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1484 LETTERS TO THE EDITOR

gastroesophageal reflux for certain and suggest EoE as the mostlikely diagnosis.

EoE is currently defined as a chronic immune/antigen-mediated esophageal disease characterized clinically by symp-toms related to esophageal dysfunction and histologically byeosinophil-predominant inflammation.2

Data from the literature show that EoE is often associated withallergic diathesis because up to 93% of pediatric and 86% of adultpatients have another allergic disease.2 Sensitization to aeroaller-gens, pollens in the great majority of the cases, was observed inmore than 80% of adult patients.2,3

Inhalant allergens have been demonstrated to cause experi-mental EoE, and some studies showed an association between thepollen season and esophageal eosinophilic infiltration, symptomexacerbation, higher incidence, and newly diagnosed cases ofEoE.4-7 In contrast to these observations, esophagitis symptomsstarted before and recovered along with esophageal eosinophiliaduring the grass pollen season. In any case, seasonal variationsin the incidence of EoE were not confirmed in a more recentstudy.8

In sensitized patients aeroallergens appear to have only acomplementary role in EoE pathogenesis.2 Ingestion of plant-derived food cross-reacting with pollen allergens might have apathogenic role in triggering EoE.2 In fact, sensitization tocross-reactive plant-derived allergens was found in 69% of acase series of adults with EoE, and profilin, followed bypathogenesis-related proteins (Bet v 1 homologues), representedthe most frequent allergens.3 Our patient proved sensitized to pro-filin. However, because no dietary restriction and no changes inthe usual diet were carried out, a relationship with food seemshighly improbable.

In the described case grass pollen sublingual vaccine seems tobe the only triggering factor of esophageal eosinophilia.

In a population of pediatric patients treated with milk oralimmunotherapy, some cases of likely EoE (3/110 [2.72%]) havebeen reported as a complication of the maintenance phase 3 and14 months after a final dose of 200 mL was achieved. All thepatients recovered after a milk-free diet.9 A similar case has beenreported after egg oral immunotherapy.10 These cases led us toconjecture that repeated esophageal stimuli with a high dose of of-fending allergens might elicit esophageal eosinophilia, perhapsthrough a locally immune-mediate response.

It is likely that esophageal eosinophilia represents only anextremely rare adverse reaction to pollen SLIT. It is noteworthythat mite SLIT was and even now is continued without anyproblem. Nevertheless, we believe that esophageal eosinophiliashould be considered in all patients receiving SLITwho complainof dysphagia or other gastroesophageal symptoms. Long-termevolution of esophageal eosinophilia is not known. Therefore wesuggest considering the occurrence of esophagitis symptoms withesophageal eosinophilia as an absolute contraindication tocontinuing sublingual therapy with the culprit vaccine.

Andrea Antico, MDa

Rossella Fante, MDb

From athe Allergy Unit, Ospedale Civile SRL, Volta Mantovana, Italy, and bRossella

Fante, Pathology Unit, Azienda Ospedaliera ‘‘C. Poma,’’ Mantova, Italy. E-mail:

antico47@gmail.com.

Disclosure of potential conflict of interest: The authors declare that they have no relevant

conflicts of interest.

REFERENCES

1. Canonica GW, Bousquet J, Casale T, Lockey RF, Baena-Cagnani CE, Pawankar R,

et al. Sublingual immunotherapy: World Allergy Organization Position Paper

2009. Allergy 2009;64(suppl 91):1-59.

2. Liacouras CA, Furuta GT, Hirano I, Atkins D, Attwood SE, Bonis PA, et al. Eosin-

ophilic esophagitis: updated consensus recommendations for children and adults.

J Allergy Clin Immunol 2011;128:3-20.e6.

3. Simon D, Straumann A, Dahinden C, Simon HU. Frequent sensitization to

Candida albicans and profilins in adult eosinophilic esophagitis. Allergy 2013;

68:945-8.

4. Rayapudi M, Mavi P, Zhu X, Pandey AK, Abonia JP, Rothenberg ME, et al. Indoor

insect allergens are potent inducers of experimental eosinophilic esophagitis in

mice. J Leukoc Biol 2010;88:337-46.

5. Fogg MI, Ruchelli E, Spergel JM. Pollen and eosinophilic esophagitis. J Allergy

Clin Immunol 2003;112:796-7.

6. Onbasi K, Sin AZ, Doganavsargil B, Onder GF, Bor S, Sebik F. Eosinophil infil-

tration of the oesophageal mucosa in patients with pollen allergy during the season.

Clin Exp Allergy 2005;35:1423-31.

7. Almansa C, Krishna M, Buchner AM, Ghabril MS, Talley N, DeVault KR, et al.

Seasonal distribution in newly diagnosed cases of eosinophilic esophagitis in

adults. Am J Gastroenterol 2009;104:828-33.

8. Sorser SA, Barawi M, Hagglund K, Almojaned M, Lyons H. Eosinophilic esoph-

agitis in children and adolescents: epidemiology, clinical presentation and seasonal

variation. J Gastroenterol 2013;48:81-5.

