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. 2025 Jan 21;30(1):e12768. doi: 10.1111/bjhp.12768

The association between depressive symptoms and lower urinary tract symptoms and impact among women: Investigating behavioural, cognitive and physiological pathways

Sonya S Brady 1,✉, Andrés Arguedas 2, Jared D Huling 2, Gerhard Hellemann 3, David R Jacobs Jr 4, Cora E Lewis 5, Cynthia S Fok 6, Pamela J Schreiner 4, Stephen K Van Den Eeden 7,8, Alayne D Markland 9
PMCID: PMC11751663  NIHMSID: NIHMS2037551  PMID: 39838806

Abstract

Objective

Mechanistic studies are needed to understand why depressive symptoms are associated with poorer physical health. The objective of this study was to examine whether behavioural, cognitive and physiological factors mediated an association between depressive symptoms, measured in early adulthood, and lower urinary tract symptoms (LUTS) and their impact, a composite variable measured in mid‐life adulthood, among women in the Coronary Artery Risk Development in Young Adults study, conducted in four regions of the United States.

Design

Prospective cohort study.

Methods

Data were examined for 871 women. Depressive symptoms were measured and averaged across Years 5, 10 and 15. Year 20 health behaviour combined information about smoking, physical activity and diet. Year 25 cognitive function combined performance on different cognitive tests. Year 25 metabolic syndrome combined standard risk criteria for waist circumference, triglycerides, high‐density lipoprotein, blood pressure and glucose. A cluster analysis of urinary incontinence, other LUTS and impact data—collected two years after Year 25—was used to group women into one of four categories: no or very mild symptoms with no impact (bladder health) versus mild, moderate or severe symptoms/impact.

Results

Structural equation modelling showed a statistically significant direct path between depressive symptoms and LUTS/impact. Tests of indirect paths showed that health behaviours, cognitive function and metabolic syndrome did not mediate the association between depressive symptoms and LUTS/impact.

Conclusions

Depressive symptoms in early adulthood appear to be associated with LUTS and their impact in mid‐life adulthood over and above health behaviours, cognitive function and metabolic syndrome.

Keywords: bladder health, cognitive function, depressive symptoms, health behaviours, lower urinary tract symptoms, metabolic syndrome

INTRODUCTION

Lower urinary tract symptoms (LUTS) include urinary incontinence (UI), frequent and/or urgent urination, nocturia (i.e., waking at night to urinate) and problems with bladder emptying (Haylen et al., 2010). LUTS are common among women (Milsom & Gyhagen, 2019). For example, ~32% of women aged 40 or older in the United States, United Kingdom and Sweden report at least sometimes experiencing stress UI (i.e., loss of urine with activities such as laughing, sneezing or coughing) and over 24% report at least sometimes experiencing urgency UI (i.e., losing urine before reaching a toilet after a strong urge to urinate) (Coyne et al., 2009). Over a third of women report at least sometimes waking at night to urinate two or more times (Coyne et al., 2009). Impact of LUTS on quality of life (QoL) and well‐being is an important component of health. LUTS are related to reduced QoL and more symptoms of depression, particularly among those who experience bother or functional loss due to LUTS (e.g. avoiding travel, physical activities or social activities) (Coyne et al., 2013; Felde et al., 2017; Milsom et al., 2012; Ragins et al., 2008).

Depressive symptoms may not only be a consequence of LUTS but also a risk factor for LUTS. Self‐reported depressive symptoms are prospectively associated with self‐reported incident UI in studies that have followed women across 6–18 years (Felde et al., 2017; Legendre et al., 2015, 2020; Melville et al., 2009; Mishra et al., 2015). Other longitudinal studies of women have shown that depressive symptoms can be associated with maintenance or worsening of existing LUTS, as opposed to incidence (Bradley et al., 2014; Liu et al., 2019; Maserejian et al., 2014). Behavioural, cognitive and physiological factors may conceivably mediate an association between depressive symptoms and poorer bladder health among women. Depressive symptoms are associated with poorer health behaviours (Wang et al., 2021), poorer cognitive functioning (Cooper et al., 2015) and metabolic syndrome (Pan et al., 2012). Poorer health behaviours (Choo et al., 2015), poorer cognitive functioning (Hatta et al., 2011; Lussier et al., 2013) and metabolic syndrome (Bunn et al., 2015) are also associated with LUTS.

