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Korean J Anesthesiol > Volume 79(4); 2026 > Article
Jo, Lee, Kim, Kim, Park, Kong, and Lee: The impact of preoperative comorbidity and intraoperative hypotension on postoperative acute kidney injury after non-cardiac surgery: a structural equation modeling-based mediation analysis

Abstract

Background

Preoperative comorbidities are associated with postoperative acute kidney injury (AKI). However, whether this association is direct or mediated by intraoperative hypotension (IOH) is unclear. We hypothesized that IOH mediates the relationship between preoperative comorbidities and postoperative AKI.

Methods

Data from adult patients undergoing non-cardiac surgery under general anesthesia were analyzed. Inverse probability of treatment weighting (IPTW) was applied to achieve a balance between the exposure groups by reducing the baseline differences in the measured covariates. Structural equation modeling (SEM)-based mediation analysis was conducted using the American Society of Anesthesiologists physical status (ASA-PS) classification ≥ 3 as an input and postoperative AKI as an outcome. IOH (duration of mean arterial pressure < 60 mmHg), along with albumin and hemoglobin levels, was considered a mediator. We also performed interaction analysis between patient sex and age.

Results

After IPTW, 8643.9 (10.8%) patients had an ASA-PS of ≥ 3. AKI occurred more frequently (4.5% vs. 6.9%, P < 0.001) in patients with ASA-PS ≥ 3. ASA-PS ≥ 3 was associated with a total effect estimate of 0.02 on the log-odds of postoperative AKI (P < 0.001). Of the total effect of ASA-PS ≥ 3 on postoperative AKI, 48% was significantly mediated by IOH (26%) and hypoalbuminemia (26%), though anemia showed no significance. The effect of high ASA-PS scores on postoperative AKI was significantly modified by sex, but not by age.

Conclusions

High ASA-PS scores increase AKI risk after non-cardiac surgery, a relationship partially mediated by statistically significant pathways involving IOH and hypoalbuminemia.

Introduction

Patients with the American Society of Anesthesiologists physical status (ASA-PS) classification ≥ 3 have an increased risk of perioperative complications [1,2]. Multiple studies have reported that patients with ASA-PS ≥ 3 are associated with worse postoperative outcomes, including acute kidney injury (AKI) [35]. ASA-PS ≥ 3 is also associated with the intraoperative hypotension (IOH) [6]. The kidney is highly susceptible to ischemia, making it vulnerable to the effects of IOH.
Numerous studies have identified an association between IOH and postoperative AKI, showing that a longer mean arterial pressure (MAP) below 65 mmHg, as well as at 60 mmHg and 55 mmHg, is associated with an increased incidence of AKI [79]. However, because these studies focused on retrospective analyses of clinical data, the causality of this relationship remains unclear. Additionally, randomized controlled trials comparing a permissive hypotension group (< 60 mmHg) with a tight blood pressure management group (> 60 mmHg) failed to demonstrate that intraoperative blood pressure management can prevent postoperative AKI [10]. If IOH plays a significant mediating role, targeted intraoperative blood pressure management could help mitigate the risk of postoperative AKI. Conversely, if the ASA-PS exerts a direct effect, broader strategies focusing on preoperative optimization may improve outcomes.
In this study, we investigated the relationships among ASA-PS, IOH, and postoperative AKI. Specifically, we aimed to quantify the extent to which IOH mediates the association between ASA-PS ≥ 3 and postoperative AKI using the structural equation modeling (SEM)-based mediation analysis technique.

Materials and Methods

Ethics

This single-center retrospective study was approved by the Institutional Review Board on May 16, 2025 (number: 2505-058-1639). The requirement for written informed consent was waived owing to the retrospective nature of the study. This manuscript adheres to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines [11].

Participants

All patients aged 18–90 years who underwent non-cardiac surgery under general anesthesia at Seoul National University Hospital between January 2011 and December 2020 were included. We excluded patients without preoperative or postoperative serum creatinine data, no intraoperative blood pressure records, an ASA-PS score of 6, and a preoperative glomerular filtration rate below 60 mL/min/1.73 m2.

