Introduction
The
health of the child is the outcome of cumulative
effect of various factors which include
biological, socio-economic, environmental,
parental factors etc. Socio-economic status plays
a significant role in child health. Socio-economic
determinants such as poverty, low education level
and limited access to basic amenities contribute
to higher child mortality rates.[1] Children from
disadvantage backgrounds may face higher risks of
under-nutrition, poor access to health care and
inadequate living conditions.[2] Factors such as
maternal education, rural-urban disparities,
family income, poor nutritional status, completion
of immunization programs and health-seeking
behavior can influence child mortality.[3] Breast
feeding, proper nutrition, hygienic practices and
timely initiation of supplementary foods can
significantly influence a child's health and
development.[4] Studies have shown that higher
levels of maternal education are associated with
lower child mortality rates.[5] The size of the
child at birth including birth weight and
gestational age is an important determinant of
child mortality.[6] Child nutrition outcomes are
recognized as key indicators for tracking the
nutrition and health status of children.[7]
Under this
background, the present study was conducted to
understand the child health and its association
with maternal socio-economic conditions among the
Adivasi children of Jorhat district of Assam.
Materials and Methods
Assam, a state
located in the North-Eastern part of India not
only known for its scenic natural beauty and
biodiversity but also has a unique identity for
producing best quality tea. Tea Industry is the
backbone of Assam economy. Adivasi population also
known as tea tribe or tea garden community is an
integral part of Assam and Assam’s tea industry.
In Assam, the term ‘Adivasi is usually referred to
the emigrant tea garden laborers along with their
present generation whose ancestors were previously
mobilized by colonial planters in the nineteenth
century.[8] They constitute approximately 1/5th
of the State’s population. Assam has a total
population of 31.2 million and the tea garden
communities constitute around 18 to 20 percent
(approximately 6.5 million) of the total
population.
For present study,
seven tea garden areas of Jorhat district were
randomly selected for data collection. Data on
child health and maternal socio-economic
conditions were collected from 409 married women
who have at least a child less than five year of
age through interviews using structured schedules.
Data on birth weight, breast feeding practices,
illness, immunization, overall health of the child
was collected from each mother through interview.
Data on socio-economic conditions like occupation,
household income, and educational attainment were
collected from each mother. The data on income was
divided into three groups such as high income
(above 75th percentile), middle income
group (between 50th-75th
percentile) and low income group (below 50th
percentile). The educational level of the married
women was divided as lower primary (those who
attained class I to class V), upper primary (those
who attained class VI to class IX) and secondary
and above (those who studied up to class X and
above). Occupations of the married women were
divided into permanent tea garden worker, daily
wage earner and housewife. Permanent tea garden
workers enjoy housing facilities, weekly ration,
primary medical care, paid maternity leave and
some other bonus.
Anthropometric
measurements were collected to assess the
nutritional status of children. Anthropometric
measurements such as weight and height were
collected from children aged 1 to 5 years using
standard equipments and procedures. The Child
Growth Standards were used to calculate the z
scores for stunting-height for age (HAZ),
underweight-weight for age (WAZ) and
wasting-weight for height (WHZ).[9] According to
WHO recommendations, a child is considered
stunting when his or her HAZ<-2SD from the
reference population median. A child whose
WAZ<-2SD from the reference population median
is considered as underweight and a child whose
WHZ<-2SD from the reference population median
is considered as wasting. The data were analyzed
using MS-Excel for the present research. The
health of the children was also analyzed in
relation with the socio-economic conditions of the
mothers. In order to test the level of
significance, chi-square test was used.
Results
Table 1 show that
the frequency of the children who had normal birth
weight (between 2.5kg and 4.5kg) and low birth
weight (less than 2.5kg) was 61.37 percent and
38.63 percent respectively. 53.54 percent of the
children were breastfed within 1st hour
of birth and 46.45 percent of the children were
breastfed after 1st hour of birth. Only
26.65 percent of the children were exclusively
breastfed while the higher frequency of children
(73.35%) was not exclusively breastfed. The table
further shows the frequency of children who had
illness during the preceding fortnight from the
day of interview was 13.93 percent. The prevalence
of underweight, stunting and wasting among the
children was 36.67 percent, 40.59 percent and
14.42 percent respectively.
