epidemiology and risk factors of infection in early childhood · risk factors in early childhood....

ARTICLE

Epidemiology and Risk Factors of Infection in Early ChildhoodNadja Hawwa Vissing, MD, PhD, Bo Lund Chawes, MD, DMSc, Morten Arendt Rasmussen, MSc, PhD, Hans Bisgaard, MD, DMSc

BACKGROUND: There is a large, unexplained variation in the frequency of childhood infections. We described incidence and risk factors of infections in early childhood.METHODS: Simple infections were captured during the first 3 years of life in the Copenhagen Prospective Studies on Asthma in Childhood 2000 birth cohort. Environmental exposures were analyzed by quasi-Poisson regression and sparse principal component analysis.RESULTS: The 334 children experienced a median of 14 (range 2–43) infectious episodes at ages 0 to 3 years. The overall rate of infections was associated with the number of children in the day care (adjusted incidence rate ratio [aIRR] 1.09 [1.2–1.16]) and the m2 per child in the day care (aIRR 0.96 [0.92–0.99]). Upper respiratory infections were also associated with the number of children in the day care (aIRR 1.11 [1.03–1.20]) and the m2 per child in the day care (aIRR 0.95 [0.91–0.99]), whereas lower respiratory infections were associated with caesarean section (aIRR 1.49 [1.12–1.99]), maternal smoking (aIRR 1.66 [1.18–2.33]), older siblings (aIRR 1.54 [1.19–2.01]), and the age at entry to day care (aIRR 0.77 [0.65–0.91]). The sparse principal component analysis revealed a risk factor profile driven by tobacco exposure, social circumstances, and domestic pets, but could only be used to explain 8.4% of the infection burden.CONCLUSIONS: Children experienced around 14 infections during the first 3 years of life, but incidences varied greatly. Environmental exposures only explained a small fraction of the variation, suggesting host factors as major determinants of infectious burden.

abstract

Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark

Dr Vissing handled the data, performed the descriptive statistics and the quasi-Poisson regression analysis, and wrote the first draft of the manuscript; Dr Chawes contributed to the analyses and interpretation of the data and critically reviewed and revised the manuscript; Dr Rasmussen performed the sparse principal component analysis and contributed considerably to the analyses and interpretation of the data; Dr Bisgaard was the guarantor of the study as a whole, from conception and design to conduct of the study and acquisition of data, data analysis, and interpretation of data. As the corresponding author, he had full access to the data and had final responsibility for the decision to submit for publication; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

DOI: https:// doi. org/ 10. 1542/ peds. 2017- 0933

Accepted for publication Feb 28, 2018

Address correspondence to Hans Bisgaard, MD, DMSc, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Ledreborg Alle 34, 2820 Gentofte, Denmark. E-mail: [email protected]

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2018 by the American Academy of Pediatrics

PEDIATRICS Volume 141, number 6, June 2018:e20170933

WHAT’S KNOWN ON THIS SUBJECT: Children experience numerous infections during childhood with a large and unexplained variation in individual susceptibility. Various environmental risk factors have been studied with inconsistent results, and few researchers have comprehensively investigated the entire exposome and its influence on childhood infections.

WHAT THIS STUDY ADDS: We found that only a minor fraction (8.4%) of the large variance in infection frequency between otherwise healthy children can be explained by environmental risk factors, suggesting that host factors are the major determinants of infection susceptibility in early childhood.

To cite: Vissing NH, Chawes BL, Rasmussen MA, et al. Epidemiology and Risk Factors of Infection in Early Childhood. Pediatrics. 2018;141(6):e20170933

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Children experience numerous simple infectious episodes, particularly in the first 3 years of life.1, 2 Although such infections are rarely fatal in industrialized countries, they have a considerable impact on childhood health, hospitalization rates, and quality of life and are a sizeable economic burden to society because of health care use, parental work absenteeism, and secondary infections of parents and siblings.3, 4

There is considerable variation in the frequency of simple infections between otherwise healthy children, 2, 3, 5 but there is limited data on epidemiology and risk factors in early childhood. Suspected risk factors include day care attendance, 1, 6 – 8 duration of breastfeeding, 9, 10 crowding in day care, 11 the presence of siblings, 3, 12 environmental tobacco exposure (ETS), 13 –15 indoor air pollution, 16 low socioeconomic status17 and male sex.18 However, there is a lack of reproducibility between studies, 19, 20 which complicates evidence-based preventive strategies. Furthermore, the authors of most previous studies only focus on single or few selected risk factors, despite the fact that many exposure variables are highly correlated.

