Li J, Ma LJ, Ma XY, Gao B. Relationship between weight-to-waist index and post-stroke depression. World J Psychiatry 2025; 15(3): 100909 [DOI: 10.5498/wjp.v15.i3.100909]
Corresponding Author of This Article
Bo Gao, MD, Department of Neurology, The Affiliated Hospital of Yan’an University, No. 94 Shuangyong Avenue, Baota District, Yan’an 716000, Shaanxi Province, China. bobo0426@yau.edu.cn
Research Domain of This Article
Demography
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Author contributions: Li J, Ma LJ, and Gao B designed the methodology; Li J and Ma LJ performed the formal analysis of the data; Li J wrote the original draft; Li J and Gao B conceptualized the study; Ma LJ and Ma XY edited the various iterations of the manuscript; Gao B wrote and edited the manuscript, and performed the project administration.
Institutional review board statement: The National Health and Nutrition Examination Survey protocol is reviewed and approved by the National Center for Health Statistics Research Ethics Review Board, with informed consent obtained from all participants. The National Health and Nutrition Examination Survey data are publicly accessible, allowing any interested parties to obtain the full dataset by visiting the official website (https://www.cdc.gov/nchs/nhanes/index.htm).
Informed consent statement: The need for patient consent was waived due to the retrospective nature of the study.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No additional data are available.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Bo Gao, MD, Department of Neurology, The Affiliated Hospital of Yan’an University, No. 94 Shuangyong Avenue, Baota District, Yan’an 716000, Shaanxi Province, China. bobo0426@yau.edu.cn
Received: August 30, 2024 Revised: December 12, 2024 Accepted: January 20, 2025 Published online: March 19, 2025 Processing time: 180 Days and 3.1 Hours
Abstract
BACKGROUND
The weight-to-waist index (WWI) serves as an innovative metric specifically designed to assess central obesity. However, the relationship between WWI and the prevalence of post-stroke depression (PSD) remains inadequately explored in the literature.
AIM
To elucidate the relationship between WWI and PSD.
METHODS
Data from the National Health and Nutrition Examination Survey 2005 to 2018 were analyzed. Multivariable logistic regression models and propensity score matching were utilized to investigate the association between WWI and PSD, with adjustments for potential confounders. The restricted cubic spline statistical method was applied to explore non-linear associations.
RESULTS
Participants with elevated WWI values had a significantly greater risk of developing PSD. Specifically, individuals in the higher WWI range exhibited more than twice the likelihood of developing PSD compared to those with lower WWI values (odds ratio = 2.21, 95% confidence interval: 1.84-2.66, P < 0.0001). After propensity score matching, the risk of PSD remained significantly elevated (odds ratio = 1.43, 95%confidence interval: 1.09-1.88, P = 0.01). Tertile analysis revealed that participants in the highest WWI tertile faced a significantly higher risk of PSD compared to those in the lowest tertile. Restricted cubic spline analysis further revealed a non-linear association, with the risk of PSD plateauing at higher WWI values.
CONCLUSION
There is a significant association between elevated WWI and increased risk of PSD. Thus, regular depression screening should be implemented in stroke patients with elevated WWI to enhance patient outcomes.
Core Tip: Weight-to-waist index (WWI) is designed to evaluate central obesity, a condition strongly linked to a spectrum of metabolic and cardiovascular diseases. This study aims to elucidate the relationship between WWI and post-stroke depression (PSD) by analyzing data from the National Health and Nutrition Examination Survey from 2005 to 2018. There was a significant association between elevated WWI values and PSD risk. Individuals with higher WWI range exhibited more than double the likelihood of developing PSD compared to those with lower WWI values. As an emerging indicator of central obesity, WWI may serve as a valuable tool for assessing PSD risk.
Citation: Li J, Ma LJ, Ma XY, Gao B. Relationship between weight-to-waist index and post-stroke depression. World J Psychiatry 2025; 15(3): 100909
Stroke is the second leading cause of death and disability worldwide[1], and its disease burden is substantial in both low- and high-income countries[2]. However, even more concerning than stroke itself are its complications. Common complications among stroke survivors include depression, anxiety, fatigue, apathy, insomnia, mania, and cognitive impairment[3]. Of these, post-stroke depression (PSD) is prevalent, with an incidence of 11% to 41% within the 1st 2 years after stroke[4]. As the population of stroke survivors increases, the prevalence of PSD is increasing correspondingly[5]. The clinical manifestations of PSD include low mood, social withdrawal, reduced interest, emotional blunting, pessimism, sleep disturbances, and fatigue. In severe cases, suicidal ideation can occur[6]. PSD hinders neurological recovery[7] and diminishes patients’ quality of life, placing a substantial burden on individuals, families, and society[8]. PSD is frequently overlooked, and its underlying mechanisms remain elusive. A growing body of research suggests that PSD pathogenesis is a result of complex interactions among multiple factors[9,10]; obesity may be a critical contributing factor[11].
