The bidirectional association between premenstrual disorders and perinatal depression: A nationwide register-based study from Sweden

Qian Yang; Emma Bränn; Elizabeth R Bertone- Johnson; Arvid Sjölander; Fang Fang; Anna Sara Oberg; Unnur A Valdimarsdóttir; Donghao Lu

doi:10.1371/journal.pmed.1004363

. 2024 Mar 28;21(3):e1004363. doi: 10.1371/journal.pmed.1004363

The bidirectional association between premenstrual disorders and perinatal depression: A nationwide register-based study from Sweden

Qian Yang ^1,^*, Emma Bränn ¹, Elizabeth R Bertone- Johnson ^2,³, Arvid Sjölander ⁴, Fang Fang ¹, Anna Sara Oberg ⁴, Unnur A Valdimarsdóttir ^1,^5,⁶, Donghao Lu ^1,^*

PMCID: PMC10978009 PMID: 38547436

Abstract

Background

Premenstrual disorders (PMDs) and perinatal depression (PND) share symptomology and the timing of symptoms of both conditions coincide with natural hormonal fluctuations, which may indicate a shared etiology. Yet, there is a notable absence of prospective data on the potential bidirectional association between these conditions, which is crucial for guiding clinical management. Using the Swedish nationwide registers with prospectively collected data, we aimed to investigate the bidirectional association between PMDs and PND.

Methods and findings

With 1,803,309 singleton pregnancies of 1,041,419 women recorded in the Swedish Medical Birth Register during 2001 to 2018, we conducted a nested case-control study to examine the risk of PND following PMDs, which is equivalent to a cohort study, and transitioned that design into a matched cohort study with onward follow-up to simulate a prospective study design and examine the risk of PMDs after PND (within the same study population). Incident PND and PMDs were identified through clinical diagnoses or prescribed medications. We randomly selected 10 pregnant women without PND, individually matched to each PND case on maternal age and calendar year using incidence density sampling (N: 84,949: 849,482). We (1) calculated odds ratio (OR) and 95% confidence intervals (CIs) of PMDs using conditional logistic regression in the nested case-control study. Demographic factors (country of birth, educational level, region of residency, and cohabitation status) were adjusted for. We (2) calculated the hazard ratio (HR) and 95% CIs of PMDs subsequent to PND using stratified Cox regression in the matched cohort study. Smoking, BMI, parity, and history of psychiatric disorders were further controlled for, in addition to demographic factors. Pregnancies from full sisters of PND cases were identified for sibling comparison, which contrasts the risk within each set of full sisters discordant on PND. In the nested case-control study, we identified 2,488 PMDs (2.9%) before pregnancy among women with PND and 5,199 (0.6%) among controls. PMDs were associated with a higher risk of subsequent PND (OR 4.76, 95% CI [4.52,5.01]; p < 0.001). In the matched cohort with a mean follow-up of 7.40 years, we identified 4,227 newly diagnosed PMDs among women with PND (incidence rate (IR) 7.6/1,000 person-years) and 21,326 among controls (IR 3.8). Compared to their matched controls, women with PND were at higher risk of subsequent PMDs (HR 1.81, 95% CI [1.74,1.88]; p < 0.001). The bidirectional association was noted for both prenatal and postnatal depression and was stronger among women without history of psychiatric disorders (p for interaction < 0.001). Sibling comparison showed somewhat attenuated, yet statistically significant, bidirectional associations. The main limitation of this study was that our findings, based on clinical diagnoses recorded in registers, may not generalize well to women with mild PMDs or PND.

Conclusions

In this study, we observed a bidirectional association between PMDs and PND. These findings suggest that a history of PMDs can inform PND susceptibility and vice versa and lend support to the shared etiology between both disorders.

Qian Yang and co-workers use data from Swedish national registers to simulate a prospective study which investigates the association of premenstrual disorders and post-natal depression in 1.8 million singleton pregnancies.

Author summary

Why was this study done?

Perinatal depression (PND) and premenstrual disorders (PMDs) share symptomology (e.g., feeling depressed), and the timing of symptom onset of both conditions coincides with natural hormonal fluctuations.
Prospective data are lacking to study the potential bidirectional association between these conditions, which can guide clinical management.

What did the researchers do and find?

We conducted a nested case-control study and transitioned that design into a matched cohort study with onward follow-up to simulate a prospective study design.
Among approximately 1.8 million singleton pregnancies in Sweden during 2001 to 2018, we identified 84,949 women with PND and 849,482 unaffected women, individually matched on age and calendar year. Pregnancies from full sisters of women with PND were also identified for sibling comparison.
Among women with PND, 2.9% had PMDs before pregnancy, in contrast to 0.6% among matched unaffected women. PMDs were associated with a nearly 5 times higher risk of subsequent PND. In the matched cohort with a mean follow-up of 6.90 years, women with PND had almost 2 times higher risk of subsequent PMDs, compared to matched unaffected women.
The bidirectional association between PMDs and PND was noted for both prenatal and postnatal depression, regardless of history of psychiatric disorders, and also in sibling comparison.

What do these findings mean?

These findings suggest that a history of PMDs can inform PND susceptibility and vice versa.
The main limitation of this study was that our findings, based on clinical diagnoses or prescribed medications, may not generalize well to women with mild PMDs or PND.

Introduction

Premenopausal women experience natural hormonal fluctuations associated with various life events, such as puberty, menstrual cycle, pregnancy, and menopause. Some women are more likely to develop or manifest mood symptoms during these events. For instance, perinatal depression (PND) is characterized by depressive symptoms occurring during pregnancy and up to 12 months after delivery and affects 11% of mothers globally [1]. PND has been positively associated with maternal suicidal behavior and has a negative influence on mother–infant bonding [2]. Similarly, premenstrual disorders (PMDs) are characterized by somatic and/or psychological symptoms that recur in luteal phase. PMDs cause significant functional impairment [3–5]. PMDs affect 20% to 30% of women of reproductive age [4], and about 5% to 8% of women suffer from severe symptomology [3]. PMDs are associated with increased risks of suicidal behavior and accidents [6].

PND and PMDs share symptomology (e.g., feeling depressed) and the timing of symptom onset of both conditions coincides with natural hormonal fluctuations [7,8]. Therefore, it has been postulated that these disorders may have common etiology and shared risk factors [9]. This hypothesis is supported by 2 recent systematic reviews showing that women with PND were more likely to have a history of PMDs [10,11]. However, existing studies relied on retrospectively collected on data premenstrual symptoms during or after pregnancy, which might be prone to recall bias and thereby biased results [12,13]. Moreover, the community- or clinic-based sampling in previous studies may have introduced significant selection bias [14]. Premenstrual symptoms can worsen after pregnancy due to an escalated abnormal response to hormonal changes in relation to pregnancy [15]. It is thus plausible that women with PND are at risk for subsequent PMDs. However, few studies with a relatively small sample size have examined this hypothesis by comparing proportions without adjustment for confounders and generated inconsistent results [16–18].

Taken together, without prospective evidence, it remains unclear whether women with PMDs have an increased risk of developing PND when becoming pregnant or after giving birth and vice versa. Using the Swedish nationwide registers with prospectively collected data, we aimed to investigate the bidirectional association between PMDs and PND. To study the bidirectional association in the same population effectively, we conducted a nested case-control study, a design inherently equivalent to a cohort study [19]. To examine the risk of PND following PMDs in a manner that simulates a prospective approach, we then transitioned this design into a matched cohort study to assess the risk of PMDs after PND. We further employed sibling comparisons to account for shared genetic and familial environmental risk factors for both disorders.

Methods

Data sources

Based on the Medical Birth Register (MBR), we identified 1,803,309 singleton pregnancies from 1,041,419 women during 2001 to 2018. The MBR covers virtually all births in Sweden since 1973, with rich information prospectively collected from prenatal, delivery, and neonatal care [20,21]. Multiple births (n = 51,824), pregnancies after PND diagnosis (n = 34,790), pregnancies from women who emigrated before 2001 (n = 952), or pregnancies before age 15 or after age 52 (n = 383) were excluded. The Patient Register, Prescribed Drug Register, Migration Register, Causes of Death Register, and Multi-Generation Register (MGR) were cross-linked using the unique personal identification number. The Patient Register collects information on all inpatient admissions for psychiatric care since 1973 and for somatic diseases since 1987 and >80% outpatient visits since 2001 [22]. The Prescribed Drug Register contains information on medications redeemed from all pharmacies in Sweden since July 2005 [23]. MGR contains information on familial links for individuals born from 1932 onward [24].

