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Article |

Childhood Hardship, Maternal Smoking, and Birth Outcomes:  A Prospective Cohort Study FREE

Emily W. Harville, PhD; Renée Boynton-Jarrett, MD, ScD; Chris Power, PhD; Elina Hyppönen, PhD
[+] Author Affiliations

Author Affiliations: Tulane University, New Orleans, Louisiana (Dr Harville); Division of General Pediatrics, Boston University School of Medicine, Boston, Massachusetts (Dr Boynton-Jarrett); and Institute of Child Health, London, England (Drs Power and Hyppönen).


Arch Pediatr Adolesc Med. 2010;164(6):533-539. doi:10.1001/archpediatrics.2010.61.
Text Size: A A A
Published online

Objective  To determine the association between type, chronicity, and severity of childhood hardships and smoking status during pregnancy, preterm birth (PTB), and low birth weight (LBW).

Design  Prospective cohort study.

Setting  The National Child Development Study, a nationally representative study of births in Great Britain in 1958.

Participants  Four thousand eight-hundred sixty-five women with at least 1 singleton live birth.

Main Exposures  Hardship during childhood, indicated by several variables, including financial/structural hardship, lack of parental interest in education, family dysfunction, violence/mental health issues, and family structure.

Main Outcome Measures  Smoking in pregnancy, LBW, and PTB.

Results  A consistent and graded association was seen between all types of childhood hardships and smoking status during pregnancy (odds ratio [OR] for 4 or more hardships, 2.02; 95% confidence interval [CI], 1.58-2.58; P < .001 for all comparisons). Most hardships were also associated with risk of LBW and PTB, with associations between number of hardships and both outcomes persisting after controlling for smoking status and adult social class (for LBW, OR, 1.51; 95% CI, 1.10-2.06; for PTB, OR, 1.44; 95% CI, 1.08-1.92).

Conclusion  Childhood hardships have an enduring impact on future pregnancy outcomes, in part through their association with smoking during pregnancy and adult socioeconomic position.

Mounting research evidence suggests a relation between psychosocial stressors during pregnancy and poor pregnancy outcomes, such as low birth weight (LBW), intrauterine growth retardation, and preterm birth (PTB).1 Yet studies to date fail to explain the persistent associations of poverty and African American race/ethnicity with poorer pregnancy outcomes.2 A shared limitation of past studies is that the period of investigation is limited to the pregnancy itself.3 Building evidence of the role of adverse exposures in early life calls for investigation of the role of preconception and interconceptional health and pregnancy outcomes.4,5 Hypothetically, psychosocial and material hardships in childhood and adolescence may ultimately influence pregnancy outcome.2

Childhood hardships are associated with health behaviors, including smoking as an adult,68 as well as numerous health outcomes in adulthood including depression, affective disturbances, somatic disturbances, and substance use and abuse.8,9 These associations are stable over time, despite changing environments and secular trends.10 Childhood hardships are also associated with increased risk of ischemic heart disease,11 obesity, and diabetes mellitus.12 These hardships also raise the risk for chronic obstructive pulmonary disease, with the association being partly accounted for by smoking behavior.13

There are several pathways through which childhood hardships could also influence pregnancy outcomes. First, hardships could directly alter the hormonal, cardiovascular, or metabolic milieu in a way that influences pregnancy outcomes, for instance, by raising cortisol levels,14 raising the risk of hypertensive disorders of pregnancy, or increasing the propensity for diabetes. The concept of allostatic load encapsulates the idea that chronic exposure to psychosocial stressors over time wears down physiologic systems that are responsible for homeostasis and leads to altered regulation over time.15 Hardships could also indirectly affect pregnancy through effects on health behaviors. Smoking and other health behaviors are strongly associated with LBW in particular.1618 Finally, psychological risk factors, such as maternal depression, have also been associated with both childhood hardships8 and adverse birth outcomes.19

To date, a paucity of research has specifically examined childhood experiences and reproductive outcomes. One study found that childhood adverse experiences, such as sexual abuse or substance abuse in the household, were associated with an increased risk of fetal death in first pregnancy.20 Women who had experienced sexual abuse had more pelvic pain and were less likely to have an episiotomy but were not otherwise at increased risk for birth complications.21 Childhood abuse has also been associated with increased risk of common pregnancy-related complications, such as heartburn, nausea and vomiting, incontinence, and backache.22

The objective of this study was to examine the associations between childhood hardship and reproductive outcomes in a longitudinal study. We hypothesize that women exposed to greater childhood hardships would have an elevated risk for poor pregnancy outcomes. Improved understanding of the contribution of childhood factors to women's reproductive health may inform public health approaches to addressing disparities in birth outcomes. This study is unique in that we used a longitudinal birth cohort with prospective measurement of childhood hardships, health risk behaviors, and future pregnancy outcomes.

