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RETRACTED ARTICLE: Association of milk consumption with the incidence of cholelithiasis disease in the US adult population

This article was retracted on 05 September 2024

This article has been updated

Abstract

Background

Cholelithiasis is a common digestive system disease that imposes major burden on patients and society. Investigating the relationship between dietary factors and cholelithiasis risk can provide a basis for disease prevention. Previous studies on milk intake and cholelithiasis incidence have been limited.Therefore, the aim of our study was to assess the association between milk consumption and the incidence of cholelithiasis in males and females.

Methods

We selected 14,722 adults (≥ 18 years old) from National Center for Health Statistics (NHANSE) 2017–2020, and collected general characteristics of patients in the database, such as age, gender, race and body mass index (BMI), as well as dietary information (milk consumption). The occurrence of cholelithiasis was used as the outcome event, and the group was divided into cholelithiasis and non-cholelithiasis groups according to the outcome event. We used logistic regression models in generalized linear model (GLM) functions, controlling for demographic, lifestyle, and dietary factors, to estimate the association between milk intake and the incidence of cholelithiasis in males and females.

Results

A total of 14,722 adults were included. In the present study, the overall weighted prevalence of cholelithiasis was 10.96%, with 15.18% and 6.48% prevalence in females and males, respectively. Compared to infrequent milk intake, frequent milk intake (once a week or more) in females was associated with reduced cholelithiasis risk (OR 0.74, 95% CI 0.61–0.90). Daily milk intake in males was also related to lower cholelithiasis risk (OR 0.69–0.82). As adjusted variables increased in the models, predictive performance was improved (AUC 0.711 in females, 0.730 in males).

Conclusions

Appropriate milk intake may correlate with decreased cholelithiasis risk. Our study provides a basis for dietary interventions against gallstones, but prospective studies are needed to verify the results.

Peer Review reports

Introduction

Cholelithiasis is one of the most common digestive system diseases and the most costly in terms of socioeconomic impact, severely affecting quality of life and imposing a huge burden on healthcare resources [1]. Cholelithiasis refers to the formation of stones in the biliary system including the gallbladder or bile ducts, resulting from abnormally high levels of cholesterol or bilirubin (a blood breakdown product) in the bile.

Cholelithiasis is highly prevalent, affecting approximately 10–20% of the global adult population, with over 20% of patients with cholelithiasis disease developing symptoms including biliary colic or biliary infections [2]. Previous studies have identified numerous risk factors for cholelithiasis, such as female sex [2], metabolic syndrome including physical inactivity, obesity and overnutrition [3, 4], insulin resistance and diabetes [5, 6], non-alcoholic fatty liver disease [7], dietary factors like high caloric and carbohydrate intake, high glycemic load, low fiber intake, high heme iron intake, rapid weight loss or bariatric surgery [8,9,10,11,12,13,14], prolonged fasting [15], long-term total parenteral nutrition, spinal cord injury, gastrectomy, decreased gallbladder motility due to weight cycling, increased hepato-intestinal circulation of bilirubin due to cirrhosis, Crohn's disease, ileal resection, use of certain medications (hormones, octreotide, betaine, calcium-regulated neurophosphatase inhibitors), and pregnancy [16, 17]. While metabolic syndrome increases cholelithiasis risk, primary prevention through lifestyle changes is also possible. Moreover, common mutations in the hepatic cholesterol transporter ABCG8 represent a major genetic risk factor, accounting for about 25% of total risk [16, 18, 19]. Although our understanding of the genetics and pathophysiology has improved recently, invasive surgery-based procedures still dominate treatment strategies. Dissatisfaction with clinical outcomes has prompted deeper investigation into the etiology and prevention of cholelithiasis.

Some researchers believe diet is closely related to cholelithiasis incidence [20]. Dietary habits represent one of the more modifiable risk factors. While previous studies have explored associations between various dietary components and cholelithiasis disease, milk as a common, accessible, and nutritious food has not been prospectively studied in relation to cholelithiasis incidence [21,22,23]. Therefore, we aimed to investigate the relationship between milk intake and cholelithiasis incidence in males and females using NHANES data.

