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Childhood adversity and women’s cardiometabolic health in adulthood: associations with health behaviors, psychological distress, mood symptoms, and personality



We tested whether childhood adversity is associated with poor cardiometabolic health in adulthood among a sample of overweight or obese Dutch women of reproductive age. Health behaviors, psychological distress, mood symptoms, or personality traits were included as potential mediators.


Data came from a follow-up visit (N = 115), carried out in 2016/2017, of a randomized controlled lifestyle intervention trial in 577 obese infertile women. The associations between total adversity exposure score and cardiometabolic health were tested with regression models. Sleep, smoking and eating behavior, symptoms of depression, anxiety and stress, and personality traits were potential mediators.


Childhood adversity scores were not associated with cardiometabolic outcomes but were associated with poorer sleep quality score (M = 7.2 (SD = 3.5) for those with ≥2 types of events versus 4.8 (2.9) for those with no events; p = 0.022), higher external eating score (26.4 (8.7) versus 21.8 (10.3); p = 0.038), higher perceived stress score (17.1 (6.8) versus 12.3 (4.5); p = 0.016), post-traumatic stress score (1.9 (1.5) versus 0.6 (1.1); p < 0.001), and lower agreeableness score (28.2 (4.2) versus 30.3 (3.1); p = 0.035).


Childhood adversity was associated with poorer health behaviors including sleep and eating behavior, and more stress-related symptoms, but not with women’s cardiometabolic health.

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Childhood is an important developmental period during which exposure to adverse interpersonal or environmental events can meaningfully impact several domains of development and health [1, 2]. Childhood adversity is relatively common, such that in high-income countries the prevalence of having experienced at least one adverse event during childhood was estimated to be almost 40% by the WHO World Mental Health Survey [3]. More recently, in the U.S., the prevalence of exposure to violence, crime or abuse in children and youth was estimated to be as high as 58% [4]. Childhood adversity has negative effects on psychosocial and physical development [2, 5]. For example, people who experienced childhood adversity are more likely to be overweight or obese [6], have higher blood pressures [7], and an increased risk of type 2 diabetes in adulthood [8]. There are indications of increased risks of cancer and premature mortality too [2, 9,10,11].

Childhood adversity can come in the form of a broad array of types of events. These include witnessing a natural disaster, severe accidents, suffering from severe illness, or the death of someone close. However, being a victim of interpersonal trauma, including child abuse and sexual abuse, is more likely to result in mental health problems than other types of events [12]. It is not clear whether this association is also stronger for physical health outcomes.

Childhood adversity may directly impact cardiometabolic health. A large body of evidence suggests a direct effect of early life conditions on later development and health. The developmental origins of health and disease hypothesis [13] states that environmental stressors in early life during critical periods of development affect health and disease, such as increasing the risks of cardiovascular disease and mortality [14], through alterations in the body’s physiology, immune and vascular functioning, increased levels of stress hormones, and higher rates of glucose intolerance [1, 7, 13, 15].

Besides a possible direct effect, childhood adversity may impact cardiometabolic health in an indirect manner. For example, childhood adversity has been linked with several negative health behaviors in adulthood, such as poor sleep quality [16], smoking [17] and an unhealthy diet [6], which are known to increase the risk of cardiometabolic diseases [18,19,20]. This suggests the association between childhood adversity and poor cardiometabolic health may be at least partially mediated by adverse health behaviors [21].

Psychological distress and mood symptoms are other potential mediators in the association between childhood adversity and poor cardiometabolic health [22]. Childhood adversity has been associated with high levels of perceived stress later in life [23]. Depressive symptoms, anxiety symptoms [24, 25], and also early-onset psychiatric disorders like pre-school onset depression, attention-deficit disorder, oppositional defiant disorder, conduct disorder, post-traumatic stress disorder (PTSD), generalized anxiety disorder, and separation anxiety [26], each have been shown to occur more often after early life adversity, and these may increase the risk for heart disease [27,28,29,30]. Indeed, findings from a systematic review showed that psychological distress and mood symptoms partly mediate the association between childhood adversity and cardiometabolic outcomes [31].

Personality is another factor that could partially mediate the negative effects of childhood adversity on cardiometabolic health. People who have experienced childhood adversity have higher levels of neuroticism [32], and lower levels of conscientiousness and openness to experience [33]. People who have experienced childhood adversity more often have type D personality, which is a combination of social inhibition and negative affectivity [34]. Low conscientiousness and high neuroticism are linked to poorer physical health [35], and type D personality is a documented risk factor for cardiovascular morbidity and mortality [36]. Collectively, these findings point to the possibility of personality traits partially mediating the effects of early adversity on later cardiometabolic health. Indeed, there is some evidence for this. One longitudinal study demonstrated that the effect of childhood adversity on cardiometabolic health in adolescence was mediated by levels of positive personality traits, such that those who experienced greater early adversity had lower levels of positive traits [37].

