Abstract
Background:
Exposure to higher levels of outdoor air pollution is associated with increased morbidity in individuals with cystic fibrosis. Limited information exist regarding the potential adverse effects of indoor air pollution on those with cystic fibrosis.
Methods:
Individuals with cystic fibrosis who were enrolled in the Twin and Sibling Study from 2000–2013, self-reported exposure to four known sources of indoor air pollution (secondhand smoke, forced hot air, wood stove and fireplace). Change in lung function, rates of hospitalizations and pulmonary exacerbations were followed over 4 years to compare outcomes in those who were exposed to those who were not exposed.
Results:
Of 1432 participants with data on secondhand smoke exposure, 362 (25.3%) were exposed. Of 765 individuals with data on forced hot air exposure, 491 (64.2%) were exposed. Of 1247 participants with data on wood stove exposure and 830 with data on fireplace exposure, 182 (14.6%) and 373 (44.9%) were exposed, respectively. In longitudinal analysis, pediatric individuals either exposed to secondhand smoke or to forced hot air had a 0.60% predicted/year decrease in FEV1% predicted (P=0.002) or a 0.46% predicted/year decrease in FEV1% predicted (P=0.048), respectively compared to individuals who were not exposed. Adults exposed to secondhand smoke had a 42% increased yearly risk of hospitalization compared to those who were not exposed (P=0.045).
Conclusions:
Our questionnaire-based data suggest that exposure to sources of indoor air pollution increase morbidity in both the pediatric and adult cystic fibrosis populations. Future studies with quantitative indoor air quality assessments are needed.
Keywords: indoor air quality, secondhand smoke, obstructive lung disease
1. Introduction
Cystic fibrosis (CF) is the most common lethal autosomal recessive genetic disorder in Caucasians, affecting approximately 30,000 individuals in the United States and 70,000 individuals worldwide1. Although advances in therapies have improved life expectancy to a median predicted survival of 47.4 years in the US, CF remains a progressive pulmonary and extrapulmonary disorder which leads to loss of lung function, frequent pulmonary exacerbations (PEx), and oftentimes lung transplantation and premature death1,2.
The strongest predictor of mortality in CF is forced expiratory volume in one second (FEV1), with more frequent PEx leading to further FEV1 decline3,4. As both genetic and non-genetic factors contribute to more frequent PEx and loss of lung function, identification of modifiable non-genetic factors may provide an opportunity for intervention5–8.
Studies have shown that higher levels of outdoor particulate matter (PM) is associated with significantly greater rates of annual PEx and a more rapid decline in lung function9,10. Furthermore, higher levels of outdoor PM are also associated with shorter time to initial methicillin-resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa acquisition in the pediatric CF population11,12,. Both of these infections have been shown to decrease lung function and survival in CF6,7.
In recent years, indoor air pollution has become a worldwide public health concern. It may even be more harmful than outdoor air pollution, given Americans spend the majority of their time indoors13. However, unlike outdoor air pollution, indoor air pollution is a potentially modifiable exposure. According to the Environmental Protection Agency (EPA), indoor air pollution sources include those that release gases or particles into the air. These can include tobacco products, cooking, forced hot air (central heating system that draws in air from inside the home, sends it over a heat source, and redistributes the air throughout the house via a powerful blower through ducts), cooling systems, and combustion sources such as wood stoves and fireplaces 14.
Exposure to higher levels of indoor air pollution contributes to increased respiratory symptoms, increased rescue medication use, decreased quality of life and increased risk of PEx in patients with other chronic obstructive lung diseases such as asthma and COPD15,16. Limited data exist on how indoor air pollution affects those with CF. Collaco and colleagues showed that individuals with CF who reported ever being exposed to secondhand smoke (SHS), have significantly lower baseline lung function compared to those with CF with no exposure17. To our knowledge there have been no other studies evaluating the effects of indoor air pollution, beyond SHS, on those with CF.
The aim of this study was to further evaluate how exposure to known sources of indoor air pollution affect those with CF. We hypothesized that exposure to SHS, forced hot air, wood stoves, or fireplace would be associated with greater decline in lung function and more frequent hospitalizations and PEx compared to those individuals with CF who are not exposed to these sources of indoor air pollutants.
2. Methods
2.1. Study Design
The study population included individuals prospectively enrolled in the US Cystic Fibrosis Twin and Sibling Study (Twin-Sib study), with linked data obtained from the Cystic Fibrosis Foundation Patient Registry (CFFPR). Briefly, the Twin-Sib study was an observational national cohort of individuals with a confirmed diagnosis of CF with an affected twin and/or sibling. Detailed clinical information, including indoor air pollution exposure data, and DNA samples were collected from affected siblings and their parents with the primary aim to study genetic and environmental modifiers of disease over time8. The encounter-based CFFPR collects detailed demographic and clinical data for individuals treated at CF Foundation-accredited care centers in the US and who consent to have their data entered into the Registry18. All demographic and most indoor air pollution exposure data for this study was obtained from the Twin-Sib study. Clinical and smoking data was obtained from the Twin-Sib study where available, and when needed, was supplemented with the CFFPR.
Approval and annual review of this study was obtained through the Johns Hopkins University institutional review board (NA_00035659) with review by local institutional review boards if required by participating institutions. Written informed consent or assent was obtained from all participants and/or guardians.
2.2. Study Participants
Participants in the Twin-Sib study were recruited between October 27, 2000- March 31, 2013 on the basis of having a twin and/or sibling also affected by CF. Four years of data, including the baseline year, were collected. All participants had to have at least one pulmonary function test result obtained after the age of 6 years and prior to any lung transplantation. A smoking history was obtained from the study participant as part of the Twin-Sib study. Participants were excluded if they had a personal history of >1 month active smoking of tobacco or marijuana. Except for two sets of twins, all participants attended CF care centers in the United States.
