The Development and Evaluation of 9 Obesity-Based Index for Gallstones in U.S. Adults

doi:10.21203/rs.3.rs-4344114/v1

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The Development and Evaluation of 9 Obesity-Based Index for Gallstones in U.S. Adults

https://doi.org/10.21203/rs.3.rs-4344114/v1

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Objective: Gallstones have gradually become a highly prevalent digestive disease worldwide. This study aimed to investigate the association of nine different obesity-related indicators (BRI, WWI, BMI, WC, LAP, CMI, VAI, AIP, TyG) with gallstones and to compare their predictive properties for screening gallstones.

Methods: Data for this study were obtained from the National Health and Nutrition Examination Survey (NHANES) for the 2017-2020 cycle, and weighted logistic regression analyses with multi-model adjustment were conducted to explore the association of the 9 indicators with gallstones. Subject working curves were analyzed to assess the screening ability of the 9 indicators. In addition, variation in the relationship between the two indicators with the most predictive power and gallstones was described by restricted cubic spline.

Results: In total, 3698 participants were involved in the final analysis and 392 (10.6%) carried gallstones. The results of weighted multifactorial logistic regression analysis indicated that BRI, WWI, BMI, WC, LAP, and CMI were independent risk factors for gallstones. The ORs and confidence intervals for the highest quartile were 3.21 (1.55-6.28) for BRI, 2.26 (1.01-5.05) for WWI, 2.83 (1.48-5.39) for BMI, 2.83 (1.54-5.22) for WC, 2.39 (1.22-4.69) for LAP, 2.03 (1.19-3.46) for CMI. The area under the ROC curve for BRI was 0.67. The Delong test compared the performance of different ROCs and revealed that the difference between the area under the curve of BRI and the other metrics was significant (P<0.05), except for WWI.

Conclusion: BRI, WWI, BMI, WC, LAP, and CMI were essential indicators for recognizing gallstones. By comparison, we realized that BRI was a better predictor of gallstones.

Obesity

Screening indicators

Gallstones

NHANES

BRI

Gallstones are a globally common disease of the biliary system, with a worldwide prevalence of approximately 6%-15% in the 21st century ^{[1, 2]}. With rising living standards (multifactorial factors such as dietary changes) and an aging population, the gallstone patient group is expanding, resulting in an enormous economic and health burden globally ^[3]. Nearly 10–20% of the U.S. adult population suffers from gallstones, and total annual healthcare expenditures for biliary tract disorders amount to a staggering $10.3 billion ^[4]. Not only can gallstones trigger acute or chronic body inflammation(cholecystitis, cholangitis, pancreatitis), but they even increase the risk of gallbladder cancer and are associated with an increasing mortality threat ^{[5, 6]}. In recent years, emerging research has revealed that gallstones may be a risk factor for a patient's susceptibility to other systemic diseases, such as diabetes mellitus ^[7], cardiovascular diseases ^{[8, 9]}, renal cancer, and colorectal cancer ^{[10, 11]}. Therefore, it is crucial to screen for effective indicators to predict the occurrence and progression of gallstones.

Obesity is usually defined as a metabolic disorder characterized by excessive accumulation and/or abnormal distribution of body fat. The prevalence of obesity has risen rapidly in recent years, and even during pandemics, its rates are still steadily increasing. Currently, approximately 70.2% of the U.S. adult population remains overweight or obese ^[12]. Epidemiologic research has found that the prevalence of gallstone disease is on the rise with the increase in obese populations ^{[13, 14]}. A Mendelian study by Yuan et al. demonstrates from a genetic perspective that a genetic vulnerability to obesity facilitates the development of symptomatic gallstones ^[15]. Body mass index (BMI) is a well-known indicator to define obesity and is widely adopted in health examinations and clinical studies. Nevertheless, it is worth noting that traditional indicators such as BMI and waist circumference (WC) cannot properly reflect the distribution of body fat, the accumulation of visceral fat, and the metabolism of glucose and lipids. In recent years, researchers have developed new screening tools based on BMI, WC, lipid, and glucose indices to better reflect the characteristics associated with obesity from multiple perspectives. For example, the Lipid Accumulation Product (LAP) and the Visceral Adiposity Index (VAI) are better indicators of body fat distribution and visceral fat accumulation states, with gender-specific options for calculation ^{[16, 17]}. The body roundness index (BRI), which models the human body as an ellipse and employs the theory of eccentricity to construct a formula, can also reflect the degree of visceral fat accumulation ^[18]. The weight-corrected waist circumference index (WWI) has the strength to reflect both fat and muscle mass, and it has been proposed to reflect "true obesity" in metabolically unhealthy conditions ^[19]. The cardiometabolic index (CMI) was proposed by Wakabayashi et al. as a modification of the LAP formula, which integrates abdominal obesity and lipid levels. The atherogenic index of plasma (AIP) is another composite index of lipid levels ^[20]. The triglyceride-glucose index (TyG) is characterized as a more effective indicator of insulin resistance ^[21].