Obesity is characterized by excessive or abnormal fat accumulation, leading to a wide range of adverse health effects[12]. Obesity is closely linked to the development of hypertension, diabetes, cardiovascular disease, and an elevated risk of anxiety and depression[13-16]. Historically, body mass index (BMI) has been the standard for assessing obesity. However, its accuracy has recently come under scrutiny due to its inability to account for variations in muscle mass, bone density, and fat distribution[17,18]. In contrast, waist circumference (WC) is considered a more accurate indicator of obesity, given its strong correlation with abdominal fat accumulation[19,20]. More recently, a novel obesity metric has been proposed, termed the weight-to-waist index (WWI). WWI is defined as WC divided by the square root of body weight. It effectively captures central obesity independent of overall body weight[21,22]. Moreover, WWI is positively correlated with age, thereby reflecting age-related changes in abdominal composition. Furthermore, studies have shown that WWI can effectively predict changes in aging-associated fat and muscle composition, making it broadly applicable across diverse populations[23]. Growing evidence indicates that WWI is more accurate than BMI[24,25]. Despite the established and significant associations of WWI with depression and various chronic conditions, the potential link between WWI and PSD remains largely underexplored. Therefore, in this study, we sought to elucidate the association between WWI and PSD using a cross-sectional design.
MATERIALS AND METHODS
Study population
In the United States, the National Health and Nutrition Examination Survey (NHANES) is an ongoing, nationally representative cross-sectional survey. As a key initiative of the National Center for Health Statistics, NHANES is approved and sponsored by the Centers for Disease Control and Prevention to evaluate the health and nutritional status of the civilian United States population. The NHANES protocol is reviewed and approved by the National Center for Health Statistics Research Ethics Review Board, with informed consent obtained from all participants. The NHANES data are publicly accessible, allowing any interested parties to obtain the full dataset by visiting the official website (https: //www.cdc.gov/nchs/nhanes/index.htm).
In this study, data from seven cycles in the NHANES database (2005-2018) were utilized, comprising a total of 70190 participants. Exclusion criteria were as follows: (1) Participants without stroke data, n = 30496; (2) Participants without Patient Health Questionnaire-9 (PHQ-9) data, n = 5410; and (3) Those missing WWI scores and other key variables, n = 1169. Ultimately, 33115 subjects were included in the final analysis. The participant selection process is outlined in Figure 1.
Figure 1 Flowchart of participant selection from National Health and Nutrition Examination Survey 2005-2018.
NHANES: National Health and Nutrition Examination Survey; PHQ-9: Patient Health Questionnaire-9; PSD: Post-stroke depression.
Assessment of PSD
Assessment of PSD including: (1) Participants’ stroke status was determined through a question from the NHANES questionnaire: “Has a doctor or other health professional ever informed you that you had a stroke?”[26,27]; (2) Depressive symptoms were subsequently assessed using the PHQ-9[28,29]. Each question offers four response options corresponding to different frequencies: “Not at all”, “Several days”, “More than half the days”, and “Nearly every day”. These responses are scored from 0 to 3, with the total score spanning from 0 to 27 across the nine items. A score of 10 or above is indicative of depressive tendencies[30]; and (3) Finally, participants with both a history of stroke and a PHQ-9 score of 10 or above were defined as the PSD cohort[31].
Assessment of WWI
Certified health technicians collected weight and body measurement data within the mobile examination unit. To ensure accurate weight measurement, participants were instructed to remove their shoes and outer clothing. WC was measured by marking a horizontal line above the superior lateral border of the right iliac crest, extending it to the right mid-axillary line. A tape measure was then aligned at the intersection of these two lines. The WWI was calculated by dividing the WC (in centimeters) by the square root of the participant’s weight (in kilograms)[22,25].
