Skip to main content
NCBI home page
Environmental Health Perspectives logoLink to Environmental Health Perspectives
. 2011 Jul 21;119(11):1647–1652. doi: 10.1289/ehp.1003253

Stress during Pregnancy and Offspring Pediatric Disease: A National Cohort Study

Marion Tegethoff 1,2,3, Naomi Greene 4, Jørn Olsen 4,5, Emmanuel Schaffner 6,7,8, Gunther Meinlschmidt 2,7,9,✉
PMCID: PMC3226491  PMID: 21775267

Abstract

Background: Identifying risk factors for adverse health outcomes in children is important. The intrauterine environment plays a pivotal role for health and disease across life.

Objectives: We conducted a comprehensive study to determine whether common psychosocial stress during pregnancy is a risk factor for a wide spectrum of pediatric diseases in the offspring.

Methods: The study was conducted using prospective data in a population-based sample of mothers with live singleton births (n = 66,203; 71.4% of those eligible) from the Danish National Birth Cohort. We estimated the association between maternal stress during pregnancy (classified based on two a priori–defined indicators of common stress forms, life stress and emotional stress) and offspring diseases during childhood (grouped into 16 categories of diagnoses from the International Classification of Diseases, 10th Revision, based on data from national registries), controlling for maternal stress after pregnancy.

Results: Median age at end of follow-up was 6.2 (range, 3.6–8.9) years. Life stress (highest compared with lowest quartile) was associated with an increased risk of conditions originating in the perinatal period [odds ratio (OR) = 1.13; 95% confidence interval (CI): 1.06, 1.21] and congenital malformations (OR=1.17; CI: 1.06, 1.28) and of the first diagnosis of infection [hazard ratio (HR) = 1.28; CI: 1.17, 1.39], mental disorders (age 0–2.5 years: HR = 2.03; CI: 1.32, 3.14), and eye (age 0–4.5 years: HR = 1.27; CI: 1.06, 1.53), ear (HR = 1.36; CI: 1.23, 1.51), respiratory (HR = 1.27; CI; 1.19, 1.35), digestive (HR = 1.23; CI: 1.11, 1.37), skin (HR = 1.24; CI: 1.09, 1.43), musculoskeletal (HR = 1.15; CI: 1.01–1.30), and genitourinary diseases (HR = 1.25; CI; 1.08, 1.45). Emotional stress was associated with an increased risk for the first diagnosis of infection (HR = 1.09; CI: 1.01, 1.18) and a decreased risk for the first diagnosis of endocrine (HR = 0.81; CI; 0.67, 0.99), eye (HR = 0.84; CI; 0.71, 0.99), and circulatory diseases (age 0–3 years: HR = 0.63; CI: 0.42, 0.95).

Conclusions: Maternal life stress during pregnancy may be a common risk factor for impaired child health. The results suggest new approaches to reduce childhood diseases.

Keywords: antenatal stress, child health and development, intrauterine exposure, prenatal exposure delayed effects, prenatal programming, psychosocial stress

Early-life factors can predispose individuals to diseases over the life course (Gluckman et al. 2008). Follow-up studies have shown that fetal growth impairment is linked to an increased risk of morbidity and premature mortality (Barker et al. 1993; Forsen et al. 2000). However, fetal growth is probably only a crude indicator of complex developmental processes that are subject to genetic factors and various intrauterine exposures that may affect gene expression and influence disease susceptibility. Therefore, the effects of intrauterine exposures on postnatal outcomes should be studied more directly (Gillman 2002), and the National Institutes of Health and the World Health Organization (WHO) have advised that the role of maternal stress during pregnancy should be given high research priority (National Institutes of Health 2003; WHO 2006). Follow-up studies have raised concerns that offspring of mothers exposed to stress during pregnancy may have an increased risk of specific diseases such as malformations, asthma, and mental and behavioral disorders (Cookson et al. 2009; Hansen et al. 2000; O’Connor et al. 2002). However, a comprehensive study covering a larger spectrum of diseases is needed.

The purpose of this study was to assess the association between common psychosocial stress during pregnancy and the risk of a wide range of offspring diseases in a population-based birth cohort with prospective data linked with a national hospital register. The decision to give an overview of a broad range of diseases accounts for the large body of evidence linking maternal adversities with changes in numerous physiological systems in the offspring (Entringer et al. 2008; Field et al. 2002; Lin et al. 2004; Monk et al. 2004, 2011; O’Connor et al. 2005).

Methods

Study cohort. This study is based on prospective data from the Danish National Birth Cohort, including births between 1996 and 2003 (Olsen et al. 2001). Participants gave written informed consent, and the Danish National Committee for Biomedical Research Ethics, Copenhagen, approved the study on behalf of all committees in the country. About 50% of all general practitioners in the country took part in the recruitment, and 60% of the invited women participated. Of these, we considered as eligible all pregnancies with live singleton births (see “Results”).

Stress exposure. We obtained information on maternal stress from a telephone interview taken around 30 weeks of gestation. We studied two a priori–defined types of stress—emotional stress and life stress—as used in previous studies (Sondergaard et al. 2003; Tegethoff et al. 2010a, 2010b). The separation of these two types of maternal stress is theoretically based on the well-described stressor specificity of biological responses, which may differentially affect the fetus (Pacak and Palkovits 2001; Richardson et al. 2006). Virtually all available studies investigating maternal stress have used one of these two types of stress measures (Beydoun and Saftlas 2008; Lobel 1994). The applied instruments were developed to be feasible in a large cohort study. Emotional stress and life stress were each assessed by nine questions, each covering the time period since the beginning of pregnancy. Answers (no = 0, a little = 1, a lot = 2) were added up into a score for each stress type (range, 0–18). The scale for emotional stress covers self-reported feelings (e.g., anxiety, nervousness; for detailed description of items, see Table 1). Items were selected from the Symptom Check List-90 (Derogatis 1977) and The General Health Questionnaire (Goldberg 1972) to cover frequent symptoms of anxiety and depression. Life stress was assessed using an inventory based on the major categories of the Life Events Questionnaire (Norbeck 1984) on whether the women felt burdened in major areas of life such as work, housing, and human relations (for detailed description of items, see Table 1). For additional information on scale validation, see Supplemental Material, Additional Methods 1 (http://dx.doi.org/10.1289/ehp.1003253). We addressed up to two missing answers per stress type by using person-specific mean substitution. Women with more than two missing answers were excluded. In the analyses, we included life stress and emotional stress as categorical independent variables, with the limits between the categories defined by cutoffs as close as possible to the quartiles of the distributions of the respective stress scores (Table 2). Even though some overlap of emotional stress and life stress was expected, a low correlation between these constructs (Spearman rho correlation: r = 0.46; p < 0.001) affirmed their discriminant validity. To account for overlap, the analysis of the associations between life stress and child diseases was adjusted for emotional stress, and vice versa.

Table 1.

Items used to assess life stress and emotional stress.

