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Monday, December 5, 2022

Race and health

From Wikipedia, the free encyclopedia
 
Race and health refers to how being identified with a specific race influences health. Race is a complex concept that has changed across chronological eras and depends on both self-identification and social recognition. In the study of race and health, scientists organize people in racial categories depending on different factors such as: phenotype, ancestry, social identity, genetic makeup and lived experience. "Race" and ethnicity often remain undifferentiated in health research.

Differences in health status, health outcomes, life expectancy, and many other indicators of health in different racial and ethnic groups are well documented. Epidemiological data indicate that racial groups are unequally affected by diseases, in terms or morbidity and mortality. Some individuals in certain racial groups receive less care, have less access to resources, and live shorter lives in general. Overall, racial health disparities appear to be rooted in social disadvantages associated with race such as implicit stereotyping and average differences in socioeconomic status.

Health disparities are defined as "preventable differences in the burden of disease, injury, violence, or opportunities to achieve optimal health that are experienced by socially disadvantaged populations". According to the U.S. Centers for Disease Control and Prevention, they are intrinsically related to the "historical and current unequal distribution of social, political, economic and environmental resources".

The relationship between race and health has been studied from multidisciplinary perspectives, with increasing focus on how racism influences health disparities, and how environmental and physiological factors respond to one another and to genetics.

Racial health disparities

Health disparities refer to gaps in the quality of health and health care across racial and ethnic groups. The US Health Resources and Services Administration defines health disparities as "population-specific differences in the presence of disease, health outcomes, or access to health care". Health is measured through variables such as life expectancy and incidence of diseases.

For racial and ethnic minorities in the United States, health disparities take on many forms, including higher rates of chronic disease, premature death, and maternal mortality compared to the rates among whites. It is important to note that this pattern is not universal. Some minority groups—most notably, Hispanic immigrants—may have better health outcomes than whites when they arrive in the United States. However this appears to diminish with time spent in the United States. For other indicators, disparities have shrunk, not because of improvements among minorities but because of declines in the health of majority groups.

In the U.S., more than 133 million Americans (45% of the population) have one or more chronic diseases. One study has shown that between the ages of 60 to 70, racial/ethnic minorities are 1.5 to 2.0 times more likely than whites (Hispanic and non Hispanic) to have one of the four major chronic diseases specifically Diabetes, cancer, cardiovascular disease (CVD), and chronic lung disease. However, the greatest differences only occurred among people with single chronic diseases. Racial/ethnic differences were less distinct for some conditions including multiple diseases. Non-Hispanic whites trended toward a high prevalence for dyads of cardiovascular disease (CVD) with cancer or lung disease. Hispanics and African Americans had the greatest prevalence of diabetes, while non-Hispanic blacks had higher odds of having heart disease with cancer or chronic lung disease than non-Hispanic whites. Among non-Hispanic whites the prevalence of multimorbidities that include diabetes was low; however, non-Hispanic whites had a very high prevalence of multimorbidities that exclude diabetes. Non-Hispanic whites had the highest prevalence of cancer only or lung disease only. 

Between 1960 and 2005 the percentage of children with a chronic disease in the United States quadrupled with minority having higher likelihood for these disease. The most common major chronic biases of youth in the United States are asthma, diabetes mellitus, obesity, hypertension, dental disease, attention deficit hyperactivity disorder (ADHD), mental illness, cancers and others. This results in Black and Latinx adult patients facing a disproportionate amount of health concerns, such as asthma, with treatment and management guidelines not developed with studies based on their populations and healthcare needs.

Although individuals from different environmental, continental, socioeconomic, and racial groups etc. have different levels of health, yet not all of these differences are always categorized or defined as health disparities. Some researchers separate definitions of health inequality from health disparity by preventability. Health inequalities are often categorized as being unavoidable i.e. due to age, while preventable unfair health outcomes are categorized as health inequities. These are seen as preventable because they are usually associated with income, education, race, ethnicity, gender, and more.

Defining race

Definitions of race are ambiguous due to the various paradigms used to discuss race. These definitions are a direct result of biological and social views. Definitions have changed throughout history to yield a modern understanding of race that is complex and fluid. Moreover, there is no one definition that stands, as there are many competing and interlocking ways to look at race. Due to its ambiguity, terms such as race, genetic population, ethnicity, geographic population, and ancestry are used interchangeably in everyday discourse involving race. Some researchers critique this interchangeability noting that the conceptual differences between race and ethnicity are not widely agreed upon.

Even though there is a broad scientific agreement that essentialist and typological conceptions of race are untenable, scientists around the world continue to conceptualize race in widely differing ways. Historically, biological definitions of race have encompassed both essentialist and anti-essentialist views. Essentialists have sought to show that racial groups are genetically distinct populations, describing "races as groups of people who share certain innate, inherited biological traits". In contrast, anti-essentialists have used biological evidence to demonstrate that "race groupings do not reflect patterns of human biological variation, countering essentialist claims to the contrary".

Over the past 20 years, a consensus has emerged that, while race is partially based on physical similarities within groups, it does not have an inherent physical or biological meaning. In response, researchers and social scientists have begun examining notions of race as constructed. Racial groups are "constructed" from differing historical, political, and economic contexts, rather than corresponding to inherited, biological variations. Proponents of the constructionist view claim that biological definitions have been used to justify racism in the past and still have the potential to be used to encourage racist thinking in the future. Since race is changing and often so loosely characterized on arbitrary phenotypes, and because it has no genetic basis, the only working definition we can assign it is a social construct. This is not to say race is imaginary or non-existent. It is an important social reality. However to say that the concept of race has any scientific merit or has a scientific foundation can lead to many issues in scientific research, and it may also lead to inherent racial bias.

Social views also better explain the ambiguity of racial definitions. An individual may self-identify as one race based on one set of determinants (for example, phenotype, culture, ancestry) while society may ascribe the person otherwise based on external forces and discrete racial standards. Dominant racial conceptions influence how individuals label both themselves and others within society. Modern human populations are becoming more difficult to define within traditional racial boundaries due to racial admixture. Most scientific studies, applications, and government documents ask individuals to self-identify race from a limited assortment of common racial categories. The conflict between self-identification and societal ascription further complicates biomedical research and public health policies. However complex its sociological roots, race has real biological ramifications; the intersection of race, science, and society permeates everyday life and influences human health via genetics, access to medical care, diagnosis, and treatment.

Race and disease

Diseases affect racial groups differently, especially when they are co-related with class disparities. As socioeconomic factors influence the access to care, the barriers to access healthcare systems can perpetuate different biological effects of diseases among racial groups that are not pre-determined by biology.

Some researchers advocate for the use of self-reported race as a way to trace socioeconomic disparities and its effects in health. For instance, a study conducted by the National Health Service checks program in the United Kingdom, which aims to increase diagnosis across demographics, noted that "the reported lower screening in specific black and minority ethnic communities... may increase inequalities in health." In this specific case, the lack of attention to certain demographics can be seen as a cause of increased instances of disease from this lack of proper, equal preventive care. One must consider these external factors when evaluating statistics on the prevalence of disease in populations, even though genetic components can play a role in predispositions to contracting some illnesses.

Individuals who share a similar genetic makeup can also share certain propensity or resistance to specific diseases. However, there are confronted positions in relation to the utility of using 'races' to talk about populations sharing a similar genetic makeup. Some geneticists argued that human variation is geographically structured and that genetic differences correlate with general conceptualizations of racial groups. Others claimed that this correlation is too unstable and that the genetic differences are minimal and they are "distributed over the world in a discordant manner". Therefore, race is regarded by some as a useful tool for the assessment of genetic epidemiological risk, while others consider it can lead to an increased underdiagnosis in 'low risk' populations.

Single-gene disorders

There are many autosomal recessive single gene genetic disorders that differ in frequency between different populations due to the region and ancestry as well as the founder effect. Some examples of these disorders include:

Multifactorial polygenic diseases

Many diseases differ in frequency between different populations. However, complex diseases are affected by multiple factors, including genetic and environmental. There is controversy over the extent to which some of these conditions are influenced by genes, and ongoing research aims to identify which genetic loci, if any, are linked to these diseases. "Risk is the probability that an event will occur. In epidemiology, it is most often used to express the probability that a particular outcome will occur following a particular exposure." Different populations are considered "high-risk" or "low-risk" groups for various diseases due to the probability of that particular population being more exposed to certain risk factors. Beyond genetic factors, history and culture, as well as current environmental and social conditions, influence a certain populations' risk for specific diseases.

Disease progression

Racial groups may differ in how a disease progresses. Different access to healthcare services, different living and working conditions influence how a disease progresses within racial groups. However, the reasons for these differences are multiple, and should not be understood a consequence of genetic differences between races, but rather as effects of social and environmental factors affecting.

Prevention

Genetics have been proven to be a strong predictor for common diseases such as cancer, cardiovascular disease (CVD), diabetes, autoimmune disorders, and psychiatric illnesses. Some geneticists have determined that "human genetic variation is geographically structured" and that different geographic regions correlate with different races. Meanwhile, others have claimed that the human genome is characterized by clinal changes across the globe, in relation with the "Out of Africa" theory and how migration to new environments cause changes in populations' genetics over time.

