Combined impact of nutritional and inflammatory status and depressive symptoms on mortality following hysterectomy

Background Hysterectomy is a common surgery for women, where nutrition, inflammation, and depression impact recovery. These factors are interconnected. Although previous studies have explored the changes in nutrition and inflammation after hysterectomy, there is still no reliable biomarker to predict adverse postoperative outcomes. Additionally, the role of depression in postoperative recovery should not be overlooked. This study aims to fill this gap by identifying the advanced lung cancer inflammation index (ALI) as a potential indicator of poor postoperative prognosis following hysterectomy. It also seeks to examine the combined effect of ALI and depression on postoperative mortality.

This study uses NHANES data (2005–2023) and employs multivariable Cox proportional hazards regression models, restricted cubic spline plots, subgroup analysis, threshold analysis, and mediation analysis to evaluate the independent and combined effects of ALI and PHQ-9 depression scores on postoperative mortality following hysterectomy.

Over 18 years, 620 all-cause and 150 cardiovascular-related deaths were recorded. Multivariable-adjusted analysis showed that high ALI was significantly linked to a lower risk of both all-cause and cardiovascular mortality. In contrast, women with PHQ-9 scores ≥ 10 had a significantly higher risk of death. Combined analysis showed that women with high ALI and no depression had the lowest mortality risk. Further analysis confirmed that ALI was negatively correlated with mortality, while depression scores increased the risk.

This study identifies ALI as a biomarker for poor postoperative prognosis and highlights the combined effects of nutrition, inflammation, and depression. Proper control of these factors reduces mortality risk post-hysterectomy.

Hysterectomy, Postoperative, The advanced lung cancer inflammation index (ALI), The Patient Health Questionnaire-9(PHQ-9), Nutrition, Inflammation, Depression, Mortality, NHANES Combined impact of nutritional and inflammatory status and depressive symptoms on mortality following hysterectomy Ying Yang1,2, Yazhou Liu1,2, Xiaohang Lu3, Wei Sun2, Haiyan Chen2 and Ning Wang4* Page 2 of 14 Yang et al. BMC Women's Health (2025) 25:478

Hysterectomy is a common and widely used procedure in gynecology, primarily performed to treat uterine fibroids, uterine cancer, uterine prolapse, and other severe gyne - cological conditions [ 1]. This procedure not only effec - tively alleviates or cures these conditions but also significantly improves patients’ quality of life, relieves symptoms, and restores normal function. However, despite its effectiveness in treating gynecological condi - tions, hysterectomy can lead to various long-term conse - quences, particularly affecting both physical and mental health. An increased risk of postoperative depression is a major concern [2]. The psychological stress from the sur- gery, along with hormonal changes and the loss of repro - ductive capacity, may significantly raise the incidence of depressive symptoms. Since the introduction of the term “post-hysterectomy syndrome” in the 1970 s, many stud - ies have shown that women who undergo hysterectomy are more likely to experience psychological issues such as insomnia, anxiety, and depression compared to those who do not undergo the procedure [3– 5]. Furthermore, the postoperative effects of surgery can have significant physiological impacts on the body [ 6], particularly in terms of immune function, nutrition, and inflammatory responses [ 7]. After hysterectomy, sev - eral factors, including hormonal imbalances, changes in metabolism, and alterations in gastrointestinal function, can affect the body’s nutritional status [8]. These changes may lead to deficiencies in essential nutrients, which, in turn, can increase systemic inflammation. Chronic inflammation is linked to the development of many non-communicable diseases, such as obesity-related metabolic syndrome, cardiovascular diseases, neurode - generative disorders, certain cancers, and even increased mortality [ 9– 12]. Therefore, the interaction between nutrition and inflammation in women after hysterectomy raises overall health risks and significantly increases mor- tality risk in this population. The relationship between depression and inflamma - tion is complex and multifaceted [ 13, 14]. Some epide - miological studies suggest that depression can affect inflammation levels, while other research indicates that inflammation may contribute to the development of depression [ 15, 16]. Furthermore, some researchers have proposed a bidirectional link between inflamma - tion and depression [ 17]. This relationship may worsen health issues in women after hysterectomy. Additionally, chronic inflammation linked to depression may impair immune function, increasing the risk of other comorbidi- ties [18, 19]. Although many studies have explored the links between depression, inflammation, and nutritional health, their combined impact on mortality in women after hysterec - tomy remains understudied. The challenges these women face extend beyond physical health to include mental health and nutrition, both of which require attention. This study aims to identify key indicators of inflamma - tion and nutrition while also examining how depressive states affect survival rates in this population. Addition - ally, we analyze the combined effects of inflammatory nutrition and depression on mortality risk. The goal is to provide new insights into long-term health outcomes and identify potential interventions to improve quality of life and survival.

