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Tuesday, June 18, 2019

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 changes across time and space and that 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. Some individuals in certain racial groups receive less care, have less access to resources, and live shorter lives in general. Epidemiological data indicates that racial groups are unequally affected by diseases, in terms or morbidity and mortality. These health differences between racial groups create racial health disparities.

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”. Health disparities are intrinsically related to the “historical and current unequal distribution of social, political, economic and environmental resources".

Social, political, economic, environmental, cultural and biological factors constitute determinants of health. The relation between race and health has been studied from a multidisciplinary perspective, paying attention to how racism influence health disparities and how environmental factors and physiological factors respond to each other 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.

How researchers view race is often linked to how we address racial disparities because the national administrator of health uses these research findings to implement policies.

Difference between health inequity and health disparities

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.

Biological definitions of race encompass essentialist and anti-essentialist views. The scientific community does not universally accept a single definition of race. Essentialism is a mode of thought that uses scientific data to argue that racial groups are genetically distinct populations. Essentialists describe "races as groups of people who share certain innate, inherited biological traits, a.k.a. use of biological evidence to demonstrate racial differences". As its counterpart, anti-essentialism uses biological evidence to demonstrate that "race groupings do not reflect patterns of human biological variation, countering essentialist claims to the contrary". It should be noted that despite Essentialism and anti-Essentialism views, modern scientific evidence suggests there are more genetic differences within individuals belonging to the same racial groups, than between individuals belonging to different racial groups.

In the last 20 years there has been major criticisms on the once widely held view that race is biological. In response to these criticisms, 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 very real and plays a role in our society; 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 preventative 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 single gene genetic disorders that differ in frequency between different populations due to the region and ancestry. While some assume this diseases to be solely based on race, other authors point out that race is not a useful markers as self-reported ancestry and racial identity or classification does not determine the genome of individuals. Some examples of single-gene disorders include:
  • Cystic fibrosis, the most common life-limiting autosomal recessive disease among people of Northern European heritage
  • Sickle-cell anemia, most prevalent in populations with sub-Saharan African ancestry but also common among Latin-American, Middle Eastern populations, as well as those people of South European regions such as Turkey, Greece, and Italy
  • Thalassemia, most prevalent in populations having Mediterranean ancestry, to the point that the disease's name is derived from Greek thalasson, "sea"
  • Tay–Sachs disease, an autosomal recessive disorder more frequent among Ashkenazi Jews than among other Jewish groups and non-Jewish populations
  • Hereditary hemochromatosis, most common among persons having Northern European ancestry, in particular those people of Celtic descent
  • Lactose intolerance affects (over their lifetime) as many as 25% of Europeans but up to 50-80% of Hispanics, along with Ashkenazi Jews, but nearly 100% of Native Americans.

Multifactorial polygenic diseases

Many diseases differ in frequency between different populations. However, complex diseases are affected by multiple factors, both 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 persons 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, cultural and linguistic 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 socio economic 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 a trait, 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 or "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

Malaria-endemic countries eastern hemisphere
 
Malaria-endemic countries 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. A number of genetic diseases more prevalent in malaria-afflicted 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 enough 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 together 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: income and social status, education, physical environment, social support networks, genetics, health services 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. Research in this area is new and ongoing.

Inequality in disease

From Wikipedia, the free encyclopedia

Social epidemiology focuses on the patterns in morbidity and mortality rates that emerge as a result of social characteristics. While an individual's lifestyle choices or family history may place him or her at an increased risk for developing certain illnesses, there are social inequalities in health that cannot be explained by individual factors. Variations in health outcomes in the United States are attributed to several social characteristics, such as gender, race, socioeconomic status, the environment, and educational attainment. Inequalities in any or all of these social categories can contribute to health disparities, with some groups placed at an increased risk for acquiring chronic diseases than others.

