Visceral Adiposity Index and Lipid Accumulation Product Index: Two Alternate Body Indices to Identify Chronic Kidney Disease among the Rural Population in Northeast China

Dongxue Dai, Ye Chang, Yintao Chen, Shuang Chen, Shasha Yu, Xiaofan Guo and Yingxian Sun
Additional contact information
Dongxue Dai: Department of Cardiology, the First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang 110001, China
Ye Chang: Department of Cardiology, the First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang 110001, China
Yintao Chen: Department of Cardiology, the First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang 110001, China
Shuang Chen: Department of Cardiology, the First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang 110001, China
Shasha Yu: Department of Cardiology, the First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang 110001, China
Xiaofan Guo: Department of Cardiology, the First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang 110001, China
Yingxian Sun: Department of Cardiology, the First Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang 110001, China

IJERPH, 2016, vol. 13, issue 12, 1-11

Abstract: We aimed to compare the relative strength of the association between anthropometric obesity indices and chronic kidney disease (CKD). Another objective was to examine whether the visceral adiposity index (VAI) and lipid accumulation product index (LAPI) can identify CKD in the rural population of China. There were 5168 males and 6024 females involved in this cross-sectional study, and 237 participants (2.12%) suffered from CKD. Obesity indices included body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), VAI and LAPI. VAI and LAPI were calculated with triglyceride (TG), high-density lipoprotein (HDL), BMI and WC. VAI = [WC/39.68 + (1.88 × BMI)] × (TG /1.03) × (1.31/ HDL) for males; VAI = [WC/36.58 + (1.89 × BMI)] × (TG/0.81) × (1.52/HDL) for females. LAPI = (WC-65) × TG for males, LAPI = (WC-58) × TG for females. CKD was defined as an estimated glomerular filtration rate (eGFR) of less than 60 mL/min per 1.73 m 2 . The prevalence of CKD increased across quartiles for WHtR, VAI and LAPI. A multivariate logistic regression analysis of the presence of CKD for the highest quartile vs. the lowest quartile of each anthropometric measure showed that the VAI was the best predictor of CKD in females (OR: 4.21, 95% CI: 2.09–8.47, p < 0.001). VAI showed the highest AUC for CKD (AUC: 0.68, 95% CI: 0.65–0.72) and LAPI came second (AUC: 0.66, 95% CI: 0.61–0.70) in females compared with BMI (both p -values < 0.001). However, compared with the traditional index of the BMI, the anthropometric measures VAI, LAPI, WC, and WHtR had no statistically significant capacity to predict CKD in males. Our results showed that both VAI and LAPI were significantly associated with CKD in the rural population of northeast China. Furthermore, VAI and LAPI were superior to BMI, WC and WHtR for predicting CKD only in females.

Keywords: visceral adiposity index; lipid accumulation product index; chronic kidney disease; rural population (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/13/12/1231/pdf (application/pdf)
https://www.mdpi.com/1660-4601/13/12/1231/ (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:13:y:2016:i:12:p:1231-:d:85081

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 ().