Nutritional status of children in rural India: a case study from Tamil Nadu, first in the world to initiate the Mid-Day Meal scheme

doi:10.4236/health.2011.310109

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Vol.3, No.10, 647-655 (2011)

doi:10.4236/health.2011.310109

Health

Nutritional status of children in rural India: a case study

from Tamil Nadu, first in the world to initiate the Mid-Day

Meal scheme

Palanisamy Navaneethan1,2, Thiagarajan Kalaivani1, Chandrasekaran Rajasekaran1*,

Nautiyal Sunil2

1Division of Plant Biotechnology, School of Bio Sciences and Technology, VIT University, Vellore, Tamil Nadu, India;

*Corresponding author: [email protected]

2Centre for Ecological Economics and Natural Resources, Institute for Social and Economic Change, Bangalore, India

Received 5 January 2011; revised 16 February 2011; accepted 20 March 2011.

ABSTRACT

In India, during the mid-nineties the Union Gov-

ernment had initiated the Mid-Day Meal sche-

mes in schools to promote primary education

on one hand, and to reduce malnutrition on the

other. However, Tamil Nadu had launched this

program several decades before; during the

regime of Mr. Kumarasami Kamraj (1954-1963).

An empirical study was undertaken in the rural

areas of Tamil Nadu, in the south of India, to

understand the nutritional status of the children

between 11 and 18 years old. This group is vul-

nerable, as during this age, individuals undergo

physical and mental changes. We calculated the

Body Mass Index (BMI) of school children to

assess their nutritional status. A total of 806 sc-

hool children took part in this study and the

majority of them were found to be underweight

in the study region. Irrespective of their age gr-

oup and sex, as per the WHO’s international

standards, 83% of the students were underwei-

ght (BMI < 18.5). Only 16% of the students w ere

in the normal range (BMI 18.5 - 24.9), and of the

rest, 0.39% and 0.06% were in the BMI range of

25 - 29.9 (overweight) and 30 - 35.9 (obese), res-

pectively. Based on available data, a regression

analysis was carried out. This regression model

showed that students’ age, sex and father’s

occupation significantly affects their BMI. Fur-

ther analysis showed that BMI w as independent

of the students’ blood group. It was concluded

that malnutrition among school children can be

eliminated by providing additional healthy foods

and by improving the Socio Economic Back-

ground (SE B) of the region.

Keywords: BMI (Body Mass Index); Underweight;

Regression Analysis; Fathers’ Occupation;

SEB (Socio Economic Background)

1. INTRODUCTION

Humans have been haunted by diseases from time

immemorial. The current trend of food consumption and

urbanization has led to many complications in diagnos-

ing diseases. On one side, there are increased cases of

obesity and on the other, there is malnutrition (under-

weight). This paradox is very common in developing

countries and is found to increase proportionally with

time [1,2]. In India alone there are approximately 60

million children who are underweight [3], and the

prevalence is higher in rural areas compared to urban

areas [4]. The number of malnourished children in India

is among the highest in the world and is twice than that

of the sub-Saharan region [5]. The condition of being

underweight may have resulted from a) low dietary in-

take b) excessive work out c) chronic infections [6].

Even though many methods are available to study the

nutritional status of an individual, anthropometry is con-

sidered as a good tool, especially to study the malnutrition

of individuals [7,8]. Within anthropometry, some studies

suggest the skin fold measures or waist/hip/arm circum-

ferences as an indicator of malnutrition, while others sug-

gest using the Body Mass Index (BMI) [8,9]. For our

study we used BMI as a measure to study the malnour-

ishment in children. We have four reasons for choosing

this method: 1) simple procedure 2) no technical compli-

cations 3) inexpensive 4) can be used to study large popu-

lations. In fact, many researchers favored the application

of BMI in the nutritional assessment of individuals

[10,11]. One can foresee the development of clinical

diseases with the help of BMI [12]. BMI has a direct

relationship with body fat [13] and some researchers

P. Navaneethan et al. / Health 3 (2011) 647-655

648

advocate the use of BMI in determining the fatness in

children and adolescents [14]. Yet in spite of the many

advantages, controversies still exist regarding the authe-

nticity of BMI.

