Essay: ASDRs

A. ASDRs
1. Introduction.
The age-specific death rate (ASDR) is a commonly used mortality measurement that involves determining death rates in terms of age cohorts. An ASDR shows the average number of deaths in an age group per 1,000 people in that specific age group (“Measures of Risk”, 2012).
1.1 Definition.
According to the CDC, the age-specific death rate is defined as the number of deaths within an age group, divided by the total number of people in that age group, and multiplied by 1,000 (“Measures of Risk”).
1.2 CDR.
According to the CDC, the Crude Death Rate (CDR) is the number of total deaths within a population from all causes per 100,000 people. It is calculated by dividing the total number of deaths by the mid-year population, and then multiplying by 100,000. The ASDR is not a crude mortality measurement due to the fact that the deaths are observed relative to the number of people within that age cohort (Poston & Bouvier, 2010). The CDR should not be used to compare mortality across countries or within the same country at the same point in time because the measure is not standardized; not all members are equally at risk of experiencing death since risk varies by a number of factors such as age, sex race and socioeconomic status (Poston & Bouvier, 2010).
2. Compare and Contrast
2.1 U.S.
According to the United Nations, the ASDR trend for the Democratic Republic of the Congo (DRC) generally increased in an exponential pattern as age increased. However, the age cohort of 0-4 years did not follow this trend; the DRC showed a very high mortality rate for ages 0-4, at a value of 24.97. The maximum ASDR was 449.81 in the oldest age cohort of 95+ years. For the United States, the United Nations’ data shows a similar exponential trend, but all of the values are generally lower. The U.S. shows a higher mortality rate than the subsequent age cohorts, but the value is much lower than DRC’s at 1.43. The maximum value achieved by the 95+ age group is 265.91, which is only about 59% of the DRC’s maximum value (United Nations, Department of Economic and Social Affairs, Population Division, 2015).
2.2 CDP (2).
The United Nations shows the data for Mexico is similar to the DRC in its exponential trend from ages 5-95+, with an increased value for the 0-4 age cohort. The value for the 0-4 age cohort for Mexico is only 4.79, which is much lower than the DRC’s value of 24.97. The maximum value for Mexico is only 47% of the DRC’s maximum value as well at 211.50. For Sweden, the mortality rate for the 0-4 age group is extremely low at 0.66, and all of the values are lower in general as well. The maximum value achieved is still fairly high though for the 95+ age group, at a value of 358 and 80% of the DRC’s value (United Nations, Department of Economic and Social Affairs, Population Division, 2015).
2.3 PB/Lecture (2).
According to Poston and Bouvier, the ASDR for Venezuela in 2005follows a similar exponential curve, but with fairly high maximum values. The mortality rate for the 0-4 age group is about 16.8, but the value for 95+ is 325.76. This value is high, but still much lower at about 72% of the DRC’s 95+ mortality rate. Based on the figure by Poston and Bouvier, Afghanistan in 2005 had a massive mortality rate of approximately 50 for the 0-4 age cohort, which is about 208% of the DRC’s. The trend follows an exponential curve as well, but achieves another massive maximum value at 95+of around 600, which is about 134% of the DRC’s value. Afghanistan’s trend, however, contains a dip around ages 10-14, but rises exponentially from there (Poston & Bouvier, 2010)
2. Explanations.
The ASDR values for the United States are much lower than the DRC’s most likely because of the development levels of the countries. The United States has a fairly advanced medical system and can give out many vaccinations, medications and even surgery to help increase life expectancy. However, the DRC is not as technologically advanced and does not have access to certain procedures that would help keep people alive longer. The DRC’s higher ASDR rates could be attributed to the fact that a majority of people in the DRC are below the poverty line. This means that children may not be able to obtain the food, care and shelter they need to survive their first few years where the chance of death is higher. This trend remains true for Sweden, Mexico, Venezuela and Afghanistan as well. Sweden, being highly advanced, has an extremely low child mortality rate as well. Mexico, being less developed than Sweden, has higher ASDR values than Sweden, but still lower than the less developed DRC. Afghanistan is similar to the DRC in development, but other factors such as violence and war could contribute to them having substantially higher ASDR values than the DRC.
4. Gender.
4.1 Males.
The ASDR for males in 2015 in DRC was 13.23 for the 0-4 age group, and increased exponentially to a maximum value of 134.40 for the 95+ age cohort. The ASDR for males in the U.S. in 2015 was much lower for the 0-4 age group at a value of 0.80. The U.S. data achieved a maximum value at the 95+ group at a value of 69.46 (United Nations, Department of Economic and Social Affairs, Population Division, 2015).