Exposure, mediator, and outcome variables

The primary exposure of interest was a high ASA-PS score of ≥ 3. IOH, defined as the duration (in minutes) of MAP < 60 mmHg, hypoalbuminemia, and anemia, was considered a potential mediator. To better reflect the intraoperative values, the hemoglobin and albumin values were defined as the average of all intraoperative measurements when available. Otherwise, the value measured at the time point closest to surgery was used. The primary outcome was postoperative AKI, determined using the Kidney Disease Improving Global Outcomes creatinine criteria [12]. AKI was assessed as a binary variable (presence or absence) and severity (stages 1–3).
All relevant clinical data, including demographic characteristics, preoperative medications, laboratory values, surgical information, and outcomes, were extracted from the Seoul National University Hospital Clinical Data Warehouse.

Statistical analysis

Continuous variables were assessed for normality using the Kolmogorov–Smirnov test. When the assumption of normality was not met, the Wilcoxon rank-sum test was performed, and the results are reported as medians with interquartile ranges. Categorical variables are presented as frequencies and percentages and were compared using the chi-square test or Fisher’s exact test. Imbalances between groups were evaluated using standardized mean differences (SMDs), with a threshold of 0.1 considered indicative of meaningful imbalance. To account for the observed baseline imbalances in confounders, inverse probability of treatment weighting (IPTW) was applied using age, sex, body mass index (BMI), anesthesia duration, emergency operation, preoperative use of angiotensin-converting enzyme inhibitor (ACEi) or angiotensin receptor blocker (ARB), beta-blocker use, and surgical procedure type (gastrointestinal or renal surgeries). To minimize the impact of extreme outliers, the stabilized weights were calculated and truncated at a threshold of 10. To account for potential nonlinear associations, age and BMI were modeled using restricted cubic splines (RCS) within both the IPTW estimation and SEM framework.
We constructed a directed acyclic graph to illustrate the exposure–mediator–outcome relationships among the variables (Fig. 1). We hypothesized that IOH, hypoalbuminemia, and anemia would mediate the effect of ASA-PS ≥ 3 on the risk of postoperative AKI. SEM analysis was performed to evaluate the hypothesized exposure–mediator–outcome pathway and to quantify both the direct and indirect effects of ASA-PS ≥ 3 on postoperative AKI through these mediators [9,13,14]. Mediation analysis was conducted using the bootstrapping method with 10 000 replicates to obtain robust estimates of CIs and P values.
All statistical analyses were performed in R (version 4.5.2; R Foundation for Statistical Computing), and a P value < 0.05 was considered statistically significant. Subgroup analyses were performed to examine whether the associations of interest differed according to sex or older age (> 65 years). Mediator–mediator interactions were tested and are presented in Supplementary Material 1. To enhance reproducibility and transparency, a sample dataset derived from the open-access Informative Surgical Patient Dataset for Innovative Research Environment was used [15]. The sample dataset, along with the source code for the analysis, is available in Supplementary Material 2.

Results

A total of 79 788 patients were included between January 2011 and December 2020, including 8671 patients (10.9%) with high ASA-PS scores (Fig. 2). Patients with ASA-PS ≥ 3 scores were more likely to be male, older, and have a higher BMI. They were also more likely to be on preoperative medications such as ACEi, ARB, and beta-blockers (Table 1). After applying IPTW, baseline imbalances in all measured confounders, except BMI, were effectively corrected, resulting in SMDs of < 0.1 (Table 2). Laboratory profiles in the high ASA-PS group showed lower hemoglobin levels; higher white blood cell counts; lower platelet counts; prolonged prothrombin and activated partial thromboplastin times; elevated glucose, aspartate aminotransferase, and alanine aminotransferase levels; increased sodium levels; and decreased albumin levels (Supplementary Material 3).
Postoperative AKI occurred more frequently (4.5% vs. 6.9%, P < 0.001) in patients with high ASA-PS scores (Table 3). These patients also experienced more AKI across all stages (stage 1 [3.9% vs. 5.6%, P < 0.001]; stage 2 [0.4% vs. 1.0%; P < 0.001]; stage 3 [0.1% vs. 0.3%, P < 0.001]), higher in-hospital mortality (1.2% vs. 4.6%; P < 0.001), and longer hospital stay (9 [6–13] vs. 12 [8–22] days, P < 0.001) and intensive care unit stay (1 [1–2] vs. 1 [1–4] days, P < 0.001).
SEM analysis showed that high ASA-PS scores were associated with a total effect estimate of 0.02 (95% CI [0.02–0.03]) on the log-odds of postoperative AKI (P < 0.001) (Table 4). Approximately 48% (34%–62%) of this excess risk was mediated by IOH, hypoalbuminemia, and anemia. IOH and hypoalbuminemia showed significant positive mediating effects on AKI (26% [18%–34%], P < 0.001; 26% [18%–35%], P < 0.001), whereas the mediating effect of anemia was not statistically significant (−4% [−8% to –1%], P = 0.098).
In the interaction analyses, sex significantly modified the effect of high ASA-PS scores on postoperative AKI (P = 0.013). Age of > 65 years did not significantly modify the effect of high ASA-PS scores on postoperative AKI (P = 0.053). The stratified total, direct, and mediated effects of high ASA-PS on postoperative AKI according to sex and age group are shown in Supplementary Material 4.
In the sensitivity analysis, treating the ASA-PS as a continuous variable, the results remained robust and consistent with those of the primary analysis (Supplementary Material 5). ASA-PS was associated with a total effect estimate of 0.01 (95% CI [0.00–0.01]) on the log-odds of postoperative AKI (P < 0.001). Approximately 88% (95% CI [51–124], P < 0.001) of this excess risk was mediated by IOH, hypoalbuminemia, and anemia. Although age and BMI exhibited significant nonlinear associations with AKI, sensitivity analysis incorporating RCS for these variables showed results comparable to those of the primary analysis (Supplementary Material 6).