Some diseases are more prevalent in some populations identified as races due to their common ancestry. Thus, people of African and Mediterranean descent are found to be more susceptible to sickle-cell disease while cystic fibrosis and hemochromatosis are more common among European populations. Some physicians claim that race can be used as a proxy for the risk that the patient may be exposed to in relation to these diseases. However, racial self-identification only provides fragmentary information about the person's ancestry. Thus, racial profiling in medical services would also lead to the risk of underdiagnosis.

While genetics certainly play a role in determining how susceptible a person is to specific diseases, environmental, structural and cultural factors play a large role as well. For this reason, it is impossible to discern exactly what causes a person to acquire a disease, but it is important to observe how all these factors relate to each other. Each person's health is unique, as they have different genetic compositions and life histories.

Race-based treatment

Racial groups, especially when defined as minorities or ethnic groups, often face structural and cultural barriers to access healthcare services. The development of culturally and structurally competent services and research that meet the specific health care needs of racial groups is still in its infancy. In the United States, the Office of Minority Health The NIH (National institutes of health) and The WHO are organizations that provide useful links and support research that is targeted at the development of initiatives around minority communities and the health disparities they face. Similarly, In the United Kingdom, the National Health Service established a specialist collection on Ethnicity & Health. This resource was supported by the National Institute for Health and Clinical Excellence (NICE) as part of the UK NHS Evidence initiative NHS Evidence. Similarly, there are growing numbers of resource and research centers which are seeking to provide this service for other national settings, such as Multicultural Mental Health Australia. However, cultural competence has also been criticized for having the potential to create stereotypes.

Scientific studies have shown the lack of efficacy of adapting pharmaceutical treatment to racial categories. "Race-based medicine" is the term for medicines that are targeted at specific racial clusters which are shown to have a propensity for a certain disorder. The first example of this in the U.S. was when BiDil, a medication for congestive heart failure, was licensed specifically for use in American patients that self-identify as black. Previous studies had shown that African American patients with congestive heart failure generally respond less effectively to traditional treatments than white patients with similar conditions.

After two trials, BiDil was licensed exclusively for use in African American patients. Critics have argued that this particular licensing was unwarranted, since the trials did not in fact show that the drug was more effective in African Americans than in other groups, but merely that it was more effective in African Americans than other similar drugs. It was also only tested in African American males, but not in any other racial groups or among women. This peculiar trial and licensing procedure has prompted suggestions that the licensing was in fact used as a race-based advertising scheme.

Critics are concerned that the trend of research on race-specific pharmaceutical treatments will result in inequitable access to pharmaceutical innovation and smaller minority groups may be ignored. This has led to a call for regulatory approaches to be put in place to ensure scientific validity of racial disparity in pharmacological treatment.

An alternative to "race-based medicine" is personalized or precision medicine. Precision medicine is a medical model that proposes the customization of healthcare, with medical decisions, treatments, practices, or products being tailored to the individual patient. It involves identifying genetic, genomic (i.e., genomic sequencing), and clinical information—as opposed to using race as a proxy for these data—to better predict a patient's predisposition to certain diseases.

Environmental factors

A positive correlation between minorities and a socioeconomic status of being low-income in industrialized and rural regions of the U.S. depict how low-income communities tend to include more individuals that have a lower educational background, most importantly in health. Income status, diet, and education all construct a higher burden for low-income minorities, to be conscious about their health. Research conducted by medical departments at universities in San Diego, Miami, Pennsylvania, and North Carolina suggested that minorities in regions where lower socioeconomic status is common, there was a direct relationship with unhealthy diets and greater distance of supermarkets. Therefore, in areas where supermarkets are less accessible (food deserts) to impoverished areas, the more likely these groups are to purchase inexpensive fast food or just follow an unhealthy diet. As a result, because food deserts are more prevalent in low income communities, minorities that reside in these areas are more prone to obesity, which can lead to diseases such as chronic kidney disease, hypertension, or diabetes.

Furthermore, this can also occur when minorities living in rural areas undergoing urbanization, are introduced to fast food. A study done in Thailand focused on urbanized metropolitan areas, the students who participated in this study as were diagnosed as "non-obese" in their early life according to their BMI, however were increasingly at risk of developing Type 2 Diabetes, or obesity as adults, as opposed to young adults who lived in more rural areas during their early life. Therefore, early exposure to urbanized regions can encourage unhealthy eating due to widespread presence of inexpensive fast food. Different racial populations that originate from more rural areas and then immigrate to the urbanized metropolitan areas can develop a fixation for a more westernized diet; this change in lifestyle typically occurs due to loss of traditional values when adapting to a new environment. For example, a 2009 study named CYKIDS was based on children from Cyprus, a country east of the Mediterranean Sea, who were evaluated by the KIDMED index to test their adherence to a Mediterranean diet after changing from rural residence to an urban residence. It was found that children in urban areas swapped their traditional dietary patterns for a diet favoring fast food.

Genetic factors

The fact that every human has a unique genetic code is the key to techniques such as genetic fingerprinting. Versions of genetic markers, known as alleles, occur at different frequencies in different human populations; populations that are more geographically and ancestrally remote tend to differ more.

A phenotype is the "outward, physical manifestation" of an organism." For humans, phenotypic differences are most readily seen via skin color, eye color, hair color, or height; however, any observable structure, function, or behavior can be considered part of a phenotype. A genotype is the "internally coded, inheritable information" carried by all living organisms. The human genome is encoded in DNA.

For any trait of interest, observed differences among individuals "may be due to differences in the genes" coding for a trait and "the result of variation in environmental condition". This variability is due to gene-environment interactions that influence genetic expression patterns and trait heritability.

For humans, there is "more genetic variation among individual people than between larger racial groups". In general, an average of 80% of genetic variation exists within local populations, around 10% is between local populations within the same continent, and approximately 8% of variation occurs between large groups living on different continents. Studies have found evidence of genetic differences between populations, but the distribution of genetic variants within and among human populations is impossible to describe succinctly because of the difficulty of defining a "population", the clinal nature of variation, and heterogeneity across the genome. Thus, the racialization of science and medicine can lead to controversy when the term population and race are used interchangeably.

Evolutionary factors

Currently malaria-endemic countries in the eastern hemisphere
 
Currently malaria-endemic countries in the western hemisphere

Genes may be under strong selection in response to local diseases. For example, people who are duffy negative tend to have higher resistance to malaria. Most Africans are duffy negative and most non-Africans are duffy positive due to endemic transmission of malaria in Africa. A number of genetic diseases more prevalent in malaria-affected areas may provide some genetic resistance to malaria including sickle cell disease, thalassaemias, glucose-6-phosphate dehydrogenase, and possibly others.

Many theories about the origin of the cystic fibrosis have suggested that it provides a heterozygote advantage by giving resistance to diseases earlier common in Europe.

In earlier research, a common theory was the "common disease-common variant" model. It argues that for common illnesses, the genetic contribution comes from the additive or multiplicative effects of gene variants that each one is common in the population. Each such gene variant is argued to cause only a small risk of disease and no single variant is sufficient or necessary to cause the disease. An individual must have many of these common gene variants in order for the risk of disease to be substantial.

More recent research indicates that the "common disease-rare variant" may be a better explanation for many common diseases. In this model, rare but higher-risk gene variants cause common diseases. This model may be relevant for diseases that reduces fertility. In contrast, for common genes associated with common disease to persist they must either have little effect during the reproductive period of life (like Alzheimer's disease) or provide some advantage in the original environment (like genes causing autoimmune diseases also providing resistance against infections). In either case varying frequencies of genes variants in different populations may be an explanation for health disparities. Genetic variants associated with Alzheimer's disease, deep venous thrombosis, Crohn disease, and type 2 diabetes appear to adhere to "common disease-common variant" model.

Gene flow

Gene flow and admixture can also have an effect on relationships between race and race-linked disorders. Multiple sclerosis, for example, is typically associated with people of European descent, but due to admixture African Americans have elevated levels of the disorder relative to Africans.

Some diseases and physiological variables vary depending upon their admixture ratios. Examples include measures of insulin functioning and obesity.

Gene interactions

The same gene variant, or group of gene variants, may produce different effects in different populations depending on differences in the gene variants, or groups of gene variants, they interact with. One example is the rate of progression to AIDS and death in HIV–infected patients. In Caucasians and Hispanics, HHC haplotypes were associated with disease retardation, particularly a delayed progression to death, while for African Americans, possession of HHC haplotypes was associated with disease acceleration. In contrast, while the disease-retarding effects of the CCR2-641 allele were found in African Americans, they were not found in Caucasians.

Theoretical approaches in addressing health and race disparities

Public health researchers and policy makers are working to reduce health disparities. Health effects of racism are now a major area of research. In fact, these seem to be the primary research focus in biological and social sciences. Interdisciplinary methods have been used to address how race affects health. according to published studies, many factors combine to affect the health of individuals and communities. Whether people are healthy or not, is determined by their circumstances and environment. Factors that need to be addressed when looking at health and race include income and social status, education, physical environment, social support networks, genetics, health services, targeted instruction, and gender. These determinants are often cited in public health, anthropology, and other social science disciplines. The WHO categorizes these determinants into three broader topics: the social and economic environment, the physical environment, and the person's individual characteristics and behaviors. Due to the diversity of factors that often attribute to health disparities outcomes, interdisciplinary approaches are often implemented.

