Relationships between psychosocial factors during pregnancy and preterm birth in Puerto Rico.

Psychosocial stress during pregnancy has been associated with adverse pregnancy outcomes including preterm birth (PTB). This has not been studied in Puerto Rico, an area with high PTB rates. Our objective was to develop a conceptual model describing the interrelationships between measures of psychosocial stress and depression, a result of stress, among pregnant women in Puerto Rico and to examine their associations with PTB. We used data from the Puerto Rico Testsite for Exploring Contamination Threats pregnancy cohort (PROTECT, N = 1,047) to examine associations among depression and different continuous measures of psychosocial stress using path analysis. Psychosocial stress during pregnancy was assessed using validated measures of perceived stress, negative life experiences, neighborhood perceptions and social support. Logistic regression was used to examine associations between psychosocial stress measures in tertiles and PTB. Perceived stress, negative life experiences, and neighborhood perceptions influenced depression through multiple pathways. Our model indicated that perceived stress had the strongest direct effect on depression, where one standard deviation (SD) increase in perceived stress was associated with a 57% SD increase in depression. Negative life experiences were directly but also indirectly, through perceived stress, associated with depression. Finally, neighborhood perceptions directly influenced negative life experiences and perceived stress and consequently had an indirect effect on depression. Psychosocial stress was not associated with PTB across any of the measures examined. Our study examined interrelationships between multiple measures of psychosocial stress and depression among a pregnant Puerto Rican population and identified negative neighborhood perceptions as important upstream factors leading to depression. Our findings highlight the complex relationship between psychosocial stress measures and indicate that psychosocial stress and depression, assessed using 5 different scales, were not associated with PTB. Future research should investigate other environmental and behavioral risk factors contributing to higher rates of PTB in this population.

Introduction

Preterm birth (PTB), one of the leading causes of neonatal morbidity and mortality worldwide, disproportionately impacts pregnancies in Puerto Rico. The rates of PTB in Puerto Rico are some of the highest both in the U.S. and globally, with rates as high as 19.9% in 2006[1]. The PTB rate in Puerto Rico declined to 11.9% in 2018, which remains high relative to the mainland U.S. [2]. Some studies have shown that psychosocial stress, as indicated by stressful life events, perceived stress, and depression, is higher among women who go on to deliver preterm [3]. However, associations remain inconsistent and population-specific [3]. In Puerto Rico, pregnant women may also be at a heightened risk for psychosocial stress and clinical outcomes influenced by stress, as an estimated 10% of Puerto Ricans experience major depressive disorder as compared to 8% in the rest of the U.S. [4]. Thus, maternal psychosocial stress during pregnancy may represent a particularly important risk factor for PTB in the Puerto Rican population.

The relationships between measures of psychosocial stress are complex. Psychosocial stress can be triggered from many different sources [5], and is often more prevalent among those with low socioeconomic status (SES) [6]. Increased stressful life events, perceived stress, and a lack of social support are associated with increased symptoms of depression during pregnancy [7-9]. Social support may buffer the effects of stress, although existing studies testing this hypothesis are limited [3]. A growing body of literature also suggests that the quality of one’s neighborhood may be a source of psychosocial stress or outcomes influenced by stress. For example, pregnant women living in deprived or lower quality neighborhoods experience stressful life events, inadequate social support, and have high levels of perceived stress, depression, and anxiety [10-13].

The origins of stress and links between different measures of stress during pregnancy have not been explored among Puerto Ricans, but could be important for developing successful interventions to improve pregnancy outcomes.

The purpose of this study was to examine the relationships between different psychosocial stress measurements among pregnant women in the Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) cohort and to investigate the associations of those factors with PTB. Neighborhood perceptions, perceived stress, and negative life experiences were measured to indicate psychosocial stress during pregnancy. We created a conceptual model to test the pathways through which psychosocial stress may influence depression and assessed the role of social support in those relationships. Lastly, we examined associations between these measures and PTB, hypothesizing that increased psychosocial stress and depression would be associated with increased odds of PTB.

Material and methods

Study population

Pregnant women included in the present study were enrolled in the PROTECT cohort, an ongoing prospective birth cohort in Northern Puerto Rico that has been previously described in detail [14, 15]. Briefly, we included a subset of women who delivered between January 2011 and September 2017 prior to Hurricane Maria. Women were recruited in early pregnancy prior to 20 weeks gestation from affiliated prenatal clinics. Women were eligible for inclusion in PROTECT if they were between 18–40 years of age, lived in the Northern Karst region, did not use oral contraceptives 3 months prior to conception, did not have in vitro fertilization to become pregnant, and were free of known obstetric and medical complications (e.g., diabetes). Women who developed preeclampsia (3%) and gestational hypertension (2.3%) were not excluded from PROTECT. PROTECT was originally designed to examine environmental risk factors for PTB. Therefore, conditions that were a priori known to increase the risk of PTB, such as medical conditions and twinning, were excluded to focus on spontaneous PTB, rather than medically-related. Women in PROTECT are invited to complete 3 study visits, occurring between 16–20 weeks gestation, 20–24 weeks gestation, and 24–28 weeks gestation. These study visits were timed to coincide with periods of rapid fetal growth. The Institutional Review Board at all participating locations (University of Michigan, University of Puerto Rico, Northeastern University, and the University of Georgia) approved PROTECT and all women provided written informed consent prior to participation.

Life Experiences Survey (LES)

Women completed the Life Experiences Survey (LES) at the 2nd study visit, which provided information on whether or not they had experienced certain life events (N = 39) anytime in the past year [16]. If they did experience the event, they were asked if it had a negative or positive impact, ranging from extremely negative (a score of -3) to extremely positive (a score of +3). The number of events that each participant perceived as negative (coded -3, -2, -1) were summed to obtain a negative summary measure, indicative of the perceptions of negative events. The absolute value of the summary measure, indicative of perceptions of negative events, was taken to create a positive, continuous measure of negative life experiences (range 0–28). Thus, higher scores were indicative of increased negative life events. Events perceived as positive (a score of +1, +2, or +3) were coded as 0 and had no impact in the current analysis.

