Abstract

Background

This study aims to explore the relationship between female reproductive factors (age at first birth (AFB), age at last birth (ALB), gravidity, and number of live birth (NLB)) and prevalence of depression among the US women.

Methods

The relationship between AFB, ALB, gravidity, and NLB with the prevalence of depression was explored using publicly available data from the National Health and Nutrition Examination Survey 2005–2018. This cross-sectional study included female participants aged 20Ìýyears and older, with reproductive factors and depressive symptoms reported by the participants. Depression was evaluated using the Patient Health Questionnaire-9, with a score of ≥ 10 representing major depression disorder. Weighted multivariable logistic regression and restricted cubic splines (RCS) were utilized to explore the association of AFB, ALB, gravidity and NLB with depression.

Results

In this study of 11,488 US women, 1,332 (11.6%) women had depression. Compared to the reference group of women with AFB under 18Ìýyears, the fully adjusted ORs and 95% CIs for depression were 0.83 (95% CI: 0.68–0.99), 0.75 (95% CI: 0.60–0.95), and 0.69 (95% CI: 0.51–0.93) for women with AFB of 21–23, 24–26, and 27–29Ìýyears, respectively. Furthermore, women with five or more pregnancies had a significantly higher prevalence of depression compared to those with two or fewer pregnancies (OR = 1.20, 95% CI: 1.01–1.42). RCS models demonstrated linear associations of ALB, gravidity and NLB with the prevalence of depression. Additionally, the RCS analysis revealed a roughly L-shaped relationship between AFB and prevalence of depression.

Conclusions

Women with later AFB are associated with a decreased prevalence of depression, while multiple pregnancies are associated with an increased prevalence of depression. These findings suggest that reproductive factors should be considered when screening for and developing preventive strategies for depression.

Introduction

Depression is one of the most common psychological disorders, a mental disorder typically characterized by persistent low mood and diminished interest, which has a high incidence. In recent years, the incidence of depression has been rising annually, affecting around 280 million people worldwide [1]. In women with depression, depressive episodes last longer and recur more frequently than in men [2]. Patients with depression are often at high risk of suicide, with 10% to 15% dying by suicide [3]. Depression-induced suicide is a crucial factor affecting family and social stability. Elucidating the pathogenesis of depression is the focus and difficulty of current research. Female reproductive factors have received increasing attention in recent years [4,5,6,7].

There is growing evidence of a relationship between fertility patterns and women's health. For example, studies on the relationship between parity and depression have been inconsistent, with more births detrimental to physical health in some studies and no relationship observed in others [8, 9]. Some studies have shown that later childbearing is associated with lower mortality [9] and better cognitive performance in women [10]. As social development progresses, further attention still needs to be paid to the impact of reproductive factors on women's physical and mental health. Some studies have shown that the relationship between depression and age at first birth (AFB) is U-shaped among females [11]. But others have shown a negative relationship between AFB and major depressive disorderÌý[6]. Given the controversial findings of current research and the limited number of epidemiological studies within the US adult population, this study utilized data from the National Health and Nutrition Examination Survey (NHANES) to explore the association between reproductive factors and the prevalence of depression among adult women in the US.

Material and methods

Study population

NHANES, organized by the National Center for Health Statistics (NCHS) and the Centers for Disease Control and Prevention, is a continuous, systematic collection and analysis of health-related data (). The NHANES sample was collected every two years through a sophisticated, multistage sampling methodology to ensure accurate representation of the civilian, non-institutional population of the US. Data collected included demographic, dietary, laboratory, examination, and questionnaire information. This study utilized data from seven NHANES survey cycles: 2005–2006, 2007–2008, 2009–2010, 2011–2012, 2013–2014, 2015–2016, and 2016–2018. A total of 35,481 female individuals were included, and 16,945 women were excluded due to incompleteness of the Patient Health Questionnaire (PHQ-9). In addition, 7,048 women were excluded due to a lack of female reproductive factors, including AFB (n = 6,867), age at last birth (ALB) (n = 173), gravidity (n = 2), and number of live births (NLB) (n = 6). Finally, 11,488 women were included in the analysis (Fig.Ìý1).