The National Child Development Study was a cohort study of children born in Great Britain during 1 week of March 1958. Originally, 17 638 participants were enrolled (with an additional 920 immigrants added before age 16 years), and participants have been followed up at ages 7, 11, 23, 33, and 41. Seventy-three percent participated at either age 33 or 41 years,23 with a small bias toward losses from the unskilled manual labor social class.24 The current study is based on all singleton live births to female cohort members by age 41 years (10 699 births to 4954 women). Four thousand eight hundred sixty-five women (10 134 pregnancies; 95%) had complete information on LBW status, PTB, and smoking status for at least 1 pregnancy. All women had information on at least 1 childhood hardship; missing data numbers for specific hardships are provided in the Tables.

North Thames Multi-Centre Research Ethics Committee approved the 41-year survey and the current analysis was approved by the institutional review board of Tulane University.

ASSESSMENT OF THE OUTCOME

At the 33-year and 41-year follow-ups, cohort members were asked if they had ever been pregnant and, if so, the outcome of each pregnancy (miscarriage, abortion, stillbirth, live birth), the gestational age, and the birth weight of the baby. Two outcomes were identified: (1) LBW, defined as a birth weight lower than 2500 g and (2) PTB, delivery more than 3 weeks prior to the estimated date. Participants were also asked if they smoked before or during the pregnancy.

ASSESSMENT OF THE EXPOSURE

The phrase “childhood hardship” is used herein to refer to a number of adverse situations in childhood. Childhood hardships were measured in several ways during the study (Table 1). A local authority health visitor interviewed the parents (usually the mothers) at ages 7, 11, and 16 years; the cohort members were also interviewed at age 16 years. Principal components analysis was used to categorize the childhood hardships. We performed an exploratory factor analysis using the maximum likelihood method followed by the oblique (promax) rotation. Items with factor loadings more than 0.45 were assigned to the factor for which they had the greatest loading. A 6-factor solution was chosen because of parsimony and consistency with theoretically predetermined latent constructs of types of hardships. Financial and structural hardship was represented by unemployment, being eligible for free school lunches, sharing a bed at ages 11 or 16 years, and contact with the criminal justice system. Parental lack of interest in education was represented by parents' lack of interest in education and hope their child would leave school at the minimum age. Indicators of family dysfunction were family problems with tension, alcoholism, or other problems (reported by the health visitor). Lack of supportive caregiving was represented by parents not reading to the child and the father not taking an active role in the child's upbringing. Violence/mental health/social services issues were represented by physical neglect (teacher report), maladjustment, mental health, bullying, and contact with social services. Family structure disruption was represented by being in foster care, divorced parents, single mother, and parent dead (by age 16 years). For items measured more than once, participants were categorized as having experienced it if it was reported at any point. Within each factor, the number of different types of hardships within that factor was considered to be a proxy for severity of that adversity type. We summed the number of hardships in each factor and created scales for each factor. A final summary indicator, the number of overall hardships, was also examined. The number of hardships in each category was assessed, and the top categories collapsed to retain reasonable category numbers.

Table Graphic Jump LocationTable 1. Description of Childhood Hardship Factors

Finally, we examined hardships by the time they occurred. Hardships were separated into prepubertal (≤11 years) and adolescent (16 years). Three of the categories allowed for comparison of timing effects: lack of interest in education, family structure, and violence/mental health. Financial hardship was also measured comparably on more than 1 occasion, but there was too little variation over time to allow for comparison between early (prepubertal) and late (adolescent) hardships. However, this measure was used with the 3 others for the construction of an overall score for number of hardships.

