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Open Access 01.12.2015 | Research

Childhood pneumonia increases risk for chronic obstructive pulmonary disease: the COPDGene study

verfasst von: Lystra P. Hayden, Brian D. Hobbs, Robyn T. Cohen, Robert A. Wise, William Checkley, James D. Crapo, Craig P. Hersh, on behalf of the COPDGene Investigators

Erschienen in: Respiratory Research | Ausgabe 1/2015

Abstract

Background

Development of adult respiratory disease is influenced by events in childhood. The impact of childhood pneumonia on chronic obstructive pulmonary disease (COPD) is not well defined. We hypothesize that childhood pneumonia is a risk factor for reduced lung function and COPD in adult smokers.

Methods

COPD cases and control smokers between 45–80 years old from the United States COPDGene Study were included. Childhood pneumonia was defined by self-report of pneumonia at <16 years. Subjects with lung disease other than COPD or asthma were excluded. Smokers with and without childhood pneumonia were compared on measures of respiratory disease, lung function, and quantitative analysis of chest CT scans.

Results

Of 10,192 adult smokers, 854 (8.4 %) reported pneumonia in childhood. Childhood pneumonia was associated with COPD (OR 1.40; 95 % CI 1.17-1.66), chronic bronchitis, increased COPD exacerbations, and lower lung function: post-bronchodilator FEV₁ (69.1 vs. 77.1 % predicted), FVC (82.7 vs. 87.4 % predicted), FEV₁/FVC ratio (0.63 vs. 0.67; p < 0.001 for all comparisons). Childhood pneumonia was associated with increased airway wall thickness on CT, without significant difference in emphysema. Having both pneumonia and asthma in childhood further increased the risk of developing COPD (OR 1.85; 95 % CI 1.10-3.18).

Conclusions

Children with pneumonia are at increased risk for future smoking-related lung disease including COPD and decreased lung function. This association is supported by airway changes on chest CT scans. Childhood pneumonia may be an important factor in the early origins of COPD, and the combination of pneumonia and asthma in childhood may pose the greatest risk.

Clinical trials registration

ClinicalTrials.gov, NCT00608764 (Active since January 28, 2008).

Additional file 1: Table S1. Chest CT Parameters for Subjects With and Without History of Childhood Pneumonia. Table S2. Effect of Childhood Pneumonia with Childhood Asthmatics Removed. Table S3. Effect of Childhood Pneumonia in Childhood Asthmatics Only. Table S4. Recall Assessment in Subjects Who Did Not Report Known COPD or Emphysema Diagnosis. Figure S1. Classification of subjects in cohort based on childhood pneumonia status. Figure S2. Distribution of age of first pneumonia in entire cohort (a) in subjects with a history of childhood pneumonia (b) and in subjects without a history of childhood pneumonia (c). Includes all subjects who reported an age of first pneumonia. (PDF 943 kb)

Electronic supplementary material

The online version of this article (doi:10.1186/s12931-015-0273-8) contains supplementary material, which is available to authorized users.

Competing interests

Outside of the submitted work Craig P. Hersh has received lecture fees from Novartis and consulting fees from CSL Behring; Robert A. Wise has received grants and consulting fees from AstraZeneca, Boehringer Ingelheim and Forest Labs as well as personal fees from Sunovion, Roche-Genentech, GlaxoSmithKline, Novartis, Teva, Mylan, MEDA, Pulmonx, and Spiration. The remaining authors have no potential competing interests.

Authors’ contributions

LPH contributed to the conception and design of the work, analysis and interpretation of data, and drafting of the work. BDH, RTC and WC, contributed to the analysis and interpretation of data. JDC and RAW contributed to the acquisition of data. CPH contributed to the conception and design of the work, the acquisition of data, analysis and interpretation of data, and drafting of the work. All authors revised the work critically for important intellectual content, provided final approval of the published version, and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors read and approved the final manuscript.

beta coefficient

Confidence interval

COPD

Chronic obstructive pulmonary disease

Computed tomography

CVD

Cardiovascular disease

FEV₁

Forced expiratory volume in the first second

FVC

Forced vital capacity

GOLD

Global initiative for chronic obstructive lung disease

Hounsfield units

MMRC

Modified Medical Research Council

Odds ratio

post-BD

post bronchodilator

PRISm

Preserved ratio impaired spirometry

Standard error

SGRQ

St. George’s Respiratory Questionnaire

SRWA-Pi10

Square root of wall area of a hypothetic airway of 10 mm internal perimeter

Background

Pneumonia is a common pediatric diagnosis that poses a significant risk for future respiratory disease [1, 2]. Multiple investigations have found an association between pneumonia in childhood and decreased adult lung function, raising the question of whether childhood pneumonia is a risk factor for chronic obstructive pulmonary disease (COPD). Prior studies are limited by small sample sizes, short-term follow-up, absence of post-bronchodilator lung function, differing definitions of respiratory illness, sampling bias, and recall bias [3‐10]. This study examines the effect of childhood pneumonia in a large population of older adults, including objective diagnosis of COPD with standardized post-bronchodilator spirometry and analysis of chest computed tomography (CT).