Demographic characteristics may be important in childhood adversity research. For example, the prevalence of childhood adversity seems to differ among racial/ethnic groups and is related to income disparities, such that Black and Hispanic children, as well as those from low-income families, are exposed to more adversity [38]. Compared to the U.S., income disparities in the Netherlands are small and there are fewer racial/ethnic minorities, and it is important to assess the impact of childhood adversity on cardiometabolic health in countries with different racial and ethnic demographics and variations in income gaps [39]. Furthermore, the association between childhood adversity and cardiometabolic health was shown to be more pronounced in women [40], indicating that there might be sex-specific effects that merit deeper focus on female samples.

From a prevention point of view, the investigation of potential indirect effects of childhood adversity on cardiometabolic health may provide insight into potential intermediate targets for intervention, if prevention of the adversity is not possible. This could result in better cardiometabolic health outcomes in the long-term for people who have experienced childhood adversity.

In the current study, using a Dutch sample of overweight and obese women of reproductive age, we examined whether childhood adversity (as a total score, but also interpersonal victimization specifically) was associated with poorer cardiometabolic health in adulthood. We also examined whether the association between childhood adversity and later cardiometabolic health was mediated by adverse health behaviors, psychological distress, mood symptoms, or specific personality traits.


In the original randomized controlled trial (RCT), carried out in the Netherlands, 577 obese infertile women were allocated to either a six-month lifestyle intervention or a control group. Women were eligible for participation in the RCT if they were between 18 and 39 years of age, had a body mass index (BMI) of ≥29 kg/m2, and were infertile. Women with severe endometriosis, premature ovarian insufficiency, endocrinopathy, untreated preexisting hypertension, or women with a history of hypertension related pregnancy complications were not eligible for participation. The RCT was carried out in 23 hospitals and resulted in 822 women who were eligible for participation, 245 of these women decided not to participate, leaving 577 women who provided written informed consent. At the time of randomization, women were approximately 30 years old, had a mean weight of 103 kg and a mean BMI of 36 kg/m2 (range = 29–51). Results of the primary and secondary outcomes of this trial have been published previously [41, 42] and demonstrated that rates of a vaginal birth of a healthy singleton at 37 weeks or more were not higher in the intervention group, compared to the control group. The lifestyle intervention did lead to weight loss and improved cardiometabolic health in the short-term. The study was conducted following the principles of the Declaration of Helsinki, approved by the medical ethics committee of the University Medical Centre Groningen (METc code: 2008/284) and all participants gave written informed consent.


The follow-up visit of the RCT was carried out between 3 and 8 years (mean = 5 years) after baseline assessments. The protocol of the follow-up visit has been published [43]. In short, between July 2016 and September 2017, a total of 115 women who participated in the follow-up visit filled out questionnaires regarding personality, physical health, psychological distress, mood symptoms, and life events. To evaluate adversity exposure during childhood and adolescence, the 17-item Life Events Checklist for DSM-5 (LEC-5) [44] was used. This questionnaire was slightly modified to be able to distinguish childhood adversity (between birth and 18 years of age); for events that a person experienced or witnessed, the year in which the event took place was asked and later used to calculate age at exposure. We calculated two total scores. The first score was a total adversity exposure score with all items summed (if a woman reported any type of event occurring once or more before the age of 19, she received a score of one for experiencing that type of event during childhood). Based on these scores, participants were then divided into three categories: a group that did not experience any type of event; a group that experienced one type of event; and a group that experienced two or more types of events. To be able to conduct sensitivity analyses to ascertain whether associations were stronger for interpersonal victimization-events, a second score, interpersonal victimization, was calculated. This score included physical assault, sexual assault, and unwanted or uncomfortable sexual experiences, based on previous research indicating the greater relative impact of these type of events on health [12]. This variable was scored dichotomously, such that if a woman experienced this type of event at any point during childhood she received a score of one, and if she never experienced these events she received a score of zero. Thus, a dichotomous interpersonal victimization score reflected physical and sexual assault directly experienced by the individual during childhood, and the 3-point total adversity score included those experiences as well as events that occurred more broadly in the woman’s environment during childhood.

Health behaviors were assessed across three domains. Sleep quality was measured using the Pittsburg Sleep Quality Index (PSQI), a 19-item questionnaire that has been shown to have good internal consistency (Cronbach’s alpha (α) = 0.83) [45]. Smoking behavior was assessed via one item “Are you a current smoker?” (yes or no). To assess eating behavior, the Dutch Eating Behavior Questionnaire (DEBQ) was used, which resulted in three scores: external eating, restrained eating and emotional eating [46]. External eating reflects the sensitivity to external food cues, like the presence of food or taste, restrained eating reflects dieting attitudes and behaviors, and emotional eating reflects eating as coping mechanism to handle negative emotions. The DEBQ has demonstrated high internal consistency and subscale validity [46].