Our objective with this study was to characterize the epidemiology of simple infections during the first 3 years of life in a longitudinal clinical birth cohort study with extensive assessment of early life exposures, aiming to identify a risk factor profile associated with incidence of infections.

METHODS

Study Cohort

The Copenhagen Prospective Study on Asthma in Childhood 2000 (COPSAC2000) is a longitudinal birth cohort study of 411 children born to asthmatic mothers with a

particular focus on asthma, allergy, and eczema as clinical outcomes along with a strong focus on infections as explanatory variables.21 Children born prematurely (<36 weeks of gestation), with severe congenital malformation or lower respiratory infection during the first month of life were excluded. In the first 3 years of life, the children attended the COPSAC2000 research clinic at 1 month of age and every 6 months thereafter for scheduled investigations as well as for acute care visits.21 The research clinic was de facto acting general practitioner for the children.

The study was approved by the Copenhagen Ethics Committee (KF01-289/96) and the Danish Data Protection Agency (2008-41-1754). Written and oral informed consent was obtained from both parents.

Infections

Infection burden was captured at the scheduled 6-monthly visit from birth until age 3 years and at additional acute care visits, where the COPSAC2000 pediatricians interviewed the parents about any illnesses, symptoms, duration, medication, and vaccinations since the last visit. Infections were classified according to the International Classification of Diseases, 10th Revision 22 and stored in a designated database. When needed, the physician added additional clinical information. In case of missed visits, the parents were interviewed at the subsequent visit on infectious episodes. For the current study, the International Classification of Diseases, 10th Revision 22 diagnoses were retrieved and grouped as follows:

I. Upper respiratory tract infections (URTIs): common cold, tonsillitis, pharyngitis, otitis media, and croup;

II. Lower respiratory tract infections (LRTIs): pneumonia and bronchiolitis;

III. Gastrointestinal infections (GIs): GI, diarrhea, and vomiting; and

IV. Isolated fever and other infections.

We analyzed the overall incidence of infections (the 4 groups combined) and the incidence rates of groups I, II, and III separately. Group VI comprised a heterogeneous group of infections without respiratory or gastrointestinal symptoms and was not analyzed as a separate outcome. Details on diagnoses can be found in Supplemental Information (Supplemental Table 5).

Source Data Validation

Source data validation was performed to evaluate the quality of data as previously published.23 Records from the COPSAC2000 database were compared with information recorded by the children’s general practitioner and revealed ˃90% completeness and no important influence from socioeconomics or concurrent asthma.

Risk Factors

A total of 84 environmental and constitutional risk factors were collected during the first 3 years of life. These risk factors include information on demographics, third trimester exposures, maternal infections during pregnancy, newborn characteristics, neonatal biomarkers, postnatal exposures, day care attendance, diet, indoor environment, and genetics21, 24 – 29 (Supplemental Table 6).

Statistics

First, we applied a quasi-Poisson regression model estimating unadjusted incidence rate ratios (IRRs) for the following 18 variables suspected to be associated with infection burden: sex, 18 birth weight and length, mode of delivery (vaginal or caesarean), 30 paternal

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asthma, maternal smoking during pregnancy, 13, 14 older siblings, 3, 5, 12 cats or dogs in the home, 31 household income, 17, 18 the mother’s occupation and level of education, 17 duration of breastfeeding, 9, 10 day care attendance1, 6 – 8, 11 (age at introduction, number of children, and m2 per child in the day care), and ETS assessed by nicotine concentration in the child’s hair at ages 1 and 3 years.32 These variables were selected a priori on the basis of literature to reduce the risk of multiple testing. The quasi-Poisson model was used to account for overdispersion in the data. Thereafter, we performed an adjusted quasi-Poisson regression analysis including risk factors with a P value ˂.20, estimating adjusted incidence rate ratios (aIRRs). In the adjusted analysis, some variables were closely correlated (ie, smoking during pregnancy and ETS, birth weight and birth length, and socioeconomic variables), and, in these cases, only 1 variable was included for adjustment to avoid collinearity (see Supplemental Information for clarification). We performed a stratified analysis on the basis of a diagnosis of asthma at any time point before age 3 years.