Life stress Emotional stress
Have you felt burdened during pregnancy by any of the things I am going to ask now. You may answer: no, a little, or a lot. Now I am going to ask you how you have been feeling during pregnancy. You may answer: no, a little, or a lot.
Have you been burdened by . . . Have you felt . . .
1. . . . financial circumstances? 1. . . . scared for no reason?
2. . . . your housing situation? 2. . . . hopeless about the future?
3. . . . your work situation? 3. . . . constantly under strain?
4. . . . the relationship to your partner? 4. . . . nervous or shaky inside?
5. . . . relationships to family and friends? 5. . . . blue?
6. . . . your pregnancy? 6. . . . easily annoyed or irritated?
7. . . . own diseases? 7. . . . that everything was an effort?
8. . . . disease of your partner, family members, or close friends? 8. . . . tense or keyed up?
9. . . . other things? 9. . . . that everything was getting on top of you?
Open in a new tab

Table 2.

Sample characteristics (n = 66,203).

Characteristic n (%)a
Maternal age (years)
< 27 13,614 (20.6)
27–29 17,880 (27.0)
30–32 16,517 (25.0)
> 32 18,192 (27.5)
Parity
Primiparous 29,574 (44.7)
Multiparous 34,240 (51.7)
Unknown 2,389 (3.6)
General maternal health
Very good 33,454 (50.5)
Average 28,114 (42.5)
Bad 2,263 (3.4)
Unknown 2,372 (3.6)
Socioeconomic status
High 32,627 (49.3)
Medium 23,299 (35.2)
Low 5,220 (7.9)
Unknown 5,057 (7.6)
Infant sex
Male 33,779 (51.0)
Female 32,424 (49.0)
Hypertension during pregnancy
Yes 8,824 (13.3)
No 57,192 (86.4)
Unknown 187 (0.3)
Gestational diabetes
Yes 1,632 (2.5)
No 64,225 (97.0)
Unknown 346 (0.5)
Smoking
Yes 17,020 (25.7)
No 47,255 (71.4)
Unknown 1,928 (2.9)
Maternal life stress during pregnancyb (score)
Low (0) 19,793 (29.9)
Low-medium (> 0 to ≤ 1) 14,488 (21.9)
Medium-high (> 1 to ≤ 3) 20,377 (30.8)
High (> 3) 11,545 (17.4)
Maternal emotional stress during pregnancyb (score)
Low (≤ 1) 25,083 (37.9)
Low-medium (> 1 to ≤ 2) 11,432 (17.3)
Medium-high (> 2 to ≤ 4) 15,971 (24.1)
High (> 4) 13,717 (20.7)
Maternal life stress after pregnancyb (score)
Low (0) 32,296 (48.8)
Low-medium (> 0 to ≤ 1) 13,829 (20.9)
Medium-high (> 1 to ≤ 2) 9,725 (14.7)
High (> 2) 10,353 (15.6)
Maternal emotional stress after pregnancyb (score)
Low (0) 22,313 (33.7)
Low-medium (> 0 to ≤ 1) 12,557 (19.0)
Medium-high (> 1 to ≤ 3) 15,847 (23.9)
High (> 3) 15,486 (23.4)
aPercentages may not total 100 because of rounding. bStress groups were defined by the closest possible cutoffs to the quartiles of their distribution.
Open in a new tab

Outcome measures. Information on children’s diseases was derived from the Danish National Hospital Register (Copenhagen, Denmark), which contains information on all inpatients and outpatients in Danish hospitals and provides reporting of diagnoses, the validity of which has been demonstrated for several diseases (Andersen et al. 1999; Christensen et al. 2007; Moth et al. 2007; Sorensen and Larsen 1994; Vestergaard et al. 2006). All hospital diagnoses, based on the Danish version of the International Classification of Diseases, 10th Revision (ICD-10) (Danish National Board of Health 1993), were divided into major diagnostic categories (dichotomous) selected a priori according to chapters 1–14 and 16 and 17 of the ICD-10, which cover all relevant diagnoses during childhood. Additionally, we used a dichotomous overall category (“any disease”), indicating whether any disease in any of the categories had been diagnosed [see Supplemental Material, Table 1 (http://dx.doi.org/10.1289/ehp.1003253) for details concerning the major diagnostic categories and numbers of diagnoses for specific outcomes within each category in the study cohort].

Statistical analyses. We used the Wilcoxon signed-rank test to compare the score reflecting maternal stress during pregnancy with the score reflecting maternal stress after pregnancy for each stress type.

For conditions that may have onset after the perinatal period (diagnostic categories 1–14) and for “any disease,” we estimated the associations of maternal life stress and emotional stress during pregnancy with the risk of the offspring for the first diagnosis of a disease within each major diagnostic category by conducting separate Cox proportional hazards regression models for each of the diagnostic categories. Data on timing of competing events, such as deaths and emigration, were not available in this data source, but these events are uncommon in Denmark (WHO 2005). In each Cox proportional hazards regression model, data on all children without a diagnosis in the respective category were censored at the end of follow-up (31 December 2006). Age in days was used as time variable. We tested the proportional hazards assumption by visually checking Schoenfeld residuals and the test of Grambsch and Therneau. If the assumption was not met, we stratified the data by age (Table 3) based on the Schoenfeld residuals to ensure that the proportional hazards assumption was met. For conditions originating in the perinatal period and for malformations, we used separate logistic regression models to estimates associations with maternal life stress and emotional stress. Low-stress groups were used as reference categories. We tested for trends using log-rank–based trend tests of the survivor function stratifying for the other covariates or by repeating logistic regressions with the stress categories modeled as a continuous ordinal variable.

Table 3.

Cox regression models of offspring diseases predicted by stress during pregnancy.

