Infant Mortality and Lower Birth Rate – A Cross-sectional Study with Socioeconomic Factors

Infant Mortality and Lower Birth Rate – A Cross-sectional
Study with Socioeconomic Factors
Abstract
The main goal was to identify risk factors, in particular, low birth weight, to prove the nature of
interventions in order to reduce socio-economic inequalities and factors that can bring the child's
low birth weight. According to the study, all deliveries to residents of Cardiff and Southern Glam
were analyzed. This subset of the total election data represents mothers with simple birth
estimates that have at least 37 weeks’ of pregnancy. The multidimensional relationships between
the explanatory and LBW variables were computed using logistic regression. The description of
the relationship between low birth weight and other variables was examined with the percentage
and Pearson Chi-square stats. The study found that when analyzing several LBW risk factors,
some variable risk factors would intervene to reduce LBW results. This study shows that the
lower increase in maternal dependence and smoking, along with blood pressure were essential
predictors of LBW. Looking at character behavior, as mentioned above, it would be advisable to
take steps to reduce LBW risk. The study showed that over 98% of this group has a socio-
economic impact on the correct birth weight. More than 70 percent of non-smokers related to
their children's healthy weight.
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Introduction
Low birth weight (LBW) is one of the biggest predictors of infant mortality. The global
incidence of LBW is around 17%, although estimates range from 19% in developing countries to
5-7% in developed countries (Demelash, Motbainor, Nigatu, Gashaw, & Melese, 2015). LBW is
usually associated with situations where uterine malnutrition is produced due to changes in
placental blood circulation. There are many known risk factors, the most important of which are
socio-economic factors, medical risks before or during ingestion and the mother's lifestyle.
However, although interventions exist to prevent many of these factors before and during
pregnancy, the incidence of LBW has not decreased (Broman, Nichols, & Kennedy, 2017; Doyle
et al., 2015).
The main objective was to identify the risk factors, particularly of low birth weight, in order to
revise the nature of interventions to reduce socioeconomic inequality, and factors that may risk
for a child with a low birth weight. The data set to be used in the evaluation is derived from the
Cardiff fertility study, which was collected in 1970 to 79 years and recorded in 1994. The study
included all deliveries to residents of Cardiff and southern Glam bodies. This subset of full
election data represents mothers with simple birth estimates that are at least 37 weeks in the tidal
age during childbirth. There are only over 4700 mothers and their birth results, along with
demographic and other data.
Methods
 The study variables brief description of the categorical variables were made in the study of
the relationship between each explanatory variable and low birth weight, especially in the
context of low and significant variable weights at birth. The string variables were converted
in numerical and categorical variables for this purpose.
 The explanatory memorandum was examined and for the categorical variables their
frequency with percentages have presented in Table 1. Mean and standard deviation were
not the appropriate measures here.
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 The LBW frequency was calculated for each category of explanatory variables and the one
to one association was evaluated with Chi-square test. The multidimensional relationships
between the explanatory and LBW variables were calculated by means of logistic
regression.
 Custom model behavior and LBW were calculated using the Multi-variable logistic
adjustment of the explanatory factors and statistically.
 The main interactions were noted in the logistic modeling, and two way and more than two
interactions were not observed. The one way associations were confounded by the chi square
analysis, due to the categorical nature of the variables. The coefficients of the regression
models were not represented as we were not interested particularly in the equation form.
 The results are presented in the form of odds ratio, especially with 95% of confidence
intervals and values of significance level. The analysis made assumptions, including the
manipulation of missing values, in which the state's environment was programmed to bypass
the analysis of the missing value.
 The chi square frequency values with percentage representation and the logistic regression
analyses have presented in Table 2. The odds in favor of both the scenarios for lower birth
weight have been provided with adjusted odd ratios from multiple logistic models.
Results
Descriptive Summary
A summary of the study sample has been provided with a description of the relationship between
low birth weight and socioeconomic status. Overall out of the study subjects of 4781 infants,
2450 (P = 51.24%) males and 2331 (P = 48.76%) females had an LBW outcome prior to 1979.
The modal age group in the sample was 30 - 39 years (N =1802, P = 37.69%).The study sample
was evenly split between subjects with a low socioeconomic behaviour status (N = 2419, P =
50.6%) and high socioeconomic status (N =2362, P = 49.4%). Just above half of the study
mothers were in between 155 and 165 centimeters. Current smokers and ex-smokers were less
than 30% (N = 1349, P = 28.22%) and rest were found to be non-smokers (N = 3432, N =
71.78%). Considering the blood pressure readings indicated that most of the participants had
normal blood pressure (N = 4399, P = 92.01%) and rest of them were diagnosed with
hypertension (N = 382, P = 7.99%). More than half of the proportion of subjects (N = 2458, P =
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51.41%) had BMI scores between 18.5 and 25. Some of them had a height reading above the 165
centimetres (N = 1689, P = 37.02%).
1.706
1.501
0 .5 1 1.5 2
Averge Socioeconomic Status
LBW Normal
Birth Weight Category
Relation of Socioeconomic Status with LBW
Figure 1: Lower Birth Weight Percentage Distribution
Source: Cardiff fertility study, which was collected in 1970 to 79 years and recorded in 1994
Categorical Association
A description of the relationship between low birth weight and other variables was investigated
with the proportion of subjects and Pearson’s Chi-square statistic. The proportion of marital
status was found to behave no statistically significant association with LBW (p>0.05) at 5%
level. Unemployment ratio was found to be lower in those subjects who had normal weight child
(N = 4606, P = 96.68%). The mothers with hypertension ailments (N = 382, P = 7.99%) were
found to have a significant association with the lower birth weight of their child. The smoking
habit of mothers and subjects diagnosed with infant mortality (N = 1349, P = 28.22%) was
strongly associated. As expected, the proportion of subjects with a healthy weight at 20 weeks of
pregnancy had significantly fewer LBW outcomes. There was a decreasing trend observed in
increasing body mass index, but the relationship was not statistically significant. The
predominance of white peoples was noted in the sample and they were found to be giving birth
to healthy babies (N = 4158, N = 91.1%).
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