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Preconception mental health and the relationship between antenatal depression or anxiety and gestational diabetes mellitus: a population-based cohort study

BMC Pregnancy and Childbirth volume 22, Article number: 670 (2022) Cite this article

Abstract

Background

Antenatal depression and anxiety are highly prevalent conditions that have been associated with increased risk for myriad adverse outcomes. Current literature exploring the connection between antenatal mental health and gestational diabetes mellitus (GDM) is limited, presenting conflicting evidence. We sought to evaluate the association between antenatal depression/anxiety (DEP-ANX) and GDM using population-based, administrative data, accounting for aspects of preconception mental health.

Methods

In this population-based retrospective cohort study, we included all singleton births in British Columbia, Canada from April 1, 2000, to December 31, 2014. We identified instances of DEP-ANX from outpatient and inpatient records that included relevant diagnostic codes and stratified our cohort by preconception DEP-ANX persistence. Logistic regression models were run to estimate odds of GDM given antenatal DEP-ANX. Models were adjusted for the birthing person’s socio-demographics and pregnancy characteristics. Using an expanded cohort, we ran conditional logistic regression models that matched birthing people to themselves (in a subsequent pregnancy) based on discordance of exposure and outcome.

Results

Out of the 228,144 births included in this study, 43,664 (19.1%) were to birthing people with antenatal health service use for DEP-ANX. There were 4,180 (9.6%) cases of GDM among those antenatal exposure to DEP-ANX compared to 15,102 (8.2%) among those without exposure (SMD 0.049). We observed an unadjusted odds ratio (OR) of 1.19 (95% CI: 1.15 – 1.23) and fully adjusted OR of 1.15 (95% CI: 1.11 – 1.19) overall. Apparent risk for GDM given antenatal DEP-ANX was highest among the no DEP-ANX history stratum, with a fully adjusted OR of 1.24 (95% CI: 1.15 – 1.34). Associations estimated by matched sibling analysis were non-significant (fully adjusted OR 1.19 [95% CI: 0.86 – 1.63]).

Conclusions

Results from this population-based study suggest an association between antenatal DEP-ANX and GDM that varied based on mental health history. Our analysis could suggest that incident cases of DEP-ANX within pregnancy are more closely associated with GDM compared to recurring or chronic cases.

Peer Review reports

Introduction

Depression and anxiety are highly prevalent among individuals of reproductive age [1,2,3], and nearly 20% of birthing people experience an episode of depression or anxiety during pregnancy [4, 5]. Preconception mental health disorders increase risk for an antenatal episode [6,7,8,9], and both preconception and antenatal depression/anxiety have been independently associated with adverse perinatal outcomes such as gestational diabetes mellitus (GDM) [10, 11]. While the risk from preconception and antenatal mental health disorders is a critical issue, very little research has aimed to understand how different mental health trajectories are associated with adverse outcomes like GDM.

GDM is a unique subtype of diabetes mellitus (DM), indicated by glucose intolerance first detected during pregnancy. GDM has been shown to pose significant risks to perinatal health, increasing the likelihood of hemorrhage, preeclampsia, and operative delivery [12,13,14]. Instances of GDM have been shown to also have lasting impacts on cardiovascular and metabolic health, with elevated risk for future cardiovascular disease and type 2 DM for both the birthing person and child [15,16,17]. Cases of comorbid antenatal depression/anxiety (DEP-ANX) and GDM have been further shown to increase the likelihood of adverse outcomes, including preeclampsia to preterm birth [18, 19].

Current literature investigating the link between antenatal DEP-ANX and GDM is limited, and presents conflicting evidence regarding the significance and magnitude of this association [11, 20,21,22,23,24,25,26]. There are similarly contradictory results regarding the connection between depression/anxiety history and GDM [10, 27, 28]. Our understanding of this relationship is thus largely guided by studies focused on bidirectional associations between DEP-ANX and DM [29, 30]. DEP-ANX and DM are hypothesized to originate from shared pathways, in which trauma, genetics, environment, and inequities contribute to the activation of physiological responses driving both conditions [31, 32].

In this study, we aimed to incorporate preconception mental health into a study of how antenatal depression/anxiety influences risk for GDM. We hypothesized that compared to those without history of DEP-ANX, individuals with chronic histories would have higher odds of GDM related to antenatal DEP-ANX, given increased exposure to chronic stress and its cumulative effects (allostatic load) [33, 34].

Materials and methods

We conducted a population-based, retrospective cohort study of all live births in British Columbia (BC), Canada from April 1, 2000, to December 31, 2013. Birthing person data were collected from 10-years preconception through delivery. Population Data (PopData) BC created our cohort through the BC Perinatal Data Registry (BCPDR) [35], containing nearly 100% of births in BC, regardless of place of delivery. They then linked these data with the Discharge Abstract Database (DAD) [36], documenting all BC hospital stays and day surgeries; the Medical Services Plan (MSP) Payment Information File [37], describing all BC medical visits; vital statistics data [38], containing birth information; and the Central Demographics File (previously BC Consolidation file) [39], detailing demographic and registration data for provincial health coverage (MSP).

