Body Mass Index and Chronic Energy DeficiencyAmong Urban Bengalee Male Slum Dwellers of Kolkata,India: Relationship with Family Income

Raja Chakraborty & Kaushik Bose & Samiran Bisai

Received: 28 November 2006 /Accepted: 15 February 2007 /Published online: 29 March 2007# Springer Science + Business Media B.V. 2007

Abstract A cross-sectional study of 191 adult (>18 years) Bengalee male slum dwellers ofKolkata, India, was undertaken to study the relationships of family income with body massindex (BMI) and chronic energy deficiency (CED). Results revealed that the mean height,weight, and BMI of the subjects were 162.2 cm, 54.0 kg, and 20.5 kg/m2, respectively. Theoverall frequency of CED (BMI<18.5 kg/m2) was 33.5%. Based on the World HealthOrganization classification, the prevalence of CED among this population was high (20–39%) and thus the situation is serious. Overall, monthly family income (MFI) wassignificantly positively correlated (r=0.18, p<0.05) with BMI. Linear regression analysesshowed that MFI had significant impact (p<0.05) on BMI. The percent variation in BMIexplained by MFI was 2.6%. Subjects belonging to the lowest family income group (FIG)had the lowest mean BMI (19.5 kg/m2) and the highest rate of CED (46.6%) while those inthe highest FIG had the largest mean BMI (21.4 kg/m2) and lowest rate of CED (23.1%).There was a significant FIG difference (F=2.965, p<0.05) in mean BMI. Moreover, thereexisted FIG differences (χ2=7.54, p<0.06) in CED rates. In conclusion, this studyprovided strong evidence that FIG was significantly associated with BMI and the presenceof CED. The rate of CED was high, indicating a serious situation. These findings may havesevere public health implications. It is recommended that immediate nutritional interventionprograms be initiated among this population along with serious efforts to increase theirfamily income.

Keywords India . Bengalee males . Income . Chronic energy deficiency . Body mass index

Introduction

By nearly any measure, India remains one of the poorest countries in the world, with apopulation of more than one billion and a fertility rate well above replacement level [30].

Intl Jnl Anthropology (2006) 21:209–215DOI 10.1007/s11599-007-9023-8

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

Nevertheless, infant mortality rates dropped from 115 in 1980 to 70 in 1998, and the totalfertility rate dropped from 5 to 3.2 during the same period [30]. Improvements in thenutritional status of the population have been less impressive [8]. More than half theworld’s undernourished population lives in India [14].

The use of anthropometry as an indicator of nutritional and health status of adults hasnow been well established [31]. The body mass index (BMI) is an indicator of overalladiposity and low BMI and high levels of undernutrition (based on BMI) is a major publichealth problem, especially among rural underprivileged adults of developing countries [31].Although adult nutritional status can be evaluated in many ways, the BMI is most widelyused because its use is inexpensive, noninvasive, and suitable for large-scale surveys [7, 10,17]. Thus, BMI is the most established anthropometric indicator used for assessment ofadult nutrition status [16]. BMI is generally considered a good indicator of not only thenutritional status but also the socioeconomic condition of a population, especially adultpopulations of developing countries [7, 11, 23, 28]. A BMI<18.5 kg/m2 is widely used as apractical measure of chronic energy deficiency (CED), i.e., a “steady” underweight inwhich an individual is in energy balance irrespective of a loss in body weight or bodyenergy stores [12]. Such a steady underweight is likely to be associated with morbidity orother physiological and functional impairments [9, 28, 31].

Several recent investigations have studied the relationships of socioeconomic status(SES) with BMI and CED among different populations [1, 4, 5, 11, 18, 21, 24, 27]. It is awell-established fact that a large proportion of the population in Asia lives in poverty [30].Therefore, it is important from the public health point of view to evaluate the relationship ofincome with BMI and CED in different populations of Asia. However, we could not locateany study from India that has dealt with the relationship of monthly family income (MFI)with BMI and CED among urban males of Bengalee ethnicity. In view of this, the presentinvestigation was undertaken to study the relationship of MFI with BMI and CED amongBengalee urban male slum dwellers of Kolkata, India.

