It can be seen in Table 1 that the total numbers of live birth of under-3 children were 2,994 in last 3 years preceding the survey. Table 1 also shows the mother and child characteristics; which includes survival status of child, sex of child, number of birth by mother, age of mother, education of mother, place of residence of mother, caste of mother, wealth status of mother, relationship of mother with household head, religion of mother, types of cooking fuel used in house and mother work and breastfeeding interaction.
Among 2994 live births, 85 children died before reaching 36 months of the life. Among these children 1871 children were born as the first child of the house and 1123 baby were born as others. Among those children, 363 children’s mothers were below the age of 20 years. Looking at the education status, 70% of children’s mothers had some education, 56% of children’s mothers were from urban areas and 86% of children’s mothers were from Hindu religion. Only around 20% of children’s mothers used LPG gas for cooking, 15% of children’s mothers were household head and around 26% of children’s mothers belongs to nuclear family.
Table 1: Frequency distribution of maternal and child characteristics for under-3 death in Nepal 2012–2014
Mother and children characteristics
|
Under Three Children
n= 2994
|
Frequency
|
Percentage
|
Survival status of under 3 children
|
|
2909
85
|
97.17
2.83
|
Independent Variables
|
Maternal Characteristics
|
Number of birth by mother
|
• First birth
• More than 1 birth
|
1871
1123
|
62.55
37.45
|
Age of Mother at child death
|
• Age 15-19 Years
• Age 20 Years and older
|
363
2631
|
12.10
87.90
|
Education of Mother
|
• No education
• Have some Education
|
883
2111
|
29.49
70.51
|
Place of residence
|
|
|
|
1298
1696
|
43.44
56.56
|
Caste/Ethnicity
|
|
|
• Terai Caste
• Other castes
|
917
2077
|
30.61
69.39
|
Wealth index
|
|
2623
371
|
87.62
12.28
|
Household Relationship
|
|
2517
477
|
84.12
15.88
|
Work and breastfeeding interaction
|
|
|
• No work no breastfeeding
• Work and breastfeeding
• Work but no breastfeeding
• No work breastfeeding
|
211
330
42
2411
|
7.00
11.08
1.40
80.52
|
Family Structure
|
|
2193
801
|
73.23
26.77
|
|
Sex of child
|
|
|
|
1389
1605
|
46.43
53.57
|
Types of cooking fuel
|
|
|
• Wood and other which generates smokes
• LPG and ignitable which do not generates much smoke
|
2386
608
|
79.71
20.29
|
Religion
|
|
409
2585
|
13.79
86.21
|
Analyzing the mother work and breastfeeding interaction, the Table 1 showed that 80% of mothers were not working but breastfeeding their children Further around 7% of the mother were neither working nor breastfeeding their children. Around 11% of the mother were both working and breastfeeding their children and very less percentage less than 2% of mother were working but not breastfeeding their children
Looking at Table 2 it can be seen that the risk of death of under-3 children from a mother who does not have education is 28 percent higher as compared to mothers who have some education. This is supported by the findings from the survey data from 17 developing countries regarding the positive statistical association between maternal education and the health and survival of under-2 years children on post neonatal risk, undernutrition during the 3–23 month period, and non-use of health services (Bicego & Ties Boerma, 1993). Maternal education has a strong positive impact on child survival. Uneducated mothers have the highest risk of child mortality. Mother's education is a strong determinant of child survival in India, Tanzania, and Ethiopia (Armstrong Schellenberg et al., 2002; Das Gupta, 1990; Fenta & Fenta, 2020).
Similarly, the risk of death of under-3 children other than nuclear family is 51% higher. The prevalence of malnutrition in the two rural areas of Peshawar is 35% in children under three years of age. Both socioeconomic factors (large family size of 87% respondents) and maternal factors were responsible for its high prevalence (Gul & Kibria, 2013). Study done in Pakistan found that the education of the mother, birth order number, preceding birth interval, size of child at birth, breastfeeding, and family size were found to have a significant effect on child mortality (Ahmed et al., 2016).