For our study, we have chosen children of 11 - 18

years. During this age, individuals undergo changes both

physically and mentally. In India, this group constitutes

around 21.4% of the total population [15]. This age

group is the intermediate between childhood and adult-

hood. Assessing their nutritional level is of great impor-

tance, as it can reveal the past and future life styles [16].

According to the United Nations sub-committee (1998),

this age group is considered as an optimal period to

study the health and nutritio nal status of individua ls [17].

Studies carried out by various workers revealed a high

prevalence of under-nutrition (BMI < 18.5) among ado-

lescent girls [15,18,19]. Many researchers have strongly

recommended that being underweight should be con-

sisered as a public health issue [20-25]. There is a linear

relationship between being underweight and low bone

mass [26]. Underweight individuals are prone to various

kinds of infections, since they have low immune power,

which ma y ult im a tely l ead t o deat h of t he individual [27].

In 2000, representatives fro m th e UN O me mb er co un-

tries made a resolution to eliminate poverty [28], thereb y

reducing the number of children with malnutrition

(wasting, stunting, and underweight) [29]. Evaluating

the nutritional status of individuals and as a whole

population is not only helpful to the workers of public

health, but also helps researchers from economic and

social sciences to analyze the economic standards of

those individuals [30]. In this endeavor, we have under-

taken empirical research to evaluate the nutritional status

of children living in rural areas of Tamil Nadu.

2. METHODS AND MATERIALS

2.1. Stu dy Area

The study was carried out in 6 different government

and government aided schools in Pernambut block of

Vello re district in Tamil Nadu, India. Figure 1 shows th e

study location. The schools include; Government Adi

Dravidar Welfare higher secondary school- Pernambut

(A), Government Girls high school-Pernambut (B),

Hindu higher secondary school-Karambur (C), Govern-

ment higher secondary school-Vadacheri (D), Govern-

ment Adi Dravidar Welfare high school-T T Mottur (E)

and Government high school-Balur (F). The economic

status of the 6 different locations is given in Tabl e 1. In

the past and present, the mortality rate has been used as a

health indicator by the public health workers [15]. Since

the Pernambut block has the highest mortality rate com-

pared to other parts of Vellore district (including infant

deaths) [31], the study was carried out in this region.

Table 1. General information of the study area*.

Title School A School B School C School D School E School F

Name of the village/town Pernambut Pernambut Karambur Vadacheri T T Mottur Balur

Taluk GudiyathamGudiyathamVaniyambadi Vaniyambadi Gudiyatham Gudiyatham

District Vellore Vellore Vellore Vellore Vellore Vellore

Total population 6932 6932 1716 2333 4102 5235

Male population 3481 3481 870 1149 2077 2644

Female population 3451 3451 846 1184 2025 2591

Literacy rate 56.94 56.94 77.7 74.07 59.49 67.89

Sex ratio 991 991 972 1030 975 980

Farmers 57 57 120 91 230 272

Industrial workers 1466 1466 14 37 95 46

Other workers 703 703 118 290 318 765

Agricultural labourers 443 443 21 100 983 1104

Village area (in hectares) 1088.48 1088.48 207.07 292.89 762.68 706.31

Total agricultural area (i n hectares) 56.34 56.34 175 194 621.70 78.92

*(Source: http://www.census2001.tn.nic.in and District census handbook 1991, Tamil Nadu, retrieved on 10thJuly 2010).

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(Indian and Tamil Nadu political map, Source: www.mapsofindia.com, Accessed on July, 2010; Vellore district map, Source: www.atsui6.dharkness.info, Ac-

cessed on October, 2010)

Figure 1. Location of the study area.