Neighborhood Perceptions (NP)

Also at the 2nd study visit, women were asked two questions about perceptions of their neighborhood. Women were first asked if in their opinion, their neighborhood was a very good (a score of 1), good (a score of 2), not very good (a score of 3), or not at all a very good (a score of 4) place to live. Women were then asked if they felt as if their neighborhood was very safe (a score of 1), somewhat safe (a score of 2), somewhat unsafe (a score of 3), or very unsafe (a score of 4). These questions were adapted from the National Children’s Study [17]. Responses to both questions were summed to create an overall continuous measure of neighborhood perceptions (NP; range 2–8); thus, higher scores were indicative of negative neighborhood perceptions.

Perceived Stress Scale (PSS)

The 10-item Perceived Stress Scale (PSS) was administered during the 3rd visit. The PSS is designed to measure the extent to which individuals feel that situations in his or her life are stressful [18]. Each item asked about how often specific feelings or thoughts, such as feeling nervous or irritated, occurred within the last month. Responses to each question were ranked on a 5 point Likert scale, with responses ranging from “never” (a score of 0) to “almost always” (a score of 4). Some questions that were positively stated, such as successfully dealing with life hassles, were reverse coded so that higher scores were always associated with increased perceived stress. Responses were summed to create a continuous measure of perceived stress (range 0–40), where higher scores were indicative of increased stress.

Center for Epidemiologic Studies-Depression (CES-D)

The 20-item Centers for Epidemiologic Studies-Depression (CES-D) scale was also administered at the 3rd visit. The CES-D is a screening tool measuring depression symptoms according to the Diagnostic Statistical Manual-IV [19] and has been shown to have good validity among Puerto Rican populations [20]. Questions are designed to measure how often in the past week individuals experience depressive symptoms. Responses are ranked on a Likert scale and range from “rarely” (a score of 0) to “majority” (a score of 3). Responses were summed to allow for continuous analysis of the depression scale (range 0–48). Higher scores were consistent with increased feelings of depression.

ENRICHD Social Support Instrument (ESSI)

The Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD) Social Support Instrument (ESSI) was administered during the 3rd visit and is a 7-item scale measuring functional social support [21]. The ESSI is acceptable for use in the general population [22] and has been previously used to assess social support during pregnancy [23]. Women were asked about amount and sources of social support, such as having someone available to listen or provide advice, responses ranged from “none of the time” (a score of 1) to “all the time” (a score of 5). Responses were summed to create a continuous measure of social support (range 8–33), where higher scores were indicative of higher social support.

All psychosocial stress questionnaires were administered in either Spanish or English, depending on participant preference, by trained study staff.

Gestational age

Gestational age was assessed using self-reported date of last menstrual period collected at the first study visit and first ultrasound estimates of gestational age per American College of Obstetricians and Gynecologists (ACOG) guidelines [15, 24]. We categorized gestational age into PTB (<37 weeks gestational age) and full term birth (≥37 weeks gestational age).

Statistical analysis

We examined the means and standard deviations (SD) of the CES-D, ESSI, PSS, LES, and NP across demographic characteristics. For each scale, the overall score was coded as missing if the response to any individual question was missing. Linear regression models were used to determine differences in the CES-D, ESSI, PSS, LES, and NP scales across demographic groups. To examine correlations between each measure, we calculated Pearson’s correlation coefficients.

Path analysis

Our conceptual path model was developed by reviewing the literature and previously published research. All continuous measures were assessed for normality. Path analysis were used to test our hypotheses using the package ‘lavaan’ [25] in R Version 3.5.0. Path analysis is an extension of regression analysis which estimates standardized regression coefficients reflecting the direct, indirect, and total effects among variables and evaluates mediation between variables. In path analyses, direct effects indicate the association between two variables where the effect is not mediated through other included variables. Indirect effects show the relationship between one variable and another, through one or more mediating variables. The total effect is the sum of the direct and indirect effects.

The best fitting version of the model was developed through an iterative process where we tested multiple pathways, starting with two variables and gradually adding others. One at a time, we removed those pathways that were non-significant and resulted in poor model fit. Model fit was examined using the chi-square to degree of freedom index (X2/df; values <3 are preferred), Root Mean Square Error of Approximation (RMSEA; values <0.05 are preferred), Standardized Root Mean Square Residual (SRMR; values <0.08 are preferred), Comparative Fit Index (CFI; values >0.9 are preferred), and Tucker-Lewis Index (TLI; values >0.9 are preferred) [26].

When calculating standard errors (SE), we used bias-corrected bootstrapping with 1,000 draws and calculated the corresponding 95% confidence intervals (CI). Missing data in path analyses were analyzed using the full information maximum likelihood (FIML) estimation, which is a recommended way of handling missing data in structural equation modeling [27]. FIML is built into the ‘lavaan’ package and estimates a likelihood function for all participations based on the non-missing CES-D, ESSI, PSS, LES, and NP measures and covariates for each participant so that all available participants and data are used.

Moderated mediation

To test the hypothesis that social support would moderate the associations between psychosocial stress measures and depression, we used the PROCESS macro for SAS 9.4 developed by Hayes. PROCESS is a tool for estimating interactions and the conditional indirect effects of moderated moderation models [28]. Continuous variables were mean centered for moderated-mediation analyses. We calculated regression coefficients for associations between each measure among those who experienced low (one SD below the mean ESSI value; simple slope a1), medium (mean ESSI value), and high (one SD above the mean ESSI value; simple slope a2) social support. PROCESS model 58 allows for multiple mediators and provides 5,000 bootstrapped sample estimates for estimation of indirect effects and 95% bias-corrected bootstrapped CIs. A complete case analysis (N = 841) was used for moderated mediation models.

Logistic regression

Logistic regression was used to calculate crude and adjusted odds ratios (OR) and 95% CIs for the associations between individual psychosocial stress measures and depression in tertiles and PTB. Tests for linear trend were conducted using the Cochrane-Armitage test. In logistic regression models, missing data for psychosocial stress measures, depression, and covariates was handled using Multiple Imputation via Chained Equations (mice), in which the independent variables with complete data were used to predict missing values [29]. PTB was not used as a predictor for missing values. We used the package ‘mice’ in R Version 3.5.0 to produce 10 values for all psychosocial stress measures, depression, and covariates with missing values [29]. Statistical significance was assessed at p-value <0.05.