The Coronary Artery Risk Development in Young Adults (CARDIA) study provides a unique opportunity to examine factors that may mediate an association between depressive symptoms and poorer bladder health among women. In a previous study of CARDIA women, depressive symptoms over 20 years, examined with different degrees of nuance (greater mean level of symptoms across 5 assessments, membership to a worse symptom trajectory group, greater individual‐level symptom intercept and slope), were consistently associated with a subsequently assessed composite measure of LUTS and impact (Brady et al., 2023). An unanswered question is whether specific mechanisms may account for the association between depressive symptoms and greater LUTS/impact among CARDIA women. The present study utilized CARDIA data to examine whether poorer health behaviours, poorer cognitive function and metabolic syndrome individually and collectively mediate the association between depressive symptoms and LUTS/impact among CARDIA women.

MATERIALS AND METHODS

Procedure

CARDIA is a prospective cohort study that recruited 5115 Black and White women and men aged 18–30 years at baseline (1985–86; Year 0) from the populations of four U.S. cities (Birmingham, AL, USA; Minneapolis, MN, USA; Chicago, IL, USA; Oakland, CA, USA). Details on study design have been previously reported (Friedman et al., 1988). In‐person follow‐up examinations were conducted 2, 5, 7, 10, 15, 20 and 25 years after baseline with response rates of 91%, 86%, 81%, 79%, 74%, 72% and 72% of the surviving cohort, respectively. Written informed consent was obtained at each examination and each centre's IRB approved the study protocols.

Following the Year 25 (2010–11) examination, an ancillary study about non‐cancerous genitourinary conditions collected data on LUTS and impact among CARDIA participants. Data were collected via questionnaire mailings between March, 2012 and February, 2013. Of the 1981 surviving CARDIA women available at the Year 25 examination, LUTS and impact questionnaires were completed by 1465 women (74.0%).

Measures

LUTS/impact cluster categories

The outcome variable was previously developed through a cluster analysis of four constructs: UI severity, UI impact, other LUTS severity and other LUTS impact (Markland et al., 2021). UI severity was calculated by multiplying responses to questions assessing frequency and amount of urine leakage (Sandvik et al., 2000). UI impact on well‐being was assessed with the Incontinence Impact Questionnaire (IIQ) (Uebersax et al., 1995). Presence and severity of other LUTS were assessed with the American Urologic Association Symptom Index (AUASI) score, a composite of 7 individual LUTS (urgency, frequency, nocturia, incomplete emptying, hesitancy, intermittency and weak stream) (Barry et al., 2007, 2017; Scarpero et al., 2003). Impact of this LUTS composite on QoL was assessed with one question from the AUASI. Missing data rates for questionnaires were 2.1% for UI severity, 2.2% for UI impact, 4.8% for other LUTS severity and 3.7% for other LUTS impact. The cluster analysis, using UI and other LUTS severity/impact variables, yielded four LUTS/impact cluster categories: women who reported no or very mild symptoms of UI and other LUTS along with no impact (defined here as bladder health, the reference group) and mild, moderate or severe symptoms and impact. Among women with complete data (n = 1302), 44% (n = 569) were classified into the bladder health cluster compared to those classified into mild (31%, n = 407), moderate (20%, n = 259) and severe (5%, n = 67) symptoms/impact clusters (Markland et al., 2021). ‘More burdensome LUTS/impact’ was defined as membership to a more symptomatic LUTS category with greater impact.

Depressive symptoms at Years 5, 10 and 15

Depressive symptoms in the past week were assessed with the 20‐item Center for Epidemiologic Studies‐Depression Scale (CES‐D) (Radloff, 1977) at Years 5, 10 and 15. Response options for each item were ‘rarely or none of the time’ (0), ‘some of the time’ (1), ‘much of the time’ (2) and ‘most or all of the time’ (3); scores summed across items ranged from 0 to 60. A score of 16 points or more is the typical cut‐off for probable depression (Weissman et al., 1977); a score of 20 has more recently been recommended if a better balance between sensitivity and specificity is desired (Vilagut et al., 2016). Cronbach's alpha coefficient, an index of internal consistency, was high within each CES‐D assessment, ranging from .88 to .89. Correlations between CES‐D scores across assessments ranged from .37 to .51. Scores were averaged across Years 5, 10 and 15; to be included in analyses, participants needed to have completed at least 2 of 3 assessments.