Ethics approval for our use of deidentified administrative data was approved by the University of British Columbia Behavioural Research Ethics Board. Data access was approved by the Data Stewards. Both approvals include a waiver of informed consent from participants. All inferences, opinions, and conclusions drawn are those of the authors and do not reflect opinions or policies of the Data Stewards.

Study cohort

Our cohort included singleton births to birthing people with complete record of neighborhood-based income quintiles and final gestational age (GA). We excluded births to individuals who had pre-existing DM, and/or any record of health service use with diagnostic codes corresponding to bipolar disorder, schizophrenia, psychosis, or mania (Supplemental Table 1). Finally, we required that birthing people be registered with MSP for > 100 days/year from 5-years preconception to birth. We loosened this criterion to 3-years preconception for our sibling cohort analyses, described below, to increase statistical power (see Fig. 1).

Table 1 Comparison of socio-demographic and clinical characteristics among individuals with and without antenatal DEP-ANX
Full size table
Fig. 1
figure 1

Flow diagram for population-based study in British Columbia, CA, investigating the association between antenatal DEP-ANX and GDM. Abbreviations: DEP-ANX, depression and/or anxiety; GDM, gestational diabetes mellitus

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Measures

Time periods of interest. We determined approximate date of conception (DOC) by subtracting final GA (reported in the BCPDR) from the offspring’s date of birth (DOB), then subtracting two weeks. Final GA is approximated by the BCPDR based (in order of accuracy) on earliest ultrasound, last menstrual period, or newborn examination. We defined pregnancy as the period between the DOC and DOB, and preconception periods (0 – 1 year, 2 – 3 years, 4 – 5 years, 6 – 10 years, and > 10 years) using the approximate DOC.

Mental health measures. Depression and anxiety were classified as a single exposure, DEP-ANX, due to high rates of co-occurrence (particularly within the perinatal period) [40], overlapping risk factors, and neurobiological similarities [41,42,43,44,45]. We identified DEP-ANX cases within each period based on the presence of relevant diagnostic codes (Supplemental Table 2) from fee-for-service provider visits and hospitalization data. MSP outpatient records are coded using the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM), while DAD hospitalizations are coded using the ICD-10-CM. Mental health was further described by DEP-ANX history, independent of antenatal DEP-ANX, according to observed DEP-ANX persistence across preconception. Persistence was categorized into the following groups (Fig. 2): 1) no history; 2) episodic history; 3) chronic history with discontinuous treatment; and 4) chronic history with continuous treatment.

Table 2 Association between antenatal DEP-ANX and GDM across preconception DEP-ANX persistence strata. RDs and ORs represent the log likelihood of GDM among those with antenatal DEP-ANX compared to those without
Full size table
Fig. 2
figure 2

Decision tree for preconception DEP-ANX persistence classification. Abbreviations: DEP-ANX, depression and/or anxiety

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Outcomes

Instances of GDM were identified from the BCPDR based on results of routine prenatal screening (typically between 24 and 28 weeks) [46].

Covariates

Birthing person and coparent age, coparent status, income quintile, marital status, number of living children, and birth year were used to describe individual-level demographics. Pregnancy health and prenatal care were characterized by smoking status (during the current pregnancy), history of premature birth, parity, preconception body mass index category (BMI; equal to weight [kilograms] divided by height [meters] squared), pregnancy and non-pregnancy induced hypertension (PIH and non-PIH), intrauterine growth restriction (IUGR), frequency of prenatal visits, and frequency of antenatal hospitalization.

We described labor and delivery by use of induction, mode of delivery (vaginal or non-vaginal), and presence of a midwife at birth. Finally, neonatal outcomes were summarized by infant sex, final GA, small-for-gestational-age (SGA; birth weight below 10th percentile for final GA and sex), large-for-gestational-age (LGA; birth weight over 90th percentile for final GA and sex), admission to the neonatal intensive care unit (NICU), and preterm birth.

Statistical analysis

We compared socio-demographics, health during pregnancy, labor and delivery, and neonatal outcomes between those with and without antenatal DEP-ANX using standardized differences. Differences of 0.1 or more were deemed clinically meaningful [47]. We repeated this process to identify differences in our cohort based on persistence of preconception DEP-ANX.