Study design and data collection This study uses a retrospective cohort design and ana - lyzes data from NHANES collected between 2005 and 2023. NHANES is organized and managed by the National Center for Health Statistics (NCHS), which uses a nationally representative, stratified, multistage probability sampling method [ 20]. More details about the project are available on the website: h t t p : / / w w w . c d c . g o v / n c h s / n h a n e s. The database is maintained by NCHS, and all participants gave written informed consent. The study received approval from the NCHS Institutional Review Board (IRB). Since NHANES is a public database with anonymous data, no additional ethical approval or informed consent was needed for this study. It strictly followed the guidelines set by the relevant institutions and data administrators to protect the safety and privacy of participants. Study population and inclusion/exclusion criteria This study investigates women who have undergone hys - terectomy, with the cohort including both women who have had hysterectomy procedures and a general female population for comparison. The following inclusion and exclusion criteria were applied to ensure the validity and reliability of the study findings: Inclusion Criteria: (1) Women who have undergone hysterectomy. (2) Participants who have complete medi - cal and demographic data available for analysis, includ - ing depression questionnaire data and hematological test results. Exclusion Criteria: (1) Women with incomplete hyster- ectomy records, which prevent accurate classification of the surgical procedure performed. (2) Individuals miss - ing depression questionnaire data or whose depression status could not be determined. (3) Participants without available hematological test results, as these are essential for assessing inflammatory and nutritional status, both of which are key to our analysis. (4) Individuals lacking essential covariate data, which are necessary to control for confounding variables in our analyses. (5) Partici - pants without mortality data, as the primary outcome of interest is postoperative mortality risk. (6) Individuals for Page 3 of 14 Yang et al. BMC Women's Health (2025) 25:478 whom sample weights are unavailable, as the study uti - lizes survey data that requires appropriate weighting for accurate population representation. Definition of a hysterectomy Hysterectomy data were collected from the reproduc - tive health section of the NHANES questionnaire. These interviews took place at the Mobile Examination Center (MEC). Each participant’s hysterectomy status was deter- mined by their response to the question, “Have you ever had a hysterectomy, that is, the removal of your uterus?” (coded as RHD280). Participants who answered “yes” were classified as having had a hysterectomy. Assessment of depressive symptoms The Patient Health Questionnaire-9 (PHQ-9) was used to diagnose and assess the severity of depressive symp - toms in the hysterectomy population. The PHQ-9 con - tains nine questions, with each question scored from 0 to 3. This results in a total score ranging from 0 to 27. A higher score indicates more severe depressive symptoms. Based on the PHQ-9 scoring criteria, patients are catego - rized into three groups: no depression (0–4 points), mild depression (5–9 points), and moderate to severe depres - sion (≥ 10 points). Furthermore, extensive research on the validity of the PHQ-9 defines patients with a score of ≥ 10 as having clinically significant depression [21]. Measurement of ALI The hematological laboratory data for this study were obtained from the NHANES laboratory database. The complete blood count was performed using the Beckman Coulter method, while the white blood cell differential count was measured using flow cytometry. The advanced lung cancer inflammation index (ALI) was calculated by measuring serum albumin levels (Alb), neutrophil count, lymphocyte count, and body mass index (BMI). The for - mula used is: ALI = BMI × Alb/NLR [ 22]. All laboratory measurements were carried out in strict accordance with standardized certification procedures. Ascertainment of mortality The mortality rate of the follow-up population was deter- mined by linking NHANES data with the National Death Index (NDI) mortality file, which was publicly available until December 31, 2019. This linkage was performed using a probabilistic matching algorithm. The algorithm matches records from the two datasets based on the patient’s Social Security Number (SSN), name, date of birth, and other identifying information. In the event of death, the time between the NHANES examination and the subject’s death (in months) was recorded. Addition - ally, disease-specific mortality was classified using the International Statistical Classification of Diseases, 10th Revision (ICD-10). For this study, the NCHS classified deaths due to heart disease (codes 054–064) and all other causes (code 010) [23]. Covariates This study included independent risk factor covariates associated with women who had undergone hysterec - tomy. These covariates were selected based on previous research. The specific factors considered were age, race, income-to-poverty ratio, education level, BMI, smoking status, alcohol consumption, self-reported history of dia - betes, self-reported history of hypertension, and medica - tion use. Medication variables included female hormone use, antidepressants use and treatment for sleep disor - ders. The study aimed to minimize confounding bias. Trained interviewers collected demographic informa - tion, including age, race, income-to-poverty ratio, and education level, through household and sample popu - lation surveys using the Computer-Assisted Personal Interviewing (CAPI) system. Health technicians from MEC conducted physical measurements. BMI was calcu - lated as weight (in kilograms) divided by height squared (in