Mortality rate

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Colour-coded map of the crude death rates of countries, globally, based on WHO data for 2000-2005, presented per thousand persons in the population, per year. Death rate world map.PNG
Colour-coded map of the crude death rates of countries, globally, based on WHO data for 2000–2005, presented per thousand persons in the population, per year.

Mortality rate, or death rate, [3] :189,69 is a measure of the number of deaths (in general, or due to a specific cause) in a particular population, scaled to the size of that population, per unit of time. Mortality rate is typically expressed in units of deaths per 1,000 individuals per year; thus, a mortality rate of 9.5 (out of 1,000) in a population of 1,000 would mean 9.5 deaths per year in that entire population, or 0.95% out of the total. It is distinct from "morbidity", which is either the prevalence or incidence of a disease, and also from the incidence rate (the number of newly appearing cases of the disease per unit of time). [3] :189[ verification needed ]

Contents

An important specific mortality rate measure is the crude death rate, which looks at mortality from all causes in a given time interval, for a given population. As of 2020, for instance, the CIA estimates that the crude death rate globally will be 7.7 deaths per 1,000 persons in a population. [4] In a generic form, [3] :189 mortality rates can be seen as calculated using , where d represents the deaths from whatever cause of interest is specified that occur within a given time period, p represents the size of the population in which the deaths occur (however this population is defined or limited), and is the conversion factor from the resulting fraction to another unit (e.g., multiplying by to get mortality rate per 1,000 individuals). [3] :189

Crude death rate, globally

The crude death rate is defined as "the mortality rate from all causes of death for a population," calculated as the "[t]otal number of deaths during a given time interval" divided by the "[m]id-interval population", per 1,000 or 100,000; for instance, the population of the U.S. was ca. 290,810,000 in 2003, and in that year, approximately 2,419,900 deaths occurred in total, giving a crude death (mortality) rate of 832 deaths per 100,000. [5] :3-20fAs of 2020, the CIA estimates the U.S. crude death will be 8.3 per 1,000, while it estimates that the global rate will be 7.7 per 1,000. [4] [ contradictory ]

According to the World Health Organization, the ten leading causes of death, globally, in 2016, for both sexes and all ages, were as presented in the table below. [6]

Crude death rate, per 100,000 population

  1. Ischaemic heart disease, 126
  2. Stroke, 77
  3. Chronic obstructive pulmonary disease, 41
  4. Lower respiratory infections, 40
  5. Alzheimer's disease and other dementias, 27
  6. Trachea, bronchus, lung cancers, 23
  7. Diabetes mellitus, 21
  8. Road injury, 19
  9. Diarrhoeal diseases, 19
  10. Tuberculosis, 17

Other specific measures of mortality include: [5]

Measures of mortality, where the number following "per" is the value of described above.
Perinatal mortality rate – the sum of fetal deaths (stillbirths) past 22 (or 28) completed weeks of pregnancy plus the number of deaths among live-born children up to 7 completed days of life, per 1,000 births. [7]
Maternal mortality rate – Number of deaths assigned to pregnancy-related causes during a given time interval, divided by the "[n]umber of live births during the same time interval", per 100,000. [5] :3-20
Infant mortality rate – Number of deaths among children < 1 year of age during a given time interval divided by the [n]umber of live births during the same time interval", per 1,000. [5] :3-20
Child mortality rate (also known as 'Under-five mortality rate') – the number of deaths of children less than 5 years old, per 1,000 live births. [8]
Standardized mortality ratio (SMR) – the ratio of the number of deaths in a given (index) population to the number of deaths expected, a form of indirectly (as opposed to directly) standardized rates, where the categories are usually "defined by age, gender and race or ethnicity". [9] The numerator is calculated as , where " is the number of persons in category of the index population and is the corresponding category-specific event rate in a standard population." [9] Sometimes presented per 100. [9] It has also been described as a proportional comparison to the numbers of deaths that would have been expected if the population had been of a standard composition in terms of age, gender, etc. [10] [ full citation needed ][ verification needed ]
Age-specific mortality rate (ASMR) – the total number of deaths per year, per 1,000 persons of a given age (e.g., age 62 at last birthday). [5] :3-21
Cause-specific death rate – "Number of deaths assigned to a specific cause during a given time interval" divided by the "[m]id-interval population", per 100,000. [5] :3-21
Cumulative death rate – the "incidence proportion of death," that is, "[t]he proportion of a [defined] group that dies over a specified time interval", [3] :64 whether in reference to all deaths over the time inverval, to "to deaths from a specific cause or causes". [3] :64 It has also been described as a measure of the (growing) proportion of a group that die over a specified period (often as estimated by techniques that account for missing data by statistical censoring).[ according to whom? ][ citation needed ]
Case fatality rate (CFR) – the proportion of diagnosed cases of a particular medical condition that lead to death. [11]
Infection fatality rate (IFR) – the proportion of infected cases of a particular medical condition that lead to death. Similar to CFR, but adjusted for asymptomatic and undiagnosed cases. [12]