Covariate assessments
Several key potential covariates were selected based on previous studies, including age (as a continuous variable), sex (male or female), and race/ethnicity (non-Hispanic White, non-Hispanic Black, Mexican American, other Hispanic, or other races), education level (< high school, high school, > high school), poverty ratio (0 to 1.5, 1.5 to 3.5, > 3.5), BMI (underweight < 18.5, normal 18.5 to < 25, overweight 25 to < 30, or obese ≥ 30 kg/m²), smoking status (former, never, current), alcohol consumption (former, heavy, light, moderate, never), hyperlipidemia (yes or no), hypertension (yes or no), heart failure (yes or no), Healthy Eating Index (HEI) score (as a continuous variable), and physical activity (measured in Metabolic Equivalent of Task units as a continuous variable).
Statistical analysis
Weighted analyses were performed in accordance with NHANES analytical guidelines. In the baseline analysis, the study population was characterized by continuous variables (mean ± SE) and categorical variables (percentage). Continuous variables were analyzed using Student’s t-test, while categorical variables were assessed using the χ2 test. In this study, a 1:2 propensity score matching (PSM) method was employed to achieve balance between cases and controls[32-34]. In the multivariate logistic regression analysis, WWI was considered a continuous variable. Subsequently, WWI was stratified into tertiles and treated as a categorical variable. Weighted multivariate logistic regression models were utilized to examine the association between WWI and PSD prevalence, with adjustments for various covariates. Three models were developed. Model 1 was unadjusted for confounding factors. Model 2 was adjusted for age, sex, race, poverty ratio, education, marital status, alcohol consumption, and smoking status. Model 3 was adjusted for age, sex, race, poverty ratio, education, marital status, diabetes, hypertension, hyperlipidemia, heart failure, HEI score, and physical activity. To explore the potential non-linear relationship between WWI and PSD, restricted cubic spline (RCS) analysis was performed for smoothing curve fitting. Finally, subgroup analyses were performed stratified by age, sex, race/ethnicity, education level, household income, smoking status, alcohol consumption, diabetes, hypertension, hyperlipidemia, and heart failure, both before and after PSM.
RESULTS
Baseline characteristics of NHANES participants (2005-2018)
Table 1 presents the baseline characteristics of NHANES participants with and without PSD from 2005 to 2018. A total of 33115 participants were included, among which 228 were diagnosed with PSD, representing 0.7% of the cohort. The mean age was 59.2 years and 49.3 years, respectively, in the PSD and non-PSD groups. The proportion of females was higher in the PSD group compared to the non-PSD group (60% vs 40%). In the PSD group, 36% of participants had an educational attainment below high school, compared to 24% in the non-PSD group. Smoking and alcohol consumption were more prevalent in the PSD group (42% vs 21% and 33% vs 16%), respectively. The prevalence rates of hyperlipidemia and hypertension in the PSD group were 84% and 80%, respectively, compared to 70% and 42%, respectively, in the non-PSD group. The mean WWI in the PSD group was 11.55, significantly higher than 11.06 in the non-PSD group. Table 2 demonstrates that after PSM, a total of 576 participants were retained, with 192 in the PSD group and 384 in the non-PSD group. After PSM, although the PSD and non-PSD groups were similar in age, sex, race/ethnicity, education level, marital status, and poverty ratio, WWI continued to differ between the two groups. The mean WWI in the PSD group was 11.96, notably higher than 11.41 in the non-PSD group.
Table 1 Characteristics of the study population from National Health and Nutrition Examination Survey 2005-2018 before matching, n (%).
