Malnutrition in India

Running Head: Malnutrition in India

The Effects of Malnutrition on Child Development in Rural India

College of Charleston

Kaitlin Zobel

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India ranks as the highest for child malnutrition in the world, allotting for one-third child

of deaths under the age of five (Black, Allen, Bhutta, Caulfield, Onis, 2008). Many studies have

been conducted to explain the impact of nutrition on child development. Specifically

development of malnourished children in the rural community of India. This review of literature

will focus on assessing the major causes of child malnutrition in India. In India, child

malnutrition is often the result of high levels of exposure to infection and lack of proper infant

and child feeding practices during the first 2-3 years of life (Dhaded and Goudar, 2014). The

scope of this review was limited to peer reviewed articles conducted from 2009-2015. A

comprehensive analysis of the risk factors that affect malnutrition in children of India was

conducted. Factors thought to be the leading causes of malnutrition in children of India include:

socio-economic status, the impact of nutritional availability, and environmental determinants

(Black, Allen, Bhutta, Caulfield & Onis, 2008, Chowdhury & Ghosh, 2011, Ghosh, Chowdhury,

Chandra & Ghosh, 2015, Mukhopadhyay, Mahajan, Louis & Narang, 2012, Fenske, Burns,

Hothorn & Rehfuess, 2013, Sahu, Kumar, Bhat, Premarajan, Sarkar, Roy & Joseph, 2015). The

following six research articles demonstrate and support the factors correlated with malnutrition

on child development in rural areas of India.

In a research article conducted by Dhaded and Goudar (2014), a study was conducted

assessing the impact of breast-feeding on child development at 3 years of age in India. The

prevalence of child under nutrition in India is essentially double that of Sub- Saharan Africa,

calculating for morbidity, mortality, lack of productivity and economic growth (Gragnolati,

Shekar, Gupta, Bredenkamp & Lee, 2014). The focus of this study was the public health concern

with the decline of breast-feeding in developing countries, even after concluding that breast-

feeding leads to many benefits. Breast milk contains LCPUFA, arachidonic and

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docosahexaenoic, which lead to improved cognitive skills, behavior, and decreased rates of

infection in children (Grummer-Strawn, 1996, Vohr, Poindexter, Dusick, McKinley, Wright &

Lager, 2006). The sample consisted of about 530 children at 3 years of age, allowing 20% error

of account of mortality during the 2nd or 3rd year, missed cases, and refusal to participate. The

Ages and Stages Questionnaire assessed the 530 children for developmental delay in India,

growth measurements, and hemoglobin. WHO growth charts were used to the physical growth

rates amongst the sample size. The study tested the number of infections acquired verses

development outcome over the duration of breast-feeding and weaning period. A chi-square test

was used to compare the categorical variables with differences considered significant at P < 0.05

level. The results in this study supported the hypothesis breast-feeding corresponds to a decrease

in mortality amongst children ages 2-3 and an increase in child development in India. Precisely

254 (47.7 %) of the children were exclusively breastfed for 6-12 months and 433 (81.7%) of

mothers had started weaning their children at 12 months and later. A total of 514 (97%) of

children received nutritional supplements. Children who were exclusively breastfed for at least 6

or more months had significantly higher ASQ scores with P value for communication (0.003),

gross motor (0.004), fine motor (0.007), and problem solving (0.013), compared to children

exclusively breastfed for less than six months. It also reported that 69.2% of the children had

hemoglobin percentage more than 11% and children with higher hemoglobin concentration

showed a higher score with ASQ. One limitation of the study was that the covariate analysis

assesses different causes of under-nutrition that are not carried out in the study. Another

limitation was: at the screening level, estimation of hemoglobin should have be carried out using

more accurate methods verses Sahli’s method.

