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Association between lipid accumulation products and stress urinary incontinence: a cross-sectional study from NHANES 2005 to 2018

Lipids in Health and Disease volume 23, Article number: 358 (2024) Cite this article

Abstract

Background

Stress urinary incontinence (SUI), a common disorder of the pelvic floor, often results in anxiety, poor quality of life, and psychological issues among its sufferers. The relationship between lipid accumulation products (LAP) and stress-related urine incontinence remains unclear. This research aimed to investigate any possible correlation between the risk of SUI and the level of lipid accumulation products.

Methods

For this cross-sectional research, people with SUI who were 20 years of age or older were recruited using information from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018. A weighted multivariate logistic regression model was used to evaluate the findings. As a potential biomarker, lipid accumulation product levels were sorted among individuals in ascending order and subjected to a trend test (P for trend). Additionally, a nonlinear analysis was conducted using smooth curve-fitting methods. Lipid accumulation products' effectiveness in predicting SUI was evaluated using receiver operating characteristic (ROC) curves. Finally, a subgroup analysis was performed to confirm that the connection between SUI and lipid accumulation products was consistent across all demographic groups.

Results

A thorough survey performed on 14,945 participants indicated that 23.61% of the respondents had SUI. A noteworthy association was observed between higher lipid accumulation product values and a greater probability of SUI in multivariate logistic regression analysis. Specifically, the stratification of lipid accumulation products into quartiles demonstrated a substantial positive correlation between the upper and lower quartiles, as evidenced by an elevated odds ratio for SUI (OR = 1.92; 95%CI 1.51–2.44; P < 0.0001). The subgroup analysis supported link consistency across all cohorts under investigation. Finally, the ROC curve indicated that lipid accumulation products (AUC = 0.67, 95%CI 0.654–0.690) had a superior predictive effect on the likelihood of SUI.

Conclusions

Increased lipid accumulation product values are associated with a higher chance of SUI in adult participants. This suggests that lipid accumulation products could be a valuable marker for detecting SUI, offering new perspectives for its evaluation and treatment.

Background

Stress urinary incontinence (SUI) represents a prevalent condition associated with pelvic floor dysfunction, defined by uncontrollable urine leakage during abdominal pressure-raising movements, including coughing, laughter, and sneezing [1]. Owing to variations in the survey methodologies and study subjects, the worldwide occurrence of SUI varies greatly, ranging from 10 to 70% [1]. The frequency of SUI increases with age, peaks in the 50–60 age group, and subsequently decreases progressively [2]. Between 2017 and 2020, the frequency of SUI in the US was 31% in adult males and 46% in adult women [3, 4]. Patients with SUI often experience anxiety, sadness, a worse quality of life, and mental health issues [5]. Although not fatal, SUI may cause poor self-esteem, diminished quality of life, and social isolation. SUI places a considerable financial strain on the healthcare system, and with the continued aging of the population over the next several decades, these costs are expected to increase [6]. Even though SUI is a prevalent issue, only 25% of people seek or get treatment [7]. Identifying possible risk factors and interventions is crucial for enhancing SUI management.

Common risk factors associated with SUI include childbirth, intense physical exertion, older age, diabetes, and socio-behavioral variables, such as smoking [8]. Moreover, hormonal changes during menopause have been highlighted as significant contributors to the onset of SUI in women [9]. However, these characteristics are insufficient to account for the overall prevalence of SUI. Obesity is regarded as a significant factor that increases the likelihood of developing SUI [10, 11]. Obesity is a complex condition characterized by excessive body fat accumulation. Research indicates a strong link between obesity and various illnesses, including type 2 diabetes, hypertension, obstructive sleep apnoea, and cardiovascular disease [12]. Numerous studies have established a significant link between obesity and SUI. Leslee L. Subak et al.demonstrated that women who are overweight or obese have fewer bouts of urinary incontinence when they lose weight [13]. Additionally, W Stuart Reynolds et al. pointed out that abdominal obesity is a better predictor of SUI occurrence in women than overall obesity [14]. According to reports, the occurrence of urinary incontinence among women with severe obesity could be as high as 60% to 70% [15], whereas in severely obese males, the prevalence can reach 24% [16]. The higher prevalence of urinary incontinence in women with obesity is due to anatomical, hormonal, and reproductive factors [17]. Women have a wider pelvis, shorter urethra, and weaker pelvic floor muscles, making them more vulnerable to increased abdominal pressure [1]. The decline in estrogen levels in postmenopausal women and pelvic floor damage due to childbirth further increase this risk [18].