Characteristic
Overall (n = 33115)
Non-PSD (n = 32887)
PSD (n = 228)
P value
Age (years)
49.4 (17.7)
49.3 (17.7)
59.2 (12.7)
< 0.001
Sex
0.013
Female
16806 (51)
16670 (51)
136 (60)
Male
16309 (49)
16217 (49)
92 (40)
Race
0.006
Non-Hispanic White
14148 (43)
14035 (43)
113 (50)
Non-Hispanic Black
7071 (21)
7009 (21)
62 (27)
Mexican American
5214 (16)
5192 (16)
22 (9.6)
Other Hispanic
3165 (9.6)
3150 (9.6)
15 (6.6)
Other race
3517 (11)
3501 (11)
16 (7.0)
Poverty ratio
< 0.001
< 1.3
9334 (31)
9223 (31)
111 (53)
1.3-3.5
11557 (38)
11476 (38)
81 (39)
> 3.5
9481 (31)
9465 (31)
16 (7.7)
Education
< 0.001
Below high school
7977 (24)
7895 (24)
82 (36)
High school
7643 (23)
7579 (23)
64 (28)
Over high school
17471 (53)
17389 (53)
82 (36)
Marital status
< 0.001
Married/living with partner
19894 (60)
19791 (60)
103 (45)
Never married
5983 (18)
5949 (18)
34 (15)
Widowed/divorced/separated
7221 (22)
7131 (22)
90 (40)
Smoke
< 0.001
Former
8042 (24)
7978 (24)
64 (28)
Never
18189 (55)
18120 (55)
69 (30)
Now
6868 (21)
6773 (21)
95 (42)
Alcohol
< 0.001
Former
5190 (16)
5121 (16)
69 (33)
Heavy
6588 (21)
6551 (21)
37 (18)
Mild
10771 (34)
10717 (34)
54 (26)
Moderate
4994 (16)
4966 (16)
28 (13)
Never
4543 (14)
4521 (14)
22 (10)
BMI
< 0.001
Obese (30 or greater)
12614 (38)
12493 (38)
121 (53)
Overweight (25 to < 30)
11011 (33)
10952 (33)
59 (26)
Normal (18.5 to < 25)
8956 (27)
8912 (27)
44 (19)
Underweight (< 18.5)
502 (1.5)
498 (1.5)
4 (1.8)
DM
< 0.001
DM
6088 (19)
5993 (18.6)
95 (41.3)
Pre-diabetes
2721 (8.4)
2708 (8.4)
13 (5.7)
No
23693 (73)
23573 (73)
120 (53)
Hypertension
< 0.001
No
19132 (58)
19087 (58)
45 (20)
Yes
13980 (42)
13797 (42)
183 (80)
Hyperlipidemia
< 0.001
No
10067 (30)
10030 (30)
37 (16)
Yes
23047 (70)
22856 (70)
191 (84)
Heart failure
991 (3.0)
939 (2.9)
52 (23)
< 0.001
HEI 2015
50.77 (13.74)
50.79 (13.74)
46.74 (12.35)
< 0.001
MET
4402 (6469)
4409 (6476)
2848 (4289)
0.007
WWI
11.06 (0.85)
11.06 (0.85)
11.55 (0.75)
< 0.001
Table 2 Characteristics of the study population from National Health and Nutrition Examination Survey 2005-2018 after matching, n (%).
Table 3 illustrates the relationship between WWI and PSD across multivariate regression models. Model 1 (unadjusted for confounding factors): WWI was significantly associated with the incidence of PSD. In the unmatched analysis, each unit increase in WWI corresponded to a 2.21-fold increase in the risk of PSD [95% confidence interval (CI): 1.84-2.66, P < 0.0001]. After matching, the risk of PSD increased by 1.43 times (95%CI: 1.09-1.88, P = 0.01). Tertile analysis indicated that compared to Q1 (WWI: 8.11-10.69), Q3 (WWI: 11.44-15.70) significantly increased PSD risk. In the unmatched analysis, the odds ratio (OR) was 6.20 (95%CI: 3.69-10.43, P < 0.0001), and after matching, the OR was 2.25 (95%CI: 1.27-3.97, P = 0.01).
Table 3 Multivariable logistics regression analysis of the association between weight-to-waist index and post-stroke depression.
Model
Characteristic
Unmatching
Matching
OR (95%CI)
P value
OR (95%CI)
P value
Model 1
WWI
2.21 (1.84-2.66)
< 0.0001
1.43 (1.09-1.88)
0.01
WWI category
Q1 (8.11-10.69)
Reference
Reference
Reference
Reference
Q2 (10.70-11.43)
2.29 (1.21-4.32)
0.01
1.58 (0.71-3.52)
0.26
Q3 (11.44-15.70)
6.20 (3.69-10.43)
< 0.0001
2.25 (1.27-3.97)
0.01
Model 2
WWI
1.66 (1.31-2.12)
< 0.0001
1.59 (1.13-2.24)
0.01
WWI category
Q1 (8.11-10.69)
Reference
Reference
Reference
Reference
Q2 (10.70-11.43)
1.59 (0.78-3.24)
0.19
1.73 (0.75-4.03)
0.20
Q3 (11.44-15.70)
3.09 (1.67-5.71)
< 0.001
2.83 (1.45-5.52)
0.003
Model 3
WWI
1.55 (1.05-2.29)
0.03
2.31 (1.36-3.94)
0.003
WWI category
Q1 (8.11-10.69)
Reference
Reference
Reference
Reference
Q2 (10.70-11.43)
2.07 (0.88-4.87)
0.09
4.53 (1.54-13.39)
0.01
Q3 (11.44-15.70)
3.14 (1.19-8.26)
0.02
6.60 (2.08-20.88)
0.002
For Model 2 (partially adjusted for confounding factors: Age, sex, race, poverty ratio, education, marital status, alcohol consumption, and smoking status), in the unmatched analysis, each unit increase in WWI was associated with a 1.66-fold increase in PSD risk (95%CI: 1.31-2.12, P < 0.0001). After PSM, the PSD risk increased by 1.59 times (95%CI: 1.13-2.24, P = 0.01). Tertile analysis demonstrated that the risk of PSD was significantly higher in Q3 compared to Q1. In the unmatched analysis, the OR was 3.09 (95%CI: 1.67-5.71, P < 0.001), and after matching, the OR was 2.83 (95%CI: 1.45-5.52, P = 0.003).