2.2. Stud y Subjects

Around 810 school students (both boys and girls)

from the above mentioned schools of the age group 11 -

18 years participated in the study. As the study was car-

ried out as a part of the National Service Scheme (NSS)

program, permission was granted to us by the respective

headmasters of the schools. A team of 15 stud ents under

one faculty head visited each of the six schools during

the first quarter of 2010.

2.3. Anthropometry and Data Analysis

As previously mentioned, BMI was calculated for all

the students who participated. Moreover, the WHO still

favours the use of BMI in assessing the nutritional status

of children. The following formula was used to calculate

BMI [32].

BMI = (Weight in Kilogram)/(Height in metre)2

The unit for BMI is Kg/m2. Before measurements, we

visited each class and provided the students with infor-

mation about BMI, good food habits and so on. Height

of the students was measured using a metal tape, which

was permanently fixed to a vertical wooden stand. The

students (without footwear) were asked to stand straight

against the tape and the height was noted to the nearest

1cm. The weight machine which is generally available in

the hospitals in India was used to measure the weight of

the children. The weight was measured to the nearest 0.5

Kg. During all these measurements, the students were

wearing their school uniform. The weight of the school

uniform did not interfere with the individual’s weight.

The BMI was calculated using a standard scientific cal-

culator (Casio®, Japan). These data were initially noted

in a registry notebook. Each of the students was pro-

P. Navaneethan et al. / Health 3 (2011) 647-655

650

vided with a health card which contained; 1) the name of

the student, 2) age, 3) height in cm, 4) weight in Kg, 5)

student’s BMI, 6) BMI inference, 7) remarks, and 8)

school seal. In the remarks, based on student’s BMI,

health suggestions were written. Before distributing the

health card, general information regarding each student

was collected. The data were finally entered into Excel

2003 spreadsheets (Microsoft Corporation®, Windows)

for further analysis. For carrying out regression analysis

Quantitative Micro Software).

3. RESULTS

3.1. Students’ Body Mass Index Irrespective

of Age, Sex and Father’s Occupation

The participation percentage of the students was

around 99% (806 out of 810). Irrespective of the age

groups, father’s occupation and sex, as per WHO’s in-

ternational stand ards, out of the 806 students, 83% of the

students were underweight (BMI < 18.5). Only 16% of

the students were in the normal range (BMI 18.5 - 24.9),

the remaining 0.39% and 0.06% were in the BMI range

of 25 - 29.9 (overweight) and 30 - 35.9 (obese) respec-

tively. The overweight and obese population was not that

significant when compared with the underweight popu-

lation. As mentioned earlier, in rural India, there are

more students who are underweight than belonging to

the other BMI categories. For further analysis, we have

classified the students based on their ages for example,

11 - 13, 14 - 16, and 17 - 18 years. Figure 2 shows the

classification of students based on their ages. A recent

study in this direction also showed that BMI varies with

ethnicity [33]. Tables 2 and 3 classify the students based

on international and Asian standards, respectively. Ac-

cording to the Asian standards, 15% of th e stud en ts lie in

the normal range (BMI 18.5 - 22.9), 1% of the students

are overweight (BMI 23 - 27.4) and 0.34% of the stu-

dents are obese (BMI 27.5 - 34.9). The underweight

percentage remains the same to the International stan-

dards, irrespective of the ages of the students.

3.2. Students’ Body Mass Index in Relation

with Age, Sex and Father ’s Occupation

Several studies have shown that BMI is dependent on

many factors (age, education of the parents, occupation

of the father, socio economic status, food habits and so

on) [34-37]. In our study we concentrated on age, sex

and father’s occupation as main factors. We classified

the students based on their father’s occupation. Figure 3

categorizes the students based on their fathers’ occupa-

tion. We found that a majority of the students in the 6

different schools of the study region come from a low

Figure 2. Age g roup distrib ution of stud ents. The students from

six different schools were classified based on their ages. The

majority of the students were between 14 - 16 years. A = Gov-

ernment Adi Dravidar Welfare higher secondary school-Per-

nambut; B = Government Girls high school-Pernambut; C =

Hindu higher secondary school-Karambur; D = Government

higher secondary school-Vadacheri; E = Government Adi Dra-

vidar Welfare high school-T T Mottur; and F = Government

high school-Balur.