Smoking remains a major risk for children, with one in fifteen high school seniors reporting daily cigarette use [11]. Most smokers initiate the habit by age 18, putting them at risk for a wide range of comorbidities including COPD [12]. Recently, there has been interest in the early origins of COPD and the potential synergistic relationship between childhood respiratory infection, aberrant lung development, and increased susceptibility to smoking related injury [10, 13‐15]. More data is needed to guide providers in anticipating the outcomes of childhood pneumonia and potential additional complications from smoking.

This study examines the association between pneumonia in childhood and future respiratory illness in smokers. We hypothesize that childhood pneumonia is a risk factor for reduced lung function and COPD in adult smokers. Some of the results have been published previously as an abstract [16].

Materials and methods

Subjects

We evaluated 10,192 current and former United States smokers with and without COPD from the COPDGene Study, a multicenter, observational study designed to identify genetic and environmental factors associated with COPD. COPDGene enrolled subjects from 2008–2011. It was approved by the Institutional Review Boards at each of the twenty-one clinical sites. All participants provided written informed consent [17]. Subjects were 45–80 years of age, non-Hispanic white or African American, and had at least a 10 pack-year smoking history. Exclusion criteria included history of lung disease other than COPD or asthma (e.g. extensive bronchiectasis, cystic fibrosis, pulmonary fibrosis, lung cancer). Study protocol, enrollment criteria, and data collection forms were previously described and are available at www.copdgene.org [17, 18].

Data collection

Participants completed a modified American Thoracic Society Respiratory Epidemiology Questionnaire, Modified Medical Research Council (MMRC) dyspnea scale, and questionnaires related to demographics and medical history [18‐20]. Quality of life was assessed using the St. George’s Respiratory Questionnaire (SGRQ) [21]. Subjects completed a standardized spirometry protocol (ndd EasyOne Spirometer, Zurich, Switzerland). Inspiratory and expiratory chest CT scans were obtained. Airway measurements, performed using VIDA software (VIDA Diagnostics; Iowa City, Iowa), assessed wall thickening in segmental airways, subsegmental airways, and the square root of the wall area of a hypothetical airway with 10mm internal perimeter (SRWA-Pi10) [22, 23]. SLICER software (www.slicer.org) was used to quantify emphysema by inspiratory scan low-attenuation areas < -950 Hounsfield units (HU) and gas trapping on expiratory scan at < -856 HU [24].

Case identification

Childhood pneumonia was defined by subject self-report. The questionnaire asked: “Have you ever had pneumonia or bronchopneumonia?” and their age at the first episode. Subjects were classified as childhood pneumonia if they reported an age of first pneumonia at < 16 years or “As a child; age not known.” Subjects were classified as no childhood pneumonia if they reported no pneumonias, an age of first pneumonia ≥ 16 years, or if they did not indicated their first pneumonia was during childhood. Age sixteen was used to define pediatric pneumonia as this was when most subjects in the cohort started smoking (mean 16.9, standard deviation 4.6 years), which is concurrent with a rise in subjects reporting a first episode of pneumonia between ages 15-20.

Chronic bronchitis was defined by cough and phlegm production lasting more than three months per year for at least two years. COPD exacerbations were defined by use of antibiotics or systemic steroids. Severe COPD exacerbations required an emergency room visit or hospitalization. Cardiovascular disease (CVD) was defined by self-reported history of coronary artery disease, congestive heart failure, heart attack (MI), angioplasty, coronary artery bypass graft surgery, peripheral vascular disease, transient ischemic attack, or stroke [25]. Childhood asthma was defined as reported history of asthma diagnosed by a health professional with age of onset at < 16. COPD was defined based on post-bronchodilator forced expiratory volume in the first second (FEV₁) to forced vital capacity (FVC) ratio < 0.7 with FEV₁ < 80 % predicted, corresponding to Global Initiative for Chronic Obstructive Lung Disease (GOLD) Stages 2-4 [26]. Control smokers had normal spirometry, defined as FEV₁/FVC ≥ 0.7 and FEV₁ ≥ 80 %.

