The high rates of chronic disease and health inequalities experienced by rural populations have made rural health a research priority for the NIH, including the NCI (1–5). Cancer mortality rates in rural populations have been increasing over time and are disproportionately higher compared with urban populations (6). As such, the NCI has hosted and participated in several meetings and workshops on rural cancer control aimed at accelerating the pace of cancer research in rural populations (7–9) with priority measures to address disparities in rural-associated cancer mortality, including access to care, cancer surveillance, implementation and dissemination research, and evidence-based interventions. Several factors that characterize today's rural America also present opportunities for cancer epidemiologists to conduct population-based research on cancer etiology and risk; findings from these studies may inform primary prevention and targeted interventions downstream. These factors include the ongoing demographic shift (a rapidly aging population and accelerating population diversity of racial/ethnic minorities and immigrants), high prevalence of comorbid conditions, and rural-associated environmental exposures. The purpose of this commentary is to discuss the potential opportunities and methodologic challenges in conducting epidemiologic research on cancer etiology in rural populations.

The changing demographic landscape of rural areas has implications for cancer incidence and comorbid conditions that could be important to cancer risk. The median age of adults in rural areas is 51 years compared with 45 years in urban areas (10). As this older population continues to age, the number of cancer cases will also rise. As such, targeted research on the elderly rural population may be warranted. Between 2000 and 2010, Hispanics contributed more than half of the growth in rural population (11). Subpopulations of Hispanics have been shown to have higher rates of certain cancers and have a higher prevalence of cancer-related risk factors (12). The etiology of certain cancers (i.e., breast, colorectal, and liver) may also be different among Hispanics compared with non-Hispanics (8). Whether factors associated with rurality influences cancer incidence in these populations is unclear; nevertheless, the growing presence of minority populations in rural areas presents a research opportunity. Opportunities and challenges in cancer epidemiologic research with respect to rural populations, the elderly, and Hispanic populations have been discussed in an NCI-sponsored think tank on the topic (8, 13).

There may be differences in the prevalence of certain risk factors and comorbid conditions, such as diabetes and obesity, across rural settings. It is estimated that approximately 5%–6% of all incident cancers in 2012 were attributed to the combined effects of diabetes and obesity (14). Rural populations have a higher prevalence of comorbid conditions, including diabetes (15) and obesity (16), which may partially explain the increasing cancer incidence of certain cancers (17) in these populations.

The limited knowledge about the prevalence and distribution of potentially adverse environmental exposures in rural America and their subsequent association with cancer etiology further suggests opportunities for epidemiologic research to better understand these risk factors. Rural-associated environmental exposures may include chemicals and metals found in well-water (∼45% of rural residents use private well-water; ref. 18), agriculture-associated exposures (19), and occupation-associated exposures with emerging industries found in rural regions such as those related to the hydraulic fracturing (fracking). These exposures may be associated with an increased cancer risk (20–23).

Environmental exposures may act downstream to interfere with several biological pathways responsible for inflammation, hormone function, immune function, DNA repair, or gene expression. Thus, the study of cancer etiology in rural populations presents opportunities to investigate and better understand gene–environment (GxE) interactions among populations exposed to environmental hazards. The importance of these studies has been demonstrated among rural populations, globally. In the United States (U.S.), investigators using the prospective Agricultural Health Study cohort of 89,000 farmers observed that pesticide use modified associations of variants in the 8q24 cancer susceptibility gene and risk of prostate cancer (24). Additional GxE studies may help to identify subset of rural populations that are at a greater risk of developing cancer due to certain environmental exposures. In parallel, rural populations propose the opportunity to investigate the effects of environmental exposures (more prevalent in rural populations) on epigenetic changes and their subsequent role in the development of cancer.

The recognition that a person's cancer risk may not result from a single environmental exposure, but from cumulative exposures over time is of importance; hence, epidemiologic studies should incorporate methodologies that capture multiple environmental exposures longitudinally. A recent study on cumulative environmental exposures used the Environmental Quality Index to capture exposures across multiple dimensions to evaluate the burden of environmental exposures on all-site and site-specific cancers within 2,687 counties using Rural-Urban Continuum Code (RUCC; ref. 25) and observed increases in cancer incidence associated with poorest environmental quality. Additional considerations for implementing validated and innovative methodology that allows the capture of cumulative environmental measures is important.

