Variance in disease risk: rural populations and genetic diversity

Genome ◽  
2016 ◽  
Vol 59 (7) ◽  
pp. 519-525 ◽  
Author(s):  
W.D. Jenkins ◽  
A.E. Lipka ◽  
A.J. Fogleman ◽  
K.R. Delfino ◽  
R.S. Malhi ◽  
...  
Keyword(s):  
Rural Communities ◽  
Rural Areas ◽  
Disease Risk ◽  
Epidemiological Studies ◽  
Genomic Variation ◽  
Genomic Diversity ◽  
Disease Epidemiology ◽  
Industrialized Nations ◽  
The Us ◽  
Significant Disease

Over 19% of the US population resides in rural areas, where studies of disease risk and disease outcomes are difficult to assess due to smaller populations and lower incidence. While some studies suggest rural disparities for different chronic diseases, the data are inconsistent across geography and definitions of rurality. We reviewed the literature to examine if local variations in population genomic diversity may plausibly explain inconsistencies in estimating disease risk. Many rural communities were founded over 150 years ago by small groups of ethnically and ancestrally similar families. These have since endured relative geographical isolation, similar to groups in other industrialized nations, perhaps resulting in founder effects impacting local disease susceptibility. Studies in Europe and Asia have found that observably different phenotypes may appear in isolated communities within 100 years, and that genomic variation can significantly vary over small geographical scales. Epidemiological studies utilizing common “rural” definitions may miss significant disease differences due to assumptions of risk homogeneity and misinterpretation of administrative definitions of rurality. Local genomic heterogeneity should be an important aspect of chronic disease epidemiology in rural areas, and it is important to consider for designing studies and interpreting results, enabling a better understanding of the heritable components of complex diseases.

A Review of the Literature on Rural Suicide

Crisis ◽  
2006 ◽  
Vol 27 (4) ◽  
pp. 189-199 ◽  
Author(s):  
Jameson K. Hirsch
Keyword(s):  
Rural Communities ◽  
Rural Areas ◽  
Urban Areas ◽  
Epidemiological Data ◽  
Epidemiological Studies ◽  
Health Concern ◽  
Prevention And Intervention ◽  
Rural And Urban ◽  
Urban And Rural Areas ◽  
Suicidal Thoughts And Behaviors

Abstract. Background. Suicide is a major cause of mortality worldwide. Differences in rates of suicide exist between urban and rural areas; however, little rigorous research has examined the phenomena of rural suicide. Objective. This review examines the current body of literature on rural suicide and investigates differences between rural and urban suicide, including socioeconomic, psychological, and cultural variables. Prevention and intervention strategies specific to rural communities are discussed. Description of studies. All empirical and epidemiological studies of rural suicide were included in the review regardless of study design or methodology. Results. Although findings are mixed, research and epidemiological data indicate that suicide is a public health concern in rural areas, with suicide rates often greater than in urban areas. Discussion. Rural locale may create geographic, psychological, and sociocultural barriers to treatment of suicide. A better understanding of the role of rurality in the development and maintenance of suicidal thoughts and behaviors is needed and may inform prevention and intervention efforts.

scholarly journals Geodemographic Area Classification and Association with Mortality: An Ecological Study of Small Areas of Cyprus

2019 ◽  
Vol 16 (16) ◽  
pp. 2927 ◽  
Author(s):  
Demetris Lamnisos ◽  
Nicos Middleton ◽  
Nikoletta Kyprianou ◽  
Michael A. Talias
Keyword(s):  
Rural Communities ◽  
Rural Areas ◽  
Metropolitan Areas ◽  
Spatial Models ◽  
Premature Mortality ◽  
Epidemiological Studies ◽  
Population Census ◽  
Socioeconomic Indicators ◽  
Small Areas ◽  
Area Classification

