Biological Psychology 144 (2019) 11–19
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Partner social support during pregnancy and the postpartum period and inflammation in 3-month-old infants
T
Kharah M. Rossa, Jenna C. Thomasb, Nicole L. Letourneaua, Tavis S. Campbellb, ⁎ Gerald F. Giesbrechtc, , the APrON Study Team a
Faculty of Nursing, University of Calgary, Calgary, AB, Canada Department of Psychology, University of Calgary, Calgary, AB, Canada c Department of Pediatrics, University of Calgary, Calgary, AB, Canada b
A R T I C LE I N FO
A B S T R A C T
Keywords: Social support Pregnancy Postpartum period Infant Inflammation
Prenatal social stress “programs” offspring immune activity in animal models, but how the prenatal social environment affects human offspring inflammation is not known. Here, we test associations between prenatal partner support quality, i.e. positive/helpful support, negative/upsetting support, and their interaction, and infant inflammatory markers. A sample of 113 women from the Alberta Pregnancy Outcomes and Nutrition (APrON) cohort were followed from early pregnancy to 3-months postpartum. Partner support quality was measured during pregnancy and the postpartum period. Three-month-old infant blood samples were assayed for inflammatory markers, i.e., adaptive immune markers IFNγ, IL12p70 and IL10. The prenatal positive-by-negative partner support interaction predicted infant IFNγ, IL12p70, and IL10, p’s < .035, independent of covariates and postpartum partner support. When negative partner support was high, high positive support predicted higher infant IFNγ, IL12p70, and IL10. As such, partner support during pregnancy that is both highly negative/ upsetting and also highly positive/helpful predicted adaptive immunity markers in infants at 3 months of age.
1. Introduction Experiences in early life, i.e. during the prenatal period, can get “under the skin” before an individual is born to leave a lasting imprint on physiology and affect health trajectories over the lifespan (Gillman et al., 2007). Maternal experiences during pregnancy affect stress axes activity, e.g. hypothalamic-pituitary-adrenal (HPA) and sympatheticadrenal-medulla (SAM) pathways, which are signals transmitted to the fetus, either via direct transfer of signaling molecules across the placenta (e.g. cortisol) or indirectly by affecting placental function (Coe & Lubach, 2005; Irwin & Cole, 2011; Sapolsky, Romero, & Munck, 2000). This in turn affects fetal physiological development (Gillman et al., 2007). Developmental programming of the immune and inflammatory systems, in particular, has implications for risk for inflammatory diseases, including vascular diseases, allergies, asthma and susceptibility to infections (e.g., Chen, Liu, Yan, Wu, & Ping, 2016). Most research has focused on the developmental implications of the physical environment or maternal risk factors (e.g., Chen et al., 2016; Rogers & Velten, 2011; Swanson, Entringer, Buss, & Wadhwa, 2009; Wadhwa, Buss, Entringer, & Swanson, 2009). However, evidence from animal models suggests that prenatal social stressors, such as conflict or housing with strangers, ⁎
also predicts immune dysregulation in offspring (Coe & Crispen, 2000; Couret, Jamin, Kuntz-Simon, Prunier, & Merlot, 2009; Gotz & Stefanski, 2007). Humans are social animals, and the social environment is a powerful predictor of health in general (e.g., Dunkel Schetter, 2017) and immune function in particular (e.g., Kiecolt-Glaser, Gouin, & Hantsoo, 2010). In human samples, only three studies were found that reported associations between prenatal psychological stress, i.e. pregnancy anxiety, depression and stressful life events, and altered adaptive immunity in offspring (Entringer et al., 2008; Mattes et al., 2009; O’Connor et al., 2013). However, no studies have specifically assessed the role of the prenatal social environment in the developmental programming of the offspring immune system. The social environment is particularly important and salient during pregnancy (Dunkel Schetter, 2011). Access to social support, either perceived or received, is associated with better maternal outcomes, including lower prenatal distress (Rini, Dunkel Schetter, Hobel, Glynn, & Sandman, 2006) and better pregnancy outcomes (Collins, DunkelSchetter, Lobel, & Scrimshaw, 1993; Hoffman & Hatch, 1996; Williamson & LeFevre, 1992). Prenatal social support, both perceived and received, is also associated with inflammation and immune function during pregnancy, predicting healthier inflammatory profiles, e.g.
Corresponding author at: University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada. E-mail address:
[email protected] (G.F. Giesbrecht).
https://doi.org/10.1016/j.biopsycho.2019.03.005 Received 9 July 2018; Received in revised form 20 February 2019; Accepted 12 March 2019 Available online 15 March 2019 0301-0511/ © 2019 Elsevier B.V. All rights reserved.
