FDNY Nutrition Cohort Characteristics. There were no significant demographic differences between the source cohort (N=9,508) and the study cohort (N=4,015/9,508; 42.23%) Out of the total subjects with WTC-OAD (N=921), 586 subjects (63.62%) had WTC-LI only, 197 subjects (21.39%) had AHR only, and 138 subjects (14.98%) had both WTC-LI and AHR. Within those with AHR (N=335), 126 (37.61%) had a positive bronchodilator, 175 (52.24%) had a positive methacholine, and 34 (10.15%) had both.
Subjects with WTC-OAD were more likely to be retired, member of the emergency medical services (EMS) rather than firefighter, and exposed the morning of 9/11 when compared to those who never developed WTC-OAD (p<0.001), Table 1. Of note, age at 9/11, smoking status, and race were no different in the WTC-OAD and never WTC-OAD populations, Table 1.
Clinical Measures. Time to reach WTC-OAD case definition was(mean ± SD) 6.37 ± 7.23 years for the study cohort. For both ever WTC-OAD cases and never WTC-OAD subjects, BMI, blood pressure, and HDL were found to be significantly higher at time of REAP-S compared to immediately post-9/11, Table 1. Similarly, their FEV1%Pred, HDL, LDL, total cholesterol, and triglycerides were significantly lower at time of REAP-S, and FVC%Pred was not significantly different. WTC-OAD cases had significantly higher BMI, blood pressure, and triglycerides, and lower FEV1%Pred, FVC%Pred at 1st post 9/11 and at the time of REAP-S assessment compared to those who never developed WTC-OAD. Subjects with WTC-OAD had an elevated total cholesterol compared to those that never developed WTC-OAD at their 1st post-9/11 assessment. In contrast, at the time of the REAP-S questionnaire, those subjects with WTC-OAD had lower total cholesterol, Table 1.
REAP-S Questionnaire Responses. Length of time between initial post 9/11 assessment and REAP-S administration was (mean ± SD) 16.59 ± 0.49 years. The study cohort had a mean±SD REAP-S score of 29.46 ± 4.22. Subjects with WTC-OAD had significantly lower mean REAP-S score of 28.99 ± 4.37 compared to those who never developed WTC-OAD with 29.60 ± 4.17; p<0.01. In contrast, 50% of our study cohort often eat more than the recommended amount of meat per day (Q7), 79.30% rarely drink sugary drinks (Q13), 48.80% rarely eat processed meats (Q8), 48.50% rarely eat fried foods (Q9), and 46.40% rarely eat snacks (Q10), Table 2. WTC-OAD cases had significantly higher reported consumption of processed meat (Q8) and sugary drinks (Q13), and decreased intake of grain products (Q3), vegetables (Q5), and fried foods (Q9). WTC-OAD also skipped breakfast more often (Q1), ate out more frequently (Q2), and did not feel well as often to shop or cook (Q15) (p<0.05), Table 2.
Quality of Diet assessed by REAP-S. Low-dietary quality was significantly associated with 2.67 odds (95%CI[1.57,4.52]; p<0.01) of developing WTC-OAD whereas moderate-dietary quality was associated with 1.22 odds (95%CI[1.05,1.42]; p=0.01), when comparing to high-dietary quality as a reference group, Figure 2. Increasing BMI had a small but significant protective odds ratio of 0.97(95%CI[0.95, 0.98]; p<0.01). Job description was significant, at 1.60 odds (95%CI[1.26,2.03]; p<0.01). Exposure intensity was a time-dependent risk factor, with 1.29 odds (95%CI[1.07, 1.56]; p=0.01). Age at 9/11 and smoking were not significant risk factors in this model. Overall, job description, exposure, and BMI were found to have significant odds of developing WTC-OAD, while age at 9/11 and smoking were not, Figure 2.
Dietary Quality Subgroups and Lung Function of those with low-, moderate-, or high-dietary quality are shown in Table 3. Mean FEV1%Pred and FVC1%Pred at both time points are significantly higher in those with higher dietary quality compared to those with lower dietary quality (p<0.05). FEV1/FVC ratio was not significantly associated with dietary quality at either timepoint, Table 3.
Processed meat, sugary drinks, and vegetable intake Impacted the Odds of Developing WTC-OAD. Assessment of individual REAP-S questions highlighted that WTC-OAD was more likely in subjects with increased consumption of processed meats (Q8) and sugary drinks (Q13), and decreased intake of vegetables (Q5), Table 2 and Figure 3. Additionally, there was a dose response seen with increasing intake of processed meats (OR 1.64 (95%CI[1.23,2.19] ;p=0.001) and 1.27 (95%CI[1.08,1.48] ; p=0.003)) and less vegetables (OR 1.53(95%CI[1.24,1.90] ; p<0.001) and 1.31(95%CI[1.12, 1.55]; p=0.001)). Less whole grain consumption is also associated with higher risk of WTC-OAD (Q3), 1.26(95%CI[1.08, 1.46]; p=0.004). WTC-OAD subjects trended towards increased fried food intake but these measures were not significant after Bonferroni correction (p=0.006), Table 2 and Figure 3.
Dietary habit assessment showed that not being well enough to cook, skipping breakfast, and eating out increase odds of WTC-OAD. Not feeling well enough to cook (Q15) increased odds of developing WTC-OAD by 1.91(95%CI[1.33, 2.73]; p<0.001) whereas skipping breakfast (Q1) was 1.20(95%CI[1.04, 1.40]; p=0.015). Eating out (Q2) also had odds of 1.25(95%CI[1.08, 1.45]; p=0.003), Table 2.
AGE Rich Foods Confer a Higher Likelihood of Developing WTC-OAD. Using data adapted from Uribarri et al., we summarized the amount of AGE in food groups represented in REAP-S, Supplemental Figure 1.(83) Fried foods (3971.86 kU/serving), processed meats (3925.89 kU/serving), and meats (3687.58 kU/serving) were identified as having the highest AGEs per serving. Sugary foods and drinks (7.2 kU/serving) do not naturally have high level of AGEs but instead cause high levels of endogenous AGEs. Frequency of eating foods highest in AGEs, meat (Q7), processed meats (Q8), and fried foods (Q9), was assessed by logistic regression model adjusted for age, smoking, BMI, exposure, and job description. An AGE-rich exposure response gradient was identified with the odds of developing WTC-OAD: not significantly increased in participants answering usual/often consumption of one AGE-rich food group, significantly increased in participants answering usual/often consumption to any two AGE-rich food groups, 1.50(95%CI[1.14, 1.97]; p=0.04), and highly significant in those answering usual/often consumption to all three AGE-rich food groups, 2.31(95%CI[1.35, 3.95]; p=0.002), Figure 4.