CONFOUNDERS AND ADULTHOOD MEDIATORS

The most basic potential confounders of the hardship–birth outcome association were considered to be age at the time of pregnancy, interbirth interval,25 and prepregnancy body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared). Weights and heights were self-reported at ages 23 and 41 years and measured at age 33 years; the measures closest in time to the birth of the child were used to calculate BMI. Smoking during any trimester of the pregnancy was counted as smoking during pregnancy but could vary from pregnancy to pregnancy. Finally, we examined indicators of adult social position: social class at the time of the birth (calculated from own or partner's occupation, using the Registrar General's Social Class classification 1-5),26 partnership status at time of birth (married/partnered or not), and educational level (indicated by qualifications: none, less than O level or equivalent, O level or equivalent, A level, or higher). For the smoking analysis, we also examined grandmaternal smoking, characterized as reported smoking during pregnancy (heavy, medium, variable) or nonsmoker. More extensive adjustment for confounders, including alcohol use, adult income, and adult weight gain, did not add substantial information to the results and hence we omit them.

STATISTICAL ANALYSIS

Models were created using generalized estimating equations, with an exchangeable working correlation matrix. This allowed us to consider all the pregnancies reported by each woman, while adjusting for intrawoman correlation. Logistic models were used for dichotomous outcomes (LBW/PTB/smoking). One model predicted smoking during pregnancy, with adjustment for adult social class and grandmaternal smoking. For birth outcomes, 2 models were run: model 1 was unadjusted and model 2 adjusted for age, interbirth interval, prepregnancy BMI, smoking during pregnancy, adult social class, level of education, and relationship status at the time of the birth. One thousand eighty-six cohort members (22%) were missing data on at least 1 confounder, most often BMI. Multiple imputation, using SAS PROC MI and PROC MIANALYZE (SAS Institute Inc, Cary, North Carolina), was used to impute missing values for confounders; results are presented using these imputed values. Similar results were obtained when repeating the analyses in the sample for cohort members with complete information (n = 7823 pregnancies). All analyses were done with SAS version 9.1.

Most women in this population had their first child in their 20s. Most had 1, 2, or 3 children in their lifetime, and about half were current or former smokers (Table 2). There was little racial or ethnic diversity in this sample (96% European/white).

Table Graphic Jump LocationTable 2. Description of Study Population (4865 Women With at Least 1 Singleton Live Birth)

The prevalence of childhood hardships ranged from less than 1% (family problems with alcohol) to almost 30% (father did not take an interest in child's schooling). Generally, financial problems and minor neglect, particularly from the father, were the most common issues.

In their first pregnancy, 7.9% (n = 385) of women gave birth to a LBW baby, while 7.5% (n = 349) gave birth more than 3 weeks early in their first pregnancy. Overall, 5.8% of pregnancies resulted in a LBW baby, while 6.5% resulted in PTB. Thirty-nine percent (n = 1875) of women had smoked at some point during their first pregnancy. Childhood hardships were associated with smoking during pregnancy, and the risk increased with number of adversities (Table 3). This held even after adjusting for grandmaternal smoking and social class as an adult.

Table Graphic Jump LocationTable 3. Associations Between Childhood Hardship and Smoking in Pregnancy in 4865 Women

In bivariate analysis, the majority of childhood hardships were associated with increased risk for LBW for women, with odds ratios (ORs) ranging from 1.2 to 1.9 (Table 4). Most strongly associated were violence/mental health issues and the number of hardships. Adjustment for age, BMI, and interbirth interval did not significantly reduce these associations. Adjustment for smoking weakened the association, as did adjustment for adult social position. Many associations were null or near to null when adjusting for all the variables. Results were similar, with largely overlapping confidence intervals (CIs), when small for gestational age (birth weight < 10th percentile for gestational age) was modeled (eTable 1) or when data were limited to LBW without PTB (data not shown). In unadjusted analyses, several childhood hardships were associated with moderately increased risk of PTB (Table 4). Most strongly associated were lack of parental interest in education, violence/mental health issues, and overall hardships. These associations were attenuated by adjustment for smoking and other covariates, with a relation persisting between family structure, the overall number of adversities, and PTB. Of the individual hardships that made up the subscales, most strongly associated with LBW were contact with social services (adjusted OR [AOR], 1.30; 95% CI, 1.07-1.60), not getting on with one's father (AOR, 1.38; 95% CI, 0.97-1.96), and maladjustment (AOR, 1.28; 95% CI, 0.98-1.66). Most strongly associated with PTB were contact with social services (AOR, 1.22; 95% CI, 1.01-1.47), not getting on with one's father (AOR, 1.44; 95% CI, 1.01-2.05), and alcoholism (AOR, 2.15; 95% CI, 0.87-5.31) (complete data in eTable 2).

