CoChat
Sign Up
Cited by 180Body Composition Measurement TechniquesDiabetes, Cardiovascular Risks, and LipoproteinsObesity, Physical Activity, Diet

A body shape index and body roundness index: two new body indices to identify diabetes mellitus among rural populations in northeast China

Open access
Chang, Ye, Guo, Xiaofan, Chen, Yintao, Guo, Liang, Li, Zhao, Yu, Shasha, Yang, Hongmei, Sun, Yingxian·2015·BMC Public Health
DOI 10.1186/s12889-015-2150-2PMC PMC4544789
Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND: The Body Mass Index (BMI) has long been used as an anthropometric measurement. Waist circumference (WC) and waist-to-height ratio (WHtR) have been proposed as alternatives to BMI. Recently, two new anthropometric indices, the A Body Shape Index (ABSI) and Body Roundness Index (BRI) have been developed as possible improved alternatives to BMI and WC. The main research aim is to assess the capacity of the ABSI and BRI to identify subjects with diabetes mellitus (DM) and the secondary aim is to determine whether ABSI and/or BRI is superior to the traditional body indices (BMI, WC, and WHtR). METHODS AND RESULTS: This cross-sectional study was conducted in the rural areas of northeast China from January 2012 to August 2013, and the final analysis included data obtained form 5253 men and 6092 women. 1182 participants (10.4 %) suffered from DM. Spearman rank test showed that BRI and WHtR showed the highest Spearman correlation coefficient for DM whereas ABSI showed the lowest. The prevalence of DM increased across quartiles for ABSI, BMI, BRI, WC and WHtR. A multivariate logistic regression analysis of the presence of DM for the highest quartile vs. the lowest quartile of each anthropometric measure, showed that the WHtR was the best predictor of DM (OR: 2.40, 95 % CI: 1.42-3.39 in men; OR: 2.67, 95 % CI: 1.60-3.74 in women, both P < 0.001), and the ABSI was the poorest predictor of DM (OR: 1.51, 95 % CI: 1.05-1.97 in men; OR: 1.55, 95 % CI: 1.07-2.04 in women, both P < 0.05). ABSI showed the lowest AUCs (AUC: 0.61, 95 % CI: 0.58-0.63 for men; AUC: 0.61, 95 % CI: 0.59-0.63 for women) for DM in both sexes, while BRI (AUC: 0.66, 95 % CI: 0.63-0.68 for men; AUC: 0.67, 95 % CI: 0.65-0.69 for women) had high AUCs for DM that equaled those of WHtR. CONCLUSIONS: Our results showed neither ABSI nor BRI were superior to BMI, WC, or WHtR for predicting the presence of DM. ABSI showed the weakest predictive ability, while BRI showed potential for use as an alternative obesity measure in assessment of DM.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s12889-015-2150-2

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Chang et al. reported that for diabetes, BRI showed higher AUROC values and ORs compared with BMI among rural populations in northeast China.

    “Chang et al. [19] similarly reported that for diabetes, BRI showed higher AUROC values and ORs compared with BMI, indicating that BRI has superior discrimination power for the disease among rural populations in northeast China.”

    From The discriminatory ability of the body roundness index and body mass index for metabolic diseases in Korean adults: a comparative study (2025) · cites this paper as [19]

    The Results (Table 5; page not given) show higher numerical AUCs for BRI than BMI in both men and women. The available Results passage does not establish that BRI’s odds ratios exceeded BMI’s, and the Discussion and Conclusions explicitly say BRI was not superior to BMI for identifying diabetes. Thus the claim of superior discrimination overstates the paper’s conclusion. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 26