Fig.Ìý1

Study flow chart. Abbreviations: NHANES, National Health and Nutrition Examination Surveys; PHQ-9, Patient Health Questionnaire-9

Reproductive factors

Information on female reproductive factors was collected through the Reproductive Health Questionnaire, which included questions on pregnancy history, use of hormone replacement therapy, menstrual history, and other relevant reproductive conditions. Data on the AFB, ALB, gravidity, and NLB (count the total deliveries, not the number of live-born children), were gathered from self-reported questionnaires. The researchers also collected participants' menstrual age, oral contraceptive use and female hormone use and history of gynecological surgery (including oophorectomy and hysterectomy).

Covariates

The covariates included in this study were age, race, family income to poverty ratio (PIR), education level, marital status, hypertension, diabetes mellitus (DM), smoker, alcohol user, work activity, recreational activity, coronary heart disease (CHD), congestive heart failure (CHF), angina pectoris, heart attack, stroke, body mass index (BMI), waist circumference (WC) [12,13,14,15,16,17,18]. Detailed information on covariates can be found in the NHANES database ().

Depression ascertainment

Depression diagnoses were assessed using the PHQ-9 [19], a depression screening tool that is a commonly used depression assessment tool in clinical settings. Each question on the PHQ-9 has four options, where 0 = not at all; 1 = a few days; 2 = more than half the days and 3 = almost every day. A score of 10 or higher on the scale indicates depression, with a maximum total score of 27 points [20, 21]. Trained interviewers conducted the Reproductive Health Questionnaire and the PHQ-9 as part of the Mobile Examination Center (MEC) private interview, utilizing the Computer-Assisted Personal Interviewing (CAPI) system.

Statistical analysis

All NHANES estimations relied on sample weights computed as outlined in [22], with the ‘survey’ package used for these calculations [12]. Continuous variables were expressed as mean ± standard deviation, and categorical variables were reported as frequencies (%). Differences between groups were analyzed using weighted t-tests for continuous variables and chi-square tests for categorical variables. In the present study, the variable with the largest proportion of missing values among all variables has a proportion of missing values of 9.4% (1,080 of 11,488) (Supplementary TableÌý1). Weighted multivariable logistic regression analyses were conducted to investigate the associations of AFB, ALB, gravidity and NLB with depression. In Model 1, adjustments were made for age and race/ethnicity. Model 2 incorporated additional adjustments for education level, smoking, alcohol consumption, marital status, family PIR, hypertension, and DM. Model 3 built upon Model 2 by including further adjustments for work and recreational activities, CHF, heart attack, CHD, oral contraceptive use, stroke, hormone therapy, age at menarche, hysterectomy, angina pectoris, bilateral oophorectomy, BMI, and WC [12,13,14]. Restricted cubic splines (RCS) were used to model nonlinear relationships between independent and dependent variables. To achieve an optimal balance between model fit and overfitting for the primary splines of AFB, ALB, gravidity, and NLB, the number of knots, ranging from three to seven, was selected based on the minimum Akaike Information Criterion (AIC) value, but if within two of each other for different knots, the lowest number of knots was chosen [23]. Accordingly, three knots were used to examine the relationship between female reproductive factors and depression prevalence in this study. Subgroup analyses were subsequently conducted to evaluate whether age, race, age at menarche, hysterectomy, or use of female hormones affected the association of AFB, ALB, gravidity and NLB with depression, based on model 3. Statistical analysis was performed using SPSS version 22.0 and R version 4.2.0, with a P-value < 0.05 considered statistically significant.

Results

Baseline characteristics

Of the 11,488 participants, 11.6% (1,332) had depression. Individuals with depression were significantly younger than those without depression (P < 0.001). In addition, age at menarche, AFB, and ALB were significantly lower in those with depression than those without depression (P < 0.001). Table 1 shows the baseline characteristics of the study population. Finally, we also performed the multiple imputation on the missing independent and dependent variables and compared the characteristics of the populations between depression and non-depression in Supplementary TableÌý2.