Obesity is mainly caused by metabolic diseases such as insulin resistance, dyslipidemia, and reduced glucose tolerance [19]. Therefore, stable and reliable markers of obesity are critical. Waist circumference (WC) and body mass index (BMI) are commonly used markers of obesity in clinical practice. Although BMI measures total obesity, it cannot evaluate various body parts, leading some researchers to argue that it is an imprecise and contentious method for estimating the risk of developing certain illnesses and mortality [20, 21]. The assessment of abdominal obesity is conducted through the measurement of WC. However, it does not discriminate between subcutaneous and visceral adipose tissues. The latter represents ectopic fat accumulation, which may lead to insulin resistance (IR) and organ damage [22]. Given the limitations of BMI and WC, other indices such as waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) have been proposed to assess obesity-related risks accurately. However, these indices still need help with differentiating fat types and distribution. Interventions meant to prevent SUI may thus be hampered if body measures such as WC and BMI are the only measures used to determine the prevalence of obesity. Lipid accumulation products (LAP) have recently been identified. Derived from triglycerides (TG) and WC, this sex-specific indicator is a significant marker of various metabolic diseases, including obesity [23, 24]. Kahn (2005) first used LAP to identify cardiovascular risk and demonstrated its superiority over traditional obesity indicators such as BMI and WC [25]. Subsequent research has confirmed the effectiveness of LAP in predicting metabolic syndrome and IR. For example, Wiltgen et al. (2009) showed that LAP is a reliable marker of IR in women with polycystic ovary syndrome [26]. Chiang and Koo (2012) discovered a correlation between LAP and the degree of metabolic syndrome components in the Taiwanese population [27]. Additionally, LAP may be a possible marker for several illnesses, such as type 2 diabetes, infertility, psoriasis, obstructive sleep apnea, metabolic syndrome (MetS), and non-alcoholic fatty liver disease, according to several types of research conducted recently [28,29,30,31,32,33]. Consequently, LAP may be a reliable and precise marker for fat accumulation and metabolic diseases in obese individuals. Given the available data, it is reasonable to assume that this indicator will become more significant for evaluating various diseases in the future.

This study hypothesizes a significant association between LAP and SUI, proposing LAP as an effective predictor. Previous studies that used BMI and WC to assess the relationship between obesity and SUI did not effectively differentiate visceral fat or capture metabolic abnormalities [21, 22]. In contrast, LAP, which combines WC and triglycerides (TG), accurately reflects visceral fat accumulation and metabolic dysfunction [25]. The novelty of this study lies in the systematic exploration of the relationship between LAP and SUI, offering a new approach for the early identification of individuals at high risk.

Methods

Data source and participants

The National Health and Nutrition Examination Survey (NHANES) provides data from a comprehensive nationwide study carried out by the National Centre for Health Statistics (NCHS) to assess the country's health and nutritional conditions were used in this study. The NCHS Research Ethics Review Committee approved all NHANES research methods, and each survey respondent gave informed permission. Data were obtained regarding the participants' examinations, laboratory results, nutrition, and demographics. Public access to all the NHANES research designs and data is available at www.cdc.gov/nchs/NHANEs/. As this study had a cross-sectional design, the results reflect the presence of SUI at a specific point in time rather than new incident cases. NHANES datasets covering 2005–2018 were used in this study. Data on LAP and stress urinary incontinence were analyzed from participants who provided complete information. Initially, 70,190 participants were recruited. Participants aged < 20 years (n = 30,441), those who were pregnant (n = 708), those with incomplete SUI data (n = 5,246), and those with missing LAP data (n = 18,850) were excluded from the study. Ultimately,14,945 people participated in the study (Fig. 1).

Fig. 1
figure 1

Selection flowchart for participants from NHANES 2005–2018

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Exposure and outcome definitions

The definition of the exposure variable was LAP. The following formulae were applied to determine the LAP index: for males, [WC (cm)–65] × [TG (mmol/l)], and [WC (cm)-58] × [TG (mmol/l)] in females [28, 34]. In the NHANES, all participants were initially interviewed at home and underwent physical examinations at the Mobile Examination Centre (MEC) [35]. Trained health technicians measured WC following a standardized protocol described in the NHANES operations manual [36]. WC was measured in centimeters (cm) using a non-stretchable measuring tape placed at the upper edge of the iliac crest. Venous blood samples were collected and processed for serum TG analysis by the NHANES guidelines after participants had fasted for at least 8 h [37]. The TG levels were measured using a Cobas 6000 chemistry analyzer.

