Familial aggregation of forearm bone mineral density in Chinese

Xiumei Hong, Tianhua Niu, Changzhong Chen, Binyan Wang, Scott A. Venners, Zhian Fang, Xiping Xu

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Osteoporosis is a major public health concern and its prevalence can be predicted based on forearm bone mineral density (BMD). This study is to investigate the familial aggregation of forearm BMD in a population-based, cross-sectional study in Anhui, China. Information on sociodemographic and environmental variables was obtained from 1,636 subjects from 409 nuclear families (including mother, father, and their first two children) by a standardized questionnaire. The forearm BMD was measured by peripheral dual-energy X-ray absorptiometry (pDXA). Using generalized additive models with a sequential adjustment for covariates, it was clearly indicated that the forearm BMD of the mother, the father, and the first sibling each had a significant and independent relation to the forearm BMD of the second sibling. Furthermore, using multiple logistic regression, the second sibling had an odds ratio (OR) of 5.3 (95%CI: 2.0-14.5) of having an extremely low (bottom 10th percentile) proximal forearm BMD and an OR of 4.3 (95%CI: 1.6-12.0) of having an extremely low distal forearm BMD when the parental mean forearm BMD was low and the first sibling's forearm BMD was low. Our findings showing strong familial aggregation of both proximal and distal forearm BMD values suggest that genetic factors play a significant role in determining both traits.

Original languageEnglish (US)
Pages (from-to)335-341
Number of pages7
JournalEuropean Journal of Epidemiology
Volume22
Issue number5
DOIs
StatePublished - May 2007
Externally publishedYes

Keywords

  • Bone mineral density
  • Familial aggregation
  • Regression model

ASJC Scopus subject areas

  • Epidemiology

Fingerprint

Dive into the research topics of 'Familial aggregation of forearm bone mineral density in Chinese'. Together they form a unique fingerprint.

Cite this