},{"id":348192586,"identity":"03fe7c60-a732-4da3-9cc1-2935b0e806ab","order_by":6,"name":"Xin Hou","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Hou","suffix":""},{"id":348192587,"identity":"5fb9dd1f-4ce7-4869-a6b5-a02d58a30cb8","order_by":7,"name":"Min Xiang","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Xiang","suffix":""},{"id":348192588,"identity":"f0e8ac87-c77a-42e7-ab2a-539534d0c42f","order_by":8,"name":"Jiangtao Lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBACxmYYi5354IMPP4jWkgDEzGzJhjN7gAw2ouwCa+Exk+ZgI0ILczvzs4dff9jJAbV8kGbgYcjjl28g5DA2c2OZhGRjBmbeDcYFFgzFkm0EbAH6xUxaIoE5sQGoJXkGD0PihmMEtbB/A2qpB2rheXCYh40hcT9hLTxmkh8SDoO0ANlALRsIeR+orEyaIe040C9sxowzeyQSZxxLwK/FsP/4NskfNtVyDOzNz398+GGT2N98gICWBlCMABn2EIUSBFwFBPIgxxGTTEbBKBgFo2AEAwClDDmS77JudwAAAABJRU5ErkJggg==","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jiangtao","middleName":"","lastName":"Lin","suffix":""}],"badges":[],"createdAt":"2024-08-06 10:16:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4867643/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4867643/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63878521,"identity":"68e088e2-9cc9-40b5-b4cd-e1814ff09760","added_by":"auto","created_at":"2024-09-03 09:53:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":522701,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the study.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4867643/v1/39a41d3c3eedfb191761460d.png"},{"id":63878244,"identity":"4ad6de96-972e-4c7e-a1fa-87a4b5430e59","added_by":"auto","created_at":"2024-09-03 09:45:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":75912,"visible":true,"origin":"","legend":"\u003cp\u003eSmoothed curve fitting shows the association between LBFL and asthma prevalence after adjusting for confounders (age, gender, ethnicity, marital status, educational attainment, BMI, PIR, serum cotinine, past-year alcohol drinking, and diabetes mellitus). The red area indicates a 95% confidence interval.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4867643/v1/b43a7452dde88a2c5a2b9186.png"},{"id":63878246,"identity":"2a3f67a2-8998-4b4f-aa14-4ffb3e8be2fa","added_by":"auto","created_at":"2024-09-03 09:45:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":317446,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve analysis of LBFL in evaluating asthma prevalence in the fully adjusted model.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4867643/v1/a9a8357aeab2897ddaa78d20.png"},{"id":63878522,"identity":"d41a8cd5-a4a5-46c9-b9d9-fa8653d7c6a9","added_by":"auto","created_at":"2024-09-03 09:53:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":329095,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4867643/v1/62ceef55790ee6af78d0e009.png"},{"id":63878523,"identity":"0a0fdc89-e5ae-4dc5-be24-ab633821b4c7","added_by":"auto","created_at":"2024-09-03 09:53:04","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":304260,"visible":true,"origin":"","legend":"\u003cp\u003ePath diagram of the mediation analysis of the absolute value of FEV\u003csub\u003e1\u003c/sub\u003e on the relationship between LBFL and asthma prevalence.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4867643/v1/4b8fe85f09eee5172414cdad.png"},{"id":85426875,"identity":"b1d1b3e7-6e30-4ca9-ad07-ba5dc4f2ca78","added_by":"auto","created_at":"2025-06-25 17:01:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2847042,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4867643/v1/048f8e13-cb9a-4f93-953e-54154e46f3ff.pdf"},{"id":63878248,"identity":"752f8dc5-4352-4b20-a8a5-6546b78eb403","added_by":"auto","created_at":"2024-09-03 09:45:04","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":155304,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineDataSupplementfuranandasthma.docx","url":"https://assets-eu.researchsquare.com/files/rs-4867643/v1/05003bcb0c6c2bf66a682a34.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Associations of furan exposure with the prevalence and mortality in asthma: A prospective cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAsthma is a chronic inflammatory respiratory disease marked by airway hyperresponsiveness and remodeling, leading to dyspnea and wheezing. \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The multifaceted risk factors associated with asthma encompass environmental variables such as air pollution\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, occupational dust\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, smoking\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, and environmental chemicals exposure\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Great deal of research revealed that exposure to environmental chemicals associated with the rising frequency of asthma, exacerbation and increased healthcare use caused by asthma\u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Thus, it is imperative to investigate the relationship between environmental pollutants and asthma in order to support public health and environmental protection policies so lowering the burden of asthma.\u003c/p\u003e \u003cp\u003eFuran (C4H4O) is a volatile and carcinogenic heterocyclic compound in various thermally processed foods, such as cooking, baking, canning, and sterilization at 150 to 200\u0026deg;C\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Previous studies have reported that furan can penetrate biofilms. For instance, the intestine and lungs and be rapidly absorbed and extensively metabolized\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Furan can enter the human body through ingestion and inhalation when preparing food\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Tǎbǎran \u003cem\u003eet al.\u003c/em\u003e found that lung club cells of mice exposed to furan showed necrosis with airway denudation, regeneration and partial repair\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Meanwhile, a recent study has showed that the link between blood furan and chronic obstructive pulmonary disease (COPD) is mediated by inflammation\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. To date, the relationship between furan and asthma has never been investigated.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to explore the association between furan exposure, prevalence and mortality in asthma among adults. Furthermore, we investigated whether furan exposure is associated with lung function, participants-reported health outcomes, and participants-reported health-related quality of life (HQL).\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eNHANES is a population-based survey carried out annually by the National Center for Health Statistics (NCHS) since 1999, a division of the Centers for Disease Control and Prevention (CDC). The NHANES included interviews, physical exams, and laboratory tests. The study protocol received approval from the NCHS Research Ethics Board, and all participants gave their written consent. Details of NHANES has been documented elsewhere (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/nhanes/index.htm\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/nhanes/index.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e13,14\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eUltimately, we obtained the data from the NHANES 2007\u0026ndash;2012. These cycles were chosen because participants underwent the spirometry test in these waves. The total sample size of the NHANES 2007\u0026ndash;2012 was 30,442. Individuals under 18 years old (n\u0026thinsp;=\u0026thinsp;12,729), those missing data for asthma (n\u0026thinsp;=\u0026thinsp;17), and those without data for blood furan (n\u0026thinsp;=\u0026thinsp;10,649) were excluded after merging databases. Thus, 7,047 individuals satisfied the inclusion criteria for final analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eExposure Definitions\u003c/h2\u003e \u003cp\u003eSerum blood furan levels were measured using a protocol outlined in a previously published study\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In brief, the approach detects specific volatile organic compounds (VOCs) in whole blood at low parts-per-trillion levels. Since non-occupationally exposed individuals have blood VOC concentrations within this range, this method is useful for measuring levels. Laboratory measurements were carried out using centralized quality assurance and control techniques. The minimum detectable concentration of blood furan was 0.0250 (unit: ng/mL).