Relationship between weight-adjusted waist circumference index and prevalence of gallstones in U.S. adults: a study based on the NHANES 2017-2020
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SUBMITTER: Ke B
PROVIDER: S-EPMC10641849 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe weight adjusted waist index (WWI) represents a novel indicator for assessing central obesity. The objective of this study is to investigate the association between WWI and coronary heart disease (CHD).MethodThe data of 44,528 participants in total were gathered from NHANES database from 1999 to 2020. WWI is calculated as the waist circumference (WC, cm) divided by the square root of the body weight (kg), and CHD was determined based on participants' self-reports. The association between WWI and CHD was examined using multiple logistic regression analysis, restrictive cubic spline (RCS), receiver operating characteristic (ROC) curve, mediation analysis, subgroup and interaction analyses.ResultThis was a cross-sectional investigation. A total of 44,528 participants were included [50.23% male; mean WWI 10.89 (0.01) cm/√kg]. The multivariate logistic regression analysis revealed that in three models, one-standard-deviation increment in WWI was associated with an increased probability of CHD occurrence by 2.39 (2.22,2.57),1.47 (1.32,1.65), and 1.15 (1.00,1.32) times, respectively. Additionally, RCS analysis indicated a linear relationship between WWI and CHD. and the ROC analysis results showed that the discriminatory power of WWI for CHD was superior to that of body mass index (BMI) and WC. Glycated hemoglobin (HbA1c) partially mediated the relationship between WWI and CHD. Subgroup and interaction analyses confirmed that age, systolic blood pressure, and diabetes status had a significant impact on the association between WWI and CHD (P for interaction <0.05).ConclusionThe level of WWI has been demonstrated to be associated with an increased risk of CHD. Specifically, as WWI increases, the risk of CHD becomes higher. On this basis, it is hypothesized that WWI may potentially serve as an independent risk factor for CAD, thereby highlighting the substantial value of WWI in the identification and management of CHD.
| S-EPMC11758883 | biostudies-literature
Project description:BackgroundWaist circumference can be used as an anthropometric measure to assess central obesity and is easier and more convenient than the waist-to-hip ratio in identifying the risk of obesity and medical problems. Most studies showing an association between obesity and infertility in women have used BMI to measure obesity. Our goal was to examine any potential association between waist circumference and infertility.MethodsThis cross-sectional study, which formed part of the National Health and Nutrition Examination Survey (NHANES), comprised women ages 18 to 45 between 2017 and 2020. Participants without waist circumference data or information on infertility were removed from the study. The independent relationship between waist circumference and infertility was investigated using weighted binary logistic regression and subgroup analysis.ResultsWe investigated 1509 participants and discovered that the prevalence of infertility rose as the WC trisection rose. (tertile 1, 7.55%; tertile 2, 10.56%; tertile 3, 15.28%; trend < 0.001). Multivariate logistic regression showed that after total adjustment, higher WC levels were associated with an increased likelihood of infertility in women (OR1.02; 95% CI 1.01-1.03), and There was a 2% rise in the incidence of infertility for every unit (cm) increased WC. Subgroup analysis and interaction tests showed no significant dependence of the effects of marital status, diabetes, hypertension, and high cholesterol on the association between WC and infertility (p for all interaction tests > 0.05). The inflection point of the positive non-linear relationship between WC and infertility was 116.6 cm.ConclusionExcessive waist circumference assessment may increase the probability of infertility, and more attention should be paid to the management of waist circumference should be given more attention.
| S-EPMC10627239 | biostudies-literature
Project description:Obesity is a common public health issue worldwide, and its negative impact on lung function has garnered widespread attention. This study sought to investigate the possible association between a new obesity metric, the weight-adjusted waist index (WWI), and lung functions, providing a basis for the monitoring and protection of lung functions. We conducted a cross-sectional evaluation, analyzing data from adults in the U.S. gathered through the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2012. To explore the correlation between WWIs and lung functions, we utilized a multivariate logistic regression model with appropriate weighting to ensure accuracy. Smooth curve fitting also helped to confirm the linear nature of this relationship. Subgroup analyses were conducted to confirm the uniformity and dependability of the results. Our study included data from 13,805 adults in the United States. Multivariate linear regression analysis revealed that, in the fully adjusted model, higher WWIs were negatively correlated with forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), FEV1/FVC, peak expiratory flow rate (PEF), and forced expiratory flow rate (FEF) 25%-75% (β = -0.63; 95% confidence interval [CI] [-0.71, -0.55]; β = -0.55; 95% CI [-0.62, -0.48]; β = -0.02; 95% CI [-0.03, -0.01]; β = -1.44; 95% CI [-1.65, -1.23]; β = -0.52; 95% CI [-0.65, -0.39], respectively). Additionally, when analyzing the WWI as a categorical variable, a significant downward trend in the FVC, FEV1, PEF, and FEF 25%-75% was observed from Q2 to Q4 as the WWI increased (trend P < 0.05). Subgroup analysis showed stronger associations between WWI and lung functions, particularly among younger, non-Hispanic white, male participants, and current smokers. Our results indicate that elevated WWI is strongly associated with declining lung functions, demonstrating the importance of long-term monitoring and tracking of WWIs.
