Risk Factors Analysis of Bone Mineral Density Based on Lasso and Quantile Regression in America during 2015–2018

Chao Sun, Boya Zhu, Sirong Zhu, Longjiang Zhang, Xiaoan Du and Xiaodong Tan
Additional contact information
Chao Sun: School of Public Health, Wuhan University, Wuchang District, Wuhan 430071, China
Boya Zhu: School of Public Health, Wuhan University, Wuchang District, Wuhan 430071, China
Sirong Zhu: School of Public Health, Wuhan University, Wuchang District, Wuhan 430071, China
Longjiang Zhang: School of Public Health, Wuhan University, Wuchang District, Wuhan 430071, China
Xiaoan Du: School of Public Health, Wuhan University, Wuchang District, Wuhan 430071, China
Xiaodong Tan: School of Public Health, Wuhan University, Wuchang District, Wuhan 430071, China

IJERPH, 2021, vol. 19, issue 1, 1-11

Abstract: This study aimed to explore the risk factors of bone mineral density (BMD) in American residents and further analyse the extent of effects, to provide preventive guidance for maintenance of bone health. A cross-sectional study analysis was carried out in this study, of which data validity was identified and ethics approval was exempted based on the National Health and Nutrition Examination Survey (NHANES) database. Candidates’ demographics, physical examination, laboratory indicators and part of questionnaire information were collected and merged from NHANES in 2015–2016 and 2017–2018. The least absolute shrinkage selection operator (lasso) was used to select initial variables with “glmnet” package of R, quantile regression model to analyze influence factors of BMD and their effects in different sites with “qreg” code in Stata. Among 2937 candidates, 17 covariates were selected by lasso regression (λ = 0.00032) in left arm BMD, with 16 covariates in left leg BMD (λ = 0.00052) and 14 covariates in total BMD (λ = 0.00065). Quantile regression results displayed several factors with different coefficients in separate sites and quantiles: gender, age, educational status, race, high-density lipoprotein (HDL), total cholesterol (TC), lead, manganese, ethyl mercury, smoking, alcohol use and body mass index (BMI) ( p < 0.05). We constructed robust regression models to conclude that some demographic characteristics, nutritional factors (especially lipid levels, heavy metals) and unhealthy behaviors affected BMD in varying degrees. Gender and race differences, Low-fat food intake and low exposure to heavy metals (mostly lead, manganese and mercury) should be considered by both clinical doctors and people. There is still no consensus on the impact of smoking and alcohol use on bone mineral density in our study.

Keywords: BMD; lasso; quantile regression; nutritional factors; heavy metals; NHANES (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1660-4601/19/1/355/pdf (application/pdf)
https://www.mdpi.com/1660-4601/19/1/355/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:19:y:2021:i:1:p:355-:d:714178

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().