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. Author manuscript; available in PMC: 2024 Aug 1.
Published in final edited form as: Lung. 2023 Jul 19;201(4):325–334. doi: 10.1007/s00408-023-00636-4

Association of World Trade Center (WTC) Occupational Exposure Intensity with Chronic Obstructive Pulmonary Disease (COPD) and Asthma COPD Overlap (ACO)

Rafael E de la Hoz 1,2,7, Moshe Shapiro 1, Anna Nolan 3, Akshay Sood 4, Roberto G Lucchini 1, James E Cone 5, Juan C Celedón 6
PMCID: PMC10763856  NIHMSID: NIHMS1951962  PMID: 37468611

Abstract

Introduction

Reported associations between World Trade Center (WTC) occupational exposure and chronic obstructive pulmonary disease (COPD) or asthma COPD overlap (ACO) have been inconsistent. Using spirometric case definitions, we examined that association in the largest WTC occupational surveillance cohort.

Methods

We examined the relation between early arrival at the 2001 WTC disaster site (when dust and fumes exposures were most intense) and COPD and ACO in workers with at least one good quality spirometry with bronchodilator response testing between 2002 and 2019, and no physician-diagnosed COPD before 9/11/2001. COPD was defined spirometrically as fixed airflow obstruction and ACO as airflow obstruction plus an increase of ≥ 400 ml in FEV1 after bronchodilator administration. We used a nested 1:4 case-control design matching on age, sex and height using incidence density sampling.

Results

Of the 17,928 study participants, most were male (85.3%) and overweight or obese (84.9%). Further, 504 (2.8%) and 244 (1.4%) study participants met the COPD and ACO spirometric case definitions, respectively. In multivariable analyses adjusted for smoking, occupation, cohort entry period, high peripheral blood eosinophil count and other covariates, early arrival at the WTC site was associated with both COPD (adjusted odds ratio [ORadj] = 1.34, 95% confidence interval [CI] 1.01–1.78) and ACO (ORadj = 1.55, 95%CI 1.04–2.32).

Conclusion

In this cohort of WTC workers, WTC exposure intensity was associated with spirometrically defined COPD and ACO. Our findings suggest that early arrival to the WTC site is a risk factor for the development of COPD or of fixed airway obstruction in workers with pre-existing asthma.

Keywords: Occupational lung disease; Smoke inhalation injury; Chronic obstructive pulmonary disease; World Trade Center Attack, 2001; Longitudinal changes in lung function; Spirometry

Introduction

Occupational exposures at the World Trade Center (WTC) disaster site in 2001–2002 have been associated with a variety of adverse health effects [1], including a heterogeneous and often not easily classifiable group of chronic lower airway diseases (LAD) [1, 2]. In all surveillance cohorts with lung function data, the most frequently reported spirometric ventilatory impairment pattern has been reduced forced vital capacity (FVC), while airflow obstruction (characterized by a reduced FEV1/FVC ratio) has been considerably less frequently demonstrated [1, 38].

A subgroup of WTC workers with LAD has been shown to have accelerated longitudinal lung function decline [7, 9], but it is still unclear whether occupational WTC exposures lead to disabling chronic lung diseases, as such exposures have been inconsistently associated with chronic obstructive pulmonary disease (COPD) or asthma-COPD overlap (ACO), or with interstitial lung diseases.

A potential explanation for the discrepant findings of previous studies of WTC occupational exposure and COPD or ACO is limited phenotypic assessment (e.g., not including lung function measures) [10, 11]. We hypothesized that occupational exposures at the WTC site would be associated with COPD and ACO if these conditions were defined using objective spirometric data. We tested this hypothesis among participants in the Mount Sinai WTC General Responders Cohort, the largest occupational cohort of WTC rescue and recovery workers with spirometric data and assessment of bronchodilator responsiveness regardless of clinical status.

Methods

Subject Recruitment and Study Procedures

All study subjects participated in the screening, surveillance, and clinical programs of the WTC Health Program Clinical Center of Excellence at Mount Sinai Medical Center in New York City [8]. Details on subject recruitment, eligibility criteria, and screening and surveillance protocols have been previously reported [4, 8]. In brief, the members of this open cohort were workers or volunteers who performed rescue, recovery, clean up, and service restoration duties at the WTC disaster site between 11-September-2001 and June 2002 [12]. Beginning in July 2002, all subjects underwent an initial screening evaluation, which included questionnaires on respiratory and general health, and WTC-related occupational exposures, as well as physical examination, laboratory testing, spirometry, and chest radiograph (the latter repeated on alternate visits). Subsequent (“monitoring”) health surveillance visits included a similar evaluation at 12- to 18-month intervals, and clinical services were offered (often contiguously to the screening) for individualized diagnostic and treatment services [1, 1317]. Inclusion into this study required that WTC workers did not report a physician’s diagnosis of COPD before 11-September-2001, and that they had at least one screening and surveillance spirometry with adequate assessment of bronchodilator responsiveness (see below) between their baseline examination and 30-June-2019. We did not exclude subjects with pre-existing asthma from the current analysis, as fixed airflow obstruction and thus COPD or ACO could result from WTC exposures in those subjects.

All spirometries were performed using the EasyOne® portable flow device (ndd, Zurich, Switzerland). Bronchodilator response (BDR) was assessed at least once (most often at the baseline visit), irrespective of clinical status or indication, by repeating spirometry 15 min after administration of 180 μg of albuterol via metered dose inhaler and a dual-valve disposable spacer (LiteAire, Thayer Medical, Tucson, Arizona). BDR was calculated as change in FEV1 and/or FVC following albuterol administration as both absolute volume and as a percentage of the respective pre-bronchodilator measurement. Clinically significant BDR was then defined as an increment in pre-bronchodilator FEV1 or FVC ≥ 200 ml and ≥ 12% after bronchodilator administration. Of note, medication withholding was not required from those already on treatment. Predicted values for spirometric measurements were calculated for all subjects, based on reference equations from the third National Health and Nutrition Examination Survey (NHANES III) [18], and all testing, quality assurance, ventilatory impairment pattern definitions, bronchodilator response presence, and interpretative approaches followed American Thoracic Society recommendations [19, 20]. To be included in data analyses, spirometric maneuvers had to be acceptable and reproducible (based on a computer quality grade [21] of A or B, or C if at least 5 trials had been obtained), and a forced exhalatory time of at least 6 s.