Table 1: Birth weight, initiation of
breast feeding, exclusive breast feeding,
malnutrition and illness of the Adivasi
children
|
Variables
|
N
|
Percentage
|
Birth weight
|
Normal
|
251
|
61.37%
|
Low birth weight
|
158
|
38.63%
|
Initiation Breast feeding
|
Within 1st hour of birth
|
219
|
53.54%
|
After 1st hour of birth
|
190
|
46.45%
|
Exclusive Breast feeding
|
Yes
|
109
|
26.65%
|
No
|
300
|
73.35%
|
Illness
|
Yes
|
57
|
13.93%
|
No
|
352
|
86.06%
|
Malnutrition
|
Underweight
|
150
|
36.67%
|
Stunting
|
166
|
40.59%
|
Wasting
|
59
|
14.42%
|
Table 2 shows the
association of children’s malnutrition and
maternal socio-economic conditions. The prevalence
of underweight was significantly (Χ2=18.63;df=2;
p<0.05) higher among the children whose mothers
belong to low income group (42.86%), followed by
middle income group (41.80%) and the high income
group (18.36%). The frequency of stunting was also
significantly (Χ2=28.98;df=2;p<0.05)
higher among the children whose mothers belong to
low income group (48.68%), followed by middle
income group (46.72%) and the high income group
(17.35%). Further, the significantly (Χ2=6.16;
df=2; p<0.05) higher frequency of wasting was
found among the children from low income group
(17.99%), followed by middle income group (14.75%)
and the high income group (7.14%). The higher
frequency of underweight was found among the
children whose mothers attained secondary and
above education (41.00%), followed by mothers who
attained upper primary education (35.88%) and
lower primary education (31.94%). The frequency of
stunting was higher among the children who mothers
attained secondary and above education (47.00%),
followed by mothers who attained lower primary
education (40.43%) and upper primary education
(38.17%). The higher frequency of wasting was
found among the children whose mothers attained
secondary and above education (16.00%), followed
by mothers who attained upper primary education
(15.27%) and lower primary education (6.38%). The
prevalence of underweight was higher among the
children whose mothers are housewives (40.62%),
followed by permanent tea garden workers (29.82%)
and daily wage earners (29.82%). The frequency of
stunting was highest among the children whose
mothers are daily wage earners (42.97%), followed
by housewives (38.54%) and permanent tea garden
workers (33.33%). The higher frequency of wasting
was found among the children whose mothers are
daily wage earners (15.23%), followed by
housewives (13.54%) and permanent tea garden
workers (12.28%).
Table 2: Malnutrition among children in
relation with mother’s socio-economic
conditions
|
Socio-economic variables
|
N
|
Malnutrition
|
Underweight
|
Stunting
|
Wasting
|
Income level
|
Low
|
189
|
81 (42.86%)
|
92 (48.68%)
|
34 (17.99%)
|
Middle
|
122
|
51 (41.80%)
|
57 (46.72%)
|
18 (14.75%)
|
High
|
98
|
18 (18.36%)
|
17 (17.35%)
|
7 (7.14%)
|
|
Χ2 =18.63;df=2; p<0.05
|
Χ2=28.98;df=2;p<0.05
|
Χ2=6.16;df=2; p<0.05
|
Educational level
|
Lower Primary
|
47
|
15 (31.94%)
|
19 (40.43%)
|
3 (6.38%)
|
Upper Primary
|
262
|
94 (35.88%)
|
100 (38.17%)
|
40 (15.27%)
|
Secondary and above
|
100
|
41 (41.00%)
|
47 (47.00%)
|
16 (16.00%)
|
|
Χ2=1.33;df=2;p>0.05
|
Χ2=2.34;df=2;p>0.05
|
Χ2=2.81;df=2;p>0.05
|
Occupation
|
Permanent tea garden worker
|
57
|
17 (29.82%)
|
19 (33.33%)
|
7 (12.28%)
|
Daily wage earner
|
256
|
94 (29.82%)
|
110 (42.97%)
|
39 (15.23%)
|
Housewife
|
96
|
39 (40.62%)
|
37 (38.54%)
|
13(13.54%)
|
|
Χ2=1.79;df=2;p>0.05
|
Χ2=2.01;df=2;p>0.05
|
Χ2=0.40;df=2;p>0.05
|
Table 3 shows the
relationship between mother’s socioeconomic
conditions and birth weight of the children. The
slightly higher frequency of low birth weight was
found among the children from middle income group
(41.80%), followed by low income group (39.68%)
and high income group (32.65%). The significantly
(Χ2=25.74; df=2; p<0.05) higher
frequency of low birth weight was found among the
children whose mothers attained lower primary
education (72.34%), followed by upper primary
education (35.11%) and secondary and above
education (32.00%). The frequency of low birth
weight was found higher among children whose
mothers are daily wage earners (41.80%), followed
by permanent tea garden workers (40.35%) and
housewives (29.17%).
Table 3: Birth weight of children in
relation with mothers’ socioeconomic
conditions
|
Socio-economic variables
|
N
|
Birth-weight
|
Significance Level
|
Normal
|
Low birth weight
|
Income level
|
Low
|
189
|
114 (60.32%)
|
75 (39.68%)
|
Χ2=2.08;df=2; p>0.05
|
Middle
|
122
|
71 (58.19%)
|
51 (41.80%)
|
High
|
98
|
66 (67.35%)
|
32 (32.65%)
|
Educational level
|
Lower Primary
|
47
|
13 (27.66%)
|
34 (72.34%)
|
Χ2=25.74;df=2; p<0.05
|
Upper Primary
|
262
|
170 (64.88%)
|
92 (35.11%)
|
Secondary and above
|
100
|
68 (68.00%)
|
32 (32.00%)
|
Occupation
|
Permanent tea garden worker
|
57
|
34 (59.65%)
|
23 (40.35%)
|
Χ2=4.78;df=2; p>0.05
|
Daily wage earner
|
256
|
149 (58.20%)
|
107 (41.80%)
|
Housewife
|
96
|
68 (70.83%)
|
28 (29.17%)
|
Table 4 shows the
overall health of the children in relation with
mother’s socioeconomic conditions. The overall
good health of the children was found
significantly (Χ2=34.01; df=2;
p<0.05) higher among the middle income group
(80.32%), followed by high income group (79.59%)
and low income group (52.91%). The overall good
health was significantly (Χ2=13.88;
df=2; p<0.05) higher among the children whose
mothers attained secondary and above education
(75.00%), followed by upper primary education
(68.70%) and lower primary education (44.68%). The
overall good health of the children was higher
among children whose mothers are daily wage earner
(70.31%), followed by permanent tea garden workers
(63.16%) and housewives (62.50%).