9. Sanchez-Garcia S, Rodriguez Del Rio P, Escudero C, Martinez-Gomez MJ, Ibanez

MD. Possible eosinophilic esophagitis induced by milk oral immunotherapy.

J Allergy Clin Immunol 2012;129:1155-7.

10. Ridolo E, De Angelis GL, Dall’aglio P. Eosinophilic esophagitis after specific

oral tolerance induction for egg protein. Ann Allergy Asthma Immunol 2011;

106:73-4.

Available online March 15, 2014.http://dx.doi.org/10.1016/j.jaci.2014.01.030

The association between asthma and allergicdisease and mortality: A 30-year follow-upstudy

To the Editor:Over the last 30 years, rates of asthma and allergic disease have

increased markedly in the United States.1-3 Little is known aboutthe long-term mortality burden of these conditions, which typi-cally develop in children and young adults. It has been suggestedthat asthma and allergy may represent a state of systemic immu-nologic perturbation, perhaps with long-term consequences,4 andobservational studies have linked allergic disease with cardiovas-cular disease5 and cancer.6 A better understanding of themortalityrisk of asthma and allergy may direct resource allocation andinform disease mechanism. We therefore investigated data avail-able from the first National Health and Nutrition ExaminationSurvey Epidemiologic Follow-up Study (NHEFS) to determinethe association between asthma, food allergy, and hay fever,and all-cause, cardiovascular, cancer, and respiratory mortality.We further explored whether asthma-mortality associations maybe influenced by lung function in the subset of participants whoperformed spirometry.

The NHEFS included a US-based full cohort of 14,407 sub-jects aged 25 to 74 years who completed an interview and med-ical examination in 1971-1975. A subcohort of 6,913underwent a more detailed health interview and examination,including questions on smoking and performance of spirometry(see Fig E1 in this article’s Online Repository at www.jacionline.org). While the full cohort oversampled certaingroups considered at risk for malnutrition, the subcohort isconsidered nationally representative. Follow-up occurred in1982-1984, 1986, 1987, and 1992. The NHEFS ascertained

TABLE I. Demographic characteristics of NHEFS participants at

baseline (1971-1974)

Characteristic

Full cohort

(n 5 13,042)

Subcohort

(n 5 5,132)

Age (y), %

25-34 26.6 25.9

35-44 21.7 19.3

45-54 16.1 23.6

55-64 12.1 17.4

65-75 23.3 13.6

Race, %

White 83.6 89.2

African American 15.2 10.8

Other 1.2 —

Sex (%)

Male 39.6 45.3

Female 60.4 54.7

Education

<10th grade/special school 37.3 30.7

11th-12th grade 38.5 41.8

College/graduate 23.5 27.2

Missing 0.6 0.2

Annual income ($), %

<5,000 25.5 18.9

5,000-<10,000 29.3 26.4>_10,000-<15,000 20.9 24.0>_15,000 20.4 27.1

Missing 3.7 3.5

Smoking status, %*

Never 38.2 38.0

Ever 46.4 —

Current — 19.6

Former — 42.2

Missing 15.4 0.01

Pack years category, %*

0 NA 41.4

<30 31.5

30-60 15.6

>60 7.5

Missing 3.9

NA, Not applicable/available.

*The full cohort includes all NHEFS participants who met inclusion/exclusion criteria.

The subcohort includes all NHEFS participants who had additional spirometry performed

and further information obtained on smoking history. For the full cohort, smoking status

(never/ever) was obtained at the 1982-1984 survey. For the subcohort, smoking status

(never/ever/current) and pack-years smokedwere obtained at baseline.A smoking history

was not obtained on all subjects at baseline. Please see this article’s Online Repository at

www.jacionline.org for methods and variable definitions.

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LETTERS TO THE EDITOR 1485

mortality through December 31, 2006, based on deaths identi-fied during previous follow-up and matching between NHEFSrecords and the National Death Index. Because a smoking his-tory was not obtained on the full cohort at baseline, we useddata obtained in 1982-1984 to ascertain smoking status.Missing education, income, and smoking data were imputed.See this article’s Online Repository at www.jacionline.org foradditional methods.

We used Cox proportional hazard regression models todetermine the association between current asthma, food allergy,and hay fever, and all-cause and cause-specific mortality. Allanalyses were performed in STATA 12 (College Station, Tex)using age as the underlying timemetric and the 1982-1984 surveyas the start of follow-up. Analyses took place at the Research DataCenter at the National Center for Health Statistics in Hyattsville,

Maryland, because the mortality data through 2006 are consid-ered restricted-use data.

At baseline, 3.6% of the subjects reported a history of doctor-diagnosed asthma, 4.5% reported food allergy, and 8.6% reportedhay fever; 6800 (52.1%) died during follow-up. There were 2492cardiovascular deaths, 1588 cancer deaths, and 539 respiratorydeaths. Demographic characteristics of NHEFS subjects are listedin Table I.