Psychological distress and mood symptoms were assessed with three questionnaires. Symptoms of anxiety and depression were assessed with the 14-item Hospital Anxiety and Depression Scale (HADS), resulting in summed anxiety and depression scores, with previous reports of good reliability (α depression = 0.82; α anxiety = 0.83) [47, 48]. The primary care PTSD screen (PC-PTSD), a short 5-item questionnaire with a total summed score, was used to screen for symptoms of post-traumatic stress disorder (PTSD) [49]. This questionnaire has demonstrated excellent diagnostic accuracy [49]. Perceived stress was measured with the 10-item summed Perceived Stress Scale (PSS), a questionnaire that has demonstrated excellent reliability (α = 0.89) [50, 51].

Personality was measured with two scales. The Big Five Inventory (BFI), a 44-item questionnaire, measures five dimensions of personality: extraversion, agreeableness, conscientiousness, neuroticism and openness [52], with previous reported reliability ranging from α = 0.73 to 0.86 [53]. The Type D Scale (DS-14), a 14-item questionnaire, measures type-D personality [54] and also has demonstrated good overall reliability previously, α = 0.87 [54]. The two components of type-D personality also demonstrated good reliability in previous research; social inhibition (α = 0.86) and negative affectivity (α = 0.88).

Physical examination to assess cardiometabolic health

Physical examinations were performed by trained research staff in a mobile research vehicle, parked near the participant’s house. Height, weight, waist- and hip-circumference were each measured twice, and a third time if there was a large difference (> 0.5 kg for weight, > 0.5 cm for height and > 1 cm for waist- and hip-circumference) between the first two measurements. After a five-minute resting period, seated blood pressure was measured three times. Fasting blood samples were drawn by trained nurses, and the biochemical analyses were performed by the AMC Clinical Chemistry Laboratory. From the fasting blood samples, continuous levels of glucose, triglycerides, high-density lipoprotein cholesterol (HDL-C) were obtained.

To assess the presence of metabolic syndrome, a reflection of composite cardiometabolic health, cut-off values for obesity, hyperglycemia, dyslipidemia (HDL-C and triglycerides) and hypertension were calculated based on the US National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria [55]. A positive classification of metabolic syndrome was based on having three or more elements either above the cut-off values, or based on pharmacological treatment for hyperglycemia, dyslipidemia or hypertension.

Statistical analysis

Demographic characteristics were examined with ANOVA or chi-square tests. A model with the visual representation of the associations tested is shown in Fig. 1, including the specific paths described below. ANOVA models and chi-square tests were used to test the difference in cardiometabolic health outcomes (individual measures and the composite classification score) between the groups with zero, one or ≥ 2 different types of childhood adversity, and in the sensitivity analysis between the groups with and without interpersonal victimization (path C). Second, the associations between childhood adversity levels and potential mediators (personality traits, psychological distress, mood symptoms and health behavior variables) were tested using ANOVA models and Tukey post-hoc tests (path A). The third set of analyses utilized a univariate (logistic) regression model examining the association between the mediators (personality, psychological distress, mood symptoms and health behavior) and the composite and individual cardiometabolic health outcomes (path B). To adjust for the possibility that intervention status affected the association of interest, sensitivity analyses were run that included the covariate representing randomization group in all models. All statistical analyses were performed using IBM SPSS version 24.0 (Armonk, NY, USA).

Fig. 1

Visual model with the hypothesized main effect and mediation effects. Note: The mediators in this model include health behavior (sleep quality, smoking behavior and external, restrained, and emotional eating behavior), psychological distress and mood symptoms (symptoms of depression, anxiety, perceived stress and post-traumatic stress symptoms), and personality (openness, conscientiousness, extraversion, agreeableness, neuroticism and type D personality)


Types of adverse events and participant characteristics

The adversity exposure groups and interpersonal victimization groups were similar in demographic characteristics (Table 1). In our sample, n = 69 (57.4%) reported no childhood adverse events, n = 29 (25.2%) reported 1 type of childhood adverse event, and n = 17 (14.8%) reported ≥2 types of adverse events in childhood (with n = 7 (6.1%) reporting ≥3 types of events). The most commonly reported adverse event was a transportation accident (n = 18) including car, boat, train and plane accidents, followed by physical assault (n = 11), sexual assault (n = 8), unwanted sexual experiences (n = 8), life threatening illness/injury (n = 7), severe illness or injury (n = 6) and sudden unexpected death of someone close (n = 6).

Table 1 Characteristics of the study participants

Associations between childhood adversity and cardiometabolic health

No differences were observed in cardiometabolic health outcomes between women without adversity or women with one or two or more types of adverse childhood events (Table 2). No group differences were observed in the sensitivity analyses testing the association between interpersonal victimization and cardiometabolic health either.

