Participants
This study was undertaken in Shenyang City, Liaoning Province, China. Community-dwelling residents in this study were recruited from nine communities of Tiexi District of Shenyang City from May to October 2017 [22]. In brief, we randomly selected 6,812 residents older than 55 years of age. They were invited to complete questionnaires and undergo physical examinations, as well as biochemical tests. Baseline characteristics were used to complete the following cross-sectional analyses. Participants for whom a variable value was not available, or who showed extreme values for gender, fat percentage, bone mass density, muscle mass density, or serum 25-(OH)-D3, were excluded. In the end, 4,506 participants (1,601 males) were eligible for the following analyses. We hereby stated that all undertaken methods and designments accorded with the World Medical Association Declaration of Helsinki–Ethical Principles for Medical Research Involving Human Subjects. This study was approved by the Ethics Committee of China Medical University (Shenyang, China, AF-SOP-07-1.0-01). We informed objectives and relevant issues to participants before undertaking this study. All participants were also asked to complete consent forms.
Serum 25-(oh)-d Measurements
Participants were asked for an overnight fast. Blood were collected using standard venipuncture. Serum was separated using double centrifugation. 25-(OH)-D3 in serum was estimate using liquid chromatography–tandem mass spectrometry. We defined less than 20 ng/mL of 25-(OH)-D3 as vitamin D deficiency [24].
Determination Of Osteosarcopenic Obesity
Information was collected by measurements. We used dual-energy X-ray absorptiometry (Discovery-W, Hologic Inc, Waltham, MA, USA) to estimate the body compositions. Bone mineral density was examined according to the recommendations of the International Society for Clinical Densitometry of 2007.
Low bone mass was defined as less than − 1.0 of a T-score, using World Health Organization criteria.
Appendicular skeletal muscle mass was measured. We defined low muscle mass using the following cutoff point: more than 1 standard deviation (SD) lower than the mean in men and women (less than 20.24 for men, and less than 13.93 for women).
The fat in the upper 40% of body was estimated to define obesity (greater than 27.50% and 35.96% in men and women, respectively).
We divided adverse body compositions into 4 categories (0, 1, 2, and 3 components).
Statistical Analyses
Continuous characteristics were shown using mean and SD, and compared among subgroups based on tertiles of 25-(OH)-D3 using analysis of variance (ANOVA). Categorical characteristics were shown using percentages. We compared percentages using chi-square tests. The relationship between the serum level of 25-(OH)-D3 and osteosarcopenic obesity, as well as its compositions, was estimated using multivariable logistic regression. The odds ratio (OR) and 95% confidence interval (95% CI) are given. Three regression models were used as follows: Crude Model; Model I (adjusted for age); and Model 2 (adjusted for age; diastolic blood pressure [DBP]; systolic blood pressure [SBP]; alanine aminotransferase [ALT]; creatinine; triglycerides [TG]; high density lipoprotein cholesterol [HDL-C]; fasting blood glucose [FBG]; gender; pension status; education; regular exercise; smoking status; drinking status). Consistent analyses were repeated when estimating associations of vitamin D deficiency with osteosarcopenic obesity, as well as for compositions. Using multinomial logistic regression models, we estimated the relationship between osteosarcopenic obesity compositions and tertiles of 25-(OH)-D3, and vitamin D deficiency. We also undertook subgroup analyses using SBP (< 139 or ≥ 139 mmHg), DBP (< 80 or ≥ 80 mmHg), ALT (< 17.65 or ≥ 17.65 U/L), creatinine (< 67.60 or ≥ 67.60 µmol/L), TG (< 1.41 or ≥ 1.41 mmol/L), HDL-C (< 1.31 or ≥ 1.31 mmol/L), FBG (< 5.60 or ≥ 5.60 mmol/L), age (< 60 or ≥ 60 years), education (≤ junior high school or > junior high school), gender (female or male), regular exercise (yes or no), smoking status (yes or no), drinking status (yes or no), and pension status (yes or no) to detect the relationship between any 25-(OH)-D3, deficiency of serum vitamin D3 and osteosarcopenic obesity. A two-tailed α level of 0.05 was used as statistical significance. All analyses were completed using SPSS 21.0 software (IBM, ASiaAnalytics, Shanghai, China).