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108

CHAPTER –V

HOUSEHOLD DEPRIVATION AND

NUTRITIONAL STATUS OF PRESCHOOL

CHILDREN IN RURAL AREAS OF

KASARAGOD DISTRICT

109

CHAPTER –V

HOUSEHOLD DEPRIVATION AND NUTRITIONAL STATUS OF PRESCHOOL CHILDREN IN RURAL AREAS OF KASARAGOD DIST RICT

5.1 Introduction

Malnutrition directly and indirectly implicated in more than half of all

children’s deaths all over the world. Those children who manage to survive, thousands

are left chronically vulnerable to a variety of diseases and their intellectual abilities

crippled for the rest of their lives. Such a situation places a huge economic burden on

families and the country as a whole. Children in preschool stage require more

attention, as this is the period of rapid growth and development, which makes them

highly vulnerable to malnutrition. Malnutrition in this stage has far reaching

consequences on child’s future by severely affecting child’s physical and mental

development.

5.2 Components Household deprivation score

Different studies reveal that household deprivation status has strongly

influenced the child nutritional status among preschool children (Srinivasan and

Mohanty 2004, Srinivasan et al 2007). In this context, the present study constructed a

household deprivation score (HDS) based on the socio-economic status of household.

The index of deprivation is based on simple measurement of deprivation of the

households in three dimensions of deprivation: basic economic assets, basic amenities

and basic communications with the outside world. This deprivation index is not a

direct measure of the economic condition of the household as the per capita income or

expenditure or the standard of living index but a measure of the extent to which the

household is deprived in the above three dimensions. Based on the deprivation score a

household deprivation score (HDS) is constructed. HDS-I includes those which have

no above six possessions or have one or two possessions; it indicates ‘moderate

deprivation’ (MD). HDS-II includes three or four possessions; they indicate ‘just

above deprivation’ (JAD). HDS-III includes five or six items which indicate ‘well

above deprivation’ (WAD). The household deprivation score (HDS) is based on six

variables at the household level. The variables used for these dimensions are in a

binary scale. They are 1) whether the household has a pucca or semi-pucca/kutcha

house, 2) whether the household has some land, 3) whether the household has

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electricity, 4) whether the household has drinking water facilities in the residence, 5)

whether there is at least one literate adult member in the household and, 6) whether the

household has a radio, a T.V, or a newspapers.

5.3 Measurement of Undernutrition

The following are the commonly used indicators of undernutrition that are

based on anthropometric data.

i) Weight-for-age: A child of a given age (in months) and sex is said to be

moderately undernourished when his or her weight (in kgs) falls below two

standard deviations of the median in the reference population, and severely

undernourished, when his or her weight falls below three standard deviations of

the median.

ii) Height-for-age: Similarly, moderate and severe undernutrition can be

ascertained for a given age and sex by comparing the recorded observation on

height (in cms) with that of the median for the reference population.

iii) Weight-for-height: Gender specific and age independent norms are available

on median weights for given heights. If the recorded weight for a given height

is less than standard deviations (or 80%) of the median weight value of the

reference population, the child is identified as moderately undernourished.

The three indices defined above capture different aspects of undernutrition.

Low height-for-age can be taken as an indicator of poor environmental and social

conditions and includes the effects of undernourishment since birth or even before

birth. Low weight-for-height is a measure of current nutritional status. The indicator

based on weight-for-age reflects both long-term undernutrition as well as short-term or

current undernutrition. Child nutritional status is possible to compute Z-scores of the

three nutritional indices weight-for-age, height-for-age and weight-for-height.

5.4 Household deprivation score and Child nutritional status

In India, many studies have been conducted on the nutrition and health status

of preschool children, but they are very scarce on the causative factors of malnutrition.

Rajaram et al (2003) assessed the nutritional status of preschool children in Kerala and

Goa and found a significant relationship between socioeconomic variables and degree

of malnutrition. A similar type of study was also done in North-East India by Rao et al

(2004). The present study assesses the nutritional status of preschool children in rural

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areas of Kasaragod district were measured by weight-for-age (WAZ), height-for-age

(HAZ) and weight-for-height (WHZ). It compute Z-scores of the three nutritional

status indicators. The nutritional status of preschool children was assessed for the

different demographic and socio-economic variables such as household deprivation

score, religion, community, sex, age, birth order, education status of parents,

occupation status of parents, mother’s nutritional status and mother’s knowledge on

nutrition and the results was presented in following tables. Among the samples, there

were a total of 400 preschool children, of whom 209 were boys and 191 were girls.

5.5 Household Deprivation status and Weight-for-age (WAZ)

Adequate nutrition and health during the first several years of life is

fundamental to the attainment of the Millennium development goals for child survival

and the prevention of malnutrition. Poor nutrition during these critical formative years

has both immediate and long-term consequences. The linkage between household

deprivation score and undernourishment in terms of weight-for-age (WAZ) is

explained in table 5.1.

Household deprivation score is constructed on the basis of six possessions.

Type of house is a good index of economic status of the household and it was one of

the indicators of measurement of household deprivation score. In the case of type of

house consists of pucca and semi-pucca/kutcha, 62.5 percent of families occurring

semi-pucca/ kutcha houses and only 37.50 percent have pucca houses. While 31.2

percent lived in semi-pucca/kutcha houses, their prevalence of moderate undernutrition

was more in these families. On the other hand, the prevalence of severe undernutrition

was more in families living in semi- pucca/kutcha houses (5.2%) and pucca (0.8%)

houses.

Landholding status of household is another indicator of household deprivation

score. HDS score categorized in to–having some land and no land. While 89.8 percent

of the households have some land, the remaining 10.2 percent of households have no

land. The cross tabulation of have some land and child undernutrition classification,

the proportion of preschool children with underweight (< -2 to > -3 Z-score) was 30.8

percent, while that of severe underweight (< -3 Z-score) was 5.5 percent. The

proportion of underweight was the lowest in the state of Kerala (NFHS-3, 2005-06).

Around 93.5 percent of the households have electricity facilities available in the

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household. According to DLHS-3 (2007-08) survey, rural Kasaragod has 87.8 percent

electrified households. The survey finding is higher than that of the DLHS-3 survey.

Table 5.1 Relationship between Household deprivation score and Weight-for-age Variables considered for HDS

Weight-for-age (WAZ) Normal

(< -1 to > -2 Z score)

Moderate (< -2 to > -3 Z-

score)

Severe ( < -3 Z-score)

Total

Type of House Pucca 127(31.8) 20(5.0) 3 (0.8)

150 (37.50)

Semi-Pucca/Kutcha 104 (26.0) 125 (31.2) 21 (5.2) 250 (62.5) Landholding status of households Have some land 214 (53.5) 122 (30.5) 22 (5.5) 358 (89.5) No land 17 (4.2) 22 (5.5) 3 (0.75) 42 (10.5) Electricity House is electrified 224 (56.0) 131 (32.8) 19 (4.8) 374 (93.5) House is not electrified 7 (1.8) 14 (3.5) 5 (1.2) 26 (6.5) Drinking Water Facilities Own arrangement within the residence

167 (41.8) 77 (19.2) 14 (3.5) 258 (64.5)

No arrangement within the residence

64 (16.0) 68 (17.0) 10 (2.5) 142 (35.5)

Adult Literacy Presence of adult literate 226 (56.5) 139 (34.8) 23 (5.8) 388 (97.0) No adult literate 5 (1.2) 6 (1.5) 1 (0.2) 12 (3.0) Access of Media At least one of these 202 (50.5) 129 (32.2) 23 (5.8) 354 (88.5) No radio/TV/newspaper 29 (7.2) 16 (4.0) 1 (0.2) 46 (11.5)

Source: Survey data, Figures in parenthesis indicate percentages.

Drinking water facilities available with in the house is another indicator of

household deprivation score. About 64.5 percent of households was getting own

arrangement within the residence. Children from homes, where there is safe drinking

water have significantly reduced the probability of underweight among preschool

children. In the case of adult literacy, about 97 percent of the adult males in the

households surveyed were literate. Possession of at least a primary education

significantly reduced the probability of underweight incidence in study area. Access of

media is another indicator of measuring the household deprivation status. The survey

found that while 11.2 percent of household do not have radio/TV/newspapers, 88.5

percent of families have at least one of these.

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5.6 Household Deprivation status and Height-for-age (HAZ)

The linkage between household deprivation score and stunting in terms of

height-for-age (HAZ) is explained in table 5.2. Household deprivation score is

constructed on the basis of six components, the prevalence of moderate undernutrition

was more in families living in semi-pucca/kutcha houses (37.6%) and pucca (10.8%)

houses. In the study the prevalence of severe undernutrition was seen in families living

in semi- pucca/kutcha houses. Land holding of households directly influences child

nutritional status. Landholding is a symbol of wealth and it improves children’s and

their family health status. 93.5 percent of families have electricity facilities available in

the home and there is no clear indication that of the improvement of child nutritional

status in terms of stunting.