The research opportunities highlighted above are intended to be illustrative; however, they also raise several methodologic issues for any cancer epidemiology study seeking to investigate these associations. One critical methodologic issue in examining cancer outcomes in rural populations is the definition of “rurality.” Federal agencies have presented definitions for what constitutes an urban geographic area, but these vary from agency to agency. Thus, the proportion of the U.S. population defined as rural can vary substantially depending on the definition used (26). For example, there are three definitions based on the U.S. Census Bureaus' list of census places from the 2000 U.S. census. For the first of these definitions, rural populations are defined as those populations of at least 2,500 or more people that are outside an urban area. By this definition, 87.7 million people or 31% of the U.S. population are classified as rural. However, raising the population size threshold from 2,500 to 10,000 (definition number 2) will increase the rural population to 41% of the U.S. population, and further increase to 50,000 or more people will increase the rural population to 63% of U.S. population. Alternative definitions can add several additional thresholds including population density, land use, and distances to urban areas. Hence, the use of multiple definitions for rural populations reflects a stark reality for epidemiologic research. Researchers should clearly define criteria for rural populations or establish a “common” or “working” definition to allow for comparisons to be made between studies. The Division of Cancer Control and Population Sciences (DCCPS) at NCI adapted the nonmetropolitan 2013 RUCC to define rural populations (27, 28) in their recent funding announcement on observational and interventional research for improving reach and quality of cancer in rural areas. Future evaluation of research emerging from this initiative will provide data for the ability of data harmonization, pooling, and cross-study comparisons.

Achieving the necessary sample size to have a sufficiently powered study may present a challenge when conducting research in rural settings, given smaller population sizes of rural and/or nonurban communities and distances between environments. Recruitment and retention efforts may also prove challenging in rural populations, as study participants may be difficult to reach. Expansion of methodologies to deal with small population studies is warranted.

Assessment of exposures in the vastly geographic diverse rural areas also presents a challenge. The integration of geospatial tools or geographic information systems (GIS) into epidemiologic research has created a paradigm shift which can aid with environmental exposure assessment (which otherwise could not be obtained through traditional epidemiologic methods), cancer cluster identification, and cancer surveillance (29). Geographic location provides information about the lived conditions and permits opportunities to examine contextual factors (i.e., the physical and social environment) that may be important to identify cancer risk factors or disparities in screening, treatment, and survivorship. Geospatial tools also allow researchers to explore the impact of various geospatial measures on cancer risk, treatment, and survival. Examples of novel usage of GIS include identifying zones of potential exposure to agricultural pesticides and determining the proximity of residences to specific crop species that may be sprayed with pesticides, as was done by Ward and colleagues in their study of non-Hodgkin lymphoma (30). Cancer registry data and geospatial tools can also be used to create and examine incidence and mortality maps for clues to “hot spots” or “ecological niches” and conduct ecologic studies to generate hypotheses to be investigated. For example, Christian and colleagues (31) examined geographic patterns of lung cancer incidence, specifically in southeastern Kentucky, and found that environmental exposures related to the coal-mining industry could contribute to the high incidence of lung cancer in that region. As such, geospatial tools have the potential to introduce a new paradigm in better understanding rural cancer disparities.

Epidemiologists rely on a range of study designs to initially identify novel exposures and their associations to cancer risks and outcomes. Identifying and leveraging existing resources and infrastructure can be used to assess certain environmental exposures. For example, surveillance for environmental pollutants and known cancer risk factors may be linked to cancer surveillance data and generate novel scientific hypotheses relevant to rural health. Other examples include leveraging existing datasets (used in quality measures) and existing biospecimens from cohort studies [used to help with exposure (blood) or genetic studies (DNA, tumor)] to examine exposures.

In summary, it is evident that many opportunities exist to address the heavier cancer burden in rural populations through cancer epidemiologic research. The research opportunities, as well as the methodologic challenges, highlighted here are meant only to be illustrative. We encourage researchers in this field of study to deliberate on how to address these challenges. A list of funding opportunity announcements from NCI/DCCPS (specifically focused on rural cancer control) can be found on their website (32). Further conversations on other scientific gaps, challenges, and opportunities relating to epidemiologic research in rural populations are warranted to expand this important area of research.