For any of these, a "sex-specific mortality rate" refers to "a mortality rate among either males or females", where the calculation involves both "numerator and denominator... limited to the one sex". [5] :3-23

Use in epidemiology

In most cases, there are few ways, if at all possible to obtain exact mortality rates, so epidemiologists use estimation to predict correct mortality rates. Mortality rates are usually difficult to predict due to language barriers, health infrastructure related issues, conflict, and other reasons. Maternal mortality has additional challenges, especially as they pertain to stillbirths, abortions, and multiple births. In some countries, during the 1920s, a stillbirth was defined as "a birth of at least twenty weeks' gestation in which the child shows no evidence of life after complete birth". In most countries, however, a stillbirth was defined as "the birth of a fetus, after 28 weeks of pregnancy, in which pulmonary respiration does not occur". [13]

Census data and vital statistics

Ideally, all mortality estimation would be done using vital statistics and census data. Census data will give detailed information about the population at risk of death. The vital statistics provide information about live births and deaths in the population. [14] Often, either census data and vital statistics data is not available. This is especially true in developing countries, countries that are in conflict, areas where natural disasters have caused mass displacement, and other areas where there is a humanitarian crisis [14]

Household surveys

Household surveys or interviews are another way in which mortality rates are often assessed. There are several methods to estimate mortality in different segments of the population. One such example is the sisterhood method, which involves researchers estimating maternal mortality by contacting women in populations of interest and asking whether or not they have a sister, if the sister is of child-bearing age (usually 15) and conducting an interview or written questions about possible deaths among sisters. The sisterhood method, however, does not work in cases where sisters may have died before the sister being interviewed was born. [15]

Orphanhood surveys estimate mortality by questioning children are asked about the mortality of their parents. It has often been criticized as an adult mortality rate that is very biased for several reasons. The adoption effect is one such instance in which orphans often do not realize that they are adopted. Additionally, interviewers may not realize that an adoptive or foster parent is not the child's biological parent. There is also the issue of parents being reported on by multiple children while some adults have no children, thus are not counted in mortality estimates. [14]

Widowhood surveys estimate adult mortality by responding to questions about the deceased husband or wife. One limitation of the widowhood survey surrounds the issues of divorce, where people may be more likely to report that they are widowed in places where there is the great social stigma around being a divorcee. Another limitation is that multiple marriages introduce biased estimates, so individuals are often asked about first marriage. Biases will be significant if the association of death between spouses, such as those in countries with large AIDS epidemics. [14]

Sampling

Sampling refers to the selection of a subset of the population of interest to efficiently gain information about the entire population. Samples should be representative of the population of interest. Cluster sampling is an approach to non-probability sampling; this is an approach in which each member of the population is assigned to a group (cluster), and then clusters are randomly selected, and all members of selected clusters are included in the sample. Often combined with stratification techniques (in which case it is called multistage sampling), cluster sampling is the approach most often used by epidemiologists. In areas of forced migration, there is more significant sampling error. Thus cluster sampling is not the ideal choice. [16]

Mortality statistics

Causes of death vary greatly between developed and less developed countries;[ citation needed ] see also list of causes of death by rate for worldwide statistics.

