Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2015 Dec 28;10(12):e0144639.
doi: 10.1371/journal.pone.0144639. eCollection 2015.

Surface-Based Body Shape Index and Its Relationship with All-Cause Mortality

Affiliations

Surface-Based Body Shape Index and Its Relationship with All-Cause Mortality

Syed Ashiqur Rahman et al. PLoS One. .

Abstract

Background: Obesity is a global public health challenge. In the US, for instance, obesity prevalence remains high at more than one-third of the adult population, while over two-thirds are obese or overweight. Obesity is associated with various health problems, such as diabetes, cardiovascular diseases (CVDs), depression, some forms of cancer, sleep apnea, osteoarthritis, among others. The body mass index (BMI) is one of the best known measures of obesity. The BMI, however, has serious limitations, for instance, its inability to capture the distribution of lean mass and adipose tissue, which is a better predictor of diabetes and CVDs, and its curved ("U-shaped") relationship with mortality hazard. Other anthropometric measures and their relation to obesity have been studied, each with its advantages and limitations. In this work, we introduce a new anthropometric measure (called Surface-based Body Shape Index, SBSI) that accounts for both body shape and body size, and evaluate its performance as a predictor of all-cause mortality.

Methods and findings: We analyzed data on 11,808 subjects (ages 18-85), from the National Health and Human Nutrition Examination Survey (NHANES) 1999-2004, with 8-year mortality follow up. Based on the analysis, we introduce a new body shape index constructed from four important anthropometric determinants of body shape and body size: body surface area (BSA), vertical trunk circumference (VTC), height (H) and waist circumference (WC). The surface-based body shape index (SBSI) is defined as follows: SBSI = ((H(7/4))(WC(5/6)))/(BSA VTC) (1) SBSI has negative correlation with BMI and weight respectively, no correlation with WC, and shows a generally linear relationship with age. Results on mortality hazard prediction using both the Cox proportionality model, and Kaplan-Meier curves each show that SBSI outperforms currently popular body shape indices (e.g., BMI, WC, waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), A Body Shape Index (ABSI)) in predicting all-cause mortality.

Conclusions: We combine measures of both body shape and body size to construct a novel anthropometric measure, the surface-based body shape index (SBSI). SBSI is generally linear with age, and increases with increasing mortality, when compared with other popular anthropometric indices of body shape.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Relationship between BSA, VTC, height and WC for given BMI categories.
The BSA and height, and VTC and height can predict the BMI categories (a, b). BSA and WC (and VTC and WC) show a non-linear relationship for a given BMI category (c, d).
Fig 2
Fig 2. Variation of different body shape indices with age (in years).
Fig 3
Fig 3. Variation of relative death rate with increasing values of SBSI z-score.
(a) Female; (b) Male.
Fig 4
Fig 4. The Kaplan Meier curves for four body shape indices using all subjects.
The SBSI shows a better prediction performance than other body shape measures (with more separation between the curves, and less crossovers). 1st Q, 2nd Q, etc. denote respectively 1st quartile, 2nd quartile, etc.
Fig 5
Fig 5. The KM curves using ABSI and SBSI on subjects in the BMI category overweight.
a: ABSI (male); b: ABSI (female); c: SBSI (male); d: SBSI (female). As expected, both measures indicate that female subjects have better survival rates when compared with male subjects. SBSI shows an overall better prediction performance than ABSI. 1st Q, 2nd Q, etc. denote respectively 1st quartile, 2nd quartile, etc.
Fig 6
Fig 6. The KM curves using ABSI and SBSI on subjects in the BMI category obese I.
a: ABSI (male); b: ABSI (female); c: SBSI (male); d: SBSI (female).

References

    1. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999–2008. JAMA. 2010;303(3):235–241. 10.1001/jama.2009.2014 - DOI - PubMed
    1. Mokdad AH, Ford ES, Bowman BA, Dietz WH, Vinicor F, Bales VS, et al. Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. JAMA. 2003;289(1):76–79. 10.1001/jama.289.1.76 - DOI - PubMed
    1. Ogden CL, for Health Statistics (US) NC, et al. Prevalence of obesity in the United States, 2009–2010. US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics; 2012.
    1. WHO. Obesity: preventing and managing the global epidemic. 894 World Health Organization; 2000. - PubMed
    1. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999–2010. JAMA. 2012;307(5):483–490. 10.1001/jama.2012.40 - DOI - PMC - PubMed