| S-EPMC11498673 | biostudies-literature
Project description:ObjectiveThe weight-adjusted-waist index (WWI) is a novel measure of central adiposity, potentially linked to various sleep disturbances. This study explores the relationship between WWI and sleep outcomes, such as trouble sleeping, sleep disorder, and sleep duration.MethodsData from the National Health and Nutrition Examination Survey 2007-2012 were analyzed, including 13,494 participants. The analysis focused on individuals aged 20 years and older who provided information on WWI and sleep. Sleep status was determined based on responses to the following questions: (1) "How many hours do you sleep?"; (2) if they reported trouble sleeping; and (3) if they had physician-diagnosed sleep disorders. Regression models assessed the association between WWI and sleep outcomes across the entire population and within subgroups. Restricted cubic spline (RCS) analysis was conducted to examine potential non-linear relationships between WWI and sleep outcomes.ResultsA higher WWI was significantly correlated with an increased likelihood of trouble sleeping (OR = 1.26, 95% CI: 1.16, 1.36; p < 0.001) and sleep disorder (OR = 1.71, 95% CI: 1.50, 1.95; p < 0.001) in the overall population. RCS analysis indicated a linear relationship between WWI and these sleep outcomes. Subgroup analysis identified that the connection between WWI and trouble sleeping was most pronounced among Non-Hispanic Blacks and individuals with lower educational levels. For sleep disorder, the association was stronger in males and Non-Hispanic Blacks. A slight negative association between WWI and sleep duration was found, especially among non-drinkers (β = - 0.13, 95% CI: - 0.24, - 0.02; p = 0.028).ConclusionThe findings highlight a significant and linear relationship between elevated WWI and an increased likelihood of experiencing trouble sleeping and sleep disorder, with variations observed across different demographic and lifestyle subgroups. These results imply that central adiposity, as measured by WWI, plays an important role in sleep health.Level of evidenceLevel III: Evidence obtained from well-designed cohort or case-control analytic studies.
| S-EPMC11811478 | biostudies-literature
Project description:Cardiovascular disease (CVD) is a significant health concern, particularly among patients with diabetes. The weight-adjusted waist circumference index (WWI), a novel metric that accounts for central obesity, has shown potential in predicting obesity-related health risks. This study aimed to evaluate the association of WWI with CVD and mortality in patients with diabetes. Utilizing data from the National Health and Nutrition Examination Survey from 1999 to 2020, WWI was calculated by dividing waist circumference (WC) by the square root of body weight. Multivariate logistic regression, multivariate Cox regression and restricted cubic spline curves were used to assess the association between WWI and the prevalence of CVD and mortality in patients with diabetes, subgroup and sensitivity analyses were carried out to delve into the stability of the findings. The predictive performance of WWI was evaluated using the area under the receiver operating characteristic curve (ROC). This study included 8,005 individuals with diabetes. With the increase in WWI values, the risk of developing CVD and the likelihood of mortality progressively rise. The fully adjusted continuous model indicated a 28% higher chance of developing CVD and a 25% higher risk of all-cause mortality for each one-unit increase in WWI. When using the lowest quartile of WWI as the reference category, the highest quartile was linked to an increased risk of CVD (OR 1.66; 95% CI 1.10-2.50, p = 0.015) and all-cause mortality (HR 1.53, 95% CI 1.27-1.83, p < 0.001) among patients with diabetes. Subgroup and sensitivity analyses confirmed that these associations were consistent and stable in most different demographics. The ROC analysis indicated that WWI had a higher predictive capacity for CVD and all-cause mortality than WC, waist to hip ratio, and weight to height ratio. The WWI was significantly associated with the prevalence of CVD and all-cause mortality among patients with diabetes in the United States and may serve as a useful tool for identifying individuals at risk.