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Next, a study was conducted on the nutritional and socioeconomic status in relation to

cognitive development of Santal children of Purulia district, India. Cognitive development of

children depends on nutritional and socioeconomic factors. The objectives of this research study

by Chowdhury and Ghosh (2011) are to assess the cognitive development and investigate the

relationship of nutritional and SES to cognitive development in children. A sample size of 838

(417 boys and 421 girls) Santal children ages 5-12 was used in the study. Participants were

selected by random sampling from the Balarampur and Bagmundi areas upon approval of

children, parents, and school authorities. Socioeconomic status was measured using the

Kuppusswami scale (Kumar et al., 2007). Chronic and acute under-nutrition were calculated by

Z-score using the age-specific reference values of height-for-age, weight-for-height and weight-

for-age of the WHO (WHO, 1983). Z-scores ranking between +1 and -0.99, -1 and -1.99, -2 and

-2.99 and below -3 were categorized as well nourished, mildly under nourished, moderately

under nourished, and severely under nourished. Statistical analysis of the mean, median, and

standard error of mean values of RCPM scores were computed. The results showed the RCPM

scores of the adequately nourished children and upper-lower SES are significantly higher (p

<0.05) than the children with lower SES and nutritional status. In conclusion of the study, RCPM

scores of Santal children were significantly correlated with nutritional status and SES (p< 0.01).

The results also showed stunting, wasting, and under-weight children in Santal are significantly

associated with IQ scores. More than half of the children studied in the sample size were noted to

be under nourished resulting in a direct effect on cognitive development (Tarleton et al., 2006).

In conclusion, the observed Santal children show lower development levels due to nutrition and

SES. One limitation of the study was that the information received on head circumference related

to nutritional status and cognitive development. According to Botting (1998), head

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circumference is an important indicator of intellectual development. However, in regards to this

present study it proved to not be relative, head circumference remains unaffected with the

development in Santal children (Nwuga, 1997). Another limitation was that no significant

difference in RCPM scores between Santal boys and girls in all age groups observed. This

limitation is perplexing because typically males require more nutrition due to body mass index

and height-to-weight ratio.

Thirdly, an assessment of malnutrition on child development in a school located in

Kolkata, India using a stepwise linear regression model was reviewed. This research article by

Satabdi and Tusharkanti Ghosh, Chowdhury, and Chandra (2015) aimed to figure out the

influence of levels of under nutrition and SES on cognitive development in the children of

Kolkata. A random sampling of 566 children ages 5-12 from various schools. Children with past

surgeries and decreased neurological function skills, or diseases were excluded from this study.

Similar to the previous study, cognitive development was measured by scores of RCPM, chronic

and acute nutritional statuses were measured from height-for-age and weight-for-age values of

WHO, and SES was determined using Kuppuswami scale. The height-for-age ratio observes 57.

95% of children are undernourished and 52.8% according to the weight-for-age ratio. The results

of the study showed a positive correlation between cognitive development by nutrition and SES

of school children in Kolkata, India. Results from the height-to-weight ratio showed that stunting

is higher in boys (66.99%) than girls (47.30%). Weight-to-age results show that a higher

percentage of boys (62.41%) were underweight than girls (41.88%). Thinness was also notably

higher in boys (11.76%) than girls (7.69%). The study noted under-nutrition higher in boys may

be because of the higher amount of boys in the lower SES categories. One limitation of the study

was that the intake of nutrition was not measured in the children’s diet, which potentially aided

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in validating the assessment of the children. Another limitation wass the weight-to-age ratio is

found to be insignificant after the study included age and sex as independent variables,

concluding weight-to-age was not a strong determinant of cognitive development. In conclusion,

under-nutrition and SES decreased cognitive development in children of Kolkata.

Fourthly, a longitudinal growth study by Mukhopadhyay, Mahajan, Louis, and Narang

(2012) of very low birth weight neonates during the first year of life was conducted to identify

the risk factors associated with malnutrition in a developing country. This prospective study

intended to compare risk factor associations between well-nourished and under weight infants.