Results

There were 1,548 women who were enrolled in the PROTECT cohort prior to September 2017. Of this group, 1,050 had gestational age information available at the time of our analysis. Three women were additionally excluded due to missing information on all covariates. Our final sample size for this analysis included 1,047 women, 107 (10.2%) of which delivered preterm (S1 File Fig A). The highest percentage of women in the PROTECT analytic sample were between ages 18–24 years (38.0%), had received a college degree (43.6%), were employed (62.4%), and were married (56.4%) (Table 1) [15]. Demographics of our analytic sample was similar to those of the overall PROTECT cohort [15] and characteristics of women with complete information on all stress scales is provided in S2 File Table A. Significant correlations were observed between all the CES-D, PSS, LES, NP, and ESSI measures (p-value <0.05 for each correlation) (Table 2). Scores on the PSS, CES-D, LES, and NP were all positively correlated with one another. The strongest correlation observed was between PSS and CES-D (r = 0.65). The ESSI was inversely correlated with each measure, as expected.

Table 1

Demographic characteristics of the PROTECT study population (N = 1,047).

Categorical	N (%)
Preterm Birth
Yes	107 (10.2)
No	940 (89.8)
Maternal Age, years
18–24	397 (38.0)
25–29	320 (30.6)
30–34	214 (20.5)
≥35	115 (11.0)
Maternal Education
<High school	77 (7.44)
High school or equivalent	132 (12.8)
Some college or technical school	375 (36.2)
≥College degree	451 (43.6)
Employment Status
Unemployed	388 (37.6)
Employed	644 (62.4)
Pre-pregnancy BMI
Underweight (<18.5 kg/m2)	64 (6.46)
Normal (18.5-<25 kg/m2)	492 (49.7)
Overweight (25-<30 kg/m2)	262 (26.5)
Obese (≥30 kg/m2)	172 (17.4)
Marital Status
Single	210 (20.3)
Married	585 (56.4)
Living together	242 (23.3)
Alcohol Use
Never	524 (51.0)
Before pregnancy	442 (43.0)
Currently drinking	62 (6.03)
Smoking
Never	873 (84.2)
Ever	132 (12.7)
Current	32 (3.09)
Insurance Status
Public	364 (35.7)
Private	637 (62.5)
Uninsured	19 (1.86)
Continuous	Mean (SD)
ENRICHD Social Support Instrument (ESSI)	27.6 (3.53)
Perceived Stress Scale (PSS)	13.7 (6.84)
Center for Epidemiologic Studies-Depression (CES-D)	11.6 (9.08)
Life Experience Survey (LES)	3.02 (4.03)
Neighborhood Perceptions (NP)	2.53 (0.84)

Abbreviations: SD, standard deviation; BMI, body mass index.

Note: totals may not sum to 1,047 due to missing values.

Table 2

Pearson correlation coefficients between psychosocial stress measures.

	CES-D	PSS	LES	ESSI	NP
Center for Epidemiologic Studies-Depression (CESD)		0.65	0.37	-0.26	0.14
Perceived Stress Scale (PSS)			0.34	-0.29	0.17
Life Experience Survey (LES)				-0.17	0.09
ENRICHD Social Support Instrument (ESSI)					-0.16
Neighborhood Perceptions (NP)

Note: all correlations are significant at p value<0.05

Distribution of missingness on the ESSI, PSS, CES-D, LES, and NP scales across demographic characteristics is provided in S2 File Table B. Mean scores on the PSS, LES, and CES-D scales were higher among women who were between ages 18–24, single, currently drinking alcohol, or ever smokers compared to reference groups (S1 File Fig B and Fig C and Fig D). Women with higher stress as measured by NP scale (indicative of increased stress levels) were more likely to be unemployed compared to employed, ever compared to never smokers, and have public compared to private insurance (S1 File Fig E). Women with lower scores on the ESSI (indicative of increased stress) were more likely to be unemployed, single or living with a partner, current or ever smokers, and have public insurance compared to reference groups (S1 File Fig F). Overall, most psychosocial stress variables were associated with lower SES indicators.

Marital status, education, and maternal age were a priori included as covariates in our path analyses and in logistic regression models based on their known associations with psychosocial stress [12]. CES-D was the primary outcome in our final model and the exposures that demonstrated associations that were greatest in magnitude included the PSS (β = 0.57, direct path) and the LES (β = 0.18, indirect path through PSS) (Fig 1 and Table 3). In other words, a one SD increase in perceived stress was directly associated with a 57% SD increase in feelings of depression and a one SD increase in negative life experiences was indirectly associated with a 18% SD increase in feelings of depression. Only the PSS and LES were directly associated with the CES-D.

Fig 1

Path diagram indicating the relationship between psychosocial stress measures and depression in PROTECT study population.

Maternal age, marital status, and education are included as covariates in model (N = 1,047). Note: All paths are significant at p<0.05; missing data handled using full information maximum likelihood. Model fit statistics: X2 = 0.71, p value = 0.40, CFI = 1.00, TLI, 1.02, RMSEA = 0.00, SRMR = 0.00. Abbreviations: X2/df, chi-square to degree of freedom index; RMSEA, Root Mean Square Error of Approximation; CFI, Comparative Fit Index; TLI, Tucker-Lewis Index; SRMR, Standardized Root Mean Square Residual.

Table 3

Standardized regression coefficients (standard errors) for the best fitting structural equation model of psychosocial stress measures and depression in pregnancy.

	Life Experience Survey (LES)
	Direct (SE)	Indirect (SE)	Total (SE)
Neighborhood Perceptions (NP)	0.08 (0.15)	-	0.08 (0.15)
	Perceived Stress Scale (PSS)
Neighborhood Perceptions (NP)	0.12 (0.25)	0.03 (0.08)	0.15 (0.27)
Life Experience Survey (LES)	0.32 (0.06)	-	0.32 (0.06)
	Center for Epidemiologic Studies-Depression (CES-D)
Neighborhood Perceptions (NP)	-	0.10 (0.08)	0.10 (0.08)
Life Experience Survey (LES)	0.15 (0.07)	0.18 (0.05)	0.34 (0.08)
Perceived Stress Scale (PSS)	0.57 (0.04)	-	0.57 (0.04)

Note: all paths are significant at p value<0.05; standard errors are estimated using 1,000 bootstrap estimates; missing data handled using full information maximum likelihood specification;—indicates no path; model adjusted for maternal age, marital status, and maternal education.

Abbreviations: SE, standard error.

LES affected the CES-D through both direct (β = 0.15) and indirect (β = 0.18) paths, and the indirect effect was greater in magnitude than the direct effect. The LES also had a positive direct effect on the PSS (β = 0.32).