Despite several studies investigating the correlation between some anthropometric indices (BMI, WC, WWI) and gallstone disease ^{[22, 23]}, it remains difficult to identify the best predictor. In this study, we compared the novel developed screening tool with traditional indicators, comprehensively evaluated the predictive potential of nine measures related to obesity for the risk of gallstone disease, and attempted to identify the method with the most screening power, intending to provide new perspectives for the prediction and diagnosis of gallstone disease in clinical practice.

Study Design and Participants

The survey data utilized in this study originated from individuals who enrolled in the U.S. National Health and Nutrition Examination Survey (NHANES) during the cycle of January 2017 to March 2020. The NHANES is an ongoing epidemiological survey program conducted by the Centers for Disease Control and Prevention (CDC) to assess the health and nutritional conditions of the U.S. population ^[24]. It relies on a complex multi-stage probability sampling strategy to collect information from a nationally representative sample through standardized household interviews, health screenings, and laboratory tests ^[25]. The survey was approved by the Ethics Review Board of the National Center for Health Statistics (NCHS), and all participants voluntarily participated and signed an informed consent form. More information is available free of charge on the NHANES website (https://www.cdc.gov/nchs/nhanes/index.htm).

A total of 15,560 participants were enrolled in the 2017–2020 cycle of NHANES. We sequentially excluded individuals who were younger than 20 years, pregnant, lacked information on nine body measurements (BMI, WC, LAP, VAI, BRI, WWI, CMI, AIP, TYG), missing information on gallstones, and missing information on covariates. A total of 3698 subjects were ultimately selected for analysis. The detailed process of participant screening is illustrated in Fig. 1.

Definition of 9 obesity-related screening indicators and gallstones:

In this study, the 9 screening measures associated with obesity include BMI, WC, LAP, VAI, BRI, WWI, CMI, AIP, and TyG. The formulas for their calculation are summarized in Fig. 2. Data related to body measurements (BMI, weight, height, and WC) were collected by trained professional technicians at the mobile examination center according to standardized protocols. In addition, HDL-C, TG, and FPG data, which are the other indicators required in the formula, were analyzed by the University of Minnesota laboratory under strict surveillance and quality management. HDL-C, FPG, and TG were measured by turbidimetric immunoassay, hexokinase (HK) assay, and automated direct chemiluminescence analyzer, respectively.

For the definition of gallstones, participants were interviewed by a well-trained specialized interviewer who asked the question, "Has a doctor or other health professional ever diagnosed you with gallstones?" The answer to this question was the basis for determining whether or not a person suffered from gallstones. This convenient and rapid approach has been utilized in previous studies ^{[23, 26]}.