Interdisciplinarity or interdisciplinary studies involves the combining of two or more academic disciplines into one activity (e.g., a research project) The term interdisciplinary is applied within education and training pedagogies to describe studies that use methods and insights of several established disciplines or traditional fields of study. Interdisciplinarity involves researchers, students, and teachers in the goals of connecting and integrating several academic schools of thought, professions, or technologies—along with their specific perspectives—in the pursuit of a common task.

Biocultural approach

Biocultural evolution was introduced and first used in the 1970s. Biocultural methods focus on the interactions between humans and their environment to understand human biological adaptation and variation. These studies:

"research on questions of human biology and medical ecology that specifically includes social, cultural, or behavioral variables in the research design, offer valuable models for studying the interface between biological and cultural factors affecting human well-being"

This approach is useful in generating holistic viewpoints on human biological variation. There are two biocultural approach models. The first approach fuses biological, environmental, and cultural data. The second approach treats biological data as primary data and culture and environmental data as secondary.

The salt sensitivity hypothesis is an example of implementing biocultural approaches in order to understand cardiovascular health disparities among African American populations. This theory, founded by Wilson and Grim, stems from the disproportional rates of salt sensitive high blood pressure seen between U.S. African American and White populations and between U.S. African American and West Africans as well. The researchers hypothesized that the patterns were in response to two events. One the trans-Atlantic slave trade, which resulted in massive death totals of Africans who were forced over, those who survived and made to the United States were more likely able to withstand the harsh conditions because they retained salt and water better. The selection continued once they were in the United States. African Americans who were able to withstand hard working conditions had better survival rates due to high water and salt retention. Second, today, because of different environmental conditions and increased salt intake with diets, water and salt retention are disadvantageous, leaving U.S. African Americans at disproportional risks because of their biological descent and culture.

Bio social inheritance model

Similar to the biocultural approach, the bio social inheritance model also looks at biological and social methods in examining health disparities. Hoke et al. define Biosocial inheritance as "the process whereby social adversity in one generation is transmitted to the next through reinforcing biological and social mechanisms that impair health, exacerbating social and health disparities."

Controversy

There is a controversy regarding race as a method for classifying humans. Different sources argue it is purely social construct or a biological reality reflecting average genetic group differences. New interest in human biological variation has resulted in a resurgence of the use of race in biomedicine.

The main impetus for this development is the possibility of improving the prevention and treatment of certain diseases by predicting hard-to-ascertain factors, such as genetically conditioned health factors, based on more easily ascertained characteristics such as phenotype and racial self-identification. Since medical judgment often involves decision making under uncertain conditions, many doctors consider it useful to take race into account when treating disease because diseases and treatment responses tend to cluster by geographic ancestry. The discovery that more diseases than previously thought correlate with racial identification have further sparked the interest in using race as a proxy for bio-geographical ancestry and genetic buildup.

Race in medicine is used as an approximation for more specific genetic and environmental risk factors. Race is thus partly a surrogate for environmental factors such as differences in socioeconomic status that are known to affect health. It is also an imperfect surrogate for ancestral geographic regions and differences in gene frequencies between different ancestral populations and thus differences in genes that can affect health. This can give an approximation of probability for disease or for preferred treatment, although the approximation is less than perfect.

Taking the example of sickle-cell disease, in an emergency room, knowing the geographic origin of a patient may help a doctor doing an initial diagnosis if a patient presents with symptoms compatible with this disease. This is unreliable evidence with the disease being present in many different groups as noted above with the trait also present in some Mediterranean European populations. Definitive diagnosis comes from examining the blood of the patient. In the US, screening for sickle cell anemia is done on all newborns regardless of race.

The continued use of racial categories has been criticized. Apart from the general controversy regarding race, some argue that the continued use of racial categories in health care and as risk factors could result in increased stereotyping and discrimination in society and health services. Some of those who are critical of race as a biological concept see race as socially meaningful group that is important to study epidemiologically in order to reduce disparities. For example, some racial groups are less likely than others to receive adequate treatment for osteoporosis, even after risk factors have been assessed. Since the 19th century, blacks have been thought to have thicker bones than whites have and to lose bone mass more slowly with age. In a recent study, African Americans were shown to be substantially less likely to receive prescription osteoporosis medications than Caucasians. Men were also significantly less likely to be treated compared with women. This discrepancy may be due to physicians' knowledge that, on average, African Americans are at lower risk for osteoporosis than Caucasians. It may be possible that these physicians generalize this data to high-risk African-Americans, leading them to fail to appropriately assess and manage these individuals' osteoporosis. On the other hand, some of those who are critical of race as a biological concept see race as socially meaningful group that is important to study epidemiologically in order to reduce disparities.

David Williams (1994) argued, after an examination of articles in the journal Health Services Research during the 1966–90 period, that how race was determined and defined was seldom described. At a minimum, researchers should describe if race was assessed by self-report, proxy report, extraction from records, or direct observation. Race was also often used questionable, such as an indicator of socioeconomic status. Racial genetic explanations may be overemphasized, ignoring the interaction with and the role of the environment.

From concepts of race to ethnogenetic layering

There is general agreement that a goal of health-related genetics should be to move past the weak surrogate relationships of racial health disparity and get to the root causes of health and disease. This includes research which strives to analyze human genetic variation in smaller groups than races across the world.

One such method is called ethnogenetic layering. It works by focusing on geographically identified microethnic groups. For example, in the Mississippi Delta region ethnogenetic layering might include such microethnic groups as the Cajun (as a subset of European Americans), the Creole and Black groups [with African origins in Senegambia, Central Africa and Bight of Benin] (as a subset of African Americans), and Choctaw, Houmas, Chickasaw, Coushatta, Caddo, Atakapa, Karankawa and Chitimacha peoples (as subsets of Native Americans).

Better still may be individual genetic assessment of relevant genes. As genotyping and sequencing have become more accessible and affordable, avenues for determining individual genetic makeup have opened dramatically. Even when such methods become commonly available, race will continue to be important when looking at groups instead of individuals such as in epidemiologic research.

Some doctors and scientists such as geneticist Neil Risch argue that using self-identified race as a proxy for ancestry is necessary to be able to get a sufficiently broad sample of different ancestral populations, and in turn to be able to provide health care that is tailored to the needs of minority groups.

Association studies

One area in which population categories can be important considerations in genetics research is in controlling for confounding between population genetic substructure, environmental exposures, and health outcomes. Association studies can produce spurious results if cases and controls have differing allele frequencies for genes that are not related to the disease being studied, although the magnitude of its problem in genetic association studies is subject to debate. Various techniques detect and account for population substructure, but these methods can be difficult to apply in practice.

Population genetic substructure also can aid genetic association studies. For example, populations that represent recent mixtures of separated ancestral groups can exhibit longer-range linkage disequilibrium between susceptibility alleles and genetic markers than is the case for other populations. Genetic studies can use this disequilibrium to search for disease alleles with fewer markers than would be needed otherwise. Association studies also can take advantage of the contrasting experiences of racial or ethnic groups, including migrant groups, to search for interactions between particular alleles and environmental factors that might influence health.

Human genome projects

The Human Genome Diversity Project has collected genetic samples from 52 indigenous populations.

Sources of racial disparities in care

In a report by the Institute of Medicine called Unequal Treatment, three major source categories are put forth as potential explanations for disparities in health care: patient-level variables, healthcare system-level factors, and care process-level variables.

Patient-level variables

There are many individual factors that could explain the established differences in health care between different racial and ethnic groups. First, attitudes and behaviors of minority patients are different. They are more likely to refuse recommended services, adhere poorly to treatment regimens, and delay seeking care, yet despite this, these behaviors and attitudes are unlikely to explain the differences in health care. In addition to behaviors and attitudes, biological based racial differences have been documented, but these also seem unlikely to explain the majority of observed disparities in care.

Health system-level factors

Health system-level factors include any aspects of health systems that can have different effects on patient outcomes. Some of these factors include different access to services, access to insurance or other means to pay for services, access to adequate language and interpretation services, and geographic availability of different services. Many studies assert that these factors explain portions of the existing disparities in health of racial and ethnic minorities in the United States when compared to their white counterparts.

Care process-level variables

Three major mechanisms are suggested by the Institute of Medicine that may contribute to healthcare disparities from the provider's side: bias (or prejudice) against racial and ethnic minorities; greater clinical uncertainty when interacting with minority patients; and beliefs held by the provider about the behavior or health of minorities. While research in this area is ongoing, some exclusions within clinical trials themselves are also present. A recent systematic review of the literature relating to hearing loss in adults demonstrated that many studies fail to include aspects of racial or ethnic diversity, resulting in studies that do not necessarily represent the US population.

Heritability of IQ

From Wikipedia, the free encyclopedia

Research on the heritability of IQ inquires into the degree of variation in IQ within a population that is due to genetic variation between individuals in that population. There has been significant controversy in the academic community about the heritability of IQ since research on the issue began in the late nineteenth century. Intelligence in the normal range is a polygenic trait, meaning that it is influenced by more than one gene, and in the case of intelligence at least 500 genes. Further, explaining the similarity in IQ of closely related persons requires careful study because environmental factors may be correlated with genetic factors.

