Infant Deaths Rates in Predominantly African Americans Research Paper

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Updated: Mar 13th, 2024

Purpose of the article

African American communities, like other minority communities, grapple with severe social issues that hamper their physical, social, psychological, and economic development. Issues such as discrimination and inequality continue to plague this community. As a result, the access of African Americans to quality education, well-paying jobs and quality health care facilities is normally lower compared to the dominant white community and other minority communities. Additionally, these social disadvantages create more social ills for African American communities, for instance, high crime rates. Several studies such as those of Eberstein, Nam and Hummer (1990) and Frisbie, Biegler, Turk, Forbes and Pullum (1997) show that African Americans record higher rates of infant mortality than the dominant white community due to the social ills that grapple them. The problem that will be addressed in this particular study is the potential impact of education level, income level, crime rate, access to adequate prenatal care and family dysfunctionality on infant mortality rates among the African American community. The study aims to answer the following research questions:

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  • Is there a relationship between maternal education levels and infant mortality rates among the black community?
  • Is there a relationship between household income levels and infant mortality rates among the black community?
  • What is the relationship, if any, between crime rates and infant mortality rates?
  • What is the relationship between access to prenatal care and infant mortality rates?
  • Is there a relationship between family dysfunctionality and infant mortality rates?

It is hoped that this study will make some contributions. First, the study will increase the knowledge of social factors on infant mortality rates. Second, the findings of the study will provide the basis upon which future studies can be carried out particularly on other minority groups. Third, the findings of the study will help the government and policymakers to come up with policies that will help to reduce the rates of infant mortality among African Americans, for instance, by tackling the social ills that plague the community.

Theoretical perspective

This study will be guided by the classic demographic transition theory which was introduced by Thomson in 1930 and later by Nostestein in 1953. The theory postulates that fall infertility is a consequence of the variation in the quality of life as a result of urbanization and industrialization. The theorists argue that urbanization and industrialization have improved the quality of life, for instance, through improved medical and health care facilities and services. As a result, the number of surviving children has increased forcing many married couples to reduce the rate of conception. Additionally, the cost of life in industrialized and urban centers is expensive and therefore it becomes difficult to bring up a large number of children (Mason, 1997, p.444). The classic demographic transition theory has been used by several demographers in their studies including Cleland (1985), Cleland and Wilson (1987), and McDonald (1993) among many others. This theory has several weaknesses.

First, it is contradictory when applied on a decadal scale. The theory does not explain why the relationship between the level of industrialization and the first experience of fertility decline is weak in Europe and most of the developing nations. Secondly, in some developing countries such as some Asian and Latin American countries, the level of fertility is declining although these countries are predominantly agrarian and non-industrialized. Despite these weaknesses, the classic demographic transition theory can be applied in the study of infant mortality in minority communities such as African American communities. African American communities are relatively disadvantaged compared to Caucasian communities. Most African Americans grapple with unequal opportunities such as poor access to high-quality education and low paying jobs. As a result, their socio economic status is relatively low and they live in poor neighborhoods. The low educational and income levels as well as residing in congested and polluted neighborhoods are likely to increase the infant mortality rates in African American communities.

Empirical antecedents

Many studies have been carried out and much literature written about factors that influence infant mortality rates. Eberstein, Nam and Hummer (1990) carried out a study to determine the main and interaction effects of infant mortality as a cause of death. The researchers used live birth cohorts born between 1980 and 1982 in Florida State. The data for this research was obtained from the National Center for Health Statistics (1986). The dependent variable was the cause of infant death which was categorized into five groups namely: infections, perinatal conditions, delivery complications, congenital malformations and sudden infant death syndrome. The independent variables on the other hand consisted of race/ethnicity, marital status and prior fetal deaths.

Other independent variables measured by the study include: education, birth order, birth weight, month of initiation of prenatal care and maternal age (Eberstein, Nam and Hummer, 1990, p.415). Data analysis was done through multinomial logic regression to measure the gross and net impacts of the independent variables on the dependent variables. The results of this study are indicated in table 1. Eberstein, Nam and Hummer (1990) found out that the Hispanics recorded higher levels of infant mortality from perinatal conditions than other ethnic communities. On the other hand, the black communities recorded a higher infant mortality rate from SIDS than other ethnic communities. Infant mortality rate also decreased as the age of the mother increased. Low education levels were positively correlated with higher deaths from infections and perinatal mortality. The study by Eberstein, Nam and Hummer (1990) is important for this study because it explains how factors such as education levels and socio economic status affect infant mortality rates.