The primary exposures of interest were sources of indoor air pollution. At the time of enrollment into the Twin Sib Study, participants were asked about exposure to four known sources of indoor air pollution: SHS at home, forced hot air, fireplace, and wood stove. Exposure was defined as either (i) ever or (ii) never having been exposed, without reference to duration, location, or severity.
The primary outcome of interest was annual rate of FEV1% predicted change. Spirometry was performed, using American Thoracic Society (ATS) and European Respiratory Society (ERS) criteria, at enrollment (or once reached age 6) and at each follow up interval, approximately every 3 months for routine clinical care19. Baseline FEV1% predicted was defined as the highest FEV1% predicted in the year of eligibility. The FEV1 measurements in liters were converted to percentiles for FEV1 using the Global Lung Initiative (GLI) equations, which account for patients’ age, height, ethnic group, and sex and were adopted by the CFFPR for their annual report in 201320,21. Secondary outcomes included annual number of all-cause hospitalizations and annual PEx, defined as those requiring treatment with IV antibiotics.
2.3. Statistical Analysis
Descriptive statistics were produced to summarize the distributions of demographic and clinical characteristics of the study population for each indoor air pollution source (SHS, forced hot air, fireplace, and wood stove). To evaluate the association between each exposure and rate of change in FEV1% predicted, we used multivariable mixed effects linear regression models, with random effects to account for subjects nested within families and repeated measurements during follow-up, which included the three years post baseline, as well as a subject-specific random slope. These models included an interaction term for FEV1% predicted and year (annual rate of change) and were adjusted for the following a priori identified potential confounders: age, sex, race, baseline FEV1% predicted, pancreatic insufficiency, insurance status (any private, public, no insurance) as a proxy for socioeconomic status, and Pseudomonas aeruginosa infection status. Models evaluating exposure to forced air, fireplace, and wood stove were further adjusted for SHS exposure. Analyses were conducted separately within the pediatric (ages 6–18) and adult (>18 years of age) populations since the annual rate of decline in lung function is known to be higher in adolescence compared to adulthood 22,23. Children may have been enrolled prior to the age of six, but they were only included in analyses upon first pulmonary function test after turning six years. The participants were classified as either pediatric or adult according to their age at enrollment. Results of these models are presented as rate of change in FEV1% predicted with corresponding 95% confidence intervals (95% CI). To evaluate the association for each exposure with annual incidence of hospitalizations and PEx, we used multivariable mixed effects Poisson regression with random effects to account for subjects nested within families and repeated measurements during follow-up and adjusted for the previously described covariates. Results of these models are presented as incidence rate ratios (IRR) and 95% CI. Those subjects with missing data for a particular indoor air pollution exposure were compared to those subjects without missing data for that exposure to explore differences between baseline characteristics. A p-value <0.05 was considered statistically significant. All analyses were conducted using STATA 15.1 (StataCorp, College Station, TX).
3. Results
3.1. Participant Characteristics
The study included 1759 individuals with at least one available pulmonary function test during follow up. Baseline demographic and clinical characteristics at baseline are reported in Table 1. The majority of participants were male (52.9%) and white (92.6%). The mean age at first pulmonary test was 15.2 (SD=9.45) years and the mean FEV1% predicted at this time was 82.4 (SD=23.95).
Table 1:
Baseline characteristics according to exposure to sources of indoor air pollution
| SHS | No SHS | Forced Air | No Forced Air | Wood stove | No wood stove | Fire place | No fire place | |
|---|---|---|---|---|---|---|---|---|
| (n=362) | (n= 1070) | (n=491) | (n= 274) | (n= 182) | (n= 1065) | (n= 373) | (n= 457) | |
| Age, years, mean (SD) | 15.9 (10.58) | 13.8 (8.02) | 15.3 (10.61) | 14.3 (8.70) | 15.9 (9.91) | 13.8 (8.57) | 16.1 (10.32) | 13.6 (9.19) |
| Age group, n (%) | ||||||||
| Pediatric | 268 (74.0) | 843 (78.8) | 371 (75.6) | 213 (77.7) | 133 (73.1) | 858 (80.6) | 267 (71.6) | 372 (81.4) |
| Adult | 94 (26.0) | 227 (21.2) | 120 (24.4) | 61 (22.3) | 49 (26.9) | 207 (19.4) | 106 (28.4) | 85 (18.6) |
| Twin/sib, n (%) | ||||||||
| Dizygotic | 4 (1.1) | 28 (2.6) | 2 (0.4) | 2 (0.7) | 0 (0.0) | 26 (2.4) | 0 (0.0) | 4 (0.9) |
| Monozygotic | 28 (7.7) | 74 (6.9) | 13 (2.7) | 6 (2.2) | 17 (9.3) | 71 (6.7) | 3 (0.8) | 19 (4.2) |
| Sibling | 330 (91.2) | 968 (90.5) | 476 (97.0) | 266 (97.1) | 165 (90.7) | 968 (90.9) | 370 (99.2) | 434 (95.0) |