Secondly, we applied an unsupervised data-driven sparse principal component analysis (SPCA)33, 34 to explore common underlying patterns from the entire set of variables from the COPSAC2000 database without a priori hypotheses on association to infections (ie, a total of 84 descriptive covariates) (Supplemental Table 6). SPCA is a modification of the multivariate technique principal component analysis (PCA). Further details can be found in the Supplemental Information. The SPCA patterns were used as input variables in a forward stepwise Poisson regression for the prediction of incidence of infections.

The quasi-Poisson regression analyses were performed in SAS (SAS Institute,

Inc, Cary, NC) version 9.3 and R version 2.12.0. The SPCA analyses were performed in MatLab version R2016b by the algorithm available on http:// models. life. ku. dk/ sparsity. 34

RESULTS

Baseline Characteristics

Children who missed 2 or more successive 6-monthly scheduled visits were excluded from the analysis leaving 334 (81%) of the 411 children eligible for analysis. Children in the study group were significantly more often born by caesarean delivery, exposed to a cat at home, attended more crowded day cares, and came from families with higher household incomes but were less exposed to maternal smoking during pregnancy (Table 1). A total of 327 (98%) children were fully vaccinated according to the national immunization program (Supplemental Table 7).

Simple Infection Burden

A total of 5009 infections were reported among the 334 children (Fig 1A), yielding a median incidence rate of 14 infections per child (mean 15; range 2–43; interquartile range (IQR) 10–18). Respiratory tract infections were most frequent with a median of 10 episodes per child, corresponding to 71% of all infections (9 episodes per child for URTI and 1 episode per child for LRTI) (Table 2).

With Figure 1B, we show the incidence rates of infections at ages 0 to 3 years, illustrating an incidence peak around age 1 year with a slight decline in the third year of life. Figure 1C reveals the seasonal variation in incidence rates with respiratory tract infections being more common in the winter, whereas fever and gastroenteritis had less seasonal variation.

Duration of Infections

Table 2 reveals the mean durations of infectious episodes for each category.

Median duration of all infectious episodes was 6 days (IQR 3–8), which decreased with increasing age (IRR per year 0.94 [0.90–0.97]; P = .001). The same inverse association between disease duration and age was seen for URTI (IRR 0.96 [0.92–1.00]; P = .057), LRTI (IRR 1.10 [0.87–0.94]; P = .02), and GI (IRR 0.84 [0.73–0.96]; P = .01), whereas the duration of isolated fever increased with age (IRR 1.10 [1.02–1.19]; P = .02).

The median number of days with infection throughout the 3-year study period was 94 days (IQR 64–132), in which the majority of days were caused by URTI (62 days [IQR 40–97]) (Table 2).

Antibiotics

Antibiotics were administered in 24.9% of the infectious episodes (87.7% of LRTI episodes, 23.1% of URTI episodes, 12.5% of isolated fever episodes, and 10.2% of GI episodes). The most frequently used drug was amoxicillin (59.4%) followed by penicillin (27.9%) (Fig 2, Supplemental Table 8).

Quasi-Poisson Regression Risk Factor Analysis

Overall Rate of Infections

The only risk factors significantly related to the overall incidence of infections was crowding in day care, measured as m2 per child in the day care (aIRR per IQR: 0.96 [0.92–0.99]; P = .04), meaning that children in day care centers with m2 per child in the lower quartile had 4% fewer infections than those in the upper quartile (Table 3). Also, the total number of children in the day care was associated with increased incidence of infections (aIRR 1.09 [1.02–1.16]; P = .01), meaning that children attending day care with the number of children in the upper quartile experienced 9% more infections than those in the lower quartile.