Our exposure of interest was self-reported arrival at the WTC disaster site within 48 h (heretofore referred to as “early arrival”) at the WTC site. While environmental sampling was extremely limited [22] due to risk underestimation [23], early arrival at the site was previously associated with higher toxic inhalant concentrations (based on limited air sampling reports [24, 25]), reduced respiratory personal protective equipment usage [26], and adverse post-disaster lower airway symptoms and diagnoses in several large occupational cohorts [1, 3, 8, 26]. Our main outcome of interest was COPD, defined spirometrically (COPDspiro) as fixed air flow obstruction [27] (a postbronchodilator [post-BD] FEV1/FVC ratio < 0.7) in the absence of any subsequent spirometry with normal result or low FVC impairment pattern. As a secondary outcome, we defined a subgroup of those patients as asthma COPD overlap (ACOspiro), requiring both evidence of COPD (as above) and a post-BD increase in FEV1 ≥ 400 ml [28].

For descriptive purposes, we categorized COPD severity using the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification based on post-BD FEV1 [27]: mild/GOLD 1 if ≥ 80%, moderate/GOLD 2 if < 80% but ≥ 50%, severe/GOLD 3 if < 50% but ≥ 30%, and very severe/GOLD 4 if < 30%. Further, we report the prevalence of clinically significant exertional dyspnea (the most frequent respiratory symptom in this cohort), defined by level 2 (“I walk slower than people of my same age on the level because of breathlessness, or have to stop for breath when walking at my own pace on the level”) or higher on the modified Medical Research Council (mMRC) breathlessness scale[29, 30] for each functional severity COPD category.

Covariates assessed at the baseline examination included age (divided into 5-year intervals), self-identified sex and ethnicity/race (Latino of any race, non-Latino White, non-Latino Black, and others), measured height, self-reported cumulative WTC exposure duration (< 60 vs. ≥ 60 days), occupation before 11-September-2001 (protective services; construction; building cleaning and maintenance, and electrical, telecommunications, and other installation and repair group [BCM&IRG]; and all others), date of entry into the cohort (2002–2005, 2006–2008, and 2009 and later)[12], and both smoking status (former or not), and smoking intensity (in pack-years). A subject was considered a never smoker if (s)he had smoked less than 20 packs of cigarettes (or 12 oz. of tobacco) in a lifetime, or less than 1 cigarette/day (or 1 cigar/week) for one year. A minimum of 12 months without tobacco use was required to deem a subject a former smoker[31]. Weight was measured and body mass index (BMI) recorded at each visit and classified as normal (18 < BMI < 25 kg/m2), overweight (25 ≤ BMI < 30 kg/m2), and obese (BMI ≥ 30 kg/m2). Covariates assessed at any visit included: BDR, highest recorded diastolic blood pressure (dichotomous, with 90 mm Hg as cut point), highest recorded serum glucose (whether fasting or not, dichotomous, with 200 mg/dl as cut point), highest serum triglycerides (whether fasting or not, dichotomous, with 300 mg/dl as cut point), highest peripheral blood eosinophil count (BEC, dichotomous, with 300/mcl as cut point)[32] and neutrophil count (dichotomous, with 6,000/mcl as cut point), and lowest HDL cholesterol (dichotomous, with 40 and 50 mg/dl as cut points for men and women, respectively). As in our previous study[8], we used HDL, glucose, triglycerides, and diastolic blood pressure as surrogate indicators of probable metabolic syndrome (MetSyn), categorized as 0–1 and 2–4 indicators.

The Mount Sinai Program for the Protection of Human Subjects (HS 17-01098) approved this study, and participants consented to have their data aggregated for research.

Statistical Analyses

We employed a nested 1:4 [33] case-control design matching on age (within ± 2 years), sex and height (within 5 cm), using incidence density sampling [34], where we matched each case to a sample of those who were at risk at the time of case occurrence, and a control subject could provide a matched comparison to more than one case. We used multiple imputation with fully conditional specification to address missing responses among the independent variables, and performed sensitivity analyses without multiple imputation as a comparison. The results with the complete and imputed data sets were essentially identical, and we thus present only the latter. Collinearity among variables was excluded by a variance inflation factor of 5. We examined standardized differences (StD) [35] to compare subjects included and excluded from the study, and those with COPDspiro and with self-reported diagnosis of COPD (and no COPDspiro). We deemed a standardized difference ≥ 0.2 as suggestive of a potentially significant difference in a covariate. Conditional logistic regression was used for the multivariable analyses, with fully specified models with covariates selected based on known, detected, or potential associations and confounding, and models are presented for COPDspiro and for the ACOspiro subgroup. In sensitivity analyses, we considered other WTC exposure indicators, particularly work on the pile resulting from the destructed WTC towers, and cumulative self-reported exposure duration, and tested the association of our main exposure variable and self-reported physician diagnoses of COPD and ACO. We also tested for interactions between the exposure of interest and selected covariates (age, smoking, and BEC), and between BEC and smoking. Lastly, we modeled FEV1 and FVC trajectories across time for subjects with 2 or more available good quality pre-bronchodilator spirometries during the study period, using linear mixed models with a random intercept to account for within-subject correlation between visits. We categorized time in one-year intervals between 1-July-2002 and 30-June-2019 and treated them as a classification variable. Models were adjusted for sex, age at time of spirometry, ethnicity/race and height. We created separate models for (1) ACOspiro, (2) COPD alone (i.e., excluding ACO), and (3) the rest of the cohort (NoCOPD).

A two-sided p value below 0.05 defined statistical significance, and we used the SAS program version 9.4 (SAS Institute, Cary, NC) for all analyses.

Results

After excluding 6074 subjects because of either low-quality spirometries (n = 5821) or pre-WTC self-reported physician-diagnosed COPD (n = 253), our study population consisted of 17,928 subjects. Compared to subjects excluded from this analysis, those included were more likely to be early entrants into the cohort (between 2002 and 2005) and to have a high BEC, but otherwise had very similar characteristics (Table OS1).