Further, the risk of death of under 3 children in the first baby is 284% higher as compared to the second and third baby of mothers. A Comparative Analysis of child mortality from 39 countries and a study from India found that mortality and risk of dying chance of first children compared to those born in middle and last born child shown to be higher than average while other factors are controlled (Hobcraft et al., 1985; Mishra et al., 2018). Likewise, the risk of death of under-3 children from a mother who is not a household head is 55% higher. It was further supported by the theory of family development and structure and feministic perspectives, according to this theoretical perspective, women experience changes over time such as when the family structure changes from extended family to nuclear family system in recent days. In a nuclear family decision-making power of a woman is high, independent of making decisions, and will involve in income-generating work (Carter & McGoldrick, 1988).
Table 2: Results of the Cox hazard analysis for selected predictor variables associated with under-3 mortality, NDHS 2012–2014
Variables
|
Hazard ratio
|
Robust Standard Error
|
Z
|
P-Value
|
95% Confidence Interval
|
Education of mother
|
0.722
|
.034
|
-6.79
|
0.000
|
0.657
|
0.793
|
Family Structure
|
1.511
|
.070
|
8.88
|
0.000
|
1.379
|
1.655
|
Birth by mother
|
3.835
|
0.048
|
106.84
|
0.000
|
3.742
|
3.931
|
Age of mother
|
1.525
|
1.279
|
0.50
|
0.614
|
0.294
|
7.895
|
Relationship with the household head
|
0.452
|
0.086
|
-4.15
|
0.000
|
0.311
|
0.658
|
Interaction work and breastfeeding
|
0.428
|
0.123
|
-2.95
|
0.003
|
0.243
|
0.752
|
Sex of child
|
0.859
|
0.450
|
-0.29
|
0.772
|
0.307
|
2.40
|
Place of residence
|
0.852
|
0.204
|
-0.66
|
0.507
|
0.532
|
1.365
|
Wealth
|
0.390
|
0.327
|
-11.22
|
0.000
|
.331
|
0.460
|
Caste of mother
|
0.652
|
0.022
|
-12.15
|
0.000
|
0.608
|
0.698
|
Religion of mother
|
2.015
|
0.626
|
2.25
|
0.024
|
1.095
|
3.705
|
Cooking fuel
|
1.227
|
0.474
|
0.53
|
0.595
|
0.575
|
2.617
|
Notes: n= 2994, Log pseudo likelihood = -521.39236, prob. χ2=0.005, time at risk =52748
Analysis time: current age of the child in months (months since birth for dead children), SE: adjusted for two clusters in a number of births by mother
Further table 2 also shows that the risk of death of under-3 children from a mother who does not work and does not breastfeed her child is 57% higher. This was supported by the study done in 26 developing countries of sub-Saharan Africa, South Asia and the Middle East using demographic health survey findings from logistic regression analysis shows that the maternal work is associated with a 24.5% higher risk of child mortality as compared to those mothers stay at home (Amir-ud-Din et al., 2021). Furthermore, the risk of death of under-3 children from other than rich family is 61% higher. A study from North India found that Socioeconomically advantaged children had significantly lower death rates (Krishnan et al., 2013) and women and children from poor wealth quintile have a greater disadvantage in all indicators of women and child health (Jungari & Chauhan, 2017). Likewise, State-Level Analysis on the correlation between wealth and health of India found a positive correlation between children's health and economic growth of country from 1990 to 2007 (Coffey et al., 2022).
The risk of death of under-3 children from the Terai caste of Nepal is 35% higher than other castes of Nepal. This result is strongly supported by the study done in north India found that the scheduled tribes and scheduled castes having poor wealth quintile and northern Indian women and children are at a greater disadvantage in all indicators of women and child health as compared to other groups (Jungari & Chauhan, 2017). Furthermore the risk of death of under-3 children who are not from the Hindu religion is 100.2% higher. Specific religious denominations in providing social support and facilitating access to formal health care resources (Cau et al., 2010). Likewise findings from Nigeria suggest that age, place of residence, educational status, wealth index, and religion of fathers and mothers are major determinants of childhood mortality (Yaya et al., 2017).