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Annals of Epidemiology May 2019The weathering hypothesis states that chronic exposure to social and economic disadvantage leads to accelerated decline in physical health outcomes and could partially...
PURPOSE
The weathering hypothesis states that chronic exposure to social and economic disadvantage leads to accelerated decline in physical health outcomes and could partially explain racial disparities in a wide array of health conditions. This systematic review summarizes the literature empirically testing the weathering hypothesis and assesses the quality of the evidence regarding weathering as a determinant of racial disparities in health.
METHODS
Databases (Web of Science, Ovid MEDLINE, PubMed, and Embase) were searched for studies published in English up to July 1, 2017. Studies that tested the weathering hypothesis for any physical health outcome and included at least one socially or economically disadvantaged group (e.g., Blacks) for whom the weathering hypothesis applies were assessed for eligibility. Threats to validity were assessed using the Quality in Prognostic Studies tool.
RESULTS
The 41 included studies were rated as having overall good methodological quality. Most studies found evidence in support of the weathering hypothesis, although the magnitude of support varied by the health outcome and population studied.
CONCLUSIONS
Future evaluations of the weathering hypothesis should include an examination of additional health outcomes and interrogate mechanisms that could link weathering to poor health.
Topics: Ethnicity; Health Status Disparities; Healthcare Disparities; Humans; Population Groups; Social Determinants of Health
PubMed: 30987864
DOI: 10.1016/j.annepidem.2019.02.011 -
Bioinformatics (Oxford, England) Nov 2010Genome-wide association studies (GWASs) have been widely used to map loci contributing to variation in complex traits and risk of diseases in humans. Accurate...
MOTIVATION
Genome-wide association studies (GWASs) have been widely used to map loci contributing to variation in complex traits and risk of diseases in humans. Accurate specification of familial relationships is crucial for family-based GWAS, as well as in population-based GWAS with unknown (or unrecognized) family structure. The family structure in a GWAS should be routinely investigated using the SNP data prior to the analysis of population structure or phenotype. Existing algorithms for relationship inference have a major weakness of estimating allele frequencies at each SNP from the entire sample, under a strong assumption of homogeneous population structure. This assumption is often untenable.
RESULTS
Here, we present a rapid algorithm for relationship inference using high-throughput genotype data typical of GWAS that allows the presence of unknown population substructure. The relationship of any pair of individuals can be precisely inferred by robust estimation of their kinship coefficient, independent of sample composition or population structure (sample invariance). We present simulation experiments to demonstrate that the algorithm has sufficient power to provide reliable inference on millions of unrelated pairs and thousands of relative pairs (up to 3rd-degree relationships). Application of our robust algorithm to HapMap and GWAS datasets demonstrates that it performs properly even under extreme population stratification, while algorithms assuming a homogeneous population give systematically biased results. Our extremely efficient implementation performs relationship inference on millions of pairs of individuals in a matter of minutes, dozens of times faster than the most efficient existing algorithm known to us.
AVAILABILITY
Our robust relationship inference algorithm is implemented in a freely available software package, KING, available for download at http://people.virginia.edu/∼wc9c/KING.
Topics: Algorithms; Genome, Human; Genome-Wide Association Study; Genotype; Humans; Phenotype; Polymorphism, Single Nucleotide; Population Groups
PubMed: 20926424
DOI: 10.1093/bioinformatics/btq559 -
Appetite Feb 2022Red and processed meat (RPM) consumption associates directly with several unfavorable health outcomes and with environmental impact of diet. RPM consumption differs...
Red and processed meat (RPM) consumption associates directly with several unfavorable health outcomes and with environmental impact of diet. RPM consumption differs between certain population groups, and moreover, encompasses various subjective meanings. Literature on determinants of subjective importance of meat in diet (SIM), however, is scarce. Aims of this study were to determine which sociodemographic and -economic characteristics associate with SIM and RPM consumption. The study was based on the FinHealth 2017 Study. The sample comprised 4671 participants aged 18-74 years. SIM was asked with a question including five response options from "not important at all" to "very important". Habitual dietary intake including RPM consumption was studied with a food frequency questionnaire. RPM consumption level grew in parallel with SIM categories. RPM consumption was high and SIM prevailing in men, those living in rural areas, and those with low education. Women living in household with children consumed more RPM than other women but did not find meat more important. Conversely, men living in household with children found meat more important but did not consume it more than other men. Domain analyses considering individuals within the highest RPM consumption quintile revealed that the oldest age group found meat significantly less important than the youngest group. In order to be able to lower RPM consumption at population level and to move towards healthier and climate-wiser diets, it is important to identify subgroups that consume much meat but also subgroups that find meat especially important. Such dietary transition may be especially challenging to subgroups that consume much meat and also consider it important. Actions to support the dietary transition in different population groups should be developed.