NP affected the PSS directly (β = 0.12) and indirectly through LES (β = 0.03). NP also affected the CES-D indirectly (β = 0.10) through its effects on PSS and LES scores. Our final model has good fit, as indicated by the model fit statistics all being within the acceptable range. For example, the RMSEA value was 0.00 and the X2/df index was 0.71.

The ESSI was not directly or indirectly associated with the PSS, NP, LES, or CES-D and thus was not included in our final conceptual model. However, in moderated mediation analyses, we found that the relationship between the PSS and CES-D varied based on participants’ levels of social support. No moderation by the ESSI was observed for other relationships. To interpret the moderation finding between PSS and CES-D, we plotted estimated levels of CES-D among those with high, medium, and low ESSI scores (S1 File Fig G). Under the condition of low ESSI scores, the indirect effect of NP on CES-D through PSS was greater in magnitude (simple slope a1 = 0.85; 95% CI = 0.76, 0.94) than compared to women with high ESSI scores (simple slope a2 = 0.72; 95% CI = 0.64, 0.82). The full conceptual framework indicating the associations between different parameterizations of stress, confounders, and effect modifiers is shown in S1 File Fig H.

Associations between psychosocial stress, depression, and PTB were null (Table 4). For example, in adjusted analyses women with high compared to low scores on the PSS had no difference in odds of PTB (OR = 0.87; 95% CI = 0.46, 1.63). A 11% increase in odds of PTB was observed among women with high compared to low scores on the LES (95% CI = 0.64, 1.93). High compared to low scores on the CES-D was associated with a 2% decrease in odds of PTB (95% CI = 0.57, 1.69). Tests for linear trend were non-significant across all psychosocial stress measures.

Table 4

Crude and adjusted odds ratios of preterm birth (95% confidence intervals) in association with tertiles of psychosocial stress measures and depression in PROTECT (N = 1,047).

	Crude	Adjusted1
	OR (95% CI)	OR (95% CI)
ENRICHD Social Support Instrument (ESSI)
High	Ref	Ref
Medium	1.25 (0.72, 2.15)	1.03 (0.55, 1.95)
Low	1.14 (0.66, 1.97)	0.87 (0.46, 1.63)
p trend	0.61	0.63
Perceived Stress Scale (PSS)
Low	Ref	Ref
Medium	0.98 (0.57, 1.68)	0.96 (0.55, 1.67)
High	0.77 (0.45, 1.32)	0.71 (0.40, 1.23)
p trend	0.35	0.23
Life Experience Survey (LES)
Low	Ref	Ref
Medium	1.29 (0.76, 2.18)	1.36 (0.79, 2.32)
High	1.06 (0.62, 1.81)	1.11 (0.64, 1.93)
p trend	0.80	0.66
Center for Epidemiologic Studies-Depression (CES-D)
Low	Ref	Ref
Medium	1.24 (0.75, 2.04)	1.29 (0.77, 2.14)
High	1.06 (0.63, 1.78)	0.98 (0.57, 1.69)
p trend	0.82	0.96
Neighborhood Perceptions (NP)
Low	Ref	Ref
Medium	0.93 (0.58, 1.51)	0.95 (0.58, 1.55)
High	0.74 (0.35, 1.54)	0.70 (0.33, 1.49)
p trend	0.43	0.40

Abbreviations: OR, odds ratio; CI, confidence interval; Ref, reference.

1Models adjusted for maternal age, education, and marital status.

Note: Psychosocial stress measures were categorized into tertiles indicating high, medium, and low stress. The tertile cut points were as follows: PSS- Low: ≤10, Medium: 11–16, High: >16; CES-D- Low: ≤6, Medium: 7–12, High:>12, LES- Low: 0, Medium: 1–3, High: >3, ESSI- Low: <28, Medium: 28–29, High: >29, NP- Low: ≤2, Medium: 3, High: >3

Discussion

In this study, we examined the relationship between parameterizations of self-reported psychosocial stress and depression in pregnant women from Puerto Rico. We observed that neighborhood perceptions influenced depression through two separate pathways: 1) through increasing negative life experiences and 2) through increasing perceived stress. We also showed that in this population perceived stress had the strongest direct effect on depression. None of these measures were associated with PTB.

These findings support a growing body of literature suggesting that the qualities of one’s neighborhood may be a source of increased psychosocial stress and depression [10, 11, 30]. Neighborhood perceptions were positively associated with all other metrics of psychosocial stress, including negative life experiences, perceived stress, and ultimately depression. This is in line with previous work showing that women in neighborhoods with high material and social deprivation have increased perceived stress and depression [11]. It is also consistent with a study of African-American women in Michigan which showed that lower levels of perceived neighborhood safety and walkability were associated with increased feelings of perceived stress and depression [30]. Additionally, our findings are supported by a previous study showing that women in disadvantaged neighborhoods experience more stressful life events during pregnancy compared to women in advantaged neighborhoods [10].

The direct effect we observed between perceived stress and depression was the greatest in magnitude compared to all other associations in our final model. In addition to a strong direct effect, perceived stress partially mediated the relationships between other psychosocial stress measures (neighborhood perceptions, negative life experiences) and depression. These findings are consistent with another study which demonstrated that perceived stress mediates the relationships between different forms of psychosocial stress and depression [12].

It is hypothesized that psychosocial stress contributes to PTB through activation of the hypothalamic-pituitary-adrenal (HPA) axis, which increases cortisol production [5]. Psychosocial stress may also increase oxidative stress and inflammation, which are increased in mothers who go on to experience PTB [5, 31–33]. Additionally, psychosocial stress may lead to unhealthy behaviors, such as smoking or poor nutrition, which may increase the risk of PTB through these or other pathways [5].

We hypothesized that increased psychosocial stress would be associated with increased odds of PTB, as this has been observed in other studies and is biologically plausible [3, 5]. However, our null associations are consistent with a large body of literature suggesting no association between psychosocial stress or depression and PTB. A recent systematic review examining the association between depression and PTB found that only 25% of studies showed a statistically significant association [34]. Studies of other parameterizations of stress in association with PTB have also been largely null [35-38].