We modeled the relationship between antenatal DEP-ANX and GDM using logistic regression. Covariates were added in a stepwise fashion to identify potential confounders that significantly improved model fit. Associations between antenatal DEP-ANX exposure and GDM were quantified using absolute risk differences (RDs) and odds ratios (ORs). Unadjusted associations were assessed first (Base Model), followed by adjustment for socio-demographics, including birthing person age category, income quintile, marital status, number of living children, and year of birth (Model 1). Finally, we added characteristics of pregnancy, including preconception BMI, PIH, non-PIH, antenatal hospitalization, and IUGR (Model 2). Regressions were also run following stratification according to persistence of preconception DEP-ANX.

To better adjust for genetic and epigenetic (social and environmental) factors that might confound the relationship between antenatal DEP-ANX and GDM, we conducted analyses in a sibling cohort nested within our larger cohort [48]. This analyzes the association between DEP-ANX and GDM across pregnancies to the same birthing person, rather than comparing across different birthing people. We restricted to birthing people who delivered more than once within the study period and stratified by preconception DEP-ANX history (no history vs. any history). We ran unconditional logistic regression models for the full sibling cohort and each stratum using clustered standard errors to account for correlation between sibling pairs. Associations estimated by these models were used to determine whether the relationship between antenatal DEP-ANX and GDM observed in the full cohort persisted within the sibling cohort. We then ran conditional regression models that matched birthing people to themselves (in successive deliveries), selecting only discordant pregnancies. Only individuals who were discordant in exposure and outcome in ≥ 2 pregnancies contributed to this model.

All P-values were two-sided and statistical significance was defined with an alpha of 0.05. All statistical analyses were carried out using RStudio software.

Results

Between April 1, 2000, and December 31, 2013, there were 582,459 births recorded in BC. Of these, we excluded all multiple births (N = 17,789), and births without income (N = 18,635) or final GA (N = 727) information reported. We further excluded births parents with any health service use for excluded mental health conditions (N = 16,380) and birthing people with pre-existing diabetes (N = 2,398). Birthing people registered with MSP for < 100 days/year from 5-years preconception to delivery were also excluded (N = 298,386). Our final cohort consisted of 228,144 births to 166,974 birthing people. See Supplemental Table 3 for a comparison between included and excluded births.

Table 3 Stratified sibling cohort analysis of association between antenatal DEP-ANX and GDM. RDs and ORs represent the risk or log likelihood of GDM among those with antenatal DEP-ANX compared to those without
Full size table

Of included births, 43,664 (19.1%) were to individuals with any health service use for DEP-ANX during pregnancy (Table 1). There were 4,180 (9.6%) cases of GDM among those with antenatal exposure to DEP-ANX compared to 15,102 (8.2%) cases among those without antenatal DEP-ANX (SMD 0.049). Compared to those without, those with exposure to antenatal DEP-ANX were less likely to be married (62.9 vs. 69.5%; SMD 0.145), have a coparent present (94.4 vs. 96.6%; SMD 0.107), and/or have midwifery care at delivery (10.4 vs. 14.8%; SMD 0.134). Additionally, birthing people with antenatal DEP-ANX were more likely to smoke during pregnancy (11.7 vs. 8.6%; SMD 0.127), have ≥ 10 prenatal visits (37.0 vs. 31.9%; SMD 0.108), and be hospitalized during pregnancy (12.3 vs. 9.0%; SMD 0.197).

Stratification by preconception DEP-ANX persistence revealed meaningful differences across socio-demographics and pregnancy characteristics, summarized in Supplemental Table 4. The chronic, continuous group was older, less likely to be married and have other living children, and more likely to smoke than those with no DEP-ANX history.

Unadjusted logistic regression models, which examine the relationship across pregnancies to the same birthing person, suggested a significant association between antenatal DEP-ANX and GDM among our full cohort (OR 1.19 [95% CI: 1.15 – 1.23]) as seen in Table 2. This association was maintained after adjusting for birthing person age category, neighborhood-based income quintile, marital status, number of living children, and year of birth (Model 1; aOR 1.20 [95% CI: 1.15 – 1.24]). Following adjustment for preconception BMI, PIH, non-PIH, antenatal hospitalization, and IUGR (Model 2), we saw a slight attenuation in risk for GDM given antenatal DEP-ANX; however, the association remained significant (aOR 1.16 [95% CI: 1.11 – 1.20]).

Stratified analysis revealed differential associations between antenatal DEP-ANX and GDM across persistence groups (Table 2). Unadjusted odds for GDM given antenatal DEP-ANX were highest among those with no DEP-ANX history (OR 1.23 [95% CI: 1.14 – 1.32]) and remained so in the fully adjusted model (Model 2 aOR 1.25 [95% CI 1.16 – 1.35]). Comparatively, the unadjusted association between antenatal DEP-ANX and GDM among those with a chronic, continuous history of DEP-ANX was significantly smaller (OR 1.11 [95% CI: 1.05 – 1.18]). This association was minimally attenuated after adjusting for socio-demographics and pregnancy characteristics (Model 2 aOR 1.10 [95% CI: 1.04 – 1.17]). Among those with an episodic history of DEP-ANX, odds of GDM given antenatal DEP-ANX resembled those among our chronic, continuous group. Associations within our chronic, discontinuous strata were not statistically significant.

