IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v13y2016i12p1231-d85081.html
   My bibliography  Save this article

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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Dongxue Dai & Ye Chang & Yintao Chen & Shuang Chen & Shasha Yu & Xiaofan Guo & Yingxian Sun, 2016. "Visceral Adiposity Index and Lipid Accumulation Product Index: Two Alternate Body Indices to Identify Chronic Kidney Disease among the Rural Population in Northeast China," IJERPH, MDPI, vol. 13(12), pages 1-11, December.
  • Handle: RePEc:gam:jijerp:v:13:y:2016:i:12:p:1231-:d:85081
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/13/12/1231/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/13/12/1231/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shasha Yu & Hongmei Yang & Xiaofan Guo & Liqiang Zheng & Yingxian Sun, 2016. "Association between Obese Phenotype and Mildly Reduced eGFR among the General Population from Rural Northeast China," IJERPH, MDPI, vol. 13(6), pages 1-11, May.
    2. Xiang-Hui Zhang & Mei Zhang & Jia He & Yi-Zhong Yan & Jiao-Long Ma & Kui Wang & Ru-Lin Ma & Heng Guo & La-Ti Mu & Yu-Song Ding & Jing-Yu Zhang & Jia-Ming Liu & Shu-Gang Li & Qiang Niu & Dong-Sheng Rui, 2016. "Comparison of Anthropometric and Atherogenic Indices as Screening Tools of Metabolic Syndrome in the Kazakh Adult Population in Xinjiang," IJERPH, MDPI, vol. 13(4), pages 1-12, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huixian Hou & Rulin Ma & Heng Guo & Jia He & Yunhua Hu & Lati Mu & Yizhong Yan & Jiaolong Ma & Shugang Li & Jingyu Zhang & Yusong Ding & Mei Zhang & Qiang Niu & Jiaming Liu & Shuxia Guo, 2017. "Association between Six CETP Polymorphisms and Metabolic Syndrome in Uyghur Adults from Xinjiang, China," IJERPH, MDPI, vol. 14(6), pages 1-14, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:13:y:2016:i:12:p:1231-:d:85081. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.