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of different sources of support on maternal or child health during the child-bearing years (Dunkel Schetter, 2011), the general consensus is that the partner relationship is particularly important. Quality of partner relationships is associated with adverse pregnancy outcome risk (Dunkel Schetter, Sagrestano, Feldman, & Killingsworth, 1996; Hoffman & Hatch, 1996; Levitt, Weber, & Clark, 1986; Peacock, Bland, & Anderson, 1995). One study did compare associations between maternal inflammation during pregnancy with partner and closest friend or family relationship quality (Ross et al., 2017), and found that only partner relationship quality was associated with maternal inflammation. Given the centrality of the partner relationship during the childbearing years, and previously reported associations specifically between partner relationship quality and maternal inflammation, we chose to focus on social support from the partner. The purpose of this study was to evaluate associations between partner positive and negative social support, both during pregnancy and the postpartum period, with inflammatory biomarkers in 3-monthold infants. Partner social support was assessed during pregnancy and once during the postpartum period, and a blood sample was obtained from infants to assay inflammatory markers. Based on previous findings, we hypothesized that: 1) More positive or helpful partner support would be associated with lower infant inflammation, 2) more negative or upsetting partner support would be associated with higher infant inflammation, and 3) positive and negative partner support would interact, such that mothers with ambivalent partner relationships, i.e. high on both positive and negative aspects, would have 3-month-old infants with greater peripheral inflammation. Furthermore, we hypothesized that maternal experiences of partner social support during pregnancy would be a stronger predictor of infant inflammation than postpartum experiences of partner relationship quality (i.e. smaller effect sizes or non-significant postpartum associations, compared to prenatal associations), consistent with developmental origins of health.
lower pro-inflammatory markers (IL6 and CRP), and higher anti-inflammatory IL10 (Coussons-Read, Okun, & Nettles, 2007; Giurgescu et al., 2015; Ross et al., 2017), and healthier lymphocyte response to a candidin test (Herrera, Alvarado, & Martinez, 1988). (For an exception, see Coussons-Read, Okun, Schmitt, & Giese, 2005). Maternal immune system signals during pregnancy can cross to fetal circulation to impact offspring immune activity (Chandorkar, Ampasavate, Stobaugh, & Audus, 1999; Cheng, Davis, & Sharma, 2018; Jennewein, Abu-Raya, Jiang, Alter, & Marchant, 2017). Levels of prenatal inflammatory markers in maternal circulation are linked to levels of inflammatory markers in cord blood and in infants up to one year of age (Herberth et al., 2011; Onore, Schwartzer, Careaga, Berman, & Ashwood, 2014; Prescott et al., 2003; Ross et al., 2016). As such, factors that are associated with the maternal inflammatory milieu during pregnancy, such as social support, could affect maternal immune signalling to the fetus, and thus fetal immune development. No studies, however, have examined whether prenatal social support is associated with inflammation in the offspring. Previous studies of prenatal social support and inflammation have generally assumed that all kinds of support are equally beneficial to health, but this assumption is not necessarily true. Perceived social support is generally associated with positive health outcomes, whereas received social support is inconsistently associated with health outcomes or even with negative health outcomes (Cohen & Wills, 1985; Cutrona, 1990; Rini & Dunkel Schetter, 2010; Uchino, 2007). One explanation for this contradiction is that received social support is health beneficial only if it is perceived as effective (Rini & Dunkel Schetter, 2010). Social support that is ineffectively provided (e.g., unwanted, does not match support needs or is delivered in a manner that is upsetting or distressing) is associated with poor health outcomes (for reviews,see Uchino, 2007; Cohen & Wills, 1985, 1985; Cutrona, 1990; Rini & Dunkel Schetter, 2010), including greater distress during pregnancy, following a cancer diagnosis, and after hematopoietic stem cell transplantation (Reynolds & Perrin, 2004; Rini et al., 2006, 2011; Stapleton et al., 2012), greater cortisol reactivity following increases in psychological distress (Giesbrecht et al., 2013), and lower offspring cortisol stress reactivity (Thomas, Letourneau, Bryce, Campbell, & Giesbrecht, 2017). Other researchers have taken this a step further by noting that positive, helpful or effective support and negative, upsetting or ineffective support are not polar opposites, but are instead independent but correlated constructs (Burg & Seeman, 1994; Uchino, Holt-Lunstad, Uno, & Flinders, 2001). Furthermore, both positive and negative support aspects are independently associated with health, and researchers have recommended considering both when studying the effects of social support (Burg & Seeman, 1994; Uchino et al., 2001). A framework proposed by Uchino, Holt-Lunstad, Uno and Flinders Uchino et al. (2001) explicitly recognizes both the beneficial and detrimental aspects of social support, and expands this by further exploring how positive and negative support aspects combine or interact to predict health outcomes. Using this framework, close relationships can be defined as high to low on both positive/helpful and negative/upsetting dimensions of support. As such, individuals can be “supportive” (high positive, low negative), i.e. helpful in a way that is not upsetting; “aversive” (low positive, high negative), i.e. not helpful and also causing upset; “ambivalent” (high positive, high negative), i.e. providing help in a way that also causes upset; and “indifferent” (low positive, low negative), i.e. not helpful or upsetting in a support context (Uchino et al., 2001). When the combination of positive and negative support aspects are considered, ambivalent (high positive, high negative) partner relationships are associated with poor health outcomes, including higher markers of peripheral inflammation, e.g. IL6 and CRP (Uchino et al., 2013, 2015). No studies, however, have explored this framework during the child-bearing years to determine whether prenatal or postpartum positive support, negative support or the positiveby-negative interaction is associated with inflammation in infants. Although little systematic research has directly compared the effects
2. Methods 2.1. Participants The sample consisted of 113 women enrolled in an ongoing prospective cohort called the Alberta Pregnancy Outcomes and Nutrition (APrON) study (for more details, see Kaplan et al., 2014), which is a community sample recruited from prenatal clinics between 2009 and 2012. Women were included if they had a singleton pregnancy, were less than 22 weeks gestational age (GA) at the first study visit, and were 18 years of age or older. Women were excluded if they smoked or consumed alcohol during pregnancy, or were being treated with a synthetic glucocorticoid. For the purposes of these analyses, women were only included if they had consented to having an infant blood draw done at three months postpartum (46% or 116/254) and also reported being in an intimate partner relationship over the study follow-up (97% or 113/116). Participants received a $20 grocery gift voucher for every assessment completed. All protocols and procedures were reviewed and approved by the University of Calgary Institutional Review Board.