For example, cardiovascular disease is the leading cause of death in the United States, followed closely by cancer, with the fifth most deadly being diabetes. The general risk factors associated with these diseases include obesity and poor diet, tobacco and alcohol use, physical inactivity, and access to medical care and health information. Although it may seem that many these risk factors arise solely from individual health choices, such a view neglects the structural patterns in the choices that individuals make. Consequently, a person's likelihood for developing heart disease, cancer, or diabetes is in part correlated with social factors. Among all racial groups, individuals who are impoverished or low income, have lower levels of educational attainment, and/or live in lower-income neighborhoods are all more likely to develop chronic diseases, such as heart disease, cancer, and diabetes.

Gender

In the United States and Europe, up until the 19th century, women tended to die at an earlier age than men. This was largely due to the risks involved in pregnancy and childbirth. However, in the late 19th century there was a shift in life expectancy and women started to live longer than men. Notably, this is partly explained by biological factors. For instance, there is a cross-cultural trend that male fetal mortality rates are higher than female fetal mortality rates. Additionally, estrogen decreases the risk of females acquiring heart disease by lowering the amount of cholesterol in the blood, while testosterone suppresses the immune system in males and puts them at risk for acquiring serious illnesses. However, biological differences do not fully account for the large gender gap in the health outcomes of men and women. Social factors play a large role in gender disparities in health.

One of the main factors that contributes to the decreased life expectancy of males is their propensity to engage in risk-taking behaviors. Some commonly cited examples include heavy drinking, illicit drug use, violence, drunk driving, not wearing helmets, and smoking. These behaviors contribute to injuries that may lead to premature death in males. In particular, the effect of risk-taking behavior on health is especially visible in the case of smoking. As smoking rates have fallen in the United States overall, less men engage in this behavior and the life expectancy gap between men and women has slightly decreased as a result.

The behaviors of men and women also vary in regards to diet and exercise, leading to differential health outcomes . On average, men exercise more than women, but their diet is less nutritious. Consequently, men are more likely to be overweight, while women are at greater risk for obesity. Exposure to violence is another social factor that has an influence on health. In general, women have a higher likelihood of experiencing sexual and intimate partner violence, while men are twice as likely to die from suicide or homicide.

Markedly, the impact of gender on health becomes especially salient in different socioeconomic contexts. In the United States, there is a large economic gender inequality with many economically disadvantaged women occupying much fewer positions of power than men. According to the Panel Study of Income Dynamics, "among adults with the strongest attachment to the labor force, only 9.6% of women earned more than $50,000 annually, compared with 44.5% of men." This gendered economic inequality is partly responsible for the gender-health paradox: the general trend that women live longer than men, but experience a greater degree of non-life-threatening chronic illnesses over the course of a lifetime. A low socioeconomic status in women contributes to feelings of a lack of personal control over the events in their lives, increased stress, and low self-esteem. Perpetual states of stress inflict damage on the bodies and minds of women, placing them at risk for physical ailments, such as heart disease and arthritis, as well mental health disorders, such as depression.

Another significant social factor is that men and women deal with their illnesses in different ways. Women generally have strong support networks and are able to rely on others for emotional support, with the potential to improve their states of health. In contrast, men are less likely to have strong support networks, they have fewer doctor visits, and often cope with their illnesses on their own. Also, men and women express pain in different ways. Researchers have observed that women openly express feelings of pain, while men are more reserved in this regard and prefer to appear tough even when they experience severe mental or physical suffering. This finding suggests that this is due to socialization processes. Women are taught to be submissive and emotional, while men are taught to be strong, powerful figures that do not show their emotions. The social stigma associated with expressions of pain prevents men from admitting their suffering to others, making it more difficult to overcome the pain.

Moreover, neighborhood effects have a greater influence on women than men. For instance, research findings suggest that women living in impoverished neighborhoods are more likely to experience obesity, while this effect is not as strong for men. The physical environment also generally impacts a woman's self-rated health. This effect can be explained by the fact that women spend more time at home than their male counterparts, as a result of higher unemployment rates, and therefore may be more exposed to negative environmental characteristics that take a toll on their health.