| Race, n (%) | ||||||||
| White | 331 (91.4) | 998 (93.3) | 455 (92.7) | 256 (93.4) | 177 (97.3) | 993 (93.2) | 353 (94.6) | 421 (92.1) |
| African-American | 11 (3.0) | 24 (2.2) | 8 (1.6) | 11 (4.0) | 0 (0.0) | 28 (2.6) | 5 (1.3) | 15 (3.3) |
| Other | 20 (5.5) | 48 (4.5) | 28 (5.7) | 7 (2.6) | 5 (2.8) | 44 (4.1) | 15 (4.0) | 21 (4.6) |
| Sex, n (%) | ||||||||
| Female | 162 (44.8) | 521 (48.7) | 231 (47.1) | 142 (51.8) | 88 (48.4) | 518 (48.6) | 180 (48.3) | 224 (49.0) |
| Male | 200 (55.3) | 549 (51.3) | 260 (53.0) | 132 (48.2) | 94 (51.7) | 547 (51.4) | 193 (51.7) | 233 (51.0) |
| del F508 mutation, n (%) | ||||||||
| Homozygous | 169 (46.7) | 526 (49.2) | 228 (46.4) | 130 (47.5) | 85 (46.7) | 512 (48.1) | 156 (41.8) | 230 (50.3) |
| Heterozygous | 158 (43.7) | 445 (41.6) | 214 (43.6) | 115 (42.0) | 87 (47.8) | 447 (42.0) | 181 (48.5) | 182 (39.8) |
| Other | 35 (9.7) | 99 (9.3) | 49 (10.0) | 29 (10.6) | 10 (5.5) | 106 (10.0) | 36 (9.7) | 45 (9.9) |
| Insurance status, n (%) | ||||||||
| Any private | 187 (51.7) | 812 (75.9) | 344 (70.1) | 192 (70.1) | 122 (67.0) | 755 (70.9) | 298 (79.9) | 282 (61.7) |
| Federal/state | 171 (47.2) | 251 (23.5) | 143 (29.1) | 80 (29.2) | 54 (29.7) | 306 (28.7) | 75 (20.1) | 169 (37.0) |
| No insurance | 4 (1.1) | 7 (0.7) | 4 (0.8) | 2 (0.7) | 6 (3.3) | 4 (0.4) | 0 (0.0) | 6 (1.3) |
| FEV1 % predicted, mean (SD) | 79.1 (24.44) | 85.4 (22.32) | 84.1 (22.47) | 84.0 (23.65) | 83.2 (24.27) | 84.4 (22.80) | 85.2 (22.13) | 83.4 (23.19) |
| Pancreatic insufficiency, n (%) | 315 (87.0) | 927 (86.6) | 408 (83.1) | 248 (90.5) | 154 (84.6) | 929 (87.2) | 304 (81.5) | 400 (87.5) |
| Colonization status | ||||||||
| P. aeruginosa, n (%) | 197 (54.4) | 537 (50.2) | 253 (51.5) | 134 (48.9) | 93 (51.1) | 546 (51.3) | 187 (50.1) | 226 (49.5) |
| MRSA, n (%) | 88 (36.1) | 225 (29.2) | 111 (30.7) | 87 (42.9) | 26 (20.0) | 236 (31.1) | 79 (29.7) | 126 (37.0) |
| Hospitalization, n (%) | 141 (39.0) | 338 (31.6) | 172 (35.0) | 100 (36.5) | 44 (24.2) | 373 (35.0) | 115 (30.8) | 170 (37.2) |
| Pulmonary exacerbation, n (%) | 126 (37.5) | 323 (32.4) | 170 (34.8) | 97 (35.5) | 43 (27.0) | 342 (34.6) | 119 (32.2) | 161 (36.0) |
SHS=Secondhand smoke, FEV1 = Forced expiratory volume over 1 second, P. aeruginosa = Pseudomonas aeruginosa, MRSA= methicillin resistant staphylococcus aureus
A total of 1432 individuals provided exposure data (answered questions about ever being exposed) to SHS, while 765, 1247 and 830 individuals provided exposure data for forced hot air, wood stoves and fireplaces, respectively. Exposure to second hand smoke was reported by 362 (25.3%) individuals; and 491 (64.2%) reported forced hot air exposure, 182 (14.6%) to wood stoves, and 373 (44.9%) to fireplaces. Individuals with missing exposure data tended to be older and had lower baseline FEV1% predicted compared to those without missing data; however, hospitalizations and PEx were similar (Appendix A).
3.2. SHS Exposure
Individuals who reported exposure to SHS were more likely to have public insurance, have a significantly lower baseline mean FEV1% predicted compared to those who denied exposure 79.1% vs 85.4% (p <0.001) and had a significantly higher likelihood of being hospitalized in the year of enrollment compared to those who denied exposure 39.0% vs 31.6%, (p=0.01). The proportions of individuals with a PEx in the first year of follow-up was similar between those exposed to SHS and those unexposed 37.5% vs 32.4%, (p=0.087) (Table 1).
Figure 1 presents the annual FEV1% predicted for children and adults, by exposure to SHS. In longitudinal analysis, pediatric individuals exposed to SHS had a significantly greater rate of decline in FEV1% predicted (−0.60% FEV1% predicted/year; 95% CI: −0.97, −0.22) compared to pediatric individuals who were not exposed after adjustment for potential confounders. Adult individuals exposed to SHS did not have a significant change in their FEV1% predicted compared to adults who were not exposed (Table 2).
Figure 1:
Effects of SHS Exposure on FEV1% Predicted for Children and Adults Over Time
Lung function decline for pediatric and adult subjects according to secondhand smoke exposure status.
Table 2:
Multivariable1 mixed effects linear regression evaluating the annual rate of FEV1 % predicted change for selected known sources of indoor air pollution
| Pediatric | Adult | |
|---|---|---|
| Slope (% predicted/year) | Slope (% predicted/year) | |
| (95% CI) | (95% CI) | |
| Secondhand smoke | −0.60 (−0.97, −0.22) | 0.46 (−0.36, 1.29) |
| Forced air | −0.46 (−0.92, 0.00) | 0.35 (−0.30, 0.99) |
| Wood stove | 0.23 (−0.29, 0.76) | 0.60 (−0.06, 1.27) |
| Fire place | 0.02 (−0.41, 0.45) | −0.15 (−0.77, 0.46) |
Adjusted for age, sex, race, baseline FEV1% predicted, pancreatic insufficiency status, insurance type (any private, public, no insurance) and Pseudomonas aeruginosa colonization status, with random effects terms to account for multiple observations within subject and subjects nested within families, as well as, a subject-specific random slope. Forced hot air, wood stove, fireplace models were further adjusted for second hand smoke exposure.
