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Published in final edited form as: Early Hum Dev. 2013 Jul 5;89(9):10.1016/j.earlhumdev.2013.06.006. doi: 10.1016/j.earlhumdev.2013.06.006

Prenatal stress due to a natural disaster predicts insulin secretion in adolescence

Kelsey N Dancause 1,2, Franz Veru 1,2, Ross E Andersen 1,3, David P Laplante 2, Suzanne King 1,2
PMCID: PMC3855052  NIHMSID: NIHMS505151  PMID: 23830724

Abstract

Prenatal stress might increase cardiometabolic disease risk. We measured prenatal stress due to an ice storm in 1998, and measured glucose tolerance among a subsample of 32 exposed adolescents in 2011. Severity of stress was positively associated with insulin secretion, suggesting that prenatal stress independently predicts metabolic outcomes in adolescence.

Keywords: Developmental origins of health and disease, metabolism, pregnancy

Introduction

Prevalence of childhood metabolic disorders has recently escalated dramatically (1). Research in the Developmental Origins of Health and Disease suggests that features of the prenatal environment, such as poor nutrition, might “program” key aspects of growth or metabolism and thereby predispose offspring to adverse cardiometabolic outcomes (2). High levels of prenatal maternal stress (PNMS) can also have long-term programming effects that might contribute to childhood metabolic disorders. PNMS exposure negatively impacts fetal growth, which increases risk for later cardiometabolic diseases, and can also disrupt the fetal hypothalamic pituitary adrenal axis, which is involved in metabolic pathways. Animal studies suggest that prenatal stress or glucocorticoid exposure is associated with alterations in glucose-insulin metabolism such as insulin resistance, hyperglycemia, and hyperinsulinaemia (3, 4). Unfortunately, evidence from humans is limited (5, 6). Retrospective case-control studies indicate increased risk of insulin resistance among adults whose mothers experienced stressors during pregnancy (5). Furthermore, risk of Type 2 Diabetes Mellitus has been shown to be elevated among children and young adults whose mothers experienced bereavement during pregnancy (7). Further human studies are needed to determine what aspect of PNMS, the objective exposure or the subjective distress, is the stronger predictor of metabolic outcomes.

Since 1998, we have studied effects of two components of PNMS (i.e., objective hardship and subjective distress) among children of women who were pregnant during a severe ice storm. The storm affected women randomly regarding socioeconomic status and physical and mental health. Analyses from Project Ice Storm indicate that PNMS due to the storm negatively impacted birth outcomes (8), and objective maternal hardship increased risk for obesity at age 5½ (9). Based on these patterns, we expected effects of PNMS on glucose-insulin metabolism.

Methods

This study was approved by the Research Ethics Board of the Douglas Hospital Research Center. We obtained written informed consent from parents and written informed assent from adolescents.

Project Ice Storm (810) includes 176 women who were pregnant during the 1998 Quebec (Canada) ice storm, and their children. In 1998, we assessed PNMS due to the storm using an objective hardship questionnaire, which addressed loss (e.g. damage to residence), scope (e.g. days without electricity), and change (e.g. time in a shelter); and a validated French version of the Impact of Events Scale–Revised (11), which addressed subjective distress due to the storm. We collected demographic and health data for the women, including household socioeconomic status (Hollingshead social position criteria) (12) at recruitment, and maternal anxiety (General Health Questionnaire) (13) and exposure to stressful life events (Life Experiences Survey) (14) at both recruitment and when the children were 13½ years old.

In 2011, we invited families to participate in a study of glucose-insulin metabolism. A subset of 18 boys and 14 girls (mean age 13.4 years) completed the assessment. Their mothers were in their 3rd (n=8), 2nd (n=9), or 1st (n=10) trimester of pregnancy during the storm, or conceived within one month of the storm (n=5) when stress hormones could still be elevated. Participating families did not differ from the rest of the families on any key maternal or child characteristics such as socioeconomic status, levels of objective hardship or subjective distress, or birth weight.

We measured height, weight, and percent body fat (%BF) through air displacement plethysmography; %BF was missing for 4 participants. We collected venous blood samples after an overnight fast, followed by collection 30 minutes after an oral glucose challenge (1.75g/kg, maximum 75g). Adolescents completed the Puberty Development Scale (15), and parents completed a survey regarding family history of diabetes. During a separate assessment period at age 13½, adolescents completed the Life Experiences Survey (14), as well as the Perceived Stress Scale (16), Mental Health Continuum (17), and Eating Attitudes Test (EAT-26) (18).

Assays for fasting and stimulated glucose (G0, G30; mmol/L) and insulin (I0, I30; mU/L) were conducted at St. Mary’s Hospital, Montreal. Insulin secretion was estimated using the insulinogenic index [(I30−I0)/(G30−G0); mU/mmol], one of the best indices for first-phase insulin secretion in youth (19).