For the variables in the study, descriptive statistics are used. Continuous variables are studied

using a t-test or u-test and categorical variables are studied using chi-squared or Fisher’s exact

test. A p-value of <0.05 is considered significant in the study. Of the 132, 127, 110, 99 and 101

neonates studied in the year trial at 3, 6, 9, and 12 months, weight and length improved, while

the head circumference declined. As expected, extremely low birth weight neonates showed

poorer growth in the conclusion of the study. Incidence rates of underweight, stunting and

wasting decrease from 40 weeks to one year. The results concluded that the Z-score for weight at

3 months is the independent predictor of malnutrition at one year, with an accuracy of 75.8%.

One limitation of the study was that the aim focus is to find a model for under-nutrition at one

year, so the growth parameters beyond 3 months were not entered into the regression model.

Another limitation was the follow-up was only one year, which was not long enough. Also, the

study did not look up nutritional factors beyond the neonatal period, leading to potentially effect

on long-term growth of the infants sampled. More limitations of the study were that the

researchers were dealing with a high-risk population, and the data collected can’t be relatable to

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the general population. The strengths of their study were the sample size and low dropout rates

of participants.

Fifthly, a comprehensive analysis consisting of socioeconomic status, nutritional status,

and environmental determinants using additive quantile regression unearths the determinants that

lead to child malnutrition in India (Fenske, Burns, Hothorn & Rehfuess, 2013). With the use of

cross-sectional data, this study was aimed to answer two questions: what are the determinants of

child stunting in India and should the established focus be on linear effects of single risk factors

children of ages 0-24 months were sampled from the Indian National Family Health Survey of

2005-2006. Researchers for this study utilize an evidence-based diagram consisting of three

categories (immediate, intermediate and underlying) to help discover the determinants of

stunting in children of India. An additive quantile regression was used for four quantiles of the z-

score height-for-age and logistic regression for stunting and severe stunting. Amongst the eleven

groups of determinants reviewed, at least one variable within each was significantly associated

with height-for-age in the 35% z-score quantile regression. The non-modifiable risk factors were:

child age and sex had the least effects and the protective risk factors: household wealth, maternal

education and BMI had the largest effects. One limitation of this study was the cross-sectional

being in a snapshot nature, consequently makes establishing a sequence of events and drawing

inferences impossible. Another limitation was the studies inability to model the impact of

immediate determinants. Researchers were unable to populate the groups of chronic diseases and

recurrent infections. Also, the study could only partially populate micronutrient deficiencies,

healthcare, maternal or religions.

Lastly, a review was conducted on malnutrition among under-five children in India in

order to implement new strategies for control (Sahu, Kumar, Bhat, Premarajan, Sarkar, Roy &

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Joseph, 2015). The Public Health concern on malnutrition among under-five children in India is

a major concern for authorities, this research study aimed to asses the burden of disease

associated with under-nutrition and over-nutrition, the determinants of both and then to unearth

the strategies needed to eradicate the issue. Annually 2.3 million deaths among 6-60 month aged

children in developing countries are due to malnutrition (World Bank India, Undernourished

Children: A Call for Reform and Action, 2014). The data for the study showed that the

prevalence of under-nutrition in under-five children of India was notably higher and wider,

under-nutrition data reported: under-weight 39 - 75%, stunting: 15.4 -74%, and wasting 10.6 -

42.3%. The results of the data varied based on the methodology assessment carried out to test the

children. The nutritional status of the children was measured by the anthropometric parameters:

weight, height, and BMI. Under-nutrition is measured with weight-for-age, height-for-age, and

BMI-for-age, as well as wasting. The main indicator of nutritional status in the children under-

five in India is weight-for-age. Weight-for-age was the most widely used indicator

(Ramachandran and Gopalan, 2006). The data showed that assessment of over-nutrition status in

under-five children in India were limited. The results of the study determined that there was a

significantly higher proportion of malnutrition among female children verses male children in

West Bengal, also compared to the males of the higher birth order and of those who come from

families with lower per capita income (Dey and Chaudhuri 2008). The study found that

malnutrition is exactly 2.7 times higher in families that have lower household wealth index