One reason for heterogeneity in these studies may be cross-sectional assessment of stress, as opposed to longitudinal measures from across the life course. In PROTECT, psychosocial stress was measured during pregnancy and focused on self-reported, acute psychosocial stress occurring immediately before (i.e., negative life experiences) and during pregnancy (i.e., neighborhood perceptions, perceived stress, social support). Previous research suggests that women’s reproductive health is modified based on early life experiences and cumulative allostatic load, the body’s chronic accumulation of stress [6, 39]. Additional research is needed to determine if indices of psychosocial stress from across the life course, such as measures of adverse childhood experiences, are more predictive of birth outcomes as compared to acute stressors included in this study.

Another potential explanation of the inconsistency across studies of stress, depression, and PTB is that these effects may only be observed when stress is sufficiently high. Our study population experienced lower levels of each psychosocial stress indicator and depression relative to other populations. For example, in PROTECT, the mean CES-D score was 11.7 and the mean PSS score was 14.9. Among women enrolled in the Boston Puerto Rican Health Study, the mean CES-D score was 24.4, which is markedly increased compared to those in PROTECT [20]. Similar high scores on the CES-D (mean score of 21.8) were observed among a convenience sample of women recruited from primary care clinics in San Juan, PR [40]. Among women enrolled in the Pregnancy Study Online, an online-based preconception cohort study of women in the U.S. and Canada, the mean PSS score was 15.8, which is also slightly higher than the mean PSS score in PROTECT [41]. The PROTECT cohort is a unique study population and differences in stress levels may also be due to differences across populations or differences in how they respond to questionnaires. Importantly, despite PROTECT women reporting lower levels of psychosocial stress, the relationships observed in our path analysis are consistent with what has been observed in other studies.

Our results should be interpreted in light of some limitations. First, this was an exploratory analysis conducted within an existing study that was designed to address additional research questions and some of our psychosocial stress measures were administered at the same study visit. Our path analysis may be considered cross-sectional and temporality of reporting may be a concern in our study. For example, it is possible that women with depression perceive certain life experiences as more negative [42]. Nonetheless, all associations we identified in our path analysis have been observed in other studies, giving us greater confidence in our results. Second, some women in our study were missing information on psychosocial stress measures, would could have biased our results. However, we used the FIML approach and multiple imputation to address missingness, which should reduce any bias occurring as a result of missing data. Third, women with preexisting medical complications were excluded from our study population, which may have resulted in our study population being inherently healthier than the general population. This may have hindered our ability to detect associations between psychosocial stress and PTB, as previous literature has shown that pregnancy complications are associated with elevated stress levels and women with pregnancy complications are at an elevated risk of PTB [43, 44]. In addition, mediation analysis assumes that there are no unmeasured confounders, which may not be the case here. Lastly, Spanish translations of the LES, NP, PSS, CES-D, and ESSI have not been validated in Puerto Rican populations.

Despite these limitations, our study has many strengths. The PROTECT cohort is a prospective study and psychosocial stress measures were collected prior delivery. Importantly, we examined several different types of psychosocial stress, each of which are reliable scales used in many other studies. Finally, in the creation of our final conceptual model, we explored several different pathways through which psychosocial stress measures have been associated with one another in the literature, giving us greater confidence in our results.

A unique aspect of this study is that we utilized data on psychosocial stress that was collected prior to Hurricane Maria, but recruitment for the cohort is ongoing. Previous research shows that natural disasters are a source of increased psychosocial stress [45]. It will be important to compare levels of psychosocial stress and the relationships between measures reported here with those collected on PROTECT participants after the Hurricane. Additionally, it will be interesting to examine how the relationship between psychosocial stress and PTB changes before vs. after this event in our study population.

Conclusions

Our study highlights the complexity of the relationships between different indices of psychosocial stress and depression among pregnant women in Puerto Rico, although none of these measures were associated with PTB. To the best of our knowledge, this is the first study examining psychosocial stress as a risk factor for PTB among Puerto Ricans residing on the island. Stress pathways leading to PTB remain largely misunderstood and our findings may help inform future models that consider diverse sources of psychosocial stress. Future research investigating stress parameterizations in relation to adverse maternal and child health outcomes should explicitly consider the mediating and moderating pathways we identified. Additionally, there may be other pathways leading to elevated stress levels and to adverse birth outcomes, such as anxiety, that were not explored here and warrant exploration. Furthermore, additional work on environmental and behavioral factors is necessary to explain the higher rates of PTB observed in Puerto Rican women.

Supporting figures for Relationships between psychosocial factors during pregnancy and preterm birth in Puerto Rico.

Fig A. Flow diagram indicating participant selection into final analytic sample.

Fig B. Distribution of Perceived Stress Scale (PSS) across demographic characteristics.

Fig C. Distribution of Life Experience Survey (LES) across demographic characteristics.

Fig D. Distribution of Center for Epidemiologic Studies-Depression (CES-D) across demographic characteristics.

Fig E. Distribution of Neighborhood Perceptions (NP) across demographic characteristics.

Fig F. Distribution of ENRICHD Social Support Instrument (ESSI) across demographic characteristics.

Fig G. Effect of perceived stress on depression moderated by social support.

Fig H. Full model including of all psychosocial stress measures, depression, confounders, and effect modifiers.

(PDF)

Click here for additional data file.

Supporting tables for Relationships between psychosocial factors during pregnancy and preterm birth in Puerto Rico.

Table A. Distribution of demographic characteristics among women with complete information on all psychosocial stress and depression measures (N = 841).

Table B. Distribution of missingness between demographic characteristics and psychosocial stress and depression measures.

(DOCX)

Click here for additional data file.

13 Nov 2019

PONE-D-19-21339

Psychosocial Factors During Pregnancy and Preterm Birth in Puerto Rico

PLOS ONE

Dear Dr. Ferguson,

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Additional Editor Comments (if provided):

Thank you for submitting this interesting paper. The reviewers have provided detailed comments which I hope will help to improve the paper. I have two comments/ suggestions -

1. Please can the authors show the post-hoc power calculation so that the readers can assess whether the lack of a statistically significant association was due to a small sample size?

2. Please add a Figure of the full conceptual framework showing the pathways of associations between the different parameters as well as confounders and effect modifiers.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: It is well established that, different psychosocial stressors have role on preterm delivery. But, cultural variation might be a factor to modify the effect of these stressors. This article, that’s why, wanted to explore the relationships of these stressors with the preterm birth. But, the title of this article is somehow misleading. Because, this title may lead to think that, this article was searching for the names of the stressor only, rather than the relationships.