Covariates:

To explore the association between the 9 measures and gallstones, we considered several confounders to be incorporated as covariates. Demographic information includes: age (≤ 40, over 40), sex, race (Mexican American, non-Hispanic white, non-Hispanic black, etc.), marital status, and education level (less than high school, high school or equivalent, and college or above). For smoking status, we categorized them into three groups depending on the self-reported questionnaire: never smokers, former smokers, and current smokers. Hypertension was recognized when any of the following conditions were satisfied: 1. Three consecutive diastolic pressures ≥ 90 mmHg and/or systolic pressures ≥ 140 mmHg. 2. self-reported or informed by a healthcare provider that they had hypertension. Diabetes mellitus was diagnosed according to the following criteria: glycosylated hemoglobin ≥ 6.5% or fasting blood glucose level ≥ 7.0 mmol/L or self-reported diagnosis of diabetes by a healthcare provider. Hypercholesterolemia was based on laboratory-measured cholesterol levels (≥ 6.2 mmol/L). More detailed descriptions of the above-mentioned covariates are publicly accessible online at the NHANES website.

Statistical analysis

All data analyses for this study were performed in strict accordance with CDC guidelines. To provide nationally representative effect estimates, we applied the recommended sample weights (WTSAFPP). Different presentation methods were adopted depending on the type of data, with continuous variables expressed as weighted means ± standard error (SE) and categorical variables as weighted proportions ± SE. In the comparison of patients with non-gallstones and gallstones, weighted linear regression was employed for the continuous variables, and weighted chi-square tests were applied to the categorical variables. To explore the relationship between 9 obesity-related screening indicators and gallstones, weighted logistic regression was applied to analyze their performance in 3 different models. Model 1 remained unadjusted, model 2 was corrected for age, sex, and race, and model 3 was further adjusted for marital status, educational attainment, smoking, hypertension, diabetes, and hypercholesterolemia. To determine the robustness of the results, we analyzed the independent variables in both continuous and categorical forms for their association with gallstone disease. We also plotted subjects' work characteristics (ROC) curves and computed the area under the curve (AUC) values to evaluate the predictive power of the different indicators. Furthermore, bootstrap resampling (carried out 500 times) was conducted as a sensitivity analysis to assess the stability of AUC. After the identification of the two most predictive indicators, restrictive cubic bars were developed to visualize their association with the risk of gallstones. A comparison of the variability of AUC between the different screening parameters was performed using the Delong test. Statistical differences existed when the p-value obtained from the significance test was less than 0.05. All analyses were performed using EmpowerStats and R4.3.2.

3.1 Participants' baseline characteristics

As illustrated in Fig. 1, a total of 3698 participants were ultimately included in the analysis. The baseline characteristics of participants with or without gallstones were summarized in Table 1. There were 392 participants with gallstones and a total of 3306 participants without gallstones, with a prevalence of 10.6%. The results of the analysis of differential comparisons suggested that there were more women in the gallstone group and a higher percentage of the population over 40 years of age. In addition, there were significant differences in race, hypertension, diabetes mellitus, height, fasting glucose, and nine obesity-related indicators between the two groups.

Table 1

Baseline characteristics of participants.
	Non-gallstone		Gallstone		P value
	Mean/%	SE	Mean/%	SE
Age, %					< 0.0001
≤ 40 years	39.39	1.74	17.92	2.74
40–80 years	60.61	1.74	82.08	2.74
Sex, %					< 0.0001
Male	52.2	1.2	25.3	3.59
Female	47.80	1.2	74.77	3.59
Race, %					0.0023
Mexican American	9.37	1.43	7.86	1.20
Non-Hispanic White	61.83	2.35	69.28	3.00
Non-Hispanic Black	11.85	1.57	5.32	0.95
Other Race	16.95	1.43	17.54	2.73
Marital status, %					0.02
Married/Living with Partner	61.78	2.58	62.10	3.78
Widowed/Divorced/Separated	18.34	1.37	23.90	3.08
Never married	19.88	1.78	14.00	2.31
Education level, %					0.4887
Less than high school	96.34	0.75	95.66	1.00
High school graduate/GED or equivalent	1.14	0.45	0.78	0.54
More than high school	2.52	0.41	3.56	0.93
Smoking status, %					0.2504
Never	56.96	1.10	52.42	4.18
Cover	26.72	1.15	32.16	3.7
Current	16.32	1.00	15.42	2.35
Hypertension, %					< 0.0001
Yes	34.80	1.88	54.30	4.17
No	65.2	1.88	45.7	4.17
Diabetes, %					< 0.0001
Yes	14.33	0.95	25.73	2.54
No	85.67	0.95	74.27	2.54
Hypercholesterolemia, %					0.5682
Yes	9.85	0.91	11.32	2.67
No	90.15	0.91	88.68	2.67
Fasting blood glucose, mmol/L	6.04	0.06	6.51	0.09	0.0001
Height, cm	168.70	0.18	164.78	0.82	0.0001
TC, mmol/L	4.80	0.04	4.84	0.09	0.6526
HDL, mmol/L	1.39	0.02	1.40	0.03	0.9764
TR, mmol/L	1.23	0.03	1.35	0.06	0.0644
BMI	29.27	0.20	32.61	0.65	< 0.0001
WC	99.63	0.51	107.06	1.46	< 0.0001
BRI	5.44	0.07	6.84	0.23	< 0.0001
WWI	10.96	0.03	11.44	0.07	< 0.0001
AIP	-0.12	0.01	-0.07	0.02	0.0217
CMI	0.65	0.02	0.77	0.05	0.0135
LAP	50.15	1.35	67.46	3.90	< 0.0001
VAI	1.70	0.05	2.11	0.12	0.0009
TyG	8.48	0.02	8.66	0.04	0.0003