Statistical analysis

Subjects with and without childhood pneumonia were compared by demographics, respiratory symptoms/diseases, lung function, and CT measurements. Statistical analysis was performed using R v3.1.1. Single variable analysis used chi-square tests, t-tests, or Wilcoxon rank sum tests. Multivariable regression analysis was performed, with most models adjusted for standard covariates of age, gender, race and smoking history. Additional covariates of FEV₁ % predicted, height, body mass index, and CT scanner model were included for some analyses. Logistic regression reported odds ratios (OR) with 95 % confidence intervals (CI) and linear regression reported absolute differences (β) with standard errors (SE). Subjects with missing or unclassifiable responses were removed from specific analyses.

Regression analysis was repeated in three subsets. First, to assess the effect of asthma, the analysis was performed on subjects without childhood asthma. Second, the analysis was run on only subjects with childhood asthma. Finally, to assess the effect of recall bias, spirometry was analyzed in subjects who did not report a history of COPD or emphysema.

Results

Subject classification and characteristics

COPDGene includes 10,192 current and former smokers (Additional file 1: Figure S1). Thirty-six subjects were excluded, as it was not possible to classify their pneumonia history by questionnaire response. Of the 10,156 subjects included, 854 (8.4 %) reported childhood pneumonia. Of these, 405 subjects had COPD and 282 had normal spirometry. Of the 9,302 subjects without childhood pneumonia, 3,267 had COPD, and 4,097 had normal spirometry. Subjects with GOLD Stage 1 spirometry (FEV₁/FVC < 0.7 with FEV₁ ≥ 80 % predicted) or subjects with Preserved Ratio Impaired Spirometry (PRISm, FEV₁/FVC ≥ 0.7 with FEV₁ < 80 % predicted) were not included in COPD analysis; they were included in the other assessments [27].

Subjects with childhood pneumonia were older and more likely to be non-Hispanic white (Table 1). They were more likely to report living with a smoker in childhood, having a greater lifetime smoking intensity, were less likely to be current smokers, and had an increased number of lifetime pneumonia episodes. The distribution of age of first pneumonia can be seen in Additional file 1: Figure S2.

Table 1

Characteristics of Subjects With and Without History of Childhood Pneumonia

	Childhood Pneumonia		No Childhood Pneumonia		p Value^b
	N = 854 (8.4 %)		N = 9302 (91.6 %)
DEMOGRAPHIC
Male gender (%)	437	(51.2 %)	4990	(53.6 %)	0.18
Mean age, years (SD)	61.7	(8.9)	59.4	(9.0)	<0.001^c
Non-Hispanic white (%)	693	(81.1 %)	6073	(65.3 %)	<0.001
SMOKE EXPOSURE
In-utero smoke exposure (%)^a	206	(33.0 %)	2082	(30.2 %)	0.18
Lived with smoker in childhood (%)^a	732	(85.7 %)	7618	(81.9 %)	0.006
Mean age started smoking, years (SD)	16.5	(4.4)	16.9	(4.7)	0.06
Pack-years of smoking (SD)	49.8	(28.4)	43.7	(24.6)	<0.001
Current smoking (%)	379	(44.4 %)	5011	(53.9 %)	<0.001
PNEUMONIA HISTORY
Ever had pneumonia (%)	854	(100.0 %)	2979	(33.9 %)	<0.001
Diagnosed with pneumonia by healthcare provider (%)^a	821	(96.1 %)	2920	(31.4 %)	<0.001
Pneumonia childhood age unknown (%)	378	(44.3 %)	0	(0.0 %)	<0.001
Age first pneumonia in years, mean (SD)^a	7.7	(4.5)	42.5	(15.6)	<0.001
Lifetime pneumonia episodes (SD)^a	3.9	(4.9)	2.5	(3.0)	<0.001

Abbreviations: SD standard deviation

^aSubjects included are fewer than total subjects due to subject survey response being missing or unclassifiable

^bUnivariate analysis with chi-square or Wilcoxon rank sum test unless otherwise specified^c t test

Respiratory symptoms and disease

Smokers with childhood pneumonia were more likely to develop COPD (Table 2). This remained robust when childhood asthma was added to the model. Childhood pneumonia was associated with increased chronic bronchitis, more frequent and severe COPD exacerbations in the year prior and increased frequency of co-morbid CVD (Table 3). These subjects were more likely to report asthma diagnosed by a healthcare provider and asthma onset in childhood. Childhood pneumonia was associated with worse disease-related quality of life with higher SGRQ, and more severe dyspnea with higher MMRC.