Rates of hospitalizations among pediatric subjects did not differ based on SHS exposure (IRR 1.14, 95% CI: 0.89, 1.46). However, adults exposed to SHS had a 42% higher yearly rate of hospitalizations compared to those who denied SHS exposure (IRR 1.42, 95% CI: 1.01, 2.00) (Table 3).
Table 3:
Multivariable1 mixed effects Poisson regression evaluating the annual rate of hospitalizations and pulmonary exacerbations for selected sources of indoor air pollution
| Hospitalizations | Pulmonary exacerbations | |||
|---|---|---|---|---|
| Pediatric | Adult | Pediatric | Adult | |
| IRR (95% CI) | IRR (95% CI) | IRR (95% CI) | IRR (95% CI) | |
| Secondhand smoke | 1.14 (0.89, 1.46) | 1.42 (1.01, 2.00) | 1.07 (0.84, 1.38) | 1.12 (0.83, 1.51) |
| Forced air | 0.90 (0.68, 1.19) | 0.94 (0.64, 1.37) | 1.02 (0.77, 1.35) | 0.95 (0.70, 1.28) |
| Wood stove | 0.77 (0.54, 1.11) | 0.92 (0.64, 1.34) | 0.69 (0.48, 1.01) | 0.99 (0.68, 1.43) |
| Fireplace | 0.88 (0.67, 1.15) | 1.29 (0.89, 1.87) | 0.90 (0.68, 1.19) | 1.17 (0.82, 1.67) |
IRR: incidence rate ratio
Adjusted for age, sex, race, pancreatic insufficiency status, insurance type (any private, public, no insurance), FEV1% predicted and Pseudomonas aeruginosa colonization status with random effects terms to account for multiple observations within subject and subjects nested within families. Forced hot air, wood stove, fireplace were further adjusted for second hand smoke exposure.
There was no difference in rates of PEx among either pediatric subjects (IRR 1.07 95% CI 0.84, 1.38) or adults (IRR 1.12, 95% CI 0.83, 1.51) exposed to SHS compared to those not exposed (Table 3).
3.3. Forced Hot Air Exposure
Baseline FEV1% predicted and baseline rates of hospitalizations and PEx were similar between those exposed to forced hot air compared to those who were unexposed (Table 1).
Annual FEV1% predicted for children and adults by exposure to forced hot air are presented in Figure 2. Pediatric subjects exposed to forced hot air had a significantly greater rate of decline in FEV1% predicted (−0.46 95% CI: −0.92, 0.00) compared to pediatric subjects who denied exposure, after adjusting for potential confounders. Adult individuals exposed to forced hot air did not have a significant change in their FEV1% predicted compared to adults who were not exposed (Table 2).
Figure 2:
Effects of Forced Hot Air Exposure on FEV1% Predicted for Children and Adults Over Time
Lung function decline for pediatric and adult subjects according to forced hot air exposure status.
There was no significant difference between rates of hospitalizations among pediatric (IRR 0.90 95% CI 0.68, 1.91) or adult (IRR 0.94 95% CI 0.64, 1.37) participants who were exposed to forced hot air compared to those not exposed. There was also no differences in PEx rates for pediatric (IRR 1.02 95% CI 0.77, 1.35) or adult (IRR 0.95 95% CI 0.70, 1.28) subjects based on their exposure to forced hot air (Table 3).
3.4. Wood Stove or Fireplace Exposure
Baseline rates of hospitalizations were significantly higher in those individuals who were not exposed to wood stove compared to those who were exposed 35.0% vs 24.2%, p= 0.004. However, baseline rates of hospitalizations did not differ between those who reported exposure to a fireplace and those who were not exposed. Baseline FEV1% predicted and rates of PEx were not significantly different between those exposed and those not exposed to a woodstove or a fireplace (Table 1).
After adjusting for potential confounders, exposure to a wood stove or fireplace did not significantly affect rate of lung function change (Table 2), rates of hospitalizations, or PEx in either the pediatric or adult subjects compared to those who did not report exposure (Table 3).
4. Discussion
In this cohort study of people with CF, pediatric subjects who were exposed to SHS or forced hot air inside their home had a significantly greater rate of decline in lung function compared to those who were not exposed. Furthermore, adults exposed to SHS had a significantly higher yearly rate of hospitalizations compared to those who were not exposed.
Our results are consistent with findings from the study by Collaco and colleagues who showed that any exposure to SHS was associated with a lower baseline FEV1% predicted. They then used the data to project FEV1% predicted at 20 years and estimated that those with SHS exposure would have a 6% lower FEV1% predicted compared to those not exposed17. Our study differs in that we analyzed 4 years of collected data (baseline lung function with 3 years of follow up) to determine the actual rate of decline in FEV1% predicted over that time. We found that children who are exposed to SHS have a 0.60%/year decline in FEV1% predicted compared to children who were not exposed, after controlling for potential confounders. This approach may be a more accurate measure of lung function decline since it has been shown that current FEV1 % predicted rate of decline cannot predict future rate of FEV1 % predicted decline, but that it does correlate moderately well with FEV1 % predicted up to 5 years24.
Younger age is associated with a greater rate of decline of FEV1% predicted25. Our data suggests that if exposed to SHS during childhood, an even greater rate of decline will occur and will therefore be lower upon reaching adulthood. This is concerning since we know that FEV1% predicted is the strongest predictor of mortality3.