  1. [1]Danaei G Finucane MM Lu Y Lu Y Singh GM Cowan MJ National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2 7 million participants Lancet 2011 378 31 40 10.1016/S0140-6736(11)60679-X 21705069 · DOI · Paper page
  2. [3]Reaven GM Insulin resistance: the link between obesity and cardiovascular disease Med Clin North Am 2011 95 5 875 892 10.1016/j.mcna.2011.06.002 21855697 · DOI
  3. [4]Expert WHO Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies Lancet 2004 363 157 163 10.1016/S0140-6736(03)15268-3 14726171 · DOI · Paper page
  4. [5]Kumanyika SK Obarzanek E Stettler N Bell R Field AE Fortmann SP Population-based prevention of obesity: the need for comprehensive promotion of healthful eating, physical activity, and energy balance: a scientific statement from American Heart Association council on epidemiology and prevention, interdisciplinary committee for prevention (formerly the expert panel on population and prevention science) Circulation 2008 118 428 464 10.1161/CIRCULATIONAHA.108.189702 18591433 · DOI · Paper page
  5. [6]Qiao Q Nyamdorj R Is the association of type II diabetes with waist circumference or waist-to-hip ratio stronger than that with body mass index? Eur J Clin Nutr 2010 64 30 34 10.1038/ejcn.2009.93 19724291 · DOI
  6. [7]Heymsfield SB Scherzer R Pietrobelli A Lewis CE Grunfeld C Body mass index as a phenotypic expression of adiposity: quantitative contribution of muscularity in a population-based sample Int J Obes (Lond) 2009 33 1363 1373 10.1038/ijo.2009.184 19773739 PMC3156622 · DOI
  7. [9]Zhu S Wang Z Heshka S Heo M Faith MS Heymsfield SB Waist circumference and obesity-associated risk factors among whites in the NHANES III: clinical action thresholds Am J Clin Nutr 2002 76 743 749 12324286
  8. [10]Janssen I Katzmarzyk PT Ross R Body mass index is inversely related to mortality in older people after adjustment for waist circumference J Am Geriatr Soc 2005 53 12 2112 2118 10.1111/j.1532-5415.2005.00505.x 16398895 · DOI
  9. [11]Kuk JL Ardern CI Influence of age on the association between various measures of obesity and all-cause mortality J Am Geriatr Soc 2009 57 11 2077 2084 10.1111/j.1532-5415.2009.02486.x 19754497 · DOI
  10. [12]Petursson H Sigurdsson JA Bengtsson C Nilsen TIL Getz L Body configuration as a predictor of mortality: comparison of five anthropometric measures in a 12 year follow-up of the Norwegian HUNT 2 study PLoS One 2011 6 10 10.1371/journal.pone.0026621 22028926 PMC3197688 · DOI
  11. [13]Windham BG Fumagalli S Ble A Sollers JJ Thayer JF Najjar SS Griswold ME Ferrucci L The relationship between heart rate variability and adiposity differs for central and overall adiposity J Obes 2012 2012 149516 10.1155/2012/149516 22649714 PMC3357556 · DOI
  12. [14]Browning LM Hsieh SD Ashwell M A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0.5 could be a suitable global boundary value Nutr Res Rev 2010 23 2 247 269 10.1017/S0954422410000144 20819243 · DOI · Paper page
  13. [15]Hsieh SD Yoshinaga H Muto T Waist-to-height ratio, a simple and practical index for assessing central fat distribution and metabolic risk in Japanese men and women Int J Obes Relat Metab Disord 2003 27 5 610 616 10.1038/sj.ijo.0802259 12704405 · DOI
  14. [16]Ho SY Lam TH Janus ED Hong Kong Cardiovascular Risk Factor Prevalence Study Steering Committee Waist to stature ratio is more strongly associated with cardiovascular risk factors than other simple anthropometric indices Ann Epidemiol 2003 13 10 683 691 10.1016/S1047-2797(03)00067-X 14599732 · DOI
  15. [17]Ashwell M Gunn P Gibson S Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis Obes Rev 2012 13 275 286 10.1111/j.1467-789X.2011.00952.x 22106927 · DOI · Paper page
  16. [18]Krakauer NY Krakauer JC A new body shape index predicts mortality hazard independently of body mass index PLoS One 2012 7 10.1371/journal.pone.0039504 22815707 PMC3399847 · DOI
  17. [19]Thomas DM Bredlau C Bosy-Westphal A Mueller M Shen W Gallagher D Maeda Y McDougall A Peterson CM Ravussin E Heymsfield SB Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model Obesity 2013 21 11 2264 2271 10.1002/oby.20408 23519954 PMC3692604 · DOI · Paper page
  18. [20]He S Chen X Could the new body shape index predict the new onset of diabetes mellitus in the Chinese population? PLoS One 2013 8 1 10.1371/journal.pone.0050573 23382801 PMC3559745 · DOI
  19. [21]Krakauer NY Krakauer JC Dynamic association of mortality hazard with body shape PLoS One 2014 9 2 10.1371/journal.pone.0088793 24586394 PMC3930607 · DOI
  20. [22]Haghighatdoost F Sarrafzadegan N Mohammadifard N Asgary S Boshtam M Azadbakht L Assessing body shape index as a risk predictor for cardiovascular diseases and metabolic syndrome among Iranian adults Nutrition 2014 30 6 636 644 10.1016/j.nut.2013.10.021 24800666 · DOI · Paper page
  21. [23]Maessen MF Eijsvogels TM Verheggen RJ Hopman MT Verbeek AL de Vegt F Entering a new era of body indices: the feasibility of a body shape index and body roundness index to identify cardiovascular health status PLoS One 2014 9 9 10.1371/journal.pone.0107212 25229394 PMC4167703 · DOI · Paper page
  22. [25]Zhou X Guan H Zheng L Li Z Guo X Yang H Prevalence and awareness of diabetes mellitus among a rural population in China: results from Liaoning Province Diabet Med 2015 32 3 332 342 10.1111/dme.12599 25308779 · DOI
  23. [26]Krakauer NY Krakauer JC Expansion of waist circumference in medical literature: potential clinical application of a body shape index J Obes Weight Loss Ther 2014 4 2 10.4172/2165-7904.1000216 · DOI
  24. [27]Fujita M Sato Y Nagashima K Takahashi S Hata A Predictive power of a body shape index for development of diabetes, hypertension, and dyslipidemia in Japanese adults: a retrospective cohort study PLoS One 2015 10 6 10.1371/journal.pone.0128972 26030122 PMC4451769 · DOI
  25. [28]Xu Y Yan W Cheung YB Body shape indices and cardiometabolic risk in adolescents Ann Hum Biol 2015 42 1 70 75 10.3109/03014460.2014.903998 24734976 · DOI
  26. [29]Yin Bun C “A Body Shape Index” in middle-age and older Indonesian population: scaling exponents and association with incident hypertension PLoS One 2014 9 1 e85421 10.1371/journal.pone.0085421 24454862 PMC3893209 · DOI