Ascertainment of PND

In line with previous studies [25], we identified PND from the date obtained by subtracting gestational age from the delivery date till 1 year postpartum, using the Swedish version of International Statistical Classification of Diseases and Related Health Problems (ICD)-10 codes (F32, F33, and F53.0) recorded in the MBR and Patient Register. According to the Swedish National Board of Health and Welfare, F32 and F33 are ICD-10 codes used to identify depression in Swedish healthcare registers according to the Swedish National Board of Health and Welfare [26] and have been reported to have high validity in the Swedish population (κ of 0·32; 88% full agreement with gold standard) [27]. F53.0 identifies perinatal depression not captured elsewhere [26]. Gestational age was, whenever possible, estimated according to ultrasound, which has been offered to all pregnant women in Sweden since 1990 and is performed for 95% of all pregnancies [28]. Nearly half of mental health problems are managed in primary care in Sweden [29]. Therefore, any prescription of antidepressants (ATC code N06A) was also considered as a proxy for PND. Antidepressants are commonly prescribed for PMDs as first-line treatment [30]. Prescriptions of antidepressants with an indication for PMDs, as described elsewhere [6], were not considered. The date of PND diagnosis was defined as the date of receiving a clinical diagnosis or filling a prescription of antidepressants, whichever came first. Since the MBR does not record the date of diagnosis and/or drug use, the median date of pregnancy was assigned as diagnosis date for those identified through MBR. Perinatal depression was then subcategorized into prenatal and postnatal depression using delivery date as cutoff point.

Ascertainment of PMDs

Clinical diagnoses of PMDs were retrieved from the Patient Register (ICD-10 code N943). PMDs include premenstrual syndrome (PMS) and premenstrual dysphoric disorder (PMDD). In practice, PMS is often diagnosed based on criteria similar to the American College of Obstetricians and Gynecologists (ACOG) criteria [31], and PMDD is diagnosed in accordance with diagnostic criteria described in DSM-5 [32]. According to the Swedish guidelines, prospective daily symptom ratings for at least 2 consecutive menstrual cycles are required [33]. To capture diagnoses made in primary care, we identified all prescriptions of antidepressants (ATC codes N06AA, N06AB, and N06AX) and contraceptives (G02B and G03A) with a specified clinical indication of PMDs from the Prescribed Drug Register. Indications of PMDs were specified by the prescribers as free-text and identified with key word recognition, as described previously [6].

Study design

We identified 84,949 incident cases of PND, including 47,424 cases of prenatal depression and 37,525 cases of postnatal depression. Using incidence density sampling, 10 controls that were free from PND at the time when the matched case was diagnosed were randomly selected for each case. Controls were matched on gestational age for prenatal depression cases and matched on postnatal day for postnatal depression cases, together with maternal age (n = 849,482). To effectively examine the bidirectional association between PMDs and PND within the same study population, we conducted a nested case-control study, a design inherently equivalent to a cohort study [19], identifying all pregnancies, corresponding PNDs and previous history of any indications for PMDs to examine the risk of PND following PMDs in a manner that simulates a prospective approach. We then transitioned this design into a matched cohort with onward follow-up of index PNDs and control pregnancies, enabling us to efficiently assess the risk of PMDs after PND within the same study population. The matching date was used as the index date. Women who had PMDs before their index date were excluded (n = 7,687) and, as they were not at risk for incident PMD diagnosis. All women were then followed from 6 months after delivery (by when over 90% of Swedish women had stopped complete breastfeeding) [34] or the index date, whichever came later, until age 52, emigration, PMD diagnosis, or end of follow-up, whichever came first. During the follow-up, we observed 500 deaths in PND group and 1,559 deaths in matched controls.

The study design is illustrated in S1 Fig. The study was approved by the Regional Ethics Review Board in Stockholm (No. 2018-1515/31). Written informed consent is waived for register-based studies by Swedish law. This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist).

Covariates

Information on the following covariates were retrieved: demographics (maternal age, country of birth, cohabitation status, region of residence, and educational level), smoking 3 months before the pregnancy, BMI in early pregnancy, parity, history of psychiatric disorders before pregnancy, and pregnancy complications and adverse outcomes including hypertensive and diabetic diseases, preterm birth (gestational week <37 weeks), stillbirth, low birth weight (birth weight<2,500 grams), congenital malformations of the offspring, and neonatal death of the offspring (death within 28 days of birth). Data origin and rational of the choice of covariates are described in S1 Methods. ICD codes are summarized in S1 Table, and categorization for covariates are presented in Table 1. Missing values in covariates were coded as unknown for adjustment.

Table 1. Characteristics of women with and without perinatal depression (PND).

	Control	PND	p
Number	849,482	84,949
Matching variables
Maternal age at pregnancy			0.755
15–24	34,353 (4.0)	3,460 (4.1)
25–34	423,729 (49.9)	42,315 (49.8)
35–44	369,579 (43.5)	36,944 (43.5)
45–52	21,821 (2.6)	2,230 (2.6)
Calendar year of pregnancy			0.914
2000–2004	76,350 (8.99)	7,620 (8.97)
2005–2009	250,584 (29.5)	25,123 (29.57)
2010–2014	306,657 (36.1)	30,702 (36.14)
2015–2018	215,891 (25.41)	21,504 (25.31)
Demographics
Cohabitation status			<0.001
Yes	754,536 (88.8)	71,064 (83.7)
No	15,966 (1.9)	3,416 (4.0)
Unknown	78,980 (9.3)	10,469 (12.3)
Country of birth			<0.001
Sweden	637,192 (75.0)	71,867 (84.6)
Others	212,208 (25.0)	13,077 (15.4)
Unknown	82 (0.0)	5 (0.0)
Highest educational level			<0.001
Primary	250,882 (29.5)	30,928 (36.4)
High school	311,924 (36.7)	32,243 (38.0)
College and beyond	250,144 (29.4)	19,257 (22.7)
Unknown	36,532 (4.3)	2,521 (3.0)
Region of residence			<0.001
South	197,509 (23.3)	19,254 (22.7)
Middle	498,808 (58.7)	49,926 (58.8)
North	146,658 (17.3)	15,600 (18.4)
Pregnancy characteristics
Smoking before pregnancy			<0.001
No smoking	680,606 (80.1)	57,696 (67.9)
1–9 cigarette per day	62,631 (7.4)	9,197 (10.8)
≥10 cigarette per day	61,190 (7.2)	13,531 (15.9)
Unknown	45,055 (5.3)	4,525 (5.3)
BMI in early pregnancy (kg/m²)			<0.001
<18.5	19,934 (2.3)	2,031 (2.4)
18.5 to 24.9	468,061 (55.1)	42,238 (49.7)
25 to 29.9	197,301 (23.2)	20,719 (24.4)
≥30	97,711 (11.5)	13,100 (15.4)
Unknown	66,475 (7.8)	6,861 (8.1)
Diabetic diseases			<0.001
No	832,688 (98.0)	82,408 (97.0)
Diabetes	7,615 (0.9)	1,392 (1.6)
Gestational diabetes	9,179 (1.1)	1,149 (1.4)
Hypertensive diseases			<0.001
No	822,521 (96.8)	81,250 (95.6)
Essential hypertension	3,339 (0.4)	436 (0.5)
Preeclampsia	23,622 (2.8)	3,263 (3.8)
History of psychiatric disorders before the pregnancy			<0.001
No	758,311 (89.3)	39,232 (46.2)
Depression	30,989 (3.7)	22,939 (27.0)
Others	60,182 (7.1)	22,778 (26.8)
Parity			<0.001
1	384,770 (45.3)	44,792 (52.7)
2	306,442 (36.1)	24,349 (28.7)
3	110,336 (13.0)	10,845 (12.8)
≥4	47,934 (5.6)	4,963 (5.8)
Pregnancy outcomes
Mode of delivery			<0.001
Cesarean section	138,242 (16.3)	18,836 (22.2)
Assisted vaginal delivery	57,968 (6.8)	6,222 (7.3)
Nonassisted vaginal delivery	653,272 (76.9)	59,891 (70.5)
Preterm birth			<0.001
No	809,231 (95.3)	78,896 (92.9)
Yes	40,251 (4.7)	6,053 (7.1)
Low birth weight¹			<0.001
No	820,694 (96.6)	80,737 (95.0)
Yes	27,596 (3.2)	4,042 (4.8)
Offspring death			<0.001
No	845,480 (99.6)	84,093 (91.1)
Stillbirth	2,817 (0.3)	614 (0.7)
Neonatal death²	1,185 (0.1)	242 (0.3)
Congenital malformations			<0.001
No	780,100 (91.8)	77,236 (90.9)
Yes	69,382 (8.2)	7,713 (9.1)

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¹Birth weight <2,500 grams.

²Death within 28 days of birth.

p-Values were obtained from chi-squared test.