Table 2 Childhood adversity and cardiometabolic health outcomes (path C)

Associations between childhood adversity and potential mediators

Total adversity score

Sleep quality scores were higher, reflecting worse sleep quality, in women with ≥2 types of childhood adverse events (7.2 (3.5)), compared to women without adversity (4.8 (2.9); p = 0.022). Also, higher external eating scores were observed in women with 1 type of childhood adverse event (26.4 (8.7)), compared to women without adversity (21.8 (10.3); p = 0.038). No differences were observed for symptoms of depression and anxiety between the groups. Levels of perceived stress were significantly higher among women with ≥2 types of childhood adverse events (17.1 (6.8)), compared to women with 1 type of childhood adverse event (12.3 (4.5); p = 0.016). Furthermore, higher rates of PTSD symptoms were found in women with ≥2 types of childhood adverse events (1.9 (1.5)), compared to women without adversity (0.6 (1.1); p < 0.001). For agreeableness, a significantly lower score was found in women with 1 type of adverse event (28.2 (4.2)), compared to the group without adverse events (30.1 (3.1); p = 0.035) (Table 3).

Table 3 Childhood adversity and health behavior, psychological distress, mood symptoms and personality (path A)

Interpersonal adversity

The sensitivity analyses focused on exposure to interpersonal victimization during childhood paralleled the associations observed for the total adversity score described above. In addition to those associations, women with childhood interpersonal victimization were more often smokers (n = 7 (31.8%); p = 0.048) than those without interpersonal victimization (n = 9 (10.7%)). A positive score on the type D personality subscale negative affectivity was more prevalent in women with childhood interpersonal victimization (n = 16 (72.7%)), compared to those without (n = 42 (45.2%); p = 0.020). Women with interpersonal victimization reported lower conscientiousness (26.6 (4.3)), compared to women without interpersonal victimization (28.7 (3.9); p = 0.030).

Associations between potential mediators and cardiometabolic health

No statistically significant associations were observed for path B between health behaviors and cardiometabolic health outcomes (shown in Table 4) or between psychological distress, mood symptoms, personality and cardiometabolic health (shown in Tables 5 and 6). Repeating the analyses with intervention randomization group as a covariate did not change the results presented in Tables 2, 3, 4, 5 and 6. Due to the lack of associations between childhood adversity and cardiometabolic health variables, no formal tests of mediation were conducted.

Table 4 Health behaviors and cardiometabolic health outcomes (path B)
Table 5 Psychological distress, mood symptoms and cardiometabolic health (path B)
Table 6 Personality and cardiometabolic health (path B)


Within an understudied population of overweight and obese Dutch women of reproductive age, the present study provides evidence that childhood adversity is associated with poorer health behaviors, including sleep quality and eating behavior, and more stress-related symptoms in adulthood. However, childhood adversity was not associated with cardiometabolic health outcomes in these women.

The associations we observed between childhood adversity and various indices of health behaviors, psychological distress, and personality are in line with previous research. As in other studies, we found a higher prevalence of smoking [17], a higher prevalence of negative affectivity, one of the subscales of type D personality [34], and lower levels of conscientiousness [32, 33] among those who experienced interpersonal victimization during childhood. The associations between childhood adversity and higher levels of perceived stress and PTSD symptoms are also in line with previous research ([23, 26]), as are the associations between childhood adversity and lower sleep quality [16] and unhealthy eating behavior [6]. We found a positive association between childhood adversity and external eating behavior, where external factors, like the presence of food or the smell of food, lead to more eating [46], which is a finding not previously observed, to our knowledge. This suggests that childhood adversity may lead to more external eating behavior, which is linked to increased rates of overweight and obesity [56].

We observed associations in the analyses with childhood interpersonal victimization that were not observed in the analyses with total childhood adversity exposure. Women who had experienced interpersonal victimization were more often smokers, had more often negative affect and lower scores on conscientiousness. The observation regarding smoking behavior is in line with previous work, suggesting that interpersonal victimization affects health behavior more than other types of childhood adversity [12]. The association between childhood interpersonal victimization and personality traits (negative affect and lower conscientiousness) in adulthood has not been described previously for childhood interpersonal victimization specifically. These results suggest childhood interpersonal victimization is linked to a personality characterized by experiencing negative emotions, having less self-discipline and being less goal-oriented. Prior research suggests that these personality traits may lead to increased rates of cardiovascular disease [36, 57].

The results described in this paper regarding associations with cardiometabolic health outcomes contrast those of a large body of existing literature demonstrating the detrimental effects of childhood adversity on cardiometabolic health, cardiovascular disease and mortality [6,7,8,9]. The discrepancy between previous findings and those in the current study may be due to a number of factors. First, the types and severity of childhood adverse events reported in our sample are less severe than the types of adverse events described in the existing literature [9]. The most common adverse event reported in our study was a transportation accident, while the literature suggests that more severe events, like childhood abuse, are associated with long-term health effects [58]. However, the sensitivity analyses conducted with interpersonal victimization as a measure of those more severe events also did not reveal associations with cardiometabolic health in our sample. In addition to the apparent difference in type of events, there appeared to be a difference in the number of people exposed to several severe childhood adverse events, which was uncommon in our sample (6% had experienced ≥3 types of events). A dose-response relationship between childhood adversity and cardiometabolic health has been suggested previously, indicating that exposure to several childhood adversities is associated with poorer cardiometabolic health [9]. The small number of women with exposure to several severe childhood adverse events in our sample precluded a dose-response type of analysis. That said, it was important to discern whether the level of childhood adversity experienced by women in this understudied population played a role in the development of health behaviors, psychological distress, mood symptoms and personality to inform prevention efforts to target these risk factors for cardiometabolic disease.