To increase statistical power for our stratified sibling analysis, we expanded our cohort to include those registered with MSP < 100 days/year from 3- to 5-years preconception (N = 86,471). Our expanded cohort consisted of 314,615 births to 220,461 birthing people. Logistic regression models run with this expanded cohort (Table 3) provided comparable ORs to those from our original cohort (Overall: OR 1.17 [95% CI: 1.13 – 1.20], Model 2 aOR 1.14 [95% CI: 1.10 – 1.18]). Results from our unmatched sibling cohort analysis further demonstrated that restricting this cohort to birthing people with more than 1 eligible pregnancy did not significantly affect the strength or direction of previously observed associations (Overall: OR 1.18 [95% CI: 1.12 – 1.24], Model 2 aOR 1.15 [95% CI: 1.09 – 1.21]).

Unadjusted conditional logistic regression models, which examine the relationship across pregnancies to the same birthing person, suggested substantially different strengths of association (Overall: OR 1.05 [95% CI: 0.96 – 1.15]; No history: OR 2.27 [95% CI: 1.68 – 3.07]; Any history: OR 1.01 [95% CI: 0.90 – 1.13]). Adjusting for socio-demographics and pregnancy characteristics revealed attenuated associations between GDM and antenatal DEP-ANX with loss of statistical significance across the full cohort (Model 2 aOR 1.07 [95% CI: 0.96 – 1.18]), no DEP-ANX history group (Model 2 aOR 1.18 [95% CI: 0.86 – 1.63]), and any DEP-ANX history group (Model 2 aOR 1.02 [95% CI: 0.90 – 1.16); however, the direction of association remained positive in all three cases.

Comment

Principal findings

In this population-based, retrospective cohort study, we found a modest association between antenatal DEP-ANX and GDM that differed in effect size based on preconception mental health. Overall, individuals with antenatal DEP-ANX that had no history of DEP-ANX appeared to be at higher risk for GDM than those with an episodic or chronic, continuous history. While these relationships were attenuated, they largely remained statistically significant after adjusting for socio-demographics and pregnancy characteristics in our original and expanded cohort. Matched sibling pairs analysis resulted odds ratios of similar magnitude among those with no DEP-ANX, but the association was no longer statistically significant and thus we cannot rule out residual confounding as an explanation for the associations in the main cohort.

Results in the context of What is Known

The positive association between DEP-ANX and GDM is consistent with prior literature. Several observational studies have demonstrated significant associations between antenatal DEP-ANX and GDM of varying effect size, reporting increased risks between 52 – 300% from unadjusted and adjusted analysis [11, 22, 28, 49]. In contrast, several studies have suggested that no association exists between GDM and DEP-ANX [20, 25]. Importantly, the magnitudes of these associations are similar to what we have reported (increased risk of 5 – 20%) and their lack of statistical significance may reflect limited statistical power.

Clinical implications

We observed a slightly larger effect size in the associations between GDM and incident DEP-ANX vs. recurring or chronic DEP-ANX, highlighting the potential role of GDM-induced stress in the development of antenatal DEP-ANX. GDM diagnosis has been previously shown to be a significant stressor, with lasting impacts on the birth person’s physical and emotional well-being [50]. While we cannot rule out residual confounding, an alternative explanation may be that antenatal DEP-ANX and GDM share biological origins (i.e., hypothalamus–pituitary–adrenal (HPA) axis dysregulation and cytokine-mediated inflammatory responses), as has been explored outside the perinatal context [31]. Despite their lower risk for GDM due to antenatal DEP-ANX, significant associations observed for those with preconception DEP-ANX history could also support the hypothesis that allostatic load plays a role in the relationship between GDM and antenatal DEP-ANX. These findings may be explained by a bidirectional mechanism in which development of either condition contributes to development of the other [29, 30].

Regardless of the mechanism connecting antenatal DEP-ANX and GDM, and even in the case of residual confounding, our findings suggest that DEP-ANX and GDM often co-occur and emphasize the importance of ongoing prenatal screening for both GDM and DEP-ANX, particularly among those without a history of either condition. Differences in association based on preconception DEP-ANX persistence may be due to diagnostic bias that delays DEP-ANX treatment among those with discontinuous or no history of DEP-ANX. Further, more regular preconception interactions with mental health services may facilitate easier access to mental health care during pregnancy, thereby mitigating the effects of antenatal DEP-ANX or preventing DEP-ANX recurrence in response to a GDM diagnosis. This points to the importance of addressing barriers to mental health services, particularly during pregnancy, and the value of providing consistent mental health care throughout a birthing person’s life.