URTIs

The same associations were seen for crowding in day care, in which the

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m2 per child was inversely associated with incidence of URTI (aIRR per IQR 0.95 [0.91–1.00]; P = .048), and the total number of children in the day care was associated with increased incidence of URTI (aIRR 1.11 [1.03–1.20]; P = .01). We observed no other significant associations.

LRTIs

Risk factors associated with incidence of LRTI were caesarean delivery (aIRR 1.49 [1.12–1.99]; P = .01), maternal smoking during pregnancy (aIRR 1.66 [1.18–2.23]; P < .005), and the presence of older siblings (aIRR 1.54

[1.19–2.01]; P < .005), whereas an older age at the introduction to day care was inversely associated with LRTI incidence (aIRR per IQR 0.77 [0.65–0.91]; P < .005). A subanalysis on the effect of the age of the youngest older siblings revealed a tendency toward the sibling effect declining with the age of the youngest older sibling; however, this decline was not statistically significant (P = .40). Male sex was associated with borderline significance (aIRR 1.29 [1.00–1.68]; P = .052).

GIs

No significant associations were found.

Children diagnosed with persistent wheeze and/or asthma before age 3 years had the same infection burden as the remaining children, except they had a higher number of LRTIs (IRR 2.97 [2.36–3.75]; P < .001). Excluding children with persistent wheeze and/or asthma yielded the same risk factor profile for LRTIs (Supplemental Table 9).

SPCA Multiparametric Risk Factor Pattern Analysis

The 84 environmental and constitutional covariates were decomposed into 11 underlying latent risk factor patterns called components.

VISSING et al4

TABLE 1 Baseline Characteristics

Study Population Excluded From Analysis

Categorical: n (%); Numeric: Mean (IQR)

Missing Data Categorical: n (%); Numeric: Mean (IQR)

Missing Data

Excluded Compared With the Study Populationa

ChildrenBoys (yes or no) 164 (49) 0 39 (51) 0 .81Pregnancy and birthBirth wt, kg 3.51 (0.63) 0 3.52 (0.57) 0 .87BMI at birth 12.8 (1.75) 0 12.8 (1.72) 0 .90Caesarean delivery (yes or no) 78 (23) 0 7 (9) 0 P = .005Early exposuresOlder children in household at 1 y (yes

or no)138 (41) 0 14 (27) 26 .06

Duration of breastfeeding, mo 0 16 P = .005 0–3 31 (9) 12 (20) 3–6 76 (23) 20 (33) >6 227 (67) 29 (48)Maternal smoking during pregnancy (yes

or no)43 (13) 0 20 (26) 0 P = .004

Nicotine level in hair at 1 y (ng/mg) 3.3 (2.1) 14 3.0 (4.4) 29 .73Nicotine level in hair at 3 y (ng/mg) 2.0 (0.9) 24 2.2 (0.6) 65 .91Day careAge at start, d 372 (186) 7 383 (189) 26 .74No. children in day care 29 (41) 12 16.9 (11) 33 P = .002Space per child, m2 13 (11) 14 9.7 (6.9) 34 .08Indoor environmentCat at home at birth (yes or no) 44 (13) 3 16 (25) 12 P = .02Dog at home at birth (yes or no) 49 (15) 3 5 (8) 12 .13Socioeconomic variablesHousehold annual income, 100 000 DKR 5.09 (2.4) 1 3.96 (2.0) 25 P < .001Mother’s education 2 32 .70 College or lower level 199 (60) 26 (58) Medium length 89 (27) 11 (25) University 44 (13) 8 (18)Mother’s employment 112 (34) 0 29 .17 Nonprofessional 112 (34) 16 (33) Professional 156 (47) 18 (38) Student 37 (12) 5 (10) Unemployed 29 (9) 9 (19)Atopic dispositionFather with asthma 60 (18) 9 8 (11) 3 .11

DKR, Danish kroner.a Calculated by χ2 test for categorical risk factors and student’s t test for numerical risk factors.



Supplemental Figure 3 reveals the key covariates driving each component and the percentage of the total variance that each component accounts for. In total, the 11 components could only be used to explain 44% of the overall data variation.