World historical and predicted crude death rates (1950–2050)
UN, medium variant, 2012 rev. [17]
YearsCDRYearsCDR
1950–195519.12000–20058.4
1955–196017.32005–20108.1
1960–196516.22010–20158.1
1965–197012.92015–20208.1
1970–197511.62020–20258.1
1975–198010.62025–20308.3
1980–198510.02030–20358.6
1985–19909.42035–20409.0
1990–19959.12040–20459.4
1995–20008.82045–20509.7

The ten countries with the highest crude death rate, according to the 2016 CIA World Factbook estimates, are: [18]

RankCountryDeath rate
(annual deaths/1,000 persons)
1Flag of Lesotho.svg  Lesotho 14.9
2Flag of Bulgaria.svg  Bulgaria 14.5
3Flag of Lithuania.svg  Lithuania 14.5
4Flag of Ukraine.svg  Ukraine 14.4
5Flag of Latvia.svg  Latvia 14.4
6Flag of Guinea-Bissau.svg  Guinea-Bissau 14.1
7Flag of Chad.svg  Chad 14.0
8Flag of Afghanistan.svg  Afghanistan 13.7
9Flag of Serbia.svg  Serbia 13.6
10Flag of Russia.svg  Russia 13.6
Scatter plot of the natural logarithm (ln) of the crude death rate against the natural log of per capita real GDP. The slope of the trend line is the elasticity of the crude death rate with respect to per capita real income.
It indicates that as of the date of the basis data set,
an increase in per capita real income tends to be associated with a decrease in the crude death rate.
Source: World Development Indicators. Income death in logs graph.JPG
Scatter plot of the natural logarithm (ln) of the crude death rate against the natural log of per capita real GDP. The slope of the trend line is the elasticity of the crude death rate with respect to per capita real income. It indicates that as of the date of the basis data set, an increase in per capita real income tends to be associated with a decrease in the crude death rate. Source: World Development Indicators.

According to Jean Ziegler (the United Nations Special Rapporteur on the Right to Food for 2000 to March 2008), mortality due to malnutrition accounted for 58% of the total mortality in 2006: "In the world, approximately 62 millions people, all causes of death combined, die each year. In 2006, more than 36 million died of hunger or diseases due to deficiencies in micronutrients". [19]

Of the roughly 150,000 people who die each day across the globe, about two thirds—100,000 per day—die of age-related causes. [20] In industrialized nations, the proportion is much higher, reaching 90%. [20]

Economics

Scholars have stated that there is a significant relationship between a low standard of living that results from low income and increased mortality rates. A low standard of living is more likely to create situations where malnutrition is more common, which can in turn cause the impacted people to become more susceptible to disease and an increased likelihood of dying from these diseases. People who have a lower standard of living are also more likely to face issues such as a lack of hygiene and sanitation, the increase of exposure to and the spread of disease, and a lack of access to proper medical care and facilities. Poor health can in turn contribute to low and reduced incomes, which can create a loop known as the health-poverty trap. [21] Indian economist and philosopher Amartya Sen has stated that mortality rates can serve as an indicator of economic success and failure. [22] [23] :27, 32

Historically, mortality rates have been adversely affected by short term price increases. Studies have shown that mortality rates increase at a rate concurrent with increases in food prices. These effects have a greater impact on vulnerable, lower-income populations than they do on populations with a higher standard of living. [23] :35–36, 70

In more recent times, higher mortality rates have been less tied to socio-economic levels within a given society, but have differed more between low and high-income countries. It is now found that national income, which is directly tied to standard of living within a country is the largest factor in mortality rates being higher in low-income countries. [24]

These rates are especially pronounced for children under the age of 5-years old, particularly in lower-income, developing countries. These children have a much greater chance of dying of diseases that have become very preventable in higher-income parts of the world. The instances of these children dying of things like malaria, respiratory infections, diarrhea, perinatal conditions, or measles are much more pronounced in developing nations. Data shows that after the age of 5 these preventable causes level out between high and low-income countries. The only cause of death that affects people aged 30–59 at a significantly higher rate in low income. [25]

See also

Related Research Articles

Death rates in the 20th century is the ratio of deaths compared to the population around the world throughout the 20th century. When giving these ratios, they are most commonly expressed by number of deaths per 1,000 people per year. Many factors contribute to death rates such as cause of death, increasing the death rate, an aging population, which could increase and decrease the death rates by birth rates, and improvements in public health, decreasing the death rate.