Table 2

COPD in Subjects With and Without History of Childhood Pneumonia

	Childhood Pneumonia		No Childhood Pneumonia		Impact of Childhood Pneumonia^a
	N = 687 (8.5 %)		N = 7364 (91.5 %)		OR	(95 % CI)	p Value^b
COPD, GOLD 2-4	405	(59.0 %)	3267	(44.4 %)	1.40	(1.17, 1.66)	<0.001
COPD, GOLD 2-4 + adjusted for childhood asthma					1.30	(1.09, 1.55)	0.003

Abbreviations: COPD chronic obstructive pulmonary disease; GOLD Global Initiative for Chronic Obstructive Lung Disease

^aEach row represents a separate regression model, odds ratio (OR) and 95 % confidence interval (CI) for logistic regression

^bCovariates for all analyses = age at enrollment in years + gender + race + pack years

Table 3

Respiratory Symptoms and Disease in Subjects With and Without History of Childhood Pneumonia

	Childhood Pneumonia		No Childhood Pneumonia		Impact of Childhood Pneumonia^b
	N = 854 (8.4 %)		N = 9302 (91.6 %)		OR (95 % CI) or β (SE)^c		p Value^d
Chronic bronchitis (%)	214	(25.1 %)	1730	(18.6 %)	1.40	(1.18, 1.66)	<0.001^e
Number of COPD exacerbations in past year (SD)	0.65	(1.2)	0.36	(0.9)	0.18	(0.03)	<0.001^f
Had a severe COPD exacerbation in past year (%)	140	(16.4 %)	1063	(11.4 %)	1.28	(1.04, 1.58)	0.02^f
Cardiovascular Disease (%)^a	179	(21.0 %)	1455	(15.6 %)	1.20	(1.00-1.44)	0.047
Diagnosed with asthma by healthcare provider (%)^a	239	(28.0 %)	1508	(16.3 %)	2.15	(1.83, 2.53)	<0.001
Childhood asthma (%)^a	137	(16.0 %)	586	(6.3 %)	3.30	(2.68, 4.05)	<0.001
SGRQ Score, Total (SD)^a	32.4	(24.0)	26.9	(22.8)	2.32	(0.67)	<0.001^g
MMRC Dyspnea Scale, 0-4 (SD)^a	1.6	(1.5)	1.3	(1.4)	0.12	(0.04)	0.006^g

Abbreviations: COPD chronic obstructive pulmonary disease; SD standard deviation; SGRQ St. George’s Respiratory Questionnaire; MMRC Modified Medical Research Council

^aSubjects included are fewer than total subjects due to subject survey response being missing or unclassifiable

^bEach row represents a separate regression model

^cOdds ratio (OR), 95 % confidence interval (CI) for logistic regression; beta coefficient (β), standard error (SE) for linear regression

^dCovariates for all analyses = age at enrollment in years + gender + race + pack-years

^fAdditional covariates: ^ecurrent smoker; current smoker & FEV₁ % predicted; ^gFEV₁ % predicted

Spirometry showed post-bronchodilator FEV₁ % predicted, FVC % predicted and FEV₁/FVC were all significantly lower in subjects with childhood pneumonia (Fig. 1, Table 4). In regression analysis, chest CT parameters related to airways disease were significantly increased in subjects with childhood pneumonia, with greater airway wall thickness in segmental and subsegmental airways and greater SRWA-Pi10 (Fig. 2, Table 5 and in the Additional file 1: Table S1). These subjects also had increased gas trapping. Multivariable analysis showed no difference in emphysema or total lung capacity measured by chest CT.

Table 4

Effect of Childhood Pneumonia on Lung Function

	Childhood Pneumonia	No Childhood Pneumonia	Impact of Childhood Pneumonia^a
	N = 850 (8.4 %)	N = 9245 (91.6 %)	β	SE	p Value^b
FEV₁ post-BD % predicted (SD)	69.1 % (25.7)	77.1 % (25.4)	−6.22	(0.88)	<0.001
FVC post-BD % predicted (SD)	82.7 % (18.6)	87.4 % (18.3)	−3.89	(0.65)	<0.001
FEV₁/FVC post-BD (SD)	0.63 (0.17)	0.67 (0.16)	−0.02	(0.005)	<0.001^c

Abbreviations: FEV ₁ forced expiratory volume in the first second; FVC forced vital capacity; post-BD post bronchodilator

^aEach row represents a separate regression model, beta coefficient (β) and standard error (SE) for linear regression

^bCovariate used for all analyses = pack years^cAdditional covariates = age at enrollment + gender + race + height