Table 4 reveals the association between the components and incidence of infections. Only component 1 was significantly associated with the overall incidence of infections (IRR per IQR 0.91 [0.86–0.97]; P = .003), but the component could only be used to

explain 8.4% of the variation in the data. Described in component 1 was a pattern primarily driven by measures of ETS, combined with socioeconomics, indoor air pollution, and pets (Supplemental Fig 3). Unexpectedly, lower levels of ETS were associated with increased incidence of infections. Component 1 was also associated with incidence of URTI (IRR per IQR 0.93 [0.86–0.99]; P = .03), and there was a trend toward an inverse association between component 1 and incidence of LRTI (IRR per IQR

1.15 [0.99–1.34]; P = .06), meaning that higher levels of ETS increased risk of LRTI.

Component 4 was significantly associated with LRTI (IRR per IQR 0.83 [0.70–0.98]; P = .03). This component was primarily driven by breastfeeding, both the duration of solely breastfeeding and any breastfeeding. Component 8 was significantly associated with both LRTI (IRR per IQR 0.78 [0.66–0.92]; P = .004) and GI (IRR per IQR 0.85 [0.74–0.98]; P = .03). This component was primarily driven by furred pets and 17q21 polymorphisms. Excluding asthmatic children from the analysis did not alter the results.

DISCUSSION

Main Findings

This prospective Danish birth cohort study revealed that otherwise healthy children experienced a median of 14 simple infectious episodes throughout the first 3 years of life (mean 15; IQR 10–18; range 2–43) with substantial variation in frequency between individuals.

Only crowding in day care had a significant but modest influence on the overall incidence of infections and incidence of URTI, whereas LRTI incidence was associated with maternal smoking, caesarean delivery, older siblings, and early day care attendance. When including 84 environmental and constitutional covariates with an explorative SPCA approach, we were only able to describe 8.4% of the large variance in infection frequency. With these findings, we suggest that host factors are the major determinants of infection susceptibility in early childhood.

Strengths and Limitations

The strength of our study is the close longitudinal prospective clinical surveillance at the COPSAC2000 clinical research unit that included 3 years of follow-up and a total

PEDIATRICS Volume 141, number 6, June 2018 5

FIGURE 1Burden of infections. A, Distribution of burden of infections per child. B, Burden of infections over time. C, Seasonal variation. RTI, respiratory tract infection.





observation of 365 730 days. The study is a single-center study with 6 monthly assessments conducted by experienced study pediatricians who examined the children and obtained their clinical history that was supported by daily diary cards. Through this, data capture was secured and the risk of misclassification was reduced. We previously validated our data with records from children’s general practitioners23 and showed good data capture with sensitivity ˃90%.

Highly detailed assessment of the exposome is a key feature of the COPSAC2000 study, including information on a wide range of environmental and constitutional risk factors collected prospectively, combining interview data with objective measurements.21

It is an advantage that, with our study, we combine traditional inferential statistical methods with an unsupervised data-driven analysis. The quasi-Poisson regression analysis reveals if a single risk factor is significantly associated with higher infection rate but does not reveal whether a pattern comprising several risk factors carries the relevant information. Many exposure variables are correlated, and a multiparametric approach is therefore needed, such as the SPCA, which can be used to handle an underlying correlation structure. Furthermore, the SPCA approach overcomes the issue of multiple testing in unidirectional analyses. Using this method, we were able to consider the high number of exposure variables available in our cohort study without a priori selection of risk factors.

It is a limitation that the selection of collected variables is driven by the cohort’s focus on atopic diseases, and a cohort study in which childhood infections are primarily addressed would possibly include other variables. However, few such studies have been conducted, 2, 3, 5, 11 and all

VISSING et al6

TABL

E 2

Burd

en o

f Inf

ectio

ns: I

ncid

ence

and

Dur

atio

n of

Infe

ctio

us E

piso

des

in 3

34 C

hild

ren

Tota

l No.

Ep

isod

esIn

cide

nce

of In

fect

ions

Per

Chi

ldNo

. of D

ays

With

Infe

ctio

n Pe

r Ch

ildDu

ratio

n of

Infe

ctio

ns, D

ays

Med

ian

Mea

nIQ

RM

edia

nM

ean

IQR

Med

ian

Mea

nIQ

R

All i

nfec

tions

, y

0–3

5009

1415

.0(1

0–18

)94

103.