(National Family Health Survey, 2005-2006). In order to account for control measures,

researchers investigated for risk factors associated with malnutrition and the influence that mal

nutrition has on the children. The researchers concluded that in order for malnutrition in India

among under-five children to decrease in prevalence, public health interventions must be

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implemented properly. Suggestions for public health interventions were that researchers

increased evaluation methods, more research was conducted on overweight children and

etiological factors associated with obesity, also that appropriate measures be taken to improve

the socioeconomic status of the children. In conclusion to their study, researchers noted that early

detection of low BMI in children is the most beneficial way to plan an intervention in order to

prevent stunting in that child (Ramachandran and Gopalan, 2006). One limitation of this study

was that there was a need for more interdisciplinary research to collect data from families on the

behavorial risk factors associated with the children to conclude why some families are prone to

have children that have a low birth weight-for-age Z-score (Griffiths and Hinde, 2002). The

researchers of this study concluded that the distribution of risk factors and the influence that

these risk factors have on the children must be analyzed in order to properly implement diverse

control methods needed to eradicate malnutrition in under five children of India. Researchers

also concluded from the study that increased population growth and involvement in politics have

an indirect effect on malnutrition in the children, hinting that improvement of socio economic

status of a country could decrease the prevalence of malnutrition. It is vital for researchers to

comprehend the effects that stunting has on children and the preventions necessary to improve

low birth weight and prevent under-five malnutrition in India (Mamidi, Shidhaye, Radhakrishna,

Babu, Reddy, 2001).

This review of literature has outlines the various determinants correlated with

malnutrition in child development in India. The results across the six literature reviews studied

indicate that malnutrition is directly related to stunting child development (Black, Allen, Bhutta

Caulfield & Onis, 2008, Chowdhury & Ghosh, 2011, Ghosh, Chowdhury, Chandra & Ghosh,

2015, Mukhopadhyay, Mahajan, Louis, & Narang 2012, Fenske, Burns, Hothorn & Rehfuess

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2013, Sahu, Kumar, Bhat, Premarajan, Sarkar, Roy & Joseph, 2015). The data in the six

literature reviews all contain identifiable strengths and limitations. Future research on

malnutrition in developing countries should be aware of both factors so they do not recreate the

same flaws in their studies. Insights gained from this research should be used to implement a

plan for a successful intervention. One suggestion for future research would be to use screening

tools along with metabolic parameters to provide etiological factors for developmental delay and

to strengthen the association of child development with etiologies in all domains. The research

conducted in this literature review is important seeing that diet is a modifiable factor and

interventions are available to help improve children’s cognitive development and malnutrition in

India. One suggestion for further research is that researchers consider expanding their studies to

urban areas as well as rural areas in India to ensure a large and relatable sample size (Dhaded and

Goudar, 2012). Finally researchers suggested that in order to manage malnutrition amongst

children in India in the future, public health interventions must be improved. Researchers

suggested that future studies focus on socio economic development, deeper research on

overweight, and obese children, and increased study of etiological factors. (Sahu, Kumar, Bhat,

Premarajan, Sarkar, Roy & Joseph, 2015). It was noted that the factors most closely associated

with socio economic inequality are poverty, illiteracy, lack of awareness regarding education on

nutritional status of food items, over-sized families, and poor sanitation in the environment in

which the children live in (Van de Poel, Hosseinpoor, Speybroeck, Van Ourti, Vega, 2008).

These factors are most often associated with being the cause of malnutrition amongst children in

India. Future studies should focus on the suggestions of the studies reviewed in order to decrease

malnutrition rates in developing countries.

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References

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Black, Allen, Bhutta, Caulfield, Onis, et al. (2008). Maternal and Child Under Nutrition: Global

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Botting, Powls, Cooke, & Marlow. (1998). Cognitive and Educational Outcome of Very Low

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Chowdhury, & Ghosh. (2011). Nutritional and Socioeconomic Status in Cognitive

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Dey and Chaudhuri. (2008). Gender Inequality in Nutritional Status Among Under Five Children

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Malnutrition in India

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