ICD-10 category and name No. of children with a diagnosis Life stress Adjusteda HR (95% CI) Life stress p for trend Emotional stress Adjusteda HR (95% CI) Emotional stress p for trend
Low-medium vs. low Medium-high vs. low High vs. low Low-medium vs. low Medium-high vs. low High vs. low
1. Infections, parasitic diseases 6,674 1.08 (1.00, 1.16) 1.10 (1.03, 1.18) 1.28 (1.17, 1.39) < 0.001 0.99 (0.92, 1.07) 1.06 (0.99, 1.13) 1.09 (1.01, 1.18) 0.008
2. Neoplasms 711 0.93 (0.75, 1.16) 1.06 (0.86, 1.30) 0.94 (0.73, 1.22) 0.99 0.96 (0.76, 1.20) 1.07 (0.86, 1.32) 1.13 (0.89, 1.44) 0.35
3. Diseases of blood, immune system 512 1.01 (0.78, 1.31) 1.01 (0.78, 1.30) 1.19 (0.89, 1.59) 0.49 1.17 (0.90, 1.52) 1.17 (0.91, 1.50) 1.12 (0.85, 1.48) 0.51
4. Endocrine, metabolic disorders 1,178 1.03 (0.87, 1.22) 1.09 (0.93, 1.28) 1.20 (0.99, 1.47) 0.09 1.03 (0.87, 1.21) 0.87 (0.74, 1.03) 0.81 (0.67, 0.99) 0.02
5. Mental and behavioral disordersb 543 1.12 (0.87, 1.44) 0.88 (0.68, 1.13) 0.86 (0.65, 1.14) 0.076
≤ 2.5 years 1.49 (0.98, 2.25) 1.34 (0.90, 2.01) 2.03 (1.32, 3.14) 0.007
> 2.5 years 0.78 (0.55, 1.10) 1.06 (0.78, 1.43) 1.11 (0.78, 1.58) 0.747
6. Diseases of nervous system 1,268 1.00 (0.85, 1.18) 1.06 (0.90, 1.23) 1.17 (0.96, 1.42) 0.21 0.85 (0.72, 1.01) 0.97 (0.83, 1.13) 0.86 (0.72, 1.04) 0.15
7. Diseases of eyeb 1,451
≤ 4.5 years 0.98 (0.83, 1.16) 0.99 (0.84, 1.15) 1.27 (1.06, 1.53) 0.34 0.95 (0.82, 1.11) 0.98 (0.84, 1.13) 0.84 (0.71, 0.99) 0.14
> 4.5 years 1.27 (0.89, 1.82) 1.62 (1.18, 2.22) 1.19 (0.80, 1.78) 0.13
8. Diseases of ear 4,344 1.04 (0.95, 1.14) 1.15 (1.05, 1.25) 1.36 (1.23, 1.51) < 0.001 1.06 (0.97, 1.16) 1.03 (0.95, 1.12) 1.04 (0.95, 1.15) 0.25
9. Diseases of circulatory systemb 362 1.14 (0.85, 1.54) 1.03 (0.77, 1.38) 1.29 (0.91, 1.84) 0.07
≤ 3.0 years 0.84 (0.57, 1.24) 0.70 (0.49, 1.02) 0.63 (0.42, 0.95) 0.08
> 3.0 years 0.95 (0.58, 1.55) 0.61 (0.37, 1.01) 1.16 (0.74, 1.82) 0.93
10. Diseases of respiratory system 12,442 1.04 (0.99, 1.10) 1.14 (1.08, 1.20) 1.27 (1.19, 1.35) < 0.001 0.98 (0.93, 1.04) 0.97 (0.92, 1.02) 1.00 (0.94, 1.06) 0.98
11. Diseases of digestive system 4,032 1.06 (0.97, 1.17) 1.21 (1.11, 1.31) 1.23 (1.11, 1.37) < 0.001 0.99 (0.90, 1.09) 1.03 (0.95, 1.13) 0.97 (0.87, 1.07) 0.71
12. Diseases of skin 2,500 0.95 (0.85, 1.07) 1.06 (0.95, 1.19) 1.24 (1.09, 1.43) 0.005 0.97 (0.86, 1.09) 0.92 (0.82, 1.03) 0.93 (0.82, 1.06) 0.33
13. Diseases of musculoskeletal system 3,107 1.03 (0.93, 1.14) 1.06 (0.96, 1.17) 1.15 (1.01, 1.30) 0.01 0.99 (0.89, 1.10) 0.91 (0.83, 1.01) 0.99 (0.88, 1.11) 0.67
14. Diseases of genitourinary system 2,243 1.13 (1.00, 1.27) 1.19 (1.06, 1.34) 1.25 (1.08, 1.45) 0.02 0.96 (0.85, 1.09) 1.09 (0.97, 1.22) 0.97 (0.85, 1.11) 0.86
Any 34,665 1.02 (0.99, 1.05) 1.11 (1.08, 1.14) 1.16 (1.12, 1.20) < 0.001 1.00 (0.97, 1.03) 1.01 (0.98, 1.04) 1.03 (0.99, 1.06) 0.07
HRs for the offspring having an initial diagnosis within the respective diagnostic category (outcomes) according to maternal life stress and emotional stress during pregnancy (predictors) (n = 66,203). Information on diagnoses of the children was obtained from the database-linked Danish National Hospital Register, which contains information on all diagnoses of inpatients and outpatients in Danish hospitals. In each diagnostic category, we used the initial diagnosis.aModel stratified for socioeconomic status, parity, maternal age, general maternal health, and infant sex, and adjusted for postnatal life stress and postnatal emotional stress of the mother. bData were split at indicated times.
Open in a new tab

We calculated all standard errors using the clustered sandwich estimator to correct for possible dependence between health outcomes in infants born to the same mother (n = 3,029). Moreover, to control for previous reproductive experiences and their possible effect on exposures (Olsen 2008), we repeated all analyses including only the first pregnancy of each woman in the cohort.

To obtain less-confounded estimates, we adjusted for potential predictors of child health, selected a priori, including socioeconomic status (Gissler et al. 1998) (based on occupation of the mother; see Bech et al. 2005), parity (Dockerty et al. 2001), maternal age (Hassold and Chiu 1985), self-reported general maternal health (Waters et al. 2000), and infant sex (Gissler et al. 1999), categorized as indicated in Table 2. Moreover, for explorative purposes, we repeated the analyses, controlling for self-reported hypertension during pregnancy (Fatemeh et al. 2010), gestational diabetes (Aman et al. 2011), and maternal smoking during pregnancy (Shea and Steiner 2008) as potential mediators (categorized as yes, no, or unknown). In addition, we repeated the analyses, controlling for birth weight and length of gestation (Gillman 2002) (continuous) as potential mediators. We obtained information on socioeconomic status, parity, and general maternal health from an interview around 12 weeks of gestation; on smoking, hypertension, and gestational diabetes from interviews around 12 weeks of gestation, 30 weeks of gestation, and 6 months postpartum; and on sex, maternal age at delivery, birth weight, and length of gestation from the Danish Medical Birth Registry (Copenhagen, Denmark). We extended the model by adjusting for postnatal exposure to maternal stress assessed, according to the method described for maternal stress during pregnancy, at 6 months postpartum, covering the time since parturition. High maternal stress may be a consequence rather than a cause of offspring disease within the first 6 months of life (Fowlie and McHaffie 2004). Therefore, we repeated the analyses after excluding all cases having their first diagnosis within the first 7 months of life.

All hypothesis tests were two-tailed, with the level of significance set at 0.05. We addressed loss to follow-up and missing data by restricting analyses to mother–child pairs with complete data on stress. For those with missing information on a particular covariate, we included an additional “missing” category for the respective variable.

Results

Study cohort characteristics. Complete information on maternal stress during and after pregnancy and on diagnoses was available for 66,203 (99%) of the eligible mother–child pairs that participated in all of the relevant interviews [see Supplemental Material, Figure 1 (http://dx.doi.org/10.1289/ehp.1003253) for details regarding study recruitment and observations included in this analysis]. Sample characteristics are provided in Table 2 (for additional information on the sample characteristics according to the stress categories, see Supplemental Material, Table 2). Median age at the end of follow-up was 6.2 (range, 3.6–8.9) years. Life and emotional stress were reported as stronger before than after birth (life stress: z = 94.81, p < 0.001; emotional stress: z = 66.18, p < 0.001, Wilcoxon signed-rank tests). Cumulative lifetime incidences of all diagnostic categories are shown according to quartile of prenatal life or emotional stress in Supplemental Material, Figure 2.

Regression analyses. After adjustment, maternal life stress during pregnancy was associated with an increased disease risk in 11 of 16 diagnostic categories, including an increased risk for the first diagnosis of infectious and parasitic diseases, mental and behavioral disorders (up to 2.5 years of age), diseases of the eye, ear, respiratory system, digestive system, skin, musculoskeletal and genitourinary systems, and of any disease (Table 3). Maternal life stress during pregnancy was associated with an increased risk of conditions originating in the perinatal period and of congenital malformations (Table 4).

Table 4.

Logistic regression models of offspring diseases predicted by stress during pregnancy.