2(6

4–13

2)6

6.9

(3–8

)

0–1

1451

44.

3(2

–6)

2632

.2(1

4–44

)6

7.4

(3–8

)

1–2

1985

55.

9(3

–8)

3440

.5(2

0–53

)6

6.8

(3–8

)

2 –3

1573

44.

7(2

–6)

2530

.5(1

4–40

)5

6.5

(3–8

)UR

TI, y

0–

331

529

9.4

(6–1

2)62

74.3

(40–

97)

78.

2(4

–9)

0–

198

93

3.0

(1–4

)19

24.1

(8–3

1)7

8.2

(4–9

)

1–2

1214

33.

6(2

–5)

2028

.9(1

0–40

)7

7.9

(5–8

)

2–3

949

22.

8(1

–4)

1521

.3(7

–28)

67.

5(4

–8)

LRTI

, y

0–3

399

11.

2(0

–2)

510

.1(0

–15)

89.

8(6

–12)

0–

111

00

0.3

(0–0

)0

3.2

(0–0

)8

9.8

(6–1

2)

1–2

162

00.

5(0

–1)

04.

0(0

–7)

88.

3(6

–10)

2–

312

70

0.4

(0–0

)0

2.8

(0–0

)7

7.4

(5–9

)Fe

ver

(iso

late

d), y

0–

388

92

2.7

(1–4

)9

10.9

(3–1

5)3

3.7

(1–5

)

0 –1

213

00.

6(0

–1)

02.

3(0

–3)

33.

7(1

–5)

1 –

237

51

1.1

(0–2

)2

4.5

(0–7

)3

4.0

(2–5

)

2 –3

301

10.

9(0

–1)

14.

0(0

–7)

34.

4(2

–7)

GI, y

0–

356

91

1.7

(0–3

)4

8(0

–12)

46.

0(2

–8)

0–

113

90

0.4

(0–1

)0

2.5

(0–2

)4

6.0

(2–8

)

1–2

234

00.

7(0

–1)

03.

1(0

–4)

34.

4(1

–6)

2–

319

60

0.6

(0–1

)0

2.4

(0–2

)2

4.2

(1–5

)


include less risk factors compared with this study.

The generalizability of our findings can be questioned because of the high risk of asthma in the cohort. Children at high risk of developing asthma and wheezy symptoms may experience more infections than nonwheezing children, 35 which could lead to an overestimation of population disease incidence in this cohort. Still, we would not expect this to affect the observed wide variation of infections within the cohort or the influence of risk factors. Furthermore, a sensitivity analysis excluding children with persistent wheeze and/or asthma yielded similar results.

Interpretation

With this unparalleled comprehensive risk factor analysis, in which we use both traditional statistics and SPCA pattern recognition analysis, we confirm the lack of evident and reproducible associations between simple childhood infections and exposure-related risk factors. These findings reveal that host factors rather than the exposome account for the variation in frequency of infections in early childhood.

The authors of previous studies have reported that day care attendance is associated with increased risk

of respiratory tract infection especially during the first years of life, 2, 7, 36 but the authors of studies with longitudinal follow-up have questioned whether the increased symptom burden continues later in childhood.8, 37, 38 We confirmed a modest influence from attendance to crowded day care facilities, reflected as a 9% increase in overall incidence of infections and an 11% increase in URTIs among children attending day care with crowding in the upper quartile compared with the lower. Likewise, we saw a 4% reduction in overall incidence of infections and a 5% reduction in URTIs per IQR of available space per child in the day care. The effect of day care is presumably caused by an increased disease transmission.

Children with older siblings have been suggested to suffer from more respiratory infections than first-born children, 39 but it has also been proposed that children with older siblings experience an earlier immune maturation12 and a subsequent improved resistance against infections later in childhood. We found that having siblings at home increased the risk of LRTIs by 54% but had no influence on the incidence of overall infections, URTIs, or GIs.

Boys are expected to have an increased risk of respiratory

infections, particularly LRTI.39, 40 We found a tendency toward increased incidence of LRTIs, but there was no apparent association between sex and other types of infections.