Exposure to SHS was also associated with a 42% higher rate of yearly hospitalizations in adults compared to those who denied exposure. We infer this reflects worse respiratory symptoms since Stephenson and colleagues found that approximately 75% of inpatient hospitalizations of those with CF are respiratory related26. Surprisingly, the higher rate for hospitalizations was not also observed for PEx. Nevertheless, this finding supports previous research that exposure to SHS increases CF morbidity27.
To our knowledge, the association of forced hot air exposure as a risk factor for lung function decline in the pediatric CF population has not been previously reported. We found that any exposure to forced hot air in the pediatric cohort was associated with a 0.46%/year decline in FEV1% predicted compared to those without exposure. This is not surprising given the fact that most residential forced hot air systems do not mechanically bring fresh air into the home, but rather recirculate indoor air 28. Thus, much of the air quality in homes with forced hot air relies on how often the air filters are changed, the quality of the filters, and the cleanliness of the duct system within the home. Unfortunately, data was not obtained on frequency of filter changes or opening of windows in this study.
We hypothesized adults exposed to SHS and forced hot air to also have a significantly greater rate of decline of FEV1% predicted compared to those who were not exposed; however, this was not observed. Our findings support the importance of preserving lung function in childhood and adolescence since we know there is a greater lung function decline during younger age. Younger individuals with CF with greater lung function compared to their adult counterparts may be more susceptible to lung function decline from indoor air pollution exposures29. We hypothesize that there may be an additive effect of harmful environmental exposures that leads to even greater rates of lung function decline in childhood and adolescence.
Some limitations merit consideration. First, we used a self-reported, dichotomous (ever or never) report at time of enrollment to define individual-level exposure to the four known sources of indoor air pollution. This may introduce misclassification and consequently, potential dose-responses could not be explored. For example, although combustion activities are a significant source of indoor PM, we found that exposure to wood stove or fireplace were not associated with lung function change and rates of hospitalizations or PEx. However, without knowing the frequency or duration of exposure, it is difficult to interpret these findings. Further, missing exposure data was not uncommon and ranged from 11% for wood stove exposure to 52% for forced air exposure. It is unclear whether those individuals who did not provide a response to an exposure were unsure of their exposure or whether they were unwilling to provide a response. Those subjects with missing exposure data tended to be older and had lower baseline FEV1% predicted compared to those with exposure data, thus introducing potential concerns for internal validity. Second, not all potential sources of indoor air pollution were asked about. For example, cooking inside the home can be a significant source of indoor air pollution by creating combustion-related particles; however, data were not available on cooking practices with this study30. Additionally, data were not collected on ventilation practices in the home such as the use of use stove fans, frequency of opening windows, or the use of air filters.
In conclusion, this study suggests that exposure to SHS and forced hot air, known sources of indoor air pollution, are associated with a greater morbidity in both pediatric and adult individuals with CF. This adds to the growing body of evidence that indoor air pollution increases morbidity in individuals with chronic lung diseases. Further studies with high resolution, objective residential indoor air pollutant measurements of individuals with CF are needed. The home is a readily modifiable environment, and if higher levels of indoor air pollution are found to negatively affect lung function and respiratory symptoms in those with CF, interventions can be implemented to help lower these levels and thus preserve lung function and survival31,32.
Highlights:
Exposure to higher levels of outdoor air pollution is associated with worse lung function and greater rates of pulmonary exacerbations in CF, but limited data on exposure to indoor air pollution exist.
Pediatric individuals exposed to secondhand smoke had a 0.60% predicted/year decrease in FEV1% predicted compared to pediatric individuals who were not exposed.
Pediatric individuals exposed to forced hot air had a 0.46% predicted/year decrease in FEV1% predicted compared to pediatric individuals who were not exposed.
Adults exposed to secondhand smoke had 42% increased yearly risk of hospitalization compared to those adults who were not exposed.
Future studies with qualitative indoor air pollution measurements are needed to further quantify exposure risks for the CF population.
Acknowledgements
The authors would like to thank Garry R. Cutting, M.D., Professor of Genetic Medicine at Johns Hopkins School of Medicine and the primary investigator on the US Twin and Sibling Study, for permission to use the data collected for the US Twin and Sibling Study for this manuscript.