Data analysis

Study population

NHANES is a cross-sectional survey of a nationally representative, non-institutionalized population sample conducted by the National Center for Health Statistics of the Centers for Disease Control. A stratified and multi-stage probability cluster design was used in the population sample to assess the health and nutrition of adults and children in the United States. All participants provided written informed consent. We used publicly available data from 2017 to 2020 at NHANES for this study, as available gallstone health information was only available during these cycles. A total of 24,814 men and women aged 18 years and older were identified. Further screening was performed according to the criteria. The inclusion criteria were as following, all participants from 2017–2020; informed consent was obtained in cooperation with follow-up. The exclusion criteria as following, those who did not complete the milk intake questionnaire; those who did not complete the gallstone questionnaire survey; unreasonable consumption of dairy products; those who were lost to follow-up. The screening process was shown in Fig. 1.

Fig. 1
figure 1

Population Screening Flowchart

Data collection

Information on age, gender, race, BMI, energy intake, smoking status, and presence of comorbid diabetes mellitus, hypertension, and hyperlipidemia of the study subjects was obtained through NHANES database screening. Gallstone status was obtained from the 2017–2020 NHANES health questionnaire based on the question "Has a doctor or other health professional ever told {you/SP} that {you/s/he} had gallstones?" Milk consumption information was obtained from the 2017–2020 NHANES diet questionnaire, which was collected by two 24-h dietary review methods, based on the question "Past 30 day milk product consumption." For data analysis validity, responses of "varied", "Refused" and "Don't know" in the questionnaires were omitted [24].

Based on the distribution of milk intake, milk consumption was categorized into quartiles, never consuming milk (Q1), rarely consuming milk (Q2, less than once a week), sometimes consuming milk (Q3, once a week or more), and often consuming milk (Q4, once a day or more).

The objective of the dietary interview component is to obtain detailed dietary intake information from NHANES participants. The dietary intake data are used to estimate the types and amounts of foods and beverages (including all types of water) consumed during the 24-h period prior to the interview (midnight to midnight), and to estimate intakes of energy, nutrients, and other food components from those foods and beverages. Following the dietary recall, participants are asked questions on salt use, whether the person’s overall intake on the previous day was much more than usual, usual or much less than usual, and whether the participant is on any type of special diet (see the MEC In-Person Dietary Interviewers Procedures Manual for more information on the proxy interview).The dietary interview component, called What We Eat in America (WWEIA), is conducted as a partnership between the U.S. Department of Agriculture (USDA) and the U.S. Department of Health and Human Services (DHHS). Under this partnership, DHHS' National Center for Health Statistics (NCHS), Division of Health and Nutrition Examination Surveys is responsible for the survey sample design and all aspects of data collection and USDA’s Food Surveys Research Group (FSRG) is responsible for the dietary data collection methodology, maintenance of the databases used to code and process the data, and data review and processing.All NHANES participants are eligible for two 24-h dietary recall interviews. The first dietary recall interview is collected in-person in the Mobile Examination Center (MEC) and the second interview is collected by telephone 3 to 10 days later.As in previous years, two types of dietary intake data are available for the 2017–2020 survey cycle: Individual Foods files and Total Nutrient Intakes files [25, 26].

Covariates analysis

In this analysis, age, race, smoking, hypertension, hyperlipidemia, body mass index (BMI), dietary intake including: energy intake, fat intake, cholesterol intake, poverty index, and dietary inflammatory index (DII) were considered as potential confounding factors. The age was divided into two groups, between 18–65 years old and over 65 years old. Race was categorized as Mexican–American, non-Hispanic white, non-Hispanic black, and other races. Smoking status was considered positive when the participant had smoked at least 100 cigarettes in his or her lifetime. Hypertension status was considered positive if the health professional had diagnosed the participant with hypertension. Hyperlipidemia status was considered positive if the health professional had diagnosed a participant with hyperlipidemia. Body mass index (BMI) calculated from height and weight, which collected by trained health technicians at the Mobile Examination Center (MEC).BMI was categorized as underweight or normal (BMI < 25), overweight (BMI 25–30), and obese (BMI > 30).

