Which Measure of Abdominal Adiposity Best Relateswith Body Mass Index Among Older Bengalee Hindusof Kolkata, India? A Comparison of Three Measures

Kaushik Bose

Received: 30 January 2007 /Accepted: 22 March 2007 /Published online: 31 July 2007# Springer Science + Business Media B.V. 2007

Abstract A cross-sectional study of 410 (210 men and 200 women) older (≥55 years)Bengalee Hindus of Kolkata, India, was undertaken to determine which measure ofabdominal adiposity best relates with body mass index (BMI), an indicator of overalladiposity. Three measures of abdominal adiposity were studied: waist circumference (WC),waist–hip ratio (WHR), and conicity index (CI). Results revealed that, in both sexes, WChad the strongest partial (age controlled) correlations with BMI (men=0.56, women=0.80).Linear regression analyses demonstrated that BMI had the strongest significant impact onWC in both sexes. BMI alone accounted for 28.2 and 61.8% variation in WC in men andwomen, respectively. This strongest significant impact remained even after controlling forage. In conclusion, this study provides strong evidence that WC can be preferred overWHR and CI in studies dealing with BMI among older Bengalee Hindus. In particular,BMI and WC can be useful in studies dealing with aging and anthropometric characteristicsamong older Bengalees.

Keywords Waist circumference . Waist–hip ratio . Conicity index . Bodymass index

Introduction

While the body mass index (BMI) is an indicator of overall adiposity, waist circumference(WC), waist–hip ratio (WHR), and conicity index (CI) are measures of abdominal adiposity[4, 13, 16]. Obesity, as measured by BMI, measures general obesity [3] and does not takeinto account the detrimental effect of abdominal and intra-abdominal fat [10]. Centralobesity measures, namely, WC, WHR, and CI, are sufficient enough to measure abdominalobesity and are considered as indirect measures of intra-abdominal visceral fat deposition[15]. However, there is no consensus as to which of these three measures should be favoredin studies dealing with abdominal adiposity, particularly their relationship with BMI.

Intl Jnl Anthropology (2006) 21:247–252DOI 10.1007/s11599-007-9027-4

K. Bose (*)Department of Anthropology, Vidyasagar University, Midnapore 721 102 West Bengal, Indiae-mail: banda@vsnl.net

Ideally, the abdominal adiposity measure with correlates best with BMI should be favored.This debate is compounded by the fact that there are distinct age, sex, and ethnic variationsin the relationship between BMI and abdominal measures [2, 11, 20]; i.e., the relation ofBMI with these measures is dependent on age, sex, and ethnicity.

The present investigation attempted to determine which measure of abdominal adipositybest relates with BMI among older (aged ≥55 years) individuals of Bengalee Hinduethnicity.

Materials and Methods

Study Population

A cut-off point of 55 years was taken to define elderly people as recommended by severalauthors [5, 9]. The present study was conducted in ward 88 of Kalighat, a locality in SouthKolkata, West Bengal, India. A random sampling procedure was followed to select thesubjects. Primary information including name, address, and age of randomly selectedindividuals were collected from the local voter list and age was ascertained from the voter’sregistration record. Subjects were also requested to complete a questionnaire that includedspecific questions on age and ethnicity. Prior to measurement, verbal information was sentto all selected individuals. Ethical approval was obtained from relevant authorities. Thesubjects were requested to make an appointment at their residence. A total of 27 (20 menand 7 women) individuals were excluded because of missing data. The study populationwas comprised of 210 men and 200 women aged 55 years and above belonging to theBengalee Hindu population residing in ward 88 of Kalighat.

Anthropometric Measurements

All anthropometric measurements were made by trained investigators using standardtechniques [14]. Height was measured to the nearest 0.1 cm using Martin’s anthropometer.Body weights of lightly clothed subjects were recorded to the nearest 0.5 kg on a weightingscale (Doctor Beliram and Sons, New Delhi, India). For height and measurement,participants were requested to remove their shoes prior to taking measurements. Kyphoticsubjects were not included in this study. Minimum waist (WC) and maximum hip (HC)circumferences were measured to the nearest 0.1 cm using a tape measure (Triced,Shanghai, China). BMI was computed following the standard equation:

BMI kg�m2Þ¼ Weight kgð Þ

.Height mð Þ2

�

WC, WHR, and CI were used as measures of abdominal adiposity. WHR and CI werecomputed using the standard equation:

WHR ¼ WC cmð Þ=HC cmð Þ

CI was derived using the equation of [20].