No. of children with a diagnosis Life stress Adjusteda OR (95% CI) Emotional stress Adjusteda OR (95% CI) Emotional stress p for trend
ICD-10 category and name Low-medium vs. low Medium-high vs. low High vs. low Life stress p for trend Low-medium vs. low Medium-high vs. low High vs. low
16. Conditions originating in perinatal period 12,590 1.03 (0.97, 1.09) 1.11 (1.06, 1.18) 1.13 (1.06, 1.21) < 0.001 1.01 (0.95, 1.07) 1.02 (0.97, 1.07) 1.04 (0.98, 1.10) 0.24
17. Malformations 5,534 1.03 (0.95, 1.12) 1.13 (1.05, 1.21) 1.17 (1.06, 1.28) < 0.001 1.00 (0.92, 1.08) 1.00 (0.93, 1.08) 1.03 (0.95, 1.12) 0.54
Abbreviations: CI, confidence interval; OR, odds ratio. ORs for the offspring having conditions originating in the perinatal period and malformations (outcomes) according to maternal life stress and emotional stress during pregnancy (predictors) (n = 66,203). aModels adjusted for socioeconomic status, parity, maternal age, general maternal health, and infant sex.
Open in a new tab

Maternal emotional stress during pregnancy was associated with an increased risk for the first diagnosis of infectious and parasitic diseases and a decreased risk for the first diagnosis of endocrine and metabolic disorders, diseases of the eye, and the circulatory system (up to 3 years of age). However, a significantly reduced risk of diseases of the eye and the circulatory system was seen only in offspring of highly stressed mothers. Crude estimates of the associations between maternal stress during pregnancy and offspring diseases (i.e., estimates not adjusted for any potential confounders) are provided in Supplemental Material, Table 3 (http://dx.doi.org/10.1289/ehp.1003253).

When we repeated the adjusted analyses using only the first pregnancy of each woman in the cohort and when we repeated the adjusted analyses controlling for smoking, hypertension, and gestational diabetes, or for birth weight and length of gestation, the estimates were of similar magnitude as those presented in Tables 3 and 4 (data not shown). Repeating the analyses after excluding cases having their first diagnosis before assessment of maternal stress after pregnancy did not appreciably change the magnitude of the significant estimates in the models [all changes in hazard ratio (HR) were < 0.10]. However, the prenatal life stress–associated risk for the first onset of mental disorders within the first 2.5 years of life decreased markedly [4th quartile vs. 1st quartile: HR =1.43; 95% confidence interval (CI): 0.82, 2.47 compared with HR = 2.03; CI: 1.32, 3.14].

Discussion and Conclusions

In this large population-based cohort study, maternal life stress during pregnancy was associated with an increased risk of a wide range of diseases during childhood. These findings are in line with data from animal models indicating changes in different physiological systems after maternal stress during pregnancy (Fowden et al. 2006). To our knowledge, this is the first comprehensive study of the relationship between maternal stress during pregnancy and a wide spectrum of offspring diseases during childhood.

Our study has important strengths, including prospective data collection for 66,203 mother–child pairs and linkage to a comprehensive medical registry with complete information on hospital discharge diagnoses. Although associations were of low to moderate strength, our results have broad relevance for the general population, because our definition of maternal stress focuses on everyday occurrences (rather than rare disasters or severe life events), and we focused on the whole range of illnesses, including very common diseases, which suggests that a substantial part of the population may be adversely affected by maternal stress. We adjusted for several potential confounders, but our results still may be biased by residual or uncontrolled confounding by factors such as chemical exposures. Temporal sequence, consistency of findings across a variety of categories, and evidence of a dose–response relationship support the possibility of a causal link (Grimes and Schulz 2002). We controlled for potential bias by maternal stress after pregnancy, which might increase the likelihood that a mother would seek to have her child hospitalized. In addition, it is unlikely that maternal stress would influence hospital treatment, because in the Danish health care system, 99% of the population must be referred for elective hospital treatment by a general practitioner, and both referrals and hospital treatment are free of charge for patients (Strandberg-Larsen et al. 2007). Moreover, we controlled for potential bias by reverse causation between child disease and maternal stress after pregnancy. One limitation is that we did not have data on the timing of the maternal stress exposure during pregnancy, which may play a role in the relationship between stress and long-term health, given that each organ system has a specific critical period in which it is most susceptible to intrauterine perturbations (Hansen et al. 2000; Khashan et al. 2008). However, life stress and emotional stress generally reflect chronic states of adversity (McEwen and Stellar 1993). Of all eligible mother–child pairs, 72% participated in the relevant interviews, and 99% of these were included in our analyses. Given the low loss to follow-up, the high percentage of complete data, and linkage to the Danish National Hospital Register, we think measurable selection bias is unlikely. However, missing stress interview data for 7,487 mother–child pairs [8% of those eligible; Supplemental Material, Figure 1 (http://dx.doi.org/10.1289/ehp.1003253)] may have been a consequence of premature birth in some cases, as the interview was not conducted if birth had already occurred. Therefore, the observed associations between stress during pregnancy and offspring health should not be generalized to children born extremely preterm (< 30 weeks of gestation). Finally, the different ICD-10 categories are heterogeneous with regard to grouping criteria (e.g., by organ system vs. etiology), but the ICD-10 has high reliability at the category level (Stausberg et al. 2008) and is the international standard diagnostic classification system of diseases.

Our findings on maternal life stress during pregnancy corroborate and extend the results of previous studies (Hansen et al. 2000; Li et al. 2008) to common forms of maternal stress and a broader range of disease outcomes. For example, in line with other studies (Beversdorf et al. 2005; Laplante et al. 2004), our data provide evidence for an increased risk of mental disorders during the first 2.5 years of life in offspring of mothers reporting high life stress during pregnancy compared with mothers reporting low life stress. However, we cannot rule out the possibility that this result was biased by reverse causation between offspring disease and postnatal life stress. In the present study, emotional stress during pregnancy was associated with an increased risk of infectious diseases only, whereas previous studies observed associations between emotional problems during pregnancy and other outcomes, including malformations, asthma, and mental disorders (Cookson et al. 2009; O’Connor et al. 2002; Schneid-Kofman et al. 2008; Van den Bergh and Marcoen 2004; Van den Bergh et al. 2005a, 2005b). Discrepancies among studies may partly reflect differences in disease outcome or emotional stress classifications. For example, we classified outcomes based on clinical diagnoses (instead of subclinical dysfunction) in the offspring, and defined emotional stress across the entire range rather than focusing on more severe psychopathology, as in Schneid-Kofman et al. (2008). Moreover, discrepancies between findings may be explained by differential mutual control for life stress and emotional stress and by differential control for maternal stress after pregnancy.

The decreased risk of certain diseases predicted by maternal emotional stress during pregnancy is in line with some previous evidence on beneficial effects of maternal stress on offspring development and brain maturation (DiPietro et al. 2006). However, some of these associations were seen only in offspring of highly stressed mothers, with marginal statistical significance. Hence, it is too early to conclude whether common forms of maternal emotional stress during pregnancy have the potential to protect certain organ systems against disease.