Table 5

Effect of Childhood Pneumonia on Chest CT Parameters

	Impact of Childhood Pneumonia^b
	β^c	SE	p Value^d
Wall Area %, Segmental	0.46	(0.12)	<0.001
Wall Area %, Subsegmental^a	0.47	(0.16)	0.003
SRWA-Pi10	0.02	(0.005)	<0.001
Emphysema % (-950 HU)	0.18	(0.32)	0.57
Gas Trapping %, expiratory scan (-856HU)	1.97	(0.72)	0.006
Total Lung Capacity (L)	0.001	(0.04)	0.99

Abbreviations: CT computed tomography; HU Hounsfield units; SRWA-Pi10 square root wall area of a hypothetical airway with 10mm internal perimeter

^aData only available for a limited portion of the cohort

^bEach row represents a separate regression model

^cBeta coefficient (β) and standard error (SE) for linear regression

^dCovariates used = age at enrollment in years + gender + race + pack-years + body mass index + CT scanner model

Sensitivity and recall analyses

To assess the effect of asthma, regression analysis was repeated in a subset of 9,405 subjects, excluding 723 with childhood asthma and 28 with unclassifiable childhood asthma status (Additional file 1: Table S2). Childhood pneumonia remained significantly associated with COPD (OR 1.24; 95 % CI 1.03-1.50). Other significant associations with childhood pneumonia were maintained, with the exception of the association with severe COPD exacerbations in the past year, which was attenuated.

A corresponding analysis was run including only 723 subjects with childhood asthma (Additional file 1: Table S3). In this subset, having childhood pneumonia showed a stronger association with COPD than in the cohort overall (OR 1.85; 95 % CI 1.10-3.18). The associations with post-bronchodilator percent predicted FEV₁ and FVC remained significant. Other associations were no longer significant.

To assess recall bias, the regression analysis was repeated in a subset of 5,743 subjects who did not report COPD or emphysema diagnosis at enrollment (Additional file 1: Table S4). This included subjects with undiagnosed COPD and without COPD. Although prevalence of COPD was not significantly increased in this subset, both percent predicted FEV₁ and FVC remained significantly lower in subjects with childhood pneumonia.

Discussion

In adult smokers, a history of childhood pneumonia was associated with COPD and reduced lung function, with the greatest association in the subset of subjects with both pneumonia and asthma in childhood. Those with childhood pneumonia had increased chronic bronchitis, more frequent and severe COPD exacerbations, more CVD, increased dyspnea, and worse disease-related quality of life. There was a novel finding of greater airways disease present in chest CT scans of subjects with childhood pneumonia, supporting the idea that childhood disease is associated with long term structural differences in the lung and a distinct COPD phenotype. By comparison, there was no difference in emphysema.

The role of childhood pneumonia in COPD development has been investigated for over sixty years. Oswald surveyed 1000 adults with chronic bronchitis in London from 1951-53, finding 14.3 % reported childhood pneumonia compared to 6 % of controls [28]. In the 1970’s Burrows proposed that childhood respiratory infections are a risk factor for obstructive lung disease in adults, with an enhanced effect in smokers, based on decreased FEV₁ and FEV₁/FVC and increased chronic bronchitis in 415 subjects, mean age of 44.5, who reported childhood respiratory trouble at < 16 years [3]. Four subsequent investigations looked more closely at the relationship between childhood pneumonia in British subjects born between 1911-1935 and adult lung function at ages 34–74, each independently finding an association with decreased FEV₁ and FVC, and suggesting an association between childhood pneumonia and COPD [4‐7]. Only one of these five studies used post-bronchodilator data and none included COPD diagnosis in their outcomes [7].

The European Community Respiratory Health Survey assessed pre-bronchodilator lung function in subjects ages 20-44 in 1991-93 and then again 5-11 years later, showing risk of developing COPD was doubled in subjects with self-reported history of serious respiratory infection at < 5 years, and that this factor accounted for about 8 % of new cases [8, 9, 13]. Recent data from the Tucson Children’s Respiratory Study provided longitudinal post-bronchodilator lung function in 44 subjects born between 1980-84 with radiographically diagnosed pneumonia at ≤ 3 years, demonstrating an association with a persistent decrease in post-bronchodilator FEV₁ and FEV₁/FVC up to age 26 [10].

Compared to prior investigations, our study examines 10,192 United States smokers ages 45-80, including 854 subjects with childhood pneumonia. Our analysis supports the association between childhood pneumonia, reduced lung function in adulthood, and COPD. Our study is unique due to the older age of participants, the objective diagnosis of COPD by post-bronchodilator spirometry, and chest CT analysis. Additionally, few other studies have addressed this question in a population of this size and included assessment of the combined effect of pneumonia and childhood asthma.

