Background: Screening for changes in pregnancy-related anxiety and depressive symptoms during pregnancy may further our understanding of the relationship between these two variables and preterm birth.Objectives: To determine whether changes in pregnancy-related anxiety and depressive symptoms during pregnancy influence the risk of preterm birth among Pakistani women; explore whether perceived stress moderates or mediates this relationship, and examine the relationship between the various components of pregnancy-related anxiety and preterm birth.Methods: A prospective cohort study design was used to recruit a diverse sample of 300 low-risk pregnant women from four centers of Aga Khan Hospital for Women and Children in Karachi, Pakistan. Changes in pregnancy-related anxiety and depressive symptoms during pregnancy were tested. Multiple logistic regression analysis was used to determine a predictive model for preterm birth. We then determined if the influence of perceived stress could moderate or mediate the effect of depressive symptoms on preterm birth.Results: Changes in pregnancy-related anxiety (OR = 1.1, CI 0.97–1.17, p = 0.167) and depressive symptoms (OR = 0.9, CI 0.85–1.03, p = 0.179) were insignificant as predictors of preterm birth after adjusting for the effects of maternal education and family type. When perceived stress was added into the model, we found that changes in depressive symptoms became marginally significant after adjusting for covariates (OR = 0.9, CI 0.82–1.01, p = 0.082). After adjusting for the mediation effect of change in perceived stress, the effect of change in depressive symptoms on preterm birth were marginally significant after adjusting for covariates. Among six different dimensions of pregnancy-related anxiety, mother’s concerns about fetal health showed a trend towards being predictive of preterm birth (OR = 1.3, CI 0.97–1.72, p = 0.078).Conclusions: There may be a relationship between perceived stress and antenatal depressive symptoms and preterm birth. This is the first study of its kind to be conducted in Pakistan. Further research is required to validate these results.

Background: We determined whether dimensions of psychosocial distress during pregnancy individually and collectively predicted preterm birth (PTB) in Pakistani women as it may be misleading to extrapolate results from literature predominantly conducted in high-income countries.Methods: This cohort study included 1603 women recruited from four Aga Khan Hospital for Women and Children in Sindh, Pakistan. The primary binary outcome of PTB (i.e., livebirth before 37 completed weeks’ gestation) was regressed on self-reported symptoms of anxiety (Pregnancy-Related Anxiety (PRA) Scale and Spielberger State-Trait Anxiety Inventory Form Y-1), depression (Edinburgh Perinatal Depression Scale (EPDS)), and covariates such as chronic stress (Perceived Stress Scale) assessed with standardized question and scales with established language equivalency (Sindhi and Urdu).Results: All 1603 births occurred between 24 and 43 completed weeks’ gestation. PRA was a stronger predictor of PTB than other types of antenatal psychosocial distress conditions. Chronic stress had no effect on the strength of association between PRA and PTB and a slight but non-significant effect on depression. A planned pregnancy significantly lowered risk of PTB among women who experienced PRA. Aggregate antenatal psychosocial distress did not improve model prediction over PRA.Conclusions: Like studies in high-income countries, PRA became a strong predictor of PTB when considering interactive effects of whether the current pregnancy was planned. Women’s resilience and abilities to make sexual and reproductive health decisions are important to integrate in future research. Findings should be generalized with caution as socio-cultural context is a likely effect modifier. We did not consider protective/strength-oriented factors, such as resilience among women.

Climate change (CC) poses risks to mental health, with pregnant women highly vulnerable due to unique physiological, emotional, and social changes. This study explored the relationship between cognitive appraisal of CC, emotional responses (e.g. eco-anxiety and solastalgia), and pro-environmental actions and mental well-being in 27 pregnant women in Canada. We used validated online surveys including measures of depressive symptoms and generalized and pregnancy-related anxiety (PRA). Results indicate that cognitive appraisal of CC showed a significant direct effect on anxiety severity when adjusted for all covariates. Eco-anxiety was significantly associated with all mental health measures, while solastalgia was significantly associated with P-RA. Pro-environmental actions showed no significant association. Contextual factors did not modify these relationships. These findings highlight that emotional responses to CC, rather than cognitive appraisal or actions, are important predictors of mental health during pregnancy, warranting further research in larger, diverse populations, particularly in regions severely affected by CC.

Allostatic load is a well-recognized indicator of cumulative physiological stress during pregnancy, with scores derived from biomarker algorithms that hold promise for identifying women at risk of preterm birth. However, there is currently no consensus on the most accurate and reliable method for aggregating these biomarkers into a composite allostatic load score, and the comparative predictive performance of various scoring approaches—along with the influence of assessment timing—remains insufficiently explored. To compare multiple allostatic load scoring algorithms’ ability to predict preterm birth among pregnant women and assess the impact of biomarker assessment timing on these associations. This prospective longitudinal cohort study (2018–2020) enrolled 1576 healthy women (10–19 weeks’ gestation), reassessed 1140 at 22–29 weeks from four Pakistani antenatal clinics. Six allostatic load biomarkers were measured with seven scoring algorithms applied to derive allostatic load scores. Their associations with preterm birth were assessed using logistic regression, with model comparisons made by Akaike Information Criterion and Area under the Curve. Average allostatic load scores across algorithms ranged from 0.16 to 6.13, with 13.1% of participants experiencing preterm birth. Six of seven allostatic load scoring algorithms—highest quartile, two-sided quartiles, highest decile, extreme z-scores, clinical limits, and extreme sextiles—were significantly associated with preterm birth when assessed in early pregnancy, though associations weakened at 22–29 weeks. Clinical limits scoring showed the strongest association with preterm birth early in pregnancy but lost significance later. The association between allostatic load and preterm birth varies by scoring algorithm and timing, with early clinical limits assessment offering robust prediction. While extreme sextiles, highest quartile and decile algorithms predict preterm birth at 22–29 weeks, they lack standardized cut-offs. Early assessment and allostatic load scoring using clinical limits offers a robust, objective tool to assess risk of preterm birth. Standardizing cut-offs for extreme sextiles and highest quantile could produce allostatic load measures that are less sensitive to timing and can complement clinical thresholds as effective screening tools.

Background: The coparenting relationship plays an important role in raising a child. The Coparenting Relationship Scale (CRS) is widely used to assess the multidimensional nature of coparenting; however, its psychometric properties have not been examined separately among mothers and partners, particularly in low- and middle-income country settings. This study evaluated the factor structure of the CRS among first-time mothers and partners in Karachi, Pakistan. Methods: The full study recruited primiparous mothers and their partners during the first or second trimester from a tertiary care hospital in Karachi, Pakistan. The analysis utilized data from 120 mothers and 102 partners who consented to participate at 12 weeks postpartum. Confirmatory factor analyses (CFAs) were performed separately for mothers and partners using the WLSMV estimator. Internal consistency was assessed using Cronbach alpha coefficients for each CRS subscale. Results: The seven-factor model demonstrated good model fit among mothers, with latent factor correlations within the admissible range and standardized factor loadings ranging from 0.49 to 0.92. Among partners, preliminary findings indicated that a six-factor model in which Coparenting Closeness and Endorsement of Partner’s Parenting were combined provided a more appropriate representation of the data. Most CRS subscales demonstrated satisfactory internal consistency; however, the Division of Labor subscale demonstrated low reliability among both mothers and partners. Conclusions: The findings provide preliminary evidence regarding the factor structure of the CRS among Pakistani mothers and partners.