Poverty index indicates the ratio of household income to the poverty line. DII indicates Score values greater than 0, equal to 0, and less than 0 represent the diet as pro-inflammatory diet, non-inflammatory effect diet, and anti-inflammatory diet, respectively. Dietary intakes, such as energy, fat and cholesterol, for men and women were obtained from two 24-h dietary recalls and averaged.

Statistical analysis

All data analyses were performed by the statistical software R (R Foundation; http://www.r-project.org; version 3.4.3 2021–12-21) and Empower R (www.empowerstats.com; X&Y Solutions Ltd. Boston, MA), which combines appropriate of sample weights, stratification, and clustering of complex NHANES sampling designs. Six-year weights from the dietary interview were reweighted according to NHANES guidelines (1/3 of 2005–2010 weight). Continuous variables were described by mean and 95% CI, and categorical variables were described by survey-weighted percentages (95% CI).

Data imbalance oversampling

Since the original gallstone dataset had an extremely imbalanced distribution between normal and diseased samples, we adopted random oversampling technique to prevent model underfitting on the minority class. Oversampling is a technique that expands the number of minority class samples by simply replicating them.

In our study, the original dataset contained 13,109 normal samples and 1,613 gallstone positive samples. To balance the ratio between the two classes, we performed random oversampling on the minority class of gallstone positive samples, i.e., for each positive sample, we randomly repeated sampling to generate multiple new samples, finally obtaining 13,109 normal samples and 13,109 positive samples. After oversampling, the ratio between the two classes was 1:1.

The reason we chose random oversampling is that it is simple to implement, can significantly increase the number of minority class samples, and help improving the model's ability to identify positive samples. In addition, since it is random oversampling, it does not introduce overly correlated duplicate samples, which can avoid overfitting to some extent. After oversampling, the dataset size was expanded and the class distribution became more balanced.

K-fold cross validation

To comprehensively evaluate the model's generalization ability, we adopted the method of combining train-test split with k-fold cross validation.First, we randomly split the dataset into training set (80%) and an independent test set (20%) at a ratio of 4:1. The training set was used for model training and cross validation, while the test set was used at the end to evaluate the model's generalization performance on unseen samples.

Through tenfold cross validation, we could obtain more reliable and robust estimates of model performance, and reduce dependence on the specific train-test split. During the 10 training rounds, we recorded the model's performance on each fold's training and validation set, and calculated the average of these 10 performance metrics, including the model's average odds ratio (OR) and P-value during training.

Finally, we evaluated the model's classification performance on the independent test set. We plotted the receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) to comprehensively assess the model's classification capability.

A weighted chi-square test was investigated to test for differences between categorical variables. The logistic regression model in the generalized linear model (GLM) function was used to calculate the ratio (odds ratio, OR) and 95% CI of the association between milk intake and cholelithiasis incidence in males and females, using the lowest quartile of milk intake as the reference. in addition, with adjustment for various confounding factors, a four different regression models.

  • Model 1: Milk intake.

  • Model 2: Adjusted for age and race/ethnicity.

  • Model 3: Adjusted for age, race/ethnicity, smoking, hypertension, BMI, and hyperlipidemia.

  • Model 4: Dietary intake adjusted for age, race/ethnicity, smoking, hypertension, BMI, hyperlipidemia, total energy, fat, cholesterol, DII, and poverty. P < 0.05 (two-sided) considered statistically significant.

Result

A total of 14722 adults, including 7147 men and 7575 women, were included in this study. The weighted prevalence of cholelithiasis was higher in females (15.18%, 1150/7575) than in males (6.48%, 463/7147). The prevalence of cholelithiasis varied among different age groups regardless of the males or females group, with a lower prevalence in the group aged 18–65 years than in the group aged 65 years or older; differences in milk intake in the female group; different distribution of cholelithiasis among races, with a higher prevalence in Non-Hispanic White than in other races; and a higher prevalence of cholelithiasis among non-smokers; The incidence of cholelithiasis disease was higher in those with hypertension and hyperlipidemia; BMI was higher in those with cholelithiasis disease in different gender groups, as detailed in Table 1.