\u003c/p\u003e \u003cp\u003eLog10 transformations were carried out where required to achieve a normal data distribution of blood furan level. In addition, participants were assigned into two groups according to the median of log10-transformed blood furan levels (LBFL): LBFL \u0026le; -1.752 ng/mL is assigned to furan \u003csup\u003eLow\u003c/sup\u003e group while LBFL \u0026gt; -1.752 ng/mL is assigned to furan \u003csup\u003eHigh\u003c/sup\u003e group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePrimary outcome\u003c/h2\u003e \u003cp\u003eThere are two primary outcomes in this study: the prevalence of asthma and respiratory mortality in asthma.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003ePrevalence of asthma\u003c/h2\u003e \u003cp\u003eAsthma is defined by a self-reported positive answer to the questionnaire: \u0026ldquo;Has a doctor or other health professional ever told you that you had asthma?\u0026rdquo;.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eRespiratory mortality in asthma\u003c/h2\u003e \u003cp\u003eAnother primary outcome was respiratory mortality in asthmatics, including chronic lower respiratory diseases (J40 - J47), influenza and pneumonia (J10 - J18). The information about mortality status and cause of death was obtained by NHANES-linked National Death Index (NDI) on December 31, 2019.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSecondary outcome\u003c/h2\u003e \u003cp\u003eThe secondary outcomes of this study were lung function (absolute value of FEV\u003csub\u003e1\u003c/sub\u003e[L], FEV\u003csub\u003e1\u003c/sub\u003e% predicted, absolute value of FVC[L], FVC % predicted, obstructive, and restrictive spirometry pattern) and participants-reported health outcomes, including asthma-related health outcomes (asthma attack, emergency room [ER] visits for asthma), respiratory symptoms (wheezing, phlegm production, dry cough, and exertional dyspnea), and participants-reported health-related quality of life (HQL) (days when physical health was poor, days when mental health was poor, inactive days because of poor health).\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eLung function\u003c/h2\u003e \u003cp\u003eLung function was assessed in participants ranging in age from 6 to 79 years. Detailed information about spirometry protocol and procedure is described elsewhere\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Spirometry testing was performed at the NHANES Mobile Examination Center following a standardized protocol, measuring forced expiratory volume in the first second (FEV\u003csub\u003e1\u003c/sub\u003e) and forced vital capacity (FVC). Predicted spirometry values were determined using normative reference equations from NHANES III data\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Percent (%) predicted FEV\u003csub\u003e1\u003c/sub\u003e, FVC, and FEV\u003csub\u003e1\u003c/sub\u003e/FVC were calculated using Global Lung Initiative equations based on the participant\u0026rsquo;s age, gender, height, and race/ethnicity\u003csup\u003e17\u003c/sup\u003e. Detailed information on spirometry administration is available in the NHANES spirometry procedures manual\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Moreover, obstructive spirometry was determined as FEV\u003csub\u003e1\u003c/sub\u003e/FVC\u0026thinsp;\u0026lt;\u0026thinsp;0.70, whereas restrictive spirometry was characterized as FVC\u0026thinsp;\u0026lt;\u0026thinsp;80% of predicted and FEV\u003csub\u003e1\u003c/sub\u003e/FVC\u0026thinsp;\u0026ge;\u0026thinsp;0.70\u003csup\u003e19\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eAsthma-related health outcomes\u003c/h2\u003e \u003cp\u003eAsthma-related health outcomes included asthma attack and ER visits for asthma in the past year. An asthma attack was identified by answering \u0026ldquo;yes\u0026rdquo; to the question. Detailed questions are described in Luyster FS \u003cem\u003eet al\u003c/em\u003e\u0026rsquo;s study\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRespiratory symptoms\u003c/h2\u003e \u003cp\u003eRespiratory symptoms consisted of wheezing, phlegm production, cough, and exertional dyspnea. Respiratory symptoms listed above were identified by answering \u0026ldquo;yes\u0026rdquo; to the question. Specific questions are described in Wu \u003cem\u003eet al\u003c/em\u003e\u0026rsquo;s study\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHQL\u003c/h2\u003e \u003cp\u003eHQL was assessed by questions about mental health and physical health in the past 30 days. Specific questions are described in Luyster FS \u003cem\u003eet al\u003c/em\u003e\u0026rsquo;s study\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDemographic and Clinical Data\u003c/h2\u003e \u003cp\u003eThe data of demographic and clinical on study participants was collected using questionnaires and laboratory tests, consisting of age, gender (male/female), race/ethnicity, educational attainment, marital status, poverty-income ratio (PIR) level, body mass index (BMI), serum cotinine (ng/ml), alcohol drinking, chronic disease (cancer/malignancy, coronary heart disease, diabetes mellitus, and hypertension) and count of white blood cell (WBC) count.\u003c/p\u003e \u003cp\u003eRace/ethnicity was classified by Mexican American, other Hispanic, non-Hispanic black and white, and others race. Educational attainment was categorized as college or more, high school, middle school or lower. Marital status was classified as married/partnered, divorced/separated, or widowed/single. The PIR was ranged from 0 to 5, calculated based on guidelines and adjusted for family size, year, and state. A value of zero means no income and five means income at least five times the federal poverty level. As a metabolite of nicotine, serum cotinine is utilized to measure recent engagement in tobacco use\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Alcohol drinking was defined as how many drinks did you have over the past 12 months on average annually, which classified as \u0026ge;\u0026thinsp;4 drinks/day, 1\u0026ndash;3 drinks/day, and never drinking. Chronic disease included bronchitis, emphysema, cancer/malignancy, coronary heart disease, diabetes mellitus, and hypertension defined as self-reported physician diagnosis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eCategorical variables are reported as frequencies and proportions, whereas continuous variables are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median (Quartiles [Q] 1, 3) based on the data distribution. The difference between two groups for each variable was analyzed appropriately using t-test or Mann Whitney U test for continuous variables and χ\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e tests for categorical variables.\u003c/p\u003e \u003cp\u003eTo explore the link between LBFL and asthma prevalence, we conducted an RCS analysis to evaluated the dose-response association. Multiple logistic regression analyses were used to assess this association, taking into account various covariates. Initially, we employed a crude model without adjusting any covariates. Next, we developed Model I, which adjusted for age, gender, ethnicity, marital status, and educational attainment. Finally, Model II comprised the same variables as Model I, with additional adjustments for BMI, PIR, serum cotinine levels, alcohol drinking in the past year, and diabetes mellitus.