Statistical analysis

We firstly compared the distributions of characteristics between PND cases and their matched controls.

PMDs and subsequent risk of PND

In the nested case-control study, we calculated the percentage of PMDs before pregnancy for PND cases and controls separately and estimated odds ratios (ORs) and 95% confidence intervals (CIs) using conditional logistic regression. The nested case–control analysis, by design, is equivalent to the analysis using full cohort (i.e., assessing the incidence of PND subsequent to PMDs). Using incidence density sampling for individual matching, the estimate OR can be interpreted as hazard ratio (HR) of PND, comparing women with and without PMDs before pregnancy [19]. This analysis was repeated separately for prenatal and postnatal depression, and PND diagnosed in different time windows [first trimester (within 13 gestational weeks) or second to third trimester for prenatal depression, and 0 to 3, 4 to 6, or 7 to 12 months after delivery for postnatal depression].

Both PMDs and PND are correlated with depression and other psychiatric disorders [35,36]. An interaction term between history of psychiatric disorders and PND was added to explore potential effect modification. Because parity is associated with many pregnancy complications and outcomes [37], we performed separate analyses for primi- and multiparous women. To explore effect modification by maternal age and calendar year, we also conducted stratified analysis by maternal age (categorized into 15 to 30 and 31 to 52) and calendar year at pregnancy.

PND and subsequent risk of PMDs

In the matched cohort study, we calculated the incidence rate (IR) of PMDs among PND cases and matched controls and HRs and 95% CIs of PMDs using Cox regression (attained age as the underlying time scale and matching sets as strata). The proportional hazard assumption was deemed reasonable by inspecting the Schoenfeld residuals. Consistent with the nested case-control analyses, we performed analyses by PND subtype (pre- and postnatal depression and PND diagnosed in different time windows) and other stratification analyses.

Adjustment

Model 1 accounted for the matching variables and Model 2 accounted for other demographic factors (country of birth, educational level, region of residency, and cohabitation status). In Model 3, smoking, BMI, parity, and history of psychiatric disorders were further controlled for. We considered Model 3 as the primary for the matched cohort study and Model 2 for the nested case-control study since these covariates were instead possible mediators in this scenario.

Sibling analysis

PMDs and PND may have shared risk factors, such as poor support from family members and genetic factors [10,11], which would confound the studied associations. Sibling comparison contrasts the risk within each set of full sisters discordant on PND and inherently controls for unmeasured confounders shared between full sisters [38]. Briefly, all pregnancies from PND cases and their full sisters were identified through MBR linked to MGR. In total, 56,941 pregnancies from 40,665 full sisters (18,869 PND cases) were included. We examined the bidirectional association using conditional logistic regression and stratified Cox regression.

Additional analyses

We limited the analysis to (1) PMDs with at least 2 specialists’ PMD diagnoses ≥28 days apart to test the validity of PMD diagnosis; (2) PND identified through clinical diagnosis alone to reduce misclassification by using dispensation of antidepressants; and (3) women without severe pregnancy complications or adverse delivery outcomes since they might confound or mediate the studied associations through chronic stress associated with such events [39]. Due to lack of individual-level data on return of postpartum menstruation, we performed a sensitivity analysis of cohort follow-up starting from 2, 3, or 12 months postpartum.

Data were prepared in SAS statistical software version 9.4 (SAS Institute, Cary, NC) and analyzed in Stata 15.1 (STATA, College Station, TX). The statistical significance was set at the nominal two-sided 5% level.

Results

Characteristics

The median age was 30.71 at PND diagnosis. Compared to the controls, women with PND were less educated, were more likely to be born in Sweden, live alone and in South Sweden, had a higher BMI, were more likely to smoke, and have been diagnosed with psychiatric disorder before the pregnancy (all p-values < 0.001; Table 1). They were also more likely to be primiparous, deliver through cesarean section, and experience pregnancy complications and adverse pregnancy and birth outcomes (all p-values < 0.001; Table 1).

PMDs and subsequent risk of PND

We identified 7,687 women with PMDs before pregnancy (2,488 among women with PND) in the nested case-control study. PMDs were associated with a higher risk of subsequent PND (OR 4.98, 95% CI [4.74,5.23]; p < 0.001). Additional adjustment of demographic factors including country of birth, educational level, region of residence, and cohabitation status slightly attenuated the observed association (OR 4.76, 95% CI [4.52,5.01]; p < 0.001) (Table 2). The association was observed for both prenatal (OR 4.58, 95% CI [4.28,4.90]; p < 0.001) and postnatal (OR 5.03, 95% CI [4.65,5.45]; p < 0.001) depression. Moreover, the association remained robust across different pre-/postnatal phases; the OR was lower for prenatal depression diagnosed during first trimester than for those diagnosed later during pregnancy and lower for postnatal depression within 6 months after delivery than those diagnosed during 7 to 12 months (Table 2). Attenuated but statistically significant results were observed after adjusting for potential mediators including history of psychiatric disorders (S2 Table).

Table 2. Association of premenstrual disorders (PMDs) with subsequent risk of perinatal depression (PND): A nested case-control study.

	Women without PND	Women with PND	Model 1¹		Model 2²
	N (%) of PMDs	N (%) of PMDs	OR (95% CI)	p	OR (95% CI)	p
Overall	5,199 (0.6)	2,488 (2.9)	4.98 (4.74,5.23)	<0.001	4.76 (4.52,5.01)	<0.001
By time of diagnosis
Prenatal depression	3,052 (0.6)	1,408 (3.0)	4.80 (4.50,5.12)	<0.001	4.58 (4.28,4.90)	<0.001
By time since pregnancy
First trimester	2,089 (0.8)	870 (3.1)	4.32 (3.98,4.68)	<0.001	3.90 (3.59,4.24)	<0.001
Second-third trimester	963 (0.5)	538 (2.7)	5.86 (5.26,6.53)	<0.001	5.54 (4.96,6.19)	<0.001
Postnatal depression	2,147 (0.6)	1,080 (2.9)	5.23 (4.85,5.63)	<0.001	5.03 (4.65,5.45)	<0.001
By time since delivery
≤6 months	1,044 (0.6)	437 (2.4)	4.31 (3.85,4.83)	<0.001	4.10 (3.66,4.61)	<0.001
7–12 months	1,103 (0.6)	643 (3.3)	6.10 (5.52,6.74)	<0.001	5.80 (5.24,6.42)	<0.001

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CIs, confidence intervals; N, number; OR, odds ratio; PMDs, premenstrual disorders; PND, perinatal depression.

ORs and p-values were obtained from conditional logistic regression.

¹Model 1 was adjusted for the matching variable (i.e., maternal age and calendar year).

²Model 2 was additionally adjusted for country of birth (Sweden or not), educational level (primary, high school, college and beyond), region of residence (south, middle, or north of Sweden), and cohabitation status (yes or no) at matching.

In the stratified analysis, an association between PMDs and subsequent PND was observed regardless of previous history of psychiatric disorders and was stronger among women without such history (p for interaction < 0.001) (Table 3). The association was stronger among multiparous than primiparous women and was comparable across maternal age and calendar year groups (S3 Table).

Table 3. Association of premenstrual disorders (PMDs) with subsequent risk of perinatal depression (PND), stratified by history of psychiatric disorders before pregnancy: A nested case control study.

	Women without PND	Women with PND	Model 1¹		Model 2²
	N (%) of PMDs	N (%) of PMDs	OR (95% CI)	p	OR (95% CI)	p
By history of psychiatric disorder
No	3,940 (0.5)	1,481 (2.9)	6.03 (5.65,6.44)	<0.001	5.73 (5.35,6.14)	<0.001
Depression	296 (2.1)	329 (3.2)	1.61 (1.34,1.93)	<0.001	1.67 (1.38,2.03)	<0.001
Other disorders	963 (1.6)	678 (3.0)	1.95 (1.74,2.18)	<0.001	1.95 (1.73,2.20)	<0.001
p for interaction				<0.001		<0.001

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CIs, confidence intervals; N, number; OR, odds ratio; PMDs, premenstrual disorders; PND, perinatal depression.

ORs and p-values were obtained from logistic regression.

¹Model 1 was adjusted for the matching variable (i.e., maternal age and calendar year).

PND and subsequent risk of PMDs

During a mean follow-up of 6.90 years (standardized deviation 4.31, range 0.003 to 17.50) from 6 months postpartum onwards, we identified 25,553 newly diagnosed cases of PMDs (4,227 among women with PND) in the matched cohort study. Compared to their matched controls, women with PND were at higher risk of PMDs (HR 2.00, 95% CI [1.93,2.07]; p < 0.001). Adjustment for pregnancy characteristics, history of psychiatric disorders, together with demographic factors slightly attenuated the association (HR 1.81, 95% CI [1.74,1.88]; p < 0.001) (Table 4). Estimated HRs were 1.67, 95% CI [1.58,1.76]; p < 0.001 for prenatal and 1.98, 95% CI [1.87,2.09]; p < 0.001 for postnatal depression. Similar associations were found across time windows during pregnancy and after delivery (Table 4).