In the full cohort, a history of asthma was associated with astatistically significant increase in respiratory and all-causemortality. Asthma was not associated with other cause-specificmortality outcomes, and food allergy and hay fever were notassociated with mortality of any cause (see Table E1 in this ar-ticle’s Online Repository at www.jacionline.org). The age-adjusted hazard ratio (HR) for asthma and respiratory mortalitywas 2.22 (95% CI, 1.47-3.35; Table II), which was similar afteradjusting for sex, income, education, race, and smoking historyand exclusion of subjects reporting a diagnosis of emphysema.In the subcohort, we found that the age-adjusted hazard of res-piratory mortality associated with a history of asthma was 2.45(95% CI, 1.25-4.78), which was similar after adjusting for de-mographic variables. However, after including smoking in themodel, the HR associated with asthma declined to 2.01 (95%CI, 0.92-4.42). Further addition of lung function to the modelresulted in an adjusted HR of 1.45 associated with asthma(95% CI, 0.67-3.14).

In the full cohort, the age-adjusted HR for all-cause mortalitycomparing those with and without a history of asthma wassignificantly elevated (HR, 1.23; 95% CI, 1.07-1.42). Thisremained significant after additionally adjusting for sex, income,education, race, and smoking history and excluding subjectsreporting a diagnosis of emphysema. We did not find an associ-ation between asthma and all-cause mortality in the subcohort(age-adjusted HR, 1.07; 95% CI, 0.82-1.40). This discrepancymay be due to differences in the asthma-mortality relationshipbetween the full cohort and the subcohort or a lack of power in thissmaller sample size (for further discussion, and exploration ofeffect modification, see the Online Repository available at www.jacionline.org).

We examined the association between asthma and allergicdisease andmortality in a population-based cohort withmore than30 years of follow-up. We identified an increased risk of respi-ratory and all-causemortality associated with a doctor’s diagnosisof asthma. Asthma was not associated with the other specificmortality causes we investigated, nor was food allergy or hayfever associated all-cause or cause-specific mortality. Althoughthere was no indication of mortality risk in the United States dueto allergic disease per se, asthmawas associatedwith an increasedrisk of respiratory and all-cause mortality. In the subcohort inwhich more detailed data on smoking history were available,adjustment for confounding by smoking history attenuated the as-sociation between asthma and mortality, raising the possibilitythat residual confounding by smoking history may underliesome of the excess mortality risk seen in the full cohort. Incorpo-ration of lung function into the model caused further attenuationof the association between asthma and respiratory mortality, sug-gesting that the asthma-mortality association may be drivenlargely by lung function abnormalities.

To our knowledge, this is the first report of an associationbetween asthma and increased risk of respiratory and all-causemortality. This contrasts with previous observations that

TABLE II. HRs for asthma and all-cause and respiratory mortality, adjusting for demographic, smoking, and lung function characteristics

Respiratory mortality

Full cohort Subcohort

Condition 1 2 3 4 1 2 5 6

Asthma 2.22 (1.47-3.35)* 2.26 (1.46-3.47)* 2.28 (1.50-3.47)* 2.22 (1.34-3.67)* 2.45 (1.25-4.78)* 2.51 (1.26-4.98)* 2.01 (0.92-4.42) 1.45 (0.67-3.14)

Mild obstruction 2.08 (1.34-3.24)*

Moderate to severe

obstruction

5.86 (3.71-9.23)*

Restriction 1.65 (1.09-2.47)*

Model 1 is adjusted for age. Model 2 is adjusted for age, sex, income, education, and race. Model 3 is the same as model 2, additionally adjusted for smoking history obtained at the

1982-1984 survey (ever/never). Model 4 is the same as model 3, excluding subjects with a history of bronchitis or emphysema. Model 5 is the same as model 2, additionally

adjusted for smoking history obtained at baseline (never/former/current) and pack-year history. Model 6 is the same as model 5, additionally adjusted for lung function category.

*Statistically significant (P < .05).

J ALLERGY CLIN IMMUNOL

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1486 LETTERS TO THE EDITOR

identified null associations for asthma and all-cause mortality.7,8

However, 1 study included only young university students, andanother, while nationally representative, did not have the benefitof a 30-year follow-up time. Our analyses within the subcohortsuggest that the respiratory mortality burden of asthma is ex-plained, at least in part, by lung function abnormalities, ratherthan by the general diagnosis of asthma. The factors that influencelung function decline in asthma are not well understood, andfurther study may help determinewhether strategies aimed at pre-vention of loss of lung function in asthma will have a mortalitybenefit.

The strengths of our study include the large sample size, longduration of follow-up, population-based design, and inclusion ofsmoking history as a covariate. We included only deathsoccurring after the 1982-1984 follow-up, making it less likelythat assessment of allergic disease, asthma, and pulmonaryfunction was confounded by the presence of other medicalcomplications. Most of our predictors were based on a history ofa doctor’s diagnosis of asthma or allergy, which may be limitedby misclassification. However, our results are in generalagreement with studies using skin testing as an objectivemeasure of atopic disease that did not have the benefit of along follow-up time.9 Our most prominent findings were withrespiratory mortality, which unlike all-cause mortality is subjectto potential misclassification, but we did detect a consistent sig-nificant increase in all-cause mortality associated with asthma inthe full cohort. Because emphysema may be difficult to differen-tiate from asthma clinically, we performed sensitivity analysesexcluding subjects with emphysema, which did not change ouroverall results. Since the NHEFS baseline visit, fewer Ameri-cans are smoking and improved asthma therapies have emerged,which may improve the long-term mortality associated withasthma and reduce lung function decline. Observing the long-term mortality risk of asthma in recent populations with moreaccess to inhaled corticosteroids and long-acting bronchodilatorswill be of value to determine whether these agents can poten-tially modify the observed association between asthma andmortality.