Another difference between the existing literature examining the association between childhood adversity and cardiometabolic health outcomes and our study is the age of the sample. Our sample consisted of obese women who sought infertility treatment several years prior, whereas other studies conducted analyses among a general population, including predominantly people of older age [7, 9, 10]. The harmful effects of childhood adversity, partially occurring through unhealthy behaviors, psychological distress, mood symptoms and personality traits, on metabolic health and cardiovascular disease may take more time to develop. Even in at-risk populations, women are protected against cardiovascular disease before menopause, as a result of the atheroprotective effects of estrogen [59, 60]. If our study population is followed until after menopause, the effects of childhood adversity on metabolic and cardiovascular disease may be more similar to those found in previous research.

Limitations of this study should be noted. Our results may not be generalizable to a population that includes men. For example, sex-specific findings suggest that men are less vulnerable to the effects of childhood adversity on cardiovascular disease [40]. In addition, the data regarding childhood adversity were collected retrospectively in adulthood, which might have led to recall bias. Individuals experiencing stress or symptoms of depression may be more likely to report childhood adversity, which may lead to overestimating the impact of childhood adversity on the outcomes [59]. Although shorter time intervals between the event and the moment of recall are ideal, it has been suggested that reports of childhood adversity are stable over time and reliable [61]. Limitations notwithstanding, this work contributes to the literature by giving insight in the association between childhood adversity and health behaviors, psychological distress, mood symptoms and personality in an understudied population.


We found that childhood adversity was associated with poorer health behaviors and greater reports of perceived stress and post-traumatic stress symptoms in adulthood. In our sample of overweight and obese women of reproductive age, no association was observed between childhood adversity and cardiometabolic health outcomes. The adverse health behaviors and increased symptoms of stress in women who experienced childhood adversity may induce poorer cardiometabolic health outcomes in the future though, warranting further follow-up of this group.

Availability of data and materials

A minimal dataset is available upon request.



Big five inventory


Body mass index


Dutch eating behavior questionnaire


Type D scale


Hospital anxiety and depression scale


High-density lipoprotein cholesterol


Life events checklist for DSM-5


Primary care – post-traumatic stress disorder


Pittsburg sleep quality index


Perceived stress scale


Post-traumatic stress disorder


Randomized controlled trial


  1. 1.

    Shonkoff JP, Garner AS, Siegel BS, Dobbins MI, Earls MF, Garner AS, McGuinn L, Pascoe J, Wood DL. The lifelong effects of early childhood adversity and toxic stress. Pediatrics. 2012;129(1):e232–46.

    Article  PubMed  Google Scholar 

  2. 2.

    Wegman HL, Stetler C. A meta-analytic review of the effects of childhood abuse on medical outcomes in adulthood. Psychosom Med. 2009;71(8):805–12.

    Article  PubMed  Google Scholar 

  3. 3.

    Kessler RC, McLaughlin KA, Green JG, Gruber MJ, Sampson NA, Zaslavsky AM, Aguilar-Gaxiola S, Alhamzawi AO, Alonso J, Angermeyer M, Benjet C, Bromet E, Chatterji S, de Girolamo G, Demyttenaere K, Fayyad J, Florescu S, Gal G, Gureje O, Haro JM, Hu CY, Karam EG, Kawakami N, Lee S, Lepine JP, Ormel J, Posada-Villa J, Sagar R, Tsang A, Ustun TB, Vassilev S, Viana MC, Williams DR. Childhood adversities and adult psychopathology in the WHO world mental health surveys. Br J Psychiatry. 2010;197(5):378–85.

    Article  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Finkelhor D, Turner HA, Shattuck A, Hamby SL. Violence, crime, and abuse exposure in a national sample of children and youth: an update. JAMA Pediatr. 2013;167(7):614–21.

    Article  PubMed  Google Scholar 

  5. 5.

    Shonkoff JP, Boyce WT, McEwen BS. Neuroscience, molecular biology, and the childhood roots of health disparities: building a new framework for health promotion and disease prevention. Jama. 2009;301(21):2252–9.

    CAS  Article  PubMed  Google Scholar 

  6. 6.

    Isohookana R, Marttunen M, Hakko H, Riipinen P, Riala K. The impact of adverse childhood experiences on obesity and unhealthy weight control behaviors among adolescents. Compr Psychiatry. 2016;71:17–24.

    Article  PubMed  Google Scholar 

  7. 7.

    Alastalo H, Raikkonen K, Pesonen AK, Osmond C, Barker DJ, Heinonen K, Kajantie E, Eriksson JG. Early life stress and blood pressure levels in late adulthood. J Hum Hypertens. 2013;27(2):90–4.