Geographical investigations are a core function of public health monitoring, providing the foundation for resource allocation and policies for reducing health inequalities. The aim of this study was to develop geodemographic area classification based on several area-level indicators and to explore the extent of geographical inequalities in mortality. A series of 19 area-level socioeconomic indicators were used from the 2011 national population census. After normalization and standardization of the geographically smoothed indicators, the k-means cluster algorithm was implemented to classify communities into groups based on similar characteristics. The association between geodemographic area classification and the spatial distribution of mortality was estimated in Poisson log-linear spatial models. The k-means algorithm resulted in four distinct clusters of areas. The most characteristic distinction was between the ageing, socially isolated, and resource-scarce rural communities versus metropolitan areas with younger population, higher educational attainment, and professional occupations. By comparison to metropolitan areas, premature mortality appeared to be 44% (95% Credible Intervals [CrI] of Rate Ratio (RR): 1.06–1.91) higher in traditional rural areas and 36% (95% CrI of RR: 1.13–1.62) higher in young semi-rural areas. These findings warrant future epidemiological studies investigating various causes of the urban-rural differences in premature mortality and implementation policies to reduce the mortality gap between urban and rural areas.

scholarly journals Can Age-Friendly Planning Promote Equity in Community Health Across the Rural-Urban Divide in the US?

2020 ◽  
Vol 17 (4) ◽  
pp. 1275 ◽  
Author(s):  
Xue Zhang ◽  
Mildred E. Warner ◽  
Elaine Wethington
Keyword(s):  
Rural Communities ◽  
Built Environment ◽  
Community Health ◽  
Rural Areas ◽  
World Health ◽  
Poor Whites ◽  
The Us ◽  
Adults And Children ◽  
Neighborhood Built Environment ◽  
Socio Economic Factors

In the US, rural communities face challenges to meet the community health needs of older adults and children. Meanwhile, rural areas lag in age-friendly built environment and services. AARP, a US based organization promoting livability for all ages, has developed a Livability Index based on the World Health Organization’s (WHO) domains of age-friendly communities: health, housing, neighborhood, transportation, environment, engagement, and opportunity. This study links the 2018 AARP Livability Index categories with demographic structure and socio-economic factors from the American Community Survey at the county level in the US to examine if the physical, built and social environment differentiate communities with better community health across the rural–urban divide. Results show that the neighborhood built environment has the largest impact on community health for all county types. Although rural areas lag in community health, those which give more attention to engagement and opportunity rank higher. Rural communities with more African Americans, children, and poor Whites, rank lower on community health. While neighborhood characteristics have the strongest link to community health, a broader approach with attention to age, race, poverty and engagement and opportunity is needed for rural areas.

scholarly journals Assessing Heat-Related Mortality Risks among Rural Populations: A Systematic Review and Meta-Analysis of Epidemiological Evidence

2018 ◽  
Vol 15 (8) ◽  
pp. 1597 ◽  
Author(s):  
Emmanuel Odame ◽  
Ying Li ◽  
Shimin Zheng ◽  
Ambarish Vaidyanathan ◽  
Ken Silver
Keyword(s):  
Rural Communities ◽  
Rural Areas ◽  
Selection Criteria ◽  
Meta Analysis ◽  
Epidemiological Studies ◽  
Included Study ◽  
Rural Populations ◽  
Urban Settings ◽  
Rural Settings ◽  
Related Mortality

Most epidemiological studies of high temperature effects on mortality have focused on urban settings, while heat-related health risks in rural areas remain underexplored. To date there has been no meta-analysis of epidemiologic literature concerning heat-related mortality in rural settings. This study aims to systematically review the current literature for assessing heat-related mortality risk among rural populations. We conducted a comprehensive literature search using PubMed, Web of Science, and Google Scholar to identify articles published up to April 2018. Key selection criteria included study location, health endpoints, and study design. Fourteen studies conducted in rural areas in seven countries on four continents met the selection criteria, and eleven were included in the meta-analysis. Using the random effects model, the pooled estimates of relative risks (RRs) for all-cause and cardiovascular mortality were 1.030 (95% CI: 1.013, 1.048) and 1.111 (95% CI: 1.045, 1.181) per 1 °C increase in daily mean temperature, respectively. We found excess risks in rural settings not to be smaller than risks in urban settings. Our results suggest that rural populations, like urban populations, are also vulnerable to heat-related mortality. Further evaluation of heat-related mortality among rural populations is warranted to develop public health interventions in rural communities.

scholarly journals Traditional Cigarette and Poly-Tobacco Use Are Associated with Medical Opioid Use in Rural Areas of the US