Table 2. Classification of students based on their BMI (International standards).

Age Group Range School A (%)School B (%)School C (%)School D (%) S c ho ol E (%) School F (%)

11 - 13 <18.5 DNA 91.18 83.33 DNA 87.5 80

18.5 - 24.9 DNA 5.88 16.67 DNA 12.5 20

25 - 29.9 DNA 2.94 0 DNA 0 0

30 - 35.9 DNA 0 0 DNA 0 0

14 - 16 < 18.5 89.05 73.04 80.70 73.85 88.31 86.11

18.5 - 24.9 10.22 26.09 17.54 26.15 11.69 13.89

25 - 29.9 0.73 0 1.75 0 0 0

30 - 35.9 0 0.87 0 0 0 0

17 - 18 < 18.5 80.77 DNA 72.22 80.95 100 DNA

18.5 - 24.9 19.23 DNA 27.78 19.05 0 DNA

25 - 29.9 0 DNA 0 0 0 DNA

30 - 35.9 0 DNA 0 0 0 DNA

DNA = Data Not Available.

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Table 3. Classification of students based on their BMI (Asian standards).

Age Group Range School A (%)School B (%)School C ( % )School D (%) School E (%) School F (%)

11 - 13 < 18.5 DNA 91.18 83.33 DNA 87.5 80

18.5 - 22.9 DNA 5.88 16. 67 DNA 12.5 20

23 - 27.4 DNA 0 0 DNA 0 0

27.5 - 34.9 DNA 2.94* 0 DNA 0 0

14 - 16 < 18.5 89.05 73.04 80.70 73.85 88.31 86.11

18.5 - 22.9 8.03* 24.35* 17.54 23.08* 11.04* 12.5*

23 - 27.4 2.92* 1.74* 0.88* 3.08* 0.65* 1.39*

27.5 - 34.9 0 0.87 0.88* 0 0 0

17 - 18 < 18.5 80.77 DNA 72.22 80.95 100 DNA

18.5 - 22.9 19.23 DNA 27.78 14.29* 0 DNA

23 - 27.4 0 DNA 0 4.76* 0 DNA

27.5 - 34.9 0 DNA 0 0 0 DNA

DNA = Data Not Available; * = Values that dif fer from International standards.

(a) (b)

(c)

Figure 3. Classification of students based on age, school and father’ s occupation. (a) Age group 1 1 - 13 years; (b) Age group 14 - 16 years

and (c) Age group 17 - 18 years. In all these cases, it was found that the majority of the students come from low SEB and their fathers’ were

daily wagers. A = Government Adi Dravidar Welfare higher secondary school-Pernambut; B = Government Girls high school-Pernambut;

C = Hindu higher secondary school-Karambur; D = Government higher secondary school-Vadacheri; E = Government Adi Dravidar

Welfare high school-T T Mottur; and F = Govern ment high school -Balur; L = Farmer; S = Shopkeeper; Q = Daily wagers; G = Govern-

ment employees; P = Business (includes making and selling of Beedi) and M = Miscellaneous.

Socio Economic Background (SEB) and their fathers’

were daily wagers. We predicted that this may have af-

fected their BMI and may have also attributed to a higher

number of infant deat hs in the region.

3.3. Regression Analysis and Model

Equation

To confirm the relationship of students’ BMI with their

age, sex and father’s occupation we carried out a regres-

sion analysis to develop a model. Father’s occupation

was divided into 3 levels of income; Low, Medium and

High. Based on this, a regression analysis was carried

out. Low income = Daily wagers; Medium income =

Farmers, Shopkeepers, Beedi makers; High income =

Government employees, Business (excludes making and

selling of Beedi) and Miscellaneous. For this analysis,

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652

we had data for around 799 students. Initially, we com-

pared BMI with age and BMI with father’s occupation

of the students separately. Figure 4 shows the compari-

son of BMI with age and BMI with father’s occupation

of the students separately. These comparisons yielded a

relationship. With this as base, we then developed a re-

gression model. Figure 5 show s the output of regression

analysis. The equation is given below,

BMI = T1* AGE + T2 * JOB –T3 * SEX + C (1)

Where, T1 = 0.3130117077; T2 = 0.3691940514; T3 =

1.153516538; C = 11.88263 747.