Finally, gender effects also vary with race, ethnicity, and nativity status. Notably, Christy Erving conducted a study in which she examined the gender differences in the health profiles of African Americans and Caribbean blacks (immigrants and U.S. born). One of the findings from this research is that on average, African American women report lower self-rated measures of health, worse physical health, and were more likely to experience severe chronic illnesses than men. This finding contradicts the gender-health paradox in the sense that researchers would expect morbidity rates to be higher for women, but less of the illnesses that they acquire should be debilitating. In contrast, the opposite trend is observed for U.S. born Caribbean blacks, with men more likely to experience chronic, life-threatening illnesses than women. The health outcomes of Caribbean black immigrants are somewhere in-between the health outcomes of U.S. born Caribbean blacks and African Americans, wherein the females have a lower value of self-reported health but experience equal rates of life-threatening, chronic disease as men. This data illustrates that even within one racial category, there can be stark gender differences in health on the basis of social differences within the groups that compose the race.

Race

Studies have shown that individuals that are racially and ethnically stigmatized, not just in the U.S., but globally as well, experience health issues such as mental and physical illness, and in some cases even death, in higher rates than the average individual. There has been some controversy around "race" being a determinant of disease and health issues, since there are unmeasured forms of background history that are potential factors in this research. Geographical origins and the types of environments individual races were exposed to are huge contributes to the health of a certain race, especially when the environment that they are in now is not the same as the one their race originates from geographically. 

Along with these factors, physical, psychological, social, and chemical environments are all included and accounted for. Including exposure over the course of one's life and through generations,and biological adaptation to these environmental exposures, including gene expression. An example of this is a study of hypertension between black people and whites. West Africans and people of West African descent levels of hypertension increased when they moved from Africa to the United States. Their levels of hypertension were twice as high as the levels of black people that were in Africa. While whites in the United States even had higher rates of hypertension than Black people in Africa, the black people in the United States rates of hypertension were higher than some predominately white populations in Europe. Again, this proves that when a race is taken out of their original geographic environment, they are more prone to disease and illness, because their genetic make-up was made for a specific type of environment. 

Transitioning from the environmental aspect of race and disease, there is a direct correlation between race and socioeconomic status which contributes to racial disparities in health. When it comes to death rates from heart disease, the rate is about twice as high for black men vs. white men. Now, death rates from heart disease are lower for both black and white women compared to their male counterparts, but the patterns of racial disparities and education disparities for women are similar to that of the men. Death from heart disease is about three times as higher for black women than white women. For both black men and women, racial differences in deaths from heart disease at every level of education is evident, with the racial gap being larger at the higher levels of education than at the lowest levels. There are a number of reasons why race matters in terms of health after socioeconomic status has been accounted for. For one, health is affected by adversity early on in one's life, such as traumatic stress, poverty, and abuse. These factors affect the physical and mental health of an individual. As we know, most of the people living in poverty in the United States are minorities, specifically African Americans, so unfortunately there is no surprise that they are the individuals with so many health issues.

Continuously, race is relevant to health issues, because of the non-equivalence of socioeconomic status indicators across racial groups. At the same level of education, minorities (black people and non-white Hispanic people) receive less income than their Anglo-white counterparts, as well as have less wealth and purchasing power. Namely, one of the biggest reasons that race matters in terms of health is due to racism. Both personal and institutionalized racism are very prominent in today's society, maybe not as blunt and easy to notice in comparison to the past, but it still exists. Certain residential segregation by race, such as redlining, has created very distinct racial differences in terms of education, employment, and opportunities. Opportunities such as access to good healthcare/medical care. Institutional and cultural racism can even harm minorities health through stereotypes and prejudices, which contributes to socioeconomic mobility and can reduce and limit resources and opportunities required for a healthy lifestyle.