Table 1 Demographic characteristics of the study participants

Association of AFB, ALB, gravidity and NLB with depression

AFB was categorized into the following age groups: < 18, 18–20, 21–23, 24–26, 27–29, 30–32, 33–35, and ≥ 36Ìýyears. Weighted multivariable logistic regression analysis indicated that participants with an AFB of ≥ 18Ìýyears had a significantly lower prevalence of depression compared to those with an AFB of < 18Ìýyears (Model 1). Further adjustment for confounding factors significantly weakened the observed associations, particularly among participants with AFB of 30–32 and ≥ 36Ìýyears (Model 2). After additional adjustments, participants with AFB of 21–23, 24–26, and 27–29Ìýyears had a significantly lower prevalence of depression compared to those with AFB < 18Ìýyears, with ORs of 0.83 (95% CI: 0.68, 0.99), 0.75 (95% CI: 0.60, 0.95), and 0.69 (95% CI: 0.51, 0.93), respectively (Model 3). In the analysis of ALB and depression, participants were grouped into ≤ 24, 25–29, 30–34, 35–39, and ≥ 40Ìýyears. Participants with an ALB > 24Ìýyears showed a significantly lower prevalence of depression compared to those with an ALB ≤ 24Ìýyears (Model 1). However, ALB was not significantly associated with depression in models 2 and 3 (TableÌý2). Additionally, participants were classified based on gravidity and number of live births into four categories: ≤ 2, 3, 4, and ≥ 5. In Models 1 and 2, women with ≥ 4 pregnancies had a higher prevalence of depression compared to those with ≤ 2 pregnancies. After additional adjustment for confounding variables, only women with ≥ 5 pregnancies showed a significantly increased prevalence of depression. In Model 1, a higher NLB was associated with a higher prevalence of depression. However, in Models 2 and 3, NLB was not significantly associated with depression (TableÌý3). The RCS fitted model was used to examine how the prevalence of depression changes with increasing AFB, ALB, gravidity, and NLB, while adjusting for covariates. The analysis revealed a roughly L-shaped relationship between AFB and depression (P for nonlinearity = 0.094, Fig.Ìý2A). Additionally, ALB, gravidity, and NLB also had linear relationships with depression prevalence (ALB, P for nonlinearity = 0.699, Fig.Ìý2B; gravidity, P for nonlinearity = 0.549, Fig.Ìý2C; NLB, P for nonlinearity = 0.953, Fig.Ìý2D).

Table 2 Associations of age at first birth, and age at last birth with the prevalence of depression

Table 3 Associations of gravidity and number of live births with the prevalence of depression

Fig.Ìý2

The RCS curve of the association of risk of (A) age at first birth, (B) age at last birth (C) gravidity and (D) number of live births and prevalence of depression. Abbreviation: RCS, restricted cubic spline

Subgroup analyses

Results varied across the prespecified subgroups of age, race, hysterectomy, use of female hormones, and age at menarche. In participants who were under 45Ìýyears of age, Non-Hispanic Black, had undergone hysterectomy, used hormonal treatments, and experienced earlier menarche, a stronger correlation between AFB and depression was identified (Supplementary TableÌý3). Moreover, statistically significant interactions were observed in most subgroups (P for trend < 0.05). The subgroup analysis of the relationship between ALB and depression indicated that an ALB of ≥ 40 years was linked to a lower prevalence of depression among Non-Hispanic White women, while a higher prevalence was observed in individuals of Other Race. Furthermore, an ALB of 25–29Ìýyears was associated with a higher prevalence of depression among participants with an age at menarche of 12–13Ìýyears (Supplementary TableÌý4). Among those who were used female hormones, and had a menarche age of 12–13Ìýyears, those with ≥ 5 pregnancies also showed an increased prevalence of depression (Supplementary TableÌý5). Furthermore, among participants who were Mexican American, Other Hispanic, and had an age at menarche of less than 12Ìýyears, a stronger correlation between NLB and depression was observed (Supplementary TableÌý6).

Discussion

This study revealed that women with the AFB of 21–23, 24–26, and 27–29Ìýyears had a significantly reduced prevalence of depression compared to those with the AFB of less than 18Ìýyears. Additionally, women with five or more pregnancies demonstrated a higher prevalence of depression relative to those with two or fewer pregnancies. RCS models indicated that ALB, gravidity, and NLB were linearly associated with depression prevalence, while the analysis revealed a roughly L-shaped relationship between AFB and depression.

