Morbidity And Mortality
Morbidity And Mortality
HISTORICAL TRAJECTORY OF MORBIDITY AND MORTALITY
KEY DETERMINANTS OF MORBIDITY AND MORTALITY
Morbidity, meaning illness or frailty, is currently defined as a diagnosis with a specific disease listed in the International Classification of Diseases, Tenth Revision (ICD-10). The language of ICD-10 was adopted by the World Health Organization (WHO) so that disease and mortality data could be compared globally. Morbidity rates are measured as the number of cases of a disease divided by the midyear population times 100,000. Morbidity reporting of specific contagious diseases is an important aspect of public health. The WHO and the U.S. Centers for Disease Control and Prevention (CDC) require the reporting of infectious diseases (e.g., AIDS, bubonic plague, malaria) in order for localities to contain and manage these diseases. Morbidity may be further delineated by a measure of adaptive functioning, or the ability of a person to take care of personal needs or live independently.
Mortality, or death, is usually defined by cause of death. Similar to morbidity, the WHO recommends using the ICD-10 as the diagnostic nomenclature for cause of mortality. Internationally, vital statistics include death certificates with standardized information, such as date of birth, date of death, and cause of death.
Mortality is measured by the crude death rate (CDR), which is defined as the number of persons in a population who died in a specific year per one thousand members of the midyear population. The age-specific death rate (ASDR), which measures the number of persons in a specified age group (typically given in five-year intervals) within a population who died in a one-year period, is another useful rate, since persons of all ages do not die at the same rate. Sex-specific death rates and disease-specific death rates can also be calculated. Since those at the most advanced ages have greater risks of mortality, nations with younger populations tend to use crude death rates. International comparisons of the crude death rate must therefore take the age structure of the countries into consideration, converting each country’s CDR into a standardized death rate by comparing both populations to the age structure of a standardized population.
Another method of measuring mortality is through the use of life tables. The Englishman John Graunt (1620-1674) began the scientific study of mortality by analyzing published lists of those who died in London and noting that mortality followed definite patterns. Some of his observations, such as the longevity of females over males, continue to be true today. He used these analyses to develop life tables, used today to determine life expectancies. Life tables begin with a population of 100,000 at age 0, and then subject the population to the mortality probabilities of each age group up until all the members of the population have died. Life tables are used to determine either life expectancy at birth or life expectancy at a specific age. Life expectancies have increased dramatically in the modern era. “In 2001 the average life expectancy at birth in the United States was 77 years. Japan had the world’s highest expectancy—81 years. The lowest life expectancy estimates for the early 2000’s were in HIV/AIDS-plagued countries in sub-Saharan Africa: 34 years for Mozambique and 37 years for Botswana and Lesotho” (McFalls 2003, p. 11).
HISTORICAL TRAJECTORY OF MORBIDITY AND MORTALITY
Historically, humans evolved around 200,000 years ago in Africa. Early humans were hunter-gatherers, and they lived as nomads with high fertility and high mortality. Estimates for most of human history give the life expectancy at birth at approximately ten to twelve years of age. Infant mortality (the number of infants who die prior to one year of age), stood at around 500 per 1,000 live births (Haub 1995). Multiple factors contributed to high mortality, including infanticide (infants were a liability for nomads); a scarcity of food; and the risks involved in hunting large mammals with primitive weapons. By about 8,000 years ago, just prior to the development of horticulture or agriculture, the human population of the Earth was approximately 5 million. According to the evolutionary biologist Jared Diamond, by the time agricultural development began, nomadic humankind had migrated to all of the globe’s continents.
Agriculture occurred independently in nine areas through the domestication of wild plants and animals: Southwest Asia, China, Mesoamerica, the Andes of South America, the Eastern United States, the Sahel zone of Africa, West Africa, Ethiopia, and New Guinea. Agricultural societies had decreased mortality and increased fertility because they increased their food availability. Humans could now remain in a stable location and store food, leading to a decrease in starvation. Agriculture was also less risky than hunting large mammals. In an agricultural society, children were valued as laborers, so there was greater fertility. However, this was matched with high mortality, and population growth was slow. Agriculture also allowed for the development of permanent settlements. Initially, the move to settlements, and later to cities, led to higher mortality because concentrations of humans allowed diseases to be spread more easily. Yet improved nutrition in agricultural societies led to increased life expectancies, so that by the time of the Roman Empire life expectancy had increased to around twenty-two years. By the Middle Ages it had grown to over thirty. In the first approximately 10,000 years of agriculture, the population of the world grew from 4 million to 629 million in 1750.