Early twin studies of adult individuals have found a heritability of IQ between 57% and 73%, with some recent studies showing heritability for IQ as high as 80%. IQ goes from being weakly correlated with genetics for children, to being strongly correlated with genetics for late teens and adults. The heritability of IQ increases with the child's age and reaches a plateau at 18–20 years old, continuing at that level well into adulthood. However, poor prenatal environment, malnutrition and disease are known to have lifelong deleterious effects.

Although IQ differences between individuals have been shown to have a large hereditary component, it does not follow that disparities in IQ between groups have a genetic basis. The scientific consensus is that genetics does not explain average differences in IQ test performance between racial groups.

Heritability and caveats

Heritability is a statistic used in the fields of breeding and genetics that estimates the degree of variation in a phenotypic trait in a population that is due to genetic variation between individuals in that population. The concept of heritability can be expressed in the form of the following question: "What is the proportion of the variation in a given trait within a population that is not explained by the environment or random chance?"

Estimates of heritability take values ranging from 0 to 1; a heritability estimate of 1 indicates that all variation in the trait in question is genetic in origin and a heritability estimate of 0 indicates that none of the variation is genetic. The determination of many traits can be considered primarily genetic under similar environmental backgrounds. For example, a 2006 study found that adult height has a heritability estimated at 0.80 when looking only at the height variation within families where the environment should be very similar. Other traits have lower heritability estimates, which indicate a relatively larger environmental influence. For example, a twin study on the heritability of depression in men estimated it as 0.29, while it was 0.42 for women in the same study.

Caveats

There are a number of points to consider when interpreting heritability:

  • Heritability measures the proportion of variation in a trait that can be attributed to genes, and not the proportion of a trait caused by genes. Thus, if the environment relevant to a given trait changes in a way that affects all members of the population equally, the mean value of the trait will change without any change in its heritability (because the variation or differences among individuals in the population will stay the same). This has evidently happened for height: the heritability of stature is high, but average heights continue to increase. Thus, even in developed nations, a high heritability of a trait does not necessarily mean that average group differences are due to genes. Some have gone further, and used height as an example in order to argue that "even highly heritable traits can be strongly manipulated by the environment, so heritability has little if anything to do with controllability."
  • A common error is to assume that a heritability figure is necessarily unchangeable. The value of heritability can change if the impact of environment (or of genes) in the population is substantially altered. If the environmental variation encountered by different individuals increases, then the heritability figure would decrease. On the other hand, if everyone had the same environment, then heritability would be 100%. The population in developing nations often has more diverse environments than in developed nations. This would mean that heritability figures would be lower in developing nations. Another example is phenylketonuria which previously caused mental retardation for everyone who had this genetic disorder and thus had a heritability of 100%. Today, this can be prevented by following a modified diet, resulting in a lowered heritability.
  • A high heritability of a trait does not mean that environmental effects such as learning are not involved. Vocabulary size, for example, is very substantially heritable (and highly correlated with general intelligence) although every word in an individual's vocabulary is learned. In a society in which plenty of words are available in everyone's environment, especially for individuals who are motivated to seek them out, the number of words that individuals actually learn depends to a considerable extent on their genetic predispositions and thus heritability is high.
  • Since heritability increases during childhood and adolescence, and even increases greatly between 16 and 20 years of age and adulthood, one should be cautious drawing conclusions regarding the role of genetics and environment from studies where the participants are not followed until they are adults. Furthermore, there may be differences regarding the effects on the g-factor and on non-g factors, with g possibly being harder to affect and environmental interventions disproportionately affecting non-g factors.
  • Polygenic traits often appear less heritable at the extremes. A heritable trait is definitionally more likely to appear in the offspring of two parents high in that trait than in the offspring of two randomly selected parents. However, the more extreme the expression of the trait in the parents, the less likely the child is to display the same extreme as the parents. At the same time, the more extreme the expression of the trait in the parents, the more likely the child is to express the trait at all. For example, the child of two extremely tall parents is likely to be taller than the average person (displaying the trait), but unlikely to be taller than the two parents (displaying the trait at the same extreme). See also regression toward the mean.

Estimates

Various studies have estimated the heritability of IQ to be between 0.7 and 0.8 in adults and 0.45 in childhood in the United States. It has been found that estimates of heritability increase as individuals age. Heritability estimates in infancy are as low as 0.2, around 0.4 in middle childhood, and as high as 0.8 in adulthood. The brain undergoes morphological changes in development which suggests that age-related physical changes could contribute to this effect.

A 1994 article in Behavior Genetics based on a study of Swedish monozygotic and dizygotic twins found the heritability of the sample to be as high as 0.80 in general cognitive ability; however, it also varies by trait, with 0.60 for verbal tests, 0.50 for spatial and speed-of-processing tests, and 0.40 for memory tests. In contrast, studies of other populations estimate an average heritability of 0.50 for general cognitive ability.

In 2006, David Kirp, writing in The New York Times Magazine, summarized a century's worth of research as follows, "about three-quarters of I.Q. differences between individuals are attributable to heredity."

Shared family environment

There are some family effects on the IQ of children, accounting for up to a quarter of the variance. However, adoption studies show that by adulthood adoptive siblings aren't more similar in IQ than strangers, while adult full siblings show an IQ correlation of 0.24. However, some studies of twins reared apart (e.g. Bouchard, 1990) find a significant shared environmental influence, of at least 10% going into late adulthood. Judith Rich Harris suggests that this might be due to biasing assumptions in the methodology of the classical twin and adoption studies.

There are aspects of environments that family members have in common (for example, characteristics of the home). This shared family environment accounts for 0.25-0.35 of the variation in IQ in childhood. By late adolescence it is quite low (zero in some studies). There is a similar effect for several other psychological traits. These studies have not looked into the effects of extreme environments such as in abusive families.

The American Psychological Association's report "Intelligence: Knowns and Unknowns" (1996) states that there is no doubt that normal child development requires a certain minimum level of responsible care. Severely deprived, neglectful, or abusive environments must have negative effects on a great many aspects of development, including intellectual aspects. Beyond that minimum, however, the role of family experience is in serious dispute. There is no doubt that such variables as resources of the home and parents' use of language are correlated with children's IQ scores, but such correlations may be mediated by genetic as well as (or instead of) environmental factors. But how much of that variance in IQ results from differences between families, as contrasted with the varying experiences of different children in the same family? Recent twin and adoption studies suggest that while the effect of the shared family environment is substantial in early childhood, it becomes quite small by late adolescence. These findings suggest that differences in the life styles of families whatever their importance may be for many aspects of children's lives make little long-term difference for the skills measured by intelligence tests.

Non-shared family environment and environment outside the family

Although parents treat their children differently, such differential treatment explains only a small amount of non-shared environmental influence. One suggestion is that children react differently to the same environment due to different genes. More likely influences may be the impact of peers and other experiences outside the family. For example, siblings grown up in the same household may have different friends and teachers and even contract different illnesses. This factor may be one of the reasons why IQ score correlations between siblings decreases as they get older.

Malnutrition and diseases

Certain single-gene metabolic disorders can severely affect intelligence. Phenylketonuria is an example, with publications demonstrating the capacity of phenylketonuria to produce a reduction of 10 IQ points on average. Meta-analyses have found that environmental factors, such as iodine deficiency, can result in large reductions in average IQ; iodine deficiency has been shown to produce a reduction of 12.5 IQ points on average.

Heritability and socioeconomic status

The APA report "Intelligence: Knowns and Unknowns" (1996) also stated that:

"We should note, however, that low-income and non-white families are poorly represented in existing adoption studies as well as in most twin samples. Thus it is not yet clear whether these studies apply to the population as a whole. It remains possible that, across the full range of income and ethnicity, between-family differences have more lasting consequences for psychometric intelligence."

A study (1999) by Capron and Duyme of French children adopted between the ages of four and six examined the influence of socioeconomic status (SES). The children's IQs initially averaged 77, putting them near retardation. Most were abused or neglected as infants, then shunted from one foster home or institution to the next. Nine years later after adoption, when they were on average 14 years old, they retook the IQ tests, and all of them did better. The amount they improved was directly related to the adopting family's socioeconomic status. "Children adopted by farmers and laborers had average IQ scores of 85.5; those placed with middle-class families had average scores of 92. The average IQ scores of youngsters placed in well-to-do homes climbed more than 20 points, to 98."

Stoolmiller (1999) argued that the range of environments in previous adoption studies was restricted. Adopting families tend to be more similar on, for example, socio-economic status than the general population, which suggests a possible underestimation of the role of the shared family environment in previous studies. Corrections for range restriction to adoption studies indicated that socio-economic status could account for as much as 50% of the variance in IQ.

On the other hand, the effect of this was examined by Matt McGue and colleagues (2007), who wrote that "restriction in range in parent disinhibitory psychopathology and family socio-economic status had no effect on adoptive-sibling correlations [in] IQ"

Turkheimer and colleagues (2003) argued that the proportions of IQ variance attributable to genes and environment vary with socioeconomic status. They found that in a study on seven-year-old twins, in impoverished families, 60% of the variance in early childhood IQ was accounted for by the shared family environment, and the contribution of genes is close to zero; in affluent families, the result is almost exactly the reverse.