ETS, estimated both by maternal smoking during pregnancy and by nicotine level in the child’s hair, was associated with increased frequency of LRTIs, and, although not statistically significant, the SPCA analysis supported the positive association between ETS and incidence of LRTI, which aligns with other reports.13 We previously showed that children exposed to tobacco smoke in utero exhibit a deficit in lung function at birth, 41, 42 which could make them more prone to LRTIs. There was no association between URTI and ETS in the univariate analysis, and, surprisingly, the SPCA pointed toward a protective effect of ETS, which could be a false discovery. The lack of association is in fact in line with other prospective studies, 2 supporting the role of ETS as a trigger of lower respiratory symptoms, such as cough and wheeze, but not enhancing the susceptibility to infections per se.

Cesarean delivery was associated with a 49% increased incidence of LRTI. The authors of a previous epidemiologic birth cohort study conducted in Norway on the basis of questionnaires filled out by 37 101 mothers were unable to find a significant association, 30 but, although not statistically significant, all of their results pointed toward an increased risk of recurrent LRTI within the first 3 years of life after caesarean delivery. The mechanism behind this association is unclear. It could be a reflection of other risk factors influencing the likelihood of a caesarean delivery, but it might be that children born by vaginal delivery are exposed to a diverse microbiological flora from the birth canal43 and that subsequent colonization of gut and airways alters immune modulation44 and susceptibility to LRTI.45


FIGURE 2Antibiotic treatment. The percentage of infections treated with antibiotics is shown.


VISSING et al8

TABL

E 3

Asso

ciat

ion

Betw

een

Risk

Fac

tors

and

Dis

ease

Inci

denc

e Du

ring

the

Firs

t 3 Y

ears

of L

ife

Any

URTI

LRTI

GI

Crud

eAd

just

edCr

ude

Adju

sted

Crud

eAd

just

edCr

ude

Adju

sted

IRR

PIR

RP

IRR

PIR

RP

IRR

PIR

RP

IRR

PIR

RP

Prob

ands

Bo

ys (

yes

or n

o)1.

07.1

61.

07.2

01.

05.4

61.

03.6

11.

27.1

01.

29.0

520.

96.7

50.

99.9

3Pr

egna

ncy

and

birt

h

Birt

h w

t, kg

0.99

.66

0.97

.27

1.02

.50

0.93

.17

0.89

.15

0.94

.46

0.91

.20

0.87

.07

Bi

rth

leng

th, c

m1.

04.1

81.

03.3

71.

07.0

91.

06.1

30.

91.2

81.

05.6

81.

02.7

51.

00.9

7

Caes

area

n de

liver

y (y

es o

r no

)1.

07.2

81.

09.1

81.

04.5

61.

06.4

01.

36a

.04a

1.49

a.0

1a1.

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Pets at home, namely dogs, have been found protective of respiratory tract infection in early childhood.31 We did not find univariate association between pet exposure and incidence of infections, but, with the SPCA, we pointed toward an increased overall incidence of infections for children with furred pets in the home, both cat and dog. Furthermore, pet exposure in combination with certain wheeze-related genotypes (17q21) was related to incidence of both LRTI and GI, but, in this setting, dog exposure increased the number of LRTIs and GIs, whereas cat exposure seemed to protect. The lack of clear and reproducible results underlines the complexity of these environmental exposures.

The burden of infections could be associated with vaccination status. However, vaccination rates were high in our study, and we were unable to address influence from vaccines. The children were vaccinated according to the Danish immunization schedule at the time of the study (diphtheria-tetanus toxoids-pertussis-polio, Haemophilus influenzae type b, and measles-mumps-rubella; Supplemental Table 7). Since then, vaccination for several other pathogens, including Pneumococcus, Meningococcus, rotavirus, and varicella-zoster virus are being implemented in many countries. It is a subject for authors of future studies to explore whether these vaccines

reduce the incidence of childhood infections in industrialized countries, either through specific protection or through nonspecific immune-modulatory effects.46

The most notable finding is that so few of so many suspected risk factors contributed substantially to the variation in incidence of infections, particularly the overall incidence and incidence of URTI and GI. This lack of evident and reproducible associations between simple childhood infections and various exposure-related risk factors is in agreement with other studies, 5, 19 suggesting that unidentified host factors are the major determinants of the highly variable infection burden in young children. Therefore, authors of future studies should search for alternative explanations of disease patterns presumably through a systems biology omics approach including other areas such as functional immunology, genetics, dietary patterns, microbiome, and inflammatory responses early in life.

