{
  "abstract": "Objectives This study aimed to compare the predictive performance of novel adiposity indices (a body shape index (ABSI) and visceral adiposity index (VAI)) with traditional anthropometrics (body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR)) for cardiovascular disease (CVD) risk in urban China. Secondary objectives included evaluating composite indices derived from principal component analysis (PCA) and evaluating optimised risk stratification strategies.Design A community-based cross-sectional study.Setting Urban and rural communities in Nanjing, China, from 2020 to 2023.Participants 38 427 adults aged 35–79 years, recruited via stratified sampling. Individuals aged <35 or >79 years, who were pregnant or had severe illness or cognitive impairment were excluded.Primary and secondary outcome measures The primary outcome was a CVD high-risk status (defined by Chinese guidelines). Secondary outcomes included detection rates, area under the curve (AUC), ORs and multicollinearity diagnostics.Results Among participants, 23.3% (n=8905) were classified as high risk for CVD. In this study, WHtR demonstrated the greatest discriminative power (AUC=0.826, 95% CI 0.819 to 0.832), followed by a PCA-derived composite obesity index (COI; AUC=0.822). ABSI showed a clear risk gradient, with a 38.5% detection rate in the high-risk group (ABSI≥0.085), and VAI exhibited a modest but statistically significant effect (OR=1.026, p=0.001). Severe multicollinearity among traditional indices (variance inflation factor >40) was mitigated by COI. Combined models (eg, COI+ABSI+ VAI) achieved comparable AUC (0.825) with improved parsimony (AIC=17 4010.34). Age, hypertension and dyslipidaemia were key covariates (ORs=1.15–3.88, p<0.001).Conclusions WHtR and composite indices (eg, COI) appeared to perform better than other indicators in predicting CVD risk, whereas ABSI and VAI enhance stratification in specific subgroups. Implementing WHtR-based screening in primary care, supplemented by composite indices and novel markers for high-risk individuals, may help optimise prevention strategies in urbanising Chinese populations.",
  "authors": [
    {
      "affiliations": [
        "Nanjing Muncipal Center for Disease Centrol and Prevention, Nanjing, Jiangsu, China",
        "China Medical University, shenyang, Liaoning, China"
      ],
      "name": "Guoliang Ma"
    },
    {
      "affiliations": [
        "Department of Nephrology, Children’s Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China"
      ],
      "name": "Wenyan Wang"
    },
    {
      "affiliations": [
        "Nanjing Muncipal Center for Disease Centrol and Prevention, Nanjing, Jiangsu, China"
      ],
      "name": "Lin Zhu"
    },
    {
      "affiliations": [
        "Nanjing Muncipal Center for Disease Centrol and Prevention, Nanjing, Jiangsu, China"
      ],
      "name": "Wenting Li"
    },
    {
      "affiliations": [
        "Nanjing Muncipal Center for Disease Centrol and Prevention, Nanjing, Jiangsu, China"
      ],
      "name": "Zhuanzhuan Fan"
    },
    {
      "affiliations": [
        "Nanjing Muncipal Center for Disease Centrol and Prevention, Nanjing, Jiangsu, China"
      ],
      "name": "Weiyi Zhong"
    },
    {
      "affiliations": [
        "Yuhuatai District Center for Disease Control and Prevention, Nanjing, Jiangsu Province, China"
      ],
      "name": "Wenjing Zang"
    },
    {
      "affiliations": [
        "Department of Non-communicable Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, China"
      ],
      "name": "Xin Hong"
    },
    {
      "affiliations": [
        "The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China"
      ],
      "name": "Kun Li"
    }
  ],
  "title": "Head-to-head comparison of visceral adiposity indices (A Body Shape Index and Visceral Adiposity Index) with traditional anthropometrics: a community-based strategy for cardiovascular risk prediction in urban China",
  "uid": "cf7de1c4-d7a0-595c-bc9a-3ee858ae8cd3"
}