Topics: Adolescent; Adult; Aged; Child; Diet; Diet Surveys; Eating; Female; Humans; Male; Meat; Middle Aged; Population Groups; Red Meat; Young Adult
PubMed: 34871587
DOI: 10.1016/j.appet.2021.105836 -
The Journals of Gerontology. Series B,... Aug 2020We estimate life expectancy with and without dementia for Americans 65 years and older by education and race to examine how these stratification systems combine to shape...
OBJECTIVES
We estimate life expectancy with and without dementia for Americans 65 years and older by education and race to examine how these stratification systems combine to shape disparities in later-life cognitive health.
METHOD
Based on the Health and Retirement Study (2000-2014), we use a multivariate, incidence-based life table approach to estimate life expectancy by cognitive health status for race-education groups. The models also simulate group differences in the prevalence of dementia implied by these rates.
RESULTS
The life table results document notable race-education differences in dementia and dementia-free life expectancy, as well as stark differences in implied dementia prevalence. At each education level, blacks can expect to live more years with dementia and they have significantly higher rates of dementia prevalence. This distribution of disparities in the older population is anchored by 2 groups-blacks without a high school diploma and whites with some college or more.
DISCUSSION
Dementia experience and dementia burden differ dramatically along race-education lines. Race and education combine to exaggerate disparities and they both have enduring effects. Future research should explicitly consider how race and education combine to influence dementia in the older American population.
Topics: Black or African American; Aged; Cognition; Dementia; Educational Status; Female; Health Status Disparities; Humans; Life Expectancy; Life Tables; Male; Prevalence; Racial Groups; Socioeconomic Factors; United States; White People
PubMed: 31111926
DOI: 10.1093/geronb/gbz046 -
Frontiers in Public Health 2021The concept of "race" emerged in the 1600s with the trans-Atlantic slave trade, justifying slavery; it has been used to justify exploitation, denigration and decimation.... (Review)
Review
The concept of "race" emerged in the 1600s with the trans-Atlantic slave trade, justifying slavery; it has been used to justify exploitation, denigration and decimation. Since then, despite contrary scientific evidence, a deeply-rooted belief has taken hold that "race," indicated by, e.g., skin color or facial features, reflects fundamental biological differences. We propose that the term "race" be abandoned, substituting "ethnic group" while retaining "racism," with the goal of dismantling it. Despite scientific consensus that "race" is a social construct, in official U.S. classifications, "Hispanic"/"Latino" is an "ethnicity" while African American/Black, American Indian/Alaska Native, Asian/Pacific Islander, and European American/White are "races." There is no scientific basis for this. Each grouping reflects ancestry in a particular continent/region and shared history, e.g., the genocide and expropriation of Indigenous peoples, African Americans' enslavement, oppression and ongoing disenfranchisement, Latin America's Indigenous roots and colonization. Given migrations over millennia, each group reflects extensive genetic admixture across and within continents/regions. "Ethnicity" evokes social characteristics such as history, language, beliefs, customs. "Race" reinforces notions of inherent biological differences based on physical appearance. While not useful as a biological category, geographic ancestry is a key social category for monitoring and addressing health inequities because of racism's profound influence on health and well-being. We must continue to collect and analyze data on the population groups that have been racialized into socially constructed categories called "races." We must not, however, continue to use that term; it is not the only obstacle to dismantling racism, but it is a significant one.
Topics: Black or African American; Ethnicity; Hispanic or Latino; Humans; Native Hawaiian or Other Pacific Islander; Racism; United States
PubMed: 34557466
DOI: 10.3389/fpubh.2021.689462 -
Genes Sep 2023Health equity means the opportunity for all people and populations to attain optimal health, and it requires intentional efforts to promote fairness in patient...
Health equity means the opportunity for all people and populations to attain optimal health, and it requires intentional efforts to promote fairness in patient treatments and outcomes. Pharmacogenomic variants are genetic differences associated with how patients respond to medications, and their presence can inform treatment decisions. In this perspective, we contend that the study of pharmacogenomic variation within and between human populations-population pharmacogenomics-can and should be leveraged in support of health equity. The key observation in support of this contention is that racial and ethnic groups exhibit pronounced differences in the frequencies of numerous pharmacogenomic variants, with direct implications for clinical practice. The use of race and ethnicity to stratify pharmacogenomic risk provides a means to avoid potential harm caused by biases introduced when treatment regimens do not consider genetic differences between population groups, particularly when majority group genetic profiles are assumed to hold for minority groups. We focus on the mitigation of adverse drug reactions as an area where population pharmacogenomics can have a direct and immediate impact on public health.