meters). Smoking status was categorized based on participants’ responses to survey questions (SMQ020: whether they had ever smoked at least 100 cigarettes; SMQ040: current smoking status). The categories included never smok - ers, former smokers, and current smokers. Never smok - ers were defined as individuals who had never smoked 100 cigarettes in their lifetime and were not currently smoking. Current smokers were those who had smoked at least 100 cigarettes and continued to smoke. Former smokers were individuals who had smoked at least 100 cigarettes but had quit. Alcohol consumption was catego- rized based on self-reported drinking frequency. Catego - ries included heavy, moderate, light, and never drinkers. Heavy drinkers were those who consumed four or more drinks per day, while moderate drinkers consumed three or fewer drinks per day. Light drinkers had consumed alcohol previously but had fewer than 12 drinking occa - sions in the past year. Never drinkers were individuals who reported never having consumed alcohol. The diagnosis of diabetes and hypertension was con - firmed using both survey data and laboratory results to ensure accurate findings. Relevant survey questions included: “Has a doctor ever told you that you have dia - betes?” “Do you use insulin?” “Do you use oral hypo - glycemic agents?” The laboratory criteria for diabetes included fasting blood glucose levels ≥ 7.0 mmol/L, HbA1c ≥ 6.5%, and an oral glucose tolerance test (OGTT) with blood glucose ≥ 11.1 mmol/L. Similarly, the diagno - sis of hypertension was based on multiple blood pressure readings ≥ 130/80 mmHg or self-reported hypertension confirmed by a doctor. Page 4 of 14 Yang et al. BMC Women's Health (2025) 25:478 Medication use, including the use of female hormones, was identified through a self-reported question in the reproductive health questionnaire. The question asked, “Have you ever used female hormones such as estrogen and progesterone?” (coded as RHQ540). Information on the use of antidepressants was extracted from the NHANES prescription data file, as detailed in Supple - mentary Table 1. The status of sleep disorders was assessed using the SLQ060 and SLQ050 question modules from NHANES. The questions included: “Has a doctor or other health - care professional ever told you that you have a sleep disorder?” and “Have you ever reported any sleep prob - lems?” Individuals who answered “Yes” were classified as having a sleep disorder and were included in further anal- ysis. Additionally, the SLQ070 question module included self-reported symptoms of sleep disorders, such as sleep apnea, insomnia, and restless leg syndrome. Individuals who answered “Yes” to these questions were also classi - fied as having a sleep disorder. Statistical analysis To ensure the national representativeness of the sam - ple, we followed the NHANES weighting guidelines ( h t t p s : / / w w w . c d c . g o v / n c h s / n h a n e s / t u t o r i a l s / w e i g h t i n g . a s p x) and applied MEC weights in the sampling design. We used time-dependent receiver operating charac - teristic (timeROC) curves to identify the most effective nutrition/inflammation biomarker for ALI in NHANES. We also described the baseline characteristics of differ - ent levels of ALI and depressive symptoms. Continuous variables were expressed as weighted means ± standard errors, while categorical variables were presented as frequency and weighted proportions. To explore the relationship between ALI, depressive symptoms, and mortality, we performed multivariable Cox proportional hazards regression analysis. Model 2 adjusted for demo - graphic characteristics, while Model 3 controlled for all covariates. The results were quantified by hazard ratios (HR) and 95% confidence intervals (CIs). To examine the combined effects, we grouped participants by ALI and depressive symptoms. We then used multivariable Cox proportional hazards regression models, adjusting for the same set of covariates, to assess mortality risk. Additionally, we will conduct a threshold analysis to further explore the relationship between ALI, depressive symptoms, and mortality. The restricted cubic splines (RCS) method in Cox proportional hazards regression models will be used to describe the linear and nonlinear associations between ALI or PHQ-9 scores and mortal - ity. We also performed subgroup analyses to assess the impact of other potential factors on the relationship between ALI, depressive symptoms, and mortality, aim - ing to verify the robustness of the results. Finally, we conducted a mediation analysis to examine how ALI and PHQ-9 scores mediate the relationship between hyster - ectomy and mortality outcomes. All statistical tests were two-sided, with a significance level set at P < 0.05. Data analysis for this study was per - formed using IBM SPSS Statistics 25.0 and R version 4.4.1.

Between 2005 and 2023, a total of 97,683 participants were enrolled in NHANES. After excluding individu - als who did not meet the study criteria or lacked neces - sary data, the final cohort included 3,703 women who had undergone hysterectomy, with a mean age of 63 ± 12 years. The baseline characteristics for the hysterectomy subgroup are shown in Table 1. Additionally, 11,883 healthy female controls were included as a comparison group, primarily for subsequent mediation analysis. The healthy controls were not directly involved in the statisti- cal modeling of the hysterectomized subgroup. A detailed participant selection flowchart is provided in Supplemen- tary Fig. 1. In the tertile-based analysis of ALI, significant differences were observed across groups in variables such as age, race, hypertension, and BMI ( p < 0.05). Among the participants, 179 women were identified as having both high ALI and high PHQ-9 scores, which indicates a subgroup with elevated systemic inflammation and significant depressive symptoms. During