Health behaviour composite at Year 20

Health behaviours were examined at Year 20 because they may be influenced by previous depressive symptoms and in turn influence subsequent cognitive and metabolic function. Consistent with previous CARDIA studies (Markland et al., 2021; Reis et al., 2013; Whitaker et al., 2018), smoking, physical activity and diet were each categorized into poor (coded 0), intermediate (coded 1) and ideal (coded 2) categories. Participants were categorized as being a current smoker (poor), former smoker who quit ≤12 months prior (intermediate) or never smoker or former smoker who quit >12 months prior (ideal) using American Heart Association (AHA) criteria (Lloyd‐Jones et al., 2010). Physical activity was self‐reported as frequency of participation over the prior 12 months in vigorous and moderate intensity activities and reported as a score in exercise units using the validated CARDIA Physical Activity History (Jacobs et al., 1989). Participants were categorized as inactive (<100 exercise units, poor), active but not meeting guidelines (100–299 exercise units, intermediate) and meeting guidelines (≥300 exercise units, ideal) to approximate AHA criteria for physical activity (Lloyd‐Jones et al., 2010). A score of 300 exercise units is roughly equivalent to 150 min of moderate physical activities per week (e.g., five 30‐min sessions of walking; Gabriel et al., 2014). A detailed diet history was assessed via a validated interviewer‐administered questionnaire, described elsewhere (Choi et al., 2020; Liu et al., 1994). Participants with extreme energy intake (<800 or >8000 kcal/day for men and <600 or >6000 kcal/day for women) were set to missing. Dietary intake was assessed with five components used by the AHA to define a healthy diet: fruits and vegetables ≥4 servings/day, sodium <1500 mg/day, fish ≥7 ounces/week, whole grains ≥3 servings/day, sugar‐sweetened beverages <36 oz/week (Lloyd‐Jones et al., 2010). Poor, intermediate and ideal diet was defined as 0–1, 2–3 and 4–5 components, respectively (Whitaker et al., 2018). An overall health behaviour composite score was calculated by summing Year 20 assessment scores for smoking, physical activity and diet behaviours, with a potential range of 0–6.

Cognitive function composite at year 25

At Year 25, cognitive function was assessed with the Digit Symbol Substitution Test (DSST), Rey Auditory Verbal Learning Test (RAVLT) and Stroop Test, inhibition condition. The DSST assesses visual motor speed, sustained attention and working memory (Wechsler, 1997). Scores for the DSST range from 0 to 133, with higher scores indicating better cognitive performance. The RAVLT test assesses the ability to memorize and retrieve words (verbal memory) after several presentations of a single word list, one after another and then after a delay of 10 min (Rosenberg et al., 1984). Analyses utilized the delayed RAVLT score (trial 7; score range 0–15), with higher scores indicating better performance. The Stroop inhibition condition evaluates the ability to view complex visual stimuli and to respond to one stimulus dimension while suppressing the response to another dimension, an executive skill largely attributed to frontal lobe function (Stroop, 1935; MacLeod, 1991). Analyses utilized the interference score of the Stroop Test with possible scores ranging from −160 to 160. Because a lower score indicates better performance, the interference score was reverse scored. Pearson's correlation coefficients between scores were as follows: DSST and RAVLT, r = .29; DSST and Stroop, r = .38; RAVLT and Stroop, r = .28. Consistent with previous CARDIA studies (Gerber et al., 2021; McEvoy et al., 2019), the DSST, RAVLT and Stroop scores were standardized to z scores and averaged; the resulting composite was standardized again so that the mean was 0 and standard deviation was 1.