Infectious diseases were a primary cause of mortality in premodern times. Epidemics caused the mortality to ebb and flow, thus maintaining minimum population growth. Livi-Bacci (1992) noted that infectious diseases are continually evolving. Three forms of the plague—bubonic, septicemic, and pneumonic—became pandemic, causing millions of deaths. The bubonic form of the disease—the most common type and spread by fleas—has symptoms of high fever, swollen lymph glands, and cardiac failure, with a 67 to 75 percent mortality rate. The septicemic form also has symptoms of fever, chills, headache, and gastrointestinal issues with a 30 to 50 percent mortality rate. The pneumonic form, spread by coughing or sneezing, has symptoms of spitting blood and is usually lethal (Dohl 1979). “The epidemic may have begun about 542 A.D. in Western Asia, spreading from there. It is believed that half the Byzantine Empire was destroyed in the sixth century, a total of 100 million deaths” (Habu 2006). Perry and Fetherston (1997) described three pandemics. The first was the Justinian Plague, which occurred in cycles, about every decade, from 541 to 622 CE. It began in Ethiopia and spread through North Africa, Europe, and most of Asia, killing an estimated 50 to 60 percent of the population. The second pandemic, called the Black Death, began in Central Asia and spread along trade routes, in two- to five-year cycles, killing 10 to 40 percent of the population (mortality was increased by the co-occurrence of epidemics of other diseases such as smallpox, influenza, and syphilis). The third pandemic started in China in 1855 and spread through Africa, Australia, Europe, India, Japan, and North and South America. Although declining, this third pandemic continues. “WHO reported an average of 1,666 plague cases per year worldwide” (Perry and Fetherston 1997, p. 56).
Throughout the world, infectious diseases became endemic, with cycles of reoccurrence. Survivors became resistant, however, so that the severity of reoccurrence lessened in the next generation. This cycling continued until there was an eventual adaptation of the disease to a less virulent strain. Yet infectious diseases, which were benign in an area where the population had adapted to the pathogens, could devastate a virgin population. This was evident when diseases such as measles, smallpox, and influenza, which had transformed into less virulent strains in Europe, reached America and caused widespread mortality. From 1500 to 1800, the population of Native Americans in what is now the continental United States decreased from 5 million to 60,000. Similar declines occurred among the inhabitants of other lands explored by Europeans, including Tasmania, Australia, and Tierra del Fuego.
Although decreases in mortality occurred with modernity, there is a debate as to whether these were due to medical advances or public health measures. The argument for public health is that mortality declines began prior to the development of medical advances. There is agreement that the effects of modernity led to rapid decreases in mortality in the eighteenth century. By the 1800s, life expectancy in the United States was about forty years. Food supplies increased with advances in technology. But diseases such as malaria, dysentery, smallpox, and typhoid fever could spread rapidly, especially in closely confined settlements, and effectively kill off a local population. In Europe, Louis Villermé (1782-1863) proved that crowding and unsanitary conditions led to the spreading of diseases. In the eighteenth century, medical advances, such as inoculations against smallpox, combined with widespread public health vaccinations and inoculations, led to the management and containment of lethal diseases. Public health measures, such as safe water supplies and sewage systems to dispose of waste products, controlled disease and immediately improved infant survival rates. Other public health measures designed to confine and contain the spread of diseases aided in controlling pandemics that followed trade and immigrants routes. Life expectancies continued to improve: In the United States, the life expectancy increased from 47 in 1900 to 77 in 2001 (McFalls 2003).
“Doubling time,” the number of years it will take a population to double its size, is used to describe population growth. In 1,000 CE, the population was 311 million and the doubling time was 1,000 years (Weeks 2005). In modernity, the population grew rapidly with doubling times decreasing. Joseph McFalls summarizes the historical population growth in increments of billions. Globally, the human population was under one billion from the Stone Age, one million years ago, until 1800. Two billion was reached in 1930, three billion in 1960, four billion in 1975, five billion in 1987, and six billion in 1999. A population of seven billion is projected for 2015.
KEY DETERMINANTS OF MORBIDITY AND MORTALITY
Morbidity and mortality are caused by a combination of factors, including disease, senescence (the physical deterioration that leads to increased vulnerability and susceptibility to diseases), and socioeconomic and political conditions. Mortality by infectious and parasitic diseases was the primary cause of mortality and morbidity in premodern societies. In modernity, the leading causes of mortality and morbidity are chronic and degenerative diseases such as cancer, cardiovascular disease, and diabetes. However, infectious diseases such as pneumonia, influenza, and HIV/AIDS, along with homicide, suicide, and accidental death, all rank high on the list of leading causes of death. The leading causes of mortality in the United States, Mexico, and Canada in 2001 were cardiovascular disease and cancer; but accidents, pneumonia, and influenza ranked in the top ten causes of mortality (Weeks 2005).