Socioeconomic status is only one part of racial disparities in health that reflect larger social inequalities in society. Racism is a system that combines with, and sometimes changes, socioeconomic status to influence health, and race still matters for health when socioeconomic status is considered.

Socioeconomic status

Socioeconomic status is a multidimensional classification, often defined using an individual's income and level of education. Other related metrics can round out this definition; for example, in a 2006 study by authors Cox, McKevitt, Rudd and Wolfe, further categories included "occupation, home and goods ownership, and area-based deprivation indices" in their determination of status.

Income inequality has risen rapidly in the United States, pushing greater amounts of the population into positions of lower socioeconomic status. A study published in 1993 examined Americans who had passed away between May and August 1960, and paired the mortality information with income, education and occupation data for each person. The work found an inverse correlation between socioeconomic status and mortality rate, as well as an increasing strength of this pattern and its reflection of the growth of income inequality in the United States.

These findings, although concerned with total mortality of any cause, reflect a similar relationship between socioeconomic status and disease incidence or death in the United States. Disease composes a very significant portion of U.S. mortality; as of May 2017, 6 out of 7 of the leading causes of death in America are non-communicable diseases, including heart disease, cancer, lower respiratory diseases, and cerebrovascular diseases (stroke). Indeed, these diseases have been seen to disproportionately affect the socioeconomically disadvantaged, albeit to different degrees and with differing magnitude. Mortality rates associated with cardiovascular disease (CVD), including coronary heart disease (CHD) and stroke, were assessed for individuals across areas of differing income and income inequality. The authors found that the mortality rates for each of the three respective diseases were greater by a factor of 1.36, 1.26, and 1.60, in areas of higher inequality compared to lower inequality areas of similar income. Across areas of differing income and constant income inequality, the rate of death due to CVD, CHD and stroke was increased by a factor of 1.27, 1.15, and 1.33 in the lower income areas. These trends across two measures of variation in socioeconomic status reflect the complexity and depth of the relationship between disease and economic standing. The authors are careful to state that while these patterns exist, they are not sufficiently described as related by cause and effect. While correlating, health and status have arisen in the U.S. from interrelated forces that may intricately accumulate or negate one another due to specific historical contexts.

As this lack of cause and effect simplicity indicates, exactly where disease-related health inequality arises is murky, and multiple factors likely contribute. Important to an examination of disease and health in the context of a complicated classification like socioeconomic status is the degree to which these measures are tied up with mechanisms that are dependent upon the individual, and those that are regionally variant. In the aforementioned 2006 study, the authors define individualized factors within three categories, "material (eg, income, possessions, environment), behavioural (eg, diet, smoking, exercise) and psychosocial (eg, perceived inequality, stress)", and provide two categories for external, regionally varying factors, "environmental influences (such as provision of and access to services) and psychosocial influences (such as social support)." The interactive and compounding nature of these forces can shape and be shaped by socioeconomic status, presenting a challenge to researchers to tease apart the intersecting factors of health and status. In the 2006 study, authors examined the specific drivers of the correlation between stroke occurrence and socioeconomic status. Identifying more nuanced and interlocking factors, they cited risk behaviors, early life influences, and access to care as tied to socioeconomic status and thus health inequality.

Inequality in disease is intricately tangled up with stratification of social class and economic status in the United States. Correlations, often disease-dependent, between health and socioeconomic attainment have been demonstrated in numerous studies for numerous diseases. The causes of these correlations are interlocking and often related to factors varying between regions and individuals, and design of future studies concerning inequality in disease require careful thought to the multifaceted driving mechanisms of social inequality.