Metabolic syndrome at year 25

Metabolic syndrome was defined as the presence of 3 or more of the following criteria from the Year 25 assessment: waist circumference ≥88 cm; triglycerides ≥150 mg/dL or drug treatment; HDL ≤50 mg/dL or drug treatment; SBP ≥130 mmHg, DBP ≥85 mmHg or drug treatment and fasting glucose ≥100 mg/dL or drug treatment (Grundy et al., 2005). Participants were assigned a score of 1 (presence of 3 or more criteria) or 0 (0, 1 or 2 criteria met).

Covariates

Covariates included age, race (Black versus White), education (high school or less, some college, college graduate), parity (one or more children versus none), menopausal status (yes versus no or unsure) and hysterectomy (yes versus no).

Analytic approach

The analytic sample was comprised of women with complete data for predictor and outcome variables (n = 871). A complete case analysis was favoured over imputation due to the number of time points at which variables were taken for analyses. Differences between the analytic sample and those women who had data for the outcome variable, but not one or more predictor variables (n = 431), were examined.

Preliminary analyses examined distributions of predictor variables within the total analytic sample and by LUTS/impact cluster category. CARDIA recruited roughly equal numbers of Black and White participants, which facilitated the examination of potential health inequities; for this reason, standardized mean differences in study variables by race were also examined (Austin, 2011). To establish the plausibility of our proposed mediation model, proportional odds ordinal logistic regression analyses were conducted to examine the odds of having more symptomatic and burdensome LUTS/impact for each unit increment in mean depressive symptoms, the health behaviour composite, cognitive function composite and presence of metabolic syndrome. Each predictor variable was examined in relation to LUTS/impact cluster category individually, adjusting for covariates. The proportional odds assumption was tested and was not violated for these analyses. Next, structural equation modelling (SEM) was conducted to test the model depicted in Figure 1. A two‐stage limited information approach similar to that developed by Muthén was applied (Muthén, 1984). In the initial step, the polychoric correlation matrix was estimated (Olsson, 1979; Pearson & Heron, 1913); model parameters were estimated from the correlation matrix (Jöreskog, 1994). The results are broadly comparable with those from multinomial logistic regression analyses (Takane & de Leeuw, 1987). The model was saturated to avoid potential bias in parameter estimates due to model misspecification. The results for indirect effects were verified using a non‐parametric bootstrap, as indirect effects have asymmetrical distributions of the standard error (MacKinnon et al., 2004). Analyses were conducted using R version 4.3. SEM models were fit using the lavaan package in R.

FIGURE 1.

FIGURE 1

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Direct and indirect effects of depressive symptoms on 2012–13 (Post‐Year 25) LUTS/impact cluster group membership (4 levels) among CARDIA women (n = 871). The correlation between Year 25 cognitive function and metabolic syndrome was ρ = −.10; p < .01. *p < .05, **p < .01, ***p < .001.

RESULTS

Compared to the 431 women not in the analytic sample, women in the analytic sample did not differ by age (M = 50.3 versus M = 50.0 years), parity (28.9% versus 27.8% nulliparous) or hysterectomy (18.5% versus 17.9%) by Year 25; however, a greater percentage of women in the analytic sample compared to those omitted were White (58.0% versus 46.4%), college graduates (56.3% versus 44.3%) and in menopause (42.1% versus 35.4%) by Year 25 (p < .05). Compared to women not in the analytic sample, women in the analytic sample were less likely to be in the bladder health (42.9% versus 45.2%) and severe LUTS/impact (4.6% versus 6.3%) clusters, more likely to be in the mild LUTS/impact cluster (32.5% versus 28.8%) and similarly likely to be in the moderate LUTS/impact cluster (20.0% versus 19.7%) (p < .01).

Table 1 shows the distributions of predictor variables within the total sample and by LUTS/impact cluster category. Mean level of depressive symptoms across Years 5, 10 and 15 were progressively higher from the bladder health (M = 8.48) to severe LUTS/impact (M = 12.72) groups; scores above the CES‐D cutoff of 20 also were progressively higher across LUTS/impact groups. The health behaviour composite at the Year 20 assessment was highest among women subsequently assigned to the bladder health group (M = 3.49) and lowest among women subsequently assigned to the severe LUTS/impact group (M = 2.83). Cognitive function at the Year 25 assessment was better among women subsequently assigned to the bladder health group (M = .05) and worse among women subsequently assigned to the severe LUTS/impact group (M = −.42). The percentage of women who met criteria for metabolic syndrome at the Year 25 assessment was progressively higher from the bladder health (11.2%) to severe LUTS/impact (25.0%) groups.