Table 4: Overall health of the children
in relation with mothers’ socioeconomic
conditions
|
Socio-economic variables
|
N
|
Overall Health
|
Significance Level
|
Good
|
Not Good
|
Income level
|
Low
|
189
|
100 (52.91%)
|
89 (47.08%)
|
Χ2= 34.01;df=2; p<0.05
|
Middle
|
122
|
98 (80.32%)
|
24 (19.67%)
|
High
|
98
|
78 (79.59%)
|
20 (20.40%)
|
Educational level
|
Lower Primary
|
47
|
21 (44.68%)
|
26 (55.31%)
|
Χ2= 13.88; df=2; p<0.05
|
Upper Primary
|
262
|
180 (68.70%)
|
82 (31.30%)
|
Secondary and above
|
100
|
75 (75.00%)
|
25 (25.00%)
|
Occupation
|
Permanent tea garden worker
|
57
|
36 (63.16%)
|
21 (36.84%)
|
Χ2= 2.50;df=2; p>0.05
|
Daily wage earner
|
256
|
180 (70.31%)
|
76 (29.69%)
|
Housewife
|
96
|
60 (62.50%)
|
36 (37.5%)
|
Discussion
In the present
study, 38.63 percent of newborns had low birth
weight which is a matter of concern because low
birth weight is strongly associated with
peri-natal morbidity and increased risk of
long-term disability1.[10] The COVID-19
pandemic has exacerbated these challenges, leading
to increase economic and social stress.[11] It
also reduces access to adequate prenatal care,
maternal follow-ups and essential supplements
resulting in a higher incidence of LBW newborns
during the lockdown period.[12]
A systematic review
published in 2015 reported that late initiation of
breastfeeding after the first hour of life is
associated with an increased risk of neonatal
death.[13] According to the findings of the
present study, 53.54 percent of children breastfed
within 1st hour of birth which means
almost a half of the children were at an increased
risk of neonatal death.
Brown et al. (2012)
shows that exclusive breastfeeding is one of the
factors that can substantially reduce under 5 year
child mortality rate.[14] Exclusive breastfeeding
is one of the factors that can substantially
reduce under 5 year child mortality rate. World
Health Organization recommends exclusive
breastfeeding for six months, and the continuation
of breastfeeding alongside solid foods for up to
two years.[15] In the present study, it is found
that only 26.65 percent of children are
exclusively breastfed. One of the reasons behind
this can be maternal occupations. Among the
Adivasi people of Assam, active participation of
women in earning livelihood is noted and tea
industry being an informal sector, most of the
women could not get paid maternity leave. Hence,
due to economic hardship, they have to go outside
to work leaving behind their children at home.
This may be one of the reasons for lower frequency
of exclusively breastfed children.
Under-nutrition
accounts for approximately half of all deaths
among children less than five year of age.[16]
Childhood under-nutrition has a long lasting
effect over the life cycle such as cognitive
impairment, lower educational attainment, higher
vulnerability to chronic diseases, and declining
productivity as well as earnings.[17,18] Present
study shows the prevalence of underweight,
stunting and wasting as 36.67 percent, 40.59
percent and 14.42 percent respectively. According
to National Family Health Survey-5, the prevalence
of underweight, stunting and wasting were 32.1
percent, 35.5 percent and 19.3 percent
respectively at national level. The comparison
with the national level depicts the existing
disparities in the improvement of nutritional
status across the country. A study conducted among
the tea garden population had found high
prevalence of underweight among children and
thinness among adults.[19] The financial
circumstances of families play an important role
in predicting the malnutrition of the children as
increased financial power enable people in
spending money toward the ideal nutritional
requirement of their families.[20] A significant
association is found between the nutritional
status and income group in the present study.
Maternal educational level is also found to have
statistically significant association with birth
weight and overall good health of the children in
the present study. Studies have shown that higher
levels of maternal education are associated with
lower under-five mortality rates.[5]
Conclusion
The
present study has highlighted the undernutrition
challenges faced by the Adivasi children of Assam.
The economic plight along with health disparities
is a matter of concern among the Adivasi
population who primarily depends on the tea
gardens and lives in the tea estates. Mother being
the prime care giver, plays a significant role in
the health outcome of her children. Therefore,
efforts should be made to empower women because
educated and financially empowered women have the
potential to bring up healthy children using the
available resources more efficiently.
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|