Cited by

Sorted by citations

Authors
Chang, Y., Guo, X., Chen, Y., Guo, L., Li, Z., Yu, S., Yang, H., & Sun, Y.
Affiliations
First Hospital of China Medical University (CN)
Corresponding author
Sun, Yingxian
ORCID
Venue
BMC Public Health
Publisher
Springer Science and Business Media LLC
Published
2015-08-19
Volume
15
Issue
1
Pages
794-794
ISSN
1471-2458 (ISSN-L)
DOI
10.1186/s12889-015-2150-2
PMC
PMC4544789
OpenAlex
W2119284546
Cited by
180
References
3
Citations by year
2026: 12 · 2025: 32 · 2024: 22 · 2023: 15 · 2022: 20 · 2021: 26 · 2020: 13 · 2019: 12 · 2018: 13 · 2017: 9 · 2016: 6
FWCI
6.88
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Public Health (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
Keywords
body shape index, body roundness index, diabetes mellitus, waist-to-height ratio, waist circumference, body mass index, anthropometric indices, rural population, Northeast China, diabetes screening, sex differences
MeSH terms
Adult, Aged, Anthropometry, Body Composition, China, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Female, Humans, Male, Middle Aged, Obesity, Predictive Value of Tests, Rural Population, Prevalence, Area Under Curve

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review