Research into the association between childhood and adult respiratory disease is complicated by the inherent difficulty differentiating between diagnoses of childhood pneumonia, asthma, and other respiratory illnesses, which can overlap and evolve over time. Asthma is independently associated with both childhood pneumonia and adult COPD [10, 13, 29, 30]. More recent studies of long-term outcomes from childhood pneumonia have differentiated pneumonia from other respiratory illness and have accounted for asthma in their analyses, finding that the effect of childhood pneumonia on future lung function is greater than that of other childhood respiratory infections, and is robust to adjustments for childhood asthma [5‐8, 10]. This is similar to our finding, where the association of childhood pneumonia with COPD persisted even after adjusting for or removing childhood asthmatics. Notably, we found that it was the combined effect of pneumonia and asthma in childhood had the greatest association with COPD.

Prior investigators have cited the possibility of impaired childhood lung growth and development playing a role in this association [2, 4‐6]. Chest CT changes demonstrated in this analysis, with increased airways disease in subjects with childhood pneumonia, support this hypothesis. There are two potential explanations. The first is that childhood pneumonia may cause airways changes that increased risk for future disease. Alternatively, there may be an underlying developmental abnormality of the lung that increases risk for both childhood pneumonia and lung disease in adult smokers. While asthma has also been associated with airways disease on CT scans, the imaging associations in this analysis were maintained even in a subset analysis where childhood asthmatics were removed, suggesting that childhood pneumonia likely has an independent role [31]. It would be interesting to examine the extent of bronchiectasis in this population given the known associations between childhood pneumonia and bronchiectasis [32], however, standardized visual readings of the chest CT scans are not yet available in COPDGene.

Limitations

The ideal study for examining the connection between childhood pneumonia and COPD would follow subjects from conception to death [33]. However, the challenges of such a study have forced researchers to take other approaches. Studies that use historical medical records paired with current cohorts available for lung function testing can be limited by selection bias [4‐7]. Studies that follow childhood cohorts are limited by younger age at follow-up, especially given that the highest rates of COPD are in those over 65 [7, 10, 34]. An alternative method, employed by our study, was the collection of self-reported medical history from a cohort of adults, understanding that this does not include details such as gestational age, birth weight, childhood socio-economic status, and objective diagnostic tests for childhood pneumonia. This COPDGene Study assessment includes only smokers; therefore we could not address the effect of childhood pneumonia in non-smokers.

We acknowledge that our strategy may lead to potential recall bias, where adult subjects with respiratory disease may be more likely to recall childhood illness. This analysis included a separate assessment for recall bias, focusing only on subjects who did not report a known COPD diagnosis, and thus were less likely to be biased in recalling childhood respiratory problems. In this subset analysis, childhood pneumonia remained associated with reduced lung function. Therefore, it is unlikely that overall study results were influenced by recall bias. Childhood pneumonia was not associated with COPD in this analysis, though this is not surprising given that the subset includes nearly all those with normal lung function, while being most likely to remove subjects with more severe COPD.

Self-reported pneumonia is a potential source of misclassification, however, prior studies have shown that self-reported pneumonia diagnosis has relatively good agreement with the medical record [35]. Additionally, versions of the American Thoracic Society Questionnaire have previously been used to examine pneumonia history, and prior epidemiologic surveys examining the relationship have also used subject self-report [3, 9, 36, 37]. Random misclassification would be expected to bias towards null results, yet we still found a significant association.

Conclusions

We found that the combination of pneumonia in childhood and smoking in adulthood is associated with COPD, increased respiratory symptoms, and reduced lung function. This was supported by novel findings of airways disease on chest CT scans. The greatest association with COPD was seen in those who had both pneumonia and asthma in childhood. Further research will be required to identify whether there are genetic associations that may play a role in determining a subtype of COPD that originates with childhood respiratory disease. In the meantime, medical providers have a valuable opportunity to reduce childhood pneumonias, especially among asthmatics, and to counsel patients about the increased risk from smoke exposure in those who have had pneumonia during childhood.

Acknowledgements

We would like to acknowledge and thank the COPDGene Investigators listed below.

Administrative Core: James Crapo, MD (PI), Edwin Silverman, MD, PhD (PI), Barry Make, MD, Elizabeth Regan, MD, PhD, Rochelle Lantz, Lori Stepp, Sandra Melanson, Sara Penchev.