the 18-year follow-up period, 620 all-cause deaths and 150 cardio - vascular-related deaths were recorded. Additionally, we compared the ability of ALI and common inflamma - tory biomarkers to predict mortality in hysterectomized patients using ROC curves. As shown in Fig. 1, ALI demonstrated superior predictive performance for both all-cause and cardiovascular mortality, providing a com - prehensive reflection of metabolic status. Proportional hazards regression analysis was con - ducted to examine the relationship between ALI, depressive symptoms, and mortality. After adjusting for covariates, when ALI was considered as a continu - ous variable, the results showed that ALI was negatively associated with both all-cause and cardiovascular mor - tality, with HRs of 0.51 (0.43, 0.59) and 0.51 (0.37, 0.69), respectively. Compared to low ALI levels, high ALI levels were linked to lower all-cause and cardiovascular mor - tality, with HRs of 0.46 (0.37, 0.58) and 0.45 (0.28, 0.71), respectively. These results suggest that higher ALI levels are independently associated with a reduced risk of both all-cause and cardiovascular mortality in patients who have undergone hysterectomy. In contrast, patients with PHQ-9 scores ≥ 10 had a higher risk of all-cause mortal - ity [HR, 1.48(1.14,1.93)] compared to those with PHQ-9 scores between 0 and 4 (Table 2). Page 5 of 14 Yang et al. BMC Women's Health (2025) 25:478 Table 1 Baseline characteristics of the study cohort Study variables Total (n = 3703) No. of participants by ALI P value Q1 6.70 (n = 1236) Age, years 63.28 ± 12.26 65.87 ± 13.25 63.15 ± 11.75 60.83 ± 11.18 < 0.001 Race < 0.001 Mexican 421 (11.37%) 113 (9.16%) 170 (13.78%) 138 (11.17%) Hispanic 319 (8.61%) 83 (6.73%) 110 (8.91%) 126 (10.20%) Non-Hispanic white 1878 (50.72%) 801 (64.91%) 640 (51.86%) 437 (35.38%) Non-Hispanic black 868 (23.44%) 165 (13.37%) 242 (19.61%) 461 (37.33%) Other/multiracial 217 (5.86%) 72 (5.83%) 72 (5.83%) 73 (5.91%) Education level, n (%) 0.628 Never attended high school 933 (25.20%) 301 (24.39%) 310 (25.12%) 322 (26.07%) High school and above 2770 (74.80%) 933 (75.61%) 924 (74.88%) 913 (73.93%) Poverty-to-income ratio, n (%) 0.073 Poor (≤ 1) 659 (17.80%) 224 (18.15%) 196 (15.88%) 239 (19.35%) Not poor (> 1) 3044 (82.20%) 1010 (81.85%) 1038 (84.12%) 996 (80.65%) Smoking status, n (%) 0.058 Never 71 (1.92%) 34 (2.76%) 23 (1.86%) 14 (1.13%) Former 2320 (62.65%) 763 (61.83%) 768 (62.24%) 789 (63.89%) Current smoker 1312 (35.43%) 437 (35.41%) 443 (35.90%) 432 (34.98%) Alcohol use, n (%) 0.665 Never 753 (20.33%) 257 (20.83%) 246 (19.94%) 250 (20.24%) Mild 686 (18.53%) 235 (19.04%) 220 (17.83%) 231 (18.70%) Moderate 2058 (55.58%) 664 (53.81%) 706 (57.21%) 688 (55.71%) Heavy 206 (5.56%) 78 (6.32%) 62 (5.02%) 66 (5.34%) Hypertension, n (%) 2272 (61.36%) 743 (60.21%) 735 (59.56%) 794 (64.29%) 0.033 Diabetes mellitus, n (%) 815 (22.01%) 272 (22.04%) 263 (21.31%) 280 (22.67%) 0.717 Hormone use, n (%) 1840 (49.69%) 638 (51.70%) 614 (49.76%) 588 (47.61%) 0.127 Antidepressants use, n (%) 146 (3.94%) 52 (4.21%) 54 (4.38%) 40 (3.24%) 0.288 BMI, kg/m2 30.65 ± 7.18 27.30 ± 5.80 30.90 ± 6.78 33.76 ± 7.36 < 0.001 Sleep disorders 1513 (40.86%) 520 (42.14%) 496 (40.19%) 497 (40.24%) 0.5 PHQ-9 score (%) 0.551 0–4 2450 (66.16%) 817 (66.21%) 808 (65.48%) 825 (66.80%) 5–9 746 (20.15%) 250 (20.26%) 264 (21.39%) 232 (18.79%) ≥ 10 507 (13.69%) 167 (13.53%) 162 (13.13%) 178 (14.41%) Abbreviations: ALI advanced lung cancer inflammation index, BMI body mass index, PHQ-9 score Patient Health Questionnaire-9 Fig. 1 The time-dependent ROC of inflammation and nutrition-relative indicators for diagnosing overall survival in US women after hysterectomy. Ab - breviations: ALI, advanced lung cancer inflammation index; SII, systemic immune-inflammation index; NLR, neutrophil-to-lymphocyte ratio; SIRI, systemic inflammatory response index Page 6 of 14 Yang et al. BMC Women's Health (2025) 25:478 In the combined analysis, these findings remained consistent after adjusting for various covariates (Models 2 and 3). Specifically, a higher ALI level combined with a lower PHQ-9 score was significantly associated with a reduced risk of all-cause mortality (Table 3). Compared to survivors with PHQ-9 scores ≥ 10 and low ALI levels, survivors with PHQ-9 scores < 10 and high ALI levels had a significantly lower risk of all-cause mortality, with an HR of 0.34(0.25,0.46). As shown in Fig. 2, after adjusting for multiple poten - tial confounding factors, the RCS analysis revealed a negative relationship between ALI and both all-cause and cardiovascular mortality. As ALI increased, the HRs for both all-cause and cardiovascular mortality significantly decreased. In contrast, the PHQ-9 score showed a posi - tive relationship with all-cause mortality and a U-shaped relationship with cardiovascular mortality (Fig. 3). To further explore this relationship, we performed a thresh - old analysis. The results showed a non-linear relation - ship between ALI and all-cause mortality. Specifically, when ALI was less than 6.76, the protective effect of ALI increased as its levels rose, with an HR of 0.42 (0.35– 0.51). In contrast, the relationship with cardiovascular mortality was consistently negative. The PHQ-9 score, however, showed a linear positive relationship with both all-cause and cardiovascular mortality (Table 4). Additionally, subgroup analyses examined the interac - tion between other factors and ALI/PHQ-9 scores in rela- tion to mortality (Figs. 4 and 5). The association between higher ALI levels and lower cardiovascular mortality was stronger in patients aged 65 to 85 years. No statistically significant interactions were found for other outcomes (all interaction p-values > 0.05). Finally, the mediation analysis revealed limited evidence for biological media - tion by ALI or PHQ-9 scores. While ALI exhibited a sta - tistically significant indirect