Closely linked to the Eberstein, Nam and Hummer’s study is the study carried out by Frisbie, Biegler, Turk, Forbes and Pullum (1997). The study is concerned with the racial and ethnic disparities in intrauterine growth retardation and other compromised birth results. The data used was obtained from the National Maternal and Infant Health Survey (NMIHS). These data were collected through questionnaire from a sample of mothers who had delivered their babies in 1988. Stratification was then done to classify the sampling elements according to their age, marital status and race among other categories. Multivariate analysis was used as the preferred data analysis technique. Frisbie, Biegler, Turk, Forbes and Pullum found out that the minority communities (Mexican Americans and African Americans) were more likely to record low socio economic status as indicated by low education and income levels. The highest occurrence of intrauterine growth retardation was in mothers with low educational levels, first-time mothers, mothers who relied on government aid and mothers who lacked access to frequent high-quality prenatal care. In sum, the highest rate of intrauterine growth retardation was recorded among African American mothers. The study by Frisbie, Biegler, Turk, Forbes and Pullum (1997) is important for this study because it shows how African American maternal and infant health is affected by many underlying social factors such as education and socio economic status.

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Frisbie, Forbes and Hummer (1998) also carried out a study to determine the pregnancy outcomes among the Hispanic population. The data used consisted of the 1989, 1990 and 1991 Linked Birth/Infant Death Data Set from the National Center for Health Statistics (NCHS). The data totaled more than 9 million births and more than 58,500 infant deaths. The logic regression models were used to analyze the collected data. The study by Frisbie, Forbes and Hummer (1998) found out that of the Hispanic subgroups, Cuban mothers record a higher rate of high school completion, a lower percentage of births given by mothers who are under eighteen years of age, and a higher rate of mothers who receive adequate prenatal care. The Puerto Ricans on the other hand record the highest percentage of smokers while the Mexican American mothers record the lowest level of education among the Hispanic population (see table 2). The results also show that the highest rates of premature births, low birth weight and infant mortality are recorded by Puerto Ricans. Mexican Americans follow Puerto Ricans closely in recording the highest rate of premature births and infant mortality. The usefulness of this article to the study is that it shows how social and environmental factors affect the health of the mother and the unborn child and how their health in turn determine the survival chances of the newborn baby.

Other articles useful to the study include Mason’s “Explaining Fertility Transitions” and Omran’s “The epidemiologic transition: A theory of the epidemiology of population change.” The article by Mason (1997) is a discussion of the evolutions made in fertility over the decades. It explains how fertility has fallen over the years from an average of more than four children per woman to an average of two or less children per woman. The article discusses the theories of fertility transitions namely: the classic demographic transition theory, the theory of wealth flows, the neoclassical microeconomic theory, and the ideational theory. This article is useful to the study because it provides the theoretical framework on which to base the study. The study has been based on the classic demographic transition theory which best explains the rates of infant mortality among the disadvantaged African American community. Closely linked to this article is the article by Omran. Omran (2005) explains the theory of epidemiologic transition which concentrates on the varying trends of health and sickness and on the relationships between these trends and their demographic effects. Omran’s article is usefulness to the study because it explains the factors that affect the demographic variables namely: fertility, mortality and migration. As a result, it provides a deeper insight and a better understanding of the correlation between infant mortality and social and environmental factors.

Hypotheses

This study will test the hypothesis that:

  • There is no relationship between the educational level of African American mothers and infant mortality rates.
  • There is no relationship between the income level of African American households and infant mortality rates.
  • Crime rates in African American communities do not have a significant effect on infant mortality rates in these communities.
  • Access to adequate prenatal care does not have a significant effect on infant mortality rates in African American communities.
  • There is no relationship between the state of families in African American communities and infant mortality rates.