Funding Statement:
This work was supported by the National Heart, Lung, And Blood Institute of the NIH award numbers F32HL149262 (SWC) and R01-HL128475 (JMC) and by the Cystic Fibrosis Foundation award numbers CARSON19B0 and CUTTIN18XX1 (GR Cutting)
APPENDIX
A:
Baseline characteristics of those with missing data per exposure vs those without missing data
| Demographics | No SHS data (n= 225) |
SHS data (n= 1534) |
No Forced Air data (n= 922) |
Forced Air data (n= 837) |
No wood stove data (n= 196) |
Wood stove data (n= 1563) |
No Fire Place data (n= 388) |
Fire Place data (n= 1371) |
|---|---|---|---|---|---|---|---|---|
| Age, years, mean (SD) | 19.5 (10.66) | 14.6 (9.09) | 15.2 (8.71) | 15.2 (10.21) | 16.2 (9.99) | 15.1 (9.37) | 16.6 (10.7) | 14.8 (9.03) |
| Age group, n (%) | ||||||||
| Pediatric | 109 (48.4) | 1173 (76.5) | 653 (70.8) | 629 (75.1) | 140 (71.4) | 1142 (73.1) | 269 (69.3) | 1013 (73.9) |
| Adult | 116 (51.6) | 361 (23.5) | 269 (29.2) | 208 (24.9) | 56 (28.6) | 421 (26.9) | 119 (30.7) | 358 (26.1) |
| Twin/sib, n (%) | ||||||||
| DZ | 5 (2.2) | 33 (2.2) | 34 (3.7) | 4 (0.5) | 0 (0.0) | 38 (2.4) | 0 (0.0) | 38 (2.8) |
| MZ | 41 (18.2) | 108 (7.0) | 128 (13.9) | 21 (2.5) | 17 (8.7) | 132 (8.5) | 3 (0.8) | 146 (10.7) |
| Sib | 179 (79.6) | 1393 (90.8) | 760 (82.4) | 812 (97.0) | 179 (91.3) | 1393 (89.1) | 385 (99.2) | 1187 (86.6) |
| Race, n (%) | ||||||||
| White | 202 (89.8) | 1426 (93.0) | 847 (91.9) | 781 (93.3) | 191 (97.5) | 1437 (91.9) | 368 (94.9) | 1260 (91.9) |
| African-American | 4 (1.8) | 36 (2.4) | 21 (2.3) | 19 (2.3) | 0 (0.0) | 40 (2.6) | 5 (1.3) | 35 (2.6) |
| Other | 19 (8.4) | 72 (4.7) | 54 (5.9) | 37 (4.4) | 5 (2.6) | 86 (5.5) | 15 (3.9) | 76 (5.5) |
| Sex, n (%) | ||||||||
| Female | 105 (46.7) | 724 (47.2) | 426 (46.2) | 403 (48.2) | 96 (49.0) | 733 (46.9) | 185 (47.7) | 644 (47.0) |
| Male | 120 (53.3) | 810 (52.8) | 496 (53.8) | 434 (51.9) | 100 (51.0) | 830 (53.1) | 203 (52.3) | 727 (52.0) |
| del F508 mutation, n (%) | ||||||||
| Homozygous | 113 (50.2) | 736 (48.0) | 463 (50.2) | 386 (46.1) | 90 (45.9) | 759 (48.6) | 162 (41.8) | 687 (50.1) |
| Heterozygous | 86 (38.2) | 651 (42.4) | 374 (40.6) | 363 (43.4) | 92 (46.9) | 645 (41.3) | 186 (47.9) | 551 (40.2) |
| Other | 26 (11.6) | 147 (9.6) | 85 (9.2) | 88 (10.5) | 14 (7.1) | 159 (10.2) | 40 (10.3) | 133 (9.7) |
| Insurance status, n (%) | ||||||||
| Any private | 133 (64.3) | 1035 (69.7) | 611 (68.0) | 557 (70.2) | 129 (68.3) | 1039 (69.2) | 308 (80.2) | 860 (65.8) |
| Federal/state | 69 (33.3) | 435 (29.3) | 275 (30.6) | 229 (28.9) | 54 (28.6) | 450 (30.0) | 75 (19.5) | 429 (32.8) |
| No insurance | 5 (2.4) | 14 (0.9) | 12 (1.3) | 7 (0.9) | 6 (3.2) | 13 (0.9) | 1 (0.3) | 18 (1.4) |
| CF disease characteristics | ||||||||
| FEV1 % predicted, mean (SD) | 73.4 (26.85) | 83.7 (23.22) | 80.6 (24.68) | 84.3 (22.98) | 83.4 (24.13) | 82.2 (23.96) | 84.9 (22.08) | 81.7 (24.42) |
| Pancreatic insufficiency, n (%) | 186 (82.7) | 1329 (86.6) | 803 (87.1) | 712 (85.1) | 164 (83.7) | 1351 (86.4) | 313 (80.7) | 1202 (87.7) |
| Colonization status | ||||||||
| Pseudomonas aeruginosa, n (%) | 111 (57.8) | 734 (51.2) | 457 (53.3) | 388 (50.5) | 93 (50.5) | 752 (52.2) | 188 (50.0) | 657 (52.6) |
| MRSA, n (%) | 36 (31.0) | 313 (30.8) | 151 (26.8) | 198 (34.9) | 26 (19.9) | 323 (32.3) | 79 (29.6) | 270 (31.3) |
| Hospitalization, n (%) | 69 (34.0) | 497 (33.5) | 286 (32.0) | 280 (35.4) | 46 (24.2) | 520 (34.8) | 117 (30.4) | 449 (34.5) |
| Pulmonary exacerbation, n (%) | 68 (37.0) | 462 (33.6) | 256 (33.2) | 274 (34.7) | 44 (26.4) | 486 (34.9) | 120 (31.4) | 410 (34.8) |
B.
Additional analyses for FEV1% predicted change
| Current results. | + MRSA, BMI & CFRD | |
|---|---|---|
| Pediatric | ||
| SHS | −0.60 (−0.97, −0.22) | −0.49 (−0.87, −0.12) |
| Forced air | −0.46 (−0.92, 0.00) | −0.51 (−0.97, −0.05) |
| Wood stove | 0.23 (−0.29, 0.76) | 0.17 (−0.35, 0.69) |
| Fireplace | 0.02 (−0.41, 0.45) | 0.12 (−0.31, 0.54) |
| Adult | ||
| SHS | 0.46 (−0.36, 1.29) | 0.47 (−0.36, 1.30) |
| Forced air | 0.35 (−0.30, 0.99) | 0.37 (−0.28, 1.02) |
| Wood stove | 0.60 (−0.06, 1.27) | 0.65 (−0.02, 1.33) |
| Fireplace | −0.15 (−0.77, 0.46) | −0.04 (−0.67, 0.59) |
This table presents results if MRSA, BMI, and CFRD are added as covariates to the multivariable linear regression model evaluating the effects of each exposure on rate of decline of FEV1% predicted per year. There is no difference in the outcomes.
C.