Table1 Participants characteristics of males and females with cholelithiasis in the National Health and Nutrition Examination Survey (NHANES), 2017–2020

In the multifactorial analysis, for the males population, the risk of cholelithiasis was lower for non-Hispanic white, non-Hispanic black, while the risk of cholelithiasis development was higher for those with age > 65 years, high BMI, high DII levels, and comorbid hypertension compared to participants without cholelithiasis disease.

As for the females group, concomitant high BMI, age > 65 years, hypertension, hyperlipidemia, smoking, high sugar intake, and high total fat intake were all independent risk factors for the development of cholelithiasis disease.

Figure 2 shows the weighted OR (95% CI) of the incidence of cholelithiasis disease based on quartiles with different frequencies of milk intake. For the females population, across models, we observed that frequent milk intake (Q3, once a week or more) was associated with a reduced risk of cholelithiasis incidence compared to infrequent milk intake (Q1, never). The OR (95% CI) for cholelithiasis incidence at this level of milk intake was 0.82 (0.72–0.94) in model 1, 0.77 (0.67–0.88) in model 2, which was adjusted for age and race/ethnicity. It was 0.73 (0.60–0.89) in model 3, which adjusted for the covariates in model 2 plus smoking, hypertension, BMI, and hyperlipidemia. Finally, the OR (95% CI) for cholelithiasis incidence at this level of milk intake was 0.74 (0.61–0.90) in model 4, which adjusted for the covariates in model 3 plus dietary intake of total energy, fat, and cholesterol.

Fig. 2
figure 2

Weighted OR and 95% CI for cholelithiasis disease in males and females according to quartiles of milk intake. Notes: OR: ratio of ratios; CI: confidence interval; P-value: survey-weighted Chi-square test and T test. a e Model 1 milk intake. b f Model 2 was adjusted for age and race/ethnicity. c g Model 3 was adjusted for age, race/ethnicity, smoking, hypertension, BMI, and hyperlipidemia. d h Model 4 was adjusted for age, race/ethnicity, smoking, hypertension, BMI and hyperlipidemia, total energy, fat, and cholesterol dietary intake. * p < 0.05

In the males group, in model 1, it was found that frequent milk drinking (Q4, once a day or more) increased the incidence of cholelithiasis compared to infrequent milk drinking (Q1, never). The OR (95% CI) for cholelithiasis incidence with frequent milk intake was 1.30 (1.15–1.48). In model 3, which adjusted for age, race/ethnicity, smoking, hypertension, BMI, and hyperlipidemia, it was found that occasional milk intake (Q2, less than once a week), sometimes milk intake (Q3, once a week or more) and frequent milk intake (Q4, once a day or more) reduced the occurrence of cholelithiasis compared to infrequent milk intake (Q1, never). The OR (95% CI) for cholelithiasis incidence at these levels of milk intake were 0.70 (0.58–0.84), 0.76 (0.64–0.90) and 0.84 (0.71–0.99), respectively. In model 4, which adjusted for the covariates in model 3 plus dietary intake of total energy, fat, and cholesterol, the OR (95% CI) for cholelithiasis incidence were 0.69 (0.58–0.83), 0.75 (0.64–0.89) and 0.82 (0.70–0.97), respectively.

In this study, we used the logistic regression method to establish four prediction models for the males group and the females group, and compared the prediction performance of the models.

The results in Fig. 3 show that in both the males and females groups, the predictive ability of the logistic regression model increases as the number of variables in the model increases.

Fig. 3
figure 3

ROC in males and females. Notes: AUC:the area under the ROC curve and the coordinate axis. a e Model 1 milk intake. b f Model 2 was adjusted for age and race/ethnicity. c g Model 3 was adjusted for age, race/ethnicity, smoking, hypertension, BMI, and hyperlipidemia. d h Model 4 was adjusted for age, race/ethnicity, smoking, hypertension, BMI and hyperlipidemia, total energy, fat, and cholesterol dietary intake. * p < 0.05

Specifically, in the females group, the AUC of model 1 that only includes age is 0.529. The AUC of model 2 after adding age and race/ethnicity variables rises to 0.598. The AUC of model 3 reached 0.709 after further adding the smoking, hypertension, BMI, and hyperlipidemia variables. The AUC of model 4, which added dietary intake of total energy, fat, and cholesterol variables, was the highest at 0.711. The same trend was also seen in the males group. The AUC of model 1 with only includes age is 0.528. The AUCs of model 2 and model 3 are 0.706 and 0.727, respectively. The AUC of model 4 is the largest at 0.73.

