Correlation between Low Birth Weight and Infant Mortality Rates, Across Different Populations (Coursework Sample)

Correlation between Low Birth Weight and Infant Mortality Rates across Different Populations <Author name> <Institutional affiliation> <Course number and name> <Instructor name> <Assignment due date> Table of Contents TOC \o "1-3" \h \z \u List of Figures PAGEREF _Toc177469390 \h 3List of Tables PAGEREF _Toc177469391 \h 3Introduction PAGEREF _Toc177469392 \h 4Research Question PAGEREF _Toc177469393 \h 4Aims and Objectives PAGEREF _Toc177469394 \h 5Background Information PAGEREF _Toc177469395 \h 5Hypothesis PAGEREF _Toc177469396 \h 6Variables PAGEREF _Toc177469397 \h 6Methodology PAGEREF _Toc177469398 \h 6Data Processing PAGEREF _Toc177469399 \h 7Results PAGEREF _Toc177469400 \h 9Analysis and Calculations PAGEREF _Toc177469401 \h 9Risk Assessment PAGEREF _Toc177469402 \h 11Conclusion PAGEREF _Toc177469403 \h 12References PAGEREF _Toc177469404 \h 14 List of Figures TOC \h \z \c "Figure" Figure 1: A graph of low birth rates against infant mortality rates PAGEREF _Toc177469354 \h 9 List of Tables TOC \h \z \c "Table" Table 1: Raw Data with all the regions of interest in this study (Tshotetsi, Dzikiti, Hajison, & Feresu, 2019) PAGEREF _Toc177469348 \h 7 Table 2: Averages for the data considering the two critical variables PAGEREF _Toc177469349 \h 8 Table 3: correlation results from the analysis PAGEREF _Toc177469350 \h 8 Table 4: Data for 2000, 2010, and 2020 (Louis, et al., 2016). PAGEREF _Toc177469351 \h 11 Correlation between Low Birth Weight and Infant Mortality Rates across Different Populations Introduction The present study examines the causes of low birth weight amongst the world`s populations in a historically and geographically comparative perspective. The information is relatively dominantly regional and covers South Asia, Eastern and Southern Africa, West and Central Africa, Middle East and North Africa, Latin America and the Caribbean, Pacific East Asia and Pacific, North America and Europe and Central Asia as well. It has been discussed that correlation between the focus variables has been derived and analyzed through correlation analysis. This is a very interesting issue because there are somewhat poor families who would like to help their families with the birth of at least an average child. Most importantly, the interrelated diversity of the results is ensured by the scope of this investigation within the global and regional settings. Research Question Over the break, I worked with Children's Hospital Foundation Thailand as their youngest angel ambassador to raise funds for families that cannot meet the financial costs. Through this experience, I have seen firsthand the critical role that birth weight plays in infant survival, especially in vulnerable populations. My work with premature and neonatal babies exposed me to the importance of understanding the correlation between low birth weight and infant mortality rates. This motivated me to focus my IA research on how low birth weight impacts infant mortality, particularly across different populations. This research paper seeks to correlate low birth weight with infant mortality rate. A hypothesis was formulated to aid in the provision of the correct answer to this question. The subsequent topics and subtopics cover the appropriate obligations to satisfactorily answer the research question. Aims and Objectives The main aim of this paper is to investigate the relationship between infant weights and their mortality rates in different populations/locations around the globe. Background Information It has been historically established that babies who are born small for gestational age have greater mortality risk than their older counterparts, even though appreciation of the repercussions of low birth weight on a child’s well-being is quite recent. This particular chapter looks to trace the transformations in attitudes that have been experienced with regard to the total number of child deaths from various illnesses and the new technological advancements that catapult the care for the most petite of infants. On the other hand helps address the need for further prevention strategies and the general illustration of the effects induced by low birth weight on the rates of illness and mortality. As early as the beginning of the 20th century, there were some assessments of relations between low weight at birth and premature birth, poor growth consequences, etc, one of which is believed to have been performed by Dr. J. Holt Puren. In the 1930s, Yllpö, a Finnish man sought to set 2500 grams as the minimum birth weight, below which a newborn was likely to experience a negative neonatal outcome due to lack of