This study used Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) cohort, which was an ongoing prospective birth cohort in Northern Puerto Rico, to collect samples. Varieties of scales including Life Experiences Survey (LES), Neighborhood Perceptions (NP), Perceived Stress Scale (PSS), Center for Epidemiologic Studies-Depression (CES-D) and ENRICHD Social Support Instrument (ESSI) were used to collect data from the participants. This strengthens the study to found out the relationships with the variables.

The pregnant women from 18-40 years of age lived in the Northern Karst region, with no history of oral contraceptives use 3 months prior to conception, in vitro fertilization, and any known obstetric and medical complications. Data were collected three times during three visits, between 16-20 weeks gestation, 20-24 weeks gestation, and 24-28 weeks gestation. It seems unclear that, on which basis these three gestational ages were chosen.

On 2nd visit they used the LEA and NP, while rests were used in the 3rd visit. They tried to develop a conceptual model at first, to identify the stressors causing depression and assess the role of social support. Then they tried to find out the association between these stressors with PTB. For this, they used the path analysis, where model fit was examined using various statistical measures, including the chi-square to degree of freedom index (X2/df; values <3 are preferred), Root Mean Square Error of Approximation (RMSEA; values <0.05 are preferred), Standardized Root Mean Square Residual (SRMR; values <0.08 are preferred), Comparative Fit Index (CFI; values >0.9 are preferred), and Tucker-Lewis Index (TLI; values >0.9 are preferred). Bias-corrected bootstrapping along with corresponding 95% confidence intervals (CI) were used to define standard errors. The methodology section was written in details, which made the study process more acceptable.

Regarding result, if all of the 1047 women took part in all of the scales then results might be more accurate. Positive correlations were found among the scores on the PSS, CES-D, LES, and NP, where PSS and CES-D had the strongest relation. The ESSI was inversely correlated with each measure, as expected. Findings suggested that, depression had direct association with perceived stress as well as, indirect association with negative life experiences.

Interestingly, this study found no associations between psychosocial stress and PTB. This is actually against to many of the previous evidences. The authors suggested that, this contrast might be due to the low level of stress and having a follow up rather than a cross sectional sample. But, this need to be clarified further or may conduct a separate study addressing this issue.

The authors mentioned some strengths and limitations of this study with adequate explanations. Undoubtedly, this study is well structured, but there are some scopes of improvement. Specially, the writings should be done in a better convenient way. The whole manuscript is difficult to follow because of so many statistical contents. They are necessary, but effort should be given to make it more palatable.

The whole study focused only over the depression as the ultimate pathway to do problem. But, there might be other pathways, like high level of anxiety, those needs to be explored.

Reviewer #2: General comment:

• The way psychosocial stress and depression are discussed is inconsistent throughout the manuscript. In some areas, depression is discussed as a result of stress (one of the research aims of the paper, lines 78-79, 93-94) and in other areas it is considered a measure of stress (lines 71-72, 91-92, 307-308). Similarly, though minor, social support is also occasionally lumped as a ‘psychosocial stress measure’ (e.g., lines 307-308). While this was probably done for ease of communication, it makes it somewhat hard to distinguish whether the references to ‘psychosocial stress’ in the discussion include social support (and also depression).

Methods:

• Line 107 – Were women with preeclampsia/gestational hypertension also excluded? Some studies suggest that stress is associated with preeclampsia/gestational diabetes and development of other medical/pregnancy complications, so this may have hindered your ability to detect an association between stress and PTB and could be included as a limitation. Just speculating, but it may also partially explain why your distribution of CES-D scores was lower than what has been reported in other Puerto Rican samples – your sample is inherently healthier than the general population.

• Line 119-120: The first part of this sentence says that the number of events was summed, but then I’m not sure why you would have to take the absolute value of this – it should already be positive, unless you summed the ‘negativity score.’ Clarification of this sentence would be helpful. You could also include the theoretical range to illustrate how the sum was calculated (0-39 for number of events vs. 0 to 117 for number + severity)

• Line 165-166: Please indicate whether the Spanish translations of survey instruments have been validated.

Results:

• Lines 225-226: It would be helpful to include a study inclusion flowchart.

• Was your sample different than the general PROTECT cohort? You provide descriptive statistics for those with missing data in table S1, but this is only for those who completed ≥1 measure – what about those who didn’t complete any of the five measures?

• Please report the prevalence of PTB in the sample in Table 1. You could also compare this to a recent estimate for Puerto Rico – may help to indicate whether the inclusion criteria resulted in an overall healthier sample than the general population

• Table 4: It would be helpful to include a footnote indicating how the categories were defined for all of the continuous stress measures (tertiles per line 215). It would also be helpful to provide the tertile cutoffs to facilitate comparison to other studies.

Discussion:

• Another limitation is potential selection bias introduced by limiting participants to those without pregnancy/medical complications – excluding those who potentially have more psychosocial stress and are at increased risk of preterm birth.

• May also want to mention strict confounding assumptions for mediation analysis as a limitation

**********

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Reviewer #1: Yes: Panchanan Acharjee

Reviewer #2: No

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20 Dec 2019

Comments from the editor

1. Please can the authors show the post-hoc power calculation so that the readers can assess whether the lack of a statistically significant association was due to a small sample size?

Response: Thank you for considering our manuscript for publication. We have decided to not conduct a post hoc power calculation as there is a consensus in the statistical community that it is incorrect to conduct such power calculations after studies have been conducted. A detailed review of scenarios when it is inappropriate to conduct post hoc power calculations is available at the citation below.

Hoenig, J. M. and D. M. Heisey (2001). "The Abuse of Power." The American Statistician 55(1): 19-24.

Furthermore this was an exploratory analysis conducted within a study that was designed to address additional research questions We have included the phrase “First, this was an exploratory analysis conducted within an existing study that was designed to address additional research questions” in the discussion section on lines 398-400.

2. Please add a Figure of the full conceptual framework showing the pathways of associations between the different parameters as well as confounders and effect modifiers.

Response: We have added a figure (Figure S8) to illustrate the full conceptual framework. This figure is referenced in the results section on lines 316-318 and includes all stress parameters, confounders, and effect modifiers.