In the present study, the prevalence of SUI was assessed using the NHANES, mainly using two questionnaire items that dealt with urinary health. Participants who reported experiencing minor involuntary urine leakage during the previous year as a result of physical activity, such as coughing or exercise, were considered to have SUI.

Assessment of covariates

This study evaluated critical variables including age, gender, ethnicity, educational attainment (under high school, high school, above high school), household income (Poverty-to-Income Ratio (PIR): < 1.3, 1.3–3.5, > 3.5) [38, 39], marital status (widowed, married, cohabiting, single, divorced, separated), smoking status (current smokers, non-smokers, former smokers with ≥ 100-lifetime cigarettes) [40], alcohol consumption (≥ 12 drinks/year, non-consumers) [41], vigorous physical activity, moderate physical activity, number of vaginal deliveries (0, 1–2, 3–4, ≥ 5) [42], history of cesarean deliveries (yes, no), ever used female hormones (yes, no), diabetes mellitus (diagnosed by physician, fasting glucose ≥ 126 mg/dL, HbA1c > 6.5%, anti-diabetic medication) [43], hypertension (diagnosed by physician, medication, blood pressure > 140/90 mmHg) [44], and high cholesterol. If a participant had a total cholesterol reading of 240 mg/dL or over, was taking medication for hypercholesterolemia, or received a medical diagnosis of high cholesterol, they were considered high cholesterol [45]. Moreover, physiological markers such as total cholesterol and low-density lipoprotein were added. The Patient Health Questionnaire-9 (PHQ-9) was primarily used to evaluate depression; a score of ≥ 10 was deemed depressive [46, 47].

Statistical analysis

The NHANES sample weights were included in the statistical analyses that adhered to the recommendations of the Centers for Disease Control and Prevention (CDC). The mean with standard error (SE) was shown for continuous variables, whereas percentages were used for categorical data. Differences between groups split by LAP (quartiles) were assessed using either a weighted chi-square test (for categorical variables) or a weighted Student's t-test (for continuous variables). The relationship between LAP and SUI was examined using three multivariate logistic regression models. The covariate modifications varied across the models: Model 1 had no covariate alterations, whereas Model 2 adjusted for sex, age, and race. In contrast, Model 3 was adjusted for age, educational attainment, ethnicity, family income ratio, smoking habits, marital status, alcohol use, diabetes, hypertension, high cholesterol, moderate physical activity, vigorous physical activity, number of vaginal deliveries, history of cesarean deliveries, depression, history of female hormone use.

Furthermore, LAP was classified into quartiles based on continuous measures, which allowed for identifying potential relationships with SUI using a trend test. Threshold effect analysis and smooth curve fitting techniques were used to evaluate the nonlinear correlations. The study used stratified subgroup analysis to investigate heterogeneity within the subgroups. The efficiency of LAP, High-Density Lipoprotein Cholesterol (HDL-C), Low-Density Lipoprotein Cholesterol (LDL-C), and Triglycerides (TG) in determining individuals with SUI and their prevalence were examined using receiver operating characteristic (ROC) analysis. The statistical analyses were conducted using Empower and R software (version 3.4.3) from The R Foundation. A value of P > 0.05 was deemed statistically significant.

Results

Characteristics of the participants

The research had 14,945 participants, with 47.98 ± 16.78 years as their average age. Of the participants, 50.10% were female, and 49.90% were male. Table 1 shows the demographic features and other covariates grouped according to LAP quartiles. Of the participants, 23.61% self-reported having had SUI in the past. A significant increase in SUI prevalence was associated with higher LAP categories. Furthermore, Individuals in the top LAP quartile had a higher likelihood of being white, having a higher level of education, being married or cohabiting, having higher rates of household poverty, drinking alcohol, being free of diabetes, having high cholesterol levels, having elevated blood pressure, be less physically active, have never had a cesarean delivery, and have never used female hormones.

Table 1 Basic characteristics of participants by LAP among US adults
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Table 2 lists the patients' clinical characteristics according to the existence or lack of SUI. The presence or absence of SUI was significantly correlated with age, gender, race, educational attainment, diabetes, hypertension, smoking habits, alcohol use, marital status, family poverty ratio, high cholesterol, physical activity, number of vaginal deliveries, depression, history of using female hormones, LDL-C, TC, and the LAP (P < 0.05).