\u003c/p\u003e \u003cp\u003eIn addition, we performed mediation analyses to determine if inflammation or lung function (represented by FEV\u003csub\u003e1\u003c/sub\u003e) mediated the relationship between LBFL and asthma prevalence, adjusting for confounders. In brief, mediation analysis was conducted using the R package \"mediation\" (version 4.5.0) with 1,000 simulations\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. We estimated the average direct effect (ADE), average causal mediation effect (ACME), and average total effect using a model-based inference approach. The proportion of the exposure's effect on the outcome that was mediated was calculated by dividing the ACME by the total effect (ACME\u0026thinsp;+\u0026thinsp;ADE)\u003csup\u003e22,23\u003c/sup\u003e. Additionally, we conducted stratified analyses to explore potential moderating effects of age, BMI, gender, ethnicity, marital status, and educational attainment.\u003c/p\u003e \u003cp\u003eMultiple Cox regression analyses were implemented to calculate adjusted hazard ratios (HRs) and 95% CIs for furan exposure and respiratory mortality in patients with asthma. Initially, the crude model was employed. Subsequently, Model I included adjustments for age, PIR, marital status, educational attainment, while Model II adjusted for the same variables as Model I and for serum cotinine, past-year alcohol drinking, coronary heart disease, and hypertension.\u003c/p\u003e \u003cp\u003eAll statistical analyses were conducted according to the CDS guidelines (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://wwwn.cdc.gov/nchs/nhanes/tutorials/default.aspx\u003c/span\u003e\u003cspan address=\"https://wwwn.cdc.gov/nchs/nhanes/tutorials/default.aspx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The statistical analyses included sample weights to account for the complex multi-stage stratified survey design used in NHANES. All statistical analyses were executed using R (version 4.3.1). Statistical significance was assessed at a two-sided \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics of participants\u003c/h2\u003e \u003cp\u003eA total of 7,047 participants were enrolled in the present study from the NHANES data from 2007 to 2012. Of the study participants, 951 participants diagnosed as asthma and 6,096 participants without asthma. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e listed the sociodemographic and clinical characteristics of the subjects grouped by asthma. As presented in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, asthmatics were more likely to be younger, more female, lower PIR, higher BMI, high serum cotinine, worse lung function, and more diabetes mellitus compared with participants without asthma (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, there were no significant differences in educational attainment and alcohol drinking, cancer, coronary heart disease, and high blood pressure were found (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). With respect to blood furan level, there is a significant increased LBFL for asthma patients (21.96% vs. 14.37%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compare with participants without asthma.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics and clinical characteristics of participants group by asthma.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll (n\u0026thinsp;=\u0026thinsp;7047)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHealthy controls (n\u0026thinsp;=\u0026thinsp;6096)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsthma (n\u0026thinsp;=\u0026thinsp;951)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.00(33.00,59.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.00(34.00,59.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.00(30.00,57.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3576(51.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3007(50.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e569(60.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3471(48.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3089(49.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e382(39.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMexican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1123(8.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1045(9.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78(4.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic Black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1445(10.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1213(10.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e232(13.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3083(67.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2627(67.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e456(69.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e767(5.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e660(5.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107(6.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Race - Including Multi-Racial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e629(7.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e551(7.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78(6.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational attainment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3482(58.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2973(58.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e509(60.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1581(22.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1368(22.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e213(21.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle school or lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1975(18.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1746(18.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e229(18.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e745(10.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e618(9.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e127(11.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e542(7.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e460(7.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82(8.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3663(55.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3235(56.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e428(48.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1239(18.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1032(17.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e207(23.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeparated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e258(2.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220(2.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38(2.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e596(5.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e528(5.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68(4.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.50(24.01,32.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.31(23.94,31.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.59(24.47,33.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.91(1.43,5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.95(1.48,5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.33(1.20,4.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum cotinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.04(0.01,4.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04(0.01, 2.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06(0.02,88.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePast-year alcohol drinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 drinks/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1049(15.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e912(19.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137(19.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;3 drinks/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2800(45.