No potential conflicts of interest were disclosed.

The contents and opinions included in this commentary are the responsibility of the authors and are not a formal position of the NCI.

1.
NIH
. 
Collaborative minority health and health disparities research with tribal epidemiology centers (R21 Clinical Trial Not Allowed)
. Bethesda, MD:
NIH
; 
2017
. Available from: https://grants.nih.gov/grants/guide/pa-files/PAR-17-483.html.
2.
NIH
. 
Collaborative minority health and health disparities research with tribal epidemiology centers (R01 Clinical Trial Not Allowed)
.
Bethesda, MD:
NIH;
2017.
Available from: https://grants.nih.gov/grants/guide/pa-files/PAR-17-484.html.
3.
NIH
. 
Integration of individual residential histories into cancer research (R01)
.
Bethesda, MD:
NIH;
2017.
Available from: https://grants.nih.gov/grants/guide/pa-files/PA-17-298.html.
4.
NIH
. 
Integration of individual residential histories into cancer research (R21)
.
Bethesda, MD:
NIH
; 
2017
. Available from: https://grants.nih.gov/grants/guide/pa-files/PA-17-295.html.
5.
Kennedy
AE
,
Vanderpool
RC
,
Croyle
RT
,
Srinivasan
S
. 
An overview of the National Cancer Institute's initiatives to accelerate rural cancer control research
.
Cancer Epidemiol Biomarkers Prev
2018
;
11
.
6.
Centers for Disease Control and Prevention
. 
New CDC report shows deaths from cancer higher in rural America
.
Atlanta, GA:
Centers for Disease Control and Prevention
; 
2017
. Available from: https://www.cdc.gov/media/releases/2017/p0706-rural-cancer-deaths.html.
7.
Division of Cancer Control and Population Sciences, NCI
. 
Rural cancer control meeting.
Rockville, MD:
NCI
; 
2018
. Available from: https://cancercontrol.cancer.gov/research-emphasis/meetings/arcc-meeting.html.
8.
Martin
DN
,
Lam
TK
,
Brignole
K
,
Ashing
KT
,
Blot
WJ
,
Burhansstipanov
L
, et al
Recommendations for cancer epidemiologic research in understudied populations and implications for future needs
.
Cancer Epidemiol Biomarkers Prev
2016
;
25
:
573
80
.
9.
Kane
M.
Rural cancer control: challenges and opportunities. a summary of small group discussions conducted at the research conference
; 
2017
. Available from: https://cpb-us-w2.wpmucdn.com/sites.wustl.edu/dist/b/1349/files/2018/09/Rural-Cancer-Control-A-Moonshot-Implementation-Research-Agenda-2fu3fqy.pdf.
10.
United States Census Bureau
. 
New census data show differences between urban and rural populations
.
Suitland, MD
:
United States Census Bureau;
2016
. Available from: https://www.census.gov/newsroom/press-releases/2016/cb16-210.html.
11.
United States Census Bureau.
The Hispanic population: 2010. 2010 Census briefs
.
Suitland, MD
:
United States Census Bureau
; 
2011
.
12.
Haile
RW
,
John
EM
,
Levine
AJ
,
Cortessis
VK
,
Unger
JB
,
Gonzales
M
, et al
A review of cancer in U.S. Hispanic populations
.
Cancer Prev Res
2012
;
5
:
150
63
.
13.
Doocy
S
,
Sirois
A
,
Tileva
M
,
Storey
JD
,
Burnham
G
. 
Chronic disease and disability among Iraqi populations displaced in Jordan and Syria
.
Int J Health Planning Manag
2013
;
28
:
e1
e12
.
14.
Pearson-Stuttard
J
,
Zhou
B
,
Kontis
V
,
Bentham
J
,
Gunter
MJ
,
Ezzati
M
. 
Worldwide burden of cancer attributable to diabetes and high body-mass index: a comparative risk assessment
.
Lancet Diabetes Endocrinol
2018
;
6
:
e6
e15
.
15.
O'Connor
A
,
Wellenius
G
. 
Rural-urban disparities in the prevalence of diabetes and coronary heart disease
.
Public Health
2012
;