Table 2 Base characteristics of participants with and without SUI in the NHANES 2005–2018 cycles
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Correlation of LAP with the likelihood of SUI

Table 3 shows the relationship between LAP and the likelihood of developing SUI. For a more accurate evaluation of the association, weighted multivariate logistic regression was used, with models adjusted using a tiered approach: unadjusted (Model 1), partially adjusted (Model 2), and wholly adjusted (Model 3). According to this study, as LAP values increased, there was a discernible increase in the prevalence of SUI.

Table 3 Associations between LAP and Stress Urinary Incontinence
Full size table

A highly significant positive association (P < 0.0001) between SUI prevalence and LAP was observed in fully adjusted model 3. To conduct a regression analysis with LAP as a continuous variable, a natural log transformation was applied to normalize its non-normal distribution. This means that following the ln LAP transformation, there is a 44% higher likelihood of receiving SUI for each unit increase in the ln LAP index. Further sensitivity analysis validated this finding by treating LAP as a categorical variable divided into quartiles. In Model 3, the top LAP quartile (Q4) exhibited a statistically significant 92% higher likelihood of SUI compared to the bottom quartile (Q1) (OR = 1.92, 95% CI 1.51–2.44, P < 0.0001). Likewise, for Models 1 and 2, the probability of SUI rose by 112% (OR = 2.12, 95% CI 1.90–2.37, P < 0.0001) and 118% (OR = 2.18, 95% CI 1.91–2.48, P < 0.0001) in Q4 relative to Q1, respectively.

Smoothed curve fitting was used to investigate the correlation between SUI and LAP. The results showed a consistent and statistically significant positive connection between SUI and LAP (Fig. 2). Threshold effect studies were conducted to clarify this connection (Table 4). According to the log-likelihood ratio test (P = 0.014), the two piecewise linear models differed significantly. The inflection point of the LAP-SUI relationship at an LAP of 10.78 is in Table 4. Below this threshold, the OR was 1.16 (95% CI: 1.03–1.32); above this threshold, the OR was 1.01 (95% CI: 1.00–1.01). This suggests that the prevalence of SUI is differentially affected by LAP below and above this level; however, the effects are all strongly positive.

Fig. 2
figure 2

Smooth curve fitting for the relationship between LAP and SUI. The solid red line represents the smooth curve fit between variables. Blue bands represent the 95% confidence interval from the fit

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Table 4 Threshold effect analysis of LAP on SUI using a linear regression model
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Subgroup analysis

Subgroup analyses and interaction tests were used to investigate how population stratification factors affected the relationship between LAP and SUI (Fig. 3). Within distinct subgroups, favorable correlations between LAP and SUI persisted. No significant interactions were found across the different categories, indicating these factors did not affect the positive association. This confirms the link's consistency across cohorts (all P-values for interaction > 0.05).

Fig. 3
figure 3

Subgroup analysis of the association between LAP and SUI

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Predictive value of LAP for the SUI

ROC curves evaluated the predictive value of LAP and traditional lipid measures (TG, LDL-C, and HDL-C) for SUI. It was shown that LAP (AUC = 0.672, 95%CI 0.654 – 0.690) more accurately predicted the likelihood of SUI than individual lipid markers (Fig. 4). Furthermore, the AUC values for LAP were significantly different from those of the individual lipid markers (all P < 0.05), indicating that LAP may be a valuable tool for assessing SUI.

Fig. 4
figure 4

ROC curves of the LAP and conventional lipid indicators about SUI

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Discussion

This research examined the association between LAP and SUI prevalence in individuals 20 years of age and older using the NHANES data from 2005 to 2018. According to the findings, the higher the LAP number, the greater the chance of SUI. The positive connection persisted when LAP was transformed into a categorical variable using quartiles (Q1–Q4). Furthermore, ROC curves demonstrated that LAP was a more reliable predictor of SUI than TG, HDL-C, and LDL-C, which are conventional blood lipid indicators. Subgroup analysis proved that the stability of the LAP and SUI was unaffected by any of the stratification factors and that the positive connection persisted.

Previous research has demonstrated that abdominal obesity is associated with a more significant occurrence and severity of SUI [48]. Individuals with SUI have a greater inclination towards obesity [49]. Urinary incontinence may be caused by obesity due to fat accumulation in the central region of the body. This fat buildup increases the pressure inside the abdomen, thereby increasing the strain on the bladder. This can result in SUI and worsen the detrusor instability. Secondly, obesity is linked to diabetes and inflammation, both of which increase the likelihood of urine incontinence [17].