3.2 Association of Nine obesity-related screening indicators and risk of gallstones

The association of the nine indicators with gallstones was explored using weighted multifactorial logistic regression, and the indicators were analyzed as both continuous variables and quartiles. All indicators were significantly associated with gallstone risk in Model 1 and Model 2. However, in Model 3, six indicators, including WWI, BRI, BMI, WC, LAP, and CMI, still showed positive correlations with gallstones. When the independent variables were analyzed as categorical variables, BRI had the highest OR of 3.21 (95%CI: 1.55–6.28). It was followed by BMI (OR = 2.83, 95% CI: 1.48–5.39), WC (OR = 2.83, 95% CI: 1.54–5.22), LAP (OR = 2.39, 95% CI: 1.22–4.69), WWI (OR = 2.26, 95% CI: 1.01–5.05), and CMI (OR = 2.03. 95%CI: 1.19–3.46). Figure 3 visually portrays the relationship between the 9 indicators and the risk of gallstones under the 3 models and the two variable types, and more detailed information on the data can be available in Supplementary file Table 1.

3.3 Predictive value of nine indicators for gallstones

Figure 4 as well as Table 2 provided the AUC levels and 95% confidence intervals for the 9 indexes screening for gallstones in US adults. Specifically, BRI was the most discriminating indicator for gallstones (AUC = 0.6700), followed by WWI (AUC = 0.6612). The excellent thresholds for BRI and WWI were identified as 5.2005 and 11.3549, respectively. Their relationship with gallstones was graphed with restricted cubic spline bars (as shown in Fig. 5). The comparison of the differences in the predictive ability of BRI with other indicators for gallstones by DeLong’s test indicated that the differences in AUC between BRI and other obesity-related screening indicators were statistically significant (P < 0.05), except for WWI ( Table 3 ). For sensitivity analysis, bootstrap resampling analysis supported the robustness of the AUC results (Supplementary file Table 2).

Table 2

Results of ROC analysis of 9 screening tools
	AUC	95%CI low	95%CI up	Best threshold	Specificity	Sensitivity
BRI	0.6700	0.6429	0.6970	5.2005	0.5024	0.7526
WWI	0.6612	0.6346	0.6879	11.3549	0.6376	0.5969
BMI	0.6400	0.6116	0.6684	30.1500	0.6152	0.5944
LAP	0.6389	0.6119	0.6658	49.9302	0.6431	0.5740
WC	0.6371	0.6093	0.6648	101.4500	0.5705	0.6454
VAI	0.6079	0.5802	0.6356	0.9386	0.3717	0.8138
CMI	0.5991	0.5716	0.6267	0.4415	0.4985	0.6684
TyG	0.5918	0.5635	0.6200	8.6134	0.5983	0.5510
AIP	0.5703	0.5423	0.5984	-0.3395	0.2671	0.8597