Table Graphic Jump LocationTable 4. Associations Between Childhood Hardship, LBW, and PTM in 4865 Women

When results were examined by timing of exposure (Table 5), family structure hardships and violence/mental health hardships most strongly influenced the birth outcomes if they happened in adolescence. Overall, the highest risk for both LBW and PTB was in those who had multiple hardships in adolescence only, but this was also a very small group. Otherwise, hardships at any time raised the risk of LBW, and multiple early hardships or any adolescent hardship raised the risk of PTB.

Table Graphic Jump LocationTable 5. Associations Between Timing of Childhood Hardship, LBW, and PTB in 4865 Women

In this analysis, we found a graded association between cumulative childhood hardships and elevated risk of smoking during pregnancy, LBW, and PTB. Most predictive were violence and mental health issues in the family, as well as the overall number of hardships experienced. Generally, hardships experienced during adolescence were most strongly associated with birth outcomes. This could be because adolescence is particularly salient; they occurred closer in time to the pregnancy; or they were measured or recalled more accurately. Adjustment for confounders and putative intermediates, particularly adult social position and smoking in pregnancy, reduced the strength of or fully accounted for associations between childhood hardship types and LBW and PTB. Our study is consistent with previous work showing associations between childhood hardships and smoking behavior.6,7,27 To date, few studies have addressed the impact of childhood hardships on pregnancy outcomes; as this is one of the first studies to evaluate the relation of childhood adversities and pregnancy outcomes prospectively, our findings make a significant contribution to the literature on the role of early life adversity and the reproductive health trajectory for women.

We adjusted for several important confounders. This analysis strategy is problematic when, as in this case, the factors considered as “confounders” could be intermediates or both confounders and intermediates. For example, both age at pregnancy and BMI have been associated with childhood hardships and social class12,27 and are also associated with pregnancy outcomes. Although a reduction in effect size could suggest mediation, it cannot be used to prove it.28

This study has several strengths, including the prospective measure of childhood hardships, the standardized and extensive protocol, and more than 4 decades of follow-up in a large, nationally representative cohort. In addition, there is an added strength in the triangulation of observations on hardships from the mother, the participant during adolescence, and the social visitor/teacher. However, a significant limitation is the intermittent measurement of hardships, some of which were measured only a single time in childhood. Exposure to neglect, abuse, and alcoholism are likely to be underascertained.29,30 In addition, all birth outcomes were reported by the mother, not directly measured, although research indicates that maternal reports of birth weight and gestational age are largely accurate.3133 Also, the period of the study means that report of gestational age is likely to be based on last menstrual period rather than ultrasonography, which is more prone to error.34 Finally, the sample has been reduced over time; those who were successfully traced and who consented to be reinterviewed differ from the overall sample, though bias by social class has not been found to be extensive.24

In summary, our findings suggest that mothers who have experienced childhood hardship are more likely to smoke during pregnancy. They also more often give birth to LBW babies who are born prematurely, but this association may be primarily due to health behaviors and associated social class. Cumulative hardships in childhood appear to have an enduring impact on birth outcomes, while greater number of exposures in adolescence or childhood and adolescence has a stronger impact on outcomes than exposure in childhood alone. These findings suggest that there are critical periods for elevated risk, as well as a cumulative effect of hardships over time. Further research is needed to specify pathways between childhood adversities and reproductive health outcomes and to evaluate protective factors that could help to alleviate long-term influences of early adversity.

Correspondence: Emily W. Harville, PhD, 1440 Canal St SL-18, New Orleans, LA 70112-2715 (harville@tulane.edu).

Accepted for Publication: January 13, 2010.

Author Contributions:Study concept and design: Harville, Boynton-Jarrett, and Hyppönen. Acquisition of data: Harville, Power, and Hyppönen. Analysis and interpretation of data: Harville, Boynton-Jarrett, Power, and Hyppönen. Drafting of the manuscript: Harville and Boynton-Jarrett. Critical revision of the manuscript for important intellectual content: Harville, Boynton-Jarrett, Power, and Hyppönen. Statistical analysis: Harville, Boynton-Jarrett, and Hyppönen. Obtained funding: Hyppönen. Study supervision: Hyppönen.

Financial Disclosure: None reported.