The prevalence of moderate and severe malnutrition was more in families of

semi-pucca/kutcha houses. Adult literacy is one of the indicators of household

deprivation score and it implies that the literacy status of parents increased, the

proportion of undernutrition was reduced consistently. The moderate and severe

malnutrition was reported in own arrangement with in the residence. The present study

revealed that only 3 percent of the adult males in the households were illiterate and

88.5 percent of families have atleast one of the radio/TV/newspapers in their

household.

Table 5.2 Relationship between Household deprivation score and Height-for-age Household Deprivation Score

Height-for-age (HAZ) Normal (< -1 to > -2 Z score)

Moderate (< -2 to > -3 Z-score)


Total

Type of House Pucca 101 (25.3) 43 (10.8) 6 (1.5) 150 (37.6) Semi-Pucca/Kutcha 74 (18.5) 150 (37.6) 26 (6.5) 250 (62.5) Landholding status of households Have some land 163 (40.9) 170 (42.6) 25 (6.3) 358 (89.5) No land 13 (3.25) 23 (5.8) 6 (1.5) 42 (10.5) Electricity House is electrified 169 (42.2) 178 (44.5) 27 (6.8) 374 (93.5) House is not electrified 6(1.5) 16 (4.0) 4 (1.0) 26 (6.5) Drinking Water Facilities Own arrangement within the residence

128 (32.0) 114 (28.5) 16 (4.0) 258 (64.5)


47 (11.8) 80 (20.0) 15 (3.8) 142 (35.5)

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Adult Literacy Presence of adult literate 172 (43.0) 187 (46.8) 29 (7.2) 388 (97.0) No adult literate 3 (0.8) 7 (1.8) 2 (0.5) 12 (3.0) Access of Media At least one of these 154 (38.5) 170 (42.5) 30 (7.5) 354 (88.5) No radio/TV/newspaper 21 (5.2) 24 (6.0) 1 (0.2) 46 (11.5) Source: Survey data, Figures in parenthesis indicate percentages.

5.7 Household Deprivation status and Weight-for-Height (WHZ)

Interrelationship between Household deprivation status components and

wasting in terms of weight-for-height (WHZ) is clearly shown in table 5.3. The

prevalence of moderate wasting was more in families living in semi-pucca/kutcha

houses (22%) and pucca (4%) houses. On the other hand, the prevalence of severe

wasting was more in families living in semi-pucca/kutcha houses (3%) and pucca

(0.8%) houses. The prevalence of moderate and severe wasting was highest in

households have their own landholding. It reveals that there is no relation between

landholding of households and wasting of preschool children.

Table 5.3 Relationship between Household deprivation score and Weight-for-height Household Deprivation Score Weight-for-height (WHZ)

Normal (< -1 to > -2

Z score)


score)

Severe ( < -3 Z-

score)

Total

Type of House Pucca 131 (32.8) 16 (4.0) 3 (0.8) 150 (37.5) Semi-Pucca/Kutcha 150 (37.5) 88 (22.0) 12 (3.0) 250 (62.5) Landholding status of households Have some land 259 (64.8) 86 (21.5) 14 (3.5) 359 (89.8) No land 22 (5.5) 18 (4.5) 1 (0.2) 41 (10.2) Electricity House is electrified 271 (67.8) 90 (22.5) 13 (3.2) 374( 93.5) House is not electrified 10 (2.5) 14 (3.5) 2 (0.5) 26 (6.5) Drinking Water Facilities Own arrangement within the residence

196 (49.0) 52 (13.0) 10 (2.5) 258 (64.5)


85 (21.2) 52 (13.0) 5 (1.2) 142 (35.5)

Adult Literacy Presence of adult literate 276 (69.0) 97 (24.2) 15 (3.8) 388 (97.0) No adult literate 5 (1.2) 7 (1.8) 0 (0) 12 (3.0) Access of Media At least one of these 248 (62.0) 92 (23.0) 14 (3.5) 354 (88.5) No radio/TV/newspaper 33 (8.2) 12 (3.0) 1 (0.2) 46 (11.5) Source: Survey data, Figures in parenthesis indicate percentages.

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5.8 Household Deprivation status and Child Nutritional status

Household deprivation status are based on the deprivation score, it was

constructed on the basis of household deprivation score (HDS). In HDS-I indicate

Moderate deprivation (MD); which those which have no above six possessions or have

one or two possessions. Thus, HDS-I indicates the deprived sections of the population.

Three or four possessions as in HDS-II; they indicates just above deprivation (JAD)

and five or six items in HDS-III, they indicates well above deprivation (WAD). This

deprivation index is not a direct measure of the economic condition of the household

as the per capita income or expenditure or the standard of living index but a measure

of the extent to which the household status was indirectly elicited (Srinivasan and

Mohanty 2004, 2008). Child nutritional status is possible to compute Z-scores of the

three nutritional indices weight-for- age (WAZ), height-for-age (HAZ) and weight-for-

height (WHZ).

Table 5.4 Relationship between Household deprivation score and Child nutritional status Household Deprivation Score

Child Nutritional status Total

Normal (< -1 to > -2 Z

score)


score)


Weight-for-Age (WAZ) HDS-I 17 (38.63) 23 (52.27) 4 (9.9) 44 (100.0)

HDS-II 79 (43.64) 85 (46.93) 17 (9.39) 181 (100.0) HDS-III 135 (77.14) 37 (21.14) 3 (1.71) 175 (100.0)

Height-for-Age (HAZ) HDS-I 11 (25.0) 29 (65.90) 4 (9.09) 44 (100.0) HDS-II 60 (33.15) 98 (54.14) 23 (12.70) 181 (100.0)

HDS-III 104 (59.42) 67 (38.29) 4 (2.29) 175 (100.0)

Weight-for-Height (WHZ)

HDS-I 22 (50.0) 20 (45.45) 2 (4.55) 44 (100.0) HDS-II 111 (61.33) 60 (33.15) 10 (5.52) 181 (100.0) HDS-III 148 (84.57) 24 ( 13.71) 3 (1.71) 175 (100.0)


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Table 5.4 clearly revealed that interrelationship between household

deprivation score and child nutritional status are expressed in terms of weight-for-age

(WAZ), height-for-age (HAZ) and weight-for-height (WHZ). HDI-I, HDI-II and HDI-

III includes 11 percent, 45.2 percent and 43.8 percent of preschool children

respectively. On the basis of weight-for-age classification, 52.27 percent, 46.93

percent and 21.14 percent of preschool children were moderately underweight in

HDS-I, HDS-II and HDS-III groups and severe underweight was more seen in HDS-I

group. Height-for-age (HAZ) classification, 65.90 percent, 54.14 percent and 38.29

percent of preschool children were moderately stunted in HDS-I, HDS-II and HDS-III

groups. But severe stunted was more seen in HDS-II group. According to weight-for-

height (WHZ) classification, 45.45 percent, 33.15 percent and 13.71 percent of

preschool children were moderately wasted in HDS-I, HDS-II and HDS-III groups.

Most of the studies showed that low economic status of households were the

most affected by child nutritional status and some local studies in India (Steinhoff et

al,1986; Ravishankar,2002; Susmitha Bharati et al,2008; Elangovan and

Shanmugan,2003) showed that the higher the level of economic status of the

household, the lower level of child malnutrition. These results confirm the earlier

findings that show household deprivation status begins to have its effect on the

nutritional status right from ‘in-utero’ an continues in the rapid stages of development

leading to malnourished children such children grow up as undernourished adults with

reduced work capacity resulting in poverty and thereby malnutrition continues to be

next generation. This study also found that household deprivation score is a stronger

determinant of nutritional status of preschool children in rural areas of Kasaragod

district. Thus, it can be said that malnutrition is both a cause and consequence of

economic status which is the key determinant of the nutritional status of preschool

children.

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Figure 5.1 Undernutrition by Household deprivation score

Stunting by Household deprivation score

0

10

20

30

40

50

60

70

HDS-I HDS-II HDS-III

Household deprivation score

Deg

ree

of

stu

nti

ng

Normal

Moderate

Severe

Wasting by Household deprivation score

0102030405060708090



Deg

ree

of

Was

tin

g

Normal

Moderate

Severe

Undernutrition by Household deprivation status

0102030405060708090



Deg

ree

of

Un

der

wei

gh

t

Normal

Moderate

Severe

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5.9 Nutritional status and Religion

Table 5.5 revealed that relationship between child nutritional status and

religion, the study found that 69 percent of households are from Hindu religion, 21.2

percent Muslims and remaining from Christians. According to weight-for-age

classification, moderate undernutrition was 36.2 percent and their corresponding

religion wise categorization were 22.5 percent, 11.2 percent and 2.5 percent

respectively among the Hindu, Muslims and Christians families and severe

undernutrition was more seen in Hindu families. In the same way, according to

height-for-age classification, moderate stunting 48.5 percent and it was more seen in

Hindu families. On the basis of weight-for-height, moderate wasting was higher in

Hindu families. NFHS-3 state report for Kerala reveals that Hindu and Muslim

children were equally likely undernourished, but Christian children are considerably

better nourished. The present study also reveals results of the same direction.