Reviewer's responses to questions

1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Comments from reviewers

Reviewer 1

General comment: It is well established that, different psychosocial stressors have role on preterm delivery. But, cultural variation might be a factor to modify the effect of these stressors. This article, that’s why, wanted to explore the relationships of these stressors with the preterm birth. But, the title of this article is somehow misleading. Because, this title may lead to think that, this article was searching for the names of the stressor only, rather than the relationships.

Response: Thank you for your detailed review of our manuscript. We agree that cultural variation is important and that it may be modifying the effect of stress on preterm delivery. We have changed the title of this manuscript to be “Relationships Between Psychosocial Factors During Pregnancy and Preterm Birth in Puerto Rico” in an effort to not mislead readers.

Specific comments:

1. This study used Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) cohort, which was an ongoing prospective birth cohort in Northern Puerto Rico, to collect samples. Varieties of scales including Life Experiences Survey (LES), Neighborhood Perceptions (NP), Perceived Stress Scale (PSS), Center for Epidemiologic Studies-Depression (CES-D) and ENRICHD Social Support Instrument (ESSI) were used to collect data from the participants. This strengthens the study to found out the relationships with the variables.

Response: We appreciate your thoughtful comments on our manuscript. We agree that including multiple stressors is an important strength of this study.

2. The pregnant women from 18-40 years of age lived in the Northern Karst region, with no history of oral contraceptives use 3 months prior to conception, in vitro fertilization, and any known obstetric and medical complications. Data were collected three times during three visits, between 16-20 weeks gestation, 20-24 weeks gestation, and 24-28 weeks gestation. It seems unclear that, on which basis these three gestational ages were chosen

Response: The timing of these study visits were chosen to coincide with periods of rapid fetal growth. We have included the sentence “These study visits were timed to coincide with periods of rapid fetal growth.” in the methods section on lines 119-120.

3. On 2nd visit they used the LES and NP, while rests were used in the 3rd visit. They tried to develop a conceptual model at first, to identify the stressors causing depression and assess the role of social support. Then they tried to find out the association between these stressors with PTB. For this, they used the path analysis, where model fit was examined using various statistical measures, including the chi-square to degree of freedom index (X2/df; values <3 are preferred), Root Mean Square Error of Approximation (RMSEA; values <0.05 are preferred), Standardized Root Mean Square Residual (SRMR; values <0.08 are preferred), Comparative Fit Index (CFI; values >0.9 are preferred), and Tucker-Lewis Index (TLI; values >0.9 are preferred). Bias-corrected bootstrapping along with corresponding 95% confidence intervals (CI) were used to define standard errors. The methodology section was written in details, which made the study process more acceptable.

Response: We are glad that you find our statistical methods to be sufficiently detailed.

4. Regarding result, if all of the 1047 women took part in all of the scales then results might be more accurate. Positive correlations were found among the scores on the PSS, CES-D, LES, and NP, where PSS and CES-D had the strongest relation. The ESSI was inversely correlated with each measure, as expected. Findings suggested that, depression had direct association with perceived stress as well as, indirect association with negative life experiences.

Response: We agree that a limitation of our study was that information on psychosocial stress was missing on some participants. However, given that we used the Full Information Maximum Likelihood approach in the path analysis and used multiple imputation in all other analyses to handle the missingness, we do not believe that our results are substantially biased. Nonetheless, we have noted the missing data on some women as a limitation on lines 405-408 with the below text.

“Second, some women in our study were missing information on psychosocial stress measures, would could have biased our results. However, we used the FIML approach and multiple imputation to address missingness, which should reduce any bias occurring as a result of missing data.”

5. Interestingly, this study found no associations between psychosocial stress and PTB. This is actually against to many of the previous evidences. The authors suggested that, this contrast might be due to the low level of stress and having a follow up rather than a cross sectional sample. But, this need to be clarified further or may conduct a separate study addressing this issue.

Response: We agree that our findings that psychosocial stress was not associated with PTB was in contrast to previous studies. We have clarified that future work is needed to determine if assessment of stress from across the life course, as opposed to a cross-sectional measure of stress, is more strongly associated with PTB. The sentences “Additional research is needed to determine if indices of psychosocial stress from across the life course, such as measures of adverse childhood experiences, are more predictive of birth outcomes as compared to acute stressors included in this study.” are included in the discussion section on lines 379-382.

Additionally, this is a unique study population and it is possible that differences in stress levels are due to differences across populations or differences in how they respond to questionnaires. For example, PROTECT participants have good ongoing relationships with study researchers, so it is possible that the stress of the interviews is lessened. We have noted this with the sentence “The PROTECT cohort is a unique study population and differences in stress levels may also be due to differences across populations or differences in how they respond to questionnaires.” in the discussion section on lines 393-395.

6. The authors mentioned some strengths and limitations of this study with adequate explanations. Undoubtedly, this study is well structured, but there are some scopes of improvement. Specially, the writings should be done in a better convenient way. The whole manuscript is difficult to follow because of so many statistical contents. They are necessary, but effort should be given to make it more palatable.

Response: We have edited our methods and results sections in an effort to make the statistical content easier to follow and understand. We have also added headings within our statistical analyses section.

7. The whole study focused only over the depression as the ultimate pathway to do problem. But, there might be other pathways, like high level of anxiety, those needs to be explored.

Response: We agree that anxiety may be an important pathway that was not explored in our study. However, a measure of anxiety was not available in this study population. We have included the below sentence in the conclusions section on lines 438- 440 to indicate that future research should focus on characterizing additional pathways, such as anxiety.

“Additionally, there may be other pathways leading to elevated stress levels and to adverse birth outcomes, such as anxiety, that were not explored here and warrant exploration.”

Reviewer #2

General comment: The way psychosocial stress and depression are discussed is inconsistent throughout the manuscript. In some areas, depression is discussed as a result of stress (one of the research aims of the paper, lines 78-79, 93-94) and in other areas it is considered a measure of stress (lines 71-72, 91-92, 307-308). Similarly, though minor, social support is also occasionally lumped as a ‘psychosocial stress measure’ (e.g., lines 307-308). While this was probably done for ease of communication, it makes it somewhat hard to distinguish whether the references to ‘psychosocial stress’ in the discussion include social support (and also depression).

Response: Thank you for taking the time to review our manuscript. We agree that distinguishing depression as a downstream consequence of stress is key to our conceptual model, and should be referred to as such throughout the manuscript. We have updated our manuscript throughout so that we are consistently differentiating depression from measures of stress. Likewise, we have updated our manuscript to reflect that other stress measures are consistently referred to as such.