Genetic Analysis Core: Terri Beaty, PhD, Nan Laird, PhD, Christoph Lange, PhD, Michael Cho, MD, Stephanie Santorico, PhD, John Hokanson, MPH, PhD, Dawn DeMeo, MD, MPH, Nadia Hansel, MD, MPH, Craig Hersh, MD, MPH, Peter Castaldi, MD, MSc, Merry-Lynn McDonald, PhD, Emily Wan, MD, Megan Hardin, MD, Jacqueline Hetmanski, MS, Margaret Parker, MS, Marilyn Foreman, MD, Brian Hobbs, MD, Robert Busch, MD, Adel El-Bouiez, MD, Peter Castaldi, MD, Megan Hardin, MD, Dandi Qiao, PhD, Elizabeth Regan, MD, Eitan Halper-Stromberg, Ferdouse Begum, Sungho Won,Brittney Fredericksen, Sharon Lutz, PhD.

Imaging Core: David A Lynch, MB, Harvey O Coxson, PhD, MeiLan K Han, MD, MS, MD, Eric A Hoffman, PhD, Stephen Humphries MS, Francine L Jacobson, MD, Philip F Judy, PhD, Ella A Kazerooni, MD, John D Newell, Jr., MD, Elizabeth Regan, MD, James C Ross, PhD, Raul San Jose Estepar, PhD, Berend C Stoel, PhD, Juerg Tschirren, PhD, Eva van Rikxoort, PhD, Bram van Ginneken, PhD, George Washko, MD, Carla G Wilson, MS, Mustafa Al Qaisi, MD, Teresa Gray, Jessica James, Alex Kluiber, Tanya Mann, Jered Sieren, Douglas Stinson.

PFT QA Core, LDS Hospital, Salt Lake City, UT: Robert Jensen, PhD.

Data Coordinating Center and Biostatistics, National Jewish Health, Denver, CO: Douglas Everett, PhD, , Anna Faino, MS, Ruthie Knowles, Joe Piccoli, Matt Strand, PhD, Carla Wilson, MS.

Epidemiology Core, University of Colorado Anschutz Medical Campus, Aurora, CO: John E. Hokanson, MPH, PhD, Jennifer Black-Shinn, MPH, PhD, Gregory Kinney, MPH, PhD, Sharon Lutz, PhD, Katherine Pratte, MSPH.

We also wish to acknowledge the COPDGene Investigators from the following participating clinical centers. Ann Arbor VA: Jeffrey Curtis, MD, Carlos Martinez, MD, MPH, Perry G. Pernicano, MD. Baylor College of Medicine, Houston, TX: Nicola Hanania, MD, MS, Philip Alapat, MD, Venkata Bandi, MD, Mustafa Atik, MD, Aladin Boriek, PhD, Kalpatha Guntupalli, MD, Elizabeth Guy, MD, Amit Parulekar, MD, Arun Nachiappan, MD. Brigham and Women’s Hospital, Boston, MA: Dawn DeMeo, MD, MPH, Craig Hersh, MD, MPH, George Washko, MD, Francine Jacobson, MD, MPH. Columbia University, New York, NY: R. Graham Barr, MD, DrPH, Byron Thomashow, MD, John Austin, MD, Belinda D’Souza, MD, Gregory D.N. Pearson, MD, Anna Rozenshtein, MD, MPH, FACR. Duke University Medical Center, Durham, NC: Neil MacIntyre, Jr., MD, Lacey Washington, MD, H. Page McAdams, MD. Health Partners Research Foundation, Minneapolis, MN: Charlene McEvoy, MD, MPH, Joseph Tashjian, MD. Johns Hopkins University, Baltimore, MD: Robert Wise, MD, Nadia Hansel, MD, MPH, Robert Brown, MD, Karen Horton, MD, Nirupama Putcha, MD, MHS. Los Angeles Biomedical Research Institute at Harbor UCLA Medical Center, Los Angeles, CA: Richard Casaburi, MD, Alessandra Adami, PhD, Janos Porszasz, MD, PhD, Hans Fischer, MD, PhD, Matthew Budoff, MD, Dan Cannon, PhD, Harry Rossiter, PhD. Michael E. DeBakey VAMC, Houston, TX: Amir Sharafkhaneh, MD, PhD, Charile Lan, DO. Minneapolis VA: Christine Wendt, MD, Brian Bell, MD. Morehouse School of Medicine, Atlanta, GA: Marilyn Foreman, MD, MS, Gloria Westney, MD, MS, Eugene Berkowitz, MD, PhD. National Jewish Health, Denver, CO: Russell Bowler, MD, PhD, David Lynch, MD. Reliant Medical Group, Worcester, MA: Richard Rosiello, MD, David Pace, MD. Temple University, Philadelphia, PA: Gerard Criner, MD, David Ciccolella, MD, Francis Cordova, MD, Chandra Dass, MD, Robert D’Alonzo, DO, Parag Desai, MD, Michael Jacobs, PharmD, Steven Kelsen, MD, PhD, Victor Kim, MD, A. James Mamary, MD, Nathaniel Marchetti, DO, Aditti Satti, MD, Kartik Shenoy, MD, Robert M. Steiner, MD, Alex Swift, MD, Irene Swift, MD, Gloria Vega-Sanchez, MD. University of Alabama, Birmingham, AL: Mark Dransfield, MD, William Bailey, MD, J. Michael Wells, MD, Surya Bhatt, MD, Hrudaya Nath, MD. University of California, San Diego, CA: Joe Ramsdell, MD, Paul Friedman, MD, Xavier Soler, MD, PhD, Andrew Yen, MD. University of Iowa, Iowa City, IA: Alejandro Cornellas, MD, John Newell, Jr., MD, Brad Thompson, MD. University of Michigan, Ann Arbor, MI: MeiLan Han, MD, Ella Kazerooni, MD, Fernando Martinez, MD. University of Minnesota, Minneapolis, MN: Joanne Billings, MD, Tadashi Allen, MD. University of Pittsburgh, Pittsburgh, PA: Frank Sciurba, MD, Divay Chandra, MD, MSc, Joel Weissfeld, MD, MPH, Carl Fuhrman, MD, Jessica Bon, MD. University of Texas Health Science Center at San Antonio, San Antonio, TX: Antonio Anzueto, MD, Sandra Adams, MD, Diego Maselli-Caceres, MD, Mario E. Ruiz, MD.