Cl ¼ WC mð Þ= 0:109ð Þ � pWeight kgð Þ=Height mð Þf g:

248 Intl Jnl Anthropology (2006) 21:247–252

Statistical Analyses

The distributions of variables/indices were not significantly skewed in both sexes.Technical errors of measurements (TEM) were calculated and results were found to bewithin reference values cited by [14] and [19]. Therefore, TEM was not incorporated instatistical analyses. Partial correlation (age controlled) analyses were undertaken to studythe association of BMI with the three measures of central adiposity. Heterogeneity betweenthe partial correlation coefficients were determined following the technique specified by[17]. Multiple regression analyses, after controlling for age, were utilized to determine theimpact of BMI on these measures. All statistical analyses were performed using theStatistical Package for Social Science (version 10.).

Results and Discussion

The mean ages of men and women were 68.0 years (SD=7.4) and 64.4 years (SD=7.0),respectively. The mean values of anthropometric characteristics are presented in Table 1.Men had significantly (p<0.001) greater mean height, weight, WC, and WHR than women.Women had significantly (p<0.05) greater mean HC than men. There were no significantsex differences in mean BMI and CI.

Table 1 Anthropometric characteristics of older Bengalee Hindus

Variable Men (n=210) Women (n=200) t

Height 161.9 146.4 27.47**(5.2) (6.2)

Weight 57.9 46.8 12.60**(7.1) (10.3)

BMI 22.1 21.7 0.94(2.4) (4.2)

HC 83.2 84.8 −2.13*(5.7) (9.5)

WC 78.2 74.0 4.54**(7.6) (10.6)

WHR 0.939 0.873 9.31**(0.051) (0.087)

CI 1.202 1.208 0.547(0.092) (0.098)

*p<0.05; **p<0.001 (significant sex differences)

Table 2 Partial correlation coefficients between BMI and central adiposity measures

Central adiposity measure Mena Womena

WC 0.622** 0.810**WHR 0.357** 0.328**CI 0.058 0.181*

*p<0.05; **p<0.001a Significant heterogeneity among the correlation coefficients in both sexes

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Table 2 presents the partial correlation coefficients of BMI with WC, WHR, and CI. Thestrongest significant (p<0.001) partial correlations of BMI were observed for WC in bothsexes (men=0.56; women=0.80). Both WHR (men=0.33; women=0.32) and CI (men=−0.01; women=0.18) had much weaker partial correlations with BMI. In both sexes,significant heterogeneity (p<0.05) was observed among the three partial correlationcoefficients. A noteworthy point was that there existed distinct sex difference in the strengthof the association of WC and BMI.

Results of multiple regression analyses (age controlled) revealed that (Tables 3 and 4)BMI had the strongest significant impact on WC in both sexes (men: F change=96.609;women: F change=358.577). BMI had much weaker impact on WHR (men: F change=26.677; women: F change=23.013) and CI (men: F change=0.034; women: F change=6.819) in both sexes. An important observation was that BMI alone accounted for 28.2 and61.8% variation in WC in men and women, respectively. A noteworthy point was that therewas a distinct sex difference in the strength of the impact of BMI on WC. Among women,this impact was more than 3.7 times stronger as compared to men, implying marked sexualdimorphism in this impact. The possible causes of this sexual dimorphism could bedifferences in fat distribution induced by hormonal factors, lifestyle, or gender.

It is now well established that although BMI is related to abdominal adiposity measureslike WC, WHR, and CI, the relationship is influenced by age, sex, and ethnicity [14, 18].Of these three abdominal adiposity measures, two of them are indices (WHR and CI) thatrequire two anthropometric measurements to be made. In case of WC, a single simplemeasurement is required. Moreover, WC is strongly associated with risk factors of severalchronic diseases like noninsulin-dependent diabetes mellitus, coronary heart disease, andhypertension. It is for these reasons that several researchers [1, 12] have recommended itsuse in studies involving abdominal adiposity. However, WC can be recommended for use instudies involving BMI and abdominal adiposity only if it relates much stronger than othermeasures of abdominal adiposity like WHR and CI with BMI. The poor association of CIand BMI found among Bengalee subjects in this study may not be present among otherethnic groups. This association may be influenced by ethnicity or age. Several recentstudies worldwide have investigated BMI and central adiposity among middle-aged andolder individuals [6–8].

Table 3 Multiple regression analyses of BMI with central adiposity measures, after controlling for age inmen

Dependent variable B seB Beta F change R2 change

WC 0.185840 0.018907 0.5818 96.609* 0.282WHR 0.007401 0.001404 0.3299 26.677* 0.099CI −0.000501 0.002711 −0.0133 0.034 0.000

*p<0.0001

Table 4 Multiple regression analyses of BMI with central adiposity measures, after controlling for age, inwomen

Dependent variable B seB Beta F change R2 change

WC 0.319590 0.016877 0.79924 358.577* 0.618WHR 0.006737 0.001404 0.32993 23.013* 0.100CI 0.004325 0.001656 0.17902 6.819** 0.033

*p<0.0001; **p<0.01

250 Intl Jnl Anthropology (2006) 21:247–252

The present investigation provides clear evidence that, of the three measures ofabdominal adiposity, WC relates best with BMI among older Bengalee Hindus. Therefore,in conclusion, this study provided strong evidence that WC can be preferred over WHR andCI in studies dealing with BMI among older Bengalee Hindus. In particular, BMI and WCcan be useful in studies dealing with aging and anthropometric characteristics among olderBengalees.