Discussion

In this large retrospective cohort study of patients undergoing non-cardiac surgery under general anesthesia, a substantial proportion of the increased risk of postoperative AKI in patients with high preoperative comorbidity burden (ASA-PS ≥ 3) was mediated through modifiable factors, particularly IOH, as well as hypoalbuminemia and anemia. Hypoalbuminemia has a significant effect on postoperative AKI. Albumin improves renal perfusion and glomerular filtration, acts as an antioxidant, scavenges harmful reactive oxygen species, inhibits renal tubular cell apoptosis, and binds to nephrotoxic substances [16]. Anemia also increases the risk of AKI by impairing oxygen delivery and exacerbating ischemic injury. This lack of oxygen impairs the function of highly metabolic tubular cells, triggering cellular injury and a rapid decline in kidney function [17]. IOH and hypoalbuminemia showed significant positive mediating effects on AKI, whereas anemia exhibited a non-significant mediating effect. However, the accuracy of this finding is limited because the measured hemoglobin levels did not capture all intraoperative values, suggesting the need for further studies incorporating real-time data for precise assessment. Furthermore, the low coefficient of hemoglobin suggests that the observed effect of anemia may lack true clinical significance, a result potentially attributable to adjustment for other mediators and confounders.
A substantial (51.8%) direct effect independent of IOH suggests the presence of additional pathways through which comorbidities predispose patients to AKI. These include baseline chronic kidney disease, inflammatory states, nephrotoxic drugs, and metabolic derangements that directly affect renal function perioperatively [9]. In previous studies, patients with ASA-PS scores ≥ 3 had more frequent preoperative use of ACEi, ARB, and beta-blocker, contrastive media, and a higher prevalence of laboratory abnormalities such as elevated inflammatory biomarkers, glucose, and liver enzymes that are all known risk factors for renal dysfunction [13,18].
Significant sex-related differences were observed in the relationship between the ASA-PS and postoperative AKI. One prior study has reported that young women receiving non‐cardiac surgery had a lower risk of postoperative AKI than men, whereas another study has reported no significant differences between sexes [18,19]. Our results showed that the odds of postoperative AKI associated with high ASA-PS scores were higher in women than in men. In male patients, the effect of high ASA-PS scores on AKI was primarily mediated by IOH, whereas hypoalbuminemia showed a predominant effect in female patients. Experimental data suggest that testosterone may increase the renal susceptibility to ischemia, whereas estrogen may confer protection [20,21].
Unlike sex, old age did not show a significant interaction with high ASA-PS scores regarding postoperative AKI (P = 0.053), indicating no substantial difference in the direct effect of ASA-PS on AKI between older and younger patients. In patients aged < 65 years, the effect of high ASA-PS scores on AKI was primarily mediated by IOH, whereas hypoalbuminemia showed a predominant effect in patients aged > 65 years. Synthesizing the findings across sex and age, older male patients may require significant attention because of the greater mediating effect of IOH on postoperative AKI occurrence [22,23].
This study has several important clinical implications. Although previous randomized trials have yielded mixed results, targeted intraoperative blood pressure management remains important for mitigating the downstream effects of comorbidities on renal outcomes. In high-risk patients, the simultaneous correction of hypoalbuminemia and prevention of IOH may yield meaningful differences in reducing perioperative renal injury. Additionally, the significant direct effect of comorbidities on AKI suggests that comprehensive perioperative care, including the optimization of chronic disease control and avoidance of nephrotoxic exposure, remains essential.
This study has some limitations. First, because this study was conducted at a single tertiary care center and was retrospective in design, selection and institutional biases may have influenced our findings. Furthermore, the retrospective nature of our study precludes strict adherence to the assumption of sequential ignorability required for formal causal mediation. Consequently, the potential for residual confounding remains, necessitating a cautious interpretation of statistical mediation pathways. Second, because IOH definitions vary widely across studies, the mediation results based on our selected absolute intraoperative MAP threshold of 60 mmHg may differ if alternative thresholds or relative definitions are applied [8,10]. To further explore the impact of intraoperative MAP, we applied different thresholds for mediation analyses; their findings are detailed in Supplementary Material 7. Third, although cardiac surgery was excluded, the remaining surgical types were diversely distributed between the high and low ASA-PS groups that requires caution when interpreting the study results. Fourth, intraoperative vasopressor use might have affected renal perfusion that in turn could have influenced the relationship between IOH and AKI. However, this aspect could not be analyzed in the present study owing to insufficient data. Fifth, although the preoperative use of ACEi and ARB may have a direct effect on postoperative AKI, we only considered their mediating effect on IOH. Finally, the exclusion of approximately 50% of the patients because of missing postoperative creatinine values likely introduced a significant selection bias. Stable patients from less complex procedures may have been omitted based on clinical judgment, requiring caution when interpreting the generalizability of the results.
In conclusion, a high ASA-PS score is associated with an increased risk of postoperative AKI that is partially mediated by IOH, hypoalbuminemia, and anemia during non-cardiac surgery. Targeted blood pressure management, correction of albumin and hemoglobin levels, and comprehensive optimization of comorbidities may reduce kidney injury and enhance recovery in this population. Further research is needed to explore strategies for optimizing preoperative conditions and managing IOH to prevent postoperative AKI and optimize patient outcomes.