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Huang H, Yan P, Shan Z, Chen S, Li M, Luo C, Gao H, Hao L, Liu L. Adverse childhood experiences and risk of type 2 diabetes: A systematic review and meta-analysis. Metabolism. 2015;64(11):1408–18.

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Appleton AA, Holdsworth E, Ryan M, Tracy M. Measuring childhood adversity in life course cardiovascular research: A systematic review. Psychosom Med. 2017;79(4):434–40.

    Article  PubMed  Google Scholar 

  10. 10.

    Bellis MA, Hughes K, Leckenby N, Hardcastle KA, Perkins C, Lowey H. Measuring mortality and the burden of adult disease associated with adverse childhood experiences in England: a national survey. J Public Health (Oxf). 2015;37(3):445–54.

    CAS  Article  Google Scholar 

  11. 11.

    Chen E, Turiano NA, Mroczek DK, Miller GE. Association of Reports of childhood abuse and all-cause mortality rates in women. JAMA Psychiatry. 2016;73(9):920–7.

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Mongan D, Shannon C, Hanna D, Boyd A, Mulholland C. The association between specific types of childhood adversity and attenuated psychotic symptoms in a community sample. Early Interv Psychiatry. 2017.

    Article  Google Scholar 

  13. 13.

    Barker DJ. Maternal nutrition, fetal nutrition, and disease in later life. Nutrition. 1997;13(9):807–13.

    CAS  Article  Google Scholar 

  14. 14.

    Wilson PWF, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97(18):1837–47.

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Slopen N, Lewis TT, Gruenewald TL, Mujahid MS, Ryff CD, Albert MA, Williams DR. Early life adversity and inflammation in African Americans and whites in the midlife in the United States survey. Psychosom Med. 2010;72(7):694–701.

    Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Kajeepeta S, Gelaye B, Jackson CL, Williams MA. Adverse childhood experiences are associated with adult sleep disorders: a systematic review. Sleep Med. 2015;16(3):320–30.

    Article  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Anda RF, Croft JB, Felitti VJ, Nordenberg D, Giles WH, Williamson DF, Giovino GA. Adverse childhood experiences and smoking during adolescence and adulthood. Jama. 1999;282(17):1652–8.

    CAS  Article  Google Scholar 

  18. 18.

    Cappuccio FP, Cooper D, D'Elia L, Strazzullo P, Miller MA. Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies. Eur Heart J. 2011;32(12):1484–92.

    Article  PubMed  Google Scholar 

  19. 19.

    Ockene IS, Miller NH. Cigarette smoking, cardiovascular disease, and stroke. Circulation. 1997;96(9):3243.

    CAS  Article  Google Scholar 

  20. 20.

    Torres SJ, Nowson CA. Relationship between stress, eating behavior, and obesity. Nutrition. 2007;23(11):887–94.

    Article  PubMed  Google Scholar 

  21. 21.

    Suglia SF, Koenen KC, Boynton-Jarrett R, Chan PS, Clark CJ, Danese A, Faith MS, Goldstein BI, Hayman LL, Isasi CR, Pratt CA, Slopen N, Sumner JA, Turer A, Turer CB, Zachariah JP. Childhood and adolescent adversity and Cardiometabolic outcomes: A scientific statement from the American Heart Association. Circulation. 2017.

  22. 22.

    Bush NR, Lane RD, McLaughlin KA. Mechanisms underlying the association between early-life adversity and physical health: charting a course for the future. Psychosom Med. 2016;78(9):1114–9.

    Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Anda RF, Butchart A, Felitti VJ, Brown DW. Building a Framework for Global Surveillance of the Public Health Implications of Adverse Childhood Experiences. Am J Prev Med. 2010;39(1):93–8.

    Article  PubMed  Google Scholar 

  24. 24.

    Luecken LJ, Jewell SL, MacKinnon DP. Prediction of postpartum weight in low-income Mexican-origin women from childhood experiences of abuse and family conflict. Psychosom Med. 2016;78(9):1104–13.

    Article  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Tomfohr-Madsen LM, Bayrampour H, Tough S. Maternal history of childhood abuse and risk of asthma and allergy in 2-year-old children. Psychosom Med. 2016;78(9):1031–42.

    Article  PubMed  Google Scholar 

  26. 26.

    Whalen DJ, Belden AC, Tillman R, Barch DM, Luby JL. Early adversity, psychopathology, and latent class profiles of global physical health from preschool through early adolescence. Psychosom Med. 2016;78(9):1008–18.

    Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Dedert EA, Calhoun PS, Watkins LL, Sherwood A, Beckham JC. Posttraumatic stress disorder, cardiovascular, and metabolic disease: a review of the evidence. Ann Behav Med. 2010;39(1):61–78.

    Article  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Kinder LS, Carnethon MR, Palaniappan LP, King AC, Fortmann SP. Depression and the metabolic syndrome in young adults: findings from the third National Health and nutrition examination survey. Psychosom Med. 2004;66(3):316–22.

    Article  Google Scholar 

  29. 29.