4.2 Females.
The ASDR for females in the DRC in 2015 was 11.74 for the 0-4 age cohort and 315.41 for the 95+ age group. The ASDR for females in 2015 for the U.S. was 0.63 for the 0-4 age group and 196.44 for the 95+ age group (United Nations, Department of Economic and Social Affairs, Population Division, 2015).
4.3 Explanations.
The ASDR patterns are similar across countries of different developmental levels. Both the U.S. and the DRC have a higher child mortality rate for males, but a higher old-age mortality rate for females of ages 95+. This could be due to the fact that women generally have a longer life expectancy than men, so more women will reach an age above 95 and will, inevitably, die within that age cohort as well.
B. Standardized CDR
1. Definition.
The standardized CDR (S-CDR), also known as simply the standardized death rate, is the total death rate of a population adjusted for a standard age distribution. It is calculated by multiplying the age-specific death rate by the proportion of the population in that specific age cohort (“Standardised Death Rate (SDR)”).
2. Comparison.
The CDR for the DRC in 2015 is the highest for ages 0-9, and then decreases and remains around the same values until about 85 years old, where it decreases again. The standardized CDR for the DRC in 2015, however, starts off relatively high for the 0-9 age cohort, decreases, but then increases again reaching a peak around 80-89 years old. After this, the values decline drastically again. The values for the standardized CDR are generally higher than the CDR values, totaling to 19.31 while the CDR totals to 10.04 (United Nations, Department of Economic and Social Affairs, Population Division, 2015).
3. Explanation.
The CDR and S-CDR are similar in the fact that they both show higher values for the youngest population groups. However, the CDR does not show an increase in mortality for the oldest age groups; in fact, it shows the lowest value at the oldest age group. This is not representative of the real population, since people 95+ do not have the least risk of death. The S-CDR is more accurate, showing an increase in the mortality for the older age groups. The CDR does not show this increase for older age groups because it is purely based off of number of deaths. There are not that many people of those ages in the population compared to other age groups, so this causes the value to be low. However, in the S-CDR where the proportion of population is taken into account, the values better represent the mortality of the actual population, showing standardized data with an increase in mortality in the youngest and oldest age groups.
C. Life Expectancy
1. Definitions.
According to the World Health Organization, life expectancy at birth (e0) is defined as the average number of years a newborn will live based on the current mortality rates at the time (“2006 Definitions and Metadata”).
2. Better Measure.
Life expectancy at birth is a better overall measurement of mortality than CDR, S-CDR and ASDR because it is not dependent on the age structure of the population. It still takes into account the mortality rates across different ages, but combines all of this data into a single measurement. Additionally, since it is a single number, it can be easily compared across different regions in a nation or across different countries.
3. Compare and Contrast.
3.1 Level (2).
The overall life expectancy at birth for the DRC in 2010-2015 was 58.10 years, while the life expectancies for Mexico and Sweden respectively were 76.48 and 81.93 (United Nations, Department of Economic and Social Affairs, Population Division, 2015).
3.2 Trends and Explanations (2).
Higher overall life expectancies at birth can be positively correlated with high levels of development. The DRC, being the least developed country, has the lowest life expectancy, followed by Mexico and Sweden respectively, increasing in developmental index. Since 1950, all three of these countries’ life expectancies have increased steadily, leading to an explanation of development level as well. In 1950, none of these countries were as technologically or medically advanced as they are currently, showing the effect of development on life expectancy.
4. Gender.
4.1 Levels and Explanations.
The male life expectancies at birth in 2010-2015 for the DRC, Mexico and Sweden respectively were 56.67, 74.04 and 80.10 years. The female life expectancies at birth in 2010-2015 for the DRC, Mexico and Sweden respectively were 59.53, 78.93 and 83.71 years (United Nations, Department of Economic and Social Affairs, Population Division, 2015). Life expectancies for both males and females seem to correlate with higher levels of development as well. Females, across all three countries, generally have higher life expectancies than males. This is most likely due to the fact that men generally take worse care of their bodies and partake in more risky behaviors (such as smoking) than women (Poston & Bouvier, 2010). This disregard for health by males inevitably contributes to a lower life expectancy at birth.