In conclusion, we identified a significantly increased risk ofrespiratory and all-cause mortality in subjects with asthma.Analyses in the smaller subcohort with more information onsmoking available suggests that residual confounding by smokinghistory may underlie at least some of this observation. There wereno associations between asthma and cardiovascular or cancermortality or other allergic disease and an increased risk ofmortality from any cause. Our data do not support the theory

that allergy is a systemic inflammatory disease leading todownstream immune dysregulation, cardiovascular disease, orcancer. Within the subcohort, excess respiratory mortality riskwas largely explained by lung function abnormalities. Takentogether, these findings are reassuring but suggest thatbetter understanding of factors contributing to lung functiondecline and efforts to prevent this may have a mortality benefit inasthma.

Jessica H. Savage, MD, MHSa,b

Elizabeth C. Matsui, MD, MHSc

Meredith McCormack, MD, MHSd

Augusto A. Litonjua, MD, MPHb,e,f

Robert A. Wood, MDc

Corinne A. Keet, MD, MSc

From athe Division of Rheumatology, Immunology, and Allergy, Brigham and Women’s

Hospital, and bHarvard Medical School, Boston, Mass; cthe Division of Pediatric Al-

lergy and Immunology and dthe Division of Pulmonary and Critical Care Medicine,

Johns Hopkins University School of Medicine, Baltimore, Md; and eChanning Divi-

sion of Network Medicine and fthe Division of Pulmonary and Critical Care Medi-

cine, Brigham and Women’s Hospital, Boston, Mass. E-mail: jrsavage@partners.org.

This work was supported in part by a training grant from the National Institutes of

Health (NIH) (grant no. 5T32AI007056-34), a grant from the American Academy

of Allergy, Asthma & Immunology and Food Allergy Research and Education, and

a KL2 Medical Research Investigator Training award (an appointed KL2 award)

from Harvard Catalyst j The Harvard Clinical and Translational Science Center (Na-

tional Center for Research Resources and the National Center for Advancing Trans-

lational Sciences) (NIH Award no. 1KL2 TR001100-01 to J.H.S.). The content is

solely the responsibility of the authors and does not necessarily represent the official

views of Harvard Catalyst, Harvard University and its affiliated academic health care

centers, or the NIH.

Disclosure of potential conflict of interest: J. H. Savage and C. A. Keet have received

research support from the National Institutes of Health (NIH). M. McCormack has

received research support from the National Institute of Environmental Health Sci-

ences. A. A. Litonjua has received royalties from UpToDate and Springer. R. A.

Wood has received consultancy fees from the Asthma and Allergy Foundation of

America, is employed by Johns Hopkins University, has received research support

from the NIH, and has received royalties from UpToDate. E. C. Matsui declares

that she has no relevant conflicts of interest.

REFERENCES

1. Akinbami LJ, Moorman JE, Bailey C, Zahran HS, King M, Johnson CA, et al.

Trends in asthma prevalence, health care use, and mortality in the United States,

2001-2010. NCHS Data Brief 2012;1-8.

2. Singh K, Axelrod S, Bielory L. The epidemiology of ocular and nasal allergy in the

United States, 1988-1994. J Allergy Clin Immunol 2010;126:778-83.e6.

3. Sicherer SH, Munoz-Furlong A, Godbold JH, Sampson HA. US prevalence of self-

reported peanut, tree nut, and sesame allergy: 11-year follow-up. J Allergy Clin

Immunol 2010;125:1322-6.

4. Prescott SL. Early-life environmental determinants of allergic diseases and the

wider pandemic of inflammatory noncommunicable diseases. J Allergy Clin Im-

munol 2013;131:23-30.

All-cause mortality

Full cohort Subcohort

1 2 3 4 1 2 5 6

1.23 (1.07-1.42)* 1.21 (1.05-1.39)* 1.22 (1.06-1.40)* 1.21 (1.03-1.42)* 1.07 (0.82-1.40) 1.08 (0.84-1.44) 1.07 (0.82-1.40) 1.00 (0.76-1.30)

0.96 (0.79-1.15)

1.57 (1.30-1.89)*

1.30 (1.14-1.49)*

TABLE II. (Continued)

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LETTERS TO THE EDITOR 1487

5. Knoflach M, Kiechl S, Mayr A,Willeit J, PoeweW,Wick G. Allergic rhinitis, asthma,

and atherosclerosis in theBruneck andARMYstudies.Arch IntMed 2005;165:2521-6.