In contrast to Turkheimer (2003), a study by Nagoshi and Johnson (2005) concluded that the heritability of IQ did not vary as a function of parental socioeconomic status in the 949 families of Caucasian and 400 families of Japanese ancestry who took part in the Hawaii Family Study of Cognition.

Asbury and colleagues (2005) studied the effect of environmental risk factors on verbal and non-verbal ability in a nationally representative sample of 4-year-old British twins. There was not any statistically significant interaction for non-verbal ability, but the heritability of verbal ability was found to be higher in low-SES and high-risk environments.

Harden, Turkheimer, and Loehlin (2007) investigated adolescents, most 17 years old, and found that, among higher income families, genetic influences accounted for approximately 55% of the variance in cognitive aptitude and shared environmental influences about 35%. Among lower income families, the proportions were in the reverse direction, 39% genetic and 45% shared environment."

In the course of a substantial review, Rushton and Jensen (2010) criticized the study of Capron and Duyme, arguing their choice of IQ test and selection of child and adolescent subjects were a poor choice because this gives a relatively less hereditable measure. The argument here rests on a strong form of Spearman's hypothesis, that the hereditability of different kinds of IQ test can vary according to how closely they correlate to the general intelligence factor (g); both the empirical data and statistical methodology bearing on this question are matters of active controversy.

A 2011 study by Tucker-Drob and colleagues reported that at age 2, genes accounted for approximately 50% of the variation in mental ability for children being raised in high socioeconomic status families, but genes accounted for negligible variation in mental ability for children being raised in low socioeconomic status families. This gene–environment interaction was not apparent at age 10 months, suggesting that the effect emerges over the course of early development.

A 2012 study based on a representative sample of twins from the United Kingdom, with longitudinal data on IQ from age two to age fourteen, did not find evidence for lower heritability in low-SES families. However, the study indicated that the effects of shared family environment on IQ were generally greater in low-SES families than in high-SES families, resulting in greater variance in IQ in low-SES families. The authors noted that previous research had produced inconsistent results on whether or not SES moderates the heritability of IQ. They suggested three explanations for the inconsistency. First, some studies may have lacked statistical power to detect interactions. Second, the age range investigated has varied between studies. Third, the effect of SES may vary in different demographics and different countries.

A 2017 King's College London study suggests that genes account for nearly 50 per cent of the differences between whether children are socially mobile or not.

Maternal (fetal) environment

A meta-analysis by Devlin and colleagues (1997) of 212 previous studies evaluated an alternative model for environmental influence and found that it fits the data better than the 'family-environments' model commonly used. The shared maternal (fetal) environment effects, often assumed to be negligible, account for 20% of covariance between twins and 5% between siblings, and the effects of genes are correspondingly reduced, with two measures of heritability being less than 50%. They argue that the shared maternal environment may explain the striking correlation between the IQs of twins, especially those of adult twins that were reared apart. IQ heritability increases during early childhood, but whether it stabilizes thereafter remains unclear. These results have two implications: a new model may be required regarding the influence of genes and environment on cognitive function; and interventions aimed at improving the prenatal environment could lead to a significant boost in the population's IQ.

Bouchard and McGue reviewed the literature in 2003, arguing that Devlin's conclusions about the magnitude of heritability is not substantially different from previous reports and that their conclusions regarding prenatal effects stands in contradiction to many previous reports. They write that:

Chipuer et al. and Loehlin conclude that the postnatal rather than the prenatal environment is most important. The Devlin et al. (1997a) conclusion that the prenatal environment contributes to twin IQ similarity is especially remarkable given the existence of an extensive empirical literature on prenatal effects. Price (1950), in a comprehensive review published over 50 years ago, argued that almost all MZ twin prenatal effects produced differences rather than similarities. As of 1950 the literature on the topic was so large that the entire bibliography was not published. It was finally published in 1978 with an additional 260 references. At that time Price reiterated his earlier conclusion (Price, 1978). Research subsequent to the 1978 review largely reinforces Price's hypothesis (Bryan, 1993; Macdonald et al., 1993; Hall and Lopez-Rangel, 1996; see also Martin et al., 1997, box 2; Machin, 1996).

Dickens and Flynn model

Dickens and Flynn (2001) argued that the "heritability" figure includes both a direct effect of the genotype on IQ and also indirect effects where the genotype changes the environment, in turn affecting IQ. That is, those with a higher IQ tend to seek out stimulating environments that further increase IQ. The direct effect can initially have been very small but feedback loops can create large differences in IQ. In their model an environmental stimulus can have a very large effect on IQ, even in adults, but this effect also decays over time unless the stimulus continues. This model could be adapted to include possible factors, like nutrition in early childhood, that may cause permanent effects.

The Flynn effect is the increase in average intelligence test scores by about 0.3% annually, resulting in the average person today scoring 15 points higher in IQ compared to the generation 50 years ago. This effect can be explained by a generally more stimulating environment for all people. The authors suggest that programs aiming to increase IQ would be most likely to produce long-term IQ gains if they taught children how to replicate outside the program the kinds of cognitively demanding experiences that produce IQ gains while they are in the program and motivate them to persist in that replication long after they have left the program. Most of the improvements have allowed for better abstract reasoning, spatial relations, and comprehension. Some scientists have suggested that such enhancements are due to better nutrition, better parenting and schooling, as well as exclusion of the least intelligent people from reproduction. However, Flynn and a group of other scientists share the viewpoint that modern life implies solving many abstract problems which leads to a rise in their IQ scores.

Influence of genes on IQ stability

Recent research has illuminated genetic factors underlying IQ stability and change. Genome-wide association studies have demonstrated that the genes involved in intelligence remain fairly stable over time. Specifically, in terms of IQ stability, "genetic factors mediated phenotypic stability throughout this entire period [age 0 to 16], whereas most age-to-age instability appeared to be due to non-shared environmental influences". These findings have been replicated extensively and observed in the United Kingdom, the United States, and the Netherlands. Additionally, researchers have shown that naturalistic changes in IQ occur in individuals at variable times.

Influence of parents genes that are not inherited

Kong reports that, "Nurture has a genetic component, i.e. alleles in the parents affect the parents' phenotypes and through that influence the outcomes of the child." These results were obtained through a meta-analysis of educational attainment and polygenic scores of non-transmitted alleles. Although the study deals with educational attainment and not IQ, these two are strongly linked.

Spatial ability component of IQ

Spatial ability has been shown to be unifactorial (a single score accounts well for all spatial abilities), and is 69% heritable in a sample of 1,367 pairs of twins from the ages 19 through 21. Further only 8% of spatial ability can be accounted for by shared environmental factors like school and family. Of the genetically determined portion of spatial ability, 24% is shared with verbal ability (general intelligence) and 43% was specific to spatial ability alone.

Molecular genetic investigations

A 2009 review article identified over 50 genetic polymorphisms that have been reported to be associated with cognitive ability in various studies, but noted that the discovery of small effect sizes and lack of replication have characterized this research so far. Another study attempted to replicate 12 reported associations between specific genetic variants and general cognitive ability in three large datasets, but found that only one of the genotypes was significantly associated with general intelligence in one of the samples, a result expected by chance alone. The authors concluded that most reported genetic associations with general intelligence are probably false positives brought about by inadequate sample sizes. Arguing that common genetic variants explain much of the variation in general intelligence, they suggested that the effects of individual variants are so small that very large samples are required to reliably detect them. Genetic diversity within individuals is heavily correlated with IQ.

A novel molecular genetic method for estimating heritability calculates the overall genetic similarity (as indexed by the cumulative effects of all genotyped single nucleotide polymorphisms) between all pairs of individuals in a sample of unrelated individuals and then correlates this genetic similarity with phenotypic similarity across all the pairs. A study using this method estimated that the lower bounds for the narrow-sense heritability of crystallized and fluid intelligence are 40% and 51%, respectively. A replication study in an independent sample confirmed these results, reporting a heritability estimate of 47%. These findings are compatible with the view that a large number of genes, each with only a small effect, contribute to differences in intelligence.

Correlations between IQ and degree of genetic relatedness

The relative influence of genetics and environment for a trait can be calculated by measuring how strongly traits covary in people of a given genetic (unrelated, siblings, fraternal twins, or identical twins) and environmental (reared in the same family or not) relationship. One method is to consider identical twins reared apart, with any similarities that exist between such twin pairs attributed to genotype. In terms of correlation statistics, this means that theoretically the correlation of tests scores between monozygotic twins would be 1.00 if genetics alone accounted for variation in IQ scores; likewise, siblings and dizygotic twins share on average half alleles and the correlation of their scores would be 0.50 if IQ were affected by genes alone (or greater if there is a positive correlation between the IQs of spouses in the parental generation). Practically, however, the upper bound of these correlations are given by the reliability of the test, which is 0.90 to 0.95 for typical IQ tests.

If there is biological inheritance of IQ, then the relatives of a person with a high IQ should exhibit a comparably high IQ with a much higher probability than the general population. In 1982, Bouchard and McGue reviewed such correlations reported in 111 original studies in the United States. The mean correlation of IQ scores between monozygotic twins was 0.86, between siblings 0.47, between half-siblings 0.31, and between cousins 0.15.