Table 3

The result of the Delong test
	P value
BRI- WWI	0.3846
BRI-BMI	< 0.001
BRI-LAP	0.0046
BRI-WC	< 0.001
BRI-VAI	< 0.001
BRI-CMI	< 0.001
BRI-TyG	< 0.001
BRI-AIP	< 0.001

To our knowledge, this is the first study to explore the association of 9 obesity-related anthropometric measures with gallstones in the US population. Through cross-sectional analysis with the 2017–2020 NHANES database, we found that the prevalence of gallstones in the U.S. adult population was 10.6%. Although gallstones are a benign surgical condition, they are strongly associated with pancreatitis, NAFLD, cardiovascular disease, and cancer ^[7–11]. Moreover, gallstones significantly increased the risk of death from hepatobiliary (HR = 2.74) and gallbladder (HR = 7.35) cancers ^[6]. Therefore, early prevention and health care through simple body measurements are crucial before clinical disease emerges.

Gallstones are recognized as a common disorder influenced by a combination of genetic and multiple environmental factors, as well as an important cause of hospital admissions for digestive disorders in the U.S. population ^[27]. Its risk factors frequently include advanced age, females, pregnancy, obesity, and race, among which obesity exerts a rather central effect on gallstone formation ^{[14, 15]}. The pathophysiologic mechanisms underlying the increased risk of gallstones due to obesity have not been fully identified. The widely accepted perspective is that obesity promotes excessive cholesterol secretion by the liver, which leads to a relative oversaturation of cholesterol in the bile, thus making gallstone deposits more susceptible to formation ^[28]. Insulin serves an important biological function in mediating obesity and hepatic metabolism, and obesity may lead to increased insulin levels and decreased insulin sensitivity. Higher insulin levels can trigger an increase in cholesterol secretion through both activation of HMG-CoA reductase and upregulation of low-density lipoprotein receptor expression ^[29]. Obesity may also affect gallbladder motility, and although postprandial plasma cholecystokinin (CCK) levels are normal in obese individuals, hyperinsulinemia may mediate a decreased sensitivity to CCK in obese individuals, resulting in decreased motility that is strongly associated with cholestasis ^[30]. Leptin is a hormone released by adipocytes that functions in the regulation of energy homeostasis. In most obese patients, leptin levels are often significantly elevated, but the role of leptin is weakened or disappeared, which is also known as leptin resistance. This is another vital reason why obese patients are prone to form gallstones ^[31]. Leptin can affect stone formation through several mechanisms such as affecting gallbladder contractility and regulating bile acid metabolism ^{[32, 33]}.

Obesity has long been one of the critical pathogenic mechanisms of gallstones, and the effect of obesity-related indicators on screening for gallstones has received extensive attention from researchers. In this study, by analyzing the Nhanes data, we found that the six indicators BRI, WWI, BMI, WC, LAP, and CMI were effective in differentiating among patients with gallstones in American adults. The outcome of the ROC curve analysis implied that BRI was the most predictive parameter. BRI is characterized by the fact that it combines height and waist circumference, which provides a better reflection of the overall adiposity and abdominal fat distribution. Its predictive ability in cardiovascular disease ^[34], colorectal cancer ^[35], diabetes mellitus ^[36], and hyperuricemia ^[37] has been confirmed. In our study, we found that it also distinguished excellently between patients suffering from gallstones. Restricted cubic spline more intuitively reflects the relationship between BRI and gallstones, and we found that the risk of gallstones increased when BRI was greater than 5.2. Another advantage of using BRI as the best predictor is that it is a non-invasive tool that does not require invasive testing procedures, which greatly increases its applicability to gallstone prevention and intervention, providing a more patient-friendly and efficient option. WWI is another novel obesity index that is also an effective indicator for identifying gallstones. A previous study found that WWI was an independent risk factor for the development of gallstones in the US adult population ^[23]. In the present study, we also came to the consistent conclusion that for every 1-unit change in WWI, there was a 1.35-fold increase in the risk of gallstones. BMI and WC are popularly evaluated as obesity indicators, and a study has proposed that a higher risk of gallstones accompanies rising BMI and WC, even in a relatively metabolically healthy adult population ^{[38, 39]}. Similarly, the present study confirms that they are independent risk factors for the prevalence of gallstones. LAP is a good indicator of fat accumulation in the organism and its calculation is based on WC and TG with different formulas according to gender. Many studies have demonstrated a positive correlation between LAP and various metabolic disorders ^{[40, 41]}. However, its effect on gallstones has not been explored, and our results revealed that LAP was significantly linked to an increased risk of gallstones. In the US population, its optimal threshold was 49.9302. CMI is a newly established composite lipid index consisting of lipids and waist-to-hip ratio. Distinct from AIP, CMI is not only computed according to TG and HDL-C but also incorporates WC and height. In the current study, CMI is positively linked to gallstone prevalence, but its predictive power does not seem to be prominent. Besides, the results of multifactor-adjusted regression analysis suggested that AIP, TyG, and VAI were not correlated with the prevalence of gallstones significantly, and they were not favorable in the identification of gallstones.