6. McWhorter WP. Allergy and risk of cancer: a prospective study using NHANESI

followup data. Cancer 1988;62:451-5.

7. Diaz-Guzman E, Khosravi M, Mannino DM. Asthma, chronic obstructive pulmo-

nary disease, and mortality in the U.S. population. COPD 2011;8:400-7.

8. Galobardes B, McCarron P, Jeffreys M, Davey Smith G. Association between early

life history of respiratory disease and morbidity and mortality in adulthood. Thorax

2008;63:423-9.9. Gergen PJ, Turkeltaub PC, Sempos CT. Is allergen skin test reactivity a

predictor of mortality? Findings from a national cohort. Clin Exp Allergy 2000;

30:1717-23.

Available online March 14, 2014.http://dx.doi.org/10.1016/j.jaci.2014.01.028

Resolution of acute IgE-mediated allergywith development of eosinophilic esophagitistriggered by the same food

To the Editor:Eosinophilic esophagitis (EoE) is characterized by isolated

eosinophilic infiltration of the esophagus that can present at anyage and symptomatically mimic gastrointestinal reflux disease(GERD). The symptoms vary by age from failure to thrive inyoung children, to abdominal pain, regurgitation, and vomitingseen in school-age children and dysphagia and food impaction inadolescents and adults.1 Atopy is commonly observed in EoE,with 28% to 86% of adults and 42% to 93% of children havinganother allergic disease and 71% to 93% of the subjects havingpositive skin prick test results to aeroallergens.2 In addition,high rates of IgE-mediated food allergy (15% to 43%) arereported in subjects with EoE, especially in children.3 Foodsare the major antigenic trigger for EoE in children and adults,with milk, egg, wheat, and soy being most common.2,4

Genetic analyses and murine model systems have recentlyidentified a role for the cytokine thymic stromal lymphopoietin(TSLP) in promoting eosinophilic esophageal inflammation. Wehave shown gain-of-function polymorphisms in the TSLP gene tobe associated with EoE development in children.5,6 Furthermore,in our mouse model, TSLP and basophils contributed to thedevelopment of EoE-like disease,7 independent of IgE,7 andincreased basophil responses in human EoE are seen with theTSLP polymorphism. Furthermore, there are reports of childrendeveloping EoE after receiving oral imunotherapy (OIT) forfood allergy.8 Together, this suggests that IgE-dependentmechanisms may not be critical for the development of EoE.However, the relationship between IgE-mediated inflammationand EoE in human subjects is unknown and conflicting.1,2,8,9

We sought to assess the association between IgE-mediated foodallergy and EoE in our cohort. We identified a subgroup of

17 children with a history of clinically relevant IgE-mediatedfood allergy who after outgrowing their IgE-mediated foodallergy were found to have EoE to the same food. Thus,IgE-mediated food allergy may proceed, and possibly predisposeto, the development of EoE, with the pathogenesis of EoE beingdistinct from that of IgE-mediated food allergy.

The study was approved by the Children’s Hospital ofPhiladelphia’s Institutional Review Board. This is a retrospectivecohort study from our database from our Center for PediatricEosinophilic Disorders. The diagnosis of EoE was confirmed per2011 consensus document.1 IgE-mediated food allergy wasconfirmed by history and testing. EoE causative foods wereconfirmed by esophagogastroduodoscopy (EGD) and biopsy.(See the Methods section in this article’s Online Repository atwww.jacionline.org for additional details.)

A total of 1375 subjects were included in the database. A totalof 1025 subjects had confirmed EoE, and a definitive causalfood was identified by biopsy for 425 subjects. Of these 425,84 had a history of IgE-mediated food allergy to any food(preceding/concurrent with EoE diagnosis); 17 of the 84 subjectsoutgrew their IgE-mediated food allergy and subsequentlydeveloped EoE to the same food. Two of these 17 subjects haddocumented normal esophageal biopsies at the time they hadIgE-mediated allergy to the food, but they were diagnosed withEoE only after the food was reintroduced into their diet followinga negative oral food challenge.

Consistent with our previous reports,2 the most common foodscausing EoE in this subgroup of 17 subjects were identical to thoseseen in the entire cohort (Table I), with milk, egg, soy, and wheatbeing the most common. The most common foods causing IgE-mediated allergy in this subgroup are similar to those in the generalpopulation: peanut, tree nuts, egg, andmilk (Table I). Themost com-mon symptoms of IgE-mediated food allergy were hives (n 5 9),emesis (n5 2), anaphylaxis (n5 2), andworsening of atopicderma-titis symptoms (n5 6). For 3 of the 17 subjects (17.6%),more than 1food was identified as causal for their EoE; in 2 subjects, 2 foodswere identified; and in 1 subject, 3 foods were identified. Atopicdisease was common among this subgroup of patients, with 82.3%(n5 14 of 17) having another allergic disease (Table I).