| S-EPMC11329698 | biostudies-literature
Project description:BackgroundThe uncertainty regarding the correlation between the weight-adjusted waist index (WWI) and diabetes within the National Health and Nutrition Examination Survey (NHANES) necessitates further exploration. As indicators of obesity, the differences in the intensity of association between WWI, body mass index (BMI), and waist circumference (WC) with diabetes are worth exploring. This investigation is undertaken to elucidate the association between WWI and diabetes in the NHANES dataset and to compare the extent to which BMI, WC, and WWI were closely associated with diabetes. Then, choose an obesity index that is more strongly associated with diabetes.MethodsA comprehensive cross-sectional stratified survey of 7,973 participants from the 2017-2020 NHANES was conducted. WWI is an anthropometric measure based on WC and weight. The formula is WWI (cm/√kg) = WC/√weight. The association between WWI and diabetes was investigated using weighted multiple logistic regression, smooth curve fitting, stratified analysis, and interaction testing.ResultsThe participants' average age was 50.84±17.34 years, and 50.68% of them were female. The detection rate of diabetes was 15.11%. This positive association was particularly notable among non-diabetic patients. For each unit increase in BMI and WC as continuous variables, the likelihood of developing diabetes in the fully adjusted model increased by 5% (OR = 1.05; 95%CI, 1.03-1.07) and 3% (OR = 1.03; 95%CI, 1.02-1.04), respectively, but for each one-unit increase in WWI, the likelihood of developing diabetes increased by 111% (OR = 2.11; 95% CI, 1.68-2.65). Tests of interactions revealed that in various subgroups, the association between diabetes and WWI remained steady.ConclusionsWe analyzed 2017-2020 NHANES data to explore the link between WWI and diabetes, finding a consistent positive correlation. The correlation between WWI and diabetes was stronger than that between WC and BMI. WWI seems to offer better potential aid in disease prevention and diagnosis.
| S-EPMC11426486 | biostudies-literature
Project description:BackgroundThe association between waist circumference (WC) and mortality is particularly strong and direct when adjusted for body mass index (BMI). One conceivable explanation for this association is that WC adjusted for BMI is a better predictor of the presumably most harmful intra-abdominal fat mass (IAFM) than WC alone. We studied the prediction of abdominal subcutaneous fat mass (ASFM) and IAFM by WC alone and by addition of BMI as an explanatory factor.Methodology/principal findingsWC, BMI and magnetic resonance imaging data from 742 men and women who participated in clinical studies in Canada and Finland were pooled. Total adjusted squared multiple correlation coefficients (R(2)) of ASFM and IAFM were calculated from multiple linear regression models with WC and BMI as explanatory variables. Mean BMI and WC of the participants in the pooled sample were 30 kg/m(2) and 102 cm, respectively. WC explained 29% of the variance in ASFM and 51% of the variance in IAFM. Addition of BMI to WC added 28% to the variance explained in ASFM, but only 1% to the variance explained in IAFM. Results in subgroups stratified by study center, sex, age, obesity level and type 2 diabetes status were not systematically different.Conclusion/significanceThe prediction of IAFM by WC is not improved by addition of BMI.
| S-EPMC3286444 | biostudies-literature
Project description:BackgroundWhile dietary factors are known to influence gallstone development, the specific relationships between comprehensive dietary quality indicators and gallstone risk remain poorly understood. This study aimed to explore the association between dietary quality indicators and gallstones using data from the 2017 to 2020 US National Health and Nutrition Examination Survey (NHANES).MethodsA total of 6,623 US adults were extracted from the 2017-2020 NHANES, of which 734 participants self-reported having gallstones. Dietary quality indicators were assessed using 24-hour dietary recall data. We used multivariate logistic regression analysis to evaluate the association between dietary quality indicators and the likelihood of gallstones. To delineate the non-linear relationships and threshold effects, we utilized a restricted cubic spline (RCS) regression model. Subgroup analyses were also performed.ResultsAfter adjusting for sex, age, race, education, poverty-to-income ratio, body mass index, large weight loss, alcohol use, smoking, physical activity, diabetes, hypertension, heart failure, coronary heart disease, angina pectoris, heart attack, total calories, total cholesterol, estrogen use, antihyperglycemic drug use, statin use, and glucocorticosteroid use (Model 4), a higher Dietary Inflammatory Index (DII) and lower Alternative Healthy Eating Index (AHEI), Healthy Eating Index (HEI-2020), Dietary Approaches to Stop Hypertension (DASH), and Mediterranean Diet (MED) were all significantly associated with gallstones. Further RCS analysis revealed a nonlinear relationship between the DII and gallstones, with a threshold value of 1.842. Above this threshold, for each unit increase in the DII score, the odds of developing gallstones increased by 27.5%. Subgroup analysis demonstrated that this association was consistent across all subgroups.ConclusionParticipants with gallstones exhibited poor dietary habits. Adopting a diet that reduces inflammation and supports overall health may help lower the risk of gallstone development, with potential implications for dietary recommendations in clinical practice.