    Richardson S, Shaffer JA, Falzon L, Krupka D, Davidson KW, Edmondson D. Meta-analysis of perceived stress and its association with incident coronary heart disease. Am J Cardiol. 2012;110(12):1711–6.

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Scott KM. Depression, anxiety and incident cardiometabolic diseases. Curr Opin Psychiatry. 2014;27(4):289–93.

    Article  PubMed  Google Scholar 

  31. 31.

    Basu A, McLaughlin KA, Misra S, Koenen KC. Childhood maltreatment and health impact: the examples of cardiovascular disease and type 2 diabetes mellitus in adults. Clin Psychol (New York). 2017;24(2):125–39.

    Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Wilson RS, Krueger KR, Arnold SE, Barnes LL. Mendes de Leon CF, Bienias JL, Bennett DA. Childhood adversity and psychosocial adjustment in old age. Am J Geriatr Psychiatry. 2006;14(4):307–15.

    Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Fletcher, Jason M. and Schurer, Stefanie. 2017. “Origins of Adulthood Personality: The Role of Adverse Childhood Experiences.” IZA Discussion Paper No. 10538. (Available at SSRN:

  34. 34.

    Demirci K, Yildiz M, Selvi C, Akpinar A. The relationship between childhood trauma and type D personality in university students. Int J Soc Psychiatry. 2016;62(6):542–8.

    Article  PubMed  Google Scholar 

  35. 35.

    Friedman HS. Long-term relations of personality and health: dynamisms, mechanisms, tropisms. J Pers. 2000;68(6):1089–107.

    CAS  Article  Google Scholar 

  36. 36.

    Pedersen SS, Denollet J. Type D personality, cardiac events, and impaired quality of life: a review. Eur J Cardiovasc Prev Rehabil. 2003;10(4):241–8.

    Article  PubMed  Google Scholar 

  37. 37.

    Wickrama KK, O'Neal CW, Lee TK, Wickrama T. Early socioeconomic adversity, youth positive development, and young adults’ cardio-metabolic disease risk. Health Psychol. 2015;34(9):905–14.

    Article  PubMed  Google Scholar 

  38. 38.

    Slopen N, Shonkoff JP, Albert MA, Yoshikawa H, Jacobs A, Stoltz R, Williams DR. Racial disparities in child adversity in the U.S.: interactions with family immigration history and income. Am J Prev Med. 2016;50(1):47–56.

    Article  PubMed  Google Scholar 

  39. 39.

    Netherlands, Statistics. 2014. “Statistics Netherlands: Income gaps stable and relatively small”.

  40. 40.

    Garad Y, Maximova K, MacKinnon N, McGrath JJ, Kozyrskyj AL, Colman I. Sex-specific differences in the association between childhood adversity and cardiovascular disease in adulthood: evidence from a National Cohort Study. Can J Cardiol. 2017;33(8):1013–9.

    Article  PubMed  Google Scholar 

  41. 41.

    Mutsaerts MAQ, van Oers AM, Groen H, Burggraaff JM, Kuchenbecker WKH, Perquin DAM, Koks CAM, van Golde R, Kaaijk EM, Schierbeek JM, Oosterhuis GJE, Broekmans FJ, Bemelmans WJE, Lambalk CB, Verberg MFG, van der Veen F, Klijn NF, Mercelina PEAM, van Kasteren YM, Nap AW, Brinkhuis EA, Vogel NEA, Mulder RJAB, Gondrie ETCM, de Bruin JP, Sikkema JM, de Greef MHG, ter Bogt NCW, Land JA, Mol BWJ, Hoek A. Randomized trial of a lifestyle program in obese infertile women. N Engl J Med. 2016;374(20):1942–53.

    CAS  Article  PubMed  Google Scholar 

  42. 42.

    van Dammen L, Wekker V, van Oers AM, Mutsaerts MAQ, Painter RC, Zwinderman AH, Groen H, van de Beek C, Muller Kobold AC, Kuchenbecker WKH, van Golde R, Oosterhuis GJE, Vogel NEA, Mol BWJ, Roseboom TJ, Hoek A, LIFEstyle study group on behalf of the. Effect of a lifestyle intervention in obese infertile women on cardiometabolic health and quality of life: A randomized controlled trial. PLoS One. 2018;13(1):e0190662.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    van de Beek C, Hoek A, Painter RC, Gemke RJBJ, van Poppel MNM, Geelen A, Groen H, Mol BW, Roseboom TJ. Women, their offspring and iMproving lifestyle for better cardiovascular health of both (WOMB project): a protocol of the follow-up of a multicentre randomised controlled trial. BMJ Open. 2018;8(1):e016579.

    PubMed  PubMed Central  Google Scholar 

  44. 44.

    Gray MJ, Litz BT, Hsu JL, Lombardo TW. Psychometric properties of the life events checklist. Assessment. 2004;11(4):330–41.

    Article  PubMed  Google Scholar 

  45. 45.

    Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213.