Funding

This research was supported by a grant of the Boston-Korea Innovative Research Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant no.: RS-2024-00403047, NTIS no.: 2460003034), and by the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea Government (MSIT) (no.: RS-2021-II211343, Artificial Intelligence Graduate School Program [Seoul National University]).

Conflicts of Interest

No potential conflict of interest relevant to this article was reported.

Data Availability

The datasets generated during and/or analyzed during the current study are not publicly available due to patient privacy and institutional data protection policies but are available from the corresponding author on reasonable request.

Author Contributions

Woo-Young Jo (Data curation; Formal analysis; Investigation; Methodology; Writing – original draft)

Hyeonhoon Lee (Data curation; Writing – review & editing)

Jayoun Kim (Formal analysis; Methodology; Writing – review & editing)

Won Ho Kim (Methodology; Supervision; Writing – review & editing)

Hee-Pyoung Park (Methodology; Supervision; Writing – review & editing)

Hyoun-joong Kong (Investigation; Methodology; Supervision)

Hyung-Chul Lee (Conceptualization; Formal analysis; Funding acquisition; Investigation; Writing – review & editing)

Supplementary Materials

Supplementary Material 1.
Estimated association between preoperative American Society of Anesthesiologists physical status (primary exposure), and postoperative acute kidney injury accounting for the effect mediated by total intraoperative mean arterial pressure below 60 mmHg, preoperative albumin and hemoglobin.
kja-25765-Supplementary-Material-1.pdf
Supplementary Material 2.
Sample dataset and R code.
kja-25765-Supplementary-Material-2.csvkja-25765-Supplementary-Material-2.R
Supplementary Material 3.
Comparison of preoperative laboratory data between low and high American Society of Anesthesiologists physical status groups after inverse probability of treatment weighting adjustment.
kja-25765-Supplementary-Material-3.pdf
Supplementary Material 4.
Estimated association between preoperative American Society of Anesthesiologists physical status ≥ 3 (primary exposure) and postoperative acute kidney injury according to sex accounting for effect mediated by total intraoperative mean arterial pressure below 60 mmHg, albumin and hemoglobin.
kja-25765-Supplementary-Material-4.pdf
Supplementary Material 5.
Estimated association between preoperative American Society of Anesthesiologists physical status (primary exposure), and postoperative acute kidney injury accounting for the effect mediated by total intraoperative mean arterial pressure below 60 mmHg, albumin and hemoglobin.
kja-25765-Supplementary-Material-5.pdf