Table 4. Association of perinatal depression (PND) with subsequent risk of premenstrual disorders (PMDs): A matched cohort study.

	Women without PND	Women with PND	Model 1¹		Model 2²		Model 3³
	N (IR) of PMDs	N (IR) of PMDs	HR (95% CI)	p	HR (95% CI)	p	HR (95% CI)	p
Overall	21,326 (3.8)	4,227 (7.6)	2.00 (1.93,2.07)	<0.001	1.97 (1.90,2.04)	<0.001	1.81 (1.74,1.88)	<0.001
By time of diagnosis
Prenatal depression	11,465 (3.8)	2,249 (7.2)	1.90 (1.82,1.99)	<0.001	1.87 (1.78,1.96)	<0.001	1.67 (1.58,1.76)	<0.001
By time since pregnancy
First trimester	6,073 (4.2)	1,151 (7.6)	1.81 (1.70,1.93)	<0.001	1.73 (1.62,1.85)	<0.001	1.52 (1.40,1.65)	<0.001
Second-third trimester	5,392 (3.4)	1,098 (6.8)	2.01 (1.88,2.15)	<0.001	1.98 (1.85,2.12)	<0.001	1.81 (1.67,1.95)	<0.001
Postnatal depression	9,382 (3.9)	1,978 (8.2)	2.12 (2.02,2.23)	<0.001	2.09 (1.98,2.20)	<0.001	1.98 (1.87,2.09)	<0.001
By time since delivery
≤6 months	4,386 (3.9)	873 (7.7)	1.98 (1.84,2.14)	<0.001	1.94 (1.80,2.09)	<0.001	1.81 (1.67,1.97)	<0.001
7–12 months	4,996 (3.9)	1,105 (8.7)	2.24 (2.09,2.39)	<0.001	2.21 (2.06,2.36)	<0.001	2.13 (1.98,2.30)	<0.001

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CIs, confidence intervals; HR, hazard ratio; IR, incidence rate, per 1,000 person-years; N, number; PMDs, premenstrual disorders; PND, perinatal depression.

HRs and p-values were obtained from conditional Cox regression.

¹Model 1 was adjusted for the matching variable (i.e., maternal age and calendar year).

³Model 3 was additionally adjusted for parity (1, and ≥2), BMI during early pregnancy (categorized into <18.5, 18.5 to 24.9, 25 to 29.9, and ≥30 kg/m²), and smoking before pregnancy (no smoking, 1–9, and ≥10 cigarettes per day) and history of psychiatric disorders before pregnancy (yes or no).

The association between PND and subsequent PMDs was stronger among women without a history of psychiatric disorder in the stratified analysis (p for interaction < 0.001) (Table 5). The association did not differ by parity and calendar year and was somewhat greater among women aged 31 to 52 years at pregnancy (S4 Table).

Table 5. Association of perinatal depression (PND) with subsequent risk premenstrual disorders (PMDs) stratified by history of psychiatric disorders: A matched cohort study.

	Women without PND	Women with PND	Model 1¹		Model 3²
	N (IR) of PMDs	N (IR) of PMDs	HR (95% CI)	p	HR (95% CI)	p
By history of psychiatric disorders
No	19,044 (3.7)	2,709 (7.6)	2.10 (2.01,2.19)	<0.001	2.08 (1.99,2.18)	<0.001
Depression	497 (8.4)	464 (7.8)	0.97 (0.84,1.12)	0.684	0.94 (0.80,1.09)	0.394
Other disorders	1,785 (5.9)	1,054 (7.7)	1.32 (1.21,1.44)	<0.001	1.34 (1.23,1.47)	<0.001
p for interaction				<0.001		<0.001

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CIs, confidence intervals; HR, hazard ratio; IR, incidence rate, per 1,000 person-years; N, number; PMDs, premenstrual disorders; PND, perinatal depression.

HRs and p-values were obtained from conditional Cox regression.

¹Model 1 was adjusted for the matching variable (i.e., maternal age and calendar year).

²Model 3 was additionally adjusted for country of birth (Sweden or not), educational level (primary, high school, college and beyond), region of residence (south, middle, or north of Sweden), and cohabitation status (yes or no) at matching, parity (1, and ≥2), BMI during early pregnancy (categorized into <18.5, 18.5 to 24.9, 25 to 29.9, and ≥30 kg/m²), and smoking before pregnancy (no smoking, 1–9, and ≥10 cigarettes per day) and history of psychiatric disorders before pregnancy (yes or no).

Additional analyses

Largely comparable bidirectional associations between PMDs and PND were observed in the sibling comparison, although results were somewhat attenuated compared to the population comparison (Table 6).

Table 6. Bidirectional association between premenstrual disorders (PMDs) and perinatal depression (PND) in sibling comparison.

PMDs and subsequent risk of PND
	Women without PND	Women with PND	Model 1¹		Model 2²
	N (%) of PMDs	N (%) of PMDs	OR (95% CI)	p	OR (95% CI)	p
Overall	277 (0.7)	536 (2.8)	3.51 (2.95,4.18)	<0.001	3.68 (3.07,4.41)	<0.001
By time of diagnosis
Prenatal depression	201 (0.8)	373 (2.9)	3.57 (2.89,4.41)	<0.001	3.79 (3.04,4.73)	<0.001
By time since pregnancy
First trimester	133 (0.8)	249 (3.2)	3.56 (2.76,4.60)	<0.001	3.49 (2.67,4.55)	<0.001
Second-third trimester	68 (0.7)	124 (2.5)	3.57 (2.45,5.21)	<0.001	4.06 (2.67,6.16)	<0.001
Postnatal depression	76 (0.7)	163 (2.5)	3.52 (2.57,4.82)	<0.001	3.68 (2.66,5.09)	<0.001
By time since delivery
≤6 months	31 (0.5)	78 (2.5)	4.35 (2.63,7.18)	<0.001	4.46 (2.65,7.51)	<0.001
7–12 months	45 (0.7)	85 (2.5)	3.43 (2.22,5.30)	<0.001	3.70 (2.33,5.89)	<0.001
PND and subsequent risk of PMDs
	Women without PND	Women with PND	Model 1¹		Model 3³
	N (IR) of PMDs	N (IR) of PMDs	HR (95% CI)	p	HR (95% CI)	p
Overall	1,375 (5.2)	952 (7.9)	1.60 (1.40,1.82)	<0.001	1.58 (1.38,1.80)	<0.001
By time of diagnosis
Prenatal depression	935 (5.2)	590 (7.4)	1.44 (1.23,1.69)	<0.001	1.41 (1.16,1.73)	<0.001
By time since pregnancy
First trimester	524 (5.1)	309 (7.6)	1.32 (1.05,1.66)	0.018	1.19 (0.88,1.62)	0.257
Second-third trimester	358 (4.9)	281 (7.3)	1.59 (1.26,1.99)	<0.001	1.64 (1.25,2.16)	<0.001
Postnatal depression	440 (5.1)	362 (8.8)	1.88 (1.51,2.36)	<0.001	1.93 (1.47,2.54)	<0.001
By time since delivery
≤6 months	207 (5.1)	157 (8.3)	1.78 (1.27,2.50)	<0.001	1.65 (1.10,2.49)	<0.001
7–12 months	217 (5.0)	205 (9.2)	2.04 (1.51,2.77)	<0.001	2.40 (1.60,3.61)	<0.001

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CIs, confidence intervals; HR, hazard ratio; IR, incidence rate, per 1000 person-years; N, number; OR, odds ratio; PMDs, premenstrual disorders; PND, perinatal depression.

Analyses were stratified on full sister sets. ORs/HRs and p-values were obtained from conditional logistic and Cox regressions.

¹Model 1 was adjusted for maternal age and calendar year of the delivery.

In both study designs, robust bidirectional associations were observed when restricting to (1) women without pregnancy complications or adverse outcomes; (2) PMDs with 2 specialists’ diagnoses ≥28 days apart; and (3) PND ascertained through clinical diagnosis (S5 Table). Moreover, similar results were observed with different start of follow-up in the cohort study (S6 Table).

Discussion

In the present study based on data from Swedish national registers, we found a bidirectional link between premenstrual disorders and perinatal depression, which was pronounced for prenatal and postnatal depression and slightly stronger for postnatal depression. The bidirectional association was verified among women without a history of psychiatric disorders. These findings were corroborated, despite the attenuation, in the sibling comparison, which controls for familial environmental and genetic factors.