effect for all-cause mortality in adjusted models (β = 0.001, 95% CI: 0.0005–0.002; P = 0.002), the effect size was clinically negligible, accom - panied by an implausible negative mediation propor - tion (PM = −33.2%). Depression scores (PHQ-9) showed no significant mediation for cardiovascular mortality (P = 0.052), with inconsistent effects for all-cause mor - tality. Collectively, these findings do not support ALI or depression as substantial mediators of the hysterectomy- mortality association (Table 5). Table 2 HRs (95% CI) for all-cause mortality and cardiovascular mortality among U.S. Patients who have undergone hysterectomy in NHANES (2005–2023) based on ALI and PHQ-9 scores Model1 Model2 Model3 HR (95% CI) p value HR (95% CI) p value HR (95% CI) p value All-cause mortality ALI Continuous data 0.36(0.31,0.42) < 0.0001 0.50(0.43,0.59) < 0.0001 0.51(0.43,0.59) < 0.0001 Quartiles Q1 Reference Reference Reference Q2 0.50(0.41,0.60) < 0.0001 0.63(0.52,0.76) < 0.0001 0.63(0.52,0.76) < 0.0001 Q3 0.33(0.27,0.41) < 0.0001 0.46(0.37,0.58) < 0.0001 0.46(0.37,0.58) < 0.0001 PHQ-9 score 0–4 Reference Reference Reference 5–9 1.11(0.91,1.35) 0.3194 1.31(1.08,1.61) 0.0074 1.24(1.01,1.52) 0.0385 ≥ 10 0.99(0.78,1.26) 0.953 1.77(1.38,2.26) < 0.0001 1.48(1.14,1.93) 0.0029 Cardiovascular mortality ALI Continuous data 0.36(0.27,0.48) < 0.0001 0.51(0.38,0.69) < 0.0001 0.51(0.37,0.69) < 0.0001 Quartiles Q1 Reference Reference Reference Q2 0.52(0.36,0.75) 0.0005 0.69(0.48,1.01) 0.0556 0.68(0.46,0.98) 0.0414 Q3 0.32(0.20,0.49) < 0.0001 0.44(0.28,0.70) 0.0005 0.45(0.28,0.71) 0.0006 PHQ-9 score 0–4 Reference Reference Reference 5–9 1.39(0.95,2.03) 0.0871 1.69(1.15,2.47) 0.0071 1.48(0.99,2.18) 0.0510 ≥ 10 0.88(0.52,1.49) 0.6308 1.70(0.99,2.90) 0.0527 1.32(0.75,2.32) 0.3282 Model 1: we did not adjust other covariant Model 2: we adjusted age and race Model 3 on ALI: we adjusted age, race, education, poverty-to-income ratio, hypertension, diabetes, alcohol use, smoking, hormone use, antidepressants use and sleep disorders Model 3 on Depression: we adjusted age, race, education, poverty-to-income ratio, hypertension, diabetes, alcohol use, smoking, hormone use, antidepressants use, BMI and sleep disorders Page 7 of 14 Yang et al. BMC Women's Health (2025) 25:478

In this study, we performed a retrospective cohort anal - ysis using a nationally representative sample to assess the impact of inflammation, nutritional status, and depressive symptoms on mortality after hysterectomy in women. The results indicated that patients with higher ALI levels and no depressive symptoms had a signifi - cantly lower risk of all-cause and cardiovascular mortal - ity compared to those with lower ALI levels or significant depressive symptoms. Previous research has demonstrated that hysterec - tomy is frequently associated with distressing symptoms. Approximately 70% of patients experience depression following the procedure, while about half report symp - toms such as headaches, dizziness, or insomnia—symp - toms that are less prevalent in individuals undergoing other types of surgery [ 3]. Hysterectomy not only affects women’s physical health but may also alter their sense of self-identity. Many patients no longer view themselves as complete women, which can negatively affect their Table 3 Combined association of ALI and PHQ-9 scores with all-cause mortality and cardiovascular mortality in patients who have undergone hysterectomy in the united states, NHANES, 2005–2023 Model1 Model2 Model3 Mortality outcome ALI HR (95% CI) p value HR (95% CI) p value HR (95% CI) p value All cause PHQ-9 score ≥ 10 Low Reference Reference Reference Intermediate 0.50(0.29,0.85) 0.0106 0.58(0.34,0.999) 0.0495 0.55(0.39,0.77) 0.0004 High 0.42(0.24,0.72) 0.0018 0.48(0.27,0.82) 0.008 0.41(0.28,0.60) < 0.0001 PHQ-9 score < 10 Low 1.08(0.78,1.52) 0.634 0.58(0.42,0.82) 0.002 0.70(0.55,0.89) 0.0039 Intermediate 0.54(0.38,0.76) 0.0005 0.38(0.26,0.53) < 0.0001 0.46(0.36,0.60) < 0.0001 High 0.35(0.24,0.50) < 0.0001 0.27(0.18,0.39) < 0.0001 0.34(0.25,0.46) < 0.0001 Cardiovascular PHQ-9 score ≥ 10 Low Reference Reference Reference Intermediate 0.69(0.22,2.17) 0.5239 0.94(0.30,3.00) 0.921 0.87(0.27,2.80) 0.8196 High 0.49(0.14,1.68) 0.2589 0.59(0.17,2.03) 0.403 0.61(0.18,2.11) 0.4395 PHQ-9 score < 10 Low 1.50(0.69,3.26) 0.3074 0.79(0.36,1.74) 0.5593 1.01(0.45,2.25) 0.9863 Intermediate 0.76(0.34,1.69) 0.4943 0.54(0.24,1.20) 0.1289 0.66(0.29,1.50) 0.3249 High 0.45(0.19,1.04) 0.0613 0.33(0.14,0.77) 0.0104 0.43(0.18,1.02) 0.0542 Model 1: we did not adjust other covariant Model 2: we adjusted age and race Model 3: we adjusted age, race, education, poverty-to-income ratio, hypertension, diabetes, alcohol use, smoking, hormone use, antidepressants use and sleep disorders Fig. 2 The association between ALI and all-cause and cardiovascular mortality in women after hysterectomy was adjusted for age, race, education, poverty-to-income ratio, hypertension, diabetes mellitus, alcohol consumption, smoking, hormone use, antidepressants use and sleep disorders. Shaded areas represent 95% CI Page 8 of 14 Yang et al. BMC Women's Health (2025) 25:478 self-confidence and self-esteem [24, 25]. Additionally, the sudden drop in estrogen levels after the surgery can have harmful effects on the neuroendocrine system, worsen - ing depressive symptoms [ 2]. Together, these physical and psychological factors contribute to greater mental health challenges for women after surgery. Depression is often linked with increased inflammation, including higher levels of pro-inflammatory cytokines and acute- phase proteins [ 26, 27]. This, in turn, raises the risk of cardiovascular diseases, diabetes, and death [ 28, 29]. Additionally, depression significantly affects patients’ quality of life, impairing disease management, health monitoring, and treatment adherence [30, 31]. These fac- tors contribute to the progression of