The 2006 edition of Assessing adolescent and adult intelligence by Alan S. Kaufman and Elizabeth O. Lichtenberger reports correlations of 0.86 for identical twins raised together compared to 0.76 for those raised apart and 0.47 for siblings. These numbers are not necessarily static. When comparing pre-1963 to late 1970s data, researches DeFries and Plomin found that the IQ correlation between parent and child living together fell significantly, from 0.50 to 0.35. The opposite occurred for fraternal twins.

Every one of these studies presented next contains estimates of only two of the three factors which are relevant. The three factors are G, E, and GxE. Since there is no possibility of studying equal environments in a manner comparable to using identical twins for equal genetics, the GxE factor can not be isolated. Thus the estimates are actually of G+GxE and E. Although this may seem like nonsense, it is justified by the unstated assumption that GxE=0. It is also the case that the values shown below are r correlations and not r(squared), proportions of variance. Numbers less than one are smaller when squared. The next to last number in the list below refers to less than 5% shared variance between a parent and child living apart.

Another summary:

  • Same person (tested twice over time) .85 or above
  • Identical twins—Reared together .86
  • Identical twins—Reared apart .76
  • Fraternal twins—Reared together .55
  • Fraternal twins—Reared apart .35
  • Biological siblings—Reared together .47
  • Biological siblings—Reared apart .24
  • Biological siblings—Reared together—Adults .24
  • Unrelated children—Reared together—Children .28
  • Unrelated children—Reared together—Adults .04
  • Cousins .15
  • Parent-child—Living together .42
  • Parent-child—Living apart .22
  • Adoptive parent–child—Living together .19

Between-group heritability

In the US, individuals identifying themselves as Asian generally tend to score higher on IQ tests than Caucasians, who tend to score higher than Hispanics, who tend to score higher than African Americans –– despite the fact that greater variation in IQ scores exists within each ethnic group than between them. Yet, although IQ differences between individuals have been shown to have a large hereditary component, it does not follow that between-group differences in average IQ have a genetic basis. The scientific consensus is that genetics does not explain average differences in IQ test performance between racial groups. Growing evidence indicates that environmental factors, not genetic ones, explain the racial IQ gap.

Arguments in support of a genetic explanation of racial differences in average IQ are sometimes fallacious. For instance, some hereditarians have cited as evidence the failure of known environmental factors to account for such differences, or the high heritability of intelligence within races. Jensen and Rushton, in their formulation of Spearman's Hypothesis, argued that cognitive tasks that have the highest g-load are the tasks in which the gap between black and white test takers is greatest, and that this supports their view that racial IQ gaps are in large part genetic. However, in separate reviews, Mackintosh, Nisbett et al. and Flynn have all concluded that the slight correlation between g-loading and the test score gap offers no clue to the cause of the gap. Further reviews of both adoption studies and racial admixture studies have also found no evidence for a genetic component behind group-level IQ differences. Hereditarian arguments for racial differences in IQ have been criticized from a theoretical point of view as well. For example, the geneticist and neuroscientist Kevin Mitchell has argued that "systematic genetic differences in intelligence between large, ancient populations" are "inherently and deeply implausible" because the "constant churn of genetic variation works against any long-term rise or fall in intelligence." As he argues, "To end up with systematic genetic differences in intelligence between large, ancient populations, the selective forces driving those differences would need to have been enormous. What's more, those forces would have to have acted across entire continents, with wildly different environments, and have been persistent over tens of thousands of years of tremendous cultural change."

In favor of an environmental explanation, on the other hand, numerous studies and reviews have shown promising results. Among these, some focus on the gradual closing of the black–white IQ gap over the last decades of the 20th century, as black test-takers increased their average scores relative to white test-takers. For instance, Vincent reported in 1991 that the black–white IQ gap was decreasing among children, but that it was remaining constant among adults. Similarly, a 2006 study by Dickens and Flynn estimated that the difference between mean scores of black people and white people closed by about 5 or 6 IQ points between 1972 and 2002, a reduction of about one-third. In the same period, the educational achievement disparity also diminished. Reviews by Flynn and Dickens, Mackintosh, and Nisbett et al. all accept the gradual closing of the gap as a fact. Other recent studies have focused on disparities in nutrition and prenatal care, as well as other health-related environmental disparities, and have found that these disparities may account for significant IQ gaps between population groups. Still other studies have focused on educational disparities, and have found that intensive early childhood education and test preparation can diminish or eliminate the black–white IQ test gap. In light of these and similar findings, a consensus has formed that genetics does not explain differences in average IQ test performance between racial groups.

Socioeconomic status

From Wikipedia, the free encyclopedia
 
An 1880 painting by Jean-Eugène Buland showing a stark contrast in socioeconomic status

Socioeconomic status (SES) is an economic and sociological combined total measure of a person's work experience and of an individual's or family's economic access to resources and social position in relation to others. When analyzing a family's SES, the household income, earners' education, and occupation are examined, as well as combined income, whereas for an individual's SES only their own attributes are assessed. Recently, research has revealed a lesser recognized attribute of SES as perceived financial stress, as it defines the "balance between income and necessary expenses". Perceived financial stress can be tested by deciphering whether a person at the end of each month has more than enough, just enough, or not enough money or resources. However, SES is more commonly used to depict an economic difference in society as a whole.

Socioeconomic status is typically broken into three levels (high, middle, and low) to describe the three places a family or an individual may fall into. When placing a family or individual into one of these categories, any or all of the three variables (income, education, and occupation) can be assessed.

Education in higher socioeconomic families is typically stressed as much more important, both within the household as well as the local community. In poorer areas, where food, shelter and safety are a priority, education is typically regarded as less important. Youth audiences are particularly at risk for many health and social problems in the United States, such as unwanted pregnancies, drug abuse, and obesity.

Additionally, low income and education have been shown to be strong predictors of a range of physical and mental health problems, including respiratory viruses, arthritis, coronary disease, and schizophrenia. These problems may be due to environmental conditions in their workplace, or, in the case of disabilities or mental illnesses, may be the entire cause of that person's social predicament to begin with.

Important factors

Income

Income refers to wages, salaries, profits, rents, and any flow of earnings received. Income can also come in the form of unemployment or worker's compensation, social security, pensions, interests or dividends, royalties, trusts, alimony, or other governmental, public, or family financial assistance. It can also come from monetary winnings, as from lotteries and other games or contests where money is awarded as a prize.

Income can be looked at in two terms, relative and absolute. Absolute income, as theorized by economist John Maynard Keynes, is the relationship in which as income increases, so will consumption, but not at the same rate. Relative income dictates a person's or family's savings and consumption based on the family's income in relation to others. Income is a commonly used measure of SES because it is relatively easy to figure for most individuals.

Income inequality is most commonly measured around the world by the Gini coefficient, where 0 corresponds to perfect equality and 1 means perfect inequality. Low-income families focus on meeting immediate needs and do not accumulate wealth that could be passed on to future generations, thus increasing inequality. Families with higher and expendable income can accumulate wealth and focus on meeting immediate needs while being able to consume and enjoy luxuries and weather crises.

Education

Education also plays a role in determining income. Median earnings increase with each level of education. As conveyed in the chart, the highest degrees, professional and doctoral degrees, make the highest weekly earnings while those without a high school diploma earn less. Higher levels of education are associated with better economic and psychological outcomes (i.e.: more income, more control, and greater social support and networking).

Education plays a pivotal role in skillsets for acquiring jobs, as well as specific qualities that stratify people with higher SES from lower SES. Annette Lareau speaks on the idea of concerted cultivation, where middle class parents take an active role in their children's education and development by using controlled organized activities and fostering a sense of entitlement through encouraging discussion. Laureau argues that families with lower income do not participate in this movement, causing their children to have a sense of constraint. An interesting observation that studies have noted is that parents from lower SES households are more likely to give orders to their children in their interactions while parents with a higher SES are more likely to interact and play with their children. A division in education attainment is thus born out of these two differences in child-rearing. Research has shown how children who are born in lower SES households have weaker language skills compared to children raised in higher SES households. These language skills affect their abilities to learn and thus exacerbate the problem of education disparity between low and high SES neighbourhoods. Lower-income families can have children who do not succeed to the levels of the middle-income children, who can have a greater sense of entitlement, be more argumentative, or be better prepared for adult life.

Research shows that lower SES students have lower and slower academic achievement as compared with students of higher SES. When teachers make judgments about students based on their class and SES, they are taking the first step in preventing students from having an equal opportunity for academic achievement. Educators need to help overcome the stigma of poverty. A student of low SES and low self-esteem should not be reinforced by educators. Teachers need to view students as individuals and not as a member of an SES group. Teachers looking at students in this manner will help them to not be prejudiced towards students of certain SES groups. Raising the level of instruction can help to create equality in student achievement. Teachers relating the content taught to students' prior knowledge and relating it to real-world experiences can improve achievement. Educators also need to be open and discuss class and SES differences. It is important that all are educated, understand, and be able to speak openly about SES.

Occupation

Occupational prestige, as one component of SES, encompasses both income and educational attainment. The occupational status reflects the educational attainment required to obtain the job and income levels that vary with different jobs and within ranks of occupations. Additionally, it shows achievement in skills required for the job. Occupational status measures social position by describing job characteristics, decision-making ability and control, and psychological demands on the job.