Previous studies have used data on history of PMDs retrospectively collected during or after pregnancy, which might be vulnerable to recall bias and systematic error [12,13]. Taking advantage of prospectively collected data in Swedish healthcare registers, the study is the first, to our knowledge, to demonstrate a positive association between PMDs and subsequent risk of PND. Moreover, previous studies exclusively focused on postnatal depression, mostly ascertained within 8 weeks postpartum [10,11]. With retrospectively collected data, one systematic review and one meta-analysis reported that women with postnatal depression were more likely to endorse a history of PMDs [10,11], which is in line with our results. The meta-analysis reported an OR of 2.20, 95% CI [1.81,2.68] for PMDs among women with postnatal depression (mostly assessed within 6 months after delivery) [10]. Correspondingly, our data show that women with PMDs have more than 3 times higher risk of PND within 6 months postpartum.

To our knowledge, no study has examined the association between prenatal depression and PMDs. Our findings on prenatal depression therefore extend knowledge to another subtype of PND that occurs during pregnancy. Although the etiology for prenatal depression is complex [40], our finding may suggest a subgroup of prenatal depression may be related to hormone changes as well. However, future studies are needed to confirm our results and to understand the biologic link between PMDs and prenatal depression. Interestingly, we found a stronger association between PMDs and PND among multiparous than primiparous women. It is known that primiparous women have a higher risk of PND [41] while parity is positively associated with PMDs [42]. It is plausible that premenstrual symptoms can worsen after pregnancy likely due to an escalated abnormal response to hormonal changes in relation to pregnancy [15]. However, it is unclear whether multiple pregnancies would further deteriorate the pathological response to hormone fluctuations. Future studies are needed to better understand the potential mechanisms.

Our work illustrates a higher risk of PMDs among women who experienced PND. Although many women with PMDs have symptom onset in adolescence [43], symptom worsening has been reported with increasing age [44] and parity [15]. It is possible that women with milder premenstrual symptoms experienced worse symptoms after pregnancy and are therefore first diagnosed with PMD after pregnancy. The delayed diagnosis of PMD could be one reason for this finding [45]. Interestingly, we noted a stronger association between PMDs and subsequent PND than the association in the other direction. This might be because many PMDs have an early onset [43], likely before the average age at first childbirth, whereas we targeted the late-onset PMDs in the cohort study. It is also plausible that women with PND are more likely to take antidepressants, which may mitigate premenstrual symptoms. On the other direction, although women with PMDs may use antidepressants as well, women are more likely to discontinue psychotic medications during pregnancy and even after due to breastfeeding [46,47]. However, future studies are warranted to disentangle the role of treatment in the differential associations observed for both directions.

There are several explanations to the bidirectional association between PMDs and PND. First, both PMDs and PND have shared liability with psychiatric disorders [35,36], which may explain the findings. PMDs could also lead to the development of psychiatric comorbidities [48], which increase the risk of PND. In this scenario, psychiatric disorders are mediators of the studied associations. Indeed, additional adjustment of psychiatric disorders attenuated the associations. However, the bidirectional associations (relative risks) remained robust and even stronger among women without a history of psychiatric disorders, suggesting our findings cannot be entirely explained by psychiatric disorders. On the other hand, although the absolute risk (e.g., probability or incidence rate) of PMDs is higher among women with a psychiatric history, a diagnosis of PND does not translate into an increased risk of PMDs to the same extent as it does for those without a psychiatric history. This is likely because the already heightened risk of PMDs among women with a psychiatric history, particularly among those with a history of depression. However, PMDs or PND have a relatively weaker correlation with other psychiatric disorders compared to depression [35,36]. Among women with a history of other psychiatric disorders, PMDs appeared to confer a higher risk of PND (Table 3) and vice versa (Table 5). Second, PMDs and PND may share other risk factors such as obesity and smoking [4,49,50]. However, the bidirectional association persisted after adjustment of BMI and smoking. Childhood adversities could be another shared risk factor [51,52]. However, sibling comparison should to some extent have addressed that, at least with respect to adversities shared between full sisters. Third, PMDs and PND may share genetic susceptibility. The twin heritability was estimated to be around 54% for PND [53] and 44% to 95% for PMDs [54–56]. Indeed, the attenuation of the associations in sibling comparison lends support to the shared genetic factors and/or familial environmental factors between both disorders. But the associations remained despite the attenuation in sibling comparison. Last, PMDs and PND may share common etiology. The symptom onset of both disorders is linked to hormonal fluctuations, particularly of estrogen and progesterone, which have receptors in the brain, and have been linked to mood alterations [57,58]. PND occurs during a period that is marked with rapid increase of steroid hormones during pregnancy and a rapid decline after delivery [7]. Similarly, the onset of PMD symptoms typically follows the rapid withdraw of hormones in the late luteal phase [8]. It is plausible that an abnormal response to natural hormone fluctuations predisposes women to both PMDs and PND. Future research is, however, needed to reveal the potentially shared underlying etiology of both conditions.

The strength of the study lies in the large sample size with long and complete follow-up, the prospectively and independently collected data on PMDs and PND, and covariates that could confound the studied association. The nested-case control study in combination with the transition into a matched cohort study with onward follow-up allowed us to study the association between PMDs and PND in a bidirectional fashion with efficiency, which is equivalent to two independent cohort studies within the same study population. Moreover, the sibling comparisons allowed us to address the influence of familial factors. However, the study has several limitations. First, the clinical diagnosis of PMDs in the Swedish Patient Register has not been validated. Although prospective daily symptom ratings for at least two consecutive menstrual cycles are required for diagnosing PMDs in Sweden according to the guidelines [33], we cannot confirm that the clinical decision to assign a diagnosis or medical treatment to every single ascertained PMD in the registers is based on prospective daily ratings. However, clinical guidelines are often well followed owing to the state-funded nature of the public healthcare system in Sweden. Moreover, the Swedish Patient Register has fairly high validity in general [59], with the overall positive predicted value for most diagnoses ranging from 85% to 95% [60]. For a range of psychiatric disorders [61–64] and gynecologic diseases [22,65], the diagnosis has been reported to have high validity. Lastly, sensitivity analysis restricting to PMDs with at least two specialist-made diagnoses at least 28 days apart yielded similar results. In addition, the diagnostic criteria for PMDs may have changed over time. However, stratification analysis by calendar year showed similar results, suggesting that our results are robust given the changes of labeling and diagnostic criteria for PMDs over time. Second, using prescription of antidepressants to identify PND cases might result in misclassifications because antidepressants are also prescribed for other psychiatric disorders. However, sensitivity analysis restricted to clinically diagnosed PND cases showed comparable results. Moreover, reverse causation may to some extent contribute to the observed associations, although we tried to minimize the risk for such bias through the study design that simulates a prospective approach. For instance, some individuals might already have PMDs before pregnancy but received the diagnosis when seeking healthcare for PND. However, similar results have been found when starting the follow-up 1 year after delivery, when such prevalent PMDs would presumably have been captured sooner after the delivery during the postpartum checkups. Third, we did not have data on the exact date of menstruation return for postpartum women, which could be individually different and affected by multiple factors including breastfeeding practices and mode of delivery. Nevertheless, sensitivity analysis with different starting points of the follow-up yielded similar results. Lastly, relying on the Patient Register, we would have missed cases with less severe symptomology and did not seek healthcare service. Moreover, with the ICD code we used to identify PND, we might have missed a small number of mood disturbances or affective disorders that are not sufficiently severe or long-lasting to be classified as depressive episodes. Our findings thus may not generalize well to women with mild PMDs or PND symptomology.

In conclusion, our findings shed light on the bidirectional association between PMDs and PND, supporting a shared underlying etiology. Preconception and maternity care providers should be aware of the risk of developing PND among women with a history of PMDs. Moreover, healthcare providers may inform women with PND about the potential risk of PMDs when menstruation returns after childbirth. The bidirectional relationship is, to a limited extent, explained by psychiatric comorbidities and familial confounding.

Supporting information

S1 Checklist. STROBE Statement—Checklist of items that should be included in reports of observational studies.

(DOCX)

pmed.1004363.s001.docx^{(24.2KB, docx)}

S1 Methods. Data origin and rational of the choice of covariates.

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S1 Fig. Flow chart.

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S1 Table. International Classification of Diseases codes used to define the studied medical conditions.

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S2 Table. Association of premenstrual disorders (PMDs) with subsequent risk of perinatal depression (PND) adjusted for mediators: A nested case-control study.

(DOCX)

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S3 Table. Stratified association of premenstrual disorders (PMDs) with subsequent perinatal depression (PND): A nested case control study.