disease and a higher risk of death. In our study, about 13.69% of women who underwent hysterectomy showed elevated depressive symptoms based on PHQ-9 scores. Women with PHQ-9 scores between 0 and 4 had a 48% lower risk of all-cause mortality compared to those with scores above 10. Our findings suggest that depression may increase the risk of mortality [32]. A review of the literature on nutrition, inflammation, and mortality emphasizes the role of chronic inflamma - tion and the influence of diet on the immune system. Chronic inflammation is considered a key factor in the development of various chronic diseases [ 33– 35], as it increases the risk of mortality through mechanisms such as immune dysfunction and exacerbation of meta - bolic disorders. In women after hysterectomy, these effects are particularly complex and pronounced. Previ - ous studies have shown that reduced ovarian blood sup - ply following hysterectomy leads to a decline in ovarian hormone secretion, which further decreases blood flow to the ovaries, creating a vicious cycle [ 36]. The decline in ovarian function and hormonal fluctuations can also cause changes in the immune system, leading to higher levels of chronic inflammation [ 37]. Furthermore, Diet is closely linked to the immune system. A balanced diet enhances immune responses, regulates inflammation, and modulates oxidative stress processes [38– 43]. On the other hand, an unbalanced diet can trigger inflammatory responses in the body [ 44, 45], weaken immune func - tion, and disrupt various physiological processes, such as hormone regulation [ 46], metabolism [ 47, 48], circadian rhythms [49], and nutrient utilization [50]. In summary, women undergoing hysterectomy often experience multiple comorbidities, including metabolic disorders, inflammatory responses, immune deficiencies, and malnutrition. Therefore, a comprehensive assessment of nutritional status and inflammation-related markers is essential [ 51]. Unlike traditional inflammatory markers, the ALI score integrates both nutritional and inflam - matory factors, offering a more complete evaluation of overall health. As shown in our analysis (Fig. 2), its area under the curve (AUC) is relatively high, indicating that it is more reliable than other markers in predicting post - operative outcomes. Previous research has emphasized the importance of predictive biomarkers, particularly in enhancing perioperative safety, which is crucial, espe - cially in the context of oncological hysterectomy [ 52, 53]. Initially, the ALI score was used to assess the systemic inflammatory response in patients with metastatic non- small cell lung cancer (NSCLC), and it has since proven to be an effective predictive marker for adverse events in Fig. 3 Association between depression index and all-cause and cardiovascular mortality in women after hysterectomy adjusted for age, race, education, poverty-to-income ratio, BMI, hypertension, diabetes mellitus, alcohol consumption, cigarette smoking, hormone use, antidepressants use and sleep disorders. Shaded areas represent 95% CI Page 9 of 14 Yang et al. BMC Women's Health (2025) 25:478 various cancers, Crohn’s disease, and heart failure [ 22, 54– 57]. Our study further suggests that in women post- hysterectomy, a high ALI score is significantly associated with lower long-term mortality. Additionally, our sup - plementary analysis shows that, compared to the 20–64 age group, the relationship between ALI levels and car - diovascular mortality is stronger in the 65–85 age group. This may be due to the elderly population’s decreased ability to manage chronic inflammation and malnutrition [58], combined with the higher prevalence of cardiovas - cular diseases in older individuals [ 59]. These findings suggest that elevated ALI levels may significantly reduce the incidence and mortality of cardiovascular diseases by improving inflammatory responses and promoting better nutritional status. Moreover, integrating structured clas - sification systems and predictive modeling into periop - erative care could improve patient management [ 60– 63]. Predictive models, such as those incorporating ALI, can inform clinical decision-making and facilitate personal - ized treatment plans that address both inflammatory and nutritional needs. In exploring the potential biological mechanisms behind the reduced mortality risk in women after hys - terectomy, ALI provides insights into the inflammatory and nutritional status of the body. ALI integrates sev - eral components, including the Neutrophil-to-Lympho - cyte Ratio (NLR), albumin, and BMI, which collectively reflect systemic inflammation and nutritional status— both of which have significant implications for recovery trajectories. NLR is a well-established marker of systemic inflam - mation, which can impair immune function and hinder postoperative recovery. Elevated NLR has been associ - ated with poor clinical outcomes across a range of con - ditions, including cancer, cardiovascular diseases, and postoperative complications. Chronic inflammation, as evidenced by high NLR levels, can suppress immune responses, delay wound healing, and increase susceptibil- ity to postoperative complications [ 64]. Moreover, NLR has been linked to depression progression, as inflam - matory cytokines play a role in the pathophysiology of depression [65]. Serum albumin is a key marker of nutritional sta - tus, with low levels typically indicating inflammation and malnutrition. Albumin is essential for maintaining oncotic pressure and supporting tissue repair processes. Low albumin levels reflect a compromised nutritional state, which can impair immune function and tissue healing. Additionally, albumin possesses antioxidant properties that protect tissues from oxidative stress and inflammatory damage, both of which are critical for post-surgical recovery [ 66]. Furthermore, low albumin levels have been