Our study provides the first relatively comprehensive comparative insight into the potential value of nine obesity-related measures in predicting gallstone disease, not only adding to research in this area but also providing a basis for efficient screening of the disease in future clinical practice. Diverse sensitivity analyses were conducted to examine the robustness of the relations between multiple metrics and gallstones. In addition, NHANES is a nationally representative database under the strict supervision of the CDC with detailed and high-quality data. The data analysis in this study was performed in accordance with the guidelines. However, there are some limitations to this study. First, this was a cross-sectional study and could not determine a causal relationship between obesity-related measures and gallstones. Although the BRI was found to be a better predictor for identifying gallstone risk compared with other indicators, further prospective investigations are warranted in the future to confirm its value for clinical application. Second, the diagnosis regarding the outcome of gallstones was based on participants' responses to a medical questionnaire rather than a more accurate ultrasound diagnosis. Third, although we adjusted for multiple covariates, there remains the influence of other potential confounders. Finally, the conclusions of this study are based on U.S. adults, and their applicability to other populations remains to be further explored.

Our study revealed that six screening tools, BRI, WWI, BMI, WC, LAP, and CMI, were positively associated with gallstone risk. Among them, BRI exhibited better predictive performance in identifying patients with gallstones in the U.S. adult population. Furthermore, the application of BRI, a non-invasive method, as a tool for gallstone risk assessment is likely to be a powerful and convenient option in clinical practice.

Acknowledgements:

The authors would like to express sincere appreciation to all the participants in the National Health and Nutrition Examination Survey (NHANES) and the researchers at the National Center for Health Statistics (NCHS), who collected and managed the NHANES data and also provided the data for public use.

Availability of data and material：

The data utilized in this study were obtained from publicly available Nhanes datasets, which can be found at the following website: https://www.cdc.gov/nchs/nhanes/index.htm.

You may contact the corresponding author with any other reasonable requests.

Authors' contributions:

Xiaodong Wu designed, conceptualized, and wrote the first draft of the paper, and Yanhong Song provided significant assistance in data analysis and graph production. Xiaoning Wang raised certain ideas on the research design. The three of them worked together to complete the whole research project. The entire process of designing, writing, and revising the article was supervised and guided by Shuodong Wu. All authors contributed to the article and agreed to the final submitted version.

Conflict of interest:

All authors consent to the publication of this article and declare that no conflict of interest is involved in its publication.

Funding：

This study did not receive any specific funding from granting agencies in the public, commercial, or non-profit sectors.

Human Ethics：

The dataset was obtained from the NHANES database and all data were ethically approved before recording into the database.

Consent to Participate Declarations:

Not applicable.

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The Development and Evaluation of 9 Obesity-Based Index for Gallstones in U.S. Adults

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Abstract

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1. Introduction

2. Materials and methods

3. Results

3.1 Participants' baseline characteristics

3.2 Association of Nine obesity-related screening indicators and risk of gallstones

3.3 Predictive value of nine indicators for gallstones

4. Discussion

5. Strengths and limitations of the research

6. Conclusion

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References

Additional Declarations

Supplementary Files

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