2.2. Procedure Mothers completed a battery of questionnaires twice during pregnancy, during the second trimester (14–26 weeks GA) and third trimester (27–42 weeks GA), and at 3 months postpartum using standardized questionnaires (for more information on measures, see Kaplan et al., 2014). At 3 months of age, an infant blood draw was completed by a certified pediatric phlebotomist to assess infant inflammatory markers (see below).
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and intracellular pathogen or viral immune activity [interferon (IFN)γ, interleukin (IL)1β, IL2, IL6, IL8, IL12p70, and tumor necrosis factor (TNF)α], and Th2 or anti-inflammatory cytokines involved in regulating immune responses and extracellular pathogen or humoral immune activity (IL10, IL13, IL4, IL5). In general, higher levels of proinflammatory/Th1 cytokines and lower levels of anti-inflammatory/ Th2 cytokines indicate potentially maladaptive immune activity. Coefficients of variance (CVs) were less than 10% for each cytokine. For statistical purposes, the lower limit of detection (LLD) was used when inflammatory marker concentrations were below the detection limit. Inflammatory markers were highly skewed, and were log transformed prior to analyses.
2.3. Partner social support Partner social support efforts were assessed at both pregnancy assessments and at 3 months postpartum using the Social Support Effectiveness Questionnaire (Rini & Dunkel Schetter, 2010). The questionnaire queries perceptions of received partner support or partner social support effectiveness over the previous three months, and consists of 25 items divided into two subscales: positive support and negative support. The positive support subscale (15 items) assesses the extent to which effective or helpful social support is provided. Participants are asked to rate three types of partner support: Instrumental support, or help with tasks and responsibilities (e.g. household chores, running errands, or childcare); informational support, or advice or information; and emotional support, or having someone to listen to and understand feelings or show affection and concern. For each type of support, participants rated how well support matched the amount needed [very poor (0) to excellent (4)]; whether the participant wished the support had been different from what was provided [not at all (0) to extremely (4)]; whether the support had been provided skillfully [not at all (0) to extremely (4)]; how difficult it had been to obtain support [never (0) to always (4)], and whether support had been offered without needing to ask [never (0) to always (4)]. The positive social support dimensions showed good internal validity across assessments, Cronbach’s α = .92 to .94. These 15 items were summed to create a positive support score at each assessment. Higher scores indicate greater positive partner support, with range of 0 to 60. The negative support subscale (10 items) assesses the extent to which the support provider was upsetting in support-seeking contexts, i.e. the extent to which the partner made the participant feel guilty or inadequate. Examples include feeling disrespected, helpless, stupid and angry. Items are responded to on a yes (2) or no (0) scale. The negative domain items showed good internal validity across assessments, Cronbach’s α = .99 to 1.00. Items were summed so that greater scores indicate greater negative support (range of 0–20). Positive and negative support totals were negatively correlated at each time point, r’s = −.56 to −.66. Both positive support, ICC = .67, and negative support, ICC = .53, showed high stability across all three assessments. The two pregnancy assessments were averaged to produce a pregnancy positive support and pregnancy negative support score. Interaction terms were calculated for both prenatal and postpartum partner support by centering the respective positive and negative support totals, and then taking their product. As such, predictor variables were pregnancy and postpartum positive support, negative support and the positive-by-negative interaction term. For descriptive purposes only, mean-splits of the positive support and negative support variables were used to determine the percentage of participants that fell into each of the traditionally-defined categories of partner relationship quality during pregnancy. The majority of women (47%) were in supportive partner relationships (high positive, low negative), 29% in aversive relationships (low positive, high negative), 13% in ambivalent partner relationships (high positive, high negative), and 11% in indifferent relationships (low positive, low negative).