The AUC values of the males and females groups have the same trend, which confirms that gradually adding relevant variables can improve the predictive performance of the logistic regression model. This validates the effect of the variable selection method when building the model.

We also observed that under most models, the AUC value of the males group is slightly higher than the females group, suggesting the model has a slightly better predictive effect on males. This may be related to differences in physiological characteristics between males and females.

Discussion

Epidemiology and risk factors of cholelithiasis disease

Cholelithiasis disease is currently highly prevalent, imposing considerable physical and mental burden on patients and healthcare costs [1, 7]. Substantial evidence suggests unhealthy lifestyles and dietary habits are risk factors for cholelithiasis [3,4,5]. Obesity, overweight, dyslipidemia, diabetes, insulin resistance, altered cholesterol homeostasis, and metabolic syndrome predispose individuals to cholelithiasis [4, 5, 21]. Rapid weight loss and pregnancy also increase the risk [8, 16, 17]. Optimizing diet structure and developing healthy dietary patterns may reduce cholelithiasis incidence and enable primary prevention. And some studies have also pointed to specific nutrients as risk or protective factors for cholelithiasis formation in humans [21]. Milk, a common and highly nutritious beverage in daily life. Therefore, our study explored the effect of milk on the incidence of cholelithiasis disease by using the NHANES database.

Milk intake and cholelithiasis incidence

In this study utilizing the nationally representative NHANES sample, we first systematically assessed the relationship between different levels of milk intake and the cholelithiasis incidence. Using tenfold cross-validation, we obtained more accurate and reliable results. Compared with infrequent milk intake, frequent milk intake (once a week or more) in adult females was associated with reduced risk of cholelithiasis disease, even after adjusting for other confounders, including (age, race, smoking, hypertension, hyperlipidemia, body mass index (BMI), dietary intake (including: energy intake, fat intake, cholesterol intake, poverty index, dietary inflammatory index). Daily milk intake in adult males was also related to lower risk of cholelithiasis. The protective effect of milk intake on risk of cholelithiasis persisted in the multivariate adjusted models. Our findings provide the basis for dietary interventions in cholelithiasis disease prevention.

Potential mechanisms

As an essential component of daily diet beneficial for bone health [22], the relationship between milk intake and cholelithiasis incidence has been understudied. Our results indicate appropriate milk intake may help prevent cholelithiasis disease. Dietary factors influence gallstone formation through various pathways. High calorie and high fat diets lead to obesity and insulin resistance known to promote gallstones [4, 5]. Additionally, dietary interventions can alter bile microbial composition and metabolism, decreasing bile saturation and lithogenicity [27, 28]. The abundant minerals, fats and proteins in milk may regulate bile composition, increase bile acid secretion, reduce bile saturation and lithogenicity, thereby inhibiting stone formation [23]. The specific mechanisms warrant further investigation.

Previous studies have suggested that milk and dairy products, as a calcium supplement, may promote gallstone formation because calcium is a nucleating factor [23]. However, our findings suggest that higher levels of milk intake are protective factors for cholelithiasis disease in both males and females. In studies exploring the correlation between milk intake and cholelithiasis incidence, we have identified the following possible biological mechanisms: dysbiosis of the intestinal flora, hormone and related drug use. Diet, a common risk factor for cholelithiasis disease, has been shown to be inextricably linked to intestinal flora. In the last few years, some investigators have analyzed the microbiota of the biliary tract using non-culture techniques and found that Enterobacteriaceae are more prevalent in patients with gallstones [29]. A study on Chinese patients with cholelithiasis showed that the microorganisms in the biliary tract were mainly of the phylum Actinomycetes, Phylum Bacteroidetes, Phylum Thick-Walled Bacteria and Phylum Aspergillus, of which the most abundant genus was Phylum Bacteroidetes [27]. Another study showed that milk intake was negatively correlated with the abundance of the phylum Bacillus, Bacillariophyceae and Bacillus spp. and that Bacillus spp. microorganisms play a role in the formation of bile pigment stones [28]. The lithogenic role of interactions between the gut microbiota and the immune system in gallstone formation is being investigated, but remains inconclusive [30].