Research implications

Stratification by persistence of preconception DEP-ANX is a novel approach not previously used to understand the relationship between DEP-ANX and GDM. By accounting for variation in preconception DEP-ANX, we were able to report association between mental health history (DEP-ANX) and GDM in a way that sheds light on the potential mechanisms connecting these conditions. Future work is needed to understand how preconception mental health might affect prenatal trajectories of both antenatal DEP-ANX and GDM. Additionally, research that can more precisely explore themes of mental health care access, diagnostic biases, and symptom severity could help elucidate the underlying mechanism linking GDM and DEP-ANX.

Strengths and limitations

This study is strengthened by its use of population-based administrative datasets and operationalization of more granular definitions for understanding individual DEP-ANX histories. This more nuanced approach allowed for deeper exploration of the relationship between DEP-ANX and GDM. Our study also possessed key limitations. Compared to included individuals, those who were excluded from our study (largely due to not having lived in the province for 5-years preconception) tended to be of lower socioeconomic status with more limited records of overall health status, potentially affecting generalizability of our findings. We did not have access to pharmacy data, prohibiting us from evaluating the role of psychotropic medication in the observed association. Additionally, our definitions for DEP-ANX relied on treatment records filed with provincial health, thus omitting data from individuals seeking care from providers outside BC’s universal health coverage (counselling psychologists, social workers, etc.) and those with under- or un-treated DEP-ANX. Omission of these data may have caused some misclassification of DEP-ANX persistence and/or antenatal DEP-ANX, particularly for those with chronic histories who may have well-established treatment regimens outside of the health system.

Our use of data for 10-years preconception despite applying a registration criterion for 5-years preconception may have also introduced misclassification, specifically for individuals who experienced DEP-ANX prior to 5-years preconception but were not living in the province at that time. This is unlikely to be associated with GDM status, though, and would therefore bias toward the null. Our inability to determine whether GDM preceded antenatal DEP-ANX made interpreting results more challenging. As we do not have date of diagnosis for GDM in the BCPDR and cannot assume that the first DEP-ANX diagnosis code reported in health services data represents actual onset of DEP-ANX, we cannot determine which diagnosis came first. Finally, we cannot rule out the possibility of residual confounding related to both socioeconomic factors that are known to be important determinants of mental health during pregnancy and to yet unmeasured factors that contribute to both GDM and antenatal DEP-ANX.

Conclusions

Results from this population-based retrospective cohort study suggest an association between antenatal DEP-ANX and GDM that varied based on mental health history. Our analysis could suggest that incident cases of DEP-ANX within pregnancy are more closely associated with GDM compared to recurring or chronic cases. These findings present a novel perspective on the relationship between DEP-ANX and GDM.

Availability of data and materials

Access to data provided by the Data Steward(s) is subject to approval but can be requested for research projects through the Data Steward(s) or their designated service providers.

Abbreviations

GDM:

Gestational diabetes mellitus

DM:

Diabetes mellitus

DEP-ANX:

Depression/anxiety

BC:

British Columbia

PopData BC:

Population Data BC

BCPDR:

BC Perinatal Data Registry

DAD:

Discharge Abstract Database

MSP:

Medical Services Plan

GA:

Gestational age

DOC:

Date of conception

DOB:

Date of birth

ICD:

International Classification of Diseases

BMI:

Body mass index

PIH:

Pregnancy induced hypertension

non-PIH:

Non-pregnancy induced hypertension

IUGR:

Intrauterine growth restriction

SGA:

Small-for-gestational-age

LGA:

Large-for-gestational-age

NICU:

Neonatal intensive care unit

RD:

Risk difference

OR:

Odds ratio

HPA:

Hypothalamus-pituitary-adrenal axis

References

  1. Lang AY, Boyle JA, Fitzgerald GL, Teede H, Mazza D, Moran LJ, et al. Optimizing preconception health in women of reproductive age. Minerva Ginecol. 2018;70(1):21.

    Google Scholar 

  2. Statistics Canada. Table 13–10–0619–01 Mental health characteristics: Perceived need for mental health care. 2019.

  3. Shim RS, Baltrus P, Ye J, Rust G. Prevalence, Treatment, and Control of Depressive Symptoms in the United States: Results from the National Health and Nutrition Examination Survey (NHANES), 2005–2008. The Journal of the American Board of Family Medicine. 2011;24(1):33–8.

    Article  PubMed  Google Scholar 

  4. Gavin NI, Gaynes BN, Lohr KN, Meltzer-Brody S, Gartlehner G, Swinson T. Perinatal Depression: A Systematic Review of Prevalence and Incidence. Obstet Gynecol. 2005;106(5, Part 1):1071–83.