Environment

The neighborhoods and areas people live in, as well as their occupation, make up the environment in which they exist. People living in poverty stricken neighborhoods are at a greater risk for heart disease, possibly because the supermarkets in their area do not sell healthy foods and there is increased availability of stores selling alcohol and tobacco than in more affluent parts of town. People living in rural areas are also more susceptible to heart disease, as well. An agriculturally based diet rich in fat and cholesterol, combined with an isolated environment in which there is limited access to health care and ways to distribute information probably creates a pattern in which people living in rural environments have higher levels of heart disease. Occupational cancer is one way in which the environment one works in can increase their rate of disease. Employees exposed to smoke, asbestos, diesel fumes, paint, and chemicals in factories can develop cancer from their workplace. All of these jobs tend to be low-paying and typically held by low income individuals. The decreased amount of healthy food in stores located in low-income areas also contributes to the increased rates of diabetes for persons living in those neighborhoods. One of the best examples of this can be seen by observing the city of Jacksonville, Florida.

Food deserts in urban Jacksonville

In Jacksonville, Florida it is hard to find groceries stores around the area because it is surrounded by fats, sugar, and high in cholesterol markets. In Duval County, there are 177,000 food insecure individuals such as children, families,senior citizens, and veterans that do not know when they will have a chance to have another meal again. Nearly 60 percent of the food that is consumed in Duval County is processed. To combat this, agencies helped distribute food and they averaged 12.3 million meals over eight counties in Northern Florida. In Duval alone, 3.5 million meals were handed out to families. The image below shows all of the hunger-relief partner agencies located within Jacksonville's food deserts that get food from Feeding Northeast Florida. In all Feeding Northeast Florida provided 4.2 million pounds of food to agencies in food deserts. These numbers were stats recorded in 2016.

Water pollution

Just like Flint Jacksonville had a water crisis and found 23 different chemicals in their water supply. It was so bad that Jacksonville was labeled top 10 in worst water in the nation. They stood at number 10 because of the 23 different chemicals. The chemicals that were most found in the water in high volumes were trihalomethanes, which is made up of four different cleaning by products such as chloroform. Trihalomethanes are confirmed to be carcinogenic. Throughout the five year testing period, unsafe levels of trihalomethanes were found during the 32 months of testing, and levels that are considered illegal by the EPA were found in 12 of those months. In one of the testing periods the trihalomethanes were found at twice the EPA legal limit. Other chemicals such as lead and arsenic that can cause health problems to people, were also found in the drinking water.

Another way that water pollution is damaged is from nutrient overload. Nutrient overload is caused by manure and fertilizers, storm water runoff, and wastewater treatment plants. This occurs in a lot of Florida rivers and the rivers are contained with blue green algae that feed on all those nutrients. All the waste that is dumped into the rivers gets fed on by other plants and animals that release toxins in the area, which makes everything surrounded by it a deadly toxin as well. The toxins that are dumped into the rivers can cause discoloration in the rivers to make a dark blue and green color. By looking at the river most people can tell how dangerous and harmful it is to be around it. If the water were to somehow get into water companies people can receive serious harm from drinking and bathing with this water.

Education

Education level is a great predictor of socioeconomic status. On average, individuals with a bachelors, associates, and high school degrees will annually earn 64.5, 50, and 41 thousand dollars respectively. This means that the average bachelor's degree earner will receive approximately $1,000,000 more over their working life than an individual with only a high school degree. Furthermore, as authors Montez, Hummer, and Hayward explained, "In 2012, unemployment was 12.4 percent among adults who did not graduate high school, compared to 8.3 percent among adults with a high school diploma and 4.5 percent among college graduates." Because the relationship between socioeconomic status and the prevalence of disease has already been well established, education is indirectly responsible for an increased prevalence of disease among the impoverished. 

More directly, educational attainment is a great predictor of how likely an individual is to engage in risky, possibly disease causing, behaviors. In terms of smoking, which directly correlates to an increased risk for diseases like lung cancer, education is an important determining factor in the likelihood of an individual to smoke. As of 2009-10, 35 percent of adults who did not graduate high school were smokers, compared to 30 percent of high school graduates and just 13 percent of college graduates. High school graduates also smoked more packs, on average, each year than smokers who had graduated from college. Furthermore, individuals with a high school degree or less were 30% less likely to abstain from smoking for at least 3 months during their time as a regular smoker. Other studies have found that binge drinking is higher among those with college degrees, implying that binge drinking is a habitat developed by many during the college years.