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2420(56.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e380(55.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1762(20.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1532(24.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e230(24.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpirometry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.18(2.57,3.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.21(2.61,3.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.03(2.31,3.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e% predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.11(88.51,107.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.78(90.08,107.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.51(80.34,102.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVC (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.05(3.33,4.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.06(3.36,4.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.92(3.18,4.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVC% predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101.24(92.16,110.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101.67(92.87,110.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.57(88.03,107.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e/FVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.00(2.11,3.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.07(2.20,3.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.57(1.72,3.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6403(90.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5555(91.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e848(88.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e638(9.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e537(8.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101(11.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6764(96.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5851(97.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e913(97.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e252(2.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e219(2.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(2.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBorderline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141(1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122(2.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6019(89.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5253(89.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e766(86.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e883(8.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e717(8.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e166(12.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4564(69.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3999(70.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e565(66.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2475(30.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2090(29.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e385(33.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLBFL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le; -1.752 ng/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6003(84.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5256(85.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e747(78.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; -1.752 ng/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1044(15.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e840(14.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e204(21.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eAbbreviation: BMI, body mass index; PIR, poverty-income ratio; FEV\u003csub\u003e1\u003c/sub\u003e, forced expiratory volume in 1 s; FVC, forced vital capacity; HBP, high blood pressure; LBFL, Log10-transformed blood furan levels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn addition, 6003 (85.2%) participants were divided into the furan \u003csup\u003eHigh\u003c/sup\u003e group and 1044 (14.8%) were divided into the furan \u003csup\u003eLow\u003c/sup\u003e group as depicted in Table E1. The patients in the furan \u003csup\u003eHigh\u003c/sup\u003e group were younger, had an elevated proportion were male, lower BMI, PIR, higher serum cotinine, worse lung function including FEV\u003csub\u003e1\u003c/sub\u003e, FEV\u003csub\u003e1\u003c/sub\u003e% predicted, FVC, FVC% predicted, and FEV\u003csub\u003e1\u003c/sub\u003e/FVC, and more participants with asthma (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePrimary Outcomes\u003c/h2\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003eFuran exposure and asthma prevalence\u003c/h2\u003e \u003cp\u003eCompared to the furan \u003csup\u003eLow\u003c/sup\u003e group, participants in the furan \u003csup\u003eHigh\u003c/sup\u003e group showed a higher risk of asthma in all models (crude model: odds ratio [OR]\u0026thinsp;=\u0026thinsp;1.68, 95% CI\u0026thinsp;=\u0026thinsp;1.31\u0026ndash;2.15, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; model 1: adjusted OR [aOR]\u0026thinsp;=\u0026thinsp;1.57 95% CI\u0026thinsp;=\u0026thinsp;1.20\u0026ndash;2.06, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002; model 2: aOR\u0026thinsp;=\u0026thinsp;1.75, 95% CI\u0026thinsp;=\u0026thinsp;1.14\u0026ndash;2.68, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012, respectively) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In addition, LBFL as continuous variable also suggested a positive association with the prevalence of asthma (crude model: OR\u0026thinsp;=\u0026thinsp;1.99, 95% CI\u0026thinsp;=\u0026thinsp;1.39\u0026ndash;2.85, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; model 1: aOR\u0026thinsp;=\u0026thinsp;1.86 95% CI\u0026thinsp;=\u0026thinsp;1.25\u0026ndash;2.78, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003; model 2: aOR\u0026thinsp;=\u0026thinsp;2.40, 95% CI\u0026thinsp;=\u0026thinsp;1.21\u0026ndash;4.78, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWeighted univariate and multivariate logistic regression analysis of LBFL for the risk of asthma\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog10-transformed blood furan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.99(1.39,2.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.86(1.25,2.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.40(1.21,4.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow (\u0026le; -1.752 ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (\u0026gt; -1.752 ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.68(1.31,2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.57(1.20,2.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.75(1.14,2.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAbbreviation: OR, odds ratio; CI, confidence interval; LBFL, Log10-transformed blood furan levels.\u003c/p\u003e \u003cp\u003eCrude model lacked adjustments for covariates.\u003c/p\u003e \u003cp\u003eModel 1 adjusted for age, gender, ethnicity, marital status, educational attainment.\u003c/p\u003e \u003cp\u003eModel 2 adjusted for age, gender, ethnicity, marital status, educational attainment, BMI, PIR, serum cotinine, past-year alcohol drinking, and diabetes mellitus.