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S4 Table. Stratified association of perinatal depression (PND) with subsequent premenstrual disorders (PMDs): A matched cohort study.

(DOCX)

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S5 Table. Bidirectional link between perinatal depression (PND) with premenstrual disorders (PMDs): Sensitivity analysis.

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S6 Table. Association of perinatal depression (PND) with subsequent premenstrual disorders (PMDs): A matched cohort study with different start of follow-up.

(DOCX)

pmed.1004363.s009.docx^{(17.8KB, docx)}

Abbreviations

ACOG: American College of Obstetricians and Gynecologists
CI: confidence interval
HR: hazard ratio
IR: incidence rate
MBR: Medical Birth Register
MGR: Multi-Generation Registers
OR: odds ratio
PMD: premenstrual disorder
PMDD: premenstrual dysphoric disorder
PMS: premenstrual syndrome
PND: perinatal depression

Data Availability

Data are from the Swedish national healthcare registers. Data cannot be put into a public data repository according to Swedish law but are available by applying through Statistics Sweden or the Swedish National Board of Health and Welfare. Detailed information on data application can be found in the following links: https://www.scb.se/vara-tjanster/bestalla-mikrodata/ and https://bestalladata.socialstyrelsen.se/.

Funding Statement

The work was supported by the Chinese Scholarship Council (No. 201700260289 to QY), the Swedish Research Council for Health, Working Life and Welfare (FORTE) (No. 2020-00971 and 2023-00399 to DL), the Swedish Research Council (Vetenskapsrådet) (No. 2020-01003 to DL), Karolinska Institutet Strategic Research Area in Epidemiology and Biostatistics (grant to DL), Karolinska Institutet SFOepi Junior Scholar Grant (to DL) and the Icelandic Research Fund (No. 218274-051 to UAV). The funders had no role in study design, data collection and analysis, preparation of the manuscript or decision to publish.

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PLoS Med. doi: 10.1371/journal.pmed.1004363.r001

Decision Letter 0

Philippa C Dodd

23 May 2023

Dear Dr Yang,

Thank you for submitting your manuscript entitled "The bidirectional association between premenstrual disorders and perinatal depression: a nationwide register-based study" for consideration by PLOS Medicine.

Your manuscript has now been evaluated by the PLOS Medicine editorial staff and I am writing to let you know that we would like to send your submission out for external peer review.

However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.

Please re-submit your manuscript within two working days, i.e. by May 25 2023 11:59PM.

Once your full submission is complete, your paper will undergo a series of checks in preparation for peer review. Once your manuscript has passed all checks it will be sent out for review.

Feel free to email us at plosmedicine@plos.org if you have any queries relating to your submission.

Kind regards,

Philippa Dodd, MBBS MRCP PhD

PLOS Medicine

PLoS Med. doi: 10.1371/journal.pmed.1004363.r002

Decision Letter 1

Philippa C Dodd

26 Oct 2023

Dear Dr. Yang,

Thank you very much for submitting your manuscript "The bidirectional association between premenstrual disorders and perinatal depression: a nationwide register-based study" (PMEDICINE-D-23-01426R1) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of these reviews, I am pleased to let you know that we would like to consider a revised version that addresses the reviewers' and editors' comments. We won't be able to make a decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We expect to receive your revised manuscript by Nov 16 2023 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript. If you have any questions please don't hesitate to contact me directly via the email address detailed below.

Best wishes,

Pippa

Philippa Dodd, MBBS MRCP PhD

PLOS Medicine

plosmedicine.org

pdodd@plos.org

-----------------------------------------------------------

COMMENTS FROM THE EDITORS

GENERAL

Please respond to all editor and reviewer comments detailed below in full.

Please ensure that the study is reported according to the STROBE guideline, and include the completed STROBE checklist as Supporting Information. Please add the following statement, or similar, to the Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)."

The STROBE guideline can be found here: http://www.equator-network.org/reporting-guidelines/strobe/

When completing the checklist, please use section and paragraph numbers, rather than page numbers as these often change in the event of publication.

* The editorial team agree with the reviewer (please see below) regarding the need to better justify the rationale for the use of both a nested-case control study and a matched cohort study. Please include additional detail as relevant in the introduction, methods, and discussion sections of your manuscript.*

** Please also take to care to ensure that you clearly and accurately differentiate between prospective and retrospective data collection and study design. Please see specific comments under ‘Introduction’ and ‘Discussion’.**

TITLE

Please include reference to Sweden in the title, we suggest, ‘The bidirectional association between premenstrual disorders and perinatal depression: a nationwide register-based study from Sweden’ or similar.

COMPETING INTERESTS

All authors must declare their relevant competing interests per the PLOS policy, which can be seen here:

https://journals.plos.org/plosmedicine/s/competing-interests

For authors with ties to industry, please indicate whether any of the interests has a financial stake in the results of the current study.

ABSTRACT

Please structure your abstract using the PLOS Medicine headings (Background, Methods and Findings, Conclusions).

Please combine the Methods and Findings sections into one section, “Methods and findings”.

Abstract Background: Provide the context of why the study is important, as in the current version. The final sentence should clearly state the study question.

Abstract Methods and Findings:

Please ensure that all numbers presented in the abstract are present and identical to numbers presented in the main manuscript text.

Please (briefly) justify the decision to use both methodological approaches in the study.

Please quantify the main results with 95% CIs and p values. When reporting p values please report as p<0.001 and where higher as p=0.002, for example. Please separate upper and lower CI bounds with commas as opposed to hyphens to prevent confusion with reporting of negative values. Suggest reporting statistical information as follows, ‘(OR 4.58; 95% CI [4.28,4.90];p</=) to improve accessibility and clarity for the reader.

Please define ‘OR’, ‘IR’ and ‘HR’ at first use for the reader.

Please include any important dependent variables that are adjusted for in the analyses.

Please include the actual amounts and/or absolute risk(s) of relevant outcomes, not just relative risks or correlation coefficients. (example for absolute risks: PMID: 28399126).

In the last sentence of the Abstract Methods and Findings section, please describe the main limitation(s) of the study's methodology.

Abstract Conclusions:

Please address the study implications without overreaching what can be concluded from the data; the phrase "In this study, we observed ..." may be useful.

Please interpret the study based on the results presented in the abstract, emphasizing what is new without overstating your conclusions.

Please avoid vague statements such as "these results have major implications for policy/clinical care". Mention only specific implications substantiated by the results.

Please avoid assertions of primacy ("We report for the first time....")

AUTHOR SUMMARY

At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The authors summary should consist of 2-3 succinct bullet points under each of the following headings:

• Why Was This Study Done? Authors should reflect on what was known about the topic before the research was published and why the research was needed.

• What Did the Researchers Do and Find? Authors should briefly describe the study design that was used and the study’s major findings. Do include the headline numbers from the study, such as the sample size and key findings.

• What Do These Findings Mean? Authors should reflect on the new knowledge generated by the research and the implications for practice, research, policy, or public health. Authors should also consider how the interpretation of the study’s findings may be affected by the study limitations. In the final bullet point of ‘What Do These Findings Mean?’, please describe the main limitations of the study in non-technical language.

Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

INTRODUCTION

In the discussion you make the distinction between using prospectively collected data as opposed to retrospectively collected data very clear (. Here is it less clear and could be misinterpreted. At first read I thought you were describing your study as prospective. Please revise for clarity

Perhaps instead you could introduce the rationale for using a nested-case control and matched cohort design to address your questions in context of other existing study designs. What advantage does this offer above existing published studies? Please also see the methods section and reviewer comments (below) in reference to the same. You may decide that all this information is better placed there. We leave it to your discretion.

In revising your introduction, please ensure that you indicate whether your study is novel and how you determined that and as in the current version, please conclude the Introduction with a clear description of the study question or hypothesis.

METHODS and RESULTS

As above please ensure that you add the following statement, or similar, to the Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)."

As above, please clearly explain the rationale for implementing a nested-case control and a matched cohort design.

Line 81 – suggest, ‘Databases’ perhaps, instead, as a sub-heading.

Please see reviewer comments below regarding the use of DSM-5 and ICD-10 coding and the potential implications this has on the construct of your data set thus the outcomes.

Line 117 – what is ‘PDR’? Please define, apologies if I have missed it previously.

As for the abstract, please quantify the main results with 95% CIs and p values. When reporting p values please report as p<0.001 and where higher as p=0.002, for example. When a p value is given, please specify the statistical test used to determine it.

Please separate upper and lower CI bounds with commas as opposed to hyphens to prevent confusion with reporting of negative values. Suggest reporting statistical information as follows, ‘(OR 4.58; 95% CI [4.28,4.90];p</=) to improve accessibility and clarity for the reader.