A total of 40,814 spirometries were available on 17,928 subjects (mean ± standard deviation [SD] = 2.28 ± 1.60] spirometries per subject), who were followed until 30-June-2019 for 4.28 ± 5.09 years since their first visit spirometry, 11 ± 5.55 years since 11-September-2001. Table 1 shows the main characteristics of the study participants, who had a mean (SD) age of 38.8 (8.8) years on 11-September-2001, and were predominantly male (85.3%), and overweight/obese (84.9%), consistent with previous reports in the WTC occupational cohorts [8, 36]. Through screening and surveillance, we identified 504 cases of COPD (2.8% of the total) a median of 4.93 (IQR 2.05–7.33) years after 11-September-2001, and most often (72.4%) at their baseline spirometry. Of the 504 subjects with COPD, 244 (48.4%, 1.4% of the study population) also met the study spirometric case definition of ACO. Of note, 2171 subjects reported a physician diagnosis of COPD, more than four times the number of COPDspiro cases. Compared to COPDspiro subjects, those individuals with self-reported physician diagnosed COPD seemed more likely to be of Latino/any race ethnicity and to work in construction or protective services, and much less likely to demonstrate bronchodilator responsiveness (see Table OS2). Also of note, and similar to our previous study on the WTC Chest CT Imaging subcohort [37], 34.1% of subjects with COPDspiro reported having never smoked tobacco products. Confirming also previous findings in that subcohort [37], annual cross-sectional prevalence of current tobacco smoking steadily decreased from 19.3% to 5.6% among all subjects examined within the years ending on 30-June-2003 to 30-June-2019, respectively.

Table 1.

Characteristics of 17,928 World Trade Center (WTC) rescue and recovery workers and volunteers, as well as those meeting the spirometric case definition of chronic obstructive pulmonary disease (COPDspiro, n = 504) and Asthma COPD overlap (ACOspiro, n = 244), and their control (n = 1682) subgroups

Characteristic value Entire group COPDspiro subgroup ACOspiro subgroup Control subgroup




n or mean % or SD n or mean % or SD n or mean % or SD n or mean % or SD
Arrival at WTC disaster site ≤ 48 h 11841 66.0 339 67.3 171 70.1 1074 65.4
> 48 h 5947 33.2 160 31.7 71 29.1 595 33.8
Missing 140   0.8 5 1.0 2 0.8 13   0.7
Age on 9/11 Years 38.8   8.8 44.7 9.9 43.1 10.0 43.5   8.7
Gender Female 2630 14.7 56 11.1 20 8.2 189 10.9
Male 15,298 85.3 448 88.9 224 91.8 1493 89.1
Ethnicity/race Non-Latino/Black 2099 11.7 61 12.1 28 11.5 248 14.3
Non-Latino/White 9994 55.7 321 63.7 153 62.7 1019 58.4
Latino/any race 4927 27.5 82 16.3 46 18.9 332 22.0
Non-Latino/Other 371   2.1 7 1.4 3 1.2 26   2.2
Missing 537   3.0 33 6.5 14 5.7 57   3.1
Height cm 174.4   9.1 175.6 8.5 176.6 8.2 175.5   8.2
Body mass index (BMI) category Normal 2668 14.9 94 18.7 31 12.7 252 13.6
Overweight 8039 44.8 199 39.5 97 39.8 792 48.2
Obese 7181 40.1 206 40.9 115 47.1 637 38.0
Missing 40   0.2 5 1.0 1 0.4 1   0.2
Cohort entry period 2002–2005 8946 49.9 284 56.3 144 59.0 757 42.8
2006–2008 4809 26.8 123 24.4 59 24.2 464 27.0
2009–2019 4173 23.3 97 19.2 41 16.8 461 30.1
Smoking status Never smoker 10,737 59.9 172 34.1 93 38.1 915 63.4
Former smoker 4379 24.4 171 33.9 79 32.4 556 23.7
Current smoker 2586 14.4 151 30.0 63 25.8 165 10.8
Missing 226   1.3 10 2.0 9 3.7 46   2.1
Smoking intensity Pack-years 4.4   9.9 12.6 18.8 10.5 16.8 5.8 12.5
Pre-WTC occupation group Construction 4270 23.8 146 29.0 69 28.3 432 22.4
BCM&IRG 1719   9.6 52 10.3 25 10.2 166   8.3
Other 3700 20.6 167 33.1 73 29.9 383 17.7
Protective 8239 46.0 139 27.6 77 31.6 701 51.6
WTC exposure duration < 60 days 8905 49.7 255 50.6 124 50.8 890 52.7
≥ 60 days 8902 49.7 246 48.8 119 48.8 781 46.5
Missing 121   0.7 3 0.6 1 0.4 11   0.7
Bronchodilator response Absent 14,308 79.8 201 39.9 12 4.9 1409 85.4
Present 2519 14.1 303 60.1 232 95.1 141   8.1
Missing 1101   6.1 132   6.6
Metabolic syndrome (MetSyn) criteria 0–1 criteria 15,033 83.9 403 80.0 194 79.5 1435 86.3
2–4 criteria 2221 12.4 64 12.7 33 13.5 208 11.5
Missing 674   3.8 37 7.3 17 7.0 39   2.2
Blood eosinophil count ≤ 300/mcl 14,180 79.1 355 70.4 161 66.0 1390 83.4
> 300/mcl 3053 17.0 111 22.0 65 26.6 249 14.4
Missing 695   3.9 38 7.5 18 7.4 43   2.3
Blood neutrophil count ≤ 6000/mcl 13,084 73.0 335 66.5 162 66.4 1283 75.4
> 6000/mcl 4159 23.2 131 26.0 64 26.2 360 22.4
Missing 685   3.8 38 7.5 18 7.4 39   2.2

BCM&IRG: buildings and grounds cleaning and maintenance, and electrical, telecommunications and other installation and repair groups

Based on post-BD FEV1, COPD was classified mostly as moderate/GOLD 2 (62.1%) or mild/GOLD 1 (27.6%), with few cases of severe/GOLD 3 (9.9%) or very severe/GOLD 4 (0.4%) COPD (Table OS3). This distribution of COPD severity did not differ by diagnostic subgroup (COPD excluding ACO vs. ACO). Table 2 also shows the count and proportion of subjects who reported level 2 or higher breathlessness on the mMRC breathlessness scale [29, 30].

Table 2.