Funding/Support: Dr Harville was supported by grant K12HD043451 from the National Institute of Child Health and Human Development. Dr Boynton-Jarrett was supported by Building Interdisciplinary Research Careers in Women's Health K12 HD043444 National Institutes of Health Office of Women's Health Research and the William T. Grant Foundation. Dr Hyppönen is funded by a Department of Health (England) Career Scientist Award. The Centre for Epidemiology of Child Health is funded by the Medical Research Council. Great Ormond Street Hospital for Children National Health Service Trust/University College London Institute of Child Health receives a proportion of funding from the Department of Health National Institute for Health Research Biomedical Research Centres funding scheme.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Child Health and Human Development or the National Institutes of Health.

Hoffman  SHatch  MC Stress, social support and pregnancy outcome: a reassessment based on recent research. Paediatr Perinat Epidemiol 1996;10 (4) 380- 405
PubMed Link to Article
Hogue  CJBremner  JD Stress model for research into preterm delivery among black women. Am J Obstet Gynecol 2005;192 (5) ((suppl)) S47- S55
PubMed Link to Article
Tiedje  LB Psychosocial pathways to prematurity: changing our thinking toward a lifecourse and community approach. J Obstet Gynecol Neonatal Nurs 2003;32 (5) 650- 658
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Ashton  DMLawrence  HC  IIIAdams  NL  IIIFleischman  AR Surgeon general's conference on the prevention of preterm birth. Obstet Gynecol 2009;113 (4) 925- 930
PubMed Link to Article
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PubMed Link to Article
van Loon  AJTijhuis  MSurtees  PGOrmel  J Determinants of smoking status: cross-sectional data on smoking initiation and cessation. Eur J Public Health 2005;15 (3) 256- 261
PubMed Link to Article
Anda  RFCroft  JBFelitti  VJ  et al.  Adverse childhood experiences and smoking during adolescence and adulthood. JAMA 1999;282 (17) 1652- 1658
PubMed Link to Article
Holzman  CEyster  JTiedje  LBRoman  LSeagull  ERahbar  MH A life course perspective on depressive symptoms in mid-pregnancy. Matern Child Health J 2006;10 (2) 1092- 7875
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Anda  RFFelitti  VJBremner  JD  et al.  The enduring effects of abuse and related adverse experiences in childhood: a convergence of evidence from neurobiology and epidemiology. Eur Arch Psychiatry Clin Neurosci 2006;256 (3) 174- 186
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Dube  SRFelitti  VJDong  MGiles  WHAnda  RF The impact of adverse childhood experiences on health problems: evidence from four birth cohorts dating back to 1900. Prev Med 2003;37 (3) 268- 277
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Dong  MGiles  WHFelitti  VJ  et al.  Insights into causal pathways for ischemic heart disease: adverse childhood experiences study. Circulation 2004;110 (13) 1761- 1766
PubMed Link to Article
Thomas  CHypponen  EPower  C Obesity and type 2 diabetes risk in midadult life: the role of childhood adversity. Pediatrics 2008;121 (5) e1240- e1249
PubMed Link to Article
Anda  RFBrown  DWDube  SRBremner  JDFelitti  VJGiles  WH Adverse childhood experiences and chronic obstructive pulmonary disease in adults. Am J Prev Med 2008;34 (5) 396- 403
PubMed Link to Article
Field  TDiego  M Cortisol: the culprit prenatal stress variable [published online August 1, 2008]. Int J Neurosci 2008;1181- 1205
PubMed
McEwen  BSWingfield  JC The concept of allostasis in biology and biomedicine. Horm Behav 2003;43 (1) 2- 15
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Kramer  MS Determinants of low birth weight: methodological assessment and meta-analysis. Bull World Health Organ 1987;65 (5) 663- 737
PubMed
Berkowitz  GS An epidemiologic study of preterm delivery. Am J Epidemiol 1981;113 (1) 81- 92
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Lang  JMLieberman  ECohen  A A comparison of risk factors for preterm labor and term small-for-gestational-age birth. Epidemiology 1996;7 (4) 369- 376
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Kaufman  JSMaclehose  RFKaufman  S A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation. Epidemiol Perspect Innov 2004;1 (1) 4
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MacKenzie  GBlaney  RChivers  AVincent  OE The incidence of child sexual abuse in Northern Ireland. Int J Epidemiol 1993;22 (2) 299- 305
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Herman-Giddens  MEBrown  GVerbiest  S  et al.  Underascertainment of child abuse mortality in the United States. JAMA 1999;282 (5) 463- 467
PubMed Link to Article
Tate  ARDezateux  CCole  TJDavidson  LMillennium Cohort Study Child Health Group, Factors affecting a mother's recall of her baby's birth weight. Int J Epidemiol 2005;34 (3) 688- 695
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Troude  PL'Helias  LFRaison-Boulley  AM  et al.  Perinatal factors reported by mothers: do they agree with medical records? Eur J Epidemiol 2008;23 (8) 557- 564
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PubMed Link to Article
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PubMed Link to Article