TABLE 1.

Distributions of predictor variables within total sample and by 2012–13 (post‐year 25) LUTS/impact cluster categories among CARDIA women (n = 871).

Total sample 2012–13 LUTS/impact cluster categories a
Bladder health Mild LUTS/impact Moderate LUTS/impact Severe LUTS/impact
n = 871 n = 374 n = 283 n = 174 n = 40
M ± SD or n (%) M ± SD or n (%) M ± SD or n (%) M ± SD or n (%) M ± SD or n (%)
Depressive Symptoms, Mean across Years 5, 10, 15 b 9.79 ± 6.27 8.48 ± 5.41 9.84 ± 5.96 11.86 ± 7.41 12.72 ± 7.25
Average score of 20 or more, n (%) 66 (7.6%) 15 (4.0%) 19 (6.7%) 25 (14.4%) 7 (17.5%)
Health Behaviour Composite, Year 20 (0–6) c 3.35 ± 1.33 3.49 ± 1.29 3.26 ± 1.31 3.32 ± 1.33 2.83 ± 1.69
Smoking (0–2) 1.46 ± .75 1.51 ± .72 1.45 ± .74 1.43 ± .75 1.15 ± .92
Physical Activity (0–2) 1.18 ± .78 1.23 ± .77 1.12 ± .79 1.22 ± .76 1.07 ± .76
Diet (0–2) .71 ± .54 .75 ± .53 .69 ± .53 .67 ± .56 .60 ± .63
Cognitive Function Composite, Year 25 (mean = 0, SD = 1) .00 ± 1.00 .05 ± 1.05 .01 ± 1.02 −.02 ± .86 −.42 ± .90
Metabolic Syndrome, Year 25, n (%) 125 (14.4%) 42 (11.2%) 41 (14.5%) 32 (18.4%) 10 (25.0%)
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a

The outcome variable is based on women's self‐reported LUTS and perceived impact of LUTS on well‐being and quality of life. Of 70 women who reported urinary leakage at least weekly, 5 (3%) were categorized into the bladder health group (i.e., no symptoms or no reported impact of symptoms); 41 (24%) were categorized into the mild LUTS/impact group; 86 (51%) were categorized into the moderate LUTS/impact group and 38 (22%) were categorized into the severe LUTS/impact group.

b

Years 5, 10 and 15 correspond to 1990–91, 1995–96 and 2000–01.

c

For the health behaviour composite and all behaviours, higher scores correspond to greater engagement in health behaviours.

Black and White CARDIA women did not differ with respect to their assignment to LUTS/impact cluster group in 2012–13 (post‐Year 25 assessment) (Table 2). In comparison to Black women, White women had fewer depressive symptoms across Years 5, 10 and 15, better health behaviours at Year 20, and better cognitive function at Year 25; a smaller percentage of White women met criteria for metabolic syndrome at Year 25, as well.

TABLE 2.

Distributions of study variables by race among CARDIA women (n = 871).

Race p‐value* Standardized mean difference a
Black (n = 366) White (n = 505)
M ± SD or n (%) M ± SD or n (%)
Depressive Symptoms, Mean across Years 5, 10, 15 b 11.59 ± 7.15 8.49 ± 5.18 <.001 .50
Health Behaviour Composite, Year 20 (0–6) b 2.96 ± 1.37 3.63 ± 1.23 <.001 .52
Cognitive Function Composite, Year 25 b −.55 ± .97 .40 ± .81 <.001 1.10
Metabolic Syndrome, Year 25 (1 versus 0) b 74 (20.22%) 51 (10.10%) <.001 .29
2012–13 (Post‐Year 25) LUTS/Impact Cluster Group
Bladder Health 162 (44.26%) 212 (41.98%) .32 .13
Mild LUTS/Impact 109 (29.78%) 174 (34.46%)
Moderate LUTS/Impact 74 (20.22%) 100 (19.80%)
Severe LUTS/Impact 21 (5.74%) 19 (3.76%)
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*

The p‐value is for the difference between means.

a

The standardized mean difference is the difference in means between Black and White women, scaled by the standard deviation of the difference in means. Values of .1 and above are considered meaningful (Austin, 2011).

b

Years 5, 10, 15, 20 and 25 correspond to 1990–91, 1995–96, 2000–01, 2005–06 and 2010–11.