Table 5.5 Relationship between Religion and Child nutritional status Religion Child Nutritional status Total

Normal (< -1 to > -2 Z score)



Weight-for-Age (WAZ) Hindu 167 (41.8) 90 (22.5) 19 (4.8) 276 (69.0) Christian 28 (7.0) 10 (2.5 ) 1(0.2) 39 (9.8)

Muslim 36 (9.0) 45 (11.2) 4 (1.0) 85 (21.2) Total 231 (57.8) 145 (36.2) 24 (6.0) 400 (100.0) Height-for-Age (HAZ) Hindu 127 (31.8) 130 (32.5) 19 (4.8) 276 (69.0) Christian 25 ( 6.2) 13 (3.2) 1 (0.2) 39 (9.8) Muslim 23 (5.8) 51(12.8) 11 (2.8) 85 (21.2) Total 175 (43.8) 194 (48.5) 31 (7.8) 400 (100.0) Weight-for-Height (WHZ) Hindu 195 (48.8) 70 (17.5) 11(2.8) 276 (69.0) Christian 33 (8.2) 6 (1.5) 0 (0) 39 (9.8) Muslim 53 (13.2) 28 (7.0) 4 (1.0) 85 (21.2) Total 281 (70.2) 104 (26.0) 15 (3.8) 400 (100.0)


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5.10 Nutritional status and Community

Table 5.6 provides information about the interrelationship between nutritional

status and community. Generally community divided in to three categories; - SC/ST,

OBC and others. While 59.2 percent of households belong to backward communities

(OBC), 17 percent belongs to Scheduled castes and Scheduled tribes. Among the 17

percent of SC/ST children occurs at 10.2 percent and 2.5 percent were moderate and

severe undernutrition respectively in rural areas of Kasaragod district. While 59.2

percent of OBC children were moderate undernutrition was reported at 22 percent and

severe undernutrition was only 3 percent. In the case of moderate stunting, it was

more seen in other backward communities (28.2%) and SC/ST (12.5%) children. On

the other hand, wasting was also higher among OBC (13.5%) and SC/ST (10%)

children. All rounds of NFHS pin points that in Kerala and India, Children belonging

to scheduled castes, scheduled tribes or other backward classes have relatively high

levels of undernutrition according to all three measures (NFHS-1992-93, 1998-99 and

2005-06).

Table 5.6 Relationship between Child nutritional status and Community Community Child Nutritional status Total




Weight-for-Age (WAZ) SC/ST 17 (4.2) 41 (10.2) 10 (2.5) 68 (17.0) OBC 137 (34.2 ) 88 (22.0) 12 (3.0) 237 (59.2)

Others 77 (19.2) 16 (4.0) 2 (0.5) 95 (23.8) Total 231 (57.8) 145 (36.2) 24 (6.0) 400 (100.0) Height-for-Age (HAZ) SC/ST 9 (2.2) 50 (12.5) 9 (2.2) 68 (17.0) OBC 103 (25.8) 113 (28.2) 21 (5.2) 237 (59.2) Others 63 (15.8) 31 (7.8) 1 (0.2) 95 (23.8) Total 175 (43.8) 194 (48.5) 31 (7.8) 400 (100.0) Weight-for-Height (WHZ) SC/ST 25 (6.2) 40 (10.0) 3 (0.8) 68 (17.0) OBC 171 (42.8) 54 (13.5) 12 (3.0) 237 (59.2) Others 85 (21.2) 10 (2.5) 0 (0) 95 (23.8) Total 281 (70.2) 104 (26.0) 15 (3.8) 400 (100.0)


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5.11 Nutritional status and Age of child Table 5.7 Relationship between Child nutritional status and Age Age of child (in months)





Weight-for-Age (WAZ) 0-12 months 24 (6.0) 12 (3.0) 2(0.5) 38 (9.5) 13-24 months 35 (8.8) 15(3.8) 1(0.2) 51 (12.8)

25-36 months 40(10.0) 27 (6.8) 8 (2.0) 75 (18.8)

37-48 months 86 (21.5) 42 (10.5) 8 (2.0) 136 (34.0) 49- 60 months 36 (9.0) 41 (10.2) 4 (1.0) 81 (20.2)

61-71 months 10 (2.5) 8 (2.0) 1 (0.2) 19 (4.8)

Total 231 (57.8) 145 (36.2) 24 (6.0) 400 (100.0) Height-for-Age (HAZ) 0-12 months 18 (4.5) 17 (4.2) 3 (0.8) 38 (9.5) 13-24 months 25 (6.2) 25 (6.2) 1 (0.2) 51 (12.8)

25-36 months 29 (7.2) 39 (9.8) 7(1.8) 75(18.8)

37-48 months 63 (15.8) 60 (15.0) 13 (3.2) 136 (34.0)

49- 60 months 31 (7.8) 44 (11.0) 6(1.5) 81(20.2) 61-71 months 9 (2.2) 9 (2.2) 1 (0.2) 19 (4.8)

Total 175 (43.8) 194 (48.5) 31 (7.8) 400 (100.0) Weight-for-Height (WHZ) 0-12 months 27 (6.8) 9 (2.2) 2 (0.5) 38 (9.5) 13-24 months 39(9.8) 12 (3.0) 0 (0) 51 (12.8) 25-36 months 49 (12.2) 22 (5.5) 4 (1.0) 75 (18.8)

37-48 months 101 (25.2) 30 (7.5) 5 (1.2) 136 (34.0) 49- 60 months 51 (12.8) 27 (6.8) 3 (0.8) 81 (20.2)

61-71 months 14 (3.5) 4 (1.0) 1 (0.2) 19 (4.8) Total 281 (70.2) 104 (26.0) 15 (3.8) 400 (100.0) Source: Survey data, Figures in parenthesis indicate percentages.

121

Figure 5.2 Undernutrition by age of the children

Several studies have reported that the extent of malnutrition varies with the

age of the child and the prevalence of underweight children varied by age. Age of the

preschool children was assessed by obtaining the date of birth records maintained by

the anganwadi workers in the ICDS centres. Table 5.7 reveals that the case of

Underweight

0

5

10

15

20

25

< -1 to > -2 Z score < -2 to > -3 Z-score < -3 Z-score

Degree of Underweight

Per

cent

0-12 months

13-24 months

25-36 months

37-48 months

49- 60 months

61-71 months

Stunting

02468

1012141618


Degree of Stunting

Per

cent

0-12 months

13-24 months

25-36 months

37-48 months

49- 60 months

61-71 months

Wasting

0

5

10

15

20

25

30


Degree of Wasting

Per

cen

t

0-12 months

13-24 months

25-36 months

37-48 months

49- 60 months

61-71 months

122

moderate underweight was 36.2 percent. The age-wise classification was higher in 37-

48 months age category (10.5 %) and 49-60 months age category (10.2 %). Severe

undernutrition was reported in study area was only 6 percent. The higher incidence of

malnutrition among children of 3 to 4 years of age is also reported in the studies of

Ballweg (1972), Ghosh (1989) and Hota et al (1995) because the reason is that poor

infant feeding practices.

According to the height-for-age classification, Moderate and severe stunting of

preschool children in sample population is 48.5 percent and 7.8 percent respectively.

While 15 percent of preschool children in the age group between 37-48 months, 11

percent of the age group between 49-60 months were facing low height-for-age index

identifies chronic malnutrition and it cannot measure short-term changes in

malnutrition. Stunting is associated with a number of long-term factors including

chronic insufficient protein and energy intake, frequent infection, sustained

inappropriate feeding practices and poverty.

Weight-for-height is another anthropometric measure of child nutritional

status. Moderate Wasting was highest (7.5 %) reported in the age group between 37-

48 months and followed 6.8 percent was reported in the age group between 49-60

months. Severe wasting reported in study area was only 3.8 percent only. Low

weight-for-height helps to identify children suffering from current or acute

undernutrition. Wasting is associated with the causes include inadequate food intake,

incorrect feeding practices, disease and infection. The findings of the study showed

that the extent of underweight (<- 2SD and <-3 SD) increased with increasing age.

This is in line with the observations reported by NFHS for almost every state in India

(NFHS-2, 1998-99 and NFHS-3, 2005-06). On the whole, the prevalence and severity

of underweight children varies significantly by age (p< 0.05). The prevalence of

stunting and wasting also followed the same trend. Similar observations were reported

from rural and urban slums across the country (NFHS-2, 1998-99; NFHS-3, 2005-06).

These findings emphasize the need for assessing linear growth at the community level

(which is not included in the current nutrition assessment programme) repeatedly to

enable the policy makers to design appropriate intervention programmes to achieve

normal growth, since growth lost during early years of life cannot be regained in later

years even by providing wholesome nourishing diet.

From the above findings clearly states that preschool children do not form a

homogenous group. It also emphasizes that the estimates of the prevalence of

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malnutrition is largely affected by the included age range. Hence, age of the children

can be considered as determinant of undernutrition among preschool children in study

area.