The average time from when the subjects had outgrown theirIgE-mediated food allergy to their diagnosis of EoEwas 2.4 years.This gradual onset of symptoms suggests that esophageal damagedeveloped slowly over years before the patients noticed symp-toms, or, alternatively, repeated exposure over time lead to thedevelopment of non-IgE sensitization causing EoE. One patientdeveloped symptoms after only 2 months of exposure to the food,similar to that described in oral immunotherapy,9 suggestingpossibly multiple mechanisms or variable patient sensitivities.

HUMAN STUDIES APPROVALData collection for the NHEFS was approved by the National

Center For Health Statistics (NCHS) Research Ethics ReviewBoard. Analysis of de-identified data from the survey is exemptfrom federal regulations for the protection of human researchparticipants.Analysis of restricted data through theNCHSResearchData Center is also approved by the NCHS Ethics Review Board.

STUDY DESIGNThe NHEFS is a national longitudinal study designed to

investigate the relationships between clinical, nutritional, andbehavioral factors assessed in the first National Health andNutrition Examination Survey (NHANES I) and subsequentmorbidity, mortality, and hospital utilization, as well as changesin risk factors, functional limitation, and institutionalization.E1

The NHEFS cohort includes all persons aged 25 to 74 years whocompleted a medical examination at NHANES I in 1971-1975(n 5 14,407). Four follow-up studies have been conducted todate. The 1982-1984 survey was designed to include all membersof the NHEFS cohort and involved conducting personal interviewswith subjects or their proxies; measuring pulse rate, weight, andblood pressure of surviving participants; collecting hospital andnursing home records of overnight stays; and collecting death cer-tificates of decedents. Follow-up occurred in 1986, 1987, and 1992using the same design and data collection procedures developed inthe 1982-1984 NHEFS, with the exception that a 30-minutecomputer-assisted telephone interview was administered ratherthan a personal interview and no physical measurements weretaken. The 1986 NHEFS was conducted for members of theNHEFS cohort who were aged 55 to 74 years at their baseline ex-amination and not known to be deceased at the 1982-1984NHEFS(n5 3,980). The 1987 NHEFS was conducted for the entire non-deceased NHEFS cohort (n 5 11,750). The fourth wave of datacollection, the 1992 NHEFS, includes the entire nondeceasedNHEFS cohort (n 5 11,195). Tracing rates for each completedwave ranged from 90% to 94% and interview rates ranged from91% to 96% of those traced. By the 1992 follow-up, 96% percentof the study population had been successfully traced at least once.

VARIABLE DEFINITIONS

Demographic variablesParticipants in the NHEFS completed an extensive question-

naire at baseline that included the demographic data of age, race,sex, income, and education level. We classified total annualfamily income and highest grade of school attended into ordinalvariables, with similar numbers of subjects in each group. Forincome we used less than $5,000, $5,000 to less than $10,000,$10,000 to less than $15,000, and more than $15,000 per year ascategories. An income of below $4,275 was considered povertyfor a family of four in 1972.E2 For education we used completionof less than 10th grade or special school, 11th to 12th grade, orattendance at college/graduate school as categories. Demographicvariables with more than 2 categories were incorporated into theanalytical models as categorical variables.

Participants were asked ‘‘has a doctor ever told you that youhave any of the following conditions, and if so, do you stillhave it?’’ for asthma, allergies to food, hay fever, and chronicbronchitis or emphysema (referred to simply as emphysema in themain article). A history of allergic diseasewas considered positiveif they reported a current diagnosis of the above conditions. For

bronchitis or emphysema, a history was considered positive ifthey reported any diagnosis.

Smoking historyFull cohort: A smoking history was obtained on all located,

nondeceased subjects at the 1982-1984 follow-up. We classifiedsubjects as ever smokers if they reported ever smoking at least100 cigarettes and never smokers if they did not.

Subcohort: At the baseline visit, a smoking history was ob-tained only for participants in the subcohort. We considered par-ticipants to be former smokers if they reported any previous use ofcigarettes (>100), cigars (>50), or pipes (>3 packages of tobacco)but no current use. Intensity of use was available for cigarettesonly. We estimated pack-years of cigarette use by multiplyingthe average number of cigarettes smoked daily when the subjectsmoked the most by the number of years since starting smokingregularly (for current smokers) or the number of years betweenstarting smoking and last smoking (for former smokers) anddividing the product by 20. Pack-years was incorporated intoanalyses as a categorical variable.

Pulmonary function dataSubjects who participated in the subcohort performed spirom-

etry using a spirometer (Model 800; Ohio Medical InstrumentCompany, Inc, Cincinnati, Ohio). The procedures have beendocumented previously.E3 Values used in this analysis includedforced vital capacity (FVC), FEV1, and the FEV1/FVC ratio.We determined predicted values of FEV1 and FVC using pub-lished spirometric reference values for Caucasians and AfricanAmericans.E4 We excluded 56 subjects whose race was catego-rized as ‘‘other’’ given the lack of information on race and corre-sponding spirometric reference values.