Infant mortality

Infant mortality is the death of young children under the age of 1. This death toll is measured by the infant mortality rate (IMR), which is the number of deaths of children under one year of age per 1000 live births. The under-five mortality rate, which is referred to as the child mortality rate, is also an important statistic, considering the infant mortality rate focuses only on children under one year of age.

Maternal death the death of a woman while pregnant or within 42 days of termination of pregnancy

Maternal death or maternal mortality is defined by the World Health Organization (WHO) as "the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes."

Case fatality rate Proportion of patients who die of a particular medical condition out of all who have this condition within a given time frame

In epidemiology, a case fatality rate (CFR) — sometimes called case fatality risk — is the proportion of deaths from a certain disease compared to the total number of people diagnosed with the disease for a certain period of time. A CFR is conventionally expressed as a percentage and represents a measure of disease severity. CFRs are most often used for diseases with discrete, limited time courses, such as outbreaks of acute infections. A CFR can only be considered final when all the cases have been resolved. The preliminary CFR, for example, during the course of an outbreak with a high daily increase and long resolution time would be substantially lower than the final CFR.

Disease burden impact of a health problem as measured by financial cost, mortality, morbidity, or other indicators

Disease burden is the impact of a health problem as measured by financial cost, mortality, morbidity, or other indicators. It is often quantified in terms of quality-adjusted life years (QALYs) or disability-adjusted life years (DALYs). Both of these metrics quantify the number of years lost due to disability (YLDs), sometimes also known as years lost due to disease or years lived with disability/disease. One DALY can be thought of as one year of healthy life lost, and the overall disease burden can be thought of as a measure of the gap between current health status and the ideal health status. According to an article published in The Lancet in June 2015, low back pain and major depressive disorder were among the top ten causes of YLDs and were the cause of more health loss than diabetes, chronic obstructive pulmonary disease, and asthma combined. The study based on data from 188 countries, considered to be the largest and most detailed analysis to quantify levels, patterns, and trends in ill health and disability, concluded that "the proportion of disability-adjusted life years due to YLDs increased globally from 21.1% in 1990 to 31.2% in 2013." The environmental burden of disease is defined as the number of DALYs that can be attributed to environmental factors. Similarly, The work-related burden of disease is defined as the number of deaths and DALYs that can be attributed to occupational risk factors to human health. These measures allow for comparison of disease burdens, and have also been used to forecast the possible impacts of health interventions. By 2014 DALYs per head were "40% higher in low-income and middle-income regions."

Maternal health is the health of women during pregnancy, childbirth, and the postpartum period. It encompasses the health care dimensions of family planning, preconception, prenatal, and postnatal care in order to ensure a positive and fulfilling experience, in most cases, and reduce maternal morbidity and mortality, in other cases.

Tropical diseases, especially malaria and tuberculosis, have long been a public health problem in Kenya. In recent years, infection with the human immunodeficiency virus (HIV), which causes acquired immune deficiency syndrome (AIDS), also has become a severe problem. Estimates of the incidence of infection differ widely.

Health in Tajikistan

The Tajikistan health system is influenced by the former Soviet legacy. It is ranked as the poorest country within the WHO European region, including the lowest total health expenditure per capita. Tajikistan is ranked 129th as Human Development Index of 188 countries, with an Index of 0.627 in 2016. In 2016, the SDG Index value was 56. In Tajikistan health indicators such as infant and maternal mortality rates are among the highest of the former Soviet republics. In the post-Soviet era, life expectancy has decreased because of poor nutrition, polluted water supplies, and increased incidence of cholera, malaria, tuberculosis, and typhoid. Because the health care system has deteriorated badly and receives insufficient funding and because sanitation and water supply systems are in declining condition, Tajikistan has a high risk of epidemic disease.

Health in Angola is rated among the worst in the world. Only a fraction of the population receives even rudimentary medical attention.