Please define the length of follow up (eg, in mean, SD, and range).

TABLES

Please provide a table showing the baseline characteristics of the study population in the main manuscript, this is currently placed in the supporting information.

Thank you for indicating that your analyses are adjusted and the factors which are adjusted for. To help facilitate transparent data reporting please also include unadjusted analyses for comparison.

Throughout, as for the main manuscript. Where 95% CIs are reported please use commas as opposed to hyphens to separate upper and lower bounds.

Throughout, as for the main manuscript, where 95% CIs are reported please also report p values as <0.001 and where higher the exact p value as p= 0.002, for example.

Where p values are reported in the footnote(s) please detail the statistical test used to determine them.

DISCUSSION

Please temper the language in your opening paragraph, ‘…in this study we found…’ might be helpful.

Please present and organize the Discussion as follows: a short, clear summary of the article's findings; what the study adds to existing research and where and why the results may differ from previous research; strengths and limitations of the study; implications and next steps for research, clinical practice, and/or public policy; one-paragraph conclusion.

Line 260 – ‘260 women without psychiatric history of .’ this sentence is incomplete, please revise

Line 265 – ‘..the study is the first…’ claims of primacy can be risky, suggest, ‘to our knowledge’ or similar.

As above (for the introduction) please take care when describing/discussing/differentiating retrospective Vs prospective data collection and study design. Importantly, prospectively collected data often contributes to retrospective study designs.

Line 270 – please use a comma instead of a hyphen to separate upper and lower CI bounds. Please also indicate to the reader that the numerical values represent CIs. Please use formatting as detailed above under abstract and methods/results.

Line 272 – perhaps ‘more than three times the risk’ instead, to improve accessibility for the reader.

Your discussion of the study strengths could be more detailed. As above, in reference to the dual study design used to answer your questions what advantages does this offer? Please discuss.

Line 316 – please remove the subheading ‘Limitations’ such that the discussion reads as continuous prose.

Please remove the funding, disclosure and conflict statements form the main manuscript and include only in the manuscript submission form when you re-submit your manuscript. In the event of publication these will be compiled as metadata.

REFERENCES

For in-text reference callouts please place citations in square brackets and preceding punctuation. For example [1,3]. Please note the absence of spaces between citations.

In the bibliography please list up to but no more than 6 author names followed by et al in that event that more than 6 contribute to the study.

Please ensure that web references include an ‘Accessed [date]’

Journal name abbreviations should be those found in the National Center for Biotechnology Information (NCBI) databases.

Please see our website for other reference guidelines https://journals.plos.org/plosmedicine/s/submission-guidelines#loc-references

SUPPORTING INFORMATION

Please cite your Supporting Information as outlined here: https://journals.plos.org/plosmedicine/s/supporting-information

In the published article, supporting information files are accessed only through a hyperlink attached to the captions. For this reason, you must list captions at the end of your manuscript file. You may include a caption within the supporting information file itself, as long as that caption is also provided in the manuscript file. Do not submit a separate caption file.

Please ensure that all abbreviations are defined for the reader at first use.

Please ensure that tables follow out guidance outlined above as for the main manuscript, including the provision of p values and unadjusted analyses, and use of commas to separate upper and lower CI bounds.

As above, please include the completed STROBE checklist as Supporting Information. When completing the checklist, please use section and paragraph numbers, rather than page numbers as these often change in the event of publication. Please be reminded to add the following statement, or similar, to the Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)."

Please ensure that your supporting information follows the referencing guidance outlined above.

Comments from the reviewers:

Reviewer #1: This is a well-conducted nationwide register-based study on the bidirectional association between premenstrual disorders and perinatal depression. The study design, datasets, statistical methods and analyses, and presentation (tables and figures) and interpretation of the results are mostly adequate and of a good standard. However, still a few issues needing attention.

1) There are 10 matched controls for each index case. Are these controls used for both the nested case-control study and the matched cohort study? or some used for each and at what split?

2) For the Cox models in the matched cohort study, as the outcome is subsequent premenstrual disorders (PMDs) rather than all cause mortality, there is a potential competing risk issue, e.g., from death. Do we have mortality data for the study cohorts? Presumably low, but good to know.

3) Missing data. There is no mention at all on missing data in the study. Are there any? How were the missing data dealt with?

Reviewer #2: This paper is a significant contribution to knowledge of mood disorders affecting menstruating and pregnant people, and the authors should be congratulated for their careful 2-part design to characterize the bidirectional nature of the relationship between menstrually related mood disorders and perinatal depression. A minor comment for your consideration:

-The paper in a couple of places conflates premenstrual disorders (PMD's, which is the basis for your analysis) and the DSM diagnosis of premenstrual dysphoric disorder (PMDD). The criteria you appear to be using for PMDs is more broad than that - the Lancet article you reference (3) is about premenstrual syndrome and refers to findings of prospective and retrospective studies suggest that 5-8% of women with hormonal cycles have moderate to severe symptoms, not the 20-30% you state in this article. In addition, you refer to the Swedish guidelines using DSM-5 criteria requiring prospective rating. However, DSM-5 was first published in 2013, and your study starts in 2001. In your previous paper on PMDs and injury (ref 4) you more accurately characterize that your PMD case ascertainment is not clearly based on prospective rating. You should clarify this distinction in this paper similarly - as written it is misleading to the reader.

Any attachments provided with reviews can be seen via the following link:

[LINK]

Attachment

Submitted filename: review comments.docx

pmed.1004363.s010.docx^{(21KB, docx)}

PLoS Med. 2024 Mar 28;21(3):e1004363. doi: 10.1371/journal.pmed.1004363.r003

Author response to Decision Letter 1

16 Nov 2023

Attachment

Submitted filename: Response letter.docx

pmed.1004363.s011.docx^{(167.9KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1004363.r004

Decision Letter 2

Philippa C Dodd

18 Dec 2023

Dear Dr. Yang,

Thank you very much for re-submitting your manuscript "The bidirectional association between premenstrual disorders and perinatal depression: a nationwide register-based study from Sweden" (PMEDICINE-D-23-01426R2) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by 3 reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

We expect to receive your revised manuscript within 1 week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

Please note, when your manuscript is accepted, an uncorrected proof of your manuscript will be published online ahead of the final version, unless you've already opted out via the online submission form. If, for any reason, you do not want an earlier version of your manuscript published online or are unsure if you have already indicated as such, please let the journal staff know immediately at plosmedicine@plos.org.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Dec 21 2023 11:59PM.

Best wishes,

Pippa

Philippa Dodd, MBBS MRCP PhD

PLOS Medicine

plosmedicine.org

pdodd@plos.org

------------------------------------------------------------

COMMENTS FROM THE EDITORS:

GENERAL

Thank you for your detailed and considered responses to previous editor and reviewer comments. Please see below for further comments that we require you address prior to publication.

AUTHOR SUMMARY

Thank you for including an author summary which reads very nicely but is too long. Each sub-heading should precede 2-3 concise (1-2 sentence) bullet point statements (much of the statistical information could be removed to conserve space, for example). Please keep in mind that the summary should be accessible to a wide audience including the lay person. Please revise for brevity, in mind of the below guidance:

The author summary should consist of 2-3 succinct bullet points under each of the following headings:

• Why Was This Study Done? Authors should reflect on what was known about the topic before the research was published and why the research was needed.

This text should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary and please see our website for published examples https://journals.plos.org/plosmedicine/

ABSTRACT

Line 32 – We agreed that case-control design being “equivalent to a cohort study but with improved efficiency” is not an accurate description. Please remove this statement.

We suggest, ‘…transitioned that design into a matched cohort study with onward follow-up to simulate a prospective study design and examine the risk of PMDs after PND…’. Please also see below for the same/similar elsewhere and amend accordingly and consistently throughout as necessary.

METHODS and RESULTS

Line 196 – ‘…to prospectively examine the risk…’ we understand what you mean but it is technically incorrect as all data is examined (in your study) in retrospect. Please revise suggest (as above), ‘to examine the risk…in a manner which simulates a prospective approach’

TABLES

Table 1 – it would be worth indicating whether there are significant differences between the PND and control groups? Please include p values reporting a p<0.001 and where higher the exact p value as 0.002, for example.

Tables 2-6 – please separate upper and lower CI bounds with commas as opposed to hyphens as the latter can be confused with reporting of negative values. Please include the statistical test used to determine p values in the footnotes.

DISCUSSION

Thank you for your consideration of not overstating your findings. We do think that wider discussion of the implications of your study (in context of the limitations you highlight) and next steps for research would be helpful. How does this study specifically inform subsequent?

Lines 428 onwards are repeated at lines 430 onwards please correct the duplication.

