Upload
others
View
3
Download
0
Embed Size (px)
Citation preview
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
110
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
111
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
112
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.
113
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)
Severe ( < -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)
No arrangement within the residence
47 (11.8) 80 (20.0) 15 (3.8) 142 (35.5)
114
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)
Moderate (< -2 to > -3 Z-
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)
No arrangement within the residence
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.
115
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)
Moderate (< -2 to > -3 Z-
score)
Severe ( < -3 Z-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)
Source: Survey data, Figures in parenthesis indicate percentages.
116
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.
117
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
HDS-I HDS-II HDS-III
Household deprivation score
Deg
ree
of
Was
tin
g
Normal
Moderate
Severe
Undernutrition by Household deprivation status
0102030405060708090
HDS-I HDS-II HDS-III
Household deprivation score
Deg
ree
of
Un
der
wei
gh
t
Normal
Moderate
Severe
118
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)
Moderate (< -2 to > -3 Z-score)
Severe ( < -3 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)
Source: Survey data, Figures in parenthesis indicate percentages.
119
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
Normal (< -1 to > -2 Z score)
Moderate (< -2 to > -3 Z-score)
Severe ( < -3 Z-score)
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)
Source: Survey data, Figures in parenthesis indicate percentages.
120
5.11 Nutritional status and Age of child Table 5.7 Relationship between Child nutritional status and Age Age of child (in months)
Child Nutritional status Total
Normal (< -1 to > -2 Z score)
Moderate (< -2 to > -3 Z-score)
Severe ( < -3 Z-score)
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
< -1 to > -2 Z score < -2 to > -3 Z-score < -3 Z-score
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
< -1 to > -2 Z score < -2 to > -3 Z-score < -3 Z-score
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
123
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)
Moderate (< -2 to > -3 Z-
score)
Severe ( < -3 Z-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
Normal (< -1 to > -2 Z score)
Moderate (< -2 to > -3 Z-score)
Severe ( < -3 Z-score)
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)
Source: Survey data, Figures in parenthesis indicate percentages.
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
Child Nutritional status Total
Normal (< -1 to > -2 Z score)
Moderate (< -2 to > -3 Z-score)
Severe ( < -3 Z-score)
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)
Higher secondary 20 (5.0) 15 (3.8) 3 (0.8) 38 (9.5) Graduation and above
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)
Higher secondary 28 (7.0) 8 (2.0) 2 (0.5) 38 (9.5) Graduation and above
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
Child Nutritional status Total
Normal (< -1 to > -2 Z score)
Moderate (< -2 to > -3 Z-score)
Severe ( < -3 Z-score)
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)
Higher secondary 29 (7.2) 15 (3.8) 1 (0.2) 45 (11.2) Graduation and above
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
Child Nutritional status Total
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)
Weight-for-Height (WHZ)
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)
Source: Survey data, Figures in parenthesis indicate percentages.
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
Child Nutritional status Total
Normal (< -1 to > -2 Z score)
Moderate (< -2 to > -3 Z-score)
Severe ( < -3 Z-score)
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)
Source: Survey data, Figures in parenthesis indicate percentages.
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)
Weight-for-Height (WHZ)
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)
Source: Survey data, Figures in parenthesis indicate percentages.
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)
Moderate (< -2 to > -3 Z-score)
Severe ( < -3 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)
37-48 months 86 (21.5) 50 (12.5) 49-60 months 36 (9.0) 45 (11.2) 61-71 months 10 (2.5) 9 (2.2)
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***
Hindu 127 (31.8) 149 (37.2) Muslim 25 (6.2) 14 (3.5) Christian 23 (5.8) 62 (15.5) Caste χ2 = 45.3946
d.f = 2 p-value =0.000***
SC/ST 9 (2.2) 59 (14.8) OBC 103 (25.8) 134 (33.5) OC 63 (15.8) 32 (8.0) Education of Mother χ2 = 15.0257
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
In Table 5.18, 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, 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
Male 96 (24.0) 113 (28.2) Female 79 (19.8) 112 (28.0) Age of child χ2 = 3.0201
d.f = 5 p-value = 0.696
0-12 months 18 (4.5) 20 (5.0) 13-24 months 25 (6.2) 26 (6.5) 25-36 months 29 (7.2) 46 (11.5)
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*
Hindu 195 (48.8) 81 (20.2) Muslim 53 (13.2) 32 (8.0) Christian 33 (8.2) 6 (1.5) Caste χ2 = 53.6908
d.f = 2 p-value= 0.000***
SC/ST 25 (6.2) 43 (10.8) OBC 171 (42.8) 66 (16.5) OC 85 (21.2) 10 (2.5) Education of Mother χ2 = 24.4187
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
Male 151 (37.8) 58 (14.5) Female 130 (32.5) 61 (15.2) Age of child χ2 = 5.0375
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
In Table 5.19, 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, 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
preschool children by Socio-economic characteristics
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.
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 = 0.136801 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
preschool children by Socio-economic characteristics
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.
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.
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.