CONCLUSIONS

Children experienced a median of 14 simple infections during the first 3 years of life, with 71% being respiratory infections. Individual variation in disease frequency for all infections and URTIs was associated with crowding in day

care, and LRTI was associated with day care attendance, ETS, caesarean delivery, duration of breastfeeding, and having older siblings at home. However, these risk factors explained only a small fraction (8.4%) of the interindividual variation in incidence of infections, suggesting that host factors are the major determinants.

ACKNOWLEDGMENTS

We thank the children and families of the COPSAC2000 cohort study for all their support and commitment. We acknowledge and appreciate the unique efforts of the COPSAC2000 research team.

ABBREVIATIONS

aIRR: adjusted incidence rate ratioCOPSAC2000: Copenhagen

Prospective Studies on Asthma in Childhood 2000

ETS: environmental tobacco exposure

GI: gastrointestinal infectionIQR: interquartile rangeIRR: incidence rate ratioLRTI: lower respiratory tract

infectionPCA: principal component analysisSPCA: sparse principal

component analysisURTI: upper respiratory tract

infection


TABLE 4 Results of the SPCA: Associations Between Components and Infections

Component Explanatory fraction, %

All infections RTI LRTI URTI GI

IRR Per IQR (95% CI)

1 8.4 0.91 (0.86–0.97)a 0.95 (0.89–1.01) 1.15 (0.99–1.34) 0.93 (0.86–0.99)a 0.92 (0.80–1.07)2 6.9 0.97 (0.91–1.05) 0.96 (0.90–1.04) 1.02 (0.84–1.24) 0.96 (0.88–1.04) 0.99 (0.84–1.17)3 4.2 1.03 (0.96–1.10) 1.02 (0.95–1.09) 1.14 (0.95–1.37) 1.00 (0.93–1.09) 1.02 (0.87–1.20)4 4.0 0.94 (0.88–1.00) 0.97 (0.91–1.04) 0.83 (0.70–0.98)a 0.99 (0.92–1.07) 0.87 (0.75–1.01)5 3.7 1.02 (0.97–1.07) 1.03 (0.98–1.09) 0.91 (0.79–1.05) 1.05 (0.99–1.11) 0.97 (0.86–1.10)6 3.6 1.02 (1.00–1.04) 1.02 (1.00–1.04) 1.02 (0.96–1.08) 1.02 (1.00–1.04) 1.01 (0.97–1.06)7 3.2 1.02 (0.96–1.08) 1.02 (0.96–1.08) 1.18 (1.00–1.41) 1.00 (0.94–1.07) 1.03 (0.90–1.19)8 2.9 0.97 (0.91–1.03) 0.98 (0.92–1.05) 0.78 (0.66–0.92)a 1.01 (0.94–1.09) 0.85 (0.74–0.98)a

9 2.5 1.00 (0.93–1.08) 1.04 (0.96–1.12) 1.14 (0.94–1.39) 1.02 (0.94–1.11) 0.95 (0.80–1.12)10 2.5 1.05 (0.99–1.11) 1.06 (0.99–1.13) 1.12 (0.94–1.32) 1.05 (0.98–1.13) 1.10 (0.95–1.26)11 2.4 1.07 (0.98–1.16) 1.06 (0.97–1.16) 1.11 (0.89–1.39) 1.05 (0.96–1.16) 0.95 (0.79–1.16)Total 42 — — — — —

Estimates are presented as IRR per IQR of the component. IQR, interquartile range; —, not applicable.a Indicates significant associations.



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FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

FUNDING: Funded by the Copenhagen Prospective Studies on Asthma in Childhood 2000, which is listed on www. copsac. com. The Lundbeck Foundation (grant R16-A1694), the Ministry of Health (grant 903516), the Danish Council for Strategic Research (grant 0603-00280B), and the Capital Region Research Foun dation have provided core support to the Copenhagen Prospective Studies on Asthma in Childhood 2000 research center.

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.


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