For Model 3 (fully adjusted for confounding factors: Age, sex, race, poverty ratio, education, marital status, diabetes, hypertension, hyperlipidemia, heart failure, HEI score, and physical activity), the association between WWI and PSD remained significant. In the unmatched analysis, each unit increase in WWI was associated with a 1.55-fold increase in the risk of PSD (95%CI: 1.05-2.29, P = 0.03). After matching, the risk of PSD increased by 2.31 times (95%CI: 1.36-3.94, P = 0.003). Tertile analysis demonstrated that the risk of PSD was significantly higher in Q3. In the unmatched analysis, the OR was 3.14 (95%CI: 1.19-8.26, P = 0.02), and after matching, the OR was 6.60 (95%CI: 2.08-20.88, P = 0.002).
Dose-response association between WWI and PSD prevalence
Figure 2 summarizes the results of RCS analysis based on weighted multivariable logistic regression with covariate adjustments. Before PSM, the relationship between WWI and PSD risk exhibited a non-linear pattern. As WWI increased, the risk of PSD gradually rose, peaking at a WWI value of approximately 10.91, after which the risk plateaued. After matching, the relationship between WWI and PSD risk exhibited a similar non-linear pattern. As WWI increased, PSD risk rose until a WWI value of approximately 11.34, after which the risk stabilized.
Figure 2 Restricted cubic spline plot between weight-to-waist index and post-stroke depression before and after matching.
WWI: Weight-to-waist index.
Subgroup analysis before and after matching
Figure 3 demonstrates the results of subgroup analysis. In several unmatched subgroups (e.g., age > 60 years; sex: Female; race: Non-Hispanic Black; education level: Less than high school, college or above; marital status: Married/living with partner; poverty ratio: < 1.3; BMI: Overweight, obese; smoking: Former smoker; alcohol consumption: Moderate drinker; diabetes mellitus: No; hypertension: No; hyperlipidemia: Yes), a significant positive association was observed between WWI and PSD risk. After matching, the significance of the association between WWI and PSD risk diminished in most subgroups, with OR values approaching 1.00. However, in certain subgroups (age > 60 years; sex: Female; race: Non-Hispanic Black; education level: Less than high school; marital status: Married/living with partner; poverty ratio: 1.3-3; BMI: Obese; smoking: Former smoker; alcohol consumption: Moderate drinker; diabetes mellitus: No; hypertension: No; hyperlipidemia: Yes), WWI remained positively associated with PSD risk.
Figure 3 Subgroup analysis before and after matching.
OR: Odds ratio; CI: Confidence interval.
DISCUSSION
In this study, we identified a significant positive association between WWI and the risk of PSD, both in pre- and post-matching analyses. The relationship between WWI and PSD risk demonstrated non-linear characteristics, as revealed by RCS analysis. In several unmatched subgroups, WWI was significantly positively associated with PSD risk. After matching, although this association was attenuated in some subgroups, WWI remained significantly associated with PSD risk in certain subgroups. Although confounding factors may influence the association between WWI and PSD, the potential role of WWI as a risk factor for PSD remains substantial. Overall, this study suggests that WWI, as an emerging indicator of obesity, may play a pivotal role in predicting PSD risk.