(a)

(b)

Figure 4. Relationship of BMI with age (a)

and with father’s occupation (b). Father’s oc-

cupation was divided into 3 levels of income;

Low, Medium and High. Based on this, a re-

gression analy sis was carri ed out. Low in com e

= Daily wagers; Medium income = Farmers,

Shopkeepers, Beedi makers; High income =

Government employees, Business (excludes

making and selling of Beedi) and Miscella-

neous.

We have assigned “0” for female students and “1” for

male students in our analysis for the variable “SEX”.

BMI of students was significantly correlated with their

age, sex and father’s occupation (unadjusted R2 =

0.071663; adjusted R2 = 0.068160). From the regression

analysis output we also found that the residual was ran-

dom. So this implied that the model had a good statisti-

cal basis. Figure 6 shows the residual analysis.

3.4. Students’ Body Mass Index

Independent of Their Blood Group

We also checked whether the blood group of the stu-

dents really affected their BMI. This idea came from a

study, which showed that the diet of an individual can be

designed b ased upon their b lood group (The b lood group

diet spotlight by Juliette Kellow) [38]. The regression

analysis was carried out as mentioned previously with

the inclusion of one more variable: Blood Group. The

output of the analysis showed that BMI was independent

of blood grouped students. Figure 7 show s the output of

regression analysis with inclusion of the variable Blood

Group. The probability of the t-statistic for Blood Group

was 0.7913, which made us infer the independency of

BMI with respect to blood group of students.

3.5. Mean Body Mass Index

We have also analyzed the mean BMI of students on

the basis of age group, as well as on the basis of the

schools. Figure 8 represents the mean BMI based on the

student’s age group. The mean BMI did not touch the

minimum value of the normal BMI range (i.e. BMI 18.5)

in any of the schools. Among these, the highest mean

Figure 5. Output of regression analysis using EViews version

5.1. The output also yielded the following equation: BMI =

0.3130117077 * AGE + 0.3691940514 * JOB – 1.153516538 *

SEX + 11.88263747. R2 = 0.071663. The probability of the

t-statistic was within normal range for all the variables and the

Durbin-Watson stat 2.104001 < 2.6.

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653653

Figure 6. Residual analysis of the regression model using

EViews version 5.1. The residual is random, indicating that the

model had a good statistical basis.

Figure 7. Output of regression analysis including the variable

“BLOOD GROUP” using EViews version 5.1. R2 = 0.071745.

The probability of th e t-stat istic was abov e no rm al r ange for th e

variable “BLOOD GROUP” and within normal range for rest of

the variables and the Durbin-Watson stat 2.103831 < 2.6.

BMI was shown by school B (Age group 14 - 16). It

was followed by school A (Age group 17 - 18). These

age groups have no access to the Mid-Day Meals in

schools. This showed us that Mid-Day Meals have no

impact on the health of students and led us to believe

that the food provided was not healthy, or parents were

illiterate about healthier life styles.

4. DISCUSSION

This study will help public health planners to assess

the health condition of rural children living in Tamil

Figure 8. Mean BMI based on the student’s age group. The

mean BMI did not touch the minimum value of the normal BMI

range (i.e. BMI 18.5; represented by a black line) in any of the

schools. The highest mean BMI was shown by the school B

(Age group 14 - 16 years). A = Government Adi Dravidar

Welfare higher secondary school-Pernambut; B = Government

Girls high school-Pernambut; C = Hindu higher secondary

school-Karambur; D = Government higher secondary school-

Vadacheri; E = Government Adi Dravidar Welfare high school-

T T Mottur; and F = Government high school-Balur.