Hierarchical linear regression was used to test associations among predictor variables and insulin secretion. We tested models including PNMS (objective or subjective) and key control variables (child’s sex, birth weight, body mass index (BMI, kg/m2), pubertal stage, and number of family members with diabetes) individually, as well as a full model including all key predictor variables. We tested potential sex effects using an interaction term (PNMS×Sex), and tested variations of the model including %BF and maternal gestational diabetes. Finally, we conducted additional analyses to test effects of other prenatal and postnatal characteristics such as life events and perceived stress. Data were analyzed using SPSS 20.0.

Results

No adolescents had diagnosed diabetes or G0≥7.0 (the cutoff for diagnosis). Three outliers for insulin secretion were detected and Winsorized. There were no sex differences in mean objective hardship scores (boys: mean 9.8, SD 3.8; girls: mean 9.1, SD 4.1; p=0.66), subjective distress scores (10.9, 10.5; 9.3, 8.4; p=0.64), birth weight (g) (3289, 657; 3466, 564; p=0.43), pubertal development indices (2.6, 0.4; 2.6, 0.3; p=0.96), BMI (23.2, 6.5; 20.6, 4.1; p=0.21), %BF (23.7, 11.5; 24.1, 5.5; p=0.92), number of relatives with diabetes (1.0, 1.0; 0.6, 0.9; p=0.32), G30 (7.4, 1.7; 7.2, 1.7; p=0.72), I0 (111.8, 139.3; 51.0, 23.8; p=0.12), I30 (595.2, 483.9; 547.6, 349.8; p=0.76), insulin secretion (31.6, 20.9; 25.6, 23.7; p=0.45), or percentage of adolescents exposed to gestational diabetes (11.1; 14.3, Chi-square p=1.00). The only variable exhibiting sex differences was G0, which was higher among boys (5.3, 0.4) than girls (4.8, 0.4) (p<0.01). No variables differed by trimester of exposure.

Objective hardship was significantly positively correlated with insulin secretion (r=0.62, p<0.01) (Figure 1), as well as with BMI (r=0.39, p=0.03) and BMI Z-score (r=0.40, p=0.02; based on World Health Organization growth references, (20)), and showed a trend with %BF (r=0.33, p=0.09). In contrast, subjective distress was not significantly correlated with insulin secretion (r=0.15, p=0.42), BMI (r=0.12, p=0.51), BMI Z-score (r=0.13, p=0.47), or %BF (r=− 0.30, p=0.90). Analyses were thus focused on objective hardship. Correlation coefficients (r) for insulin secretion and key independent variables are shown in Table 1.

Figure 1.

Figure 1

Relationship between prenatal maternal stress exposure (objective hardship due to the storm) and insulin secretion (r=0.62, p<0.01)

*Winsorized values.

Table 1.

Relationships among insulin secretiona and key independent variables: Zero-order correlations (r)

Insulin
secretion
Objective
hardship
BMI # Fam. w/
Diab.
Birth
weight
Sex Pubertal
Index
Insulin secretion 1
Objective hardship 0.62** 1
BMI 0.41* 0.39* 1
# Fam. w/Diab. 0.35 0.05 0.27 1
Birth weight −0.26 −0.05 0.21 0.07 1
Sex a −0.14 −0.08 −0.23 −0.18 0.15 1
Pubertal Index 0.06 0.07 0.12 −0.10 0.16 −0.01 1
a

Insulinogenic index [(I30−I0)/(G30−G0); mU/mmol]

b

Boys=1, Girls=2

**

p<0.01

*

p<0.05

p<0.1

In regression analyses (Table 2), higher insulin secretion was associated with greater objective hardship (p<0.01) irrespective of which control variables were included in the model. A greater number of family members with diabetes, and lower birth weight, both predicted higher insulin secretion independently of objective hardship. While objective stress alone explained 38.8% of the variance in insulin secretion, the addition of other predictors individually explained up to 10.0% additional variance, with 58.2% explained by the full model.

Table 2.

Relationships among insulin secretiona and key independent variables: Results of linear regression models

Standardized coefficients
Independent
variable
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Objective hardship 0.55** 0.61** 0.61** 0.62** 0.62** 0.52**
BMI 0.19 0.18
# Fam. w/Diab. 0.32* 0.31*
Birth weight −0.23 −0.31*
Sex b −0.09 0.05
Pubertal Index 0.02 0.08

Model R2 0.42 0.49 0.40 0.35 0.35 0.58
a

Insulinogenic index [(I30−I0)/(G30−G0); mU/mmol]

b

Boys=1, Girls=2

**

p<0.01

*

p<0.05

The addition of the interaction term Objective hardship×Sex indicated no evidence for sex differences in the association between objective hardship and insulin secretion (data not shown). Results were unchanged when controlling for gestational diabetes, or when replacing BMI with %BF (not shown).