associated with poorer mental health outcomes, including depression, suggesting a complex Table 4 Threshold analysis of ALI index and depression score for all-cause and cardiovascular mortality in patients who have undergone hysterectomy Adjusted HR (95% CI) P value P for Log-like- lihood ratio† All-cause mortality ALI Fitting by the stan- dard linear model 0.51(0.43– 0.60) < 0.0001 Inflection point:6.76 < 0.0001 Fitting by the two- piecewise linear model ALI index < 6.76 0.42(0.35– 0.51) 6.76 1.15(0.73– 1.81) 0.5366 Cardiovascular mortality ALI Fitting by the stan- dard linear model 0.46(0.33– 0.64) < 0.0001 Inflection point:5.57 0.145 Fitting by the two- piecewise linear model ALI index 5.57 0.54(0.37– 0.80) 0.0018 All-cause mortality Depression Fitting by the stan- dard linear model 1.03(1.01– 1.05) 0.0011 Inflection point:14 0.189 Fitting by the two- piecewise linear model ALI index 14 0.98(0.89– 1.07) 0.5957 Cardiovascular mortality Depression Fitting by the stan- dard linear model 1.03(0.99– 1.07) 0.1503 Inflection point:1 0.084 Fitting by the two- piecewise linear model ALI index 1 1.01(0.97– 1.06) 0.6467 *Loglikelihood ratio is used to assess whether there is a statistical difference between two segmented linear models Page 10 of 14 Yang et al. BMC Women's Health (2025) 25:478 interplay between nutritional status and emotional well- being [67]. BMI is commonly used to assess nutritional status and is associated with both chronic inflammation and recov - ery outcomes. A low BMI is linked to increased mortality risk, often reflecting inadequate nutritional intake and poor body function. Conversely, a high BMI can lead to chronic low-grade inflammation, which contributes to metabolic diseases and complicates recovery, particu - larly in the presence of depression [ 68]. Both extremes Fig. 5 Subgroup analysis of the associations between PHQ-9 scores and all-cause and cardiovascular mortality, adjusted for age, race, education, poverty- to-income ratio, hypertension, diabetes, alcohol use, smoking, BMI, hormone use, antidepressants use and sleep disorders Fig. 4 Subgroup analysis of the associations between ALI and all-cause and cardiovascular mortality, adjusted for age, race, education, poverty-to- income ratio, hypertension, diabetes, alcohol use, smoking, hormone use, antidepressants use and sleep disorders Page 11 of 14 Yang et al. BMC Women's Health (2025) 25:478 of BMI—low and high—are associated with worse health outcomes, highlighting the importance of maintaining an optimal weight for recovery and long-term health. In conclusion, the components of ALI—NLR, albu - min, and BMI—serve as vital indicators of the body’s inflammatory and nutritional status, which are criti - cal for recovery after surgery. Maintaining a healthy BMI, optimal serum albumin levels, and a low NLR may improve ALI levels and lead to better clinical outcomes. Hormone replacement therapy (HRT) has anti-inflam - matory effects, potentially improving recovery after hys - terectomy [69]. Additionally, healthcare disparities linked to socioeconomic status can hinder timely recovery and psychological well-being, particularly in underprivileged groups [ 70]. Therefore, individualized postoperative management strategies should account for these factors to improve patient outcomes. Although our study identifies ALI as a promising bio - marker associated with postoperative outcomes, its clinical applications require further exploration. In this context, we propose two potential translational applica - tions for surgical and gynecologic practitioners: (1) Pre - operative ALI Screening: Given the association between ALI and postoperative mortality risk, preoperative ALI screening could help identify high-risk patients. By evaluating ALI components, such as NLR, albumin lev - els, and BMI, clinicians could better stratify patients and tailor interventions to optimize recovery. (2) Nutri - tional Support Protocols: ALI’s reflection of nutritional status suggests its potential use in developing preopera - tive nutritional support protocols. Patients with low ALI levels could benefit from early nutritional interventions aimed at improving immune function and supporting postoperative recovery. These recommendations high - light the potential for ALI to be integrated into preopera- tive screening and nutritional management to improve postoperative outcomes. However, further prospective studies are required to validate these clinical applications. Lawes was among the first researchers to examine how inflammation and depression together affect mortality risk. A combined analysis found that men with depres - sive symptoms and high C-reactive protein (CRP) levels had a 140% higher risk of death compared to those with - out depressive symptoms and with normal CRP levels [71]. Later studies on cancer patients ALI and depression reported similar results. These studies showed that can - cer survivors with low ALI levels and depression faced a higher risk of death, while those with high ALI levels and good mental health had a 60% lower risk [ 72]. To date, no research has investigated the link between ALI and depressive symptoms in women after hysterectomy. Our study indicates that women with higher ALI levels and good mental health (PHQ-9: 0–4) have a 66% lower risk of all-cause mortality compared to those with depressive symptoms and low ALI levels. This finding addresses a gap in the current literature. The main strength of this study is its pioneering approach, using large cohort data from NHANES, which allows for broader generalization of the findings to vari - ous populations. This study is the first to identify ALI as a potential biomarker for adverse outcomes following Table 5 Mediation analysis of associations between hysterectomy populations and risk of all-cause mortality and cardiovascular mortality using ALI and depression as mediators Non-adjusted