2.5. Mediation variables Prenatal depressive symptoms, pregnancy-specific anxiety, prenatal sleep quality and prenatal stressful life events could account for any associations between partner support and child inflammatory markers. Depressive symptoms, pregnancy-specific anxiety, sleep quality and prenatal stressful life events were assessed at the same time as partner social support effectiveness during pregnancy. Depressive symptoms were measured using the Edinburgh Postnatal Depression Scale (Cox, Holden, & Sagovsky, 1987), pregnancy-specific anxiety using the Pregnancy Anxiety Scale (Rini, Dunkel-Schetter, Wadhwa, & Sandman, 1999), stressful life events using the Stressful Life Events Questionnaire (Bergman, Sarkar, O’Connor, Modi, & Glover, 2007), and sleep quality using the Pittsburgh Sleep Quality Inventory (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989). For each variable, values from both time points were averaged to obtain mean prenatal depressive symptoms, pregnancy-specific anxiety, sleep quality, and stressful life events. 2.6. Covariates Potential covariates were selected based on a review of the literature and for theoretical reasons, and included demographics [maternal age, per capita household income, education, race/ethnicity (White/ Caucasian vs. not), foreign born vs. Canada born, occupational status (working vs. not), and marital status (married vs. common-law)], health behaviors and lifestyle factors [smokers in the household, and maternal pre-pregnancy body mass index (BMI)], and pregnancy factors [parity (nulliparous vs. parous), pregnancy complications (diagnosis of diabetes, hypertension or preeclampsia vs. none), breastfeeding at 3 months postpartum (yes/no), and infant GA at birth or birth GA]. Only one (0.89%) reported living with a smoker, and only four (3.6%) reported any pregnancy complications, and therefore these variables were dropped from analyses. Of the remaining potential covariates, marital status, education, per capita household income, birth GA, breastfeeding and maternal pre-pregnancy BMI were associated with infant inflammatory markers, and so were retained as covariates (although patterns of results did not change whether a subset or all covariates were included in models). Participant education level was reported at study entry and coded as: Less than high school diploma (1), high school diploma (2), trade/technical school (3), university (4) and postgrad (5). Gestational age at birth was retrieved from labor and delivery medical records. Number of adults and children living in the household and household income over the past year were obtained at study entry. Participants reported household income on a ‘1′ (less than $20 000 per year) to ‘5′ ($100 000 or more) scale. To calculate household income, each participant was assigned the median of the selected category (e.g. $54 500 if ‘3: $40 000 to $69 999′ was selected). Participants who indicated earning either less than $20 000 or more than $100 000 were coded as $20 000 or $100 000, respectively. Per capita household income was calculated by dividing household income by the total number of adults and children in the home. At study entry, participant height was measured to the nearest
2.4. Infant inflammatory markers A blood sample was taken from 3-month-old infants via venipuncture. A #2 butterfly (winged infusion 12 in.) needle or 25-gauge 0.75-in. standard needle was used in the forearm to collect 3–4 ml of blood into an EDTA vacutainer tube (Fisher Scientific, Ontario, Canada). Inflammatory markers in infant plasma samples were assayed in duplicate by multiplex electrochemiluminescence, using a Th1/Th2 kit, as per kit instructions (MesoScale Discovery, Rockville, MD, USA) at the University of Alberta. Assayed inflammatory markers were C-reactive protein (CRP), a general marker of inflammatory activity; Th1 or pro-inflammatory cytokines involved in activating immune responses 13
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during pregnancy are summarized in Table A.2. Significant associations were observed between pregnancy support variables and IFNγ, IL12p70, IL10, and IL4. As such, only IFNγ, IL12p70, IL10, and IL4 were examined in models adjusting for covariates, i.e. marital status, maternal education, per capita household income, birth GA, breastfeeding at 3 months postpartum, and maternal pre-pregnancy BMI. Final linear regression models with covariates included are presented in Table 2 (full models, reporting coefficients for covariates, are reported in Table A.3 in supplemental materials).
0.1 cm using a SECA 214 portable stadiometer. At the same time, participants self-reported their pre-pregnancy weight. Pre-pregnancy BMI (kg/m2) was then calculated by dividing participant weight (kg) by participant height squared (m2). 2.7. Analytic strategy All statistics were run using IBM SPSS Statistics 24 (IBM, 2016). Prior to analyses, all variables were inspected for normality (see above) and outliers. Values greater than three standard deviations from the mean were Winsorized to three standard deviations from the mean. Because inspection of correlations does not capture any effect of an interaction, separate models testing unadjusted associations between pregnancy or postpartum positive support, negative support and the positive x negative interaction term with each infant inflammatory marker were run to determine on which cytokines to focus. Models with significant main or interactive effects were followed by linear regression models adjusting for covariates, i.e. marital status, education, per capita household income, birth GA, breastfeeding and maternal prepregnancy BMI. Significant interactions were probed using the Johnson-Meyer technique (Preacher, Curran, & Bauer, 2003). Regression coefficients and covariances are used to: 1) calculate the predictoron-outcome simple slopes for different values of the moderator, and 2) regions of significance, or moderator values at which simple slopes transition from non-significant to significant. Here, negative support was treated as the predictor (X) and positive support as the moderator (Z). Two sets of exploratory analyses were conducted. First, the independent effects of prenatal and postpartum partner support were considered. Linear regression models predicting significant infant inflammatory markers were run that included both prenatal and postpartum partner social support variables and covariates. Second, the role of mediation variables (prenatal depressive symptoms, pregnancy-specific anxiety, stressful life events and sleep quality) were considered. In order for an explanatory variable to mediate associations between partner support and infant inflammatory markers, the mediation variable should be (1) associated with the outcome variable (infant inflammatory markers) and (2) significantly associated with partner support. As such, correlations between explanatory variables and infant inflammatory markers were first inspected, and linear regression models predicting inflammatory variables from partner support variables were tested. Finally, a false discovery rate correction was applied to the models tested (Benjamini & Hochberg, 1995; Glickman, Rao, & Schultz, 2014). P values are ranked from lowest to highest, and criterion p values are adjusted based on the formula: pi ≤ d (i/n). Where d = false discovery rate (d = .05), n = total number of tests or p values, i = rank of the p value (such that 1 = lowest p value), and pi = ith p value. The correction is applied sequentially to each p value, starting from the highest, until an observed p value is less than the adjusted criterion p value.