Unhealthy dietary habits can also directly lead to diseases such as heart disease, hypertension, and type-2 diabetes. One of the leading causes of unhealthy eating habits is a lack of access to grocery stores, creating so called "food deserts." Studies have found that immediate access to a grocery store (within 1.5 mile radius) was 1.4 times less likely in areas where only 27%, or less, of the population was college graduates. The negative effects of these food deserts are exacerbated by the fact that impoverished neighborhoods also had an oversupply of liquor store, fast food restaurants, and convenience stores.

One significant risk for sexually active individuals is that of sexually transmitted diseases and infections. While studies have found that the correlation between education and carrying these is relatively low on average (and even less so for certain subsets such as Black women), there is a strong correlation between education and other risky sexual behaviors. Those with only a high school degree or less were significantly more likely to engage in risky practices such as early sexual initiation, sexual activity with those who use "shooting" street drugs such as heroin, and even prostitution. In addition, those with less education were also less likely to practice some safe sex practices such as condom use.

Studies have also found that adults with higher educational achievement were more likely to lead healthier lives. Intake of key nutrients such as Vitamins A and C, potassium, and calcium was positively correlated with education level. This is a critical statistic because those nutrients, such as Vitamin C, are critical in helping the body fight diseases and infections. There was also a correlation between education and exercise habits. A 2010 study found that while 85% of college graduates stated they exercised in the last month, only 68% of high school graduates and 61% of non-high school graduates said the same. Because exercise is so crucial to preventing diseases like hypertension and type 2 diabetes, this stark distinction between exercise habitats can have significant effects. By 2011, 15% of high school (or less) graduates had diabetes, compared to just 7% of college graduates.

Arguably the best way of seeing the true effects of education in the inequality of disease is to examine mortality levels, as Heart Disease, Cancer, and Lower Respiratory Diseases are the top three killers, respectively, of Americans every year. By age 25, if an individual does not have at least a high school degree, they will die an average of 9 years earlier than an otherwise similar college graduate. A different national study found that individuals with only bachelor's degrees were 26% more likely to die in the next 5 years than individuals of the same age with professional degrees such as a master's. Even more stark, Americans without a high school degree were almost twice as likely to die than those with a professional degree in the study's 5 year follow-up period.

Population health

From Wikipedia, the free encyclopedia

Income inequality and mortality in 282 metropolitan areas of the United States. Mortality is correlated with both income and inequality.
 
Population health has been defined as "the health outcomes of a group of individuals, including the distribution of such outcomes within the group". According to Akarowhe (2018), the working definition of population health is expressed thus; population health is an art, process, science and a product of enhancing the health condition of a specific number of people within a given geographical area - population health as an art, simply means that it is geared towards equal health care delivery to an anticipated group of people in a particular geographical location; as a science, it implies that it adopt scientific approach of preventive, therapeutic, and diagnostic service in proffering medical treatment to the health problem of people; as a product, it means that population health is directed toward overall health performance of people through health satisfaction within the said geographical area; and as a process it entails effective and efficient running of a health management/population health management system to cater for the health needs of the people. It is an approach to health that aims to improve the health of an entire human population. This concept does not refer to animal or plant populations. It has been described as consisting of three components. These are "health outcomes, patterns of health determinants, and policies and interventions". A priority considered important in achieving the aim of Population Health is to reduce health inequities or disparities among different population groups due to, among other factors, the social determinants of health, SDOH. The SDOH include all the factors (social, environmental, cultural and physical) that the different populations are born into, grow up and function with throughout their lifetimes which potentially have a measurable impact on the health of human populations. The Population Health concept represents a change in the focus from the individual-level, characteristic of most mainstream medicine. It also seeks to complement the classic efforts of public health agencies by addressing a broader range of factors shown to impact the health of different populations. The World Health Organization's Commission on Social Determinants of Health, reported in 2008, that the SDOH factors were responsible for the bulk of diseases and injuries and these were the major causes of health inequities in all countries. In the US, SDOH were estimated to account for 70% of avoidable mortality.