    Article  PubMed  Google Scholar 

  5. Dennis CL, Falah-Hassani K, Shiri R. Prevalence of antenatal and postnatal anxiety: Systematic review and meta-analysis. Br J Psychiatry. 2017;210(5):315–23.

    Article  PubMed  Google Scholar 

  6. Leigh B, Milgrom J. Risk factors for antenatal depression, postnatal depression and parenting stress. BMC Psychiatry. 2008;8(1):24.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Marcus SM, Flynn HA, Blow FC, Barry KL. Depressive Symptoms among Pregnant Women Screened in Obstetrics Settings. J Womens Health. 2003;12(4):373–80.

    Article  Google Scholar 

  8. Patton GC, Romaniuk H, Spry E, Coffey C, Olsson C, Doyle LW, et al. Prediction of perinatal depression from adolescence and before conception (VIHCS): 20-year prospective cohort study. Lancet. 2015;386(9996):875–83.

    Article  PubMed  Google Scholar 

  9. Giallo R, Cooklin A, Nicholson JM. Risk factors associated with trajectories of mothers’ depressive symptoms across the early parenting period: an Australian population-based longitudinal study. Arch Womens Ment Health. 2014;17(2):115–25.

    Article  PubMed  Google Scholar 

  10. Bowers K, Laughon SK, Kim S, Mumford SL, Brite J, Kiely M, et al. The Association between a Medical History of Depression and Gestational Diabetes in a Large Multi-ethnic Cohort in the United States: Depression and gestational diabetes. Paediatr Perinat Epidemiol. 2013;27(4):323–8.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Minschart C, De Weerdt K, Elegeert A, Van Crombrugge P, Moyson C, Verhaeghe J, et al. Antenatal Depression and Risk of Gestational Diabetes, Adverse Pregnancy Outcomes, and Postpartum Quality of Life. J Clin Endocrinol Metab. 2021;106(8):e3110–24.

    Article  PubMed  Google Scholar 

  12. American Diabetes Association. 14. Management of Diabetes in Pregnancy: Standards of Medical Care in Diabetes—2021. Dia Care. 2021 Jan;44(Supplement 1):S200–10.

  13. Lucas IM, Barr ELM, Barzi F, Longmore DK, Lee I, Kirkwood M, et al. Gestational diabetes is associated with postpartum hemorrhage in Indigenous Australian women in the PANDORA study: A prospective cohort. Int J Gynecol Obstet. 2021;155(2):296–304.

    Article  Google Scholar 

  14. Muche AA, Olayemi OO, Gete YK. Effects of gestational diabetes mellitus on risk of adverse maternal outcomes: a prospective cohort study in Northwest Ethiopia. BMC Pregnancy Childbirth. 2020;20(1):73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Metzger BE. Long-term Outcomes in Mothers Diagnosed With Gestational Diabetes Mellitus and Their Offspring. Clin Obstet Gynecol. 2007;50(4):972–9.

    Article  PubMed  Google Scholar 

  16. Yu Y, Arah OA, Liew Z, Cnattingius S, Olsen J, Sørensen HT, et al. Maternal diabetes during pregnancy and early onset of cardiovascular disease in offspring: population based cohort study with 40 years of follow-up. BMJ. 2019;4: l6398.

    Article  Google Scholar 

  17. Kramer CK, Campbell S, Retnakaran R. Gestational diabetes and the risk of cardiovascular disease in women: a systematic review and meta-analysis. Diabetologia. 2019;62(6):905–14.

    Article  PubMed  Google Scholar 

  18. Packer CH, Pilliod RA, Chatroux LR, Caughey AB, Valent AM. Increased rates of adverse perinatal outcomes in women with gestational diabetes and depression. J Matern Fetal Neonatal Med. 2021;34(23):3862–6.

    Article  PubMed  Google Scholar 

  19. Byrn MA, Penckofer S. Antenatal Depression and Gestational Diabetes: A Review of Maternal and Fetal Outcomes. Nurs Womens Health. 2013;17(1):22–33.

    Article  PubMed  Google Scholar 

  20. Beka Q, Bowker S, Savu A, Kingston D, Johnson JA, Kaul P. Development of Perinatal Mental Illness in Women With Gestational Diabetes Mellitus: A Population-Based Cohort Study. Can J Diabetes. 2018;42(4):350-355.e1.

    Article  PubMed  Google Scholar 

  21. Byrn M, Penckofer S. The Relationship Between Gestational Diabetes and Antenatal Depression. J Obstet Gynecol Neonatal Nurs. 2015;44(2):246–55.

    Article  PubMed  Google Scholar 

  22. Pace R, Rahme E, Da Costa D, Dasgupta K. Association between gestational diabetes mellitus and depression in parents: a retrospective cohort study. CLEP. 2018;10:1827–38.