The observed association between maternal stress during pregnancy and child health may represent long-term consequences of subtle adaptations in multiple organ systems to the intrauterine environment (Bateson et al. 2004). The potential biological mechanisms underlying such developmental plasticity, including epigenetic processes (Gluckman et al. 2009) and changes at the molecular, cellular, and organ level in the offspring, provide new ideas to the fetal origin of chronic disease concept (Fowden et al. 2006; Gluckman et al. 2008; Tegethoff et al. 2009). Specifically, in relation to maternal stress during pregnancy, numerous subclinical alterations in physiology, including changes in immune, brain, cardiovascular, autonomic, endocrine, and metabolic function, have been described, such as changes in fetal heart rate, insulin resistance, increased concentrations of immunoglobulin E in cord blood and changes in hypothalamic–pituitary–adrenal (HPA) axis function (Entringer et al. 2008; Field et al. 2002; Lin et al. 2004; Monk et al. 2004, 2011; O’Connor et al. 2005). Indeed, changes in HPA axis activity have been associated not only with maternal stress during pregnancy (Kapoor et al. 2008), but also with a wide range of diseases, including mental disorders (Goodyer et al. 2001), respiratory diseases (Priftis et al. 2009), diseases of the skin (Buske-Kirschbaum et al. 2010), and infectious diseases (Bailey et al. 2003). However, although the HPA axis has long been proposed as a causal link between early adversity and lifelong disease risk (Phillips 2007), it also has been suggested that HPA-related hormones may be noncausal markers of other causal mechanisms (Kramer et al. 2009, 2010). There also is some evidence that maternal stress affects placental HSD11B2, which in turn regulates the bioavailability of glucocorticoids in fetal organs (Harris and Seckl 2011). Elevated stress levels across pregnancy have also been associated with changes in production of pro-inflammatory cytokines in the offspring (Coussons-Read et al. 2007). Dysregulation of cytokine production has been associated with certain mental disorders (Conti and Fulcheri 2010; Raison et al. 2010); infectious diseases (Subauste et al. 1995); diseases of the eye, such as conjunctivitis (Niederkorn 2008); ear, such as otitis media (Smirnova et al. 2002); respiratory system, such as asthma (Finkelman et al. 2010); digestive system, such as disorders related to gastrointestinal motility (De Winter and De Man 2010); urogenital system, such as urinary tract infection (Mak and Kuo 2006); and skin, such as atopic dermatitis (Miraglia del Giudice et al. 2006). Other mechanisms, such as catecholamines (Harris and Seckl 2011), intrauterine artery resistance, and intrauterine perception and learning (Kinsella and Monk 2009), also may be involved in offspring disease programming.

As yet, we cannot exclude the possibility that associations between stress during pregnancy and child diseases are mediated by maternal behavioral factors, such as stress-related changes in lifestyle, or health-related factors. Adjusting for maternal smoking during pregnancy, hypertension, and diabetes did not alter associations between maternal stress during pregnancy and child health. Maternal nutrition is another candidate mediator, because stress is related to quality of nutrition (Torres and Nowson 2007), and a relationship between nutrition during pregnancy and a range of offspring diseases has been well documented (Symonds et al. 2007). Moreover, alcohol consumption during pregnancy has been associated with birth defects (O’Leary et al. 2010) and impaired offspring development and behavior (Bay and Kesmodel 2010; Sood et al. 2001), indicating that alcohol may mediate associations between maternal stress and child health. Adjusting for birth weight and length of gestation had little effect on associations.

The observed associations between maternal stress during pregnancy and offspring health may have implications for public health and health care policy: First, further investment in the reduction of life stress during pregnancy may be an important opportunity to improve child health. Second, our findings encourage consideration of preventive strategies for infants of mothers who were highly stressed during pregnancy.

This study suggests that maternal life stress during pregnancy may be a common risk factor for a wide range of diseases in the offspring; however, we found almost no evidence for adverse health consequences of maternal emotional stress during pregnancy. Future studies should a) focus on the underlying mechanisms of these relationships, b) analyze the associations between selected forms of maternal stress during pregnancy and specific offspring diseases, including more detailed information on disease characteristics and information from further health registries, and c) identify modifiable determinants within this context to improve preventive approaches and interventions.

Supplemental Material

(892 KB) PDF

Acknowledgments

We thank J. Meyer for critical reading of the manuscript. Validation of the stress scores was undertaken, in part, with data from the National Centre of Competence in Research, Swiss Etiological Study of Adjustment and Mental Health (sesam), funded by Swiss National Science Foundation project 51A240–104890.

Footnotes

The work for this manuscript was performed at the University of Basel, Basel, Switzerland, and at the University of California Los Angeles, Los Angeles, California, USA. The Danish National Birth Cohort was established by the Danish Epidemiology Science Centre, Department of Epidemiology, Institute of Public Health, University of Aarhus, Aarhus, Denmark. The Danish National Research Foundation established the Danish Epidemiology Science Centre, which initiated and created the Danish National Birth Cohort. The cohort is furthermore a result of a major grant from this foundation. Additional support for the Danish National Birth Cohort was obtained from the Pharmacy Foundation (http://www.pharmacyfoundation.org), the Egmont Foundation (www.egmont.com/the-egmont-foundation), the March of Dimes Birth Defects Foundation (http://www.marchofdimes.com), the Augustinus Foundation (Augustinus Fonden, København, Denmark), and the Health Foundation (http://www.health.org.uk/). This project was financed by the German National Academic Foundation (to M.T.) and Swiss National Science Foundation project 51A240–104890 (to G.M.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The authors declare they have no actual or potential competing financial interests.