126
:
813
20
.
16.
Patterson
PD
,
Moore
CG
,
Probst
JC
,
Shinogle
JA
. 
Obesity and physical inactivity in rural America
.
J Rural Health
2004
;
20
:
151
9
.
17.
Blake
KD
,
Moss
JL
,
Gaysynsky
A
,
Srinivasan
S
,
Croyle
RT
. 
Making the case for investment in rural cancer control: an analysis of rural cancer incidence, mortality, and funding trends
.
Cancer Epidemiol Biomarkers Prev
2017
;
26
:
992
7
.
18.
Charrois
JW.
Private drinking water supplies: challenges for public health
.
CMAJ
2010
;
182
:
1061
4
.
19.
Bukowski
J
,
Somers
G
,
Bryanton
J
. 
Agricultural contamination of groundwater as a possible risk factor for growth restriction or prematurity
.
J Occup Environ Med
2001
;
43
:
377
83
.
20.
Ayotte
JD
,
Medalie
L
,
Qi
SL
,
Backer
LC
,
Nolan
BT
. 
Estimating the high-arsenic domestic-well population in the conterminous United States
.
Environ Sci Technol
2017
;
51
:
12443
54
.
21.
Wheeler
DC
,
Nolan
BT
,
Flory
AR
,
DellaValle
CT
,
Ward
MH
. 
Modeling groundwater nitrate concentrations in private wells in Iowa
.
Sci Total Environ
2015
;
536
:
481
8
.
22.
Elliott
EG
,
Trinh
P
,
Ma
X
,
Leaderer
BP
,
Ward
MH
,
Deziel
NC
. 
Unconventional oil and gas development and risk of childhood leukemia: assessing the evidence
.
Sci Total Environ
2017
;
576
:
138
47
.
23.
Carpenter
DO.
Hydraulic fracturing for natural gas: impact on health and environment
.
Rev Environ Health
2016
;
31
:
47
51
.
24.
Koutros
S
,
Beane Freeman
LE
,
Berndt
SI
,
Andreotti
G
,
Lubin
JH
,
Sandler
DP
, et al
Pesticide use modifies the association between genetic variants on chromosome 8q24 and prostate cancer
.
Cancer Res
2010
;
70
:
9224
33
.
25.
Jagai
JS
,
Messer
LC
,
Rappazzo
KM
,
Gray
CL
,
Grabich
SC
,
Lobdell
DT
. 
County-level cumulative environmental quality associated with cancer incidence
.
Cancer
2017
;
123
:
2901
8
.
26.
United States Department of Agriculture, Economic Research Service
. 
Rural definitions: data documentation and methods
; 
2018
. Available from: https://www.ers.usda.gov/data-products/rural-definitions/data-documentation-and-methods.aspx.
27.
Department of Health and Human Services
. 
(PA-18-026). Improving the reach and quality of cancer care in rural populations (R01 Clinical Trial Required)
.
Washington, DC
:
Department of Health and Human Services
; 
2018
. Available from: https://grants.nih.gov/grants/guide/rfa-files/RFA-CA-18-026.html.
28.
United States Department of Agriculture, Economic Research Service
. 
Rural-
U
rban
C
ontinuum
C
odes
; 
2018
. Available from: https://www.ers.usda.gov/data-products/rural-urban-continuum-codes.aspx.
29.
NCI
. 
Geographic information systems and science for cancer control
.
Rockville, MD
:
NCI
; 
2018
. Available from: https://gis.cancer.gov/gis-nci/spatial_data_analysis.html.
30.
Ward
MH
,
Nuckols
JR
,
Weigel
SJ
,
Maxwell
SK
,
Cantor
KP
,
Miller
RS
. 
Identifying populations potentially exposed to agricultural pesticides using remote sensing and a geographic information system
.
Environ Health Perspect
2000
;
108
:
5
12
.
31.
Christian
WJ
,
Huang
B
,
Rinehart
J
,
Hopenhayn
C
. 
Exploring geographic variation in lung cancer incidence in Kentucky using a spatial scan statistic: elevated risk in the Appalachian coal-mining region
.
Public Health Rep
2011
;
126
:
789
96
.
32.
Department of Cancer Control and Population Sciences
. 
Rural cancer control
; 
2017.
Available from: https://cancercontrol.cancer.gov/research-emphasis/rural.html.