Funding

Supported by National Institutes of Health (NIH) grants T32 HL007427, R01HL094635, R01NR013377, P01HL105339, R01HL089897 and R01HL089856. The COPDGene® project is also supported by the COPD Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis, Pfizer, Siemens, Sunovion and Image Analysis. Neither the NIH nor the COPD Foundation Industry Advisory Board had a role in the study design, collection, analysis and interpretation of the data, writing of the manuscript or the decision to submit the paper for publication.

Institutional review board approval

This study was conducted in accordance with the amended Declaration of Helsinki. This study obtained approval from the Institutional Review Board at Brigham and Women’s Hospital and at each of the twenty-one clinical sites. All participants provided written informed consent for their medical data to be used prior to taking part in the study.

Clinical Center and IRB protocol numbers:

Ann Arbor VA, Ann Arbor, MI (PCC 2008-110732).

Baylor College of Medicine, Houston, TX (H-22209).

Brigham and Women’s Hospital, Boston, MA (2007-P-000554/2; BWH).

Columbia University, New York, NY (IRB-AAAC9324).

Duke University Medical Center, Durham, NC (Pro00004464).

Health Partners Research Foundation, Minneapolis, MN (07-127).

Johns Hopkins University, Baltimore, MD (NA_00011524).

Los Angeles Biomedical Research Institute at Harbor UCLA Medical Center, Los Angeles, CA (12756-01).

Michael E. DeBakey VAMC, Houston, TX (H-22202).

Minneapolis VA, Minneapolis, MN (4128-A).

Morehouse School of Medicine, Atlanta, GA (07-1029).

National Jewish Health, Denver, CO (HS-1883a).

Reliant Medical Group, Worcester, MA (1143).

Temple University, Philadelphia, PA (11369).

University of Alabama, Birmingham, AL (FO70712014).

University of California, San Diego, CA (70876).

University of Iowa, Iowa City, IA (200710717).

University of Michigan, Ann Arbor, MI (HUM00014973).

University of Minnesota, Minneapolis, MN (0801M24949).

University of Pittsburgh, Pittsburgh, PA (PRO07120059).

University of Texas Health Science Center at San Antonio, San Antonio, TX (HSC20070644H).

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Competing interests

Authors’ contributions

Additional file

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Titel: Childhood pneumonia increases risk for chronic obstructive pulmonary disease: the COPDGene study
verfasst von: Lystra P. Hayden
Brian D. Hobbs
Robyn T. Cohen
Robert A. Wise
William Checkley
James D. Crapo
Craig P. Hersh
on behalf of the COPDGene Investigators
Publikationsdatum: 01.12.2015
Verlag: BioMed Central
Erschienen in: Respiratory Research / Ausgabe 1/2015
Elektronische ISSN: 1465-993X
DOI: https://doi.org/10.1186/s12931-015-0273-8

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Abstract

Background

Methods

Results

Conclusions

Clinical trials registration

Electronic supplementary material

Competing interests

Authors’ contributions

Background

Materials and methods

Subjects

Data collection

Case identification

Statistical analysis

Results

Subject classification and characteristics

Respiratory symptoms and disease

Sensitivity and recall analyses

Discussion

Limitations

Conclusions

Acknowledgements

Funding

Institutional review board approval

Competing interests

Authors’ contributions

Additional file

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