A subject was considered to have obstructive lung disease if theFEV1/FVC ratio was less than the predicted lower limit of normalFEV1/FVC for age.E4,E5 Obstruction was considered mild (FEV1

>_70% predicted) or moderate to severe (FEV1 <70% predicted).Subjects were considered to have restrictive disease if there wasno evidence of obstruction and the FVC was less than 80% ofthe predicted value. The remaining subjects, without spirometricevidence of restriction or obstruction, were considered the refer-ence group. We included only those subjects who had reliablespirometry results according to NCHS documentation.

Of the 6913 participants included in the subcohort, spirometrydata were available only on 5544 subjects. Although all membersof the subcohort were eligible for the spirometry portion of theexamination, subjects were excluded from performing spirometryif a study physician did not provide permission, or if subjectscould not generate acceptable data because of poor effort ordifficulty comprehending instructions. Individual-level reasonsfor missing spirometry data are not available in the NHANESdocumentation.

Mortality data and outcomesMortality-related data through 2006 including final mortality

status, age at death, age when last presumed alive, and underlyingcause of death are restricted variables and therefore these datawere accessed through the Research Data Center of the NCHS inHyattsville, Maryland, after an approval process.

The National Death Index (NDI) obtains the cause of deathfrom the death certificate, which is completed by an individual

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licensed to do so by the state where death takes place. Theunderlying cause of death is provided on the death certificate inthe best medical opinion of the certifier. Only one underlyingcause of death may be listed by the certifying physician, thoughseveral immediate causes of death may be listed. The listedunderlying cause of death is assigned an International StatisticalClassification of Diseases, 10th Revision (ICD-10) (or the Inter-national Classification of Diseases, Ninth Revision, for deathsbefore 1999) diagnostic code by the NDI staff using a computer-ized nosology coding system. The cause of death variable used inthis analysis was provided by the NDI and has 113 categoriesidentified by ICD-10 codes, where deaths before 1999 (whichoriginally were coded using the International Classification ofDiseases, Ninth Revision) were recoded by the NDI staff usingICD-10 codes.

We examined all-cause, cardiovascular, cancer, and respiratorymortality. We used the ICD-10 codes, available from the ResearchData Center, to classify causes of death as follows: cardiovascular(eg, hypertension, ischemia, atherosclerosis, I00-I13, I20-I51,and I70-I78), cancer (eg, malignant and benign neoplasms,C00-C97 and D00-D48), and respiratory disease (eg, lower respi-ratory infection, emphysema, and asthma, J10-J18, J20-J22, andJ40-J47).

EXCLUSION CRITERIAWe excluded 28 subjects from the full cohort whowere listed as

having an age of more than 100 years in 2006, in accordance withrecommendations from the NCHS. We excluded an additional1339 subjects who reported a history of tumor, congestive heartfailure, myocardial infarction, or stroke at the baseline visit.These subjects were also excluded from the subcohort.

STATISTICAL METHODSWe tested the assumption of proportionality by examining log-

log plots (log[2log(survival)] vs log of survival time) and usingSchoenfeld residuals after model fitting. All analyses met theassumptions of proportionality.

We accounted for the complex survey design of the NHEFS byincorporating strata and primary sampling units into our analyses.To account for oversampling of some populations in the fullcohort and ensure results are representative of the generalpopulation, we included sampling weights provided by NHANESin the analyses. However, because the incorporation of NHANESsample weights is controversial, we performed sensitivity ana-lyses with and without sample weights.E6,E7 Results were similarin analyses performed with and without the sampling weightsincorporated, and using the 1971-1975 visit or the 1982-1984visit as the start of follow-up (data not shown). The unweightedresults using the 1982-1984 survey as the start of follow-up arepresented.

Missing data and imputationMissing data for education, income, and smoking status at the

1982-1984 follow-up underwent multiple imputation usingchained equations.E8 Education, income, and smoking statuswere imputed on the basis of sex, age, race, asthma and emphy-sema history, and a derived variable indicating whether the sub-ject died before or after age 56 years, the age the youngestmembers of the cohort would be at the final follow-up time.

ADDITIONAL ANALYSES

Comparison of subjects selected for the subcohort

who did and did not have spirometry data availableBecause our point estimates for all-cause mortality associated

with asthmawere slightly different between the full cohort and thesubcohort (age-adjusted HR in the full cohort, 1.23; 95%CI, 1.07-1.42; age-adjusted HR in the subcohort, 1.07; 95%CI, 0.82-1.40),we compared the mortality risk in subjects selected to be in thesubcohort who did and did not have spirometry data available.Wefound that in models adjusted for age, sex, race, income, educa-tion, smoking status, and pack-years, subjects who completedspirometry were protected from all-cause mortality (HR, 0.84;95% CI, 0.76-0.93). We next examined whether there was aninteraction between asthma and spirometry performance on all-cause mortality, and we did not find that there was a significantinteraction between spirometry performance and asthma onmortality (P > .8 for Asthma3 Spirometry performance interac-tion). It is possible that in the subcohort, we are underpowered todetect the association between asthma and all-cause mortality.However, given that there are known differences between thefull cohort and the subcohort on whom spirometry data are avail-able (eg, the full cohort oversampled the elderly and those at riskfor malnutrition while the subcohort was considered nationallyrepresentative, and the subcohort with spirometry data is pro-tected from mortality compared with the subcohort withoutspirometry data), it is also possible that there are differences inthe relationship between asthma and all-cause mortality betweenthe 2 cohorts that we were unable to detect statistically.