Growing evidence indicates that WWI serves as a significant predictor of various diseases. Research has demonstrated a close association between WWI and the incidence of type 2 diabetes mellitus[35]. Furthermore, elevated WWI values are significantly associated with an increased risk of cardiovascular disease[36]. WWI is also closely linked to an increased prevalence of stroke[16], and the incidence of depression is positively correlated with WWI levels, a relationship that has been corroborated by multiple studies in United States adults[37,38]. Moreover, WWI has been found to be positively associated with the occurrence of suicidal ideation[39]. WWI, by accurately reflecting the extent of central obesity, highlights the risk of central obesity independent of body weight[22]. Previous studies have indicated that higher WWI values are generally associated with unfavorable body composition, including high fat content, low muscle mass, and low bone density. Consequently, WWI is regarded as a more intuitive and precise measure of obesity[40]. Recent studies suggest that WWI outperforms traditional BMI and WC. Particularly in cross-ethnic or multicenter studies, WWI has demonstrated more consistent and reliable predictive power for disease occurrence across different racial groups and populations[41].
Abdominal fat, particularly visceral fat, is strongly linked to a state of chronic low-grade inflammation. This inflammatory state exerts direct effects on brain function, particularly in regions involved in mood regulation, through the release of inflammatory mediators such as C-reactive protein, interleukin-6, and tumor necrosis factor-alpha, thereby heightening the risk of depression[42-45]. Therefore, WWI, as an indicator of abdominal fat, may be directly associated with the increased risk of PSD. Moreover, adipose tissue is not merely a site for energy storage but also plays a crucial endocrine role, secreting various hormones and bioactive substances, including leptin, adiponectin, and insulin-like growth factor[46-48]. Central obesity is often accompanied by leptin resistance and reduced adiponectin levels, which may disrupt the balance of neurotransmitter systems, particularly the transmission of serotonin and dopamine, thereby increasing susceptibility to depression[49,50].
Research indicates that central obesity is strongly associated with structural alterations in brain tissue, particularly with reductions in gray matter volume and hippocampal atrophy[51]. The hippocampus, a brain region intimately involved in memory and emotional regulation, is critically associated with the onset of depression when its function declines[52,53]. Moreover, obesity may also disrupt the gut microbiota, thereby impairing the gut-brain axis, a process believed to be one of the potential mechanisms underlying the development of depression[54]. Moreover, chronic low-grade inflammation associated with obesity has been shown to exacerbate neuroinflammation, further impairing brain function and contributing to depression. Additionally, disruptions in the gut-brain axis, through alterations in gut microbiota composition, may influence inflammatory pathways that impact both mood and cognition. Individuals with higher WWI are also more susceptible to developing metabolic diseases, such as diabetes, hypertension, and hyperlipidemia[55]. These diseases, by compromising vascular function, may further impair cerebrovascular health, diminishing blood supply and nutrient delivery to the brain, thereby contributing to mood disorders and cognitive decline[56]. Additionally, individuals with higher WWI often exhibit unhealthy lifestyles, which not only contribute to obesity but are also directly or indirectly associated with the onset of depression[57-59].
Strengths and limitations
This study leveraged the nationally representative NHANES database, which provides a large sample size and encompasses a diverse population. The study introduced the WWI as an innovative indicator for assessing central obesity, providing new perspectives on the relationship between obesity and PSD. Through multivariable logistic regression analysis and PSM, the study minimized the impact of confounding factors, thereby enhancing the robustness of the findings. As this study is cross-sectional in nature, it can only elucidate the association between WWI and PSD, without establishing causality. Future longitudinal studies are warranted to further validate these findings. Although multivariable adjustments were applied, there may still be unmeasured confounding factors, such as genetic predispositions or environmental influences, that could affect the study’s outcomes.
CONCLUSION
In this study, we examined the relationship between WWI and PSD and found that individuals with elevated WWI had a significantly higher risk of developing PSD. Multivariable adjustments and PSM analyses revealed that WWI was associated with an elevated risk of PSD, suggesting that WWI might serve as a useful indicator for assessing the risk of PSD. However, because this study was cross-sectional in nature, causality could not be determined. It is important to note that PSD is often underdiagnosed, particularly in obese stroke patients who may be at higher risk of PSD due to both the physical and psychological impacts of obesity. Early identification of PSD in these individuals is crucial, as timely intervention can significantly improve outcomes. Therefore, healthcare providers should prioritize regular screening for depression in stroke patients, especially those with elevated WWI, to ensure early detection and more effective management of PSD.
ACKNOWLEDGEMENTS
The authors thank all the participants in the National Health and Nutrition Examination Survey for providing data for this study.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Psychiatry
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade A, Grade B
Novelty: Grade A, Grade A
Creativity or Innovation: Grade A, Grade A
Scientific Significance: Grade A, Grade A
P-Reviewer: Wang T S-Editor: Wang JJ L-Editor: A P-Editor: Zheng XM
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