adequate antenatal care.3. This advice was repeatedly supported by Health Organizations. The World Health Assembly declared the first in 1948: "A live born infant shall be classified as immature less as 2500g, however, this requirement does apply in other nations CITATION Nat17 \l 1033 (National Department of Health, 2017). Based on considerations of levels of maturity, a child who is called “preterm” or born before 37 weeks may be termed immature. “The Expert Group on Prematurity understands the importance of consistent nomenclature for global application,” went on the Sick Children’s Foundation’s Expert Group on Prematurity report of 1950, and this shrinks again the limit of 2500 grams. The most effective way of achieving such a primary goal of reducing perinatal and/or neonatal mortality is managing low-birth-weight babies efficiently. Further, they propose that this threshold is extended to a newborn who is born weighing 2,500 grams (5-1/2 lb) or less. Even so, the drawbacks of this criterion have been recognized, in that birth weight data is not always available, and other factors intrinsic to preterm such as gestational age have to be included CITATION Jan23 \l 1033 (Jana, Saha, Reshmi, & Muhammad, 2023). Hypothesis A hypothesis was formulated to answer the research question asked in this study. The null hypothesis stated that Low infant weight leads to high mortality rates in many populations. Variables The two main variables in this project are Low Birth weight (percentage) and the Infant Mortality Rate (per 1000 live births). The introduction covers all the aforementioned regions. Methodology Raw data was used in this research. The data was primarily obtained by observing the number of infants with low weight and their probability of falling into the mortality range rate. Other data was extracted from reliable, relevant, on-live sites from different geographical locations. The essence of collecting data from different regions around the globe was of paramount importance for comparative analysis and the checking of the various correlation coefficients. Data Processing The following tables show the data in tabulation form: Table SEQ Table \* ARABIC 1: Raw Data with all the regions of interest in this study CITATION Tsh19 \l 1033 (Tshotetsi, Dzikiti, Hajison, & Feresu, 2019) Low Birth Weight (%) Infant Mortality rate Per 1000 live birth Regions 2000 2010 2020 2000 2010 2020 South Asia 29.4 27.1 24.9 68.7 49.9 33.2 East and Africa and South Africa 15.7 15 14.4 85.6 57.6 42.9 West Africa and Central Africa 15.6 14.4 13.5 99 75.2 62.2 Middle East and North Africa 12.6 12.6 12.9 34.7 22.7 17.1 Latin America and the Caribbean 9.3 9.5 9.6 27.5 18.6 14.2 East Asia and the Pacific 8.7 8.4 8.7 31.3 17.2 12.1 North America 7.7 8 8.1 7 6.1 5.4 Europe and Central Asia 8.3 7.9 7.6 17.6 10.1 6.9 The table below depicts the averages for this study's two variables of interest. These results were deployed in the analyses for data using the Microsoft Excel Correlation command. The coefficients were obtained and displayed in the data table below. Table SEQ Table \* ARABIC 2: Averages for the data considering the two critical variables Average Low Birth Weights Infant mortality on average 27.13333333 50.6 15.03333333 62.03333 14.5 78.8 12.7 24.83333 9.466666667 20.1 8.6 20.2 7.933333333 6.166667 7.933333333 11.53333 Table SEQ Table \* ARABIC 3: correlation results from the analysis Average Low Birth Weights Infant mortality on average Average Low Birth Weights 1 Infant mortality on average 0.615456103 1 From this table, the correlation coefficients are o.6155. These coefficients typically affect the variables with a positive correlation. In this case, the correlation is strong. The table above shows the correlation results with the coefficients for every variable. The neonatal death rate in the United States has dropped considerably over the last 15 years, but a reduction has not matched this in the proportion of low-weight newborns. Instead, low birth weight baby survival has increased, owing to more specialized, hospital-based therapy via neonatal intensive care, which has resulted in a decline. Since the late 1960s, the percentage of low birth weight newborns and deficient birth weight babies has been relatively stable. Recent results show that reducing low birth weight in babies will be required to minimize further neonatal mortality and the mortality disparities between high- and low-mortality groups. Results The following graphs depict the results yielded from the various datasets of analysis: Figure 1: A graph of low birth rates against infant mortality rates The results depict a robust positive correlation. From the results, a positive gradient indicates that an increas...