Topics: Humans; Pharmacogenetics; Health Equity; Ethnicity; Pharmacogenomic Variants; Minority Groups
PubMed: 37895188
DOI: 10.3390/genes14101840 -
The European Respiratory Journal Feb 2018
Topics: Adolescent; Adult; Humans; Incidence; Population Groups; Population Surveillance; Tuberculosis; Young Adult
PubMed: 29467211
DOI: 10.1183/13993003.00176-2018 -
BMC Cancer Feb 2021South Africa (SA) has experienced a rapid transition in the Human Development Index (HDI) over the past decade, which had an effect on the incidence and mortality rates...
BACKGROUND
South Africa (SA) has experienced a rapid transition in the Human Development Index (HDI) over the past decade, which had an effect on the incidence and mortality rates of colorectal cancer (CRC). This study aims to provide CRC incidence and mortality trends by population group and sex in SA from 2002 to 2014.
METHODS
Incidence data were extracted from the South African National Cancer Registry and mortality data obtained from Statistics South Africa (STATS SA), for the period 2002 to 2014. Age-standardised incidence rates (ASIR) and age-standardised mortality rates (ASMR) were calculated using the STATS SA mid-year population as the denominator and the Segi world standard population data for standardisation. A Joinpoint regression analysis was computed for the CRC ASIR and ASMR by population group and sex.
RESULTS
A total of 33,232 incident CRC cases and 26,836 CRC deaths were reported during the study period. Of the CRC cases reported, 54% were males and 46% were females, and among deaths reported, 47% were males and 53% were females. Overall, there was a 2.5% annual average percentage change (AAPC) increase in ASIR from 2002 to 2014 (95% CI: 0.6-4.5, p-value < 0.001). For ASMR overall, there was 1.3% increase from 2002 to 2014 (95% CI: 0.1-2.6, p-value < 0.001). The ASIR and ASMR among population groups were stable, with the exception of the Black population group. The ASIR increased consistently at 4.3% for black males (95% CI: 1.9-6.7, p-value < 0.001) and 3.4% for black females (95% CI: 1.5-5.3, p-value < 0.001) from 2002 to 2014, respectively. Similarly, ASMR for black males and females increased by 4.2% (95% CI: 2.0-6.5, p-value < 0.001) and 3.4% (, 95%CI: 2.0-4.8, p-value < 0.01) from 2002 to 2014, respectively.
CONCLUSIONS
The disparities in the CRC incidence and mortality trends may reflect socioeconomic inequalities across different population groups in SA. The rapid increase in CRC trends among the Black population group is concerning and requires further investigation and increased efforts for cancer prevention, early screening and diagnosis, as well as better access to cancer treatment.
Topics: Adolescent; Adult; Age Distribution; Aged; Asian People; Black People; Colorectal Neoplasms; Confidence Intervals; Cross-Sectional Studies; Female; Humans; Incidence; Male; Middle Aged; Mortality; Registries; Regression Analysis; Sex Distribution; South Africa; White People; Young Adult
PubMed: 33549058
DOI: 10.1186/s12885-021-07853-1 -
World Journal of Gastroenterology Jan 2021Roma people make up a significant ethnic minority in many European countries, with the vast majority living in Central and Eastern Europe. Roma are a vulnerable... (Review)
Review
Roma people make up a significant ethnic minority in many European countries, with the vast majority living in Central and Eastern Europe. Roma are a vulnerable population group in social, economic, and political terms. Frequent migrations, life in segregated communities, substandard housing, poverty, and limited access to quality health care, including low immunization coverage, affect their health status and predispose them to various diseases, including viral hepatitis. Hepatitis A, B, and E are highly prevalent among Roma and mainly associated with low socioeconomic status. In contrast, hepatitis C does not seem to be more frequent in the Roma population. Enhanced efforts should be directed towards the implementation of screening programs, preventive measures, and treatment of viral hepatitis in Roma communities throughout Europe.
Topics: Ethnicity; Europe; Europe, Eastern; Humans; Minority Groups; Risk Factors; Roma; Viruses
PubMed: 33510555
DOI: 10.3748/wjg.v27.i2.143 -
JMIR Public Health and Surveillance Dec 2020Accurate size estimates of key populations (eg, sex workers, people who inject drugs, transgender people, and men who have sex with men) can help to ensure adequate...
Accurate size estimates of key populations (eg, sex workers, people who inject drugs, transgender people, and men who have sex with men) can help to ensure adequate availability of services to prevent or treat HIV infection; inform HIV response planning, target setting, and resource allocation; and provide data for monitoring and evaluating program outcomes and impact. A gold standard method for population size estimation does not exist, but quality of estimates could be improved by using empirical methods, multiple data sources, and sound statistical concepts. To highlight such methods, a special collection of papers in JMIR Public Health and Surveillance has been released under the title "Key Population Size Estimations." We provide a summary of these papers to highlight advances in the use of empirical methods and call attention to persistent gaps in information.
Topics: Computing Methodologies; Humans; Population Density; Population Groups
PubMed: 33270035
DOI: 10.2196/25076