5.12 Nutritional status and Sex of the children

It is interesting that while a child’s gender has no influence on weight-for-age,

height-for-age and weight-for-height in the study area. Table 5.8 indicates that only

marginal differences in proportion in undernutrition are observed by sex of child in

the case of underweight, stunting and wasting. Data obtained from sample girls

(21.3%) show a slightly (moderately and severe) higher tendency of getting

undernourishment than boys (21%). On the other hand, stunting of preschool children

in study area was male child (28.2%) was almost same as against female children

(28%). A higher proportion of female children had normal weight-for-age and weight-

for-height ratios than their male counterparts. This is in accordance with the reports

from South Asian countries, which have shown that there was no gender bias among

the nutritional status of preschool children in Kerala (Osmani, 1997; Soman, 1992;

Thankappan, 2007).

The extent of moderate and severe degree of underweight, stunting and

wasting was comparatively slightly higher among female children. This is line with

the nutrition picture of almost every state of India. Several nutritionists have

suggested that the negligence of the girl child during illness may tend to deteriorate

their nutritional status rather than differences in food distribution between boys and

girls. The overall nutritional status of male and female preschool children was not to

be statistically significant. However, the biological consequences known to occur in

later life cannot be over looked. Evidence suggests that malnourished female children

grow up as short statured women and give birth to low birth weight babies

characterized by growth retardation throughout the growing period, there by

perpetuating a vicious cycle through generations.

124

Table 5.8 Relationship between Child nutritional status and Sex of the children

Sex of child Child Nutritional status Total

Normal (< -1 to > -2 Z

score)


score)


Weight-for-Age (WAZ) Male 125 (31.2) 74 (18.5) 10 (2.5) 209 (52.2) Female 106 (26.5) 71 (17.8) 14 (3.5) 191 (47.8) Total 231 (57.8) 145 (36.2) 24 (6.0) 400 (100.0) Height-for-Age (HAZ) Male 96 (24.0) 101 (25.2) 12 (3.0) 209 (52.2) Female 79 (19.8) 93 (23.2) 19 (4.8) 191 (47.8) Total 175 (43.8) 194 (48.5) 31 (7.8) 400 (100.0) Weight-for-Height (WHZ) Male 151 (37.8) 52 (13.0) 6 (1.5) 209 (52.2) Female 130 (32.5) 52 (13.0) 9 (2.2) 191(47.8) Total 281 (70.2) 104 (26.0) 15 (3.8) 400 (100.0) Source: Survey data, Figures in parenthesis indicate percentages.

5.13 Nutritional status and Birth order

The proportion of children with normal height-for-age was comparatively

higher among the first born children and the extent of stunting (< - 2SD and <-3 SD)

was higher among children with birth order above three or four. A greater proportion

of first born children exhibited a better weight-for-height ratio than the ones born

later. The association between stunting, wasting and birth order was found to be

significant at 0.05 level. Only the current nutritional status was not influenced by the

birth order of the children, its association with acute and chronic forms of

malnutrition clearly shows it to be a factor determining the nutritional status of

preschool children in study area (table 5.9). These findings reveals that a birth order

of three or more shows a birth interval of less than 24 months which is unhealthy for

the mother. The arrival of younger siblings diverts the mother’s attention of the care

giver. These results strongly emphasize the need to space pregnancies.

125

Table 5.9 Relationship between Child nutritional status and Birth order

Birth Order Child Nutritional status Total




Weight-for-Age (WAZ) 1 114 (28.5) 14 (3.5) 10 (2.5) 138 (34.5) 2 or 3 105 (26.2) 55 (13.8) 11 (2.8) 171 (42.75)

4 or 5 12 (3.0) 73 (18.2) 2 (0.5) 87 (21.75)

6 or higher 0 (0) 3 (0.8) 1 (0.2) 4 (1.0) Total 231 (57.8) 145 (36.2) 24 (6.0) 400 (100.0)

Height-for-Age (HAZ) 1 90 (22.5) 36 (9.0) 12 (3.0) 138 (34.5) 2 or 3 80 (20.0) 78 (19.5) 13 (3.2) 171 (42.75)

4 or 5 6 (1.5) 76 (19.0) 5 (1.2) 87 (21.75)

6 or higher 0 (0) 2 (0.5) 2 (0.5) 4 (1.0)

Total 176 (44.0) 192 (48.0) 32 (8.0) 400 (100.0) Weight-for-Height (WHZ) 1 118 (29.5) 16 (4.0) 4 (1.0) 138 (34.5) 2 or 3 121 (30.25) 40 (10.0) 10 (2.5) 171 (42.75) 4 or 5 34 (8.5) 47 (11.8) 6 (1.5) 87 (21.75)

6 or higher 1 (0.2) 2 (0.5) 1 (0.2) 4 (1.0) Total 274 (68.5) 105 (26.25) 21 (5.25) 400 (100.0)


5.14 Nutritional status and Maternal Education

Preschool children from nutritional point of view depend on mother more than

other members in a family. She is the principal provider of the nutritional care that the

child needs during the preschool age. The type of care she provides depends to a large

extent on her knowledge and understanding of some aspects of basic nutrition and

health care (Yasoda Devi and Geervani, 1998). Several studies made during the past

three decades (Gaisie, 1969; Ruzicka and Kanitkay, 1972; Graham, 1972; Bhuiya et

al, 1986; Victoria et al 1986; Aparna Pandey, 2007) prove that maternal education is

an important determinant of the nutritional status of preschool children. As the

education status of the mothers increased the prevalence of severe malnutrition

ceased. On the whole, the linear growth of children of educated mothers was better

compared to their least education counterparts.

To screen out the linkage between maternal education and child’s nutritional

status, an evaluation of the distribution of the children suffering from moderate/

126

severe malnutrition with respect to mother’s education was made (table 5.10).

Mother’s education could bring about a noteworthy reduction in the incidence of

underweight in preschool children in study area, proportion of moderate underweight

(< -2 to > -3 Z-score) stands at 3 percent for children whose mothers have had no

formal education, as against 18.5 percent for children whose mothers have had at least

primary education. In the case of stunting, proportion of moderate stunted (< -2 to > -

3 Z-score) is as high as 23.8 percent when mother has not gone beyond primary level

of education. Mother’s education has a milder influence on wasting than on stunting

in preschool children. This signifies the importance and necessity of female education

in improving the child nutritional status of the children and hence the future

generation.

Table 5.10 Relationship between Child nutritional status and Maternal education Maternal Education





Weight-for-Age (WAZ) Illiterate 1 (0.2) 12 (3.0) 2 (0.5) 15 (3.8) Primary 90 (22.5) 74 (18.5) 11 (2.8) 175 (43.8) High school 110 (27.5) 43 (10.8) 8 (2.0) 161 (40.2)

Higher secondary 23 (5.8) 12 (3.0) 3 (0.8) 38 (9.5) Graduation and above

7 (1.8) 4 (1.0) 0 (0) 11 (2.8)

Total 231 (57.8) 145 (36.2) 24 (6.0) 400 (100.0) Height-for-Age (HAZ) Illiterate 2 (0.5) 10 (2.5) 3 (0.8) 15 (3.8) Primary 64 (16.0) 95 (23.8) 16 (4.0) 175 (43.8)

High school 83 (20.8) 68 (17.2) 9 (2.2) 161 (40.2)


6 (1.5) 5 (1.2) 0 (0) 11 (2.8)

Total 175 (43.8) 194 (48.5) 31 (7.8) 400 (100.0) Weight-for-Height (WHZ) Illiterate 4 (1.0) 9 (2.2) 2 (0.5) 15 (3.8) Primary 112 (28.0) 56 (14.0) 7 (1.8) 175 (43.8) High school 128 (32.0) 29 (7.2) 4 (1.0) 161 (40.2)


9 (2.2) 2 (0.5) 0 (0) 11 (2.8)

Total 281 (70.2) 104 (26.0) 15 (3.8) 400 (100.0) Source: Survey data, Figures in parenthesis indicate percentages.

127

Figure 5.4 Relationship between Child nutritional status and Maternal education

Maternal education and child weight-for-age

0

5

10

15

20

25

30

Illite

rate

Prim

ary

Hig

hsc

hool

Hig

her

seco

ndar

y

Gra

duat

ion

and

abov

e

Maternal education

Per

cen

t Normal

Moderate

Severe

Maternal education and Child Height-for-age

0

5

10

15

20

25

Illiterate Primary High school Highersecondary

Graduationand above

Maternal education

Per

cen

t Normal

Moderate

Severe

Maternal education and Child Weight-for-height

0

5

10

15

20

25

30

35

Illiterate Primary High school Highersecondary

Graduationand above

Maternal education

Per

cen

t Normal

Moderate

Severe

128

5.15 Nutritional status and Education of father

As the father of the preschool children’s education increased, the proportion of

undernutrition was decreased consistently. The prevalence of moderate underweight

(< -2 to > -3 Z-score) was more with 19.5 percent among primary education and the

prevalence of moderate stunting (< -2 to > -3 Z-score) was more with 24.8 percent

among primary education and the prevalence of moderate wasting was 15.2 percent

among primary education of father. Linkages between the education of father and

nutritional status of preschool children are not statistically significant. Care of

preschool children is mostly depends on the mother’s educational status and their

nutritional awareness. Better education of father is an addition to the mother’s

educational status and this will improve the health and nutritional status of preschool

children.