3.2.1. IFNγ In linear regression models with covariates, greater partner negative support during pregnancy was associated with greater infant IFNγ, b = 0.014, SE = 0.007, p = .046. Positive support, however, was not, b = 0.002, SE = 0.003, p = .592. These independent effects were qualified by a significant positive-by-negative support interaction term, b = 0.001, SE = 4.26 × 10−4, p = .033. The interaction was probed by decomposing the simple slopes, which (1) provides a value of the moderator (positive support) at which the association between the predictor (negative support) and the outcome (IFNγ) becomes significant, and (2) the simple slope of the association between negative support and IFNγ at that value of positive support. Associations between negative support and IFNγ were significant (p < .05) when positive support was relatively high, or when positive support scores were greater than 42.9. Specifically, when positive support was relatively high, higher negative support was associated with higher infant IFNγ, b = 0.014, SE = 0.007, p < .05 (Fig. 1A). In other words, mothers with partners who were both helpful (high positive support) and upsetting (high negative support) when seeking support during pregnancy had 3 month-old infants with higher viral-immunity IFNγ. This exposure profile is consistent with an ambivalent pattern of partner relationship, as per the framework proposed by Uchino et al. (2001). 3.2.2. IL12p70 Neither negative pregnancy support, b = 0.005, SE = 0.003, p = .062, nor positive pregnancy support, b = 0.001, SE = 0.001, p = .291, were independently associated with IL12p70 when covariates were added to the model. However, a significant positive-by-negative support interaction was detected, b = 4.81 × 10−4, SE = 1.68 × 10−4, p = .005, such that when positive support was high (> 43.7 positive support score), high negative support was associated with higher infant IL12p70, b = 0.006, SE = 0.003, p < .05 (Fig. 1B). As with IFNγ, this is consistent with an ambivalent pattern of partner relationship quality being associated with adaptive viral-immunity activation (IL12p70). 3.2.3. IL10 Again, neither negative pregnancy support, b = 0.012, SE = 0.006, p = .058, nor positive pregnancy support were associated with IL10, b = 0.002, SE = 0.003, p = .448, but a significant positive by negative interaction term was detected, b = 0.001, SE = 3.71 × 10−4, p = .023. The interaction was decomposed, and again, when positive support was high (> 43.6 positive support score), high negative support was associated with higher infant IL10, b = .013, SE = 0.006, p < .05 (Fig. 1C). This is again consistent with an ambivalent pattern of partner close relationship quality being associated with higher anti-inflammatory IL10.
3. Results 3.1. Sample characteristics Sample characteristics are presented in Table 1. Mothers were on average 31.2 ± 3.91 years old at study entry, White (86%), and married (93%). Correlations among infant inflammatory cytokines and pregnancy and postpartum support variables are presented in Table A.1 in supplemental materials.
3.2.4. IL4 With covariates included in models, neither negative support, b = 0.002, SE = 0.002, p = .345, nor positive support, b = 2.19 × 10−4, SE = 0.001, p = .827, during pregnancy were associated with infant IL4. However, a significant negative-by-positive support interaction was detected, b = 2.88 × 10−4, SE = 1.35 × 10−4, p = .035. When the interaction was decomposed, simple slopes were significant outside the range of possible values for positive support
3.2. Pregnancy partner support and infant inflammatory markers Results of unadjusted linear regression models predicting infant inflammatory markers from mother’s perceptions of partner support 14
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Table 1 Sample characteristics (n = 113). Note: BMI = body mass index, GA = gestational age. Variable
Mn ± SD or % (N)
Variable
Mn ± SD or % (N)
Age (years) Maternal race/ethnicity Caucasian Asian Other First assessment gestational age (weeks) Second assessment gestational age (weeks) Infant birth GA (weeks) Postpartum assessment (weeks) Pregnancy positive support Pregnancy negative support
31.2 ± 3.92
Married Education High school or less University or technical/trade Post-graduate training Per capita household income ($) Maternal pre-pregnancy BMI (kg/m) Nulliparous Breastfeeding (yes) Postpartum positive support Postpartum negative support
93 (105)
86 (97) 8 (9) 6 (7) 15.1 ± 3.67 32.3 ± .792 39.4 ± 1.43 12.7 ± 1.35 43.0 ± 8.62 3.75 ± 4.18
10 (11) 73 (83) 17 (19) 34 939 ± 15 523 24.8 ± 5.28 37 (41) 89 (101) 42.4 ± 9.58 3.77 ± 4.47
Table 2 Summary of regression models with covariates included. Note: BMI = body mass index; GA = gestational age; IFN = interferon; IL = interleukin. The full linear regression model, including coefficients for covariates, are presented in Supplemental Table A.3. Variable
b
SE
P
Pregnancy IFNγ Negative support Positive support Interaction IL4 Negative support Positive support Interaction
.014 .002 .001 .002 2.19 × 10−4 2.88 × 10−4
.007 .003 4.26 × 10−4 .002 .001 1.35 × 10−4
.046 .592 .033 .345 .827 .035
Postpartum Period IL5 Negative support Positive support Interaction
−.004 −.001 −1.31 × 10-4
.002 .001 1.69 × 10−4
.107 .599 .442
IL10
IL12p70
IL6
Variable
b
SE
P
Negative support Positive support Interaction Negative support Positive support Interaction
.012 .002 .001 .005 .001 4.81 × 10−4
.006 .003 3.71 × 10−4 .003 .001 1.68 × 10−4
.058 .448 .023 .062 .291 .005
Negative support Positive support Interaction
−.006 −.001 −6.81 × 10-5
.003 .001 2.24 × 10−4
.071 .365 .761
associated with infant IL6, p’s > .071, or infant IL5, p’s > .107.
(> 69.2 positive support score). Given that the maximum value possible on the positive support scale is 60, this interaction could not be interpreted.