| S-EPMC11905512 | biostudies-literature
Project description:BackgroundThe weight-adjusted waist index (WWI) is a novel obesity indicator that appears to outperform the body mass index (BMI) and waist circumference (WC) in assessing both overweight and obesity. Studies have demonstrated the relationship between obesity and overactive bladder (OAB). The purpose of this study is to examine the correlation between WWI and OAB.MethodsThis research utilizes data from the National Health and Nutrition Examination Survey (NHANES) collected between 2009 and 2018. Each participant's WWI was calculated as their WC in centimeters by the square root of weight in kilograms. The Overactive Bladder Symptom Score (OABSS) questionnaire is used to determine whether a participant has OAB. Multivariate logistic regression and generalized additive model analysis were employed to investigate the relationship between WWI and OAB. We used smoothing curve fitting to explore non-linear relationships. Additionally, subgroup analysis and interaction tests are conducted.ResultsIn this cross-sectional study involving 35,950 subjects, we found that individuals with a higher WWI have a higher risk of OAB (OR = 1.41, 95% CI: 1.02-1.74). Subgroup analysis and interaction testing showed that the relationship between WWI and OAB is consistent across various population characteristics. Smoothing curve fitting reveals a positive non-linear relationship between WWI and OAB. Furthermore, the association between WWI and OAB is stronger than that of other obesity-related indicators.ConclusionWeight-adjusted waist index may be able to predict the incidence of OAB and that WWI-based obesity management may help to reduce the risk of OAB.
| S-EPMC11408301 | biostudies-literature
Project description:BackgroundGallstone disease (GSD) is associated with obesity. The Cardiometabolic Index (CMI), a metric that accurately assesses central adiposity and visceral fat, has not been extensively studied in relation to GSD risk. This study investigates the link between CMI and GSD incidence in U.S. adults.MethodsThis study utilized data from the National Health and Nutrition Examination Survey(NHANES)(2017-2020) to assess the association between CMI and GSD, adjusting for confounders such as age, sex, race, chronic diseases, and lifestyle factors. Multivariable logistic regression models and subgroup analyses were employed. Generalized Additive Models (GAM) and advanced curve fitting techniques were used to explore potential non-linear relationships, with threshold effects determined via piecewise linear regression if such relationships were identified. Receiver Operating Characteristic (ROC) curves evaluated and compared the predictive performance of CMI, Body Mass Index (BMI), and Waist Circumference (WC), establishing optimal cutoff values along with their sensitivity and specificity.ResultsThis study included 3,706 participants, of whom 10.6% (392) had GSD. Participants with GSD showed significantly higher CMI values (0.57 vs. 0.44, P = 0.0002). The GSD group included more females and older adults, with increased risks for hypertension, diabetes, higher serum cholesterol and creatinine levels, and a higher risk of cancer. Logistic regression analysis revealed that higher CMI was significantly associated with greater GSD incidence (OR = 1.19, 95% CI = 1.02-1.38, P < 0.0001). The ROC curve demonstrated superior predictive performance (AUC = 0.778), outperforming conventional metrics like BMI and WC. GAM analysis indicated a non-linear positive correlation between CMI and GSD, with an optimal threshold of 0.996. Subgroup analysis found the strongest association among females, individuals aged 20-39, non-Hispanic Whites, those without a history of coronary heart disease, and alcohol consumers.ConclusionOur study reveals a nonlinear positive correlation between the CMI and the incidence of GSD among U.S. adults, with a threshold value of 0.996. Despite limitations in sample size that constrained the analysis of a fully adjusted model, after adjusting for confounding factors, the AUC for predicting GSD using CMI reached 0.778, surpassing traditional metrics. These findings underscore the importance of CMI as a critical risk factor and emphasize the necessity of targeted interventions for high-risk populations.
| S-EPMC11781038 | biostudies-literature