Simple and multivariable conditional logistic regression models of spirometrically defined chronic obstructive pulmonary disease (COPDspiro, n = 504) and asthma COPD overlap subgroup(ACOspiro, n = 244) vs. early arrival (within 48 h) at the World Trade Center (WTC) disaster site in a 1:4 nested case–control study of WTC rescue and recovery workers, matched on age (within 2 years), sex, and height (within 5 cm)

Variable Value COPDspiro ACOspiro


OR 95% CI ORadj 95% CI OR 95% CI ORadj 95% CI
Arrival at WTC disaster site ≤48 h 1.09 0.86, 1.38 1.34 1.01, 1.78 1.21 0.85, 1.72 1.55 1.04, 2.32
> 48 h   Ref   Ref   Ref   Ref
Body mass index category Normal   Ref   Ref   Ref   Ref
Overweight 0.6 0.42, 0.86 0.73 0.48, 1.09 0.8 0.50, 1.28 0.87 0.52, 1.46
Obese 0.74 0.53, 1.02 0.87 0.6, 1.25 1.16 0.72, 1.86 1.22 0.72, 2.07
Cohort entry period 2009+   ref   Ref   Ref   Ref
2006–2008 1.54 1.12, 2.13 1.38 0.95, 1.98 1.75 1.06, 2.90 1.5 0.86, 2.59
2002–2005 2.42 1.84, 3.20 1.76 1.26, 2.46 2.9 1.84, 4.57 2.14 1.27, 3.60
Smoking intensity Pack-year 1.06 1.04, 1.07 1.05 1.04, 1.07 1.05 1.03, 1.06 1.04 1.03, 1.06
Former smoking status No   Ref   Ref   Ref   Ref
Yes 1.42 1.12, 1.80 0.84 0.63, 1.12 1.51 1.08, 2.11 0.97 0.63, 1.50
Pre-WTC occupation group Protective   ref   ref   ref   ref
BCM&IRG 2.65 1.76, 4.00 2.16 1.36, 3.45 2.35 1.34, 4.12 2.17 1.14, 4.14
Other 3.46 2.49, 4.81 2.97 2.09, 4.22 2.93 1.92, 4.47 2.77 1.74, 4.42
Construction 2.63 1.96, 3.54 2.03 1.42, 2.91 2.49 1.58, 3.93 1.99 1.17, 3.39
Metabolic syndrome criteria 0–1 criteria   Ref   Ref   Ref   Ref
2–4 criteria 1.24 0.89, 1.75 1.2 0.79, 1.84 1.37 0.84, 2.23 1.16 0.65, 2.07
Blood eosinophil count ≤ 300/mcl   Ref   Ref   Ref   Ref
> 300/mcl 1.65 1.25, 2.17 1.56 1.13, 2.17 2.22 1.52, 3.24 2.15 1.43, 3.23
Blood neutrophil count ≤ 6000/mcl   Ref   Ref   Ref   Ref
> 6000/mcl 1.5 1.15, 1.96 1.09 0.8, 1.48 1.6 1.13, 2.27 1.2 0.81, 1.76

The two multivariable models were adjusted for all the listed covariates

BCM&IRG: buildings and grounds cleaning and maintenance, and electrical, telecommunications and other installation and repair groups.

In bivariate analyses, age, tobacco smoking, early entry into the cohort (2002–2008), and high peripheral blood eosinophil and neutrophil counts were associated with increased odds of COPDspiro and ACOspiro. On the other hand, protective services (law enforcement) occupation was associated with reduced odds of COPDspiro and ACOspiro, and so was overweight status with COPDspiro. Table 2 shows the results of the multivariable analysis of early arrival at the WTC disaster site and COPD or ACO. In this analysis, early arrival at the WTC disaster site was associated with 34% increased odds of COPDspiro (95% CI for ORadj = 1.01 to 1.78, p = 0.04). Further, smoking intensity, high BEC, early entry into the cohort, and occupation other than law enforcement were also associated with increased odds of COPD. Also in a multivariable analysis, early arrival at the WTC site was also associated with 55% increased odds of ACOspiro (ORadj = 1.55, 95% CI 1.04 to 2.32, p = 0.03). There was no association between early arrival at the WTC site and self-reported physician-diagnosed COPD or ACO (data not shown). Our findings were unchanged in a sensitivity analysis with additional adjustment for other WTC exposure indicators (e.g., work on the towers pile, cumulative exposure duration).

We found no evidence of a significant interaction between early arrival at the WTC disaster site and smoking status, age, or evidence of high BEC on COPDspiro or ACOspiro, or between smoking status and intensity and high BEC (p ≥ 0.10 in all instances). Table OS4 and Figure OS1 show the mean yearly pre-bronchodilator FEV1 and FVC declines for subjects with 2 or more good quality pre-bronchodilator spirometries by group (median was 3 spirometries/subject), namely COPDspiro (without ACO, n = 130), ACOspiro (n = 123), and the rest of the cohort (NoCOPD, n = 9,806) over the study period. As expected, the mean yearly pre-bronchodilator expiratory flow declines were larger for COPDspiro than for NoCOPD, but not when compared with ACOspiro, in all likelihood due to sample size limitations and the use of pre-bronchodilator spirometric values.

Discussion

In this large cohort of WTC workers, WTC exposure intensity (as suggested by early arrival at the WTC disaster site) [1, 8] was significantly associated with spirometrically defined COPD and ACO, independently of age, tobacco smoking, peripheral BEC, and occupational classification. To our knowledge, this is the first study to focus on fixed airflow obstruction as a spirometric impairment pattern in WTC responders irrespective of clinical indication and to restrict the analyses to spirometries with a minimum forced exhalatory time of 6 s, besides acceptable reproducibility criteria (quality grades).

Previous studies had limited assessment of COPD and/or ACO. In a study of a subgroup of 2,137 New York City firefighters (out of a cohort of 9,598 exposed to the WTC 2001 disaster), who underwent complete pulmonary function testing, including clinically indicated post-bronchodilator spirometric testing, COPD was diagnosed in 314 subjects (14.7%), including 99 (4.6% of the total) who also met the standard definition of a positive BDR [38], were deemed to also have asthma, and thus ACO. Defining ACO based on the standard definition of BDR would grossly misclassify ACO patients, given its presence in a very large percentage (38–52%) of COPD patients [39]. Unsurprisingly, neither COPD nor ACO thus defined were significantly associated with higher WTC-related exposures, as indicated by early arrival at the site [11]. On the other hand, in a study from the WTC Health Registry, a closed cohort that includes 14,168 rescue and recovery workers, 5.9 and 7% self-reported physician diagnoses of COPD and ACO, respectively, and ACO was associated with higher occupational WTC exposures [10]. The severe limitations of self-reported diagnosis [40] or claims data [41] definitions of COPD and/or ACO are well known. There is, however, no fully satisfactory definition of ACO, and asthma with fixed airway obstruction [42] cannot be easily excluded by our spirometric one. Self-reported physician diagnoses of COPD and ACO were not significantly correlated with COPDspiro and ACOspiro in the current analysis or associated with our main WTC-related occupational exposure variable, strongly supporting the use of spirometric evidence for research on COPD in WTC workers.