Analysis of effect modificationWe explored whether there was evidence of effect modification

by age, sex, race, and smoking history on the association betweenasthma and mortality. We first generated interaction terms (eg,Asthma 3 Age) and included these in adjusted models. For age,we generated a dichotomous variable (<_/>40 years). We foundthat for respiratory mortality, there was a significant interactionbetween age and asthma on mortality in the full cohort, but not inthe subcohort, and that younger subjects with asthma have ahigher hazard of respiratory mortality than do older subjects withasthma. In the full cohort, inmodels adjusted for age, sex, income,education, race, and smoking status obtained at the 1982-1984survey (ever/never), the hazard ratio for asthma among those aged25 to 40 years was 5.88 (95% CI, 1.79-18.99). Among oldersubjects aged 41 to 75 years, the HR for asthmawas 2.04 (95%CI,1.36-3.08; P value for interaction of asthma and age5 .03). In thesubcohort, the adjusted HR for asthma among younger subjectswas 3.00 (95% CI, 0.19-47.80) and among older subjects it was2.00 (95% CI, 0.86-4.60; P value for interaction of asthma andage5 .48). Because the interaction was not identified in the sub-cohort, it is possible that the effect modification by age on respi-ratory mortality is explained by smoking, as more information onsmoking is available in the subcohort. We did not find evidencethat there was an interaction between sex, race, and smokinghistory and asthma on all-cause and respiratory outcomes.

ADDITIONAL INFORMATIONThe findings and conclusions in this article are those of the

authors and do not necessarily represent the views of the ResearchData Center, the NCHS, or the Centers for Disease Control andPrevention.

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REFERENCES

E1. Centers for Disease Control and Prevention. NHANES I epidemiologic followup

study. Available at: http://www.cdc.gov/nchs/nhanes/nhefs/nhefs.htm. Accessed

May 1, 2012.

E2. US Department of Commerce. Characteristics of the low income population:

1972. Bureau of the Census, Washington, DC: Series P-60, Number 88; 1973

E3. National Center for Health Statistics. Plan and operation of the Health and Nutri-

tion Examination Survey, United States, 1971-1973. Washington, DC: National

Center for Health Statistics; 1973.

E4. Hankinson JL, Odencrantz JR, Fedan KB. Spirometric reference values from a sam-

ple of the general U.S. population. Am J Respir Crit Care Med 1999;159:179-87.

E5. Pellegrino R, Viedi G, Brusasco V, Crapo RO, Burgos F, Casaburi R, et al.

Interpretative strategies for lung function tests. Eur Respir J 2005;26:948-68.

E6. Mannino DM, Buist AS, Petty TL, Enright PL, Enright SC. Lung

function and mortality in the United States: data from the First National

Health and Nutrition Examination Survey follow up study. Thorax 2003;

58:388-93.

E7. Ingram DD, Makuc DM. Statistical issues in analyzing the NHANES I Epidemi-

ologic Followup Study. Series 2: data evaluation and methods research. Vital

Health Stat 2 1994;1-30.

E8. White IR, Royston P, Wood AM. Multiple imputation using chained equations:

issues and guidance for practice. Stat Med 2011;30:377-99.

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FIG E1. Overall study design. NHANES I took place in 1971-1975. The NHEFS followed all individuals aged

25 years or older who had a medical examination at NHANES I. The NHANES I subcohort had additional

data collected including spirometry and detailed smoking history.

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TABLE E1. HRs for mortality according to asthma or allergic disease status within the full cohort (N 5 13,040)

Condition

Mortality

All-cause Cardiovascular Cancer Respiratory

Asthma

Age-adjusted hazard (95% CI) 1.23 (1.07-1.42)* 1.15 (0.93-1.41) 1.23 (0.92-1.60) 2.22 (1.47-3.35)*

Fully adjusted hazard (95% CI) 1.22 (1.06-1.40)* 1.13 (0.92-1.40) 1.23 (0.93-1.62) 2.28 (1.50-3.47)*

Food allergy

Age-adjusted hazard (95% CI) 0.90 (0.79-1.02) 0.85 (0.69-1.05) 0.73 (0.53-1.02) 1.17 (0.75-1.81)

Fully adjusted hazard (95% CI) 0.95 (0.82-1.12) 0.88 (0.70-1.11) 0.81 (0.58-1.13) 1.36 (0.87-2.13)

Hay fever

Age-adjusted hazard (95% CI) 0.97 (0.86-1.09) 0.87 (0.74-1.02) 0.96 (0.78-1.18) 1.09 (0.79-1.62)

Fully adjusted hazard (95% CI) 1.02 (0.90-1.15) 0.90 (0.77-1.06) 1.04 (0.84-1.28) 1.12 (0.78-1.61)

Full model adjusts for age, sex, income, education, race, and smoking status obtained at the 1982-1984 survey.

*Statistically significant (P < .05).

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