Supplementary Material 6.
Restricted cubic spline-adjusted estimated association between preoperative American Society of Anesthesiologists physical status ≥ 3 (primary exposure), and postoperative acute kidney injury accounting for the effect mediated by total intraoperative mean arterial pressure below 60 mmHg, albumin and hemoglobin.
kja-25765-Supplementary-Material-6.pdf
Supplementary Material 7.
Estimated association between preoperative American Society of Anesthesiologists physical status ≥ 3 (primary exposure), and postoperative acute kidney injury, accounting for the effect mediated by total intraoperative mean arterial pressure below 55 mmHg, preoperative albumin, and hemoglobin.
kja-25765-Supplementary-Material-7.pdf

Fig. 1.
Directed acyclic graph illustrating the hypothesized influence of high ASA-PS on postoperative AKI. This effect may be direct or mediated by IOH, albumin and hemoglobin. ASA-PS: American Society of Anesthesiologists physical status, AKI: acute kidney injury, IOH: intraoperative hypotension.
kja-25765f1.jpg
Fig. 2.
The CONSORT flow diagram. Invalid laboratory findings represent technical errors or non-physiological ranges (albumin < 1.0 or > 6.5 g/dL, hemoglobin < 5 or > 20 g/dL, glucose < 40 or > 600 mg/dL, blood urea nitrogen < 2 or > 100 mg/dL, and aspartate/alanine aminotransferase < 1 or > 5000 U/L). ASA-PS: American Society of Anesthesiologists Physical status.
kja-25765f2.jpg
Table 1.
Comparison of Demographics, Medication, and Surgery Type between Low and High ASA-PS Groups
Variable ASA < 3 (n = 71 117) ASA ≥ 3 (n = 8671) SMD
Sex (M) 37 706 (53.0) 5050 (58.2) 0.10
Age (yr) 59.0 (49.0, 68.0) 64.6 (54.6, 73.0) 0.32
BMI (kg/m2) 23.4 (21.5, 26.0) 22.9 (20.2, 25.7) 0.16
Preoperative medication
 ACEi or ARB 7230 (10.2) 1914 (22.1) 0.33
 Beta blocker 4535 (6.4) 2077 (24.0) 0.51
Anesthesia duration (min) 190 (125, 270) 185 (115, 285) 0.10
Emergent operation (%) 5630 (7.9) 2165 (25.0) 0.47
Surgery type
 Gastrointestinal 16 189 (22.8) 1501 (17.3) 0.14
 Cardiothoracic 6981 (9.8) 1098 (12.7) 0.09
 Orthopedic 10 793 (15.2) 1039 (12.0) 0.09
 Neurologic 6099 (8.6) 925 (10.7) 0.07
 Breast and plastic 5247 (7.4) 866 (10.0) 0.09
 Hepatobiliary and pancreas 4576 (6.4) 761 (8.8) 0.09
 Renal 4867 (6.8) 309 (3.6) 0.15
 Ear, nose, and throat 4002 (5.6) 394 (4.5) 0.05
 Vascular 2958 (4.2) 559 (6.4) 0.10
 Urology (not renal) 2243 (3.2) 151 (1.7) 0.09
 Endocrine 853 (1.2) 113 (1.3) 0.01
 Gynecologic 636 (0.9) 76 (0.9) 0.00
 Others 5673 (8.0) 879 (10.1) 0.08

Values are presented as number (%) or median (Q1, Q3). ASA-PS: American Society of Anesthesiologists physical status, SMD: standardized mean difference, BMI: body mass index, ACEi: angiotensin-converting enzyme inhibitor, ARB: angiotensin receptor blocker.