Our study further underscores the non-negligible proportion of COPD cases occurring among nonsmokers, exposed in this case to occupational toxicants. Our findings agree with those of a recently published report of a significantly increased odds of COPDspiro among nonsmokers in a population-based study of individuals exposed to fine particles from a coal mine fire in Australia [43]. These two reports suggest the importance of discrete episodes of airway inhalation injuries (such as the WTC disaster, or the Hazlewood, Australia, coal mine explosion) in the evolution towards COPD in some individuals. These add to the emerging evidence for the effect of longer term exposures, such as vapors, gases, dusts and fumes in longest held occupation [4446], and environmental air pollutants [47] on the incidence of COPD.

Quantitative computed tomography (QCT) data from our WTC Chest CT Imaging subgroup of this same cohort, indicated that only about 9.6% of all study subjects [9], and 24% of 59 subjects with COPDspiro [37] had emphysema, as indicated by a low attenuation volume percent at 950 HU (LAV%, also known as EI950) exceeding the maximum of 2.5% reported in a nonsmoking healthy multiethnic population [48] and only 4% exceeding LAV% 5% (unpublished data). Our imaging data also revealed QCT evidence of both proximal (wall area percent, WAP), and (indirectly) distal airway involvement (expiratory-inspiratory mean lung density, MLDEI) in WTC workers with COPDspiro [37]. Further research is needed to investigate whether a chronic bronchitis COPD phenotype [49] predominates in this occupationally exposed cohort.

Our study had the added advantage of examining the largest, and most sociodemographically diverse occupational WTC cohort [12]. This cohort has the richest spirometry data set and is unique in that more than 80% of the subjects had bronchodilator responsiveness testing since 2002, usually at the baseline examination and, importantly, irrespective of clinical status or indications. The spirometry quality requirements for this study excluded suboptimal performance, reproducibility, expiratory effort, and (uniquely in the occupational WTC studies to date) short (< 6 s) forced exhalatory time. We also adjusted for substantial and highly prevalent potential confounders (notably, age and smoking), and for metabolic and other risk factors that have been reported in association with adverse respiratory outcomes in other cohort studies [5055]. Selection bias due to differential loss to follow-up is a possible but unlikely explanation for our findings, given the minimal observed differences between subjects who were and were not included in this analysis, and our multivariable model adjustments. We can perhaps not completely exclude, however, participation bias, in that both the healthiest and the sickest individuals may have chosen not to participate.

Study limitations include the lack of pre-WTC lung function data in the vast majority of subjects, as well as a suitable unexposed control population. Similar to essentially all WTC-related studies, we lack direct toxicant measurement data, as the exposures were understudied [22], and detailed exposure studies were very limited in size and duration [22, 24, 25]. Limited data indicated, however, that fine particulate matter (< 2.5 μm in aerodynamic diameter, PM2.5) increased 2.5 fold in the area [24], and the dust contained high concentrations of Calcium sulfate and carbonate [24, 56], PM2.5 samples reaching considerable alkalinity [56], and sharply decreasing concentrations after September 2001 [24, 25]. Additionally, respiratory personal protective equipment use was lowest within the first 48 h after the attack among all occupational groups and began improving afterwards [26]. Several studies in different occupational cohorts demonstrated increased adverse respiratory health effects within the first hours to days of the towers’ collapse [1, 3, 8, 26]. Those data support our empirically derived higher WTC-related occupational exposure indicator. In our studies thus far, adding other exposure indicators has not altered the association estimates. As these workers, aged in their early forties on 11-September-2001 had also been occupationally exposed to other vapors, dust, gas, and fumes [6], future studies might attempt to discern the effect of those pre-WTC occupational exposures. We lack data on post-WTC exposures, but we would expect those to have decreased, as a result of retirement, disability, and occupation changes for a substantial proportion of the cohort members [57]. We also lack data on other possibly relevant exposures, such as air pollution and biomass burning smoke [58]. We have data to suggest, on the other hand, that tobacco smoke exposure decreased very markedly and very early during the 2002–2019 surveillance period [8, 37]. Our study is based on screening and surveillance spirometry and may have missed some cases detectable with more detailed pulmonary function laboratory testing, and bronchodilator testing was infrequently performed after the baseline examination, and without requiring medication withholding, all of which may have contributed to an underestimation of the incidence of COPD over time. Repeat testing, particularly after treatment implementation, could have also excluded cases with “unstable” spirometric diagnosis of COPD, more likely in mild to moderate cases [59], such as most of our cases. On the other hand, our data confirmed the unreliability of self-reported diagnosis of COPD, and generally of questionnaire-based definitions of the disease[40].

Given the proportion of subjects with ACO and of nonsmokers, and the significance of early cohort entry in the adjusted associations (most excess asthma diagnoses were observed within a year after 11-September-2001 [26]), we suspect that a substantial proportion of our COPD cases were due to asthma developing fixed obstruction and thus meeting the COPD spirometric definition. Future investigations may help confirm or refute this.

In conclusion, we demonstrated in this large and diverse cohort of WTC workers and volunteers that occupational WTC exposure intensity, as indicated by early arrival at the disaster site, was associated with spirometrically defined COPD and that the association was stronger for the subgroup with ACO, independently of age, tobacco smoking and other risk factors.

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Acknowledgements

The authors would like to thank all participants in this study, and the staff of the Mount Sinai WTC Health Program Clinical Center of Excellence, and the WTC General Responders Cohort Data Center. Preliminary results of this work were presented as an abstract at the 2021 International Congress of the European Respiratory Society (Eur Respir J 2021;58 (Suppl 65):PA3353, https://doi.org/10.1183/13993003.congress-2021.PA3353), and as a preprint in SSRN (http://dx.doi.org/10.2139/ssrn.4353884). Dr. Roberto Lucchini is presently at the Department of Occupational and Environmental Health Sciences of the Robert Stempel College of Public Health and Social Work at Florida International University, Miami, FL, USA.

Funding

This work was supported by cooperative agreements No. U01 OH011697 (RED, PI), U01 OH011300 (AN, PI), and contract 200-2017-93325 (WTC General Responders Cohort Data Center, RGL, PI) from the Centers for Disease Control and Prevention/National Institute for Occupational Safety and Health (CDCP/NIOSH).

Footnotes

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s00408-023-00636-4.