References

  1. Aman J, Hansson U, Ostlund I, Wall K, Persson B. Increased fat mass and cardiac septal hypertrophy in newborn infants of mothers with well-controlled diabetes during pregnancy. Neonatology. 2011;100:147–154. doi: 10.1159/000323741. [DOI] [PubMed] [Google Scholar]
  2. Andersen TF, Madsen M, Jorgensen J, Mellemkjoer L, Olsen JH. The Danish National Hospital Register. A valuable source of data for modern health sciences. Dan Med Bull. 1999;46:263–268. [PubMed] [Google Scholar]
  3. Bailey M, Engler H, Hunzeker J, Sheridan JF. The hypothalamic-pituitary-adrenal axis and viral infection. Viral Immunol. 2003;16:141–157. doi: 10.1089/088282403322017884. [DOI] [PubMed] [Google Scholar]
  4. Barker DJ, Osmond C, Simmonds SJ, Wield GA. The relation of small head circumference and thinness at birth to death from cardiovascular disease in adult life. BMJ. 1993;306:422–426. doi: 10.1136/bmj.306.6875.422. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bateson P, Barker D, Clutton-Brock T, Deb D, D’Udine B, Foley RA, et al. Developmental plasticity and human health. Nature. 2004;430:419–421. doi: 10.1038/nature02725. [DOI] [PubMed] [Google Scholar]
  6. Bay B, Kesmodel US. Prenatal alcohol exposure – a systematic review of the effects on child motor function. Acta Obstet Gynecol Scand. 2010;90:210–226. doi: 10.1111/j.1600-0412.2010.01039.x. [DOI] [PubMed] [Google Scholar]
  7. Bech BH, Nohr EA, Vaeth M, Henriksen TB, Olsen J. Coffee and fetal death: a cohort study with prospective data. Am J Epidemiol. 2005;162:983–990. doi: 10.1093/aje/kwi317. [DOI] [PubMed] [Google Scholar]
  8. Beversdorf DQ, Manning SE, Hillier A, Anderson SL, Nordgren RE, Walters SE, et al. Timing of prenatal stressors and autism. J Autism Dev Disord. 2005;35:471–478. doi: 10.1007/s10803-005-5037-8. [DOI] [PubMed] [Google Scholar]
  9. Beydoun H, Saftlas AF. Physical and mental health outcomes of prenatal maternal stress in human and animal studies: a review of recent evidence. Paediatr Perinat Epidemiol. 2008;22:438–466. doi: 10.1111/j.1365-3016.2008.00951.x. [DOI] [PubMed] [Google Scholar]
  10. Buske-Kirschbaum A, Ebrecht M, Hellhammer DH. Blunted HPA axis responsiveness to stress in atopic patients is associated with the acuity and severeness of allergic inflammation. Brain Behav Immun. 2010;24:1347–1353. doi: 10.1016/j.bbi.2010.06.013. [DOI] [PubMed] [Google Scholar]
  11. Christensen J, Vestergaard M, Olsen J, Sidenius P. Validation of epilepsy diagnoses in the Danish National Hospital Register. Epilepsy Res. 2007;75:162–170. doi: 10.1016/j.eplepsyres.2007.05.009. [DOI] [PubMed] [Google Scholar]
  12. Conti CM, Fulcheri M. Interrelationship between psychology and cytokines. J Biol Regul Homeost Agents. 2010;24:485–490. [PubMed] [Google Scholar]
  13. Cookson H, Granell R, Joinson C, Ben-Shlomo Y, Henderson AJ. 2009. Mothers’ anxiety during pregnancy is associated with asthma in their children. J Allergy Clin Immunol 123:847–853 e811. [DOI] [PMC free article] [PubMed]
  14. Coussons-Read ME, Okun ML, Nettles CD. Psychosocial stress increases inflammatory markers and alters cytokine production across pregnancy. Brain Behav Immun. 2007;21:343–350. doi: 10.1016/j.bbi.2006.08.006. [DOI] [PubMed] [Google Scholar]
  15. Danish National Board of Health. Copenhagen: Danish National Board of Health; 1993. Classification of Diseases. 10th Revision. [Google Scholar]
  16. Derogatis LR. Baltimore: Johns Hopkins Press; 1977. SCL-90. Administration, Scoring, and Procedures for the R (Revised) Version. [Google Scholar]
  17. De Winter BY, De Man JG. Interplay between inflammation, immune system and neuronal pathways: effect on gastrointestinal motility. World J Gastroenterol. 2010;16:5523–5535. doi: 10.3748/wjg.v16.i44.5523. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. DiPietro JA, Novak MF, Costigan KA, Atella LD, Reusing SP. Maternal psychological distress during pregnancy in relation to child development at age two. Child Dev. 2006;77:573–587. doi: 10.1111/j.1467-8624.2006.00891.x. [DOI] [PubMed] [Google Scholar]
  19. Dockerty JD, Draper G, Vincent T, Rowan SD, Bunch KJ. Case-control study of parental age, parity and socioeconomic level in relation to childhood cancers. Int J Epidemiol. 2001;30:1428–1437. doi: 10.1093/ije/30.6.1428. [DOI] [PubMed] [Google Scholar]
  20. Entringer S, Wust S, Kumsta R, Layes IM, Nelson EL, Hellhammer DH, et al. 2008. Prenatal psychosocial stress exposure is associated with insulin resistance in young adults. Am J Obstet Gynecol 199:498 e491–497.
  21. Fatemeh T, Marziyeh G, Nayereh G, Anahita G, Samira T. Maternal and perinatal outcome in nulliparous women complicated with pregnancy hypertension. J Pak Med Assoc. 2010;60:707–710. [PubMed] [Google Scholar]
  22. Field T, Diego M, Hernandez-Reif M, Salman F, Schanberg S, Kuhn C, et al. Prenatal anger effects on the fetus and neonate. J Obstet Gynaecol. 2002;22:260–266. doi: 10.1080/01443610220130526. [DOI] [PubMed] [Google Scholar]
  23. Finkelman FD, Hogan SP, Hershey GK, Rothenberg ME, Wills-Karp M. Importance of cytokines in murine allergic airway disease and human asthma. J Immunol. 2010;184:1663–1674. doi: 10.4049/jimmunol.0902185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Forsen T, Eriksson J, Tuomilehto J, Reunanen A, Osmond C, Barker D. The fetal and childhood growth of persons who develop type 2 diabetes. Ann Intern Med. 2000;133:176–182. doi: 10.7326/0003-4819-133-3-200008010-00008. [DOI] [PubMed] [Google Scholar]
  25. Fowden AL, Giussani DA, Forhead AJ. Intrauterine programming of physiological systems: causes and consequences. Physiology (Bethesda) 2006;21:29–37. doi: 10.1152/physiol.00050.2005. [DOI] [PubMed] [Google Scholar]
  26. Fowlie PW, McHaffie H. Supporting parents in the neonatal unit. BMJ. 2004;329:1336–1338. doi: 10.1136/bmj.329.7478.1336. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Gillman MW. Epidemiological challenges in studying the fetal origins of adult chronic disease. Int J Epidemiol. 2002;31:294–299. [PubMed] [Google Scholar]
  28. Gissler M, Jarvelin MR, Louhiala P, Hemminki E. Boys have more health problems in childhood than girls: follow-up of the 1987 Finnish birth cohort. Acta Paediatr. 1999;88:310–314. doi: 10.1080/08035259950170088. [DOI] [PubMed] [Google Scholar]
  29. Gissler M, Rahkonen O, Jarvelin MR, Hemminki E. Social class differences in health until the age of seven years among the Finnish 1987 birth cohort. Soc Sci Med. 1998;46:1543–1552. doi: 10.1016/s0277-9536(98)00013-6. [DOI] [PubMed] [Google Scholar]
  30. Gluckman PD, Hanson MA, Buklijas T, Low FM, Beedle AS. Epigenetic mechanisms that underpin metabolic and cardiovascular diseases. Nat Rev Endocrinol. 2009;5:401–408. doi: 10.1038/nrendo.2009.102. [DOI] [PubMed] [Google Scholar]