Table 2.
Comparison of Demographics, Medication, and Surgery Type between Low and High ASA-PS Groups after IPTW Adjustment
Variable ASA < 3 (n = 71 205.6) ASA ≥ 3 (n = 8643.9) SMD
Sex (M) 38 177.6 (53.6) 4562.8 (52.8) 0.02
Age (yr) 60 (49, 68) 60 (48, 70) 0.01
BMI (kg/m2) 23.4 (21.4, 26.0) 23.9 (20.8, 26.7) 0.12
Preoperative medication
 ACEi or ARB 8261.2 (11.6) 1054.4 (12.2) 0.02
 Beta blocker 6002.1 (8.4) 765.0 (8.9) 0.02
Anesthesia duration (min) 190 (125, 270) 180 (115, 280) 0.01
Emergent operation (%) 7039.7 (9.9) 876.3 (10.1) 0.01
Surgery type
 Gastrointestinal 15 765.4 (22.1) 1917.7 (22.2) 0.00
 Renal 4612.1 (6.5) 515.5 (6.0) 0.02

Values are presented as number (%) or median (Q1, Q3). ASA-PS: American Society of Anesthe­siologists physical status, IPTW: inverse probability of treatment weighting, SMD: standardized mean difference, BMI: body mass index, ACEi: angiotensin-converting enzyme inhibitor, ARB: angiotensin receptor blocker.

Table 3.
IPTW-adjusted Comparison of Postoperative Outcomes between Low and High ASA-PS Groups
Variable ASA < 3 (n = 71 205.6) ASA ≥ 3 (n = 8643.9) P value
Postoperative AKI 3208.1 (4.5) 595.5 (6.9) < 0.001
AKI stage*
No AKI 64 789.4 (91.0) 7452.9 (86.2) < 0.001
 Stage 1 2802.2 (3.9) 482.6 (5.6) < 0.001
 Stage 2 302.6 (0.4) 88.6 (1.0) < 0.001
 Stage 3 103.3 (0.1) 24.3 (0.3) < 0.001
In-hospital mortality, n (%) 863.8 (1.2) 392.2 (4.5) < 0.001
Hospital length of stay (d) 9 (6, 13) 12 (8, 22) < 0.001
ICU length of stay (d) 1 (1, 2) 1 (1, 4) < 0.001

Values are presented as number (%) or median (Q1, Q3). IPTW: inverse probability of treatment weighting, ASA-PS: American Society of Anesthesiologists physical status, AKI: acute kidney injury, ICU: intensive care unit. *Kidney disease improving global outcome (KDIGO) creatinine criteria.

Table 4.
Estimated Association between Preoperative ASA-PS ≥ 3 (primary exposure) and Postoperative AKI Accounting for the Effect Mediated by Total Intraoperative MAP below 60 mmHg, Albumin, and Hemoglobin
Variable Total effect* Percent mediated Direct effect
Estimate (95% CI) P value Estimate (95% CI) P value Estimate (95% CI) P value
Exposure
 ASA-PS classification ≥ 3 0.02 (0.02–0.03) < 0.001 0.48 (0.34–0.62) < 0.001 0.01 (0.01–0.02) < 0.001
Mediator
 IOH 0.26 (0.18–0.34) < 0.001 0.02 (0.02–0.03) < 0.001
 Hypoalbuminemia 0.26 (0.18–0.35) < 0.001 −0.01 (−0.01 to −0.01) < 0.001
 Anemia −0.04 (−0.08 to 0.01) 0.098 0.00 (0.00–0.00) 0.090

Values are presented as estimate (95% CI). ASA-PS: American Society of Anesthesiologists physical status, AKI: acute kidney injury, MAP: mean arterial pressure, IOH: intraoperative hypotension. *Total effect, the overall association of ASA-PS ≥ 3 with postoperative AKI, comprises a direct effect (independent of mediators: intraoperative MAP < 60 mmHg, hemoglobin, and albumin) and mediated effects (via mediators, also expressed as percentage of total effect). The ‘percent mediated’ indicates how much of a total effect happens through a specific intermediate step. If it was < 0%, the direct effect was stronger than the total effect, suggesting that the mediator may lessen the overall impact. If it was > 0%, a significant part of the effect was transmitted through that mediating variable.

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