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMoreover, the RCS model exhibited that LBFL were linearly related to the prevalence of asthma adjusting for age, gender, BMI, ethnicity, marital status, educational attainment, PIR, serum cotinine, past-year alcohol drinking, and diabetes mellitus (\u003cem\u003eP\u003c/em\u003e for overall\u0026thinsp;=\u0026thinsp;0.0003; \u003cem\u003eP\u003c/em\u003e for non-linear\u0026thinsp;=\u0026thinsp;0.1311) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). And ROC analysis showed that the area under roc curve (AUC) value in the fully adjusted model was 0.655 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analyses of factors impacting the association of asthma prevalence with furan exposure\u003c/h2\u003e \u003cp\u003eFurthermore, subgroup analysis was employed to further investigate the association between furan exposure and the prevalence of asthma stratified by age, gender, BMI, ethnicity, marital status, and educational attainment in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (Detail data as shown in Table E2). In subgroups analysis, a statistically significant link between exposure to furan and asthma prevalence was only observed in the less than 60 years age group, in those with a BMI between 25-29.9 kg/m\u003csup\u003e2\u003c/sup\u003e, in females, in those were non-Hispanic white and other Hispanic, in married, and in those with middle school or low and college or more (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In addition, age, gender, BMI, ethnicity, marital status, and educational attainment did not have significant interactions with the furan exposure (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMediation analysis of lung function involved in the effects of furan on asthma\u003c/h2\u003e \u003cp\u003eFurthermore, we analyzed the associations of LBFL with inflammatory cells and lung function in adults. There was a substantial positive correlation between LBFL and lymphocytes (β\u0026thinsp;=\u0026thinsp;0.346, 95% CI\u0026thinsp;=\u0026thinsp;0.207\u0026ndash;0.485, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), neutrophils (β\u0026thinsp;=\u0026thinsp;1.005, 95% CI\u0026thinsp;=\u0026thinsp;0.559\u0026ndash;1.451, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and FEV\u003csub\u003e1\u003c/sub\u003e (β = -0.351, 95% CI = -0.500 - -0.202, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), as shown in Table E3. However, no association was observed between furan exposure with monocytes, eosinophils, and basophils (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Additionally, asthma exhibited a positive association with eosinophils and FEV\u003csub\u003e1\u003c/sub\u003e (β\u0026thinsp;=\u0026thinsp;0.041, 95% CI\u0026thinsp;=\u0026thinsp;0.025\u0026ndash;0.056, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; β = -0.222, 95% CI = -0.293 - -0.151, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; respectively) (Table E3). Nevertheless, there was no association between asthma with lymphocytes, monocytes, neutrophils and basophils (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eAs Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e displayed, mediation analyses indicated that the absolute value of FEV\u003csub\u003e1\u003c/sub\u003e partially mediated the association between furan exposure and asthma prevalence, with mediated proportions of 30.93% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eFuran exposure and respiratory mortality of asthma\u003c/h2\u003e \u003cp\u003eTwo patients were eliminated due to lack of follow-up among the 951 asthmatic patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, 18 patients died from respiratory illnesses, giving weighted respiratory mortality of 1.90%. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the positive correlation found in both models between LBFL and respiratory mortality of asthma. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that LBFL and respiratory mortality in asthma patients were positively correlated, with the Cox regression analysis controlling for age, PIR, marital status, educational attainment, serum cotinine, past-year alcohol drinking, coronary heart disease, and hypertension (hazard ratio [HR]\u0026thinsp;=\u0026thinsp;27.88, 95% CI\u0026thinsp;=\u0026thinsp;4.19\u0026ndash;185.69, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWeighted univariate and multivariate cox regression analysis of LBFL and respiratory mortality of asthma.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog10-transformed blood furan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.65(1.22, 10.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.33(7.08, 138.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.88(4.19, 185.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow (\u0026le; -1.752 ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (\u0026gt; -1.752 ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.52(1.02, 6.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.07(5.33, 42.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.88(16.86, 68.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAbbreviation: HR, hazard ratio; CI, confidence interval; LBFL, Log10-transformed blood furan levels.\u003c/p\u003e \u003cp\u003eCrude model lacked adjustments for covariates.\u003c/p\u003e \u003cp\u003eModel 1 adjusted for age, PIR, marital status, educational attainment.\u003c/p\u003e \u003cp\u003eModel 2 adjusted for age, PIR, marital status, educational attainment, serum cotinine, past-year alcohol drinking, coronary heart disease, and hypertension.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eSecondary outcome\u003c/h2\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eLung function\u003c/h2\u003e \u003cp\u003eCompared with furan \u003csup\u003eLow\u003c/sup\u003e group, those in the furan \u003csup\u003eHigh\u003c/sup\u003e group had worse FEV\u003csub\u003e1\u003c/sub\u003e, FEV\u003csub\u003e1\u003c/sub\u003e% predicted, and FVC % predicted (3.08 [2.48,3.64] vs. 3.20 [2.59,3.86] L, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; 91.90 [81.61,101.00] vs. 98.94 [90.22,107.83] %, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; 99.99 [90.15,108.09] vs. 101.52 [92.73,110.49], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01; respectively) and a higher proportion of obstructive spirometry pattern (26.63% vs. 11.29%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table E6). But no significant difference was observed in restrictive spirometry pattern (Table E6).\u003c/p\u003e \u003cp\u003eAfter multivariate adjustment, a one-unit increase in LBFL was significantly associated with 0.35 decrements in absolute value of FEV\u003csub\u003e1\u003c/sub\u003e (β = -0.35, 95% CI = -0.50 - -0.20. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and with 10.59 decrements in percent predicted FEV\u003csub\u003e1\u003c/sub\u003e (β = -10.59, 95% CI = -14.56 - -6.63. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) after adjusting for age, gender, BMI, ethnicity, marital status, educational attainment, PIR, serum cotinine, bronchitis, emphysema, diabetes mellitus. In addition, after adjusting for all confounders in the master analytical model 2 above, a non-linear correlation was observed between furan exposure and absolute value of FEV\u003csub\u003e1\u003c/sub\u003e (\u003cem\u003eP\u003c/em\u003e for overall\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; \u003cem\u003eP\u003c/em\u003e for non-linear\u0026thinsp;=\u0026thinsp;0.0156) in Figure E1. A linear correlation was observed between furan exposure and percent predicted FEV\u003csub\u003e1\u003c/sub\u003e, absolute value of FVC, and percent predicted FVC (\u003cem\u003eP\u003c/em\u003e for overall\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003cem\u003eP\u003c/em\u003e for non-linear\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Figure E1).\u003c/p\u003e \u003cp\u003eConsequently, LBFL was associated with an elevated risk of an obstructive spirometry pattern (aOR\u0026thinsp;=\u0026thinsp;5.02, 95% CI\u0026thinsp;=\u0026thinsp;2.97\u0026ndash;8.47, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), but not with restrictive spirometry pattern (aOR\u0026thinsp;=\u0026thinsp;0.84, 95% CI\u0026thinsp;=\u0026thinsp;0.45\u0026ndash;1.56, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.57) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWeighted univariate and multivariate regression models of LBFL predicting lung function and patient-reported health outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCrude Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ/OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ/OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eβ/OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.26(-0.35, -0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.33(-0.43, -0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.35(-0.50, -0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e% predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-12.43(-14.76, -10.