Occupations are ranked by the Census (among other organizations) and opinion polls from the general population are surveyed. Some of the most prestigious occupations are physicians and surgeons, lawyers, chemical and biomedical engineers, university professors, and communications analysts. These jobs, considered to be grouped in the high SES classification, provide more challenging work and greater control over working conditions but require more ability. The jobs with lower rankings include food preparation workers, counter attendants, bartenders and helpers, dishwashers, janitors, maids and housekeepers, vehicle cleaners, and parking lot attendants. The jobs that are less valued also offer significantly lower wages, and often are more laborious, very hazardous, and provide less autonomy.

Occupation is the most difficult factor to measure because so many exist, and there are so many competing scales. Many scales rank occupations based on the level of skill involved, from unskilled to skilled manual labour to professional, or use a combined measure using the education level needed and income involved.

In sum, the majority of researchers agree that income, education and occupation together best represent SES, while some others feel that changes in family structure should also be considered. SES affects students' cognitive abilities and academic success. Several researchers have found that SES affects students' abilities.

Other variables

Wealth


Wealth distribution in the United States by net worth (2007). The net wealth of many people in the lowest 20% is negative because of debt. By 2014 the wealth gap deepened.

  Top 1% (34.6%)
  Next 4% (27.3%)
  Next 5% (11.2%)
  Next 10% (12%)
  Upper Middle 20% (10.9%)
  Middle 20% (4%)
  Bottom 40% (0.2%)

Wealth, a set of economic reserves or assets, presents a source of security providing a measure of a household's ability to meet emergencies, absorb economic shocks, or provide the means to live comfortably. Wealth reflects intergenerational transitions as well as accumulation of income and savings.

Income, age, marital status, family size, religion, occupation, and education are all predictors of wealth attainment.

The wealth gap, like income inequality, is very large in the United States. There exists a racial wealth gap due in part to income disparities and differences in achievement resulting from institutional discrimination. According to Thomas Shapiro, differences in savings (due to different rates of incomes), inheritance factors, and discrimination in the housing market lead to the racial wealth gap. Shapiro claims that savings increase with increasing income, but African Americans cannot participate in this, because they make significantly less than Americans of European descent (whites). Additionally, rates of inheritance dramatically differ between African Americans and Americans of European descent. The amount a person inherits, either during a lifetime or after death, can create different starting points between two different individuals or families. These different starting points also factor into housing, education, and employment discrimination. A third reason Shapiro offers for the racial wealth gap are the various discriminations African Americans must face, like redlining and higher interest rates in the housing market. These types of discrimination feed into the other reasons why African Americans end up having different starting points and therefore fewer assets.

Effects

Health

Recently, there has been increasing interest from epidemiologists on the subject of economic inequality and its relation to the health of populations. Socioeconomic status has long been related to health, those higher in the social hierarchy typically enjoy better health than those below. Socioeconomic status is an important source of health inequity, as there is a very robust positive correlation between socioeconomic status and health. This correlation suggests that it is not only the poor who tend to be sick when everyone else is healthy, but that there is a continual gradient, from the top to the bottom of the socio-economic ladder, relating status to health. Parents with a low socioeconomic status cannot afford many of the health care resources which is the reason that their children may have a more advanced illness because of the lack of treatment. This phenomenon is often called the "SES Gradient" or according to the World Health Organisation the "Social Gradient". Lower socioeconomic status has been linked to chronic stress, heart disease, ulcers, type 2 diabetes, rheumatoid arthritis, certain types of cancer, and premature aging.

There is debate regarding the cause of the SES Gradient. Researchers see a definite link between economic status and mortality due to the greater economic resources of the wealthy, but they find little correlation due to social status differences.

Other researchers such as Richard G. Wilkinson, J. Lynch, and G.A. Kaplan have found that socioeconomic status strongly affects health even when controlling for economic resources and access to health care. Most famous for linking social status with health are the Whitehall studies—a series of studies conducted on civil servants in London. The studies found that although all civil servants in England have the same access to health care, there was a strong correlation between social status and health. The studies found that this relationship remained strong even when controlling for health-affecting habits such as exercise, smoking and drinking. Furthermore, it has been noted that no amount of medical attention will help decrease the likelihood of someone getting type 2 diabetes or rheumatoid arthritis—yet both are more common among populations with lower socioeconomic status.

Political participation

Political scientists have established a consistent relationship between SES and political participation. For example, in 2004, the American Political Science Task Force on Inequality and American Democracy has found that those with higher socioeconomic status participate at higher rates than those with lower status.

Psychological

Language development

Home environment

The environment of low SES children is characterized by less dialogue from parents, minimal amounts of book reading, and few instances of joint attention, the shared focus of the child and adult on the same object or event, when compared to the environment of high SES children. In contrast, infants from high SES families experience more child-directed speech. At 10 months, children of high SES hear on average 400 more words than their low SES peers.

Language ability differs sharply as a function of SES, for example, the average vocabulary size of 3-year-old children from professional families was more than twice as large as for those on welfare.

Children from lower income households had greater media access in their bedrooms but lower access to portable play equipment compared to higher income children. This eventually leads children from lower socioeconomic backgrounds to be at a disadvantage when comparing them with their counterparts in terms of access to physical activities.

Parental interactions

In addition to the amount of language input from parents, SES heavily influences the type of parenting style a family chooses to practice. These different parenting styles shape the tone and purpose of verbal interactions between parent and child. For example, parents of high SES tend toward more authoritative or permissive parenting styles. These parents pose more open-ended questions to their children to encourage the latter's speech growth. In contrast, parents of low SES tend toward more authoritarian styles of address. Their conversations with their children contain more imperatives and yes/no questions that inhibits child responses and speech development.

Parental differences in addressing children may be traced to the position of their respective groups within society. Working class individuals often hold low-power, subordinate positions in the occupational world. This standing in the social hierarchy requires a personality and interaction style that is relational and capable of adjusting to circumstances. An authoritarian style of address prepares children for these types of roles, which require a more accommodating and compliant personality. Therefore, low-SES parents see the family as more hierarchical, with the parents at the top of the power structure, which shapes verbal interaction. This power differential emulates the circumstances of the working class world, where individuals are ranked and discouraged from questioning authority.

Conversely, high-SES individuals occupy high-power positions that call for greater expressivity. High-SES parents encourage their children to question the world around them. In addition to asking their children more questions, these parents push their children to create questions of their own. In contrast with low-SES parents, these individuals often view the power disparity between parent and child as detrimental to the family. Opting instead to treat children as equals, high-SES conversations are characterized by a give and take between parent and child. These interactions help prepare these children for occupations that require greater expressivity.

Disparities in language acquisition

The linguistic environment of low and high SES children differs substantially, which affects many aspects of language and literacy development such as semantics, syntax, morphology, and phonology.

Semantics

Semantics is the study of the meaning of words and phrases. Semantics covers vocabulary, which is affected by SES. Children of high SES have larger expressive vocabularies by the age of 24 months due to more efficient processing of familiar words. By age 3, there are significant differences in the amount of dialogue and vocabulary growth between children of low and high SES. The effects of SES on vocabulary extend from childhood to adolescence and even into early adulthood according to a large socioeconomically diverse study. A lack of joint attention in children contributes to poor vocabulary growth when compared to their high SES peers. Joint attention and book reading are important factors that affect children's vocabulary growth. With joint attention, a child and adult can focus on the same object, allowing the child to map out words. For example, a child sees an animal running outside and the mom points to it and says, "Look, a dog." The child will focus its attention to where its mother is pointing and map the word dog to the pointed animal. Joint attention thus facilitates word learning for children.

Syntax

Syntax refers to the arrangement of words and phrases to form sentences. SES affects the production of sentence structures. Although 22- to 44-month-old children's production of simple sentence structures does not vary by SES, low SES does contribute to difficulty with complex sentence structures. Complex sentences include sentences that have more than one verb phrase. An example of a complex sentence is, "I want you to sit there". The emergence of simple sentence structures is seen as a structure that is obligatory in everyday speech. Complex sentence structures are optional and can only be mastered if the environment fosters its development.

This lag in the sentence formation abilities of low SES children may be caused by less frequent exposure to complex syntax through parental speech. Low SES parents ask fewer response-coaxing questions of their children which limits the opportunities of these children to practice more complex speech patterns. Instead, these parents give their children more direct orders, which has been found to negatively influence the acquisition of more difficult noun and verb phrases. In contrast, high SES households ask their children broad questions to cultivate speech development. Exposure to more questions positively contributes to children's vocabulary growth and complex noun phrase constructions.

Morphology

Children's grasp of morphology, the study of how words are formed, is affected by SES. Children of high SES have advantages in applying grammatical rules, such as the pluralization of nouns and adjectives compared to children of low SES. Pluralizing nouns consists of understanding that some nouns are regular and -s denotes more than one, but also understanding how to apply different rules to irregular nouns. Learning and understanding how to use plural rules is an important tool in conversation and writing. In order to communicate successfully that there is more than one dog running down the street, an -s must be added to dog. Research also finds that the gap in ability to pluralize nouns and adjectives does not diminish by age or schooling because low SES children's reaction times to pluralize nouns and adjectives do not decrease.