  31. Gluckman PD, Hanson MA, Cooper C, Thornburg KL. Effect of in utero and early-life conditions on adult health and disease. N Engl J Med. 2008;359:61–73. doi: 10.1056/NEJMra0708473. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Goldberg D. London: Oxford University Press; 1972. The Detection of Psychiatric Illness by Questionnaire. [Google Scholar]
  33. Goodyer IM, Park RJ, Netherton CM, Herbert J. Possible role of cortisol and dehydroepiandrosterone in human development and psychopathology. Br J Psychiatry. 2001;179:243–249. doi: 10.1192/bjp.179.3.243. [DOI] [PubMed] [Google Scholar]
  34. Grimes DA, Schulz KF. Bias and causal associations in observational research. Lancet. 2002;359:248–252. doi: 10.1016/S0140-6736(02)07451-2. [DOI] [PubMed] [Google Scholar]
  35. Hansen D, Lou HC, Olsen J. Serious life events and congenital malformations: a national study with complete follow-up. Lancet. 2000;356:875–880. doi: 10.1016/S0140-6736(00)02676-3. [DOI] [PubMed] [Google Scholar]
  36. Harris A, Seckl J. Glucocorticoids, prenatal stress and the programming of disease. Horm Behav. 2011;59:279–289. doi: 10.1016/j.yhbeh.2010.06.007. [DOI] [PubMed] [Google Scholar]
  37. Hassold T, Chiu D. Maternal age-specific rates of numerical chromosome abnormalities with special reference to trisomy. Hum Genet. 1985;70:11–17. doi: 10.1007/BF00389450. [DOI] [PubMed] [Google Scholar]
  38. Kapoor A, Petropoulos S, Matthews SG. Fetal programming of hypothalamic-pituitary-adrenal (HPA) axis function and behavior by synthetic glucocorticoids. Brain Res Rev. 2008;57:586–595. doi: 10.1016/j.brainresrev.2007.06.013. [DOI] [PubMed] [Google Scholar]
  39. Khashan AS, Abel KM, McNamee R, Pedersen MG, Webb RT, Baker PN, et al. Higher risk of offspring schizophrenia following antenatal maternal exposure to severe adverse life events. Arch Gen Psychiatry. 2008;65:146–152. doi: 10.1001/archgenpsychiatry.2007.20. [DOI] [PubMed] [Google Scholar]
  40. Kinsella MT, Monk C. Impact of maternal stress, depression and anxiety on fetal neurobehavioral development. Clin Obstet Gynecol. 2009;52:425–440. doi: 10.1097/GRF.0b013e3181b52df1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Kramer MS, Lydon J, Seguin L, Goulet L, Kahn SR, McNamara H, et al. Stress pathways to spontaneous preterm birth: the role of stressors, psychological distress, and stress hormones. Am J Epidemiol. 2009;169:1319–1326. doi: 10.1093/aje/kwp061. [DOI] [PubMed] [Google Scholar]
  42. Kramer MS, Lydon J, Seguin L, Goulet L, Kahn SR, McNamara H, et al. Non-stress-related factors associated with maternal corticotrophin-releasing hormone (CRH) concentration. Paediatr Perinat Epidemiol. 2010;24:390–397. doi: 10.1111/j.1365-3016.2010.01127.x. [DOI] [PubMed] [Google Scholar]
  43. Laplante DP, Barr RG, Brunet A, Galbaud du Fort G, Meaney ML, Saucier JF, et al. Stress during pregnancy affects general intellectual and language functioning in human toddlers. Pediatr Res. 2004;56:400–410. doi: 10.1203/01.PDR.0000136281.34035.44. [DOI] [PubMed] [Google Scholar]
  44. Li J, Vestergaard M, Obel C, Precht DH, Christensen J, Lu M, et al. Prenatal stress and epilepsy in later life: a nationwide follow-up study in Denmark. Epilepsy Res. 2008;81:52–57. doi: 10.1016/j.eplepsyres.2008.04.014. [DOI] [PubMed] [Google Scholar]
  45. Lin YC, Wen HJ, Lee YL, Guo YL. Are maternal psychosocial factors associated with cord immunoglobulin E in addition to family atopic history and mother immunoglobulin E? Clin Exp Allergy. 2004;34:548–554. doi: 10.1111/j.1365-2222.2004.1928.x. [DOI] [PubMed] [Google Scholar]
  46. Lobel M. Conceptualizations, measurement, and effects of prenatal maternal stress on birth outcomes. J Behav Med. 1994;17:225–272. doi: 10.1007/BF01857952. [DOI] [PubMed] [Google Scholar]
  47. Mak RH, Kuo HJ. Pathogenesis of urinary tract infection: an update. Curr Opin Pediatr. 2006;18:148–152. doi: 10.1097/01.mop.0000193276.39495.0d. [DOI] [PubMed] [Google Scholar]
  48. McEwen BS, Stellar E. Stress and the individual. Mechanisms leading to disease. Arch Intern Med. 1993;153:2093–2101. [PubMed] [Google Scholar]
  49. Miraglia del Giudice M, Decimo F, Leonardi S, Maioello N, Amelio R, Capasso A, et al. Immune dysregulation in atopic dermatitis. Allergy Asthma Proc. 2006;27:451–455. doi: 10.2500/aap.2006.27.2887. [DOI] [PubMed] [Google Scholar]
  50. Monk C, Fifer WP, Myers MM, Bagiella E, Duong JK, Chen IS, et al. Effects of maternal breathing rate, psychiatric status, and cortisol on fetal heart rate. Dev Psychobiol. 2011;53:221–233. doi: 10.1002/dev.20513. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Monk C, Sloan RP, Myers MM, Ellman L, Werner E, Jeon J, et al. Fetal heart rate reactivity differs by women’s psychiatric status: An early marker for developmental risk? J Am Acad Child Adolesc Psychiatry. 2004;43:283–290. doi: 10.1097/00004583-200403000-00009. [DOI] [PubMed] [Google Scholar]
  52. Moth G, Vedsted P, Schiotz PO. National registry diagnoses agree with medical records on hospitalized asthmatic children. Acta Paediatr. 2007;96:1470–1473. doi: 10.1111/j.1651-2227.2007.00460.x. [DOI] [PubMed] [Google Scholar]
  53. National Institutes of Health. 2003. Pregnancy and Perinatology Branch Strategic Plan 2005–2010. Washington DC:National Institutes of Health. [Google Scholar]
  54. Niederkorn JY. Immune regulatory mechanisms in allergic conjunctivitis: insights from mouse models. Curr Opin Allergy Clin Immunol. 2008;8:472–476. doi: 10.1097/ACI.0b013e32830edbcb. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Norbeck JS. Modification of life event questionnaires for use with female respondents. Res Nurs Health. 1984;7:61–71. doi: 10.1002/nur.4770070110. [DOI] [PubMed] [Google Scholar]
  56. O’Connor TG, Ben-Shlomo Y, Heron J, Golding J, Adams D, Glover V. Prenatal anxiety predicts individual differences in cortisol in pre-adolescent children. Biol Psychiatry. 2005;58:211–217. doi: 10.1016/j.biopsych.2005.03.032. [DOI] [PubMed] [Google Scholar]
  57. O’Connor TG, Heron J, Golding J, Beveridge M, Glover V. Maternal antenatal anxiety and children’s behavioural/emotional problems at 4 years. Report from the Avon Longitudinal Study of Parents and Children. Br J Psychiatry. 2002;180:502–508. doi: 10.1192/bjp.180.6.502. [DOI] [PubMed] [Google Scholar]
  58. O’Leary CM, Nassar N, Kurinczuk JJ, de Klerk N, Geelhoed E, Elliott EJ, et al. Prenatal alcohol exposure and risk of birth defects. Pediatrics. 2010;126:e843–e850. doi: 10.1542/peds.2010-0256. [DOI] [PubMed] [Google Scholar]
  59. Olsen J. Confounding by exposure history and prior outcome. Epidemiology. 2008;19:635–636. doi: 10.1097/EDE.0b013e3181773494. ; author reply 636. [DOI] [PubMed] [Google Scholar]
  60. Olsen J, Melbye M, Olsen SF, Sorensen TI, Aaby P, Andersen AM, et al. The Danish National Birth Cohort–its background, structure and aim. Scand J Public Health. 2001;29:300–307. doi: 10.1177/14034948010290040201. [DOI] [PubMed] [Google Scholar]