Studies have shown that women's reproductive health status during pregnancy and childbirth is associated with their future prevalence of chronic diseases [12,13,14]. Several epidemiological studies have explored the relationship between female reproductive factors and depression, but these findings are not entirely consistent [24]. Mirowsky et al. reported a U-shaped association between AFB and depression, finding that women who had their first child before age 23 experienced more depressive symptoms compared to nulliparous women. Women who gave birth to their first child around age 30 showed the lowest risk of depression [5]. Furthermore, an Australian cross-sectional study found that women who had their first child at a younger age, particularly during adolescence, were more likely to experience mental health problems compared to women who were 25Ìýyears of age or older [25]. Both early and late AFB were associated with increased depressive symptoms, according to a study of US women [26]. Carlsson found that women who deviate from the expected age of their first child, whether occurring too early or too late, are associated with a higher likelihood of experiencing depressive symptoms in midlife [27]. The RCS analysis of this study revealed a trend of decreasing depression prevalence with increasing AFB, indicating a correlation between a lower prevalence of depression and later childbearing. Additionally, a two-sample Mendelian randomization study identified an association between earlier AFB and an increased risk of major depressive disorder [28]. McMahon et al. concluded that older parents have psychological advantages over younger parents because they are more resilient and have fewer depressive symptoms during pregnancy [29]. Similarly, a Finnish study found that the prevalence of depression in both men and women is associated with a younger age at first birth, irrespective of the participant's educational attainment [30]. However, Kallier's research revealed that teenage mothers who gave birth out of wedlock exhibited higher depressive symptoms compared to married women who had their first child in adulthood, suggesting that marital status at first childbirth may be a more critical factor [31]. The inconsistencies between these findings and our study could be due to variations in age, sample size, and region of study participants among the studies. The relationship between ALB and depression has been less studied. With the implementation of China’s "three-child" policy and advancements in reproductive medicine, an increasing number of women are choosing to get pregnant again. Research involving long-lived families has demonstrated that later ALB is associated with improved cognitive function [10]. Muraca et al. found that women who gave birth at an advanced age were significantly more likely to suffer from depression compared to those who had children at a younger age [32]. Several studies have shown that multiple births increase women's risk of metabolic syndrome, obesity [33], and cardiovascular disease [34]. This study also found an association between a higher number of pregnancies and an increased prevalence of depression. However, after adjusting for potential confounders, the association between NLB and depression prevalence became less significant. In China, a study revealed that depression levels increased with the NLB among older individuals, with older women exhibiting higher levels of depression compared to men [35]. Li et al. found that a higher number of full-term and incomplete pregnancies is associated with an increased prevalence of depressive symptoms in postmenopausal women [36]. This may be attributed to lower plasma estrogen levels in parous women compared to nulliparous women, as endogenous estrogen is thought to have a protective effect against depressive symptoms [37,38,39]. Additionally, abortion can adversely affect women's mental health, with higher rates of depression observed among women who have undergone the procedure [40]. A study conducted in Ethiopia indicated a direct and indirect positive association between more pregnancies and postpartum anxiety and depression in women, while higher births had a direct and indirect negative association [41]. Further investigation is necessary to elucidate the effects of gravidity and NLB on depression in women. Subgroup analyses indicate that menopausal women have an increased prevalence of depression, consistent with previous research [42]. This increased prevalence may be due to a combination of hormonal, genetic, and environmental factors. Depression in women is most common during perimenopause and the low estrogen phase of the menstrual cycle. During these periods, decreased estrogen levels lead to dysfunction of the hypothalamic–pituitary–adrenal (HPA) axis, resulting in impaired emotional and cognitive functioning, significant reductions in hippocampal volume and activity, and an increased risk of depression [2]. Evidence indicates that lower serum estradiol and estrone levels are associated with higher anxiety and depression scores in older postmenopausal women [43]. Furthermore, studies have shown that estradiol treatment is more effective than placebo in alleviating major depression in perimenopausal women [44, 45]. Thus, it is crucial to improve depression screening among menopausal women [42].

Our study's primary strengths include its large sample size and national representativeness, which enhance the generalizability of the results to similar populations. Additionally, the study accounted for various factors and adjusted for covariates, thereby strengthening the robustness of our findings. Moreover, the study provides guidance for future research, emphasizing the need to consider reproductive factors in depression screening and the necessity of further investigation to confirm any causal relationship between female reproductive factors and depression. However, the study has limitations. Firstly, the data used in this study were obtained from a cross-sectional survey, which limits the ability to establish a causal relationship between female reproductive factors and depression. Secondly, our analysis examined only the overall effect of gravidity on depression prevalence without differentiating between the impacts of complete and incomplete pregnancies. Lastly, this study used a substantial amount of survey data, which may contain biases inherent in self-reported information.

Conclusion

This study utilized data from the NHANES database spanning 2005 to 2018. Following the selection criteria application, the final sample included 11,488 participants. Our findings showed that later AFB is associated with a lower prevalence of depression in women, whereas having five or more pregnancies is associated with a higher prevalence of depression in women. Therefore, when evaluating a woman's risk of depression, physicians should also consider reproductive factors.