Conflict of interest The authors had no other relevant financial conflict of interest to disclose. The contents of this article are the sole responsibility of the authors, and do not represent the official views of the CDCP/NIOSH.

References

  • 1.de la Hoz RE, Shohet MR, Chasan R, Bienenfeld LA, Afilaka AA, Levin SM, Herbert R (2008) Occupational toxicant inhalation injury: the World Trade Center (WTC) experience. Int Arch Occup Environ Health 81(4):479–485. 10.1007/s00420-007-0240-x [DOI] [PubMed] [Google Scholar]
  • 2.de la Hoz RE (2011) Occupational lower airway disease in relation to World Trade Center inhalation exposure. Curr Opin Allergy Clin Immunol 11(2):97–102. 10.1097/ACI.0b013e3283449063 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Prezant DJ, Weiden M, Banauch GI, McGuinness G, Rom WN, Aldrich TK, Kelly KJ (2002) Cough and bronchial responsiveness in firefighters at the World Trade Center site. N Engl J Med 347(11):806–815. 10.1056/NEJMoa021300 [DOI] [PubMed] [Google Scholar]
  • 4.Herbert R, Moline J, Skloot G, Metzger K, Barron S, Luft B, Markowitz S, Udasin I, Harrison D, Stein D, Todd AC, Enright P, Stellman JM, Landrigan PJ, Levin SM (2006) The World Trade Center disaster and the health of workers: five-year assessment of a unique medical screening program. Environ Health Perspect 114(12):1853–1858. 10.1289/ehp.9592 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Wisnivesky JP, Teitelbaum S, Todd AC, Boffeta P, Crane M, Crowley L, de la Hoz RE, Dellenbaugh C, Harrison D, Herbert R, Kim H, Jeon Y, Kaplan J, Katz C, Levin S, Luft B, Markowitz S, Moline JM, Ozbay F, Pietrzak RH, Shapiro M, Sharma V, Skloot G, Southwick S, Stevenson L, Udasin I, Wallenstein S, Landrigan PJ (2011) Persistence of multiple illnesses in September 11 rescue workers. Lancet 378(9794):888–897. 10.1016/S0140-6736(11)61180-X [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.de la Hoz RE, Weber J, Xu D, Doucette JT, Liu X, Carson DA, Celedón JC (2019) Chest CT scan findings in World Trade Center workers. Arch Environ Occup Health 74(5):263–270. 10.1080/19338244.2018.1452712 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.de la Hoz RE, Liu X, Doucette JT, Reeves AP, Bienenfeld LA, Wisnivesky JP, Celedón JC, Lynch DA, San José Estépar R (2018) Increased airway wall thickness is associated with adverse longitudinal first-second forced expiratory volume trajectories of former World Trade Center workers. Lung 196(4):481–489. 10.1007/s00408-018-0125-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.de la Hoz RE, Shapiro M, Nolan A, Celedón JC, Szeinuk J, Lucchini RG (2020) Association of low FVC spirometric pattern with WTC occupational exposures. Respir Med 170:106058. 10.1016/j.rmed.2020.106058 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Liu X, Reeves AP, Antoniak K, San José Estépar R, Doucette JT, Jeon Y, Weber J, Xu D, Celedón JC, de la Hoz RE (2021) Association of quantitative CT lung density measurements with divergent FEV1 trajectories in WTC workers. Clin Respir J 15(6):613–621. 10.1111/crj.13313 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Haghighi A, Cone JE, Li J, de la Hoz RE (2021) Asthma-COPD overlap in World Trade Center Health Registry enrollees, 2015–2016. J Asthma 58(11):1415–1423. 10.1080/02770903.2020.1817935 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Singh A, Liu C, Putman B, Zeig-Owens R, Hall CB, Schwartz T, Webber MP, Cohen HW, Berger KI, Nolan A, Prezant DJ, Weiden MD (2018) Predictors of asthma/COPD overlap in FDNY firefighters with World Trade Center dust exposure: a longitudinal study. Chest 154(6):1301–1310. 10.1016/jxhest.2018.07.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Woskie SR, Kim H, Freund A, Stevenson L, Park BY, Baron S, Herbert R, Siegel de Hernandez M, Teitelbaum S, de la Hoz RE, Wisnivesky JP, Landrigan P (2011) World Trade Center disaster: assessment of responder occupations, work locations, and job tasks. Am J Ind Med 54(9):681–695. 10.1002/ajim.20997 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.de la Hoz RE (2010) Occupational asthma and lower airway disease in former World Trade Center workers and volunteers. Curr Allergy Asthma Rep 10(4):287–294. 10.1007/s11882-010-0120-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.de la Hoz RE, Shohet MR, Cohen JM (2010) Occupational rhinosinusitis and upper airway disease: the World Trade Center experience. Curr Allergy Asthma Rep 10(2):77–83. 10.1007/s11882-010-0088-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.de la Hoz RE, Christie J, Teamer J, Bienenfeld LA, Afilaka AA, Crane M, Levin SM, Herbert R (2008) Reflux symptoms and disorders and pulmonary disease in former World Trade Center rescue and recovery workers and volunteers. J Occup Environ Med 50 (12):1351–1354. 10.1097/JOM.0b013e3181845f9b [DOI] [PubMed] [Google Scholar]
  • 16.de la Hoz RE, Johannson KA (2023) World Trade Center Health Program best practices for the diagnosis and treatment of fibrosing interstitial lung diseases. Arch Environ Occup Health 78(4):232–235. 10.1080/19338244.2023.2166007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Cone JE, de la Hoz RE (2023) World Trade Center Health Program best practices for diagnosing and treating chronic obstructive pulmonary disease. Arch Environ Occup Health 78(4):229–231. 10.1080/19338244.2022.2146040 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Hankinson JL, Odencratz JR, Fedan KB (1999) Spirometric reference values from a sample of the general US population. Am J Respir Crit Care Med 159(1):179–187. 10.1164/ajrccm.159.1.9712108 [DOI] [PubMed] [Google Scholar]
  • 19.American Thoracic Society (1995) Standardization of spirometry, 1994 update. Am J Respir Crit Care Med 152(3):1107–1136. 10.1164/ajrccm.152.3.7663792 [DOI] [PubMed] [Google Scholar]