2021 ◽  
Vol 18 (22) ◽  
pp. 11864
Author(s):  
Mariaelena Gonzalez ◽  
Ashley Sanders-Jackson
Keyword(s):  
Rural Communities ◽  
Tobacco Use ◽  
Rural Areas ◽  
Urban Areas ◽  
Binary Logistic Regression ◽  
Tobacco Product ◽  
Structural Level ◽  
Opioid Use ◽  
The Us ◽  
Interview Survey

Introduction: Medical prescriptions for opioids are higher in rural areas of the US as compared to urban areas. Tobacco use may also play a role in this process. This analysis examines the association between differing types of tobacco use and medical opioid use. Methods: We analyze the relationship between tobacco product use and medical opioid use among the US general population living in rural (non-metropolitan) areas using the publicly available sample adult file 2019 National Health Interview Survey (NHIS) (n = 5028). Tobacco use was classified into the following categories: only using cigarettes, only using e-cigarettes/vapes, only using cigars, only using smokeless tobacco, or using two or more of the following products. We used a binary logistic regression, controlling for individual differences. Results: Individuals who reported using only traditional cigarettes (and no other tobacco product, OR = 1.62, 95% CI: 1.31, 2.01), or who reported being a poly-tobacco users (OR = 2.13, 95% CI: 1.40, 3.22) had higher odds of medical opioid use in the last twelve months. Conclusion: Results suggest a link between tobacco use, particularly cigarette use and poly-tobacco use, and medical opioid use in rural communities. Clinical and structural level interventions need to be implemented in rural communities to reduce comorbid tobacco and opioid use.

Biomarker testing in patients (pts) with metastatic colorectal cancer (mCRC): Survey of U.S. oncologists (ONC) in rural areas and urban clusters.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 108-108
Author(s):  
Mark Andrew Lewis ◽  
Lindsay Stansfield ◽  
John M. Kelton ◽  
Michelle L. Edwards ◽  
Christopher Hanyoung Lieu
Keyword(s):  
Rural Communities ◽  
Rural Areas ◽  
Urban Areas ◽  
Stage Iv ◽  
State Legislature ◽  
Direct Care ◽  
Current Guideline ◽  
Tissue Samples ◽  
The Us ◽  
Biomarker Testing

108 Background: In the US, rural areas have higher cancer mortality rates than urban areas. Clinical practice guidelines recommend testing for BRAF and RAS mutations, and deficient mismatch repair (dMMR)/microsatellite instability (MSI) in pts with mCRC. However, data on biomarker testing rates in rural communities are limited. We surveyed ONC in the US who practice in rural areas and urban clusters to identify biomarker testing patterns and barriers. Methods: A web-based survey was administered to board-certified ONC who spend ≥ 40% of their time providing direct care to pts in rural areas or urban clusters (US Census Bureau definition) and who treated ≥ 2 pts with stage IV mCRC in the month prior to the survey. ONC in Maine, Vermont, and West Virginia were excluded (state legislature), as were those employed by the US government, Veterans Affairs, or Kaiser Permanente. Respondents were compensated. Data were analyzed descriptively. Results: From Feb 12 to Mar 18, 2021, 99 ONC (40% medical ONC, 60% hematologists/ONC) completed the survey. Respondents spent 56% and 18% of their time (mean) practicing in urban clusters and rural areas, respectively; 33% were in the South, followed by 26%, 22%, and 18% in the Northeast, Midwest, and West, respectively. 97% of ONC had ordered biomarker tests for pts; 35% referred pts for independent genomic testing. ONC tested biomarkers most commonly for stage IV disease: 72%, 65%, 63%, 59%, and 66% for KRAS, NRAS, BRAF, PD-L1, and dMMR/MSI, respectively (Table). 41% of ONC reported performing reflex testing at their primary practice, most commonly for PD-L1 (62%), KRAS (60%), and dMMR/MSI (52%). DNA-based next-generation sequencing (NGS) was the most common testing method reported. ONC indicated they would test for an actionable biomarker if it were known to occur in ≥ 28% of pts with mCRC. The most commonly cited barriers to testing were insufficient tissue samples and lack of insurance coverage. Although > 50% of ONC agreed telehealth can improve testing rates, 81% noted barriers, including pts lacking technology equipment (56%) and pts being disengaged or unwilling to use telehealth (37%). Further data on testing-related decision making and barriers will be presented. Conclusions: Biomarker testing in rural areas and urban clusters falls short of current guideline recommendations. Further exploration of rural biomarker testing practices and strategies to improve testing are needed.[Table: see text]