Phonology

Phonological awareness, the ability to recognize that words are made up of different sound units, is also affected by SES. Children of low SES between the second and sixth grades are found to have low phonological awareness. The gap in phonological awareness increases by grade level. This gap is even more problematic if children of low SES are already born with low levels of phonological awareness and their environment does not foster its growth. Children who have high phonological awareness from an early age are not affected by SES.

Positive outcomes of low SES

Given the large amount of research on the setbacks children of low SES face, there is a push by child developmental researchers to steer research to a more positive direction regarding low SES. The goal is to highlight the strengths and assets low income families possess in raising children. For example, African American preschoolers of low SES exhibit strengths in oral narrative, or storytelling, that may promote later success in reading. These children have better narrative comprehension when compared to peers of higher SES. Since 2012, there has also been some research on the Shift-and-persist model, which attempts to account for the counterintuitive positive health outcomes that can occur in individuals who grow up in low SES families.

Literacy development

A gap in reading growth exists between low SES and high SES children, which widens as children move on to higher grades. Reading assessments that test reading growth include measures on basic reading skills (i.e., print familiarity, letter recognition, beginning and ending sounds, rhyming sounds, word recognition), vocabulary (receptive vocabulary), and reading comprehension skills (i.e., listening comprehension, words in context). The reading growth gap is apparent between the spring of kindergarten and the spring of first-grade, the time when children rely more on the school for reading growth and less on their parents. Initially, high SES children begin as better readers than their low SES counterparts. As children get older, high SES children progress more rapidly in reading growth rates than low SES children. These early reading outcomes affect later academic success. The further children fall behind, the more difficult it is to catch up and the more likely they will continue to fall behind. By the time students enter high school in the United States, low SES children are considerably behind their high SES peers in reading growth.

Home environment

Home environment is one of the leading factors of a child's well-being. Children living in a poor home with inadequate living conditions are more likely to be susceptible to illness and injuries. The disparities in experiences in the home environment between children of high and low SES affect reading outcomes. The home environment is considered the main contributor to SES reading outcomes. Children of low SES status are read to less often and have fewer books in the home than their high SES peers, which suggests an answer to why children of low SES status have lower initial reading scores than their high SES counterparts upon entering kindergarten. Low SES parents are also less involved in their children's schooling. The fact that many students go to school outside of their home to learn does not mean that it is the only determinant of their literacy growth. Parenting at home plays a role in shaping emotional, physical and mental health, all things that are extremely important to educational success in the classroom. This is a crucial factor that must be acknowledged by educators because boundaries such as constant parenting stress and approach to learning, for example, have a major impact on the students' literacy development.

The home environment makes the largest contribution to the prediction of initial kindergarten reading disparities. Characteristics of the home environment include home literacy environment and parental involvement in school. Home literacy environment is characterized by the frequency with which parents engage in joint book reading with the child, the frequency with which children read books outside of school, and the frequency with which household members visited the library with the child. Parental involvement in school is characterized by attending a parent–teacher conference, attending a parent–teacher association (PTA) meeting, attending an open house, volunteering, participating in fundraising, and attending a school event. Resources, experiences, and relationships associated with the family are most closely associated with reading gaps when students' reading levels are first assessed in kindergarten. The influence of family factors on initial reading level may be due to children experiencing little schooling before kindergarten—they mainly have their families to rely on for their reading growth.

Socioeconomic status plays a role in the involvement of certain parents over others. It affects parenting practices and as a result proves to be a strong predictor of child achievement when comparing households. A parent’s involvement in their child's reading literacy performance progress is often overcome by demographic factors such as poverty, racial and ethnic identity, family and parenting stress, and the parent's educational level. Studies show that when parents become involved in reading-related activities with their children outside of school, reading performance, literacy, love for reading and language skills are more likely to improve. Parent involvement in students’ education is a large factor in their literacy achievement, but the way they parent has a large impact on the overall development of the child. These kinds of involvements are often determined by privilege and the level of stress that a parent must endure, especially when of low socioeconomic status. The reading literacy gap has been further exposed by the enhancement of these already existing inequalities. Studies have found a direct link between Family Processes (including parenting stress and discipline practices), Social-Emotional Readiness (including approaches to learning and self control), and Reading Literacy. Although seeming unrelated, the way that a parent interacts with their child and their child's learning at home sets the stage for how well they will be able to improve their reading literacy in school.

The disadvantages of the achievement gap have exposed itself further for students and children as students have been forced to practice remote learning of the 2020 pandemic. Limited access to the correct school resources affects a child's literacy level dramatically, even more so during the switch to online learning, given the combination of decreased parent involvement and access to outdoor play. Low to lower-middle class households had the highest rate of employment change during the pandemic, which includes loss of employment, reduced hours and/or reduced pay. Large historical events like this one have only extenuated and exposed already existing inequities and in turn have negatively affected students of these demographics. The US Department of Labor revealed that layoffs that occurred during the COVID 19 pandemic had the biggest impact on historically minorities groups, which include Black, Latino, low income workers, and women. This means that children of these same working adults experienced disparities as well. In a 2013 report by the US Department of Commerce, it was found that only 55% of African American and 58% of rural households had any internet access in their home. This can be compared to the 74% of white and 81% of Asian American homes that had reliable internet. Comparing this 2013 report to the occurrences existing in 2020 are not very different given that the demographic students still experience this "digital gap" and disproportionate lack in access to the internet and/or technological equipment necessary. Without access to the correct materials at home, including books and digital tools, students cannot perform as well in reading literacy as their more privileged classmates.

Family SES is also associated with reading achievement growth during the summer. Students from high SES families continue to grow in their ability to read after kindergarten and students from low SES families fall behind in their reading growth at a comparable amount. Additionally, the summer setback disproportionately affects African American and Hispanic students because they are more likely than White students to come from low SES families. Also, low SES families typically lack the appropriate resources to continue reading growth when school is not in session. After the long summer break, it is found that the reading literacy gap between middle and lower class students is about 3 months long. This is a substantial amount of skills lost over a period of break from classes that, if not addressed, can grow extremely worse over time. It is especially important to address this issue and create solutions for young students of low SES in order to address the cycle of disadvantages faced by these communities. Studies show that by providing books to disadvantaged students over the summer, the reading achievement dramatically improves for elementary school students. Specifically, providing access to self-selected books consistently over the months of summers is successful in limiting reading setbacks. Many of these students continue to feel discouraged, have less motivation and therefore fall more behind. By providing encouragement through opportunity, there is more chance of future success in literacy development.

Neighborhood influence

The neighborhood setting in which children grow up contributes to reading disparities between low and high SES children. These neighborhood qualities include but are not limited to garbage or litter in the street, individuals selling or using drugs in the street, burglary or robbery in the area, violent crime in the area, vacant homes in the area, and how safe it is to play in the neighborhood. Low SES children are more likely to grow up in such neighborhood conditions than their high SES peers. Community support for the school and poor physical conditions surrounding the school are also associated with children's reading. Neighborhood factors help explain the variation in reading scores in school entry, and especially as children move on to higher grades. As low SES children in poor neighborhood environments get older, they fall further behind their high SES peers in reading growth and thus have a more difficult time developing reading skills at grade level.

In a study by M. Keels, it was determined that when low-income families are moved from poor neighborhoods to suburban neighborhoods, there are reductions in delinquency in children. When comparing different social statuses of families, the environment of a neighborhood turns out to be a major factor in contributing to the growth of a child.

School influence

School characteristics, including characteristics of peers and teachers, contribute to reading disparities between low and high SES children. For instance, peers play a role in influencing early reading proficiency. In low SES schools, there are higher concentrations of less skilled, lower SES, and minority peers who have lower gains in reading. The number of children reading below grade and the presence of low-income peers were consistently associated with initial achievement and growth rates. Low SES peers tend to have limited skills and fewer economic resources than high SES children, which makes it difficult for children to grow in their reading ability. The most rapid growth of reading ability happens between the spring of kindergarten and the spring of first grade. Teacher experience (number of years teaching at a particular school and the number of years teaching a particular grade level), teacher preparation to teach (based on the number of courses taken on early education, elementary education, and child development), the highest degree earned, and the number of courses taken on teaching reading all determine whether or not a reading teacher is qualified. Low SES students are more likely to have less qualified teachers, which is associated with their reading growth rates being significantly lower than the growth rates of their high SES counterparts.

Influences on nonverbal behavior

Children of parents with a high SES tended to express more disengagement behaviors than their peers of low SES. This study by Michael Kraus and Dacher Keltner was published in the December 2008 issue of Psychological Science. In this context, disengagement behaviors included self-grooming, fidgeting with nearby objects, and doodling while being addressed. In contrast, engagement behaviors included head nods, eyebrow raises, laughter and gazes at one's partner. These cues indicated an interest in one's partner and the desire to deepen and enhance the relationship. Participants of low SES tended to express more engagement behaviors toward their conversational partners, while their high SES counterparts displayed more disengagement behaviors. Authors hypothesized that, as SES rises, the capacity to fulfill one's needs also increases. This may lead to greater feelings of independence, making individuals of high SES less inclined to gain rapport with conversational partners because they are less likely to need their assistance in the future.

Inequality (mathematics)

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