Line 436 – ‘prospective study design’ as above please revise and please check throughout for consistency, clarity and accuracy of reporting.

REFERENCES

Please check all references for accuracy as per reviewer comments which we agree with – ref #33 appears incomplete, please revise. Refs# 40 and 48 are detailed as ‘invalid citations’. This list is not exhaustive, please check carefully and amend in accordingly.

Ref #25 – is listed as ‘in press’ and appears not to have been published. Papers cannot be listed in the reference list until they have been accepted for publication or are publicly available on a preprint archive. Please clarify whether the paper has been accepted for publication in the BMJ, as your bibliography might suggest, and please provide a copy for the editors for reference as well as a letter confirming intent to publish. If you are unable to do the former the information may be cited in the text as a personal communication with the author if the author provides written permission to be named. Alternatively, please provide a different appropriate reference.

Please update your reference formatting in-line with our guidance which can be found here https://journals.plos.org/plosmedicine/s/submission-guidelines#loc-references

In the bibliography, please ensure that you list up to but no more than 6 author names followed by et al.

For all web references please ensure you include an, ‘Accessed [date].’

Journal name abbreviations should be those listed in the National Center for Biotechnology Information (NCBI) databases.

SUPPORTING INFORMATION

References - Please ensure that all reference formatting is applied to the supporting information as for the main manuscript. For in-text reference callouts please place citations in square parentheses separate by commas. For example, [1,3,6] or [1-3]. Please check and amend throughout the supporting files.

STROBE Checklist – thank you for including the checklist please amend to refer to section and paragraph numbers as opposed to page (or line numbers) as these often change at publication. Please also amend the column header to read ‘Section/paragraph’ or similar.

Tables – as for the main manuscript please separate upper and lower CI bounds with commas as opposed to hyphens as the latter can be confused with reporting of negative values. Please include the statistical test used to determine p values in the footnotes.

SOCIAL MEDIA

To help us extend the reach of your research, please detail any X (formerly Twitter) handles you wish to be included when we tweet this paper (including your own, your coauthors’, your institution, funder, or lab) in the manuscript submission form when you re-submit the manuscript.

COMMENTS FROM THE REVIEWERS:

Reviewer #1: Thanks authors for their great effort to improve the manuscript. I am satisfied with the response and revision. No further issues needing attention.

Reviewer #3: The authors have taken a substantial revision of the manuscript which I believe it now meets the standard of PLoS Medicine for publication. Please address the following minor comments before publication.

1. There are 3 references that are not shown correctly in the bibliography list. Please doublecheck to correct it.

2. regarding PND-->PMDs - Line 241 of the Revision 1 version of manuscript, Table 4: how to explain the positive results among those WITH history of other psychiatric disorders (new finding no. 4)? Please elaborate on this.

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. 2024 Mar 28;21(3):e1004363. doi: 10.1371/journal.pmed.1004363.r005

Author response to Decision Letter 2

16 Feb 2024

Attachment

Submitted filename: Response letter.docx

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PLoS Med. doi: 10.1371/journal.pmed.1004363.r006

Decision Letter 3

Philippa C Dodd

19 Feb 2024

Dear Dr Yang,

On behalf of my colleagues and the Academic Editor, Professor Mark Tomlinson, I am pleased to inform you that we have agreed to publish your manuscript "The bidirectional association between premenstrual disorders and perinatal depression: a nationwide register-based study from Sweden" (PMEDICINE-D-23-01426R3) in PLOS Medicine.

Prior to publication we require that you address the following:

Line 68 – please revise this point into 2 bullet points as detailed below:

* We conducted a nested case-control study and transitioned that design into a matched cohort study with onward follow-up to simulate a prospective study design.

* Among approximately 1.8 million singleton pregnancies in Sweden between 2001-2018, we identified 84,949 women with PND and 849,482 unaffected women, individually matched on age and calendar year. Pregnancies from full sisters of women with PND were also identified for sibling comparison.

Line 76 – please remove the word ‘their’

Line 83 – please include a final bullet point in the ‘what do these findings mean’ sub-section, which describes the main limitations of the study in nontechnical language.

Line 448 – please remove the statement ‘PND women’ and replace with, ‘women with PND’

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. Once you have received these formatting requests, please note that your manuscript will not be scheduled for publication until you have made the required changes.

In the meantime, please log into Editorial Manager at http://www.editorialmanager.com/pmedicine/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process.

PRESS

We frequently collaborate with press offices. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximise its impact. If the press office is planning to promote your findings, we would be grateful if they could coordinate with medicinepress@plos.org. If you have not yet opted out of the early version process, we ask that you notify us immediately of any press plans so that we may do so on your behalf.

We also ask that you take this opportunity to read our Embargo Policy regarding the discussion, promotion and media coverage of work that is yet to be published by PLOS. As your manuscript is not yet published, it is bound by the conditions of our Embargo Policy. Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit http://www.plos.org/about/media-inquiries/embargo-policy/.

Thank you again for submitting to PLOS Medicine. We look forward to publishing your paper.

Best wishes,

Pippa

Philippa Dodd, MBBS MRCP PhD

PLOS Medicine

pdodd@plos.org

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Checklist. STROBE Statement—Checklist of items that should be included in reports of observational studies.

(DOCX)

pmed.1004363.s001.docx^{(24.2KB, docx)}

S1 Methods. Data origin and rational of the choice of covariates.

(DOCX)

pmed.1004363.s002.docx^{(22KB, docx)}

S1 Fig. Flow chart.

(DOCX)

pmed.1004363.s003.docx^{(26.6KB, docx)}

S1 Table. International Classification of Diseases codes used to define the studied medical conditions.

(DOCX)

pmed.1004363.s004.docx^{(17.5KB, docx)}

S2 Table. Association of premenstrual disorders (PMDs) with subsequent risk of perinatal depression (PND) adjusted for mediators: A nested case-control study.

(DOCX)

pmed.1004363.s005.docx^{(18.6KB, docx)}

S3 Table. Stratified association of premenstrual disorders (PMDs) with subsequent perinatal depression (PND): A nested case control study.

(DOCX)

pmed.1004363.s006.docx^{(17.9KB, docx)}

S4 Table. Stratified association of perinatal depression (PND) with subsequent premenstrual disorders (PMDs): A matched cohort study.

(DOCX)

pmed.1004363.s007.docx^{(18.4KB, docx)}

S5 Table. Bidirectional link between perinatal depression (PND) with premenstrual disorders (PMDs): Sensitivity analysis.

(DOCX)

pmed.1004363.s008.docx^{(18.9KB, docx)}

S6 Table. Association of perinatal depression (PND) with subsequent premenstrual disorders (PMDs): A matched cohort study with different start of follow-up.

(DOCX)

pmed.1004363.s009.docx^{(17.8KB, docx)}

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Data Availability Statement

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PERMALINK

The bidirectional association between premenstrual disorders and perinatal depression: A nationwide register-based study from Sweden

Qian Yang

Emma Bränn

Elizabeth R Bertone- Johnson

Arvid Sjölander

Fang Fang

Anna Sara Oberg

Unnur A Valdimarsdóttir

Donghao Lu

Roles

Abstract

Background

Methods and findings

Conclusions

Author summary

Why was this study done?

What did the researchers do and find?

What do these findings mean?

Introduction

Methods

Data sources

Ascertainment of PND

Ascertainment of PMDs

Study design

Covariates

Table 1. Characteristics of women with and without perinatal depression (PND).

Statistical analysis

PMDs and subsequent risk of PND

PND and subsequent risk of PMDs

Adjustment

Sibling analysis

Additional analyses

Results

Characteristics

PMDs and subsequent risk of PND

Table 2. Association of premenstrual disorders (PMDs) with subsequent risk of perinatal depression (PND): A nested case-control study.

Table 3. Association of premenstrual disorders (PMDs) with subsequent risk of perinatal depression (PND), stratified by history of psychiatric disorders before pregnancy: A nested case control study.

PND and subsequent risk of PMDs

Table 4. Association of perinatal depression (PND) with subsequent risk of premenstrual disorders (PMDs): A matched cohort study.

Table 5. Association of perinatal depression (PND) with subsequent risk premenstrual disorders (PMDs) stratified by history of psychiatric disorders: A matched cohort study.

Additional analyses

Table 6. Bidirectional association between premenstrual disorders (PMDs) and perinatal depression (PND) in sibling comparison.

Discussion

Supporting information

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Philippa C Dodd

Roles

Decision Letter 1

Philippa C Dodd

Roles

Author response to Decision Letter 1

Decision Letter 2

Philippa C Dodd

Roles

Author response to Decision Letter 2

Decision Letter 3

Philippa C Dodd

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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