Table 3 shows associations between each predictor variable, entered into an ordinal logistic regression analysis individually, and membership to a more burdensome LUTS/impact cluster group, adjusting for race and other covariates. Each 1‐unit increment in mean CES‐D score during young adulthood was associated with 4% greater odds of membership to a more burdensome LUTS/impact group. Each 1‐unit increment in the health behaviour composite, which could range from 0 to 6, was associated with 7% lower odds of membership to a more burdensome LUTS/impact group. A one standard deviation increment in the cognitive function composite was associated with 9% lower odds of membership to a more burdensome LUTS/impact group. Meeting criteria for metabolic syndrome was associated with 32% greater odds of membership to a more burdensome LUTS/impact group.

TABLE 3.

Associations between predictor variables and 2012–13 (Post‐Year 25) LUTS/impact cluster category membership among CARDIA women (n = 871).

Proportional odds a
OR 95% CI
Covariates (Mutually adjusted and included in all subsequent models)
Age 1.00 (0.97–1.02)
Race (Black vs. White) 0.96 (0.81–1.13)
Education (vs college graduates)
High School or Less 1.20 (0.96–1.50)
Some College 0.97 (0.81–1.17)
Parity (1 or more versus 0) 1.32 (1.11–1.57)
Menopausal status (yes versus no/unsure) 1.06 (0.89–1.27)
Hysterectomy (yes versus no) 1.09 (0.90–1.33)
Study Variables, Entered Individually b
Depressive Symptoms (CES‐D score) 1.04 (1.03–1.06)
Health Behaviour Composite 0.93 (0.87–0.99)
Cognitive Function 0.91 (0.833–0.998)
Metabolic Syndrome 1.32 (1.07–1.63)
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a

The proportional odds assumption was tested and not violated for all models.

b

Proportional odds are shown for a 1‐unit increment in each variable.

Figure 1 shows the results of structural equation modelling (SEM). The direct path between depressive symptoms, averaged across Year 5, 10 and 15 CARDIA assessments, and LUTS/impact, assessed post‐Year 25, was significant. Indirect paths in Figure 1 show significant associations between depressive symptoms and worse health behaviours at Year 20, worse cognitive function at Year 25 and metabolic syndrome at Year 25. In addition, paths showed associations between health behaviours at Year 20 and both better cognitive function at Year 25 and lower likelihood of metabolic syndrome at Year 25. Year 20 health behaviours, Year 25 cognitive function and Year 25 metabolic syndrome were not associated with LUTS/impact in the SEM. Multi‐stage mediation tests of indirect paths between depressive symptoms and LUTS/impact were non‐significant (Table 4), indicating that the association between depressive symptoms and LUTS/impact cluster could not be explained by the health behaviour composite, cognitive function composite or metabolic syndrome.

TABLE 4.

Multi‐stage mediation tests of indirect paths from depressive symptoms to 2012–13 (post‐year 25) LUTS/impact cluster group membership (n = 871).

Indirect path Calculation from SEM path coefficients Estimate 95% CI
Health Behaviour Composite −.17 × −.06 .010 (−.004–.024)
Cognitive Function (−.21 + (−.17 × .22)) × .00 .000 (−.019–.018)
Metabolic Syndrome (.10 + (−.17 × −.13)) × .07 .009 (−.002–.019)
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Supplemental analyses explored whether the addition of a health behaviour composite score in early adulthood (averaging across Years 5, 10 and 15, with the requirement that participants completed at least 2 of the 3 assessments) changed the pattern of results in the structural equation model. In Figure S1, links were added between health behaviours during early adulthood and depressive symptoms during early adulthood, as well as health behaviours during early adulthood and health behaviours at Year 20. All other links in the structural equation model remained the same as that shown in Figure 1. Table S1 shows multi‐stage mediation tests of indirect paths from depressive symptoms to 2012–13 (post‐year 25) LUTS/impact cluster group membership, adjusting for health behaviours in early adulthood. The same pattern of results was observed in the revised structural equation model. Health behaviours at Year 20, cognitive function at Year 25 and metabolic syndrome at Year 25 did not mediate the association between depressive symptoms in early adulthood and LUTS/impact post‐Year 25.