    Article  Google Scholar 

  23. Kozhimannil KB, Pereira MA, Harlow BL. Association Between Diabetes and Perinatal Depression Among Low-Income Mothers. JAMA. 2009;301(8):6.

    Article  Google Scholar 

  24. Morrison C, McCook JG, Bailey BA. First trimester depression scores predict development of gestational diabetes mellitus in pregnant rural Appalachian women. J Psychosom Obstet Gynecol. 2016;37(1):21–5.

    Article  Google Scholar 

  25. Katon JG, Russo J, Gavin AR, Melville JL, Katon WJ. Diabetes and Depression in Pregnancy: Is There an Association? Journal of Women’s Health. 2011;20(7):983–9.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Wilson CA, Newham J, Rankin J, Ismail K, Simonoff E, Reynolds RM, et al. Is there an increased risk of perinatal mental disorder in women with gestational diabetes? A systematic review and meta-analysis. Diabet Med. 2020;37(4):602–22.

    Article  CAS  PubMed  Google Scholar 

  27. Wilson BL, Dyer JM, Latendresse G, Wong B, Baksh L. Exploring the Psychosocial Predictors of Gestational Diabetes and Birth Weight. J Obstet Gynecol Neonatal Nurs. 2015;44(6):760–71.

    Article  PubMed  Google Scholar 

  28. Wilson CA, Santorelli G, Dickerson J, Ismail K, Reynolds RM, Simonoff E, et al. Is there an association between anxiety and depression prior to and during pregnancy and gestational diabetes? An analysis of the Born in Bradford cohort. J Affect Disord. 2020;276:345–50.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Joseph JJ, Golden SH. Cortisol dysregulation: the bidirectional link between stress, depression, and type 2 diabetes mellitus: Role of cortisol in stress, depression, and diabetes. Ann NY Acad Sci. 2017;1391(1):20–34.

    Article  PubMed  Google Scholar 

  30. Pan A, Lucas M, Sun Q, van Dam RM, Franco OH, Manson JE, et al. Bidirectional Association Between Depression and Type 2 Diabetes Mellitus in Women. Arch Intern Med [Internet]. 2010 Nov 22 [cited 2022 Apr 4];170(21). Available from: https://doi.org/10.1001/archinternmed.2010.356.

  31. Moulton CD, Pickup JC, Ismail K. The link between depression and diabetes: the search for shared mechanisms. Lancet Diabetes Endocrinol. 2015;3(6):461–71.

    Article  PubMed  Google Scholar 

  32. Mendenhall E, Kohrt BA, Norris SA, Ndetei D, Prabhakaran D. Non-communicable disease syndemics: poverty, depression, and diabetes among low-income populations. The Lancet. 2017;389(10072):951–63.

    Article  Google Scholar 

  33. McEwen BS, Gianaros PJ. Central role of the brain in stress and adaptation: Links to socioeconomic status, health, and disease: Central links between stress and SES. Ann N Y Acad Sci. 2010;1186(1):190–222.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Evans GW, Li D, Whipple SS. Cumulative risk and child development. Psychol Bull. 2013;139(6):1342–96.

    Article  PubMed  Google Scholar 

  35. Perinatal Services BC [creator]. British Columbia Perinatal Data Registry [Internet]. Population Data BC [publisher]; 2021 [cited 2021 Aug 15]. Available from: http://www.perinatalservicesbc.ca/health-professionals/data-surveillance/perinatal-data-registry.

  36. Canadian Institute for Health Information [creator]. Discharge Abstract Database (Hospital Separations) [Internet]. Population Data BC [publisher]; 2020 [cited 2020 Oct 9]. Available from: http://www.popdata.bc.ca/data.

  37. British Columbia Ministry of Health [creator]. Medical Services Plan (MSP) Payment Information File [Internet]. Population Data BC [publisher]; 2020 [cited 2020 Oct 8]. Available from: http://www.popdata.bc.ca/data.

  38. British Columbia Vital Statistics Agency [creator]. Vital Statistics and Births [Internet]. Population Data BC [publisher]; 2021 [cited 2021 Jan 26]. Available from: http://www.popdata.bc.ca/data.

  39. British Columbia Ministry of Health [creator]. Consolidation File (MSP Registration & Premium Billing) [Internet]. Population Data BC [publisher]; 2021 [cited 2021 Feb 1]. Available from: http://www.popdata.bc.ca/data.

  40. Ross LE, McLean LM. Anxiety disorders during pregnancy and the postpartum period: A systematic review. J Clin Psychiatry. 2006;67(8):1285–98.