β (95%CI)P-value Adjust II β(95%CI) P-value ALI All-cause mortality Direct effect −0.102 (−0.115, −0.089) < 0.0001 −0.006 (−0.013, 0.003) 0.228 Indirect effect 0.004 (0.003, 0.006) < 0.0001 0.001 (0.0005, 0.002) 0.002 Total effect −0.098 (−0.110, −0.085) < 0.0001 −0.004 (−0.012, 0.005) 0.348 PM, % −4.3 −33.2 P-value < 0.0001 0.35 Cardiovascular mortality Direct effect −0.024 (−0.03, −0.017) < 0.0001 0.001 (−0.003, 0.006) 0.626 Indirect effect 0.001 (0.0007, 0.002) < 0.0001 0.0003 (0.0001, 0.0006) 0.002 Total effect −0.023 (−0.030, −0.016) < 0.0001 0.001 (−0.003, 0.006) 0.496 PM, % −5.6 26.2 P-value < 0.0001 0.498 Depression All-cause mortality Direct effect −0.99 (−0.111, −0.086) < 0.0001 −0.004 (−0.012, 0.004) 0.314 Indirect effect −0.0003 (−0.001, 0.0005) 0.456 −0.0007 (−0.001, −0.0002) < 0.0001 Total effect −0.0997 (−0.112, −0.086) < 0.0001 −0.005 (−0.013, 0.004) 0.256 PM, % 0.3 13.6 P-value 0.456 0.256 Cardiovascular mortality Direct effect −0.023 (−0.030, −0.017) < 0.0001 0.002 (−0.003, 0.006) 0.462 Indirect effect −0.002 (−0.0006, 0.0001) 0.234 −0.002 (−0.0005, 0.0000002) 0.052 Total effect −0.023 (−0.030, −0.017) < 0.0001 0.001 (−0.003, 0.006) 0.52 PM, % 0.86 −14.2 P-value 0.234 0.536 Crude model: we did not adjust other covariant. Model II on ALI: we adjusted age, race, education, poverty-to-income ratio, hypertension, diabetes, alcohol use, smoking, hormone use, antidepressants use and sleep disorders. Model II on Depression: we adjusted age, race, education, poverty-to- income ratio, hypertension, diabetes, alcohol use, smoking, hormone use, antidepressants use, BMI and sleep disorders. Page 12 of 14 Yang et al. BMC Women's Health (2025) 25:478 hysterectomy. It also examines the relationships between nutrition, inflammation, depression, and both overall and cardiovascular mortality in women after hysterectomy.

Despite the significant findings of this study, its limita - tions should be carefully considered. First, it relies on cross-sectional NHANES laboratory data, limiting our ability to assess temporal changes and long-term inter - vention effects. Given the dynamic nature of inflam - mation and nutritional status, especially post-surgery, incorporating longitudinal biomarker data or repeated ALI measurements would provide deeper insights into how these factors evolve and affect patient outcomes. This would improve the prognostic value and clinical rel- evance of our findings. Second, depression was assessed using self-reports with the PHQ-9 scale, which may not fully reflect an individual’s depressive condition. Third, the dataset did not distinguish between the types of hys - terectomy (e.g., laparoscopic, robotic, or abdominal), which may introduce heterogeneity in outcomes due to differences in surgical techniques, perioperative manage - ment, and postoperative recovery. Future studies should stratify outcomes by surgical approach to more precisely assess these relationships. Lastly, the potential confound- ing effects of the underlying indications for hysterectomy, such as whether the surgery was performed for benign or malignant conditions, were not addressed in this study. Future research with more detailed clinical data could further investigate the potential impact of these factors on depressive symptoms and nutritional-inflammatory profiles in relation to mortality outcomes.

This study identifies a nonlinear negative correlation between ALI and mortality risk in women after hyster - ectomy, along with a linear positive correlation between PHQ-9 scores and mortality risk. It highlights the impor - tance of maintaining adequate nutrition, controlling inflammation, and addressing depressive symptoms. These findings establish a theoretical basis for person - alized assessment and management of postoperative patients. They also provide essential scientific support for improving long-term outcomes and offer guidance for early intervention and targeted treatment in clinical practice. Abbreviations NHANES National Health and Nutrition Examination Survey ALI The advanced lung cancer inflammation index PHQ-9 The Patient Health Questionnaire-9 BMI Body Mass Index NCHS National Center for Health Statistics Supplementary Information The online version contains supplementary material available at h t t p s : / / d o i . o r g / 1 0 . 1 1 8 6 / s 1 2 9 0 5 - 0 2 5 - 0 4 0 0 3 - 8. Supplementary Material 1. Supplementary Material 2.

Not applicable. Authors’ contributions Ying Yang: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Visualization, Writing-Original Draft, Writing-Review & Editing; Yazhou Liu: Data Curation, Formal Analysis, Visualization; Xiaohang Lu: Data Curation, Methodology; Wei Sun: Supervision, Validation; Haiyan Chen: Supervision, Validation; Ning Wang: Conceptualization, Funding Acquisition, Supervision, Validation, Writing-Original Draft, Writing-Review &Editing. Funding This research was jointly supported by the “1 + X” Research Project of The Second Hospital of Dalian Medical University (YJ2024001202), the “1 + X” Clinical Technology Enhancement Project on Ovarian Cancer Ultra Radical Surgery (2022LCJSZD04), and the “Xingliao Talent Plan” Medical Expert Project (YXMJ-QN-17). Data availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Declarations Ethics approval and consent to participate All participants provided written informed consent before undergoing the NHANES survey, and the survey received approval from the NCHS IRB, as detailed at h t t p s : / / w w w . c d c . g o v / n c h s / n h a n e s / i r b a 9 8 . h t m. As NHANES is a publicly available database with anonymized personal information, no additional ethical approval or informed consent was necessary. Consent for publication Not Applicable. Competing interests The authors declare no competing interests. Received: 17 June 2025 / Accepted: 25 August 2025

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