Abstract
Background: The high prevalence of obesity in the UK is associated with a substantial risk of ill health (Butland et al., 2007). Prevention and management of this health risk requires accurate identification of obesity. Obesity is traditionally identified in individuals using body mass index (BMI) ≥30 kg/m2 (WHO, 2000) but BMI does not reflect differences in adiposity and muscle nor the location of adipose tissue which may be an independent predictor of risk. An alternative method of identifying weight-related health risk which combines values for BMI with waist circumference (WC) has been proposed by Krakauer et al., (2012) and is described as ‘a body shape index’ (ABSI). The aim of this study was to investigate the agreement level of categorisation of health risk associated with excessive body weight in adults in England using BMI, ABSI and WC.
Methods: Data were obtained from the Health Survey for England 2010 for 14,112 individuals living in households in England. Data from individuals aged ≤17 years, pregnant women and those with measurements reported as unreliable, indicating under nutrition or outlying data were excluded leaving 4,662 adults in the study dataset. Extracted values were used to calculate BMI and ABSI. Each adult was then categorised for health risk in three ways using BMI (WHO 2000), ABSI (Krakauer et al., 2012) and WC (WHO 2011). The kappa-statistic was used to test for levels of agreement between risk categorization. Ethical permission was obtained.
Results: Categorisation by all three methods indicated a high proportion of risk of weight-related illness within the population (Table). Pairwise analysis using the kappa-statistic showed that there was a low level of agreement between ABSI and WC (k=0.217), and ABSI and BMI (k=0.062) with a moderate level of agreement found between BMI and WC (0.489).
Table: Categorisation of health risk associated with excessive body weight in 4662 adults in England identified by three methods
Low risk Moderate risk High risk
Cut-off Number (%) Cut-off Number (%) Cut-off Number (%)
BMI (kg/m2) 18.5-24.9=1518(33) 25.0-29.9=1860 (40) ≥30=1284 (27)
ABSI (%) <40% = 1861 (40) 40-60% = 929 (20) >60%=1872 (40)
WC (cm) ≤94M/≤80F=1416 (30) 94.1-101.9M/80.1-87.9F=1202(26)
102M/≥88F=2044 (44)
M=male; F=female
Discussion: The similar proportion of individuals identified in risk categories by each of the methods suggests comparable utility at population level. However, the low agreement between methods at an individual level raises questions about their interchangeability. Refining the ABSI cut-off points may assist with this. However, if categorisation is to be useful, it must be linked to clinical outcome. ABSI has been shown to be an independent predictor of premature mortality in a USA population (Krakauer et al., 2012) but further studies are required to explore its predictive value in other populations. In addition, ABSI is calculated from measurements of height, weight and WC and requires a more complex equation than that used to determine BMI. These predictive and practical implications need to be explored before ABSI can be considered for routine use in clinical or public health care.
Conclusion: Categorisation of health risk in adults in England using BMI, ABSI and WC shows poor agreement.
Methods: Data were obtained from the Health Survey for England 2010 for 14,112 individuals living in households in England. Data from individuals aged ≤17 years, pregnant women and those with measurements reported as unreliable, indicating under nutrition or outlying data were excluded leaving 4,662 adults in the study dataset. Extracted values were used to calculate BMI and ABSI. Each adult was then categorised for health risk in three ways using BMI (WHO 2000), ABSI (Krakauer et al., 2012) and WC (WHO 2011). The kappa-statistic was used to test for levels of agreement between risk categorization. Ethical permission was obtained.
Results: Categorisation by all three methods indicated a high proportion of risk of weight-related illness within the population (Table). Pairwise analysis using the kappa-statistic showed that there was a low level of agreement between ABSI and WC (k=0.217), and ABSI and BMI (k=0.062) with a moderate level of agreement found between BMI and WC (0.489).
Table: Categorisation of health risk associated with excessive body weight in 4662 adults in England identified by three methods
Low risk Moderate risk High risk
Cut-off Number (%) Cut-off Number (%) Cut-off Number (%)
BMI (kg/m2) 18.5-24.9=1518(33) 25.0-29.9=1860 (40) ≥30=1284 (27)
ABSI (%) <40% = 1861 (40) 40-60% = 929 (20) >60%=1872 (40)
WC (cm) ≤94M/≤80F=1416 (30) 94.1-101.9M/80.1-87.9F=1202(26)
102M/≥88F=2044 (44)
M=male; F=female
Discussion: The similar proportion of individuals identified in risk categories by each of the methods suggests comparable utility at population level. However, the low agreement between methods at an individual level raises questions about their interchangeability. Refining the ABSI cut-off points may assist with this. However, if categorisation is to be useful, it must be linked to clinical outcome. ABSI has been shown to be an independent predictor of premature mortality in a USA population (Krakauer et al., 2012) but further studies are required to explore its predictive value in other populations. In addition, ABSI is calculated from measurements of height, weight and WC and requires a more complex equation than that used to determine BMI. These predictive and practical implications need to be explored before ABSI can be considered for routine use in clinical or public health care.
Conclusion: Categorisation of health risk in adults in England using BMI, ABSI and WC shows poor agreement.
| Original language | English |
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| Publication status | Published - 4 Dec 2013 |
| Event | British Dietetic Association Research Symposium 2013 - Birmingham, United Kingdom Duration: 4 Dec 2013 → 4 Dec 2013 |
Conference
| Conference | British Dietetic Association Research Symposium 2013 |
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| Country/Territory | United Kingdom |
| City | Birmingham |
| Period | 4/12/13 → 4/12/13 |