BMI is commonly utilized in epidemiological studies to assess an individual’s level of obesity. However, its use in determining body fat distribution is limited. It cannot differentiate between subcutaneous and visceral adipose tissue storage or lean and fat mass [50]. Research indicates that visceral adipose tissue and low lean mass are linked to a higher risk of SUI, regardless of BMI [51]. Second, obesity can be categorized into two primary forms: systemic and central obesity [52]. A broader understanding of obesity-related health issues could be achieved by considering central obesity. WC is the simplest and most common metric for assessing central obesity in medical settings. However, it cannot differentiate between visceral and subcutaneous fat [53]. Thus, researchers have discovered an obesity paradox when considering BMI and WC as indices for measuring obesity paradox [54]. Using visceral obesity markers is theoretically a more precise and efficient way to measure SUI. Computed tomography (CT) and magnetic resonance imaging (MRI) are the most precise techniques to determine visceral fat. However, because the required techniques are highly specialized and costly, their use as preferred indications for measuring visceral fat is restricted [55]. Thus, it is imperative to develop a practical and affordable technique for evaluating visceral obesity. Recently, LAP, derived from a combination of blood biomarkers and anthropometric measurements, has emerged as a novel tool for evaluating obesity, demonstrating high accuracy in detecting visceral obesity [56]. Initially proposed by Professor Kahn, LAP is computed using TG and WC values and is set based on gender. It is thought to have a stronger association with the metabolic state and can provide a valuable evaluation of visceral adipose tissue [25, 57]. Furthermore, obesity indicators that combine anthropometric and metabolic parameters may provide a more accurate picture of the onset and progression of obesity. LAP is a measure of central fat accumulation proven more effective than BMI in predicting the risk of renal function decline, IR, hypertension, diabetes, cardiovascular disease, and MetS [58,59,60]. Although there is a specific association between obesity and SUI, most studies rely on BMI, which does not accurately assess visceral fat. As a newer indicator, LAP more accurately reflects visceral fat and provides a better basis for evaluating the obesity-SUI relationship.

Obesity may cause metabolic problems, inflammation, and damage to many target organs due to an imbalance in adipose components [57]. Research indicates that obesity is a primary factor in SUI [61]. Elevated levels of central obesity result in elevated intra-abdominal pressure, insulin resistance, oxidative stress, and inflammatory responses. These factors may induce damage to the pelvic floor arteries, malfunction of the sphincter, and forced urination, which are possible causes of SUI [62].

Increased visceral adipose tissue contributes to low-grade systemic inflammation [63], and this persistent inflammation may also affect the adipocytes surrounding the bladder, resulting in SUI. Visceral adipose tissue functions as an endocrine organ and obesity can disrupt its regulation. White adipose tissue, which makes up the majority of visceral tissue, can secrete adipokines, which encourage the release of inflammatory cytokines that are important in bladder dysfunction [64], including interleukin-6, tumor necrosis factor α, reactive oxygen species (ROS), and C-reactive protein [65]. Increased ROS and inflammatory factor levels can harm motor, visceral autonomic, and pelvic floor neurons [66]. They may also harm the epithelial cells of the bladder and urethra, decrease bladder compliance [67], and obstruct blood flow in the submucosal vessels [68]. Second, human transverse urethral sphincter cells' myogenic development is inhibited by the inflammatory cytokine Tumor Necrosis Factor-alpha (TNF-α), indicating that TNF-α may raise the likelihood of SUI in older adults [69]. Adipose tissue-induced oxidative stress is also thought to cause metabolic abnormalities in pelvic fibroblasts. Research has indicated that elevated levels of oxidative stress lead to the upregulation of proteolytic enzymes, which in turn promote collagen degradation [68], thereby causing pelvic floor vascular damage and detrusor and sphincter sclerosis [70, 71], which could increase the prevalence and severity of incontinence.

Furthermore, visceral fat generates higher levels of free fatty acids than subcutaneous fat, increasing the possibility of insulin resistance [72]. This is because macrophages accumulate in visceral adipose tissue and emit many inflammatory cytokines, which reduce insulin sensitivity [73]. Consequently, obesity-related chronic inflammation may worsen IR, which negatively affects lipid ratios by increasing the blood levels of triglycerides and LDL-C cholesterol and decreasing HDL-C cholesterol [74, 75]. These unhealthy cholesterol ratios can lead to atherosclerotic plaque buildup in the bladder wall, causing urothelial dysfunction, bladder wall ischemia, and an increased risk of SUI [76].

