Adiposity reduces the risk of osteoporosis in Chinese rural population: the Henan rural cohort study

BMC Public Health. 2020 Mar 4;20(1):285. doi: 10.1186/s12889-020-8379-4.

Abstract

Background: Adiposity plays a crucial role in the risk of osteoporosis. However, the impact of body fat distribution on the skeleton is contentious. The study was designed to explore the association of various adiposity indices with estimated bone mineral density (BMD) and the risk of osteoporosis based on body mass index (BMI), body fat percentage (BFP), waist circumference (WC), waist to hip ratio (WHR), waist to height ratio (WHtR), and visceral fat index (VFI).

Methods: A total of 8475 subjects derived from the Henan Rural Cohort Study were analyzed. The estimated BMD of study participants were measured by calcaneal quantitative ultrasound (QUS). Linear regression and binary logistic regression were performed to estimate the association of adiposity and the outcomes.

Results: The mean age of the study participants was 55.23 ± 11.09 years and 59.61% were women. The crude and age-standardized prevalence of high osteoporosis risk was 16.24 and 11.82%. Per unit increment in adiposity indices was associated with 0.005-0.021 g/cm2 increase in estimated BMD. The adjusted odds ratios (95% confidence interval) for high osteoporosis risk in per 1 SD increase of WC, WHR, WHtR, BMI, BFP, and VFI were 0.820 (0.748, 0.898), 0.872 (0.811, 0.938), 0.825 (0.765, 0.891), 0.798 (0.726, 0.878), 0.882 (0.800, 0.972), and 0.807 (0.732, 0.889), respectively. Stratified analyses indicated greater effects on individuals aged 55 years or older.

Conclusions: The adiposity indices have an inverse association with the risk of osteoporosis among Chinese rural population, especially in the elderly.

Keywords: Adiposity; Bone mineral density; Osteoporosis; Rural population.

MeSH terms

  • Adiposity*
  • Adult
  • Aged
  • China / epidemiology
  • Cohort Studies
  • Female
  • Humans
  • Male
  • Middle Aged
  • Osteoporosis / epidemiology*
  • Risk
  • Rural Population / statistics & numerical data*