Materials and Methods

This study was carried out as part of an ongoing research project being undertaken bythe first two authors. The study area comprised of a slum (refugee colony), named“Bidhan Colony,” situated on the right hand side of the railway tracks between DumDum Junction and The Dum Dum Cantonment Railway Stations, approximately 15 kmfrom Kolkata town center. The subjects had migrated from Bangladesh during the1970–1971 civil war in erstwhile East Pakistan. Kolkata (formerly known as Calcutta)is the capital city of West Bengal province. The city lies between 22°32′40″ northlatitude and 88°24′30′′ east longitude. Kolkata is 120 km from the sea (Bay ofBengal). It is situated on the eastern bank of the river Ganges (also known as HooglyRiver).

A total of 191 adult (>18 years of age) male individuals were studied. The vastmajority of the subjects belonged to low socioeconomic status as evidenced from theirmonthly per capita income (MPCI) and MFI. The subjects lived with their families.Ethical approval and prior permission was obtained from Vidyasagar University EthicsCommittee and local community leaders, respectively, before commencement of thestudy. Informed consent was also obtained from each participant. Information onethnicity, age, MPCI, and MFI were obtained from all subjects with the help of a

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questionnaire. Both MPCI and MFI were recorded in rupees (Rs.). The current exchangerate is US $1=45 Rs. (approximate). MFI was further divided into the following fourfamily income groups (FIG):

FIG I: ≤2,000 Rs.FIG II: 2,001–3,000 Rs.FIG III: 3,001–5,000 Rs.FIG IV: >5,000 Rs.

The first author (RC) took anthropometric measurements following the standardtechniques [17]. Height and weight were recorded to the nearest 0.1 cm and 0.5 kg,respectively. Technical errors of measurements were computed and they were found to bewithin acceptable limits [29]. BMI was computed using the following standard equation:

BMI ¼ Weight kgð Þ�height m2� �

Nutritional status was evaluated using internationally accepted World Health Organization(WHO) BMI guidelines [31]. The following cutoff points were used:

CED grade III: BMI<16.0CED grade II: BMI=16.0–16.9CED grade I: BMI<17.0–18.4Normal: BMI=18.5–24.9Overweight: BMI≥25.0.

The WHO’s classification [31] of the public health problem of low BMI, based on adultpopulations worldwide, was followed. This classification categorizes prevalence accordingto percentage of a population with BMI<18.5.

(1) Low (5–9%): warning sign, monitoring required(2) Medium (10–19%): poor situation(3) High (20–39%): serious situation(4) Very high (≥40%): critical situation

The distributions of the anthropometric variables were not significantly skewed. Pearsoncorrelation coefficient (r) and linear regression analysis was used to study the relationshipof MFI and BMI. For regression analysis, BMI was used as a dependent variable. One-wayanalyses, Scheffe’s procedure [19, 20], were used to test for differences in mean BMIbetween the four FIG. Chi-square test was utilized to compute FIG differences in CEDprevalence. All statistical analyses were undertaken using the SPSS Statistical Package.Statistical significance was set at p<0.05.

Variable Mean SD

Age (years) 35.4 13.4MPCI (Rs.) 889.0 579.7MFI (Rs.) 3,925.7 2,386.2Height (cm) 162.2 6.3Weight (kg) 54.0 10.4BMI (kg/m2) 20.5 3.4

Table 1 Characteristics of thestudy sample (n=191)

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Results

The characteristics of the study sample are presented in Table 1. The mean age of thesubjects was 35.4 years (SD=13.4 years). Mean MPCI and MFI were Rs. 889.0 (SD=579.7) and Rs. 3925.7 (SD=Rs. 2386.2), respectively. Mean height, weight, and BMI ofthe subjects were 162.2 cm (SD=6.3 cm), 54.0 kg (SD=10.4 kg), and 20.5 kg/m2 (SD=3.4 kg/m2), respectively.

Figure 1 presents the nutritional status (based on BMI) of the subjects. The prevalence ofCED was 33.5%. Of these, 2.1, 7.3, and 24.1% belonged to CED III, CED II, and CED Icategories, respectively. Only 10.0% belonged to the overweight category. Based on theWHO (1995) classification, the prevalence of CED among this population was high (20–39%) and thus the situation is serious.