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-11.01(-13.61, -8.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-10.59(-14.56, -6.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVC (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03(-0.11, 0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.08(-0.20, 0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.14(-0.32, 0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVC % predicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.16(-6.65, -1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3( -5.606, -0.393)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.26( -7.10, 0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObstructive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.82(3.71, 6.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.17(4.57, 8.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.02(2.97, 8.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRestrictive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93(0.59, 1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86(0.53,1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.84(0.45, 1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma-related health outcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma attack in past yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.84(0.90, 3.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.00(0.94,4.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.25(0.82, 12.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eER visits for asthma in past yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03(0.35, 3.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02(0.31, 3.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.11(0.07, 59.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheezing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.88(3.68, 6.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.35(3.23,5.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.48(2.72, 7.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhlegm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.37(3.52, 8.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.67(3.67, 8.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.16(3.09, 16.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.47(4.75, 11.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.60(4.24, 10.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.73(3.58, 16.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExertional dyspnea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.58(1.82, 3.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.45(1.71, 3.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.90(1.58, 5.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHQL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays physical health was not good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.18(1.86, 4.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.85(1.51, 4.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.61(0.88, 4.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays mental health was not good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.05(2.71, 5.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.37(2.05, 4.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.23(0.38, 4.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive days due to health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.85(0.96, 2.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.61(0.74,2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.04(-0.17, 2.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAbbreviation: ER, emergency room; OR, odds ratio; CI, confidence interval; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; LBFL, Log10-transformed blood furan levels; HQL, health-related quality of life.\u003c/p\u003e \u003cp\u003eCrude model lacked adjustments for covariates.\u003c/p\u003e \u003cp\u003eModel 1 adjusted for age, gender, ethnicity, marital status, educational attainment.\u003c/p\u003e \u003cp\u003eModel 1 adjusted for age, gender, ethnicity, marital status, educational attainment, BMI, PIR, serum cotinine, bronchitis, emphysema, diabetes mellitus.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eAsthma-related health outcomes\u003c/h2\u003e \u003cp\u003eNo significant difference was found in asthma attack and ER visits for asthma in past year between furan \u003csup\u003eLow\u003c/sup\u003e group and furan \u003csup\u003eHigh\u003c/sup\u003e group (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and E6).\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eRespiratory symptoms\u003c/h2\u003e \u003cp\u003eCompared with participants in the furan \u003csup\u003eLow\u003c/sup\u003e group, those in the furan \u003csup\u003eHigh\u003c/sup\u003e group had a higher proportion of wheezing (27.59% vs. 10.40%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), phlegm (19.92% vs. 6.40%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), cough (26.78% vs. 7.35%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and exertional dyspnea (44.65% vs. 28.09%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table E6).\u003c/p\u003e \u003cp\u003eSimilarly, LBFL was associated with higher odds of wheezing (aOR\u0026thinsp;=\u0026thinsp;4.48, 95% CI\u0026thinsp;=\u0026thinsp;2.72\u0026ndash;7.40, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), phlegm (aOR\u0026thinsp;=\u0026thinsp;7.16, 95% CI\u0026thinsp;=\u0026thinsp;3.09\u0026ndash;16.61, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), cough (aOR\u0026thinsp;=\u0026thinsp;7.73, 95% CI\u0026thinsp;=\u0026thinsp;3.58\u0026ndash;16.71, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and exertional dyspnea (aOR\u0026thinsp;=\u0026thinsp;2.90, 95% CI\u0026thinsp;=\u0026thinsp;1.58\u0026ndash;5.30, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) in the past 12 months, adjusting for age, gender, BMI, ethnicity, marital status, educational attainment, PIR, serum cotinine, bronchitis, emphysema, diabetes mellitus.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eHQL\u003c/h2\u003e \u003cp\u003eParticipants in the furan \u003csup\u003eHigh\u003c/sup\u003e group had worse HQL including days when physical health was poor, days when mental health was poor, and inactive days due to poor health (5.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39 vs. 3.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; 6.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46 vs. 3.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; 3.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33 vs. 1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; respectively), as compared to participants in the furan \u003csup\u003eLow\u003c/sup\u003e group.\u003c/p\u003e \u003cp\u003eFurthermore, LBFL was also associated with more days with poor physical or poor mental health but not of inactive days due to poor health during after adjusted for age, gender, BMI, ethnicity, marital status, educational attainment, PIR, serum cotinine, bronchitis, emphysema, and diabetes mellitus (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, we\u0026rsquo;re first to sought to examine systematic relationship between furan exposure, asthma prevalence, and asthma-related respiratory mortality in this prospective cohort study. We found that a higher LBFL was associated with greater odds of the prevalence and mortality of asthma. Lung function, particularly FEV\u003csub\u003e1\u003c/sub\u003e, was identified as a mediator in the relationship between LBFL and asthma prevalence. Additionally, our results indicated that elevated LBFL were associated with worse lung function, increased risk of respiratory symptoms, and lower risk of self-reported HQL after adjusting for covariates. The results indicated that furan as a common environmental pollution may be a notable risk factor for asthma, which highlights the importance of considering environmental exposures in public health and deepens our understanding of the factors contributing to asthma.