However, weight gain caused by obesity may increase the pelvic floor and bladder muscle strain. Over time, this additional weight may eventually lead to overstretching of the pelvic floor muscles and weakening the muscles and their ability to sustain urine control. The urethral sphincter may relax because of weak pelvic floor muscles, which raises the possibility of unintentional urine leaks during coughing or sneezing [77,78,79]. Furthermore, obesity may result in the buildup of abdominal fat, thereby increasing intra-abdominal pressure. Chronically high intra-abdominal pressure may harm the pelvic muscles and nerve supply, which can atrophy and distort the pelvic floor muscles, resulting in pelvic floor weakness and dysfunction [80, 81]. Increased intra-abdominal pressure may worsen the relaxation of the urethral sphincter, making it more challenging to regulate the release of urine and increasing the likelihood of SUI [71].

Study strengths and limitations

The study had several advantages. First, A nationally representative NHANES sample was utilized to establish a connection between LAP and SUI. When analyzing the NHANES data, sample weight was considered to increase the study's representativeness. Second, the participant groups were stratified, and the consistency of the findings was confirmed due to the large sample size. Furthermore, adjustments were made to other confounding factors to improve the dependability of the data. While the study yielded significant results, its limitations must be recognized. First, medical information related to SUI was self-reported via interview replies owing to the inherent constraints of the SUI questionnaire design in the NHANES database, which could have resulted in an underestimation of the number of SUI cases. Second, even if many variables were considered, it is possible that additional confounding variables had an impact. Furthermore, the cross-sectional design of the study precluded establishing causation. A thorough prospective investigation is needed to validate this study's conclusions.

Conclusions

This study is the first to systematically investigate the association between LAP and SUI, demonstrating that elevated LAP levels significantly increase the risk of SUI. These findings suggest that LAP could serve as an effective tool for the early screening of SUI, thereby enabling clinicians to develop more targeted treatment strategies. Early identification of patients with elevated LAP, particularly those with central obesity and metabolic abnormalities, may facilitate the optimization of personalized interventions, such as reducing intra-abdominal pressure through weight management and metabolic regulation. As an indicator of visceral fat, LAP provides a more accurate reflection of metabolic health than traditional obesity measures, offering valuable insights for early intervention and long-term management of SUI. Future research should focus on evaluating the longitudinal predictive value of LAP and its potential to guide therapeutic strategies to reduce the incidence and burden of SUI. Additionally, LAP holds promise for large-scale screening and prevention efforts in public health, potentially mitigating the health burden associated with obesity.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

NHANES:

National Health and Nutrition Examination Survey

LAP:

Lipid accumulation products

SUI:

Stress urinary incontinence

WC:

Waist circumference

ROC:

Receiver operating curve

AUC:

Area under curve

OR:

Odds ratio

CI:

Confidential interval

IR:

Insulin resistance

PIR:

Income-to-Poverty ratio

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Acknowledgements

We are grateful to the National Health and Nutrition Examination Survey for the data provided and to all participants for their selfless dedication.

Funding

This study was supported in part by grants from the Natural Science Foundation of Guangdong Province (2020A1515010541).

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Authors and Affiliations

  1. Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, China

    JiHang Li, Dong Wang, Hu Tian, JianKun Yang, Hui Xia & WenBin Guo

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  1. JiHang Li
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  2. Dong Wang
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Contributions

JHL designed the research. JHL, DW, and HT collected, analyzed the data, and drafted the manuscript. HX, WBG, and JKY revised the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to JianKun Yang, Hui Xia or WenBin Guo.

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Ethics approval and consent to participate

The portions of this study involving human participants, human materials, or human data were conducted by the Declaration of Helsinki and were approved by the NCHS Ethics Review Board. The patients/participants provided their written informed consent to participate in this study.

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The authors declare no competing interests.

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Li, J., Wang, D., Tian, H. et al. Association between lipid accumulation products and stress urinary incontinence: a cross-sectional study from NHANES 2005 to 2018. Lipids Health Dis 23, 358 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12944-024-02350-3

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Keywords

Lipids in Health and Disease

ISSN: 1476-511X