Data and method

Research design, data type and data collection technique

Survey will be used as the research design of choice for this study. Sampling will be done to select the samples to be included. The target population will consist of mothers from African American descent who are more likely to record low educational levels, low household and personal incomes, high crime rates in their neighborhoods, low access to adequate prenatal care and dysfunctional state of their families. Samples will be selected through simple random sampling technique in which the sapling elements will be selected without bias from the target population. This sampling technique will enable the researchers to select a sample that is representative of the target population. That is, it will ensure that every member of the target population has an equal and independent opportunity of being included in the sample. The data to be collected is primary data which will be collected through the interview technique. A semi-structured questionnaire will be used as the data collection instrument. The interviewers will use and follow the questionnaire to collect data from the recipients. The use of the semi-structured questionnaire as well as the presence of the interviewers during the data collection process will enable the researchers to obtain supplementary information and clarify vague questions or responses.

Data analysis

Inferential analysis will be used to analyze the collected data. Inferential analysis is used when the researcher wants to determine the present or absence of a correlation between the dependent and independent variables. It is also used to make conclusions about the population from which the samples have been drawn. This particular study will make use of the inferential analysis technique because the main aim of the study is to determine the existence (or lack thereof) of a relationship between the dependent and independent variables. The study is also interested in determining whether the population from which the samples were selected is homogeneous or heterogeneous. Correlation analysis will be used as the preferred inferential analysis technique to test the hypotheses of this study using the data collected for each sample country. Although there are several correlation analysis methods, the Pearson’s correlation coefficient (r) will be used as the preferred analysis method.

The Pearson’s correlation coefficient tests the existence (or absence), strength and magnitude of the correlation between two sets of variables so long as the data are interval: that is, the data are not arranged in either ascending or descending order. If r is +1.0 it means that the correlation between the variables is strongly positive. On the other hand, if r is -1.0 it means that the correlation between the variables is strongly negative. If there is no correlation between the variables, the r will be 0.0 (Coolican, 1994, p.43). The Pearson’s correlation coefficient therefore ranges between 0 and 1 and can take either a positive or a negative sign depending on the direction of the correlation between the variables. The estimated statistical equation is: Y = C + D – E – I – P where Y is infant mortality, C is crime level, D is family dysfunctionality, E is education level, I is income level and P is access to adequate prenatal care.

The use of a sample (particularly a small sample) to test hypotheses pertaining to a population is almost always accompanied by the possibility of a sampling error occurring. There is also the possibility that the correlation in the population from which the sample is drawn is zero. Hence, a strong correlation found in a sample might be due to chance. To test whether or not there is a correlation in the population from which the samples are drawn, the student t-test will be used. In this study, the level of significance to be used will be 0.05 (meaning 95% confidence level). The level of significance shows the probability that the magnitude of the disparity between the dependent and independent variables might have been as a result of a sampling error or by chance instead of by treatment. The 0.05 level of significance implies that the observed outcome can only happen by chance 5 times in 100 cases but 95 percent of the cases are as a result of the treatment. The decision rule is that: if the computed t falls within the range of the values of t in the student t table, the null hypothesis will not be rejected. This means that there is no correlation in the population from which the samples were drawn. On the other hand, if the computed t falls beyond the values of t in the student t table, the null hypothesis will be rejected and the alternative hypothesis will be accepted. This implies that there is a correlation in the population from which the samples were drawn.

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Findings

Effect of educational levels on infant mortality

The estimation is that the samples with less than 9 years of schooling will record the highest rate of infant mortality, followed by samples with 9-12 years of schooling. Samples with more than 12 years of schooling will record the lowest infant mortality rates. The correlation between income and infant mortality should therefore be negative.

Effect of income levels on infant mortality

The estimation is that the samples with low household income will record the highest infant mortality rates while samples with high household income will record the lowest infant mortality rates. The correlation between income and infant mortality should therefore be negative.

Effect of crime level on infant mortality

The estimation is that samples living in high-crime neighborhoods will record the highest rate of infant mortality while samples living in low-crime neighborhoods will record the lowest infant mortality rates. The correlation between crime and infant mortality should therefore be positive.

Effect of access to adequate prenatal care on infant mortality

The estimation is that samples that have frequent and adequate access to prenatal care will record the lowest rates of infant mortality. On the other hand, samples that lack access to frequent and adequate prenatal care will record the highest rates of infant mortality. The correlation between access to adequate prenatal care and infant mortality is negative.