3.4. Independent contribution of prenatal and postpartum partner support To test the independent contributions of partner support during both pregnancy and the postpartum period, separate linear regression models were run predicting infant IL10, IL12p70 and IFNγ that included both prenatal and postpartum partner social support variables. Significant interactions between prenatal partner positive and negative support persisted, independent of postpartum partner support, for both IL10 and IL12p70, p’s < .040. (When postpartum partner support variables were included in models, the prenatal interaction between positive and negative partner support no longer significantly predicted
3.3. Postpartum partner support and infant inflammatory markers Results of linear regression models predicting infant inflammatory markers from mother’s perceptions of partner support at three months postpartum are summarized in Table A.2. Significant associations between postpartum support variables and IL5 and IL6 were detected in unadjusted models. As such, only IL5 and IL6 were examined in models adjusted for covariates (see Table 2). With covariates included in the model, however, none of the postpartum support variables were
Fig. 1. Graph of the positive x negative support interaction predicting 3-month-old infant IFNγ (Panel A), IL12p70 (Panel B) and IL10 (Panel C), controlling for marital status, maternal education, per capita household income, birth GA, breastfeeding at 3 months postpartum, and maternal pre-pregnancy BMI. During pregnancy, when positive support was high, the association between negative support and infant IFNγ, IL12p70, and IL10 was steeper. * Indicates significant simple slopes, p < .05. 15
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2015; Herrera et al., 1988). Although most research treats social support as a single construct, support can also be considered along positive/helpful and negative/upsetting dimensions (e.g., Burg & Seeman, 1994; Uchino et al., 2001). When this approach was applied here, positive or helpful aspects of partner support were not independently associated with infant inflammatory markers. Negative or upsetting aspects of partner support during pregnancy, however, were associated with higher infant IFNγ, an indicator of viral immunity, independent of positive partner support. This pattern is consistent with the observation that “bad is stronger than good” (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001; Rook, 1998), or that negative experiences can have a more potent effect on health and well-being compared to positive ones. The most consistent predictor of infant inflammatory markers, however, was the interaction between positive and negative support aspects. Specifically, ambivalent prenatal partner relationships was associated with higher infant IL10, IL12p70 and IFNγ, independent of the separate positive and negative components, consistent with previous research reporting associations between ambivalent partner relationships and increased inflammation in middle-aged or older married couples (Uchino et al., 2013, 2015). It is still not known why ambivalent patterns of support are associated with adverse health outcomes, although here differences in prenatal depressive symptoms, pregnancy-specific anxiety, prenatal stressful life events and prenatal sleep quality did not account for associations between prenatal partner support and infant inflammation. There are several additional possible explanations for associations between ambivalence and health outcomes. First, ambivalence could result when provided support does not match support needs (Cohen & Wills, 1985; Cutrona, 1990). For example, receiving advice on healthy eating when help preparing meals is actually being sought could be considered a helpful and upsetting support attempt. Second, ambivalence could arise due to unwanted or overprovision of support (e.g., Reynolds & Perrin, 2004; Brock & Lawrence, 2009). For example, insisting on taking over household tasks in a way that reduces a pregnant woman’s sense of autonomy could be considered a helpful but upsetting support attempt. Third, ambivalence could be driven by unskilled support attempts (e.g., Rini et al., 2006; Vangelisti, Sarason, & Sarason, 2009). Attempting to calm an anxious mother by noting that her anxiety could be “hurting the baby” would be considered a support attempt that is both helpful and upsetting. And fourth, ambivalence could result when support is provided with reluctance or condescension, in a manner that suggests lack of reliability or predictability of support availability (e.g., Uchino, 2007). For example, making a pregnant spouse feel guilty because recreational plans were cancelled in order to drive her to an appointment would be helpful but also upsetting. In each instance, ambivalent support attempts could have a detrimental impact on health, either by directly causing or exacerbating distress or interfering with attempts to cope with stress. Only two other studies have tested whether positive and negative close relationship qualities together predict maternal health during the child bearing years. In contrast to what was observed in this study, previous studies reported an effect of indifferent partner relationships. Indifferent partner relationships are defined as low in both positive and negative aspects, and were associated with higher maternal inflammation during the third trimester of pregnancy (Ross et al., 2017), and worse maternal cardio-metabolic health over the first year postpartum (Ross, Guardino, Hobel, & Dunkel Schetter, 2018). It is not clear why indifferent partner relationships are associated with inflammatory markers in pregnant women, but ambivalent relationships predict inflammatory markers in infants. Fetal and maternal physiology could be differentially sensitive to various aspects of close relationships. For example, indifferent partner relationships could indicate neglect, apathy or withdrawal (DeLongis, Capreol, Holtzman, O’Brien, & Campbell, 2004), which could be particularly distressing for women in the context of pregnancy and parenting small children. In contrast, ambivalent partner relationships could indicate unpredictability and lack of reliability (Uchino et al., 2001), potentially important cues when