Specific Comments:

1. Line 107 – Were women with preeclampsia/gestational hypertension also excluded? Some studies suggest that stress is associated with preeclampsia/gestational diabetes and development of other medical/pregnancy complications, so this may have hindered your ability to detect an association between stress and PTB and could be included as a limitation. Just speculating, but it may also partially explain why your distribution of CES-D scores was lower than what has been reported in other Puerto Rican samples – your sample is inherently healthier than the general population.

Response: Women with preeclampsia and gestational hypertension were not excluded from our study population, although the percent of women with preeclampsia (3%) and gestational hypertension (2.3%) were low. We have added this information to the methods section lines 116-118 with the sentence “Women who developed preeclampsia (3%) and gestational hypertension (2.3%) were not excluded from PROTECT.”

Additionally, we agree. Because we excluded pregnant women with a variety of complications in pregnancy, we may have unintentionally selected a low-stress cohort. The PROTECT cohort was originally designed to examine environmental risk factors for preterm birth and as such, conditions that were a priori known to increase the risk of preterm birth, such as diabetes and multiple births, were excluded to focus on spontaneous preterm birth, rather than medically-related. We have noted that this was the overall goal of the PROTECT cohort on lines 118-118 with the phrase: “PROTECT was originally designed to examine environmental risk factors for PTB. Therefore, conditions that were a priori known to increase the risk of PTB, such as medical conditions and twinning, were excluded to focus on spontaneous PTB, rather than medically-related.” We have also noted as a limitation that we may have unintentionally selected a low-stress cohort on lines 408-410: “Third, women with preexisting medical complications were excluded from our study population, which may have resulted in our study population being inherently healthier than the general population.”

2. Line 119-120: The first part of this sentence says that the number of events was summed, but then I’m not sure why you would have to take the absolute value of this – it should already be positive, unless you summed the ‘negativity score.’ Clarification of this sentence would be helpful. You could also include the theoretical range to illustrate how the sum was calculated (0-39 for number of events vs. 0 to 117 for number + severity).

Response: We apologize for the confusion regarding how the Life Experience Survey summary score was calculated. We summed the negative score (all responses coded as -3, -2, or -1) and then took the absolute value of that negative number. We have elaborated on this in lines 130-133 for clarification with the below sentences.

“The number of events that each participant perceived as negative (coded -3, -2, -1) were summed to obtain a negative summary measure, indicative of the perceptions of negative events. The absolute value of the summary measure, indicative of perceptions of negative events, was taken to create a positive, continuous measure of negative life experiences (range 0-28).”

3. Line 165-166: Please indicate whether the Spanish translations of survey instruments have been validated.

Response: The Spanish translations have not been validated, although the Spanish version of the CES-D and PSS have been used in other studies. References which have used Spanish versions of these survey instruments are provided below. We have additionally noted in the limitations section on lines 414-415 that these survey instruments were have not been validated in Spanish: “Lastly, Spanish translations of the LES, NP, PSS, CES-D, and ESSI have not been validated in Puerto Rican populations.”

Glass, T, Leon, CFMD, Bassuk, H and Berkman, LF. 2006. Social engagement and depressive symptoms in late life. Journal of Aging and Health, 18(4): 604–628.

Falcon LM, Todorova I, Tucker K. Social support, life events, and psychological distress among the Puerto Rican

population in the Boston area of the United States. Aging & mental health. 2009;13(6):863-73.

4. Lines 225-226: It would be helpful to include a study inclusion flowchart.

Response: We have added a study inclusion flow chart as Figure S1. This flow chart is referenced on line 246.

5. Was your sample different than the general PROTECT cohort? You provide descriptive statistics for those with missing data in table S1, but this is only for those who completed ≥1 measure – what about those who didn’t complete any of the five measures?

Response: Our study population did not differ from the general PROTECT cohort and we have noted this in the results section on lines 250-252. We have added an additional table (Table S1) that shows the distribution of demographics among participants who have complete information on all five measures (N=841). There were 6 participants who were missing information on all psychosocial stress measures. Given the lower percentage of participants missing all stress measures, we did not provide demographic information for this group.

6. Please report the prevalence of PTB in the sample in Table 1. You could also compare this to a recent estimate for Puerto Rico – may help to indicate whether the inclusion criteria resulted in an overall healthier sample than the general population

Response: We have added the prevalence of PTB to Table 1 (10.2%). We have also noted the 2018 PTB rate for Puerto Rico (11.9%) in the introduction on lines 72-73: “The PTB rate in Puerto Rico declined to 11.9% in 2018, which remains high relative to the mainland U.S.”

7. Table 4: It would be helpful to include a footnote indicating how the categories were defined for all of the continuous stress measures (tertiles per line 215). It would also be helpful to provide the tertile cutoffs to facilitate comparison to other studies.

Response: We have added a footnote to Table 4 indicating that continuous stress measures were categorized into tertiles. The Table 4 footnote also includes the tertile cut points for continuous scales.

8. Another limitation is potential selection bias introduced by limiting participants to those without pregnancy/medical complications – excluding those who potentially have more psychosocial stress and are at increased risk of preterm birth.

Response: We have acknowledged this as a limitation in the discussion section in lines 408-413 with the sentences: “Third, women with preexisting medical complications were excluded from our study population, which may have resulted in our study population being inherently healthier than the general population. This may have hindered our ability to detect associations between psychosocial stress and PTB, as previous literature has shown that pregnancy complications are associated with elevated stress levels and women with pregnancy complications are at an elevated risk of PTB.”

9. May also want to mention strict confounding assumptions for mediation analysis as a limitation

Response: We have acknowledged the confounding assumptions of mediation analyses as an additional limitation in lines 413-414: “In addition, mediation analysis assumes that there are no unmeasured confounders, which may not be the case here.”

Submitted filename: stress and PTB response to reviewer comments 12192019.docx

Click here for additional data file.

6 Jan 2020

Relationships Between Psychosocial Factors During Pregnancy and Preterm Birth in Puerto Rico

PONE-D-19-21339R1

Dear Dr. Ferguson,

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Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

9 Jan 2020

PONE-D-19-21339R1

Relationships Between Psychosocial Factors During Pregnancy and Preterm Birth in Puerto Rico

Dear Dr. Ferguson:

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