  • 20.Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, Crapo R, Enright P, van der Grinten CPM, Gustafsson P, Jensen R, Johnson DC, MacIntyre N, McKay R, Navajas D, Pedersen OF, Pellegrino R, Viegi G, Wanger J (2005) Standardisation of spirometry. Eur Respir J 26(2):319–338. 10.1183/09031936.05.00034805 [DOI] [PubMed] [Google Scholar]
  • 21.Enright PL, Skloot GS, Cox-Ganser JM, Udasin IG, Herbert R (2010) Quality of spirometry performed by 13,599 participants in the World Trade Center Worker and Volunteer Medical Screening Program. Respir Care 55(3):303–309. https://rc.rcjournal.com/content/55/3/303.short [PubMed] [Google Scholar]
  • 22.Wallingford KM, Snyder EM (2001) Occupational exposures during the World Trade Center disaster response. Toxicol Ind Health 17(5–10):247–253. 10.1191/0748233701th112oa [DOI] [PubMed] [Google Scholar]
  • 23.Lippmann M, Cohen MD, Chen LC (2015) Health effects of World Trade Center (WTC) dust: an unprecedented disaster’s inadequate risk management. Crit Rev Toxicol 45(6):492–530. 10.3109/10408444.2015.1044601 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Thurston G, Maciejczyk P, Lall R, Hwang J, Chen LC (2003) Identification and characterization of World Trade Center disaster fine particulate matter air pollution at a site in Lower Manhattan following September 11. Epidemiology 14(5):S87–S88 [Google Scholar]
  • 25.Geyh AS, Chillrud S, Williams DL, Herbstman JB, Symons JM, Rees K, Ross J, Kim SR, Lim HJ, Turpin B, Breysse P (2005) Assessing truck driver exposure at the World Trade Center disaster site: personal and area monitoring for particulate matter and volatile organic compounds during October 2001 and April 2002. J Occup Environ Hyg 2(3):179–193. 10.1080/15459620590923154 [DOI] [PubMed] [Google Scholar]
  • 26.Wheeler K, McKelvey W, Thorpe L, Perrin M, Cone J, Kass D, Farfel M, Thomas P, Brackbill R (2007) Asthma diagnosed after September 11, 2001 among rescue and recovery workers: findings from the World Trade Center Health Registry. Environ Health Perspect 115(11):1584–1590. 10.1289/ehp.10248 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Global Initiative for Chronic Obstructive Lung Disease (2021) Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease - 2021 report. https://goldcopd.org/2021-gold-reports/. 1
  • 28.Mekov E, Nuñez A, Sin DD, Ichinose M, Rhee CK, Maselli DJ, Coté A, Suppli Ulrik C, Maltais F, Anzueto A, Miravitlles M (2021) Update on asthma-COPD overlap (ACO): a narrative review. Int J Chron Obstruct Pulmon Dis 16:1783–1799. 10.2147/copd.s312560 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Fletcher CM (1952) The clinical diagnosis of pulmonary emphysema - an experimental study. Proc R Soc Med 45(9):577–584 [PubMed] [Google Scholar]
  • 30.Williams N (2017) The MRC breathlessness scale. Occup Med (Lond) 67(6):496–497. 10.1093/occmed/kqx086 [DOI] [PubMed] [Google Scholar]
  • 31.Ferris BG (1978) Epidemiology standardization project (American Thoracic Society). Am Rev Respir Dis 118(6 Pt 2):1–120 [PubMed] [Google Scholar]
  • 32.Singh D, Agusti A, Martinez FJ, Papi A, Pavord ID, Wedzicha JA, Vogelmeier CF, Halpin DMG (2022) Blood eosinophils and chronic obstructive pulmonary disease: a GOLD Science Committee 2022 review. Am J Respir Crit Care Med 11:17–24. 10.1164/rccm.202201-0209PP [DOI] [PubMed] [Google Scholar]
  • 33.Hennessy S, Bilker WB, Berlin JA, Strom BL (1999) Factors influencing the optimal control-to-case ratio in matched case-control studies. Am J Epidemiol 149(2):195–197. 10.1093/oxfordjournals.aje.a009786 [DOI] [PubMed] [Google Scholar]
  • 34.Richardson DB (2004) An incidence density sampling program for nested case-control analyses. Occup Environ Med 61(12):e59. 10.1136/oem.2004.014472 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Austin PC (2009) Using the standardized difference to compare the prevalence of a binary variable between two groups in observational research. Communications in Statistics - Simulation and Computation 38(6):1228–1234. 10.1080/03610910902859574 [DOI] [Google Scholar]
  • 36.Webber MP, Lee R, Soo J, Gustave J, Hall CB, Kelly K, Prezant D (2011) Prevalence and incidence of high risk for obstructive sleep apnea in World Trade Center-exposed rescue/recovery workers. Sleep Breath 15(3):283–294. 10.1007/s11325-010-0379-7 [DOI] [PubMed] [Google Scholar]
  • 37.Weber J, Reeves AP, Doucette JT, Jeon Y, Sood A, San José Estépar R, Celedón JC, de la Hoz RE (2020) Quantitative CT evidence of airway inflammation in World Trade Center workers and volunteers with low FVC spirometric pattern. Lung 198(3):555–563. 10.1007/s00408-020-00350-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Pellegrino R, Viegi G, Brusasco V, Crapo RO, Burgos F, Casaburi R, Coates A, van der Grinten CPM, Gustafsson P, Hankinson J, Jensen R, Johnson DC, MacIntyre N, McKay R, Miller MR, Navajas D, Pedersen OF, Wanger J (2005) Interpretative strategies for lung function tests. Eur Respir J 26(5):948–968. 10.1183/09031936.05.00035205 [DOI] [PubMed] [Google Scholar]
  • 39.Calverley PMA, Burge PS, Spencer S, Anderson JA, Jones PW (2003) Bronchodilator reversibility testing in chronic obstructive pulmonary disease. Thorax 58(8):659–664. 10.1136/thorax.58.8.659 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Feinstein L, Wilkerson J, Salo PM, MacNell N, Bridge MF, Fessler MB, Thorne PS, Mendy A, Cohn RD, Curry MD, Zeldin DC (2020) Validation of questionnaire-based case definitions for chronic obstructive pulmonary disease. Epidemiology 31(3):459–466. 10.1097/ede.0000000000001176 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Turner RM, DePietro M, Ding B (2018) Overlap of asthma and chronic obstructive pulmonary disease in patients in the United States: analysis of prevalence, features, and subtypes. JMIR Public Health Surveill 4(3):60. 10.2196/publichealth.9930 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Bakakos A, Vogli S, Dimakou K, Hillas G (2022) Asthma with fixed airflow obstruction: from fixed to personalized approach. J Pers Med 12(3):333. 10.3390/jpm12030333 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Prasad S, Gao CX, Borg B, Broder J, Brown D, Ikin JF, Makar A, McCrabb T, Hoy R, Thompson B, Abramson MJ (2022) Chronic obstructive pulmonary disease in adults exposed to fine particles from a coal mine fire. Ann Am Thorac Soc 19(2):186–195. 10.1513/AnnalsATS.202012-1544OC [DOI] [PubMed] [Google Scholar]