\u003c/p\u003e \u003cp\u003eAccurately identifying environmental chemical exposure is crucial for understanding its potential impact on lung health\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Furan, a volatile organic compound as a potential human carcinogen\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. It is common to found in heat-processed foods through heat treatment methods\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Therefore, individuals are at risk of furan toxicity. This is particularly alarming due to the widespread presence of furan in the environment, highlighting its potential role as a public health hazard.\u003c/p\u003e \u003cp\u003eThere are some issues that could explain the adverse effects of furan on respiratory health. A previous investigation indicated that bronchiolar club cell enlargement, cytoplasmic vacuolation, and necrosis along with airway denudation and an inflammatory response consisting of bronchiolar wall infiltration by low numbers of many neutrophils and lymphocytes when breathing furan \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. According to Bas et al.'s study, pro-inflammatory cells moved into the bronchioles and alveolar gaps of the rat lungs, indicating that the oral furan administration had harmed the histoarchitectural structures of the lungs\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Furan exposure may cause lung dysfunction through inflammation, altered histoarchitectural characteristics, genomic instability or damage, and loss of redox equilibrium.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. All these studies demonstrated that furan was consumed orally or inhaled causing lung damage through various pathological mechanisms. The exact mechanism of the effect of furan exposure on the lungs of asthmatic patients and mouse models of asthma need further exploration in the future.\u003c/p\u003e \u003cp\u003eLung function measurement forms a crucial part of the clinical assessment and management of patients with asthma. Individuals exposed to higher levels of furan exhibited notably lower FEV\u003csub\u003e1\u003c/sub\u003e, FEV\u003csub\u003e1\u003c/sub\u003e% predicted and FVC and FEV\u003csub\u003e1\u003c/sub\u003e/FVC, indicative of impaired lung function. Inconsistent with our study, Ahman M \u003cem\u003eet al.\u003c/em\u003e found that workers exposed to furan resin sand showed a decrease in FVC and total lung capacity but no fall in any other lung-function variable\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. There are two main reasons for the disparity about lung function between the two studies: the difference of enrolled population and the study design of two studies. Hence, further studies required to verify that one possible mechanism for furan-related asthma could be represented by FEV1. Understanding this pathway is crucial for developing targeted interventions aimed at preserving lung function and mitigating the adverse effects on environmental pollutants.\u003c/p\u003e \u003cp\u003eWe found that LBFL was positively associated with participants-reported health outcomes including HQL, and respiratory symptom burden. These respiratory symptom burden not only reflect underlying respiratory dysfunction but also significantly impact daily living and overall well-being. The worse HQL indicating that the adverse effects of furan extend beyond clinical measures to affect subjective health perceptions and daily functioning.\u003c/p\u003e \u003cp\u003eAlthough Sun \u003cem\u003eet al.\u003c/em\u003e\u0026rsquo;s study found that LBFL was associated with respiratory disease mortality in COPD patients\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Nonetheless, no other studies have investigated the effect of furan exposure on the risk of respiratory disease mortality in participants with asthma. In the study, those in the furan \u003csup\u003eHigh\u003c/sup\u003e had a higher risk of respiratory disease mortality in participants with asthma compared with the furan \u003csup\u003eLow\u003c/sup\u003e in individuals with asthma, which suggests that a reduction in LBFL may reduce the risk of respiratory disease mortality in participants with asthma.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, our study cannot demonstrate causal relationships between furan exposure and the prevalence of asthma. Further longitudinal studies are necessary to establish causality and monitor changes in lung function and asthma prevalence over time in relation to furan exposure. Second, the diagnosis of asthma depends on self-reported rather than a more reliable and accurate method such as lung function testing, which may lead to recall bias. Third, although we adjusted potential risk factors, the existence of unknown confounders cannot be completely eliminated, and some important covariates, such as medication use (OCS and ICS/LABA), asthma control level, or multi-pollutant adjustment.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study indicated a positive link of furan exposure with the prevalence and respiratory mortality of asthma. FEV\u003csub\u003e1\u003c/sub\u003e served as a mediator in this relationship underscores the potential of furan to contribute to the asthma burden through direct respiratory impairment. This implies that reducing environmental exposure to furan could potentially decrease asthma prevalence and respiratory mortality, thereby improving overall respiratory health. The evidence provided by this study underscores the need for a comprehensive approach to addressing environmental pollutants like furan and their impact on respiratory health.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACME: average causal mediation effect\u003c/p\u003e\n\u003cp\u003eADE: average direct effect\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eaOR: adjusted odds ratio\u003c/p\u003e\n\u003cp\u003eBMI: body mass index\u003c/p\u003e\n\u003cp\u003eCDC: Centers for Disease Control and Prevention\u003c/p\u003e\n\u003cp\u003eCI: confidence interval\u003c/p\u003e\n\u003cp\u003eER: emergency room\u003c/p\u003e\n\u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e: forced expiratory volume in 1 s\u003c/p\u003e\n\u003cp\u003eFVC: forced vital capacity\u003c/p\u003e\n\u003cp\u003eHBP: high blood pressure\u003c/p\u003e\n\u003cp\u003eHQL: health-related quality of life\u003c/p\u003e\n\u003cp\u003eLBFL: log10-transformed blood furan levels\u003c/p\u003e\n\u003cp\u003eNCHS: National Center for Health Statistics\u003c/p\u003e\n\u003cp\u003eNHANES: National Health and Nutrition Examination Survey\u003c/p\u003e\n\u003cp\u003eOR: odds ratio\u003c/p\u003e\n\u003cp\u003ePIR: poverty-income ratio\u003c/p\u003e\n\u003cp\u003eQ: Quartiles RCS: restricted cubic spline\u003c/p\u003e\n\u003cp\u003eSD: standard deviation\u003c/p\u003e\n\u003cp\u003eVOCs: volatile organic compounds\u003c/p\u003e\n\u003cp\u003eWBC: white blood cell\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol received approval from the NCHS Research Ethics Board, and was performed in accordance with the Declaration of Helsinki. All participants gave their written consent. Details of NHANES has been documented elsewhere (https://www.cdc.gov/nchs/nhanes/index.htm).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublicly available datasets were analyzed in this study. These data can be found here: https://www.cdc.gov/nchs/nhanes/. The code used for these analyses are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (8217010602).