DISCUSSION

The purpose of the present study was to examine whether behavioural, cognitive and physiological factors appeared to explain the association between depressive symptoms and LUTS/impact among women in the CARDIA cohort study. Mean level of depressive symptoms, assessed three times across a 10‐year period during early adulthood, was associated with more burdensome LUTS/impact when assessed over 10 years later during midlife adulthood. Contrary to hypothesis, health behaviours, cognitive function and metabolic syndrome during intervening years did not mediate the association between depressive symptoms and LUTS/impact. The health behaviour, cognitive function and metabolic syndrome variables may have been individually associated with LUTS/impact in logistic regression analyses (Table 3) because they were each associated with depressive symptoms during early adulthood (Figure 1). When predictor variables are associated and included together in an analysis, adjusting for one variable can eliminate associations between one or more other variables and an outcome. Figure 1 shows that when depressive symptoms in early adulthood were adjusted for, associations of health behaviour, cognitive function and metabolic syndrome in midlife adulthood with subsequent LUTS/impact were not significant. Health behaviour, cognitive function and metabolic syndrome in midlife adulthood did not explain variance in LUTS/impact beyond what depressive symptoms in early adulthood could explain. Our findings are consistent with several longitudinal studies that have shown self‐reported depressive symptoms to be prospectively associated with incident UI (Felde et al., 2017; Legendre et al., 2015, 2020; Melville et al., 2009; Mishra et al., 2015) or the maintenance or worsening of existing LUTS (Bradley et al., 2014; Liu et al., 2019; Maserejian et al., 2014).

Additional research is needed to ‘unpack’ the association between depressive symptoms and LUTS and their impact. Potential explanatory mechanisms include those that were the focus of the present study. It is possible that health behaviours, cognitive function and metabolic syndrome may explain an association between depressive symptoms in early adulthood and LUTS and their impact in older adulthood when these variables and/or LUTS and impact are measured at later ages. In the present study, women were between the ages of 37–55 at Year 20 when health behaviours were assessed and between the ages of 42–59 at Year 25 when cognitive function and metabolic syndrome were assessed; LUTS and impact were assessed two years later. Other potential mechanisms may include dysregulation of stress responsivity, neurotransmitter function and inflammatory processes; changes to toileting habits and the impact of depressive symptoms on other health conditions that may in turn impact LUTS/impact (de Groat, 2002; Grover et al., 2011; Jang et al., 2014; Klausner et al., 2005). Understanding the mechanisms by which depressive symptoms are associated with LUTS and their impact may aid health care providers in selecting treatments that prevent LUTS, their maintenance or worsening impact over time. A better understanding of mechanisms may also aid in the treatment of comorbid depressive symptoms and LUTS.

Study limitations and strengths

Because CARDIA was originally designed to understand the aetiology of cardiovascular disease, LUTS and impact were not assessed until after the Year 25 assessment. This prevented the examination of incident LUTS or change in LUTS/impact over time. Up to 4% of women between the ages of 20 and 29 in two population‐based Swedish samples were found to experience weekly UI (Milsom & Gyhagen, 2019). It is conceivable that some women in the CARDIA cohort experienced LUTS earlier in their lives, developed depressive symptoms as a result of LUTS impact on QoL and then maintained or experienced a worsening of LUTS. In this scenario, some of the variance in LUTS/impact attributed to depressive symptoms in the present study could instead be attributed to early, unmeasured LUTS/impact.

The present study did not examine individual LUTS, instead examining women whose symptoms and impact were categorized into clusters based on validated symptom severity scales to enhance clinical relevance of findings, similar to other analyses (Andreev et al., 2018; Markland et al., 2021). Findings did not take into account adaptive behaviours to accommodate bladder symptoms (e.g., fluid restriction, urge suppression, voiding without urgency or use of absorbent products), which may affect perceived symptom impact. In addition, the present study did not account for prior or current treatment for psychiatric symptoms or LUTS. The findings also may not generalize to older adults and to all racial and ethnic groups.