infant IFNγ, b = 0.001, SE = 0.001, p = .192). As such, associations between prenatal partner support and infant IFNγ, IL12p70 and IL10 appear to be largely independent of postpartum partner support quality. 3.5. Mediation Depressive symptoms, pregnancy-specific anxiety, stressful life events and sleep quality were tested as mediators of associations between prenatal partner support and infant IFNγ, IL12p70 and IL10. Only prenatal depressive symptoms were associated with an infant inflammatory marker, specifically IL12p70, r = -.242, p = .015. Next, a linear regression model was run predicting prenatal depressive symptoms from prenatal partner positive support, negative support, and the positive-by-negative support interaction. Higher negative partner support, b = .216, SE = .106, p = .045, and lower positive partner support, b = -0.104, SE = .047, p = .030, were associated with higher prenatal depressive symptoms. However, the positive-by-negative interaction term was not associated with prenatal depressive symptoms, b = -0.006, SE = 0.006, p = .337, indicating that prenatal depressive symptoms did not meet criteria to significantly mediate associations between prenatal ambivalent partner support and infant inflammatory markers. 3.6. False discovery rate correction Six infant inflammatory marker outcomes were considered in adjusted linear regression models, for a total of 6 tests. A false discovery rate correction was applied sequentially to each p-value, starting from the highest to the lowest. Only the prenatal positive-by-negative interaction predicting IL12p70 (p6 = .005 < .008) continued to be significant per the false discovery rate-adjusted criterion p-value, suggesting that ambivalent partner support during pregnancy is associated with an infant pro-inflammatory, Th1 cytokine that is a key regulator of viral immune responses and risk for future allergies (Piancatelli, Bellotta, Del Beato, Duse, & Della Penna, 2008). 4. Discussion The purpose of this study was to determine whether mothers’ partner support during pregnancy was associated with inflammatory markers in 3-month-old infants, in a manner consistent with developmental programming of health. Mother support from her partner during pregnancy, but not the postpartum period, was associated with offspring inflammatory markers at 3-months of age. Specifically, mothers with ambivalent partners, i.e. high positive and high negative support, had infants with higher IL10, IL12p70 and IFNγ (and only IL12p70 after adjusting for false discovery rates). Prenatal social support is associated with maternal inflammation during pregnancy (Ross et al., 2017), and maternal inflammation during pregnancy is associated with inflammation in infants (Herberth et al., 2011; Onore et al., 2014; Prescott et al., 2003; Ross et al., 2016), suggesting that social support during pregnancy could predict inflammation in infants through crosstalk between the maternal and fetal immune systems during pregnancy. This is the first study, to our knowledge, to test associations between prenatal social support and inflammation in offspring, and suggests that mother’s normative experiences of partner relationship quality during pregnancy could have implications for developmental “programming” of infant inflammatory activity. Evidence from animal models indicates a deleterious effect of prenatal social stress on offspring immune function (Coe & Crispen, 2000; Couret et al., 2009; Gotz & Stefanski, 2007), but the role of the social environment in the human context was not known. Social support, in particular, is a well-documented and potent predictor of better health and well-being, both in general (Holt-Lunstad, Smith, & Layton, 2010; Uchino, 2009) and specific to pregnancy and the postpartum period (e.g., Rini et al., 2006; Coussons-Read et al., 2007; Giurgescu et al., 16
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branch of the adaptive immune system that fights extracellular pathogens or humoral immunity (Jankovic & Feng, 2015; Kidd, 2003). Increased concentrations of these cytokines could suggest an up-regulated, “primed” adaptive immune state, with implications for infant responses to viral infection. The immunological roles of cytokines, however, is primarily derived from studies of the adult immune system, which is fundamentally different from the newborn or infant immune system (Adkins, Leclerc, & Marshall-Clarke, 2004; PrabhuDas et al., 2011; Simon, Hollander, & McMichael, 2015), and so it is not clear how well this literature generalizes to infants. Elevated IL12p70, but also IL10 and IFNγ, could also indicate altered risk for allergies and atopic dermatitis. Infants that go on to develop allergies demonstrate a Th2-skewed immune profile, characterized by reduced Th1 cytokine immune cell production following allergen challenge, e.g., lower IL12p70 and IFNγ (Chung, Miller, Wilson, McGeady, & Culhane, 2007; Nilsson et al., 2004; Prescott et al., 2003). Although this could be interpreted as prenatal ambivalent support potentially conferring reduced allergy risk via higher levels of infant IL12p70, cytokine production following immune challenge does not necessarily correspond with levels of inflammatory protein in peripheral circulation (e.g., Miller, Rohleder, & Cole, 2009; Miller & Chen, 2010). Indeed, a study of peripheral cytokine levels reported associations between higher infant IL12p70 and increased risk for atopic dermatitis (Piancatelli et al., 2008), suggesting that prenatal ambivalent support could increase allergy risk via IL12p70. Regardless, given that effects of prenatal stress on the offspring immune system can vary by age and developmental stage (Hodyl, Krivanek, Lawrence, Clifton, & Hodgson, 2007; Piancatelli et al., 2008; Sobrian et al., 1997), follow-up research is required to determine whether the alterations in inflammatory activity in 3-month-olds observed here is ultimately beneficial, harmful, or even persist long-term. There are several limitations to the current study that should be acknowledged. First, although differences in peripheral adaptive immunity cytokines IL12p70, IFNγ, and IL10 were detected by prenatal partner support quality, we cannot infer the specific immune cells or mechanisms involved. Future research should consider examining immune cellular activity, by exploring differences in immune cell gene expression profiles or testing immune cell responses to viral antigens or allergens in vitro. Second, the physiological pathways through which maternal experiences of partner relationship quality during pregnancy could be transmitted to offspring were not explored. Although we considered a number of behavioral and medical pathways through which partner support or maternal inflammation during pregnancy could influence offspring inflammatory markers, including gestational age at birth, breastfeeding, prenatal exposure to smoking or alcohol, pregnancy complications, depressive symptoms, stressful life events, pregnancy-specific anxiety and sleep quality, we were unable to directly test biological pathways. Future research should test whether maternal immune or inflammatory activity during pregnancy mediates the association between prenatal partner relationship quality and infant inflammatory activity, and whether differences in infant inflammatory activity are reflected in immune cell epigenetic profiles. In conclusion, mothers with partners who were both highly helpful and highly upsetting when seeking social support (ambivalent) during pregnancy had infants with higher IL12p70, IFNγ, and IL10, independent of postpartum partner support and covariates. This is the first study to suggest that partner support efforts within the range of the norm could be a prenatal signal transmitted to offspring to affect infant inflammatory profiles.