Morbidity and mortality are affected by biological, social, and socioeconomic conditions. In their 2005 article “Adult Mortality,” Richard Rogers and colleagues break these causes down into three categories: demographic characteristics (age, sex, and race and ethnicity); distal causes (socioeconomic status, social relationships, geographic factors, and environmental or human hazards); and proximate factors (health behaviors such as smoking and drinking, health condition, and physiological influences such as height and genetic markers).
Age is perhaps the factor most closely associated with mortality: The youngest and the oldest are the most likely to die. In 2005, Japan had the lowest infant mortality rate (IMR), 3 per 1,000, and Afghanistan had the highest, 154 per 1,000 (Weeks 2005). Infant mortality is also influenced by race and ethnicity: The higher socioeconomic segments of society have lower IMRs. The exception, known as the “Hispanic Paradox,” is that Hispanics in the United States, who have a generally lower socioeconomic status, have IMRs similar to non-Hispanic whites and Asians, revealing that family social support and lifestyles issues influence IMR. Humans are more likely to die as they age due to senescence. In 1825, Benjamin Gompertz presented a mathematical formula demonstrating the relationship between aging and death.
Gender has an effect on mortality, with females generally living longer than males. James Carey notes in his book Longevity (2003) that although females hold the longevity records across species, female mortality advantages are contextual. Females face greater risks during reproduction, especially in premodern societies. Females at the oldest ages also experience greater morbidity from chronic and degenerative diseases. With modernity, the gender gap in mortality is decreasing. In the United States, the greatest difference in death rates between sexes is for males aged fifteen to twenty-four, who are three times more likely to die than females of the same age. This increased mortality is due to accidents from risky behaviors, suicides, and homicides.
Socioeconomic status affects mortality in numerous ways. Minorities with lower socioeconomic status generally have higher mortality, and education level is inversely related to mortality. Infant mortality is greatly influenced by basic education about hygiene, eating a nutritious diet, and drinking unpolluted water. A higher level of educational attainment is generally indicative of higher socioeconomic functioning, and those with higher education attain higher income, have access to better housing, and have healthier lifestyles. Combining the effects of education and minority status, in the United States, black males with low educational attainment have a 19.9-year lower life expectancy than more educated whites (Seeman and Crimmins 2001).
Lifestyle choices, including physical fitness, exercise, limiting alcohol use, and maintaining a balanced diet, are related to lower morbidity and mortality. A pioneer longitudinal study begun in 1965 identified seven health habits, commonly called the “Alameda 7” that can improve morbidity and decrease mortality due to chronic diseases. The identified habits are: “engaging in regular physical activity, never smoking, drinking less than five drinks at one sitting, sleeping 7 to 8 hours a night, maintaining desirable body mass, avoiding snacks, and eating breakfast regularly” (Rogers et al. 2005, p. 271).
Sociopolitical causes of mortality include war, terrorism, and starvation. According to James Riley, the author of Rising Life Expectancy (2001), the leading causes of mortality in the twentieth century were war, famine, and disease. World War I led to an estimated 19 million deaths; the influenza epidemic of 1918–1919 caused over 40 million deaths; World War II caused about 52 million deaths; China’s Great Leap Forward in 1959–1961, which resulted in a politically caused famine, led to between 14 million and 26 million deaths, and UNAIDS reported in 2006 that the AIDS epidemic had caused 25 million deaths since 1981.
MORTALITY THEORIES
Malthusian theory represents one of the initial explanations of mortality and population growth. In 1798, Thomas Robert Malthus suggested that because population increased geometrically while the food supply could only increase arithmetically, population would be stabilized by positive checks, such as war, disease, and starvation, and preventive checks, such as controlling births (with the preferred method being moral restraint or abstinence, rather than contraception and abortion). Karl Marx and Freiderich Engels challenged this theory. While they agreed that the population was growing, they asserted that population growth was good, and that science could increase food supplies to such an extent that, at least in a socialistic society, poverty and starvation could be eliminated.
Changing conditions of modernity have also challenged Malthusian theory. While rapid global population growth has occurred, the stable food supply has increased along with the population base. The current Malthusian position, as presented by Paul and Anne Ehrlich in The Population Explosion (1990), is neo-Malthusian, for it accepts the use of abortion and birth control to control population size, contrary to Malthus. Neo-Malthusians argue that continued population growth will be catastrophic. They argue that the dramatic increases in food production that occurred in the past, through the use of chemicals and new technologies, cannot continue. The earth’s resources are finite, nonrenewable, and being depleted by continuing population growth, placing mankind at risk of annihilation.