Table 5.11 Relationship between Child nutritional status and Education of father Education of father





Weight-for-Age (WAZ) Illiterate 8 (2.0) 4 (1.0) 0 12 (3.0) Primary 81 (20.2) 78 (19.5) 13 (3.2) 172 (43.0) High school 83 (20.8) 37 (9.2) 8 (2.0) 128 (32.0)

Higher secondary 32 (8.0) 13 (3.2) 0 (0) 45 (11.2)

Graduation and above

27 (6.8) 13 (3.2) 3 (0.8) 43 (10.8)

Total 231 (57.8) 145 (36.2) 24 (6.0) 400(100.0)

Height-for-Age (HAZ) Illiterate 4 (1.0) 6 (1.5) 2 (0.5) 12 (3.0) Primary 54 (13.5) 99 (24.8) 19 (4.8) 172 (43.0)

High school 69 (17.2) 52 (13.0) 7 (1.8) 128 (32.0)


19 (4.8) 22 (5.5) 2 (0.5) 43 (10.8)

Total 175 (43.8) 194 (48.5) 31 (7.8) 400 (100.0)

129

Weight-for-Height (WHZ) Illiterate 8 (2.0) 4 (1.0) 0 (0) 12 (3.0) Primary 101 (25.2) 61 (15.2) 10 (2.5) 172 (43.0) High school 99 (24.8) 25 (6.2) 4(1.0) 128 (32.0) Higher secondary 38(9.5) 7 (1.8) 0 (0) 45 (11.2) Graduation and above

35 (8.8) 7 (1.80 1 (0.2) 43 (10.8)

Total 281 (70.2) 104 (26.0) 15 (3.8) 400 (100.0)

Source: Survey data, Figures in parenthesis indicate percentages. 5.16 Nutritional status and Maternal Employment status

Under the compulsion of socio-economic, cultural, psychological and many

other factors, mothers in many societies take up employment either at home or away

from home. When mothers move into employment away from home, their daily

schedules become hectic and some of them in response to time pressure reduce the

amount of time they spend on work at home, including meal preparation and child

care (Goebel and Hennon, 1982; Axelson, 1986). Several studies have also shown that

the nutritional status of the preschool children whose mothers are working outside the

home is poor than that of children of non-working women (Grewal et al, 1973;

Aquillon et al 1982; Gopaldas et al 1988; Rabjee and Geissier, 1992). There are also

many studies which justify the contradictory viewpoint by arguing that maternal

employment is related to improved dietary quality of the preschool children

(Touliaators et al, 1984). Although women’s employment enhances the household's

accessibility to income, it may also have negative effects on the nutritional status of

children, as it reduces a mother’s time for childcare. Some studies have revealed that

mothers of the most malnourished children work outside their home (Popkin, 1980;

Abbi et al, 1991). Another study argued that there is no association between maternal

employment and children's nutritional status (Leslie, 1988).

Table 5.12 reveals that 66.2 percent of mothers were spending on work at

home including meal preparation and child care and 26.8 percent of mothers were

engaged in agricultural and allied activities and only 7 percent of mothers are

included in employment class. The prevalence of moderate underweight was highest

(21.2%) in housewife mothers and 13 percent was reported in those mothers are

engaged in agricultural and allied activities. On the other hand, the prevalence of

stunting and wasting was highest in house wife mothers. House wife mother have

130

more malnourished children because they are lived in poor socio-economic status and

there is no decision power in family matters. At the certain extent, housewife mother

is found to be helpful in improving the child’s nutritional health.

Table 5.12

Relationship between Child nutritional status and Maternal employment status

Maternal

Employment

Status


Normal

(< -1 to > -2 Z

score)

Moderate

(< -2 to > -3 Z-

score)

Severe

( < -3 Z-

score)

Weight-for-Age (WAZ)

House wife 168 (42.0) 85 (21.2) 12 (3.0) 265 (66.2)

Agricultural &

allied labourer

44 (11.0) 52 (13.0) 11 (2.8) 107 (26.8)

Employed class 19 (4.8) 8 (2.0) 1 (0.2) 28 (7.0)

Total 231 (57.8) 145 (36.2) 24 (6.0) 400 (100.0)

Height-for-Age (HAZ)

House wife 127 (31.8) 120 (30.0) 18 (4.5) 265 (66.2)

Agricultural &

allied labourer

30 (7.5) 66 (16.5) 11 (2.8) 107 (26.8)

Employed class 18 (4.5) 8 (2.0) 2 (0.5) 28 (7.0)

Total 175 (43.8) 194 (48.5) 31 (7.8) 400 (100.0)


House wife 200 (50.0) 54 (13.5) 11 (2.8) 265 (66.2)

Agricultural &

allied labourer

58 (14.5) 46 (11.5) 3 (0.8) 107 (26.8)

Employed class 23 (5.8) 4 (1.0) 1 (0.2) 28 (7.0)

Total 281 (70.2) 104 (26.0) 15 (3.8) 400 (100.0)


131

Figure 5.4 Relationship between Child nutritional status and Maternal employment status

Maternal employment status and Child Weight-for-age

05

1015202530354045

house wife agricultural & alliedlabourer

employed class

Maternal employment status

Per

cen

t Normal

Moderate

Severe

Maternal employment status and Child Height-for-age

0

5

10

15

20

25

30

35

house wife Agricultural & alliedlabourer

employed class

Maternal employment

Per

cen

t Normal

Moderate

Severe

Maternal emploment status and Child Weight-for-height

0

10

20

30

40

50

60

house wife agricultural & alliedlabourer

employed class

Maternal employment

Per

cen

t Normal

Moderate

Severe

132

5.17 Nutritional status and Father’s Employment Status Table 5.13 Relationship between Child nutritional status and Father’s employment status Occupation of father





Weight-for-Age (WAZ) Agricultural labourer

56 (14.0) 52 (13.0) 9 (2.2) 117 (29.2)

Owner cultivator 17 (4.2) 11 (2.8) 1 (0.2) 29 (7.2) Artisans 45 (11.2) 18 (4.5) 3 (0.8) 66 (16.5)

Employed class 46 (11.5) 11 (2.8) 5 (1.2) 62 (15.5) Business 12 (3.0) 10 (2.5) 2 (0.5) 24 (6.0)

Others 55 (13.8) 43 (10.8) 4 (1.0) 102 (25.5) Total 231 (57.8) 145 (36.2) 24 (6.0) 400 (100.0)

Height-for-Age (HAZ) Agricultural labourer

41 (10.2) 65 (16.2) 11 (2.8) 117 (29.2)

Owner cultivator 16 (4.0) 13 (3.2) 0 (0) 29 (7.2)

Artisans 33 (8.2) 30 (7.5) 3 (0.8) 66 (16.5)

Employed class 39 (9.8) 20 (5.0) 3 (0.8) 62 (15.5) Business 7 (1.8) 14 (3.5) 3 (0.8) 24 (6.0) Others 39 (9.8) 52 (13.0) 11 (2.8) 102 (25.5)

Total 175 (43.8) 194 (48.5) 31 (7.8) 400 (100.0)

Weight-for-Height (WHZ) Agricultural labourer

70 (17.5) 42 (10.5) 5 (1.2) 117 (29.2)

Owner cultivator 22 (5.5) 7 (1.8) 0 (0) 29( 7.2) Artisans 50 (12.5) 15 (3.8) 1 (0.2) 66 (16.5) Employed class 53 (13.2) 6 (1.5) 3 (0.8) 62 (15.5)

Business 14 (3.5) 8 (2.0) 2 (0.5) 24 (6.0) Others 72 (18.0) 26 (6.5) 4 (1.0) 102 (25.5) Total 281 (70.2) 104 (26.0) 15 (3.8) 400 (100.0)


5.18 Nutritional status and Mother’s Nutritional status

Birth weight, child growth, and adolescent growth determine nutritional status

before and during pregnancy (maternal nutrition). Maternal nutrition also influences

fetal growth and birth weight (ACC/SCN, 1992). The presence of an inter-

133

generational link between maternal and child nutrition means a small mother will

have small babies who in turn grow to become small mothers. Some findings on the

relationship between maternal and child nutrition showed that a high proportion of

low birth weight and stunted children were observed among malnourished mothers.

The nutritional status of the preschool children has a significant association

with that of their mothers. Thus it can be said that the mother’s nutritional status has a

bearing on her child’s nutritional status up to 5- 6 years of life beginning from ‘in-

utero’. These findings signify the importance of maternal nutritional status in the

growth and development of a child. Evidence has shown that maternal nutritional

status begins to have its effect on the child’s body weight from prenatal life;

undernourished women were reported to be poor in performing child care tasks such

as feeding, maintaining a hygienic environment and taking sick children for health

care, thereby were responsible for deterioration of the child’s nutritional status during

postnatal life. Improving maternal nutritional status is essential for the overall growth

and development of children and unless the mother’s nutritional status is improved,

the child’s nutritional status cannot be expected to improve.