tuning fetal phenotype to an expected environment. It is also possible, however, that differences in results could be due to measurement differences. The two studies that found an effect of indifference operationalized positive relationship quality as social support or satisfaction, and negative as conflict (Ross et al., 2017, 2018). In contrast, this and other studies (e.g., Uchino et al., 2013) that found an effect of ambivalence defined positive aspects as helpful support and negative aspects as upsetting support. As such, it is possible that the pattern detected (ambivalent vs. indifferent) could also depend on how positive and negative close relationship quality is operationalized. Additional research comparing the different measurement approaches in both maternal and infant samples is needed to clarify these issues. Although postpartum partner support was more temporally proximal to when infant inflammatory markers were assessed, prenatal partner support was more consistently associated with offspring inflammation. This suggests that partner support quality could be a valuable prenatal environmental cue transmitted from the mother to the fetus during gestation. Although the literature suggests that prenatal partner support could affect infant inflammation through maternal prenatal inflammation, we were unable to test this hypothesis directly. There are several plausible pathways that could account for how maternal psychosocial experiences during pregnancy affect infant inflammatory activity. Signals from the maternal immune system are known to cross into fetal circulation during pregnancy to program offspring immune activity (Chandorkar et al., 1999; Cheng et al., 2018; Garay, Hsiao, Patterson, & McAllister, 2013; Hsiao, McBride, Chow, Mazmanian, & Patterson, 2012; Jennewein et al., 2017). Maternal immune signals could be directly transmitted from maternal to fetal circulation. Although studies of maternal inflammatory protein transport from maternal to fetal circulation in term placentas have yielded mixed results (Aaltonen, Heikkinen, Hakala, Laine, & Alanen, 2005; Kent, Sullivan, & Elder, 1994; Reisenberger et al., 1996; Zaretsky, Alexander, Byrd, & Bawdon, 2004), labelled (125I) IL6 injected into the circulation of rats mid-pregnancy was detectable in fetuses (Dahlgren, Samuelsson, Jansson, & Holmang, 2006). This suggests that inflammatory proteins can directly cross from maternal to fetal circulation, but permeability could depend on gestational stage. Immune signals could also be transmitted indirectly, for example by activating placenta production of inflammatory proteins that are then secreted into fetal circulation (e.g., Duncombe, Veldhuizen, Gratton, Han, & Richardson, 2010; Hsiao & Patterson, 2011; Wu, Hsiao, Yan, Mazmanian, & Patterson, 2017), or disrupting microchimerism, the low-level migration of maternal cells into the fetus. Maternal microchimeric cells play a role in fetal immune cell maturation, and disruption of these processes could negatively impact fetal immune system development (Cheng et al., 2018). Finally, it is also possible that prenatal psychosocial factors like social support affect activation of non-immune pathways, i.e. HPA or SAM axes, that are known to regulate both maternal and placental immune activity (Coe & Lubach, 2005; Irwin & Cole, 2011; Sapolsky et al., 2000). Future research is necessary to disentangle specific mechanisms linking prenatal partner support and infant inflammatory activity. The developmental origins of health hypothesis proposes that phenotypic modifications due to prenatal cues are meant to improve adaptation to the early-life environment, and mismatches between the early developmental and adult environments potentially increase risk for poor health outcomes (Gillman et al., 2007). Prenatal exposure to partners who provided ambivalent support was associated with higher IL12p70, IL10, and IFNγ in offspring, suggesting altered adaptive immune activity in infants, consistent with previous studies of prenatal distress and adaptive immune responses in humans (Entringer et al., 2008; Mattes et al., 2009; O’Connor et al., 2013). Higher infant IL12p70, IL10, and IFNγ could indicate an adaptive immune system “primed” to respond to viral challenges. In general, IL12p70 and IFNγ are Th1 cytokines, regulating the branch of the adaptive immune system involved in fighting intracellular infections, such as viruses. In contrast, IL10 is an anti-inflammatory and Th2 cytokine, regulating the
Acknowledgements Funding for this study was provided by Alberta Innovates Health Solutions, Canadian Institutes of Health Research, National Centre of Excellence AllerGen and Alberta Children’s Hospital Foundation. The authors gratefully acknowledge the support of the APrON Study Team, 17
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whose individual members are Bonnie J. Kaplan, Nicole Letourneau, Catherine J. Field, Deborah Dewey, Rhonda C. Bell, Francois P. Bernier, Marja Cantell, Linda M. Casey, Misha Eliasziw, Anna Farmer, Lisa Gagnon, Gerald F. Giesbrecht, Laki Goonewardene, David W. Johnston, Libbe Kooistra, Donna P. Manca, Jonathan W. Martin, Linda J. McCargar, Maeve O’Beirne, Victor J. Pop, and Nalini Singhal.
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