Health in Botswana

The government of Botswana stresses primary healthcare with emphasis on disease prevention and healthy living. In 2013, about 25% of the population were infected with HIV/AIDS.

The Ministry of Public Health in Cameroon is responsible for the maintenance of all public health services. Many missionaries maintain health and leprosy centers. The government is pursuing a vigorous policy of public health improvement, with considerable success in reducing sleeping sickness, leprosy, and other endemic diseases.

The public medical services of Ivory Coast are more important than the small number of private physicians and clinics. As of 2004, there were an estimated 9 physicians, 31 nurses, and 15 midwives per 100,000 people. About 77 percent of the population had access to safe water in 2000. Total health care expenditures were estimated at 3.7 percent of GDP.

Most of the health services of Gabon are public, but there are some private institutions, of which the best known is the hospital established in 1913 in Lambaréné by Albert Schweitzer. The hospital is now partially subsidized by the Gabonese government.

The 2010 maternal mortality rate per 100,000 births for Tanzania was 790. This is compared with 449 in 2008 and 610.2 in 1990. The UN Child Mortality Report 2011 reports a decrease in under-five mortality from 155 per 1,000 live births in 1990 to 76 per 1,000 live births in 2010, and in neonatal mortality from 40 per 1,000 live births to 26 per 1,000 live births. The aim of the report The State of the World's Midwifery is to highlight ways in which the Millennium Development Goals can be achieved, particularly Goal 4 – Reduce child mortality and Goal 5 – improve maternal health. In Tanzania there are only two midwives per 1,000 live births; and the lifetime risk of death during delivery for women is one in 23.

Malawi ranks 170th out of 174 in the World Health Organization lifespan tables; 88% of the population live on less than £2.40 per day; and 50% are below the poverty line.

The African country of Zambia faces a number of ongoing health challenges.

Serbia ranked 65th in the world in life expectancy in 2018 with 73.3 years for men and 78.5 years for women. As of 2018, it had a low infant mortality rate. As of 2017, it had 2.96 practicing physicians per 1,000 people.

In reproductive health, obstetric transition is a concept around the secular trend of countries gradually shifting from a pattern of high maternal mortality to low maternal mortality, from direct obstetric causes of maternal mortality to indirect causes, aging of maternal population, and moving from the natural history of pregnancy and childbirth to institutionalization of maternity care, medicalization and over medicalization. This concept was originally proposed in the Latin American Association of Reproductive Health Researchers in analogy of the epidemiological, demographic and nutritional transitions.

The Million Death Study (MDS) is an ongoing human premature mortality study conducted in India. It began in 1998 and is still ongoing. Among a sample size of 14 million Indians, approximately 1 million deaths are assigned medical causes through the Verbal Autopsy method to determine disease patterns and direct public health policy. The principal investigator of the study is Dr. Prabhat Jha, director of the Centre for Global Health Research and professor of epidemiology at the Dalla Lana School of Public Health, University of Toronto, Canada.