scholarly journals Socioeconomic Correlates of Anti-Science Attitudes in the US

2021 ◽  
Vol 13 (6) ◽  
pp. 160
Author(s):  
Minda Hu ◽  
Ashwin Rao ◽  
Mayank Kejriwal ◽  
Kristina Lerman
Keyword(s):  
Social Media ◽  
Rural Communities ◽  
Rural Areas ◽  
Public Attitudes ◽  
Science Attitudes ◽  
Vaccination Rates ◽  
Spatially Resolved ◽  
Political Partisanship ◽  
The Us ◽  
Urban Places

Successful responses to societal challenges require sustained behavioral change. However, as responses to the COVID-19 pandemic in the US showed, political partisanship and mistrust of science can reduce public willingness to adopt recommended behaviors such as wearing a mask or receiving a vaccination. To better understand this phenomenon, we explored attitudes toward science using social media posts (tweets) that were linked to counties in the US through their locations. The data allowed us to study how attitudes towards science relate to the socioeconomic characteristics of communities in places from which people tweet. Our analysis revealed three types of communities with distinct behaviors: those in large metro centers, smaller urban places, and rural areas. While partisanship and race are strongly associated with the share of anti-science users across all communities, income was negatively and positively associated with anti-science attitudes in suburban and rural areas, respectively. We observed that emotions in tweets, specifically negative high arousal emotions, are expressed among suburban and rural communities by many anti-science users, but not in communities in large urban places. These trends were not apparent when pooled across all counties. In addition, we found that anti-science attitudes expressed five years earlier were significantly associated with lower COVID-19 vaccination rates. Our analysis demonstrates the feasibility of using spatially resolved social media data to monitor public attitudes on issues of social importance.

Impact of the home food environment on disease risk factors in obese adults from rural communities

2013 ◽  
Author(s):  
Stacey Maurer ◽  
Kristen Medina ◽  
Danielle Lespinasse ◽  
Samantha Minski ◽  
Manal Alabduljabbar ◽  
...  
Keyword(s):  
Risk Factors ◽  
Rural Communities ◽  
Food Environment ◽  
Disease Risk ◽  
Obese Adults ◽  
Home Food Environment ◽  
Home Food

TURNING FARMERS INTO SOCIAL FARMER ENTREPRENEURS FOR DISADVANTAGED PEOPLE

2020 ◽  
Author(s):  
Remus Runcan
Keyword(s):  
Rural Communities ◽  
Low Income ◽  
Rural Areas ◽  
Urban Areas ◽  
Health And Safety ◽  
Physical Work ◽  
Healthy Environment ◽  
Rural And Urban Areas ◽  
Rural Development Programme ◽  
Rural And Urban

According to Romania’s National Rural Development Programme, the socio-economic situation of the rural environment has a large number of weaknesses – among which low access to financial resources for small entrepreneurs and new business initiatives in rural areas and poorly developed entrepreneurial culture, characterized by a lack of basic managerial knowledge – but also a large number of opportunities – among which access of the rural population to lifelong learning and entrepreneurial skills development programmes and entrepreneurs’ access to financial instruments. The population in rural areas depends mainly on agricultural activities which give them subsistence living conditions. The gap between rural and urban areas is due to low income levels and employment rates, hence the need to obtain additional income for the population employed in subsistence and semi-subsistence farming, especially in the context of the depopulation trend. At the same time, the need to stimulate entrepreneurship in rural areas is high and is at a resonance with the need to increase the potential of rural communities from the perspective of landscape, culture, traditional activities and local resources. A solution could be to turn vegetal and / or animal farms into social farms – farms on which people with disabilities (but also adolescents and young people with anxiety, depression, self-harm, suicide, and alexithymia issues) might find a “foster” family, bed and meals in a natural, healthy environment, and share the farm’s activities with the farmer and the farmer’s family: “committing to a regular day / days and times for a mutually agreed period involves complying with any required health and safety practices (including use of protective clothing and equipment), engaging socially with the farm family members and other people working on and around the farm, and taking on tasks which would include working on the land, taking care of animals, or helping out with maintenance and other physical work”

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