Demographic transition theory explains the mortality changes that have occurred with modernity. In a premodern society there is high infant mortality and a short life expectancy with high mortality. Modernity drastically improved life expectancy through changes in public health practices, the most important being the availability of fresh sanitary water, sewerage systems, adequate diets, and modern medicine. Prior to the development of modern medicine, public health practices also managed the spread of contagious diseases through containment and isolation. The most dramatic improvements in mortality rates were made initially through decreasing infant mortality. In the transition phase, the sharp drop in mortality rates precipitated an immediate rapid increase in the population, as those who would previously have died in infancy survived and lived an extended life span (Weeks 2005).
The epidemiological transition theory, hypothesized by Abdel Omran in 1971, suggests there were three stages of epidemiological modernization. The first stage was the Age of Pestilence and Famine, which lasted from premodern times until around 1875 in developed societies. The primary causes of mortality in this stage were influenza, pneumonia, smallpox, tuberculosis, and other related diseases, resulting in high infant and childhood mortality and a life expectancy averaging between twenty and forty years. The second stage was the Age of Receding Pandemics, which lasted from around 1875 to 1930 in developed countries. In this second stage there was a decline in mortality due to improved standards of living, sanitation, and public health. The third, current, stage is the Age of Chronic and Degenerative Illnesses. In this stage the causes of mortality are the chronic degenerative diseases (heart disease, cancer, and stroke), and life expectancy at birth exceeds seventy years.
S. Jay Olshansky and A. Brian Ault (1986) have proposed a fourth stage—the Stage of Delayed Degenerative Diseases. In this stage, diseases are influenced by individual behavior or lifestyle choices, and deaths are due to social pathologies such as accidents, alcoholism, suicide, and homicide, as well as lifestyle issues such as smoking and diet. Jean-Marie Robine (2001) suggests a fifth stage, called the Age of the Conquest of the Extent of Life, as it is now possible for humans to live between 110 and 120 years. James Vaupel notes that after about the age of 95, mortality decelerates and actually plateaus. This would support a compression of mortality, with those surviving to be the “oldest old” having either lesser or later onset of chronic and degenerative diseases.
Another theoretical explanation for mortality is the “rectangularization of the mortality curve” that occurred with modern health practices. In 1825 Benjamin Gompertz developed a mathematical formula, which he called a “law of mortality,” depicting mortality rates as a sloped graph, with rates of mortality increasing with age. He argued that there is a biological limit to the human life span, with a life expectancy of around age eighty-five or ninety due to senescence. So even if there are medical advances in curing cancer or treating heart disease, those who survive one specific disease will be frail, raising the risk of morbidity through other disease processes. Although there have been dramatic increases in life expectancy during demographic transitions, the greatest strides were in mortality in infancy, childhood, and early adult life. Olshansky and colleagues (2001) argue that the only way to have another similar increase in life expectancy would be to increase the life span of those over age seventy, which will be more difficult than the earlier reduction of infant mortality.
THE HUMAN LIFE SPAN
Longevity experts question the existence of a definite human life span. The longest known life span is 122 years and 5 months, based on the life span of a single human, Jeanne Calment, who died in 1997. This record could be broken by one person who lives to 122 years and 6 months. Vaupel notes that prior to the nineteenth century only a few scattered individuals survived past 100. There were countries where over one million people live but that had no documented centurions or supercenturions (aged 110 and over). However, at the beginning of the twentieth century, there were over 100,000 documented centurions. Beginning with the first documented supercenturion, Katherine Plunket, who died at age 111 in 1932 in Northern Ireland, experts began to verify the age validity of supercenturions, which requires collaborative documentation (see Vaupel 2001; Vaupel et al. 1998).
Dennis Ahlburg and James Vaupel (1990) argue that current projections for life expectancy are based on conservative forecasting. They argue that mortality rates have declined at a rate of 1 percent to 2 percent per year in developed countries, especially the mortality rates of those age 65 and over. They assume that if this mortality decrease continues at a 2 percent progression, in 2080 the expected life expectancy would be 100 years for females and 96 for males.
If life expectancy was approaching a biological limit, one would assume that the mortality rates of the oldest old would tend to be higher in countries with higher rates of the oldest old. However, Vaupel has found that countries with the oldest old, such as France, Japan, and Sweden, show a slowing of the mortality rates in the oldest old. Vaupel, the director of the Max Planck Institute for Demographic Research, argues that life expectancy has been rising at a linear pace over the last 160 years at a rate of almost three months per year. Shiro Horiuchi and John Wilmoth reported in 1998 that mortality in the elderly goes through three stages: a deceleration of mortality after age 80, a mortality plateau between ages 80 to 105, and an actual decline in mortality in the highest ages (over 110). Manton and colleagues argued in 1991 that even with the interdependence of diseases, as we progress in treating specific diseases we are altering senescence.
SEE ALSO AIDS; Death and Dying; Demographic Transition; Demography; Disease; Population Studies; Psychosomatics, Social; Public Health; Sanitation; Suicide
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Mary Ann Davis