Figures

Tables

Table Graphic Jump LocationTable 1. Description of Childhood Hardship Factors
Table Graphic Jump LocationTable 2. Description of Study Population (4865 Women With at Least 1 Singleton Live Birth)
Table Graphic Jump LocationTable 3. Associations Between Childhood Hardship and Smoking in Pregnancy in 4865 Women
Table Graphic Jump LocationTable 4. Associations Between Childhood Hardship, LBW, and PTM in 4865 Women
Table Graphic Jump LocationTable 5. Associations Between Timing of Childhood Hardship, LBW, and PTB in 4865 Women

References

Hoffman  SHatch  MC Stress, social support and pregnancy outcome: a reassessment based on recent research. Paediatr Perinat Epidemiol 1996;10 (4) 380- 405
PubMed Link to Article
Hogue  CJBremner  JD Stress model for research into preterm delivery among black women. Am J Obstet Gynecol 2005;192 (5) ((suppl)) S47- S55
PubMed Link to Article
Tiedje  LB Psychosocial pathways to prematurity: changing our thinking toward a lifecourse and community approach. J Obstet Gynecol Neonatal Nurs 2003;32 (5) 650- 658
PubMed Link to Article
Ashton  DMLawrence  HC  IIIAdams  NL  IIIFleischman  AR Surgeon general's conference on the prevention of preterm birth. Obstet Gynecol 2009;113 (4) 925- 930
PubMed Link to Article
Posner  SFBroussard  DLSappenfield  WMStreeter  NZapata  LBPeck  MG Where are the data to drive policy changes for preconception health and health care? Womens Health Issues 2008;18 (6) ((suppl)) S81- S86
PubMed Link to Article
van Loon  AJTijhuis  MSurtees  PGOrmel  J Determinants of smoking status: cross-sectional data on smoking initiation and cessation. Eur J Public Health 2005;15 (3) 256- 261
PubMed Link to Article
Anda  RFCroft  JBFelitti  VJ  et al.  Adverse childhood experiences and smoking during adolescence and adulthood. JAMA 1999;282 (17) 1652- 1658
PubMed Link to Article
Holzman  CEyster  JTiedje  LBRoman  LSeagull  ERahbar  MH A life course perspective on depressive symptoms in mid-pregnancy. Matern Child Health J 2006;10 (2) 1092- 7875
Link to Article
Anda  RFFelitti  VJBremner  JD  et al.  The enduring effects of abuse and related adverse experiences in childhood: a convergence of evidence from neurobiology and epidemiology. Eur Arch Psychiatry Clin Neurosci 2006;256 (3) 174- 186
PubMed Link to Article
Dube  SRFelitti  VJDong  MGiles  WHAnda  RF The impact of adverse childhood experiences on health problems: evidence from four birth cohorts dating back to 1900. Prev Med 2003;37 (3) 268- 277
PubMed Link to Article
Dong  MGiles  WHFelitti  VJ  et al.  Insights into causal pathways for ischemic heart disease: adverse childhood experiences study. Circulation 2004;110 (13) 1761- 1766
PubMed Link to Article
Thomas  CHypponen  EPower  C Obesity and type 2 diabetes risk in midadult life: the role of childhood adversity. Pediatrics 2008;121 (5) e1240- e1249
PubMed Link to Article
Anda  RFBrown  DWDube  SRBremner  JDFelitti  VJGiles  WH Adverse childhood experiences and chronic obstructive pulmonary disease in adults. Am J Prev Med 2008;34 (5) 396- 403
PubMed Link to Article
Field  TDiego  M Cortisol: the culprit prenatal stress variable [published online August 1, 2008]. Int J Neurosci 2008;1181- 1205
PubMed
McEwen  BSWingfield  JC The concept of allostasis in biology and biomedicine. Horm Behav 2003;43 (1) 2- 15
PubMed Link to Article
Kramer  MS Determinants of low birth weight: methodological assessment and meta-analysis. Bull World Health Organ 1987;65 (5) 663- 737
PubMed
Berkowitz  GS An epidemiologic study of preterm delivery. Am J Epidemiol 1981;113 (1) 81- 92
PubMed
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