Table 2 presents the relationships of FIG with mean age, BMI, and CED prevalenceamong the subjects. Results showed that there was no significant (F=0.464, p>0.05) FIGdifference in mean age. However, there was a significant FIG difference (F=2.965, p<0.05) in mean BMI. It was observed that FIG I had the lowest mean BMI (19.5 kg/m2)while FIG IV had the highest mean BMI (21.4 kg/m2). Moreover, the rate of CED washighest (46.6%) in the lowest FIG. There was a strong decreasing trend (χ2=7.54, p<0.06)in CED prevalence with increasing FIG. FIG IV had the lowest rate (23.1%) while FIG II(34.1%) and FIG III (26.4%) had intermediate rates.

Fig. 1 Nutritional statusof the subjects

Table 2 Relationships of FIG with mean age, BMI, and CED prevalence

FIG Mean age* Mean BMI** % CED***

I (n=58) 35.0 (10.1) 19.5 (2.9) 46.6II (n=41) 36.3 (12.9) 20.3 (3.6) 34.1III (n=53) 36.4 (15.1) 21.0 (3.3) 26.4IV (n=39) 33.4 (15.5) 21.4 (3.8) 23.1

Standard deviations are presented in parentheses.

*F=0.464, p>0.05; no significant FIG difference in mean age

**F=2.965, p<0.05; significant FIG difference in mean BMI

***χ2 =7.54, p<0.06; FIG difference in CED prevalence

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The results of Pearson correlation (r) and linear regression analyses of MFI with BMIare presented in Table 3. Results showed that MFI and BMI were significantly (r=0.18, p<0.05) positively correlated. Regression analysis demonstrated that MFI had a significantimpact (T=2.478, p<0.05) on BMI. The percent variation in BMI explained by MFI was2.6%. Similar results were obtained (results not shown) even after controlling for the effectsof age.

Discussion

Recent studies worldwide have established that low socioeconomic status is associated withlow mean BMI and high rates of CED among adults [4, 6, 24, 25, 28] in differentpopulations. However, although a large section of the Indian population live in poverty[30], extensive efforts have not been made to study the association of MFI with BMI andCED among them. The present study attempted to study this association among urbanslum-dwelling Bengalee males of Kolkata. To the best of our knowledge, this is the firstreport dealing with the association of MFI with BMI and CED among adult Bengalee menof Kolkata, India.

Results of the present study clearly demonstrated that MFI was significantly positivelyassociated with BMI among Bengalee male slum dwellers. It also was observed that MFIwas significantly negatively associated with CED prevalence rate. The results of the presentstudy are in concordance with earlier studies from Asia including India [1–3, 11, 13, 22,27] and Bangladesh [24–26], which have also shown that mean BMI is significantly higheramong individuals belonging to higher SES. These studies have also reported that CEDprevalence is significantly higher among lower SES individuals.

More importantly, the prevalence of CED was high and thus the situation is serious. Thepublic health implications of these findings are very important because low BMI and highCED are likely to be associated with morbidity or other physiological and functionalimpairments [9, 28, 31]. Therefore, the following two important recommendations forimplementation among this population can be made based on the results of this study:

1) Immediate nutritional intervention programs be initiated2) Concrete steps are taken to increase the MFI

It is expected that both these measures would help in increasing mean BMI and thereforereduce the rate of CED in this population. It should be noted here that while the firstrecommendation may generate immediate benefits, the overall long-term improvement,from the public health point of view, might lie with the second recommendation.

Lastly, similar studies should be carried out among other ethnic groups in India. India isa land of vast ethnic heterogeneity. Such investigations would generate more information asto whether the relationships of MFI with BMI and CED observed in the present study aresimilar in other ethnic populations of India. There is urgent need for studies dealing withincome, primary health care, BMI, and CED. Because South Asia is the most populated

Table 3 Pearson correlation and linear regression analyses of MFI and BMI

R p value B seB Beta Adj. R2 T p value

0.18 <0.05 0.0002 0.000 0.177 0.26 2.478 <0.05

For regression analysis, BMI was used as a dependent variable.

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region of the world with several nutritional challenges [15], practitioners of public healthshould focus their research on the socioeconomic determinants of low BMI and high CEDin this region. The gender aspect should also be considered in future studies to investigatewhether similar findings are observed among women because the subject of sex could havean effect on the relationship between income and BMI.

Acknowledgements All subjects who participated in the study are gratefully acknowledged. This work waspartly funded by the University Grants Commission (Government of India) Minor Research Project grantnumber PSW-054/03-04 ERO awarded to RC. The authors acknowledge the help of Atul Dhali, Gopal Das,and Swapan Mallik.

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