Table 5.14

Relationship between Child nutritional status and Mother’s nutritional status

Mother’s Nutritional status Child Nutritional Status

Normal

(< -1 to > -2

Z score)

Moderate

(< -2 to > -

3 Z-score)

Severe

( < -3 Z-

score)

Total

Weight-for-age (WAZ)

Not underweight 223(55.8) 99 (24.8) 9 (2.2) 331 (82.8)

Underweight 8 (2.0) 46 (11.5) 15 (3.8) 69 (17.2)

Height-for-age (HAZ)

not stunted 175 (43.8) 145 (36.2) 11 (2.8) 331 (82.8)

Stunted 0 (0) 49 (12.2) 20 (5.0) 69 (17.2)


Not wasted 266 (66.5) 61 (15.2) 4 (1.0) 331 (82.8)

Wasted 15 (3.8) 43 (10.8) 11 (2.8) 69 ( 17.2)


134

5.19 Nutritional status and Mother’s knowledge on Nutrition

Mother is the principal caretaker of the child’s nutritional health, it is expected

that a mother having adequate knowledge on etiology of nutritional deficiency signs,

nutritional requirements of the child of different ages and the nutritional composition

of food items can be take better nutritional care of her child than a mother having

inadequate knowledge on these aspects. Several studies (Jelliffe, 1957; Gopalan,

1967; Pascaul, 1972) have attributed the high incidence of malnutrition in preschool

children to nutritional ignorance of the parents. Aquillion et al (1982) observed in

Philippines that mother in the families of the normal category of children had better

knowledge of nutrition than those in families with severe malnutrition. Srikantia and

Sastry (1972) also found that the nutritional knowledge performance of mothers

whose children had a nutritional disorder was significantly poorer than that of mothers

whose children had no nutritional disorders.

The present study, the nutritional status of the preschool children of the study

area was evaluated in terms of their mother’s nutritional knowledge. Nutritional

awareness score (NAS) of mother is constructed on the basis of six questions related

to the attitudes and nutrition awareness of the mother. These answers in a binary

scale. If ‘yes’ is assigned to one and otherwise is zero. Nutritional awareness score is

categorized into three; low, medium and high NAS. Low NAS their corresponding

score ranges from 0 to 1, medium NAS ranges from 2 to 4 and high NAS ranges from

5 to 6. The high NAS indicates that the better nutritional and health awareness of

mother in study area. The results shows table 5.13 that the prevalence of moderate

underweight was high (21%) in medium nutritional awareness score category and

prevalence of stunting was highest in moderate. But in the case of the prevalence of

wasting was highest in low nutritional awareness score category. Thus, the findings of

study area are similar to the observations made in the aforesaid studies.

135

Table 5.15 Relationship between Child nutritional status and Nutritional awareness score Nutritional Awareness Score

Child Nutritional status Total Normal

(< -1 to > -2 Z score)



Weight-for-Age (WAZ) Low 29 (7.2) 59 (14.8) 14 (3.5) 102 (25.5) Medium 192 (48.0) 84 (21.0) 9 (2.2) 285 (71.2) High 10 (2.5) 2 (0.5) 1 (0.2) 13 (3.2)

Total 231 (57.8) 145 (36.2) 24 (6.0) 400 (100.0)

Height-for-Age (HAZ) Low 16 (4.0) 63 (15.8) 23 (5.8) 102 (25.5) Medium 149 (37.2) 128 (32.0) 8 (2.0) 285 (71.2)

High 10 (2.5) 3 (0.8) 0 (0) 13 (3.2)

Total 175 (43.8) 194 (48.5) 31 (7.8) 400 (100.0) Weight-for-Height (WHZ) Low 38 (9.5) 54 (13.5) 10 (2.5) 102 (25.5) Medium 233 (58.2) 47 (11.8) 5 (1.2) 285 (71.2) High 10 (2.5) 3 (0.8) 0 (0) 13 (3.2) Total 281 (70.2) 104 (26.0) 15 (3.8) 400 (100.0) Source: Survey data, Figures in parenthesis indicate percentages.

5.20 Bivariate and Multivariate analysis of Nutritional status of preschool children

Both bivariate and multivariate analyses are employed to identify the

determinants of underweight, stunting and wasting in preschool children. These

analysis focus on two; Outcomes of nutritional status for preschool children; whether

they are undernourished or not. Since the interest is in identifying preschool children

at risk of malnutrition, the dependent variables are coded as 1 if the child is

undernourished and coded as 0 if not. Based on the WHO cutoffs, a two-category

variable of nutritional status of child was created, indicating normal and underweight

or stunting or wasting. For these measures, Z-scores are constructed and standardized

by sex and age using the survey data in rural areas of Kasaragod district in Kerala.

The effect of one variable on the prevalence of malnutrition is likely to be confounded

with the effects of other variables. Therefore, socioeconomic demographic

characteristics were controlled statistically. The variables included as controls are:

religion, community, education of mother, work status of mother, household

deprivation status (measured by an index based on the adult literacy, type of house,

electricity, drinking water facility, access of media and land holding, which is used as

136

a proxy for economic status), sex of child, age of child, nutritional awareness score of

mother and birth order. Among 400 preschool children from rural areas of Kasaragod

district, from whom anthropometric data were collected. The logistic regression

technique can be used not only to identify the risk factor but also to predict the

probability of success. For definition and categories of these variables, see Table 5.16.

Table 5.16 Definition of variables and percentage of distribution of nutritional status of

preschool children in rural areas of Kasaragod district in Kerala

Variables Definition of the variable Percent Religion Hindu Children belongs to Hindu community 69.0 Muslim Children belongs to Muslim community 21.2 Christian Children belongs to Christian

community 9.8

Caste SC/ST

Children lives in a household whose head belongs to Scheduled caste (SC) or Scheduled tribe (ST)

17.0

OBC

Children lives in a household whose head belongs to OBC

59.2

OC Children lives in a household whose head does not belong to OBC or SC/ST

23.8

Education of Mother Illiterate Mother is illiterate 3.8 Primary

Mother is literate with less than 8 years school education

43.8

High school

Mother is literate with high school education

40.2

Higher secondary

Mother is literate with higher secondary education

9.5

Graduation and above Mother is literate with graduation and above

2.8

Work status of Mother House wife Housewife 66.2 Agriculture and others Agricultural and allied labourer 26.8 Employed class Employed class 7.0 Household Deprivation Status HDS-1 High Household deprivation status 11.0 HDS-2 Medium Household deprivation status 45.2 HDS-3 Low Household deprivation status 43.8

137

Sex of child Male Male children 52.2 Female Female children 47.8 Age of child 0-12 months Age of child in between 0-12 months 9.5 13-24 months Age of child in between 13-24 months 12.8 25-36 months Age of child in between 25-36 months 18.8

37-48 months Age of child in between 37-48 months 34.0 49-60 months Age of child in between 49-60 months 20.2 61-71 months Age of child in between 61-71 months 4.8 Nutrition Awareness of Mother Low Low nutritional awareness score of

mother 25.5

Medium Medium nutritional awareness score of mother

71.2

High High nutritional awareness score of mother

3.2

Birth order 1 1 44.8 2 or 3 2 or 3 47.2 4 or 5 4 or 5 7.0 6 or higher 6 or higher 1.0

N Total number of children 400 Source: Survey data.

5.21 Chi-square test and Logistic Regression Analysis

In the bivariate analysis, the chi-square test is employed to see the association

between each of the independent variables under study and the nutritional status of

preschool children as measured by underweight, stunting and wasting, and p-values

less than 0.05 are considered as significant. The chi-square bivariate analysis does not

consider confounding effects; therefore, the net effects of each independent variable

are estimated controlling other factors using the logistic regression multivariate

analysis.

The details of the multivariate statistical technique used for the analysis of

data and the need to use the technique and basic model are briefly provided below.

Logistic regression predicts the probability that the dependent variable event will

occur given a subject’s scores on the dependent variables. In logistic regression has no

assumptions about the distributions of the predictor variables; in logistic regression,

the predictors do not have to be normally distributed, linearly related or of equal

138

variance with in each group. Logistic regression analysis is especially useful when the

distribution of responses on the dependent variable is expected to be nonlinear with

one or more of the independent variables.

Logistic regression is used when the response or dependent variable is

dichotomous (i.e., binary, or 0-1). The predictor variables may be quantitative,

categorical or a mixture of the two. Suppose, the probability of the occurrence of

event Y, [P (Y=1)] depends on a set of explanatory variables X1, X2, X3, ….. Xk.

The basic form of the logistic function is

Where Z, is a linear function of a set of predictor variables, X1, X2, X3, …. Xk , given

by

Z = b0 + b0X1 + b2X2 + …….. + bkXk,

and b0, b1, b2, ….. . bk are regression coefficients.