    CAS  Article  Google Scholar 

  46. 46.

    van Strien T, Frijters JER, Bergers GPA, Defares PB. The Dutch eating behavior questionnaire (DEBQ) for assessment of restrained, emotional, and external eating behavior. Int J Eat Disord. 1986;5(2):295–315.<295::AID-EAT2260050209>3.0.CO;2-T.

  47. 47.

    Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the hospital anxiety and depression scale. An updated literature review. J Psychosom Res. 2002;52(2):69–77.

    Article  Google Scholar 

  48. 48.

    Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67(6):361–70.

    CAS  Article  Google Scholar 

  49. 49.

    Prins A, Bovin MJ, Smolenski DJ, Marx BP, Kimerling R, Jenkins-Guarnieri MA, Kaloupek DG, Schnurr PP, Kaiser AP, Leyva YE, Tiet QQ. The primary care PTSD screen for DSM-5 (PC-PTSD-5): development and evaluation within a veteran primary care sample. J Gen Intern Med. 2016;31(10):1206–11.

    Article  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–96.

    CAS  Article  Google Scholar 

  51. 51.

    Roberti JW, Harrington LN, Storch EA. Further psychometric support for the 10-item version of the perceived stress scale. J Coll Couns. 2006;9(2):135–47.

    Article  Google Scholar 

  52. 52.

    John OP, Donahue EM, Kentle RL. The big five inventory—versions 4a and 54. Berkeley: University of California, Berkeley, Institute of Personality and Social Research; 1991.

    Google Scholar 

  53. 53.

    Denissen JJA, Geenen R, van Aken MAG, Gosling SD, Potter J. Development and validation of a Dutch translation of the big five inventory (BFI). J Pers Assess. 2008;90(2):152–7.

    Article  PubMed  Google Scholar 

  54. 54.

    Denollet J. DS14: standard assessment of negative affectivity, social inhibition, and type D personality. Psychosom Med. 2005;67(1):89–97.

    Article  PubMed  Google Scholar 

  55. 55.

    Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC, Spertus JA, Costa F. “Diagnosis and Management of the Metabolic Syndrome.” An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112(17):2735–52.

    Article  PubMed  Google Scholar 

  56. 56.

    Braet C, Claus L, Goossens L, Moens E, Van Vlierberghe L, Soetens B. Differences in eating style between overweight and normal-weight youngsters. J Health Psychol. 2008;13(6):733–43.

    Article  Google Scholar 

  57. 57.

    Bogg T, Roberts BW. The case for conscientiousness: evidence and implications for a personality trait marker of health and longevity. Ann Behav Med. 2013;45(3):278–88.

    Article  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Esther MF, Karas MJ, McDevitt SC, Guenewald Tara L, Seeman TE. Childhood adversities and adult Cardiometabolic health: does the quantity, timing, and type of adversity matter? J Aging Health. 2015;27(8):1311–38.

    Article  Google Scholar 

  59. 59.

    Colman I, Kingsbury M, Garad Y, Zeng Y, Naicker K, Patten S, Jones PB, Wild TC, Thompson AH. Consistency in adult reporting of adverse childhood experiences. Psychol Med. 2016;46(3):543–9.

    CAS  Article  PubMed  Google Scholar 

  60. 60.

    Crawford SL, Johannes CB. The epidemiology of cardiovascular disease in postmenopausal women. J Clin Endocrinol Metab. 1999;84(6):1803–12.

    Article  Google Scholar 

  61. 61.

    Yancura LA, Aldwin CM. Stability and change in retrospective reports of childhood experiences over a 5-year period: findings from the Davis longitudinal study. Psychol Aging. 2009;24(3):715–21.

    Article  PubMed  Google Scholar 

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We thank all women who participated in the LIFEstyle study and the follow-up visit. We thank all students, PhD students, research nurses, and other research personnel involved in the LIFEstyle study and follow-up visit.


This research was supported by The Netherlands Organization for Health Research and Development (50–50110–96-518), the Dutch Heart Foundation (Grant number: 2013 T085), and the European Commission (Horizon2020 project ‘DynaHealth’, 633595). The department of obstetrics and gynaecology from the UMCG received an unrestricted educational grant from Ferring Pharmaceutical BV the Netherlands, unrelated to the present study.

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LvD, NB, SdR, BWM, HG, AH, and TR have been responsible for the idea and the design of the study. LvD and NB drafted the manuscript and performed the analyses. All authors revised the manuscript and had critical discussions of the manuscript. All authors have approved the final version of the manuscript.

Corresponding author

Correspondence to Lotte van Dammen.

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The study was conducted following the principles of the Declaration of Helsinki, approved by the medical ethics committee of the University Medical Centre Groningen (METc code: 2008/284) and all participants gave written informed consent.

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The authors declare that they have no competing interests.

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van Dammen, L., Bush, N.R., de Rooij, S.R. et al. Childhood adversity and women’s cardiometabolic health in adulthood: associations with health behaviors, psychological distress, mood symptoms, and personality. BMC Women's Health 19, 102 (2019).

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  • Childhood adversity
  • Cardiometabolic health
  • Health behaviors
  • Personality
  • Mental wellbeing