In addition, previous studies have shown that females are more likely to develop gallstones than males [31], which is consistent with the results of our study. We speculate that this may be related to a females' own hormonal profile, where estrogen increases hepatic cholesterol synthesis and secretion and reduces bile salt secretion, and progesterone can also reduce bile salt secretion and impair gallbladder emptying. The combination of estrogen and progesterone creates a high cholesterol-bile sludge environment in the gallbladder, which is most suitable for stone formation [31]. In addition, oral administration of some drugs containing estrogen, progesterone and the growth inhibitor analogue octreotide are likely to cause gallstones [32], the cause may be progesterone and octreotide causing hypokinesis of the gallbladder [33], delays the emptying of bile, further promoting the formation of gallstones.

Comparison with previous studies

Unlike earlier research on total protein intake [30], we specifically evaluated the association between milk as a protein source and cholelithiasis incidence. In the multivariate models, we also controlled for dietary protein, fiber, carbohydrates and fats. Our results revealed appropriate milk intake may reduce cholelithiasis incidence, providing the basis for dietary interventions. Other studies found goat milk supplementation does not increase bile lithogenicity compared to cow's milk [23]. This highlights the need to distinguish the effects of different dairy products. Overall, appropriate dairy intake may benefit gallstone prevention, but more research is needed.

To our knowledge, this study is the first to assess the association between milk intake and cholelithiasis incidence in males and females. Also, we used more comprehensive and representative data from the NHANES database for the study, and obtained more reliable results by adjusting the model to exclude the effect of confounding factors to the maximum extent possible. In addition, this study is the first to show the opposite effect of milk intake on the incidence of cholelithiasis disease. This provides a direction for us to guiding to reduce the risk of cholelithiasis by increasing a proper milk intake.

Limitations

Several limitations exist in this study. Firstly, the cross-sectional design precluded causal inference, and our findings need prospective cohort validation [32]. Secondly, self-reported milk intake is subject to recall bias. We also did not differentiate between whole and low fat milk, or examine other dairy products such as goat's milk and yogurt intake. In addition, we only examined the effect of milk intake on the incidence of cholelithiasis and did not consider whether interactions between milk and other diets might have a confounding effect on this study. Finally, limited sample size and statistical power caused uncertainty in some subgroup analyses.

Conclusions

We estimated for the first time the association between milk intake and cholelithiasis incidence using a nationally representative sample. The current study suggests that compared to infrequent milk intake, frequent milk intake (once a week or more) in females was associated with reduced cholelithiasis risk. And daily milk intake in males was also related to lower cholelithiasis risk. Although the main treatment for cholelithiasis is still surgery, the prevention of the disease is more significant in the long run through a simple, low-cost and feasible method of dietary modification. More studies are needed in the future to verify our findings and to understand the pathogenesis of cholelithiasis formation through diet and in order to better achieve prevention.

Availability of data and materials

The datasets generated and/or analysed during the current study are available in the NHANES repository, https://www.cdc.gov/nchs/nhanes/index.htm.

Change history

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Acknowledgements

The authors thank the participants, the investigators and the staff of the National Health and Nutrition Examination Survey for their valuable contribution.

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Authors

Contributions

Feng Jia and Yahui Liu designed the study. Yu Ma recruited participants and collected data. Feng Jia conducted the study, analysed the data and drafted the manuscript. Feng Jia and Yahui Liu critically revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Yahui Liu.

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All National Health and Nutrition Examination Survey procedures and protocols have been reviewed and approved by the National Center for Health Statistics Research Ethics Review Board. Ethical approval and review were not sought or obtained for this study given that it was secondary analysis of publicly available, de-identified data.

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Jia, F., Ma, Y. & Liu, Y. RETRACTED ARTICLE: Association of milk consumption with the incidence of cholelithiasis disease in the US adult population. BMC Public Health 23, 1639 (2023). https://doi.org/10.1186/s12889-023-16615-6

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