Effect of family dysfunctionality on infant mortality

It is estimated that single mothers or mothers living in conflict-ridden households will record the highest infant mortality rates. On the other hand, samples from intact and conflict-free households will record the lowest rates of infant mortality. The correlation between family dysfunctionality and infant mortality should therefore be positive.

Table 1: Cross-tabulation of sample by categorical independent variables and descriptive statistics for continuous independent variables. Source: Eberstein, Nam and Hummer (1990).

Cause specific infant deaths
VariableInfectPerin.Del compsMalform.SIDSSurvival
Marital status
Unmarried2463964422663069,218
Race/ethnicity
Black2304854563042929,804
Cuban1939312721,487
Other Hispanic18495941252,285
Prior deaths 1+5118919712881
Total sample5079641164965665
Descriptive statistics
VariableMeanSDVariableMeanSD
Education12.02.012Log birth weight8.027.002
Maternal age24.63.026Birth order1.944.006
Prenatal3.314.01

Table 2: National Center for Health Statistics Linked Birth/Infant Death for 1989, 1990 and 1991. Source: Frisbie, Forbes and Hummer (1998).

AngloMexican AmericanPuerto RicanCubanCentral/South AmericanOther Hispanic
Place of birth
U.S.95.8238.3056.2121.204.2881.60
Other4.1861.7043.7978.8095.7218.40
Age
Under 183.046.999.222.583.168.15
18 or older96.9693.0190.7897.4296.8491.85
Marital status
Unwed16.9333.2755.7217.3640.3836.94
Married83.0766.7344.2882.6456.6263.06
Residence
Northeast19.991.4274.3015.7936.5613.79
Midwest28.237.279.433.372.448.08
South31.5830.2311.4371.0622.6720.40
West20.2061.084.849.7838.3457.73
Plurality
Single97.6398.2297.9097.8798.1698.13
Plural2.371.782.102.131.841.87
Previous loss
Yes25.1715.0427.3127.1020.6121.06
No74.8384.9672.6972.9079.3978.94
Attendant
Non-physician3.787.368.734.1110.045.29
Physician96.2292.6491.2795.8989.9694.71
Prenatal care
Inadequate10.9234.0227.729.9329.3624.88
Intermediate15.0918.9118.4921.8021.7417.01
Adequate48.1229.9132.9340.6431.2035.52
Adequate plus25.8817.1720.8627.6317.7122.59
Education
<9 years2.2533.128.703.6725.427.44
9-11 years12.8728.3133.9913.2718.6027.35
12+ years84.8838.5657.3183.0655.9865.20
Parity
First birth42.4136.6939.9442.5439.1740.42
Low46.3439.3538.5649.6044.8740.65
High11.2523.9621.507.8515.9618.93
Smoking
Nonsmoker80.0595.3987.2593.9997.3189.73
Low (<9/day)4.622.616.462.691.715.15
High (>9/day)15.332.006.293.320.985.12
Sex
Male51.3551.0050.8751.5451.1250.85
Female48.6549.0049.1348.4648.8849.15
Weight gain
Low (<15 lb.)5.849.818.695.177.687.70
Med. (15-40 lb.)77.8176.8375.8277.1479.9077.05
High (>40 lb.)16.3513.3615.4917.6812.4215.25

References

Eberstein, I.W., Nam, C., & Hummer, R.A. (1990). Infant mortality by cause of death: Main and interaction effects. Demography, 27.3, 413-430.

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Frisbie, W.P., Biegler, M., Turk, P., Forbes, D., & Pullum, S.G. (1997). Racial and ethnic differences in determinants of intrauterine growth retardation and other compromised birth outcomes. American Journal of Public Health, 87.12, 1977-1983.

Frisbie, W.P., Forbes, D., & Hummer, R.A. (1998). Hispanic pregnancy outcomes: Additional evidence. Social Science Quarterly, 79.1, 149-169.

Mason, K.O. (1997). Explaining fertility transitions. Demography, 34.4, 443-454.

Omran, A.R. (2005). The epidemiologic transition: A theory of the epidemiology of population change. The Milbank Quarterly, 83.4, 731-757.

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