We assessed relationships among insulin secretion and a number of additional postnatal household, maternal, and child characteristics. Insulin secretion was unrelated to household socioeconomic status (r=0.26, p=0.16), maternal life events at recruitment(r=−0.01, p=0. 94), and maternal anxiety at recruitment (r=0.11, p=0.56) or at 13½ years (r=−0.14, p=0.47). Furthermore, there were no significant correlations between insulin secretion and adolescents’ scores on the Perceived Stress Scale (r=0.12, p=0.52), Mental Health Continuum (r=−0.09, p=0.64), or life events (r=−0.04, p=0.84). We observed positive correlations between insulin secretion and maternal life events at the 13½-year assessment (r=0.36, p=0.05), as well as adolescents’ EAT-26 scores (r=0.35, p=0.05). Maternal life events did not retain significance in regression models including the key covariates (BMI, number of family members with diabetes, birth weight, sex, pubertal index scores), and results for objective hardship were unchanged (p<0.01). However, EAT-26 scores remained significant in the final regression model (p=0.01) including BMI (p=0.40), number of family members with diabetes (p=0.03), birth weight (p=0.09), sex (p=0.45), pubertal index scores (p=0.87), and objective hardship (p<0.01). Trimming this model of non-significant variables, 34.8% of variance in insulin secretion was explained by covariates (number of family members with diabetes, B=0.33, p<0.01; birth weight, B=−0.30, p=0.02; and EAT-26 scores, B=0.29, p=0.02), and objective hardship accounted for a further 28.4% of variance (B=0.54, p<0.01).

Discussion

Increased insulin secretion is an early feature of insulin resistance (21). The relationship between PNMS due to the ice storm and increased insulin secretion supports recent studies suggesting that PNMS negatively affects metabolic health, and highlights that these effects can be manifest in adolescence. Furthermore, effects were independent of other maternal and child characteristics that might be expected to correlate with insulin secretion. The relationships between insulin secretion and adolescents’ number of family members with diabetes and birth weight follow expected patterns. Furthermore, other researchers have observed positive relationships between EAT-26 scores and obesity among adolescents (22) and young adults (23), consistent with the positive relationship between EAT-26 scores and insulin secretion in the current sample. That the effects of objective hardship remained significant despite small sample sizes, and taking into account these important covariates, lends support to our conclusions.

PNMS might have direct effects on metabolic pathways, as well as indirect effects through early growth patterns or adiposity (5, 6). Exposure to the ice storm was associated with shorter length at birth (8) and with childhood obesity (9), as well as with BMI in the current sample. However, effects on insulin secretion persisted even when controlling for these growth patterns, suggesting potential effects on central mediators of metabolism. Unfortunately, our sample is not large enough to test mediating pathways, and our findings must be replicated in larger samples. Studies of PNMS and cardiometabolic health planned by the Amsterdam Born Children and their Development study (24) could refine our knowledge of underlying mechanisms.

Our results further suggest that it is the woman’s exposure to hardship, rather than her distress, that predicts glucose-insulin metabolism. Other studies indicate differing effects of objective and subjective PNMS depending on the outcome assessed. For example, in Project Ice Storm, we have observed associations between objective hardship, but not subjective distress, and cognitive and linguistic functioning at ages 2 (10) and 5½ (25), and with childhood BMI and obesity (9). In contrast, effects of PNMS on dermatoglyphic asymmetry (26) and head circumference at birth (8) appear to be more strongly related to subjective than objective PNMS. The effects of PNMS likely reflect a number of interacting mechanistic pathways, including hormonal cascades (27), physiological responses such as maternal heart rate change (28), and epigenetic changes (29). Objective hardship and subjective distress might act through different pathways, which could account for the differing effects seen based on type of PNMS. Our results highlight the need for more research in this area.

Considering the lifelong consequences of childhood metabolic disorders (1), studies identifying preventable or treatable risk factors are increasingly necessary. The growing body of evidence suggests that any assistance we can provide pregnant women to reduce stress is important not only for their own health, but also for the long-term metabolic health of their children.

Acknowledgements

This research was supported by a grant from the Canadian Institute of Health Research (CIHR) to Suzanne King and David Laplante. Kelsey Dancause was supported by fellowships from CIHR and the National Institutes of Health (NIH). We are grateful to families for their continued participation in Project Ice Storm, and to Chunbo Yu and Aihua Liu for advice on statistical methods.

Footnotes

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This study was approved by the Research Ethics Board of the Douglas Hospital Research Center.

Conflict of interest statement

The authors declare no conflicts of interest

All authors participated in the design, execution, and analysis of the manuscript, and have seen and approved the final version. The manuscript has neither been published nor submitted elsewhere.

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