Logit of P is derived by taking natural logarithm, that is, log [(p/1–p)] = Z

The quantity [(p/1–p)] is called the odds and hence log [(p/1–p)], the log odds.

The coefficients b0, b1, b2,…..bk are similar to regression coefficients and are called

logit regression coefficients.

5.22 Malnourishment among preschool children by Background characteristics

In table 5.17, 5.18 and 5.19, effect of different background characteristics on

prevalence of malnourishment among the children under six years of age in rural

areas of Kasaragod district are shown. Selected background characteristics include

religion, community, education of mother, work status of mother, mother’s age at

marriage, household deprivation status, sex, age, nutritional awareness score of

mother and birth order.

139

Table 5.17 Percentage of Underweight preschool children by selected background characteristics Selected Background characteristics

Underweight among preschool children

χχχχ2 test

Normal (%) Underweight (%)

Religion χ2 = 12.2717 d.f = 2 p-value = 0.002**

Hindu 167 (41.8) 109 (27.2) Muslim 36 (9.0) 49 (12.2) Christian 28 (7.0) 11 (2.8) Caste χ2 = 51.0345

d.f = 2 p-value = 0.000***

SC/ST 17 (4.2) 51 (12.8) OBC 137 (34.2) 100 (25.0) OC 77 (19.2) 18 (4.5) Education of Mother χ2 = 26.5611

d.f = 4 p-value =0.000***

Illiterate 1(0.2) 14 (3.5) Primary 90 (22.5) 85 (21.2) High school 110 (27.5) 51 (12.8) Higher secondary 23 (5.8) 15 (3.8) Graduation and above 7 (1.8) 4 (1.0) Work status of Mother χ2 = 16.7605

d.f = 2 p-value = 0.000***

House wife 168 (42.0) 97 (24.2)

Agriculture and others 44 (11.0) 63 (15.8) Employed class 19 (4.8) 9 (2.2) Mother’s age at marriage χ2 = 6.4678

d.f = 2 p-value = 0.039*

< 18 years 40 (10.0) 47 (11.8) 18-25 years 158 (39.5) 103 (25.8) >25 years 33 (8.2) 19 (4.8) Household deprivation status

χ2 = 48.3176 d.f = 2 p-value = 0.000***

HDS-1 17 (4.2) 27( 6.8) HDS-2 79 (19.8) 102 (25.5) HDS-3 135 (33.8) 40 (10.0) Sex of child χ2 = 0.7602

d.f = 1 p-value = 0.3832

Male 125 (31.2) 84 (21.0) Female 106 (26.5) 85 (21.2) Age of child χ2 = 11.2865

d.f = 5 p-value = 0.045*

0-12 months 24 (6.0) 14 (3.5) 13-24 months 35 (8.8) 16 (4.0) 25-36 months 40 (10.0) 35 (8.8)


140

In Table 5.17, Chi-square test for bivariate analysis reveals that religion, caste,

education status of mother, work status of mother, mother’s mean age at marriage,

household deprivation status, age of child, nutrition awareness of mother and birth

order are the statistically significant in the case of underweight among preschool

children in rural areas of Kasaragod district in Kerala. Sex of child is statistically

insignificant in this case. As education among the masses increases, the awareness of

nutritious food intake and health care increases. In an Indian society the mother takes

all type of care for her children. It is very good determinant to look how much

mother’s education affects the malnourishment of preschool children.

Nutrition awareness of mother χ2 = 48.6990 d.f = 2 p-value = 0.000***

Low 29 (7.2) 73 (18.2)

Medium 192 (48.0) 93 (23.2) High 10 (2.5) 3 (0.8) Birth order χ2 = 10.972

d.f = 3 p-value = 0.000***

1 114 (28.5) 65 (16.2) 2 or 3 105 (26.2) 84 (21.0) 4 or 5 12 (3.0) 16 (4.0) 6 or higher 0 (0) 4 (1.0)

Total 57.8 42.2 100.0 Source: Survey data.

Level of significance:***p<0.001; **p<0.01; *p<0.05

Table 5.18 Percentage of Stunted preschool children by selected background characteristics Selected Background characteristics

Stunting among preschool children

χ2 test

Normal (%) Stunting (%)

Religion χ2 =16.7622 d.f = 2 p-value = 0.000***


d.f = 2 p-value =0.000***


d.f = 4 p-value = 0.004**

Illiterate 2 (0.5) 13 (3.2)

Primary 64 (16.0) 111 (27.8) High school 83 (20.8) 78 (19.5) Higher secondary 20 (5.0) 18 (4.5) Graduation and above 6 (1.5) 5 (1.2)

141



household deprivation status, nutrition awareness of mother and birth order are the

statistically significant in the case of stunting among preschool children in rural areas

of Kasaragod district in Kerala. Sex and age of child are statistically insignificant in

this case.

Work status of Mother χ2 = 17.4091 d.f = 2 p-value = 0.000***

House wife 127 (31.8) 138 (34.5)

Agriculture and others 30 (7.5) 77 (19.2) Employed class 18 (4.5) 10 (2.5) Mother’s age at marriage χ2 = 10.5900

d.f = 2 p-value = 0.005**

< 18 years 25 (6.2) 62 (15.5)

18-25 years 123 (30.8) 138 (34.5) >25 years 27 (4.5) 25 (2.5) Household deprivation status χ2 = 32.0313

d.f = 2 p-value = 0.000***

HDS-1 11 (2.8) 33 (8.2) HDS-2 60 (15.0) 121 (30.2) HDS-3 104 (26.0) 71 (17.8) Sex of child χ2 = 0.8475

d.f = 1 p-value = 0.3572


d.f = 5 p-value = 0.696


37-48 months 63 (15.8) 73 (18.2) 49-60 months 31 (7.8) 50 (12.5) 61-71 months 9 (2.2) 10 (2.5) Nutrition awareness of mother χ2 = 46.8839

d.f = 2 p-value = 0.000***

Low 16 (4.0) 86 (21.5)

Medium 149 (37.2) 136 (34.0) High 10 (2.5) 3(0.8)

Birth order χ2 = 9.6115 d.f = 3 p-value = 0.0221*

1 90 (22.5) 89 (22.2) 2 or 3 79 (19.8) 110 (27.5) 4 or 5 6 (1.5) 22 (5.5) 6 or higher 0 (0) 4 (1.0) Total 43.8 56.2 100.0 Source: Survey data. Level of significance:***p<0.001; **p<0.01; *p<0.05

142

Table 5.19 Percentage of Wasted preschool children by selected background characteristics Selected Background characteristics

Wasting among preschool children

χ2 test

Normal wasting

Religion χ2 = 6.4086 d.f = 2 p-value = 0.040*


d.f = 2 p-value= 0.000***


d.f = 4 p-value = 0.000***

Illiterate 4 (1.0) 11 (2.8)

Primary 112 (28.0) 63 (15.8) High school 128 (32.0) 33 (8.2) Higher secondary 28 (7.0) 10 (2.5) Graduation and above 9 (2.2) 2 (0.5) Work status of Mother χ2 = 18.5316

d.f = 2 p-value = 0.000***

House wife 200 (50.0) 65 (16.2) Agriculture and others 58 (14.5) 49 (12.2) Employed class 23 (5.8) 5 (1.2) Mother’s age at marriage χ2 =17.0286

d.f = 2 p-value =0.000***

< 18 years 46 (11.5) 41 (10.2) 18-25 years 193 (48.2) 68 (17.0) 25-30 years 42 (10.5) 10 (2.5) Household deprivation status χ2 = 32.4619

d.f = 2 p-value = 0.000***

HDS-1 22 (5.5) 22 (5.5) HDS-2 112 (27.8) 70 (17.5) HDS-3 148 (37.0) 27 (6.8) Sex of child χ2 = 0.8367

d.f = 1 p-value = 0.3603


d.f = 5 p-value = 0.4113

0-12 months 27 (6.8) 11 (2.8) 13-24 months 39 (9.8) 12 (3.0) 25-36 months 49 (12.2) 26 (6.5) 37-48 months 101 (25.2) 35 (8.8) 49-60 months 51 (12.8) 30 (7.5) 61-71 months 14 (3.5) 5 (1.2) Nutrition awareness of Mother χ2 = 71.4585

d.f = 2 p-value = 0.000***

Low 38 (9.5) 64 (16.0)

Medium 233 (58.2) 52 (13.0) High 10 (2.5) 3 (0.8)

143



household deprivation status, nutrition awareness of mother and birth order are the

statistically significant in the case of wasted among preschool children in rural areas

of Kasaragod district in Kerala. Sex and age of child are statistically insignificant in

this case.

5.23 Analysis of Logistic regression for Malnourishment by Background

characteristics

Multivariate analysis is employed to identify the determinants of underweight,

stunting and wasting in preschool children. The chi-square bivariate analysis does not

consider confounding effects; therefore, the net effects of each independent variable

are estimated controlling other factors using the logistic regression multivariate

analysis. Logistic regression predicts the probability that the dependent variable event

will occur given a subject’s scores on the dependent variables.