Strengths of the present study include the assessment of LUTS and impact among a community‐based sample. The younger age of participants at the earliest assessment of depressive symptoms (23–35 years) may be viewed as an additional strength. Most studies that have examined the association between depressive symptoms and LUTS enrolled middle‐aged or older participants. The present study also examined different mechanisms that could plausibly explain an association between depressive symptoms and LUTS/impact.

CONCLUSION

Additional mechanistic studies are needed to better understand why depressive symptoms are associated with LUTS and their impact. Such research may aid health care providers in preventing and treating LUTS, as well as treating comorbid depressive symptoms and LUTS.

AUTHOR CONTRIBUTIONS

Sonya S. Brady: Conceptualization; writing – original draft; writing – review and editing; visualization; project administration; funding acquisition. Andrés Arguedas: Validation; software; formal analysis; writing – review and editing. Jared D. Huling: Methodology; supervision; writing – review and editing. Gerhard Hellemann: Methodology; formal analysis; visualization; writing – review and editing. David R. Jacobs Jr: Methodology; writing – review and editing. Cora E. Lewis: Conceptualization; investigation; writing – review and editing; funding acquisition. Cynthia S. Fok: Writing – review and editing. Pamela J. Schreiner: Writing – review and editing; funding acquisition. Stephen K. Van Den Eeden: Writing – review and editing; funding acquisition. Alayne D. Markland: Conceptualization; writing – review and editing; funding acquisition.

Supporting information

Data S1.

BJHP-30-0-s001.docx (36.2KB, docx)

ACKNOWLEDGEMENTS

The Coronary Artery Risk Development in Young Adults Study (CARDIA) is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the University of Alabama at Birmingham (75N92023D00002 and 75N92023D00005), Northwestern University (75N92023D00004), University of Minnesota (75N92023D00006) and Kaiser Foundation Research Institute (75N92023D00003). Data about benign genitourinary conditions were collected through the Adult Life Predictors of Genitourinary Disorders CARDIA ancillary study (DK084997/115‐9107‐01‐M1; PI: Van Den Eeden). Writing of this manuscript was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) through R01 DK125274 (MPIs: Brady and Markland) and the National Institute on Aging (NIA) through K24AG073586 (PI: Markland). This manuscript has been reviewed by CARDIA for scientific content. The authors are grateful to CARDIA participants and staff for their contributions to this research.

Brady, S. S. , Arguedas, A. , Huling, J. D. , Hellemann, G. , Jacobs, D. R. Jr , Lewis, C. E. , Fok, C. S. , Schreiner, P. J. , Van Den Eeden, S. K. , & Markland, A. D. (2025). The association between depressive symptoms and lower urinary tract symptoms and impact among women: Investigating behavioural, cognitive and physiological pathways. British Journal of Health Psychology, 30, e12768. 10.1111/bjhp.12768

DATA AVAILABILITY STATEMENT

CARDIA provides National Heart, Lung, and Blood Institute Data Repository datasets for exams and follow‐up contacts for which data collection has been completed for at least five years, as well as adjudicated morbid and mortal events. All CARDIA data are available on reasonable request through the CARDIA Coordinating Center. The CARDIA website (https://www.cardia.dopm.uab.edu/) provides study materials such as protocols, manuals of operation and data collection forms for each year. Syntax for analyses in the present manuscript is available upon request from the first author (ssbrady@umn.edu).

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Associated Data

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

Supplementary Materials

Data S1.

BJHP-30-0-s001.docx (36.2KB, docx)

Data Availability Statement

CARDIA provides National Heart, Lung, and Blood Institute Data Repository datasets for exams and follow‐up contacts for which data collection has been completed for at least five years, as well as adjudicated morbid and mortal events. All CARDIA data are available on reasonable request through the CARDIA Coordinating Center. The CARDIA website (https://www.cardia.dopm.uab.edu/) provides study materials such as protocols, manuals of operation and data collection forms for each year. Syntax for analyses in the present manuscript is available upon request from the first author (ssbrady@umn.edu).

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