Average Number of follow-up by exposure and age group
| FEV1pp | Hospitalizations | PEx | |
|---|---|---|---|
| Mean # of observations | |||
| Pediatric | |||
| SHS | 15.6 | 3.4 | 3.4 |
| Forced air | 16.1 | 3.5 | 3.5 |
| Wood stove | 15.6 | 3.4 | 3.4 |
| Fireplace | 16.0 | 3.4 | 3.4 |
| Adult | |||
| SHS | 15.1 | 3.3 | 3.3 |
| Forced air | 15.6 | 3.3 | 3.3 |
| Wood stove | 15.4 | 3.3 | 3.3 |
| Fireplace | 15.4 | 3.3 | 3.3 |
D.
Rates of Decline in FEV1% predicted in the Unexposed and Exposed Groups
| Unexposed Rate of decline (95% CI) |
P value | Exposed Rate of decline (95% CI) |
P value | |
|---|---|---|---|---|
| Pediatric | ||||
| SHS | −1.72 (−1.90, −1.53) | <0.001 | −2.31 (−2.64, −1.98) | <0.001 |
| Forced air | −1.44 (−1.81, −1.08) | <0.001 | −1.91 (−2.18, −1.63) | <0.001 |
| Wood stove | −1.88 (−2.06, −1.70) | <0.001 | −1.65 (−2.14, −1.16) | <0.001 |
| Fireplace | −1.65 (−1.94, −1.37) | <0.001 | −1.63 (−1.95, −1.31) | <0.001 |
| Adult | ||||
| SHS | −2.10 (−2.55, −1.64) | <0.001 | −1.64 (−2.32, −0.95) | <0.001 |
| Forced air | −2.32 (−2.84, −1.80) | <0.001 | −1.97 (−2.36, −1.58) | <0.001 |
| Wood stove | −1.98 (−2.27, −1.68) | <0.001 | −1.37 (−1.97, −0.77) | <0.001 |
| Fireplace | −1.92 (−2.37, −1.47) | <0.001 | −2.07 (−2.49, −1.66) | <0.001 |
E.
Number of individuals with exposure observations
| Individuals with data n (%) |
Individuals without data n (%) |
|
|---|---|---|
| SHS | 1534 (87.2) | 225 (12.8) |
| Forced air | 837 (47.6) | 922 (52.4) |
| Wood stove | 1341 (76.2) | 418 (23.8) |
| Fireplace | 905 (51.5) | 854 (48.6) |
| SHS & Forced air | 834 (47.4) | 925 (52.6) |
| SHS & Wood stove | 1338 (76.1) | 421 (23.9) |
| SHS & Fireplace | 902 (51.3) | 857 (48.7) |
| Forced air & Wood stove | 826 (47.0) | 933 (53.0) |
| Forced air & Fireplace | 833 (47.4) | 926 (52.6) |
| Wood stove & Fireplace | 892 (50.7) | 867 (49.3) |
| SHS & Forced air & Wood stove | 823 (46.8) | 936 (53.2) |
| SHS & Forced air & Fireplace | 830 (47.2) | 929 (52.8) |
| SHS & Wood stove & Fireplace | 825 (46.9) | 934 (53.1) |
| SHS & Forced air & Wood stove & Fireplace | 822 (46.7) | 937 (53.3) |
Footnotes
Presentation Information: Selected portions of this manuscript were presented at the American Thoracic Society (ATS) 2019 International Conference in Dallas, TX in May 2019, as well as the 33rd Annual North American Cystic Fibrosis Conference (NACFC) in Nashville, Tennessee in November 2019.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Conflict of Interest Statement:
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this manuscript.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Author Credit statement
Sara Carson: Conceptualization, writing- original draft, funding acquisition, methodology. Kevin Psoter: methodology, formal analysis. Kirsten Koehler: writing – review and editing, Karen Siklosi: data curation. Kristina Montemayor: writing-review and editing. Alexandra Toporek: writing-review and editing. Natalie West: conceptualization, writing-review and editing. Noah Lechtzin: conceptualization, writing-review and editing. Nadia Hansel: conceptualization, writing-review and editing. Joseph Callaco: conceptualization, resources, methodology, investigation, supervision. Christian Merlo: conceptualization, methodology, writing-review and editing, supervision.
References
- 1.Cystic Fibrosis Foundation Patient Registry. 2018 Annual Data Report Published online 2019.