The table 5.20 depicts the results of the multivariate analysis of underweight

among preschool children in relation to socio-economic characteristics. The results of

the logistic regression analysis underweight among preschool children was associated

with religion, community, education status of mother, mean age at marriage, age of

child and nutritional awareness score of mother and these factors are statistically

significant. The overall significance of the logistic regression model has been

provided by the likelihood ratio test, which is highly significant. χ225 = 89.5647 (p-

value = 0.0000).

Birth order χ2 = 10.4958 d.f = 3 p-value = 0.014*

1 132 (33.0) 47 (11.8) 2 or 3 134 (33.5) 55 (13.8) 4 or 5 14 (3.5) 14 (3.5) 6 or higher 1 (0.2) 3 (0.8) Total 70.2 29.8 100.0

Source: Survey data. Level of significance::***p<0.001; **p<0.01; *p<0.05

144

Table 5.20 Summary results of Logistic regression analysis of Underweight among

preschool children by Socio-economic characteristics

Variables Coefficient Std. Error Z-statistic p-value Constant 0.792691 0.926457 0.8556 0.39221 Christian -0.208356 0.548461 -0.3799 0.70403 Muslim 0.983407 0.343239 2.8651 0.00417 *** OBC -0.844891 0.458711 -1.8419 0.06549 * OC -1.32865 0.570668 -2.3282 0.01990 ** Primary -0.775757 0.675971 -1.1476 0.25113 HS -1.46577 0.695159 -2.1085 0.03498 ** HSS -0.568919 0.787735 -0.7222 0.47016 Graduate -0.236769 0.983919 -0.2406 0.80984 Agricultural labour 0.115771 0.352303 0.3286 0.74245 Employed 0.0444871 0.515441 0.0863 0.93122 Mean age at marriage years18_25

0.644677 0.334597 1.9267 0.05401 *

Mean age at marriage years_25

0.800717 0.44532 1.7981 0.07217 *

HDS_2 0.483211 0.422108 1.1448 0.25231 HDS_3 -0.392917 0.444951 -0.8831 0.37721 Female 0.185164 0.237335 0.7802 0.43528 Age in months13_24

0.646549 0.540598 1.1960 0.23170

Age in months25_36

0.489317 0.483888 1.0112 0.31191

Age in months37_48

0.23082 0.457419 0.5046 0.61383

Age in months49_60

0.899518 0.483265 1.8613 0.06270 *

Age in months61_71

0.641072 0.664515 0.9647 0.33468

Medium NAS -0.98519 0.304249 -3.2381 0.00120 *** High NAS -1.4378 0.797572 -1.8027 0.07143 * Bo2or_3 0.0107143 0.250867 0.0427 0.96593 Bo4_or_5 0.225673 0.53317 0.4233 0.67210 Bo_6_or_higher 0.206324 1.32035 0.1563 0.87582 Source: Survey data. Level of significance:***p<0.001; **p<0.01; *p<0.05

Reference category: Hindu, SC/ST, Illiterate, Housewife, Mean age at <18 years, HDS-1, Male, Age in 0-12 months, Low NAS, birth order 1.

Mc Fadden R2 = 0.164378 Likelihood ratio test: χ2

25 = 89.5647 (p-value =0.0000)

145

To identify the determinants of Stunting multivariate analysis was performed

and summary results clearly presented in table 5.21. It reveals that religion,

community, nutritional awareness score of mother are the significant predictors of the

stunting among preschool children in rural areas of Kasaragod district in Kerala.

Stunting is associated with a number of long-term factors including chronic

insufficient protein and energy intake, frequent infection, sustained inappropriate

feeding practices and poverty. The overall significance of the logistic regression

model has been provided by the likelihood ratio test, which is highly significant. χ2 25

= 75.0015 (p-value = 0.0000).

Table 5.21 Summary results of Logistic regression analysis of Stunting among


Variables Coefficient Std. Error Z-statistic p-value

constant 1.06699 0.835734 1.2767 0.20171

Christian -0.710793 0.486459 -1.4612 0.14397

Muslim 0.676895 0.339747 1.9924 0.04633 **

OBC -1.0058 0.469402 -2.1427 0.03214 **

OC -1.26623 0.543551 -2.3296 0.01983 **

Primary 0.747999 0.62187 1.2028 0.22905

HS 0.398231 0.63477 0.6274 0.53042

HSS 0.717958 0.734419 0.9776 0.32828

Graduate 1.24707 0.925533 1.3474 0.17785

Agricultural labour 0.153432 0.332355 0.4616 0.64433

Employed -0.337969 0.487507 -0.6933 0.48815

Mean age at

marriage

years18_25

0.0153634 0.331981 0.0463 0.96309

Mean age at

marriage years_25

0.0393442 0.429964 0.0915 0.92709

HDS_2 0.470788 0.449609 1.0471 0.29505

HDS_3 -0.196273 0.456281 -0.4302 0.66708

Female 0.153659 0.231663 0.6633 0.50715

Age in

months13_24

0.165348 0.38708 0.4272 0.66926

146

Age in

months25_36

-0.0726274 0.347682 -0.2089 0.83453

Age in

months37_48

-0.0983719 0.287034 -0.3427 0.73181

Age in

months61_71

-0.246772 0.551968 -0.4471 0.65482

Medium NAS -0.913493 0.32008 -2.8540 0.00432 ***

High NAS -2.28805 0.786367 -2.9096 0.00362 ***

Bo2or_3 -0.0129289 0.238933 -0.0541 0.95685

Bo4_or_5 0.46509 0.593898 0.7831 0.43356

Bo_6_or_higher -0.907435 1.32568 -0.6845 0.49365

Source: Survey data.



Mc Fadden R2 = 0.136801 Likelihood ratio test: χ2 25 = 75.0015 [p-value = 0.0000]

Table 5.22 reveals that the summary results of logistic regression analysis of

Wasting among preschool children by socio-economic characteristics. Community,

nutritional awareness score of mother are the significant predictors of wasting among

preschool children in rural areas of Kasaragod district in Kerala. The overall

significance of the logistic regression model has been provided by the likelihood ratio

test, which is highly significant. χ2 25 = 83.5209 (p-value = 0.0000).

Table 5.22 Summary results of Logistic regression analysis of Wasting among


Variables Coefficient Std. Error Z-statistic p-value

constant 0.498082 0.939781 0.5300 0.59611

Christian -0.576997 0.663749 -0.8693 0.38468

Muslim 0.191766 0.36019 0.5324 0.59445

OBC -0.736575 0.473118 -1.5569 0.11951

OC -1.23551 0.614542 -2.0104 0.04438 **

Primary 0.0230544 0.64602 0.0357 0.97153

147

HS -0.565999 0.672377 -0.8418 0.39991

HSS -0.0139328 0.786991 -0.0177 0.98588

Graduate 0.485284 1.02616 0.4729 0.63628

Agricultural labour 0.289208 0.376629 0.7679 0.44256

Employed -0.16763 0.599377 -0.2797 0.77973

Mean age at marriage

years18_25

0.0212062 0.33721 0.0629 0.94986

Mean age at marriage

years_25

-0.10351 0.484248 -0.2138 0.83074

HDS_2 0.520173 0.441772 1.1775 0.23901

HDS_3 0.0454255 0.474882 0.0957 0.92379

Female 0.0973068 0.258533 0.3764 0.70663

Age in months13_24 0.737985 0.582824 1.2662 0.20543

Age in months25_36 0.0754294 0.523694 0.1440 0.88547

Age in months37_48 0.241824 0.495892 0.4877 0.62579

Age in months49_60 0.488802 0.51827 0.9431 0.34561

Age in months61_71 0.054517 0.732736 0.0744 0.94069

Medium NAS -1.55584 0.312 -4.9867 <0.00001 ***

High NAS -1.46763 0.786283 -1.8665 0.06197 *

Bo2or_3 -0.217988 0.274711 -0.7935 0.42748

Bo4_or_5 0.155404 0.549351 0.2829 0.77726

Bo_6_or_higher 0.413773 1.373 0.3014 0.76314

Source: Survey data.



McFadden R2 = 0.171506

Likelihood ratio test: χ2 25 = 83.5209 (p- value= 0.0000) 5.24 Conclusion

As is apparent from the data presented above, At a certain uncontrollable

factors as household deprivation status, religion, community, age, sex, birth order

further make it favourable for the onset of malnutrition. But socio-economic factors,

mother’s nutritional status, mother’s educational status and knowledge on nutrition,

148

contribute to a child’s malnutrition status to a large extent, these factors are definitely

controllable. An improvement in the nutritional status of children can be achieved by

creating awareness on the significance of maternal nutritional status, female child

care, significance of growth in early childhood through the existing ‘nutrition

education component’ of the Integrated Child Development scheme (ICDS) and

stressing on infant feeding practices, hygiene of the environment, birth spacing, which

are already in the package but are neglected. The findings of this study stress on the

empowerment of women with education, economic independence and decision

making in child rearing followed by education on nutrition and health care, thereby

achieving an improvement in the nutritional status of preschool children in rural areas

of Kasaragod district in Kerala.

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