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJiangtao Lin\u0026nbsp;and Shuwen Zhang, conceived the study, performed the data interpretation and manuscript revision, and took accountability for all aspects of the work. Shuwen Zhang planned the work, carried out the data analysis, interpretation and drafted the manuscript.\u0026nbsp;Kunlu Shen, Bingqing Sun and Bowen Liu offered the help of statistical analysis. Chunxiao Li, Xin Hou, Min Xiang, Mengqi Zhou and\u0026nbsp;Jiangtao Lin\u0026nbsp;interpreted the results and contributed to the manuscript revision. All authors approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to all volunteers who participated in this study. The graphic abstract was made with assets from Freepik.com (www.freepik.com).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGlobal Initiative for Asthma. Global strategy for asthma management and prevention. 2023. Accessed January 1 2024. 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Toxicol Pathol. 2019;47(7):842\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun D, Wang Y, Wang J, Dilixiati N, Ye Q. Inflammation mediates the association between furan exposure and the prevalence and mortality of chronic obstructive pulmonary disease: National Health and Nutrition Examination Survey 2013\u0026ndash;2018. BMC Public Health. 2024;24(1):1046.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShan Z, Rehm CD, Rogers G, et al. Trends in Dietary Carbohydrate, Protein, and Fat Intake and Diet Quality Among US Adults, 1999\u0026ndash;2016. JAMA. 2019;322(12):1178\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu TD, Fawzy A, Brigham E, et al. Association of Triglyceride-Glucose Index and Lung Health: A Population-Based Study. Chest. 2021;160(3):1026\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFuran. \u003cem\u003eReport on carcinogens: carcinogen profiles.\u003c/em\u003e 2011;12:205\u0026ndash;207.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry. Eur Respir J. 2005;26(2):319\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHankinson JL, Odencrantz JR, Fedan KB. Spirometric reference values from a sample of the general U.S. population. Am J Respir Crit Care Med. 1999;159(1):179\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Center for Health Statistics (U.S.). National Health and Nutrition Examination Survey, Respiratory Health Spirometry Procedures Manual. Accessed January 1 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://wwwn.cdc.gov/nchs/data/nhanes/2011-2012/manuals/spirometry_procedures_manual.pdf\u003c/span\u003e\u003cspan address=\"https://wwwn.cdc.gov/nchs/data/nhanes/2011-2012/manuals/spirometry_procedures_manual.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCirillo DJ, Agrawal Y, Cassano PA. Lipids and pulmonary function in the Third National Health and Nutrition Examination Survey. Am J Epidemiol. 2002;155(9):842\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuyster FS, Shi X, Baniak LM, Morris JL, Chasens ER. Associations of sleep duration with patient-reported outcomes and health care use in US adults with asthma. Ann Allergy Asthma Immunol. 2020;125(3):319\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang W, Peng SF, Chen L, Chen HM, Cheng XE, Tang YH. Association between the Oxidative Balance Score and Telomere Length from the National Health and Nutrition Examination Survey 1999\u0026ndash;2002. Oxidative Med Cell Longev. 2022;2022:1345071.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTingley D, Yamamoto T, Hirose K, Keele L, Imai K. mediation: R Package for Causal Mediation Analysis. J Stat Softw. 2014;59(5):1\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eImai K, Keele L, Tingley D, Yamamoto T. Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies. Am Polit Sci Rev. 2011;105(4):765\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBatool Z, Xu D, Zhang X, et al. A review on furan: Formation, analysis, occurrence, carcinogenicity, genotoxicity and reduction methods. Crit Rev Food Sci Nutr. 2021;61(3):395\u0026ndash;406.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFDA UJhwcfgdfh. Question and Answers on the Occurrence of Furan in Food. 2004.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaş H, Pandir D. Protective Effects of Lycopene on Furan-treated Diabetic and Non-diabetic Rat Lung. Biomed Environ Sci: BES. 2016;29(2):143\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOwumi SE, Otunla MT, Arunsi UO. A biochemical and histology experimental approach to investigate the adverse effect of chronic lead acetate and dietary furan on rat lungs. Biometals: Int J role metal ions biology Biochem Med. 2023;36(1):201\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhman M, Alexandersson R, Ekholm U, Bergstr\u0026ouml;m B, Dahlqvist M, Ulfvarson U. Impeded lung function in moulders and coremakers handling furan resin sand. Int Arch Occup Environ Health. 1991;63(3):175\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-4867643/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4867643/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eFew studies have explored the role of furan exposure plays in aggravating asthma.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo access the relationship of furan exposure to asthma.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis is a prospective cohort study, involving 7,047 adults over 20 years old from the National Health and Nutrition Examination Survey 2007\u0026ndash;2012. Blood furan levels were employed to quantify furan exposure. Multivariate survey-weighted regressions were utilized to analyze the associations between furan exposure, the prevalence of asthma. Mediation analyses for furan exposure and asthma prevalence were conducted. Multiple Cox regression was employed to evaluate the association between furan exposure and asthma prognosis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAsthmatics have higher blood furan levels than non-asthmatics (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). After adjusting for covariates, log10-transformed blood furan levels (LBFL) were independently associated with an increased risk of asthma prevalence (adjusted odds ratio [aOR]\u0026thinsp;=\u0026thinsp;2.40, 95% confidence interval [CI]\u0026thinsp;=\u0026thinsp;1.21\u0026ndash;4.78, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014). There was a significant positive linear relationship between LBFL and risk of asthma (\u003cem\u003eP\u003c/em\u003e for linear\u0026thinsp;=\u0026thinsp;0.0003). In mediation analyses, FEV\u003csub\u003e1\u003c/sub\u003e was identified as mediators in the above relationships, with mediated proportions of 32.73%. Longitudinally, multiple Cox regression analysis demonstrated that LBFL were positively correlated with respiratory mortality in asthma (HR\u0026thinsp;=\u0026thinsp;27.88, 95% CI\u0026thinsp;=\u0026thinsp;4.19-185.69, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eExposure to furan revealed a positive association with greater odds of asthma, and lung function was identified as an important mediator. An elevated LBFL also is associated with an increased health care use, worse HQL, and prognosis of asthma.\u003c/p\u003e","manuscriptTitle":"Associations of furan exposure with the prevalence and mortality in asthma: A prospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-03 09:44:59","doi":"10.21203/rs.3.rs-4867643/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":"afba8f8b-bc3e-4b3b-9e68-2234a272db49","owner":[],"postedDate":"September 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-25T16:53:25+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-03 09:44:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4867643","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4867643","identity":"rs-4867643","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}