It must be pointed out here that further studies are needed among other ethnic groups inIndia to determine which measure of abdominal adiposity relates best with BMI amongthem. Moreover, because age and sex influence the relationship between WC and BMI,future investigations should study these relationships among different ages of both sexes.Of particular interest to biological anthropologists would be to study the ethnic variation inthe relationship between BMI WC. Results of such studies could be utilized to betterunderstand human population variation in BMI and WC.

Acknowledgements All subjects who participated in this study are gratefully acknowledged.

References

1. Bjorntorp P (1987) Classification of obese patients and complications related to the distribution ofsurplus fat. Am J Clin Nutr 45(Suppl 5):1120–1125

2. Bose K (1997) Coronary heart disease among migrant South Asians in Britain: an overview. J IndAnthropol Soc 32:269–275

3. Bose K, Mascie-Taylor CGN (1997) Interrelationships of age and the body mass index with risk factorsof non-insulin dependent diabetes in European and migrant Asian males. Am J Hum Biol 9:291–296

4. Bose K, Mascie-Taylor CGN (1998) Conicity index and waist–hip ratio and their relationship with totalcholesterol and blood pressure in middle-aged European andmigrant Pakistani men. AnnHumBiol 25:11–16

5. Chilima DM, Ismail SJ (1998) Anthropometric characteristics of older people in rural Malawi. Eur J ClinNutr 52:643–649

6. Cornier M-A, Tate CW, Grundwald GK, Bessesen DH (2002) Relationship between waist circumference,body mass index, and medical care costs. Obes Res 10:1167–1172

7. Daniel M, Marion SA, Sheps SB, Hertzman C, Gamble D (1999) Variations by body mass index and agein waist-to-hip ration associations with glycemic status in an aboriginal population at risk for type 2diabetes in British Columbia, Canada. Am J Clin Nutr 69:455–460

8. Derby CA, Zilber S, Brambilla D, Morales KH, McKinlay JB (2006) Body mass index, waistcircumference and waist to hip ratio and change in sex steroid hormones: the Massachusetts MaleAgeing Study. Clin Endocrinol (Oxf) 65:125–131

9. Ghosh A, Bose K, Das Chaudhuri AB (2001) Age and sex variations in adiposity and central fatdistribution among elderly Bengalee Hindus of Calcutta, India. Ann Hum Biol 28:616–623

10. Kopelman PG (2000) Obesity as a medical problem. Nature 404:635–64311. Kusumu YS, Babu BV, Naidu JM (2007) Chronic energy deficiency and relationships of body mass

index with waist hip ratio and conicity index in some low socio-economic groups from South India. NutrMetab Cardiovasc Dis 17:e3–e4

12. Lean MEJ, Han TS, Seidell JC (1998) Impairment of health and quality of life in people with large waistcircumference. BMJ 351:853–856

13. Lee RD, Nieman DC (2003) Nutritional assessment. McGraw Hill, New York14. Lohman TG, Roche AF, Martorell R (eds) (1988) Anthropometric standardization reference manual.

Human Kinetics Books, Chicago15. Misra A, Sharma R, Pandey RM, Khanna N (2001) Adverse profile of dietary nutrients, anthropometry

and lipids in urban slum dwellers of northern India. Eur J Clin Nutr 55:727–73416. Mukhopadhyay A, Bhadra M, Bose K (2005) Human obesity: a background. In: Bose K (ed) Human

obesity: a major health burden. Journal of Human Ecology special issue number 13. Kamla RajEnterprise, Delhi, pp 1–9

17. Sokal RR, Rohlf FJ (1986) Biometry: the principles and practice of statistics in biological research. WHFreeman, New York

Intl Jnl Anthropology (2006) 21:247–252 251

18. Taylor RW, Jones IE, Williams SM, Goulding A (2000) Evaluation of waist circumference, waist-to-hipratio and the conicity index as screening tools for high trunk fat mass, as measured by dual energy X-rayabsorptiometry, in children aged 3–19 years. Am J Clin Nutr 72:490–495

19. Ulijaszek SJ, Kerr DA (1999) Anthropometric measurement error and the assessment of nutritionalstatus. Br J Nutr 82:165–177

20. Valdez R, Seidell JC, Ahn YI, Weiss KM (1993) A new index of abdominal adiposity as an indicator ofrisk for cardiovascular disease. A cross-population study. Int J Obes 17:77–82

252 Intl Jnl Anthropology (2006) 21:247–252