    Article  PubMed  Google Scholar 

  41. Barrett J, Wonch KE, Gonzalez A, Ali N, Steiner M, Hall GB, et al. Maternal affect and quality of parenting experiences are related to amygdala response to infant faces. Soc Neurosci. 2012;7(3):252–68.

    Article  PubMed  Google Scholar 

  42. Moses-Kolko EL, Perlman SB, Wisner KL, James J, Saul AT, Phillips ML. Abnormally Reduced Dorsomedial Prefrontal Cortical Activity and Effective Connectivity With Amygdala in Response to Negative Emotional Faces in Postpartum Depression. AJP. 2010;167(11):1373–80.

    Article  Google Scholar 

  43. Silverman ME, Loudon H, Liu X, Mauro C, Leiter G, Goldstein MA. The neural processing of negative emotion postpartum: a preliminary study of amygdala function in postpartum depression. Arch Womens Ment Health. 2011;14(4):355–9.

    Article  PubMed  Google Scholar 

  44. Silverman ME, Loudon H, Safier M, Protopopescu X, Leiter G, Liu X, et al. Neural Dysfunction in Postpartum Depression: An fMRI Pilot Study. CNS Spectr. 2007;12(11):853–62.

    Article  PubMed  Google Scholar 

  45. Wonch KE, de Medeiros CB, Barrett JA, Dudin A, Cunningham WA, Hall GB, et al. Postpartum depression and brain response to infants: Differential amygdala response and connectivity. Soc Neurosci. 2016;11(6):600–17.

    Article  PubMed  Google Scholar 

  46. DCPG Expert Committee,Feig DS, Berger H, Donovan L, Godbout A, Kader T, et al 2018 Diabetes and Pregnancy. Can J Diabetes 42 Supplement 1 S255 S282

  47. Stuart EA, Lee BK, Leacy FP. Prognostic score–based balance measures can be a useful diagnostic for propensity score methods in comparative effectiveness research. J Clin Epidemiol. 2013;66(8):S84-S90e1.

    PubMed  PubMed Central  Google Scholar 

  48. Hanley GE, Bickford C, Ip A, Lanphear N, Lanphear B, Weikum W, et al. Association of Epidural Analgesia During Labor and Delivery With Autism Spectrum Disorder in Offspring. JAMA. 2021;326(12):1178.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Versteegen M, Bozlak CT, Larkin H, Appleton AA. Maternal depression, adverse childhood experiences, and social support in relation to gestational diabetes risk: results from the Albany Infant and Mother Study (AIMS). BMC Pregnancy Childbirth. 2021;21(1):335.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Parsons J, Sparrow K, Ismail K, Hunt K, Rogers H, Forbes A. Experiences of gestational diabetes and gestational diabetes care: a focus group and interview study. BMC Pregnancy Childbirth. 2018;18(1):25.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

Not applicable.

Funding

This work was supported by the Canadian Institutes of Health Research. Dr. Hanley is funded by a Michael Smith Foundation for Health Research Scholar Award.

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Authors and Affiliations

  1. Department of Obstetrics & Gynaecology, University of British Columbia, Rm 590 828 West 10th Ave, Vancouver, BC, V5Z 1M9, Canada

    Grace A. Thiele & Gillian E. Hanley

  2. Departments of Psychiatry, University of British Columbia (UBC), 938 W 28th Ave, Vancouver, BC, V5Z 4H4, Canada

    Deirdre M. Ryan

  3. Department of Pediatrics, University of British Columbia (UBC), 938 W 28th Ave, Vancouver, Canada

    Tim F. Oberlander

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  1. Grace A. Thiele
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  3. Tim F. Oberlander
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  4. Gillian E. Hanley
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Contributions

GT contributed to conception of the study and study design, performed and interpreted the statistical analyses and drafted the manuscript. GH contributed to the conception of the study and study design, interpretation of analyses, and participated in drafting and revising the manuscript. DR and TO both contributed to interpretation of analyses and participated in drafting and revising the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Gillian E. Hanley.

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Ethics approval and consent to participate

All methods were performed in accordance with relevant guidelines and regulations. Ethics approval for our use of deidentified, administrative data was approved by the University of British Columbia (UBC) Behavioural Research Ethics Board (H21-01401). Data access was approved by Population Data (PopData) BC and the relevant Data Stewards. Approvals from both the UBC Behavioural Research Ethics Board and PopData BC included a waiver of informed consent from participants.

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The authors have no conflicts to disclose.

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Thiele, G.A., Ryan, D.M., Oberlander, T.F. et al. Preconception mental health and the relationship between antenatal depression or anxiety and gestational diabetes mellitus: a population-based cohort study. BMC Pregnancy Childbirth 22, 670 (2022). https://doi.org/10.1186/s12884-022-05002-5

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Keywords

BMC Pregnancy and Childbirth

ISSN: 1471-2393

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