Although studies have revealed the association of METS-VF with a variety of health conditions, its relationship with LS BMD has not been fully explored. Evaluating METS-VF's positive and negative correlational involvement with osteoporosis requires an understanding of the possible link between METS-VF and BMD. The current study used cross-sectional analysis and NHANES data to further investigate the association between METS-VF and LS BMD. Our study aims to provide strong evidence for the interaction between visceral fat metabolism and osteoporosis, and to help healthcare practitioners more effectively monitor and manage patients with osteoporosis in their daily clinical practice, thereby improving their health prognosis.

Study participants were recruited from the NHANES, which utilizes a complex, multi-stage, stratified and clustered probability design to represent the U.S. population. Participants in this study reported their LS BMD values throughout the 2011-2018 NHANES cycle. Of the 39,156 participants initially considered, 5005 participants were ultimately included after excluding those with missing lumbar spine BMD data, those with missing METS-VF data, and those under 20 years of age. The National Center for Health Statistics' Ethics Review Board authorized the study, and each participant gave their informed permission. (Fig. 1)

DXA, a globally accepted screening method for determining the risk of fragility fractures, was used to measure the LS BMD. The measurements are the responsibility of certified and trained radiologic professionals in DXA screening. Prior research has validated the accuracy of these metrics.

Age, gender, race, education, marital status, poverty-to-income ratio (PIR), CA, smoking status, alcohol usage, diabetes, and hypertension were the variables. Additionally, whether a person had ever smoked 100 cigarettes or more was used to define their smoking status, and whether they had used alcohol at least 12 times in the previous year was used to evaluate their drinking status. Diabetes mellitus was diagnosed as follows: informed by a doctor or health professional. Hypertension was diagnosed as follows: informed by a doctor or health professional. To enhance the openness of the research process, this study referenced prior research to get comprehensive data on these factors. The NHANES website offers composite assessments of every research variable. Please visit (www.cdc.gov/nchs/nhanes/).

Together with the waist-to-height ratio (WHTR), age, gender, and the Index of Insulin Resistance (METS-IR), the METS-VF evaluates exposure to adipose tissue. Units of measurement were as follows: kg/m for BMI, years for age, mg/dL for FBG and HDL-C, and gender coded as male = 1 and female = 0.

This study used complicated sampling to weight all analyses in order to better reflect the whole population of the United States. The study used survey-weighted averages and SD for continuous variables and survey-weighted percentages for categorical factors to investigate the relationship between METS-VF and LS BMD. Every statistical analysis took into account the NHANES's multi-stage design.

We employed three linear regression models -- unadjusted, marginally adjusted, and completely adjusted for covariates -- to investigate the relationship between METS-VF and LS BMD. Linear regression analyses were performed with METS-VF as a continuous and categorical variable (quartiles) to characterize the relationship between METS-VF and lumbar spine BMD.

Additionally, we used Restricted Cubic Splines(RCS)curve to examine the nonlinear association between METS-VF and LS BMD. A log-likelihood ratio test was employed to compute threshold effects and compare the two-segment linear regression model with a single linear model when a nonlinear connection was found. We then evaluated the possible confounders mentioned in the baseline table using subgroup analysis and interaction tests. To further validate the association between METS-VF and bone health, we examined the association of METS-VF with total femoral BMD, femoral neck BMD, and fragility fracture separately in sensitivity analyses. Femoral BMD data were analyzed by multiple linear regression, and fragility fractures were analyzed by multiple logistic regression as a dichotomous outcome variable. R version 4.4.2 and Empower software were used for the statistical analysis of the study, with a significance threshold of P < 0.05.