- 2.de Boer K, Vandemheen KL, Tullis E, et al. Exacerbation frequency and clinical outcomes in adult patients with cystic fibrosis. Thorax 2011;66(8):680–685. [DOI] [PubMed] [Google Scholar]
- 3.Kerem E, Reisman J, Corey M, Canny GJ, Levison H. Prediction of mortality in patients with cystic fibrosis. N Engl J Med 1992;326(18):1187–1191. [DOI] [PubMed] [Google Scholar]
- 4.Sanders DB, Bittner RCL, Rosenfeld M, Redding GJ, Goss CH. Pulmonary exacerbations are associated with subsequent FEV1 decline in both adults and children with cystic fibrosis. Pediatr Pulmonol 2011;46(4):393–400. [DOI] [PubMed] [Google Scholar]
- 5.Corey M, Farewell V. Determinants of mortality from cystic fibrosis in Canada, 1970–1989. Am J Epidemiol 1996;143(10):1007–1017. [DOI] [PubMed] [Google Scholar]
- 6.Lechtzin N, John M, Irizarry R, Merlo C, Diette GB, Boyle MP. Outcomes of adults with cystic fibrosis infected with antibiotic-resistant Pseudomonas aeruginosa. Respir Int Rev Thorac Dis 2006;73(1):27–33. [DOI] [PubMed] [Google Scholar]
- 7.Dasenbrook EC, Merlo CA, Diener-West M, Lechtzin N, Boyle MP. Persistent methicillin-resistant Staphylococcus aureus and rate of FEV1 decline in cystic fibrosis. Am J Respir Crit Care Med 2008;178(8):814–821. [DOI] [PubMed] [Google Scholar]
- 8.Vanscoy LL, Blackman SM, Collaco JM, et al. Heritability of Lung Disease Severity in Cystic Fibrosis. Am J Respir Crit Care Med 2007;175(10):1036–1043. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Goss CH, Newsom SA, Schildcrout JS, Sheppard L, Kaufman JD. Effect of ambient air pollution on pulmonary exacerbations and lung function in cystic fibrosis. Am J Respir Crit Care Med 2004;169(7):816–821. [DOI] [PubMed] [Google Scholar]
- 10.Goeminne PC, Kiciński M, Vermeulen F, et al. Impact of air pollution on cystic fibrosis pulmonary exacerbations: a case-crossover analysis. Chest 2013;143(4):946–954. [DOI] [PubMed] [Google Scholar]
- 11.Psoter KJ, De Roos AJ, Wakefield J, Mayer JD, Rosenfeld M. Air pollution exposure is associated with MRSA acquisition in young U.S. children with cystic fibrosis. BMC Pulm Med 2017;17(1):106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Psoter KJ, De Roos AJ, Mayer JD, Kaufman JD, Wakefield J, Rosenfeld M. Fine particulate matter exposure and initial Pseudomonas aeruginosa acquisition in cystic fibrosis. Ann Am Thorac Soc 2015;12(3):385–391. [DOI] [PubMed] [Google Scholar]
- 13.Klepeis NE, Nelson WC, Ott WR, et al. The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants. J Expo Anal Environ Epidemiol 2001;11(3):231–252. [DOI] [PubMed] [Google Scholar]
- 14.US EPA O. Introduction to Indoor Air Quality US EPA. Published August 14, 2014. Accessed June 18, 2020. https://www.epa.gov/indoor-air-quality-iaq/introduction-indoor-air-quality
- 15.McCormack MC, Breysse PN, Matsui EC, et al. In-home particle concentrations and childhood asthma morbidity. Environ Health Perspect 2009;117(2):294–298. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Hansel NN, McCormack MC, Belli AJ, et al. In-home air pollution is linked to respiratory morbidity in former smokers with chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2013;187(10):1085–1090. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Collaco JM, Vanscoy L, Bremer L, et al. Interactions between secondhand smoke and genes that affect cystic fibrosis lung disease. JAMA 2008;299(4):417–424. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Knapp EA, Fink AK, Goss CH, et al. The Cystic Fibrosis Foundation Patient Registry. Design and Methods of a National Observational Disease Registry. Ann Am Thorac Soc 2016;13(7):1173–1179. [DOI] [PubMed] [Google Scholar]
- 19.Miller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry. Eur Respir J 2005;26(2):319–338. [DOI] [PubMed] [Google Scholar]
- 20.Quanjer PH, Stanojevic S, Cole TJ, et al. MULTI-ETHNIC REFERENCE VALUES FOR SPIROMETRY FOR THE 3–95 YEAR AGE RANGE: THE GLOBAL LUNG FUNCTION 2012 EQUATIONS. Eur Respir J 2012;40(6):1324–1343. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Cystic Fibrosis Foundation Patient Registry. 2013 Annual Data Report to the Center Directors Cystic Fibrosis Foundation; 2014. [Google Scholar]
- 22.Konstan MW, Wagener JS, Vandevanter DR, et al. Risk factors for rate of decline in FEV1 in adults with cystic fibrosis. J Cyst Fibros Off J Eur Cyst Fibros Soc 2012;11(5):405–411. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Konstan MW, Morgan WJ, Butler SM, et al. Risk factors for rate of decline in forced expiratory volume in one second in children and adolescents with cystic fibrosis. J Pediatr 2007;151(2):134–139, 139.e1. [DOI] [PubMed] [Google Scholar]
- 24.Rosenfeld M, VanDevanter DR, Ren CL, et al. Decline in lung function does not predict future decline in lung function in cystic fibrosis patients. Pediatr Pulmonol 2015;50(9):856–862. [DOI] [PubMed] [Google Scholar]
- 25.Earnest A, Salimi F, Wainwright CE, et al. Lung function over the life course of paediatric and adult patients with cystic fibrosis from a large multi-centre registry. Sci Rep 2020;10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Stephenson A, Hux J, Tullis E, Austin PC, Corey M, Ray J. Higher risk of hospitalization among females with cystic fibrosis. J Cyst Fibros Off J Eur Cyst Fibros Soc 2011;10(2):93–99. [DOI] [PubMed] [Google Scholar]
- 27.Kopp BT, Ortega-García JA, Sadreameli SC, et al. The Impact of Secondhand Smoke Exposure on Children with Cystic Fibrosis: A Review. Int J Environ Res Public Health 2016;13(10). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.US EPA O. Improving Indoor Air Quality US EPA. Published September 3, 2014. Accessed April 26, 2020. https://www.epa.gov/indoor-air-quality-iaq/improving-indoor-air-quality
- 29.Davis PB, Byard PJ, Konstan MW. Identifying Treatments That Halt Progression of Pulmonary Disease in Cystic Fibrosis. Pediatr Res 1997;41(2):161–165. [DOI] [PubMed] [Google Scholar]
- 30.Wallace LA, Mitchell H, O’Connor GT, et al. Particle concentrations in inner-city homes of children with asthma: the effect of smoking, cooking, and outdoor pollution. Environ Health Perspect 2003;111(9):1265–1272. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Paulin LM, Diette GB, Scott M, et al. Home interventions are effective at decreasing indoor nitrogen dioxide concentrations. Indoor Air 2014;24(4):416–424. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Batterman S, Du L, Mentz G, et al. Particulate matter concentrations in residences: an intervention study evaluating stand-alone filters and air conditioners. Indoor Air 2012;22(3):235–252. [DOI] [PMC free article] [PubMed] [Google Scholar]