4.2 Trends and Explanations.
Trends for both males and females across all three countries have increased over time since 1950. Female life expectancies in these countries have been higher than males across these years as well. These steady increases for both males and females, keeping a relatively similar difference across the years, is most likely due to the increasing development of the countries as well.
D. IMRs
1. Definitions.
According to the World Health Organization, the infant mortality rate is the probability of a child dying before reaching the age of one, based on the current age-specific mortality rates. The infant mortality rate is interpreted as the probability of dying per 1000 infants under the age of one year (“2006 Definitions and Metadata”). It is calculated by dividing the number of all infant deaths by the total number of live births in that same time period, and then multiplying by 1000 (“Infant Mortality Toolkit”).
2. Important Measure.
The infant mortality rate is important because it is not only an indicator of the survival of newborns living past the age of one, but is used as an indicator of poverty, availability to healthcare, and socioeconomic status levels in a country (“Infant Mortality Toolkit”). By using infant mortality as a crude indicator of these variables, we can make the assumption that countries with high infant mortality rates will generally have high overall mortality rates as well since these factors affect overall mortality too. Additionally, with more infants dying, more births are likely to be present due to the fact that families will still want another child. Mothers also will not experience a period of infertility after their birth due to breastfeeding, leading to more births as well and increasing fertility. Therefore, in order for a demographic transition to lower birth and death rates to occur, the infant mortality rate has to be low. This will eliminate the desire for families to get pregnant again since they will have the healthy child they wanted, and periods of infertility due to breastfeeding will be present as well, lowering the fertility and mortality rates.
3. Compare and Contrast.
3.1 Levels.
The infant mortality rates for the DRC, Mexico and Sweden in 2010-2015 respectively were 73, 19 and 3 per 1000 births. The infant mortality rates for the more developed countries are much lower than the infant mortality rates for the least developed countries. As mentioned, this is most likely a result of the fact that infant mortality often crudely estimates health factors such as access to quality healthcare. Less developed countries don’t have as much access to the healthcare necessary for an infant to survive, leading to higher infant mortality rates (United Nations, Department of Economic and Social Affairs, Population Division, 2015).
3.2 Trends and Explanations.
Since 1950, the infant mortality rates of all three countries have been declining. As the numbers get lower and lower, however, the infant mortality rate seems to decrease at a slower rate for the three countries as well. The declining infant mortality rates over time mirrors the increasing development of the countries, improving upon variables such as access to healthcare, quality of healthcare and poverty rates.
4. Impacts.
4.1 Healthcare System.
The infant mortality rate in the DRC is notably impacted by the healthcare system in terms of access and advancement level of medical technology. As a less developed country, the healthcare system is not technologically advanced, and lacks the option for tests such as magnetic resonance imaging (MRI) (“Child Health in the DRC”). Additionally, people living in most major cities in the DRC have access to hospitals and emergency healthcare, but people living in rural areas do not. Most infant deaths are a product of diseases such as malaria and pneumonia, which could have been prevented with proper healthcare. Only 31% of infants are fully vaccinated, making infants highly susceptible to fatal diseases such as hepatitis and malaria (“Child Health in the DRC”). However, even if access to healthcare is increased, the quality of healthcare still ultimately determines the infant mortality rate. Lisa Berkman’s “The Health Divide” describes how Britain’s increased access to healthcare did not decrease mortality rates due to the fact that the quality of healthcare remained the same (Berkman, 2004). Without improving the quality of the healthcare system and providing the necessary vaccinations and treatment to infants, the DRC’s infant mortality rate will continue to remain extremely high.
4.2 Environmental Factors.
The infant mortality rate in the DRC is also impacted by environmental factors such as poverty. With 63% of all families below the poverty line, children often don’t receive the necessary food, nutrients and shelter necessary for their survival (“Democratic Republic of the Congo”, 2018). Half of all infant deaths are due to lack of vitamin A, iron or zinc, which is a direct result of the inability for impoverished families to provide their infants with the necessary nutrients for survival (“Poverty and Healthcare”). Additionally, “Getting the Most Out of the U.S. Healthcare System” explains how less educated families in the U.S. were less likely to receive higher level treatments due to their inability to ask about certain regimens or procedures (Gengler, 2016). Therefore, since the education level is low in the DRC as well, it is possible that families are not receiving the level of healthcare they could be receiving due to their medical intelligence. The lack of higher level treatments by under-educated families could lead to higher mortality in that context.