From a population health perspective, health has been defined not simply as a state free from disease but as "the capacity of people to adapt to, respond to, or control life's challenges and changes". The World Health Organization (WHO) defined health in its broader sense in 1946 as "a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity."

Healthy People 2020

Healthy People 2020 is a web site sponsored by the US Department of Health and Human Services, representing the cumulative effort of 34 years of interest by the Surgeon General's office and others. It identifies 42 topics considered social determinants of health and approximately 1200 specific goals considered to improve population health. It provides links to the current research available for selected topics and identifies and supports the need for community involvement considered essential to address these problems realistically.

The human role of economic inequality

Recently, human role has been encouraged by the influence of population growth there has been increasing interest from epidemiologists on the subject of economic inequality and its relation to the health of populations. There is a very robust 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, heart disease, ulcers, type 2 diabetes, rheumatoid arthritis, certain types of cancer, and premature aging. Despite the reality of the SES Gradient, there is debate as to its cause. A number of researchers (A. Leigh, C. Jencks, A. Clarkwest—see also Russell Sage working papers) see a definite link between economic status and mortality due to the greater economic resources of the better-off, 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, despite the fact that 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 stayed 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 1 diabetes or rheumatoid arthritis—yet both are more common among populations with lower socioeconomic status. Lastly, it has been found that amongst the wealthiest quarter of countries on earth (a set stretching from Luxembourg to Slovakia) there is no relation between a country's wealth and general population health—suggesting that past a certain level, absolute levels of wealth have little impact on population health, but relative levels within a country do. The concept of psychosocial stress attempts to explain how psychosocial phenomenon such as status and social stratification can lead to the many diseases associated with the SES gradient. Higher levels of economic inequality tend to intensify social hierarchies and generally degrades the quality of social relations—leading to greater levels of stress and stress related diseases. Richard Wilkinson found this to be true not only for the poorest members of society, but also for the wealthiest. Economic inequality is bad for everyone's health. Inequality does not only affect the health of human populations. David H. Abbott at the Wisconsin National Primate Research Center found that among many primate species, less egalitarian social structures correlated with higher levels of stress hormones among socially subordinate individuals. Research by Robert Sapolsky of Stanford University provides similar findings.

Research

There is well-documented variation in health outcomes and health care utilization & costs by geographic variation in the U.S., down to the level of Hospital Referral Regions (defined as a regional health care market, which may cross state boundaries, of which there are 306 in the U.S.). There is ongoing debate as to the relative contributions of race, gender, poverty, education level and place to these variations. The Office of Epidemiology of the Maternal and Child Health Bureau recommends using an analytic approach (Fixed Effects or hybrid Fixed Effects) to research on health disparities to reduce the confounding effects of neighborhood (geographic) variables on the outcomes.

The importance of family planning programs

Family planning programs (including contraceptives, sexuality education, and promotion of safe sex) play a major role in population health. Family planning is one of the most highly cost-effective interventions in medicine. Family planning saves lives and money by reducing unintended pregnancy and the transmission of sexually transmitted infections.

For example, the United States Agency for International Development lists as benefits of its international family planning program:
  • "Protecting the health of women by reducing high-risk pregnancies"
  • "Protecting the health of children by allowing sufficient time between pregnancies"
  • "Fighting HIV/AIDS through providing information, counseling, and access to male and female condoms"
  • "Reducing abortions"
  • "Supporting women's rights and opportunities for education, employment, and full participation in society"
  • "Protecting the environment by stabilizing population growth"

Population health management (PHM)

One method to improve population health is population health management (PHM), which has been defined as "the technical field of endeavor which utilizes a variety of individual, organizational and cultural interventions to help improve the morbidity patterns (i.e., the illness and injury burden) and the health care use behavior of defined populations". PHM is distinguished from disease management by including more chronic conditions and diseases, by use of "a single point of contact and coordination", and by "predictive modeling across multiple clinical conditions". PHM is considered broader than disease management in that it also includes "intensive care management for individuals at the highest level of risk" and "personal health management... for those at lower levels of predicted health risk". Many PHM-related articles are published in Population Health Management, the official journal of DMAA: The Care Continuum Alliance.