  • 44.Mehta AJ, Miedinger D, Keidel D, Bettschart R, Bircher A, Bridevaux PO, Curjuric I, Kromhout H, Rochat T, Rothe T, Russi EW, Schikowski T, Schindler C, Schwartz J, Turk A, Vermeulen R, Probst-HenschKünzli NN (2012) Occupational exposure to dusts, gases, and fumes and incidence of chronic obstructive pulmonary disease in the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults. Am J Respir Crit Care Med 185(12):1292–1300. 10.1164/rccm.201110-1917OC [DOI] [PubMed] [Google Scholar]
  • 45.Blanc PD, Annesi-Maesano I, Balmes JR, Cummings KJ, Fishwick D, Miedinger D, Murgia N, Naidoo RN, Reynolds CJ, Sigsgaard T, Toren K, Vinnikov D, Redlich CA (2019) The occupational burden of nonmalignant respiratory diseases - an official American Thoracic Society and European Respiratory Society Statement. Am J Respir Crit Care Med 199(11):1312–1334. 10.1164/rccm.201904-0717ST [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Szeinuk J, de la Hoz RE (2022) Occupational chronic obstructive pulmonary disease. In: Bang KM (ed) Modern Occupational Disease Diagnosis, Epidemiology, Management and Prevention, vol 1, 1st edn. Bentham Science Books, Singapore, pp 104–127 [Google Scholar]
  • 47.Hendryx M, Luo J, Chojenta C, Byles JE (2019) Air pollution exposures from multiple point sources and risk of incident chronic obstructive pulmonary disease (COPD) and asthma. Environ Res 179(Pt A):108783. 10.1016/j.envres.2019.108783 [DOI] [PubMed] [Google Scholar]
  • 48.Hoffman EA, Ahmed FS, Baumhauer H, Budoff M, Carr JJ, Kronmal R, Reddy S, Barr RG (2014) Variation in the percent of emphysema-like lung in a healthy, nonsmoking multiethnic sample - The MESA Lung Study. Ann Am Thorac Soc 11(6):898–907. 10.1513/AnnalsATS.201310-364OC [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Young KA, Regan EA, Han MK, Lutz SM, Ragland M, Castaldi PJ, Washko GR, Cho MH, Strand M, Curran-Everett D, Beaty TH, Bowler RP, Wan ES, Lynch DA, Make BJ, Silverman EK, Crapo JD, Hokanson JE, Kinney GL (2019) Subtypes of COPD have unique distributions and differential risk of mortality. Chronic Obstr Pulm Dis 6(5):400–413. 10.15326/jcopdf.6.5.2019.0150 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Engstrom G, Lind P, Hedblad B, Wollmer P, Stavenow L, Janzon L, Lindgarde F (2002) Lung function and cardiovascular risk: relationship with inflammation-sensitive plasma proteins. Circulation 106(20):2555–2560. 10.1161/01.cir.0000037220.00065.0d [DOI] [PubMed] [Google Scholar]
  • 51.Engstrom G, Hedblad B, Nilsson P, Wollmer P, Berglund G, Janzon L (2003) Lung function, insulin resistance and incidence of cardiovascular disease: a longitudinal cohort study. J Intern Med 253(5):574–581. 10.1046/j.1365-2796.2003.01138.x [DOI] [PubMed] [Google Scholar]
  • 52.Johnston AK, Mannino DM, Hagan GW, Davis KJ, Kiri VA (2008) Relationship between lung function impairment and incidence or recurrence of cardiovascular events in a middle-aged cohort. Thorax 63(7):599–605. 10.1136/thx.2007.088112 [DOI] [PubMed] [Google Scholar]
  • 53.Hickson DA, Burchfiel CM, Liu J, Petrini MF, Harrison K, White WB, Sarpong DF (2011) Diabetes, impaired glucose tolerance, and metabolic biomarkers in individuals with normal glucose tolerance are inversely associated with lung function: the Jackson Heart Study. Lung 189(4):311–321. 10.1007/s00408-011-9296-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Godfrey MS, Jankowich MD (2016) The vital capacity is vital: epidemiology and clinical significance of the restrictive spirometry pattern. Chest 149(1):238–251. 10.1378/chest.15-1045 [DOI] [PubMed] [Google Scholar]
  • 55.Zeig-Owens R, Singh A, Aldrich TK, Hall CB, Schwartz T, Webber MP, Cohen HW, Kelly KJ, Nolan A, Prezant DJ, Weiden MD (2018) Blood leukocyte concentrations, FEV1 decline, and airflow limitation - a 15-year longitudinal study of World Trade Center-exposed firefighters. Ann Am Thorac Soc 15(2):173–183. 10.1513/AnnalsATS.201703-276OC [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.McGee JK, Chen LC, Cohen MD, Chee GR, Prophete CM, Haykal-Coates N, Wasson SJ, Conner TL, Costa DL, Gavett SH (2003) Chemical analysis of World Trade Center fine particulate matter for use in toxicologic assessment. Environ Health Perspect 111(7):972–980. 10.1289/ehp.5930 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Napier CO, Mbadugha O, Bienenfeld LA, Doucette JT, Lucchini R, Luna-Sánchez S, de la Hoz RE (2017) Obesity and weight gain among former World Trade Center workers and volunteers. Arch Environ Occup Health 72(2):106–110. 10.1080/19338244.2016.1197174 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Grahame TJ, Klemm R, Schlesinger RB (2014) Public health and components of particulate matter: the changing assessment of black carbon. J Air Waste Manag Assoc 64(6):620–660. 10.1080/10962247.2014.912692 [DOI] [PubMed] [Google Scholar]
  • 59.Aaron SD, Tan WC, Bourbeau J, Sin DD, Loves RH, MacNeil J, Whitmore GA (2017) Diagnostic instability and reversals of chronic obstructive pulmonary disease diagnosis in individuals with mild to moderate airflow obstruction. Am J Respir Crit Care Med 196(3):306–314. 10.1164/rccm.201612-2531OC [DOI] [PubMed] [Google Scholar]

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