References

  1. [ dead link ]
  2. "World Population Prospects, the 2010 Revision". September 26, 2011. Archived from the original on 2011-09-26.
  3. 1 2 3 4 5 6 Porta, M, ed. (2014). "Mortality Rate, Morbidity rate; Death rate; Cumulative death rate; Case fatality rate". A Dictionary of Epidemiology (5th ed.). Oxford: Oxford University Press. pp. 189, 69, 64, 36. ISBN   978-0-19-939005-2.
  4. 1 2 CIA Staff (2020). "People and Society". CIA World Factbook. Retrieved January 31, 2020.
  5. 1 2 3 4 5 6 7 For tabulated definitions for Crude death rate, Cause-specific death rate, Proportionate mortality, Death-to-case ratio, Neonatal mortality rate, Postneonatal mortality rate, Infant mortality rate, and Maternal mortality rate (with example calculations for several), see Dicker, Richard C.; Coronado, Fátima; Koo, Denise; Parrish II, Roy Gibson (2012). "Lesson Three: Measures of Risk, §Mortality Frequency Measures" (PDF). Principles of Epidemiology in Public Health Practice: An Introduction to Applied Epidemiology and Biostatistics. Atlanta, GA: U.S. Department of HHS, Centers for Disease Control and Prevention (CDC). pp. 3–20 to 3–38. Retrieved January 31, 2020.CS1 maint: uses authors parameter (link)
  6. WHO Staff (2018). "Global Health Observatory (GHO) data: Top 10 causes of death". Geneva, CH: World Health Organization. Retrieved January 31, 2020.
  7. "Perinatal Mortality". 2008. Retrieved 2020-03-30.
  8. "Global Health Observatory (GHO) data – Under-five mortality" . Retrieved 2020-03-30.
  9. 1 2 3 Gail, Mitchell & Benichou, Jacques (2000). "Standardized mortality ratio (SMR)" (PDF). Encyclopedia of Epidemiologic Methods. Wiley Reference Series in Biostatistics. New York, NY: John Wiley & Sons. p. 884. ISBN   9780471866411 . Retrieved January 31, 2020.CS1 maint: uses authors parameter (link)
  10. Everitt, B.S. The Cambridge Dictionary of Statistics. Cambridge, UK: Cambridge University Press. ISBN   052181099X.[ full citation needed ]
  11. "Principles of Epidemiology - Lesson 3: Measures of Risk Section 3: Mortality Frequency Measures". Centers for disease control and prevention. U.S. Department of Health & Human Services. Retrieved 25 March 2020.
  12. "Infection fatality rate". DocCheck Medical Services GmbH. Retrieved 25 March 2020.
  13. Loudon, Irvine (1992). Death in Childbirth: An International Study of Maternal Care and Maternal Mortality 1800–1950 – Oxford Scholarship. Oxford University Press. doi:10.1093/acprof:oso/9780198229971.001.0001. ISBN   9780191678950.
  14. 1 2 3 4 Timæus, Ian M. (1991). "Measurement of Adult Mortality in Less Developed Countries: A Comparative Review". Population Index. 57 (4): 552–568. doi:10.2307/3644262. JSTOR   3644262.
  15. Graham, W.; Brass, W.; Snow, R. W. (May 1989). "Estimating maternal mortality: the sisterhood method". Studies in Family Planning. 20 (3): 125–135. doi:10.2307/1966567. ISSN   0039-3665. JSTOR   1966567. PMID   2734809.
  16. Migration, National Research Council (US) Roundtable on the Demography of Forced (2002). Estimating Mortality Rates. National Academies Press (US).
  17. "UNdata - record view - Crude death rate (deaths per 1,000 population)". data.un.org.
  18. "The World Factbook — Central Intelligence Agency – Country Comparison: Death Rate". www.cia.gov.
  19. Jean Ziegler, L'Empire de la honte, Fayard, 2007 ISBN   978-2-253-12115-2, p.130.
  20. 1 2 Aubrey D.N.J, de Grey (2007). "Life Span Extension Research and Public Debate: Societal Considerations" (PDF). Studies in Ethics, Law, and Technology. 1 (1, Article 5). CiteSeerX   10.1.1.395.745 . doi:10.2202/1941-6008.1011 . Retrieved August 7, 2011.
  21. "Health, Income, & Poverty: Where We Are & What Could Help". October 4, 2018. doi:10.1377/hpb20180817.901935.Cite journal requires |journal= (help)
  22. Sen, Amartya (1998). "Mortality as an Indicator of Economic Success and Failure". The Economic Journal. 108 (446): 1–25. doi:10.1111/1468-0297.00270. ISSN   0013-0133. JSTOR   2565734.
  23. 1 2 Bengtsson, Tommy; Campbell, Cameron; Lee, James Z. (2004). Life under pressure: mortality and living standards in Europe and Asia, 1700–1900. Cambridge, MA: MIT. ISBN   978-0262268097. OCLC   57141654.
  24. Preston, Samuel H. (2007-06-01). "The changing relation between mortality and level of economic development". International Journal of Epidemiology. 36 (3): 484–490. doi:10.1093/ije/dym075. ISSN   0300-5771. PMC   2572360 . PMID   17550952.
  25. Bengtsson, Tommy, et al. Life under Pressure: Mortality and Living Standards in Europe and Asia, 1700–1900, MIT Press, 2009. ProQuest Ebook Central,

Sources