Nadu. Nearly 80% of the school children were under-

weight. The underweight children are highly prone to

various kinds of infections, as they have low immune

power. This may be one of the factors that attributed to

the high mortality rate in the region.

The Equation (1) that we derived on regression analy-

sis showed that for a particular age, the BMI of female

students was greater than that of male students. The

same was proved by Sproston et al. [39]. The model also

showed that there are other factors that affect the health

of children. However, much further study needs to be

carried out on the role of parents’ education on children’s

health. This is an important variable that has a signifi-

cant effect on the BMI of students.

The Government of Tamil Nadu started the Mid-Day

Meals Program (MDMP) during the period of Mr. Ku-

marasami Kamaraj, who was the Chief Minister of Tamil

Nadu from 1954-63. Apart from this, he has introduced

free school uniforms to weed out caste, creed and class

distinctions among young minds. The agenda of this

program was essentially to increase the literacy rate in

the state. Initially, many people criticized this program,

but later the program gained momentum as it increased

the attendance of children in government schools. From

the 15th August, 1995, the union government of India

started financing the Cooked Mid-Day Meal Program

(CMDM). At present, Mid-Day Meals are given to

school children up to the age of 14 years (till 8th stan-

dard). Our study has shown that, children eating

Mid-Day Meals do not have normal BMI values (both

for Asian and internatio nal standards). Their BMI is less

with respect to those standards, as with the other age

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groups (14 - 16, 17 - 18). In India, ev en after introducing

the Mid-Day Meals scheme more than a decade ago, and

in the state of Tamil Nadu, a few decades ago, the num-

ber of school children who are und erweight is still on th e

rise. Thus, the food given for Mid-Day Meals needs to

be checked thorough ly to maintain its nutrition al quality.

Moreover, Mid-Day Meals alone cannot improve the

health of students. The parents have to be taught about

healthier life styles. There are many parameters that are

interrelated.

Several countries have formulated better policies;

thereby, they have shown improvement in reducing the

number of underweight children. Bhutan, a neighboring

country of India, has halved the number of underweight

children within a span of 10 years [40]. Even though the

Mid-Day Meal Program covered improving the nutri-

tional status of students in its agenda, the same was not

seen in practice. For every health program, there should

be high political commitment in order to make the pro-

gram a grand success [41]. Moreover, the program

should be evenly coordinated in all the villages.

Apart from regular meals, the students should also be

provided seasonal fruits on particular days in a week,

which are available at cheaper prices during that par-

ticular season [42]. A study has shown that women’s

education can improve the nutritional status of children

[43]. Until now, Mid-Day Meals are given to children

only till the age of 14 years. This program should be

exte nded until the ag e of 19 years. The age group o f 10 -

19 years is a crucial period in one’s life. The education

during this period decides the fate of an individual in

India. Our study clearly shows that the children above 14

years are still malnourished in the rural areas. So in

order to improve the ch ildren’s education and health , this

program should further include children until 19 years of

age. Children’s health and education will certainly im-

prove the social and economic environment in the region.

Any innovations, and in this case, Mid-Day Meals, will

benefit the children only if it is exploited to the fullest

extent. Moreover, the food being provided during

Mid-Day Meals should be hygienic [42]. Quality assess-

ment procedures should also be implemented in the

Mid-Day Meals Program. The total calories required per

student should be revised periodically and should be

region-specific.

5. ACKNOWLEDGEMENTS

We thank the VIT University Management and the Institute for So-

cial and Economic Change authorities, for their constant support and

encouragements. We thank the VIT University’s NSS team. The au-

thors would also like to extend their gratitude to Hu Di, student, of The

Central University of Finance and Economics, China for her valuable

suggestions. The authors also thank Cody Nathaniel Jones, Linfield

College, Oregon and Simon Vyse, University of Leicester for their

critical reviews on the paper.

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