  61. Pacak K, Palkovits M. Stressor specificity of central neuroendocrine responses: implications for stress-related disorders. Endocr Rev. 2001;22:502–548. doi: 10.1210/edrv.22.4.0436. [DOI] [PubMed] [Google Scholar]
  62. Phillips DI. Programming of the stress response: a fundamental mechanism underlying the long-term effects of the fetal environment? J Intern Med. 2007;261:453–460. doi: 10.1111/j.1365-2796.2007.01801.x. [DOI] [PubMed] [Google Scholar]
  63. Priftis KN, Papadimitriou A, Nicolaidou P, Chrousos GP. Dysregulation of the stress response in asthmatic children. Allergy. 2009;64:18–31. doi: 10.1111/j.1398-9995.2008.01948.x. [DOI] [PubMed] [Google Scholar]
  64. Raison CL, Lowry CA, Rook GA. Inflammation, sanitation, and consternation: Loss of contact with coevolved, tolerogenic microorganisms and the pathophysiology and treatment of major depression. Arch Gen Psychiatry. 2010;67:1211–1224. doi: 10.1001/archgenpsychiatry.2010.161. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Richardson HN, Zorrilla EP, Mandyam CD, Rivier CL. Exposure to repetitive versus varied stress during prenatal development generates two distinct anxiogenic and neuroendocrine profiles in adulthood. Endocrinology. 2006;147:2506–2517. doi: 10.1210/en.2005-1054. [DOI] [PubMed] [Google Scholar]
  66. Schneid-Kofman N, Sheiner E, Levy A. Psychiatric illness and adverse pregnancy outcome. Int J Gynaecol Obstet. 2008;101:53–56. doi: 10.1016/j.ijgo.2007.10.007. [DOI] [PubMed] [Google Scholar]
  67. Shea AK, Steiner M. Cigarette smoking during pregnancy. Nicotine Tob Res. 2008;10:267–278. doi: 10.1080/14622200701825908. [DOI] [PubMed] [Google Scholar]
  68. Smirnova MG, Kiselev SL, Gnuchev NV, Birchall JP, Pearson JP. Role of the pro-inflammatory cytokines tumor necrosis factor-alpha, interleukin-1 beta, interleukin-6 and interleukin-8 in the pathogenesis of the otitis media with effusion. Eur Cytokine Netw. 2002;13:161–172. [PubMed] [Google Scholar]
  69. Sondergaard C, Olsen J, Friis-Hasche E, Dirdal M, Thrane N, Sorensen HT. Psychosocial distress during pregnancy and the risk of infantile colic: a follow-up study. Acta Paediatr. 2003;92:811–816. doi: 10.1080/08035250310003857. [DOI] [PubMed] [Google Scholar]
  70. Sood B, Delaney-Black V, Covington C, Nordstrom-Klee B, Ager J, Templin T, et al. Prenatal alcohol exposure and childhood behavior at age 6 to 7 years. I. Dose-response effect. Pediatrics. 2001;108:E34. doi: 10.1542/peds.108.2.e34. [DOI] [PubMed] [Google Scholar]
  71. Sorensen HT, Larsen BO. A population-based Danish data resource with possible high validity in pharmacoepidemiological research. J Med Syst. 1994;18:33–38. doi: 10.1007/BF00999322. [DOI] [PubMed] [Google Scholar]
  72. Stausberg J, Lehmann N, Kaczmarek D, Stein M. Reliability of diagnoses coding with ICD-10. Int J Med Inform. 2008;77:50–57. doi: 10.1016/j.ijmedinf.2006.11.005. [DOI] [PubMed] [Google Scholar]
  73. Strandberg-Larsen M, Nielsen MB, Vallgårda S, Krasnik A, Vrangbæk K, Mossialos E. Denmark: health system review. Health Syst Transit. 2007;9:1–164. [Google Scholar]
  74. Subauste MC, Jacoby DB, Richards SM, Proud D. Infection of a human respiratory epithelial cell line with rhinovirus. Induction of cytokine release and modulation of susceptibility to infection by cytokine exposure. J Clin Invest. 1995;96:549–557. doi: 10.1172/JCI118067. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Symonds ME, Stephenson T, Gardner DS, Budge H. Long-term effects of nutritional programming of the embryo and fetus: mechanisms and critical windows. Reprod Fertil Dev. 2007;19:53–63. doi: 10.1071/rd06130. [DOI] [PubMed] [Google Scholar]
  76. Tegethoff M, Greene N, Olsen J, Meyer AH, Meinlschmidt G. Maternal psychosocial adversity during pregnancy is associated with length of gestation and offspring size at birth: evidence from a population-based cohort study. Psychosom Med. 2010a;72:419–426. doi: 10.1097/PSY.0b013e3181d2f0b0. [DOI] [PubMed] [Google Scholar]
  77. Tegethoff M, Greene N, Olsen J, Meyer AH, Meinlschmidt G.2010bMaternal psychosocial stress during pregnancy and placenta weight: evidence from a national cohort study. PLoS ONE 5e14478; doi: 10.1371/journal.pone.0014478[Online 31 December 2010] [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Tegethoff M, Pryce C, Meinlschmidt G. Effects of intrauterine exposure to synthetic glucocorticoids on fetal, newborn, and infant hypothalamic-pituitary-adrenal axis function in humans: a systematic review. Endocr Rev. 2009;30:753–789. doi: 10.1210/er.2008-0014. [DOI] [PubMed] [Google Scholar]
  79. Torres SJ, Nowson CA. Relationship between stress, eating behavior, and obesity. Nutrition. 2007;23:887–894. doi: 10.1016/j.nut.2007.08.008. [DOI] [PubMed] [Google Scholar]
  80. Van den Bergh BR, Marcoen A. High antenatal maternal anxiety is related to ADHD symptoms, externalizing problems, and anxiety in 8- and 9-year-olds. Child Dev. 2004;75:1085–1097. doi: 10.1111/j.1467-8624.2004.00727.x. [DOI] [PubMed] [Google Scholar]
  81. Van den Bergh BR, Mennes M, Oosterlaan J, Stevens V, Stiers P, Marcoen A, et al. High antenatal maternal anxiety is related to impulsivity during performance on cognitive tasks in 14- and 15-year-olds. Neurosci Biobehav Rev. 2005a;29:259–269. doi: 10.1016/j.neubiorev.2004.10.010. [DOI] [PubMed] [Google Scholar]
  82. Van den Bergh BR, Mulder EJ, Mennes M, Glover V. Antenatal maternal anxiety and stress and the neurobehavioural development of the fetus and child: links and possible mechanisms. A review. Neurosci Biobehav Rev. 2005b;29:237–258. doi: 10.1016/j.neubiorev.2004.10.007. [DOI] [PubMed] [Google Scholar]
  83. Vestergaard M, Obel C, Henriksen TB, Christensen J, Madsen KM, Ostergaard JR, et al. The Danish National Hospital Register is a valuable study base for epidemiologic research in febrile seizures. J Clin Epidemiol. 2006;59:61–66. doi: 10.1016/j.jclinepi.2005.05.008. [DOI] [PubMed] [Google Scholar]
  84. Waters E, Doyle J, Wolfe R, Wright M, Wake M, Salmon L. Influence of parental gender and self-reported health and illness on parent-reported child health. Pediatrics. 2000;106:1422–1428. doi: 10.1542/peds.106.6.1422. [DOI] [PubMed] [Google Scholar]
  85. WHO (World Health Organization) The World Health Report. 2005:2005. Geneva:WHO. [Google Scholar]
  86. WHO (World Health Organization) Geneva: WHO; 2006. Promoting Optimal Fetal Development: Report of a Technical Consultation. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

(892 KB) PDF
Click here for additional data file. (888.6KB, pdf)

Articles from Environmental Health Perspectives are provided here courtesy of National Institute of Environmental Health Sciences

RESOURCES