The following road map has been suggested for helping healthcare organizations navigate the path toward implementing effective population health management:
  • Establish precise patient registries
  • Determine patient-provider attribution
  • Define precise numerators in the patient registries
  • Monitor and measure clinical and cost metrics
  • Adhere to basic clinical practice guidelines
  • Engage in risk-management outreach
  • Acquire external data
  • Communicate with patients
  • Educate patients and engage with them
  • Establish and adhere to complex clinical practice guidelines
  • Coordinate effectively between care team and patient
  • Track specific outcomes

Healthcare reform and population health

Healthcare reform is driving change to traditional hospital reimbursement models. Prior to the introduction of the Patient Protection and Affordable Care Act (PPACA), hospitals were reimbursed based on the volume of procedures through fee-for-service models. Under the PPACA, reimbursement models are shifting from volume to value. New reimbursement models are built around pay for performance, a value-based reimbursement approach, which places financial incentives around patient outcomes and has drastically changed the way US hospitals must conduct business to remain financially viable. In addition to focusing on improving patient experience of care and reducing costs, hospitals must also focus on improving the health of populations (IHI Triple Aim).

As participation in value-based reimbursement models such as accountable care organizations (ACOs) increases, these initiatives will help drive population health. Within the ACO model, hospitals have to meet specific quality benchmarks, focus on prevention, and carefully manage patients with chronic diseases. Providers get paid more for keeping their patients healthy and out of the hospital. Studies have shown that inpatient admission rates have dropped over the past ten years in communities that were early adopters of the ACO model and implemented population health measures to treat "less sick" patients in the outpatient setting. A study conducted in the Chicago area showed a decline in inpatient utilization rates across all age groups, which was an average of a 5% overall drop in inpatient admissions.

Hospitals are finding it financially advantageous to focus on population health management and keeping people in the community well. The goal of population health management is to improve patient outcomes and increase health capital. Other goals include preventing disease, closing care gaps, and cost savings for providers. In the last few years, more effort has been directed towards developing telehealth services, community-based clinics in areas with high proportion of residents using the emergency department as primary care, and patient care coordinator roles to coordinate healthcare services across the care continuum.

Health can be considered a capital good; health capital is part of human capital as defined by the Grossman model. Health can be considered both an investment good and consumption good. Factors such as obesity and smoking have negative effects on health capital, while education, wage rate, and age may also impact health capital. When people are healthier through preventative care, they have the potential to live a longer and healthier life, work more and participate in the economy, and produce more based on the work done. These factors all have the potential to increase earnings. Some states, like New York, have implemented statewide initiatives to address population health. In New York state there are 11 such programs. One example is the Mohawk Valley Population Health Improvement Program (http://www.mvphip.org/). These programs work to address the needs of the people in their region, as well as assist their local community based organizations and social services to gather data, address health disparities, and explore evidence-based interventions that will ultimately lead to better health for everyone. Following a similar approach, Cullati et al. developed a theoretical framework for the development and onset of vulnerability in later life based on the concept of "reserves". The advantages to use the concept of reserves in interdisciplinary studies, as compared with related concepts such as resources and capital, is to strengthen the importance of constitution and sustainability of reserves (the “use it or lose it” paradigm) and the presence of thresholds, below which functioning becomes challenging.

Statistics

In the United States, the National Center for Health Statistics is responsible for the collection of data on the health of citizens.

Crystal optics

From Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/Crystal_optics ...