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Factors Influencing Cardiovascular Risk Factors and Health Perception Among Kentuckians Living in Appalachia

Abraham, Cilgy M. BS, RN; Kelly, Sarah PhD, RN; Wantland, Dean PhD, RN; Chung, Misook L. PhD, RN, FAAN, FAHA; Mudd-Martin, Gia PhD, MPH, RN, FAHA; Biddle, Martha J. PhD, RN, APRN, CCNS, FAHA; Moser, Debra K. PhD, RN, FAAN, FAHA

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The Journal of Cardiovascular Nursing: 5/6 2020 - Volume 35 - Issue 3 - p E1-E8
doi: 10.1097/JCN.0000000000000594
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Cardiovascular disease (CVD) is a major cause of death, and 720 000 Americans experience their first acute myocardial infarction, a type of CVD, every year.1 Risk factors for CVD can increase the likelihood of developing additional acute myocardial infarction. Specifically, adults living in Appalachia have multiple risk factors for CVD.2 For example, high rates of obesity, consumption of unhealthy diets, physical inactivity, and cigarette smoking contribute to the lower life expectancy for the Appalachian population.3 With most of the Appalachian adult population having CVD risk factors, there is limited knowledge on whether their perception of health is associated with CVD risk factors. Therefore, in this study, the relationship among gender, CVD risk factors, and health perception was explored. The study aims were to (1) describe the overall and age-group differences between smoking history, physical activity, systolic and diastolic blood pressure, total cholesterol, high-density lipoprotein and low-density lipoprotein cholesterol, waist circumference, hemoglobin A1c% (HbA1c %), and body mass index (BMI) in men and women living in the Appalachia region of Kentucky and (2) examine the relationship between CVD risk factors and health perception.


Residents living in central and southern Appalachia experience major health disparities that include CVD, lung disease, and cancer.4,5 The Appalachian region encompasses all of West Virginia and parts of twelve other states, including Kentucky.6 According to the 2014 Behavioral Risk Factor Surveillance Survey, approximately 6% of adults in Kentucky had coronary heart disease or angina.7

Risk for CVD increases with unhealthy behaviors (eg, physical inactivity, smoking, high cholesterol, diabetes, hypertension, and obesity).8 Compared to the United States adult population, men and women in Kentucky have higher rates of engagement in these unhealthy behaviors. The 2014 Behavioral Risk Factor Surveillance Survey reported that 26.2% of adults from Kentucky were current smokers, compared with 18.1% nationally.7 In addition, 54.3% of Kentuckians do not participate in regular physical activity, compared with 49% nationally.9 Engagement in unhealthy activities impacts health given that 39.1% of adults in Kentucky have hypertension and 43.2% have hypercholesterolemia compared with 31.4% and 38.4%, respectively, nationally.10

The prevalence of higher CVD risk factors by gender is mixed. Compared with men, women from Kentucky have a higher prevalence of high blood pressure (28.6% vs 27.8%) and high cholesterol (38.5% vs 37.6%) and were more likely to report no physical activity in the past month (33.6% vs 27%).11 Similarly, in 2014, fewer women met aerobic physical activity guidelines (47%) compared with men (53%).12 These results reveal higher rates of obesity and lower physical activity in women, which are known risk factors for CVD. However, there is a higher prevalence of obesity and diabetes and consumption of fewer than 5 fruits or vegetables per day in men than women in Kentucky.11 Because high blood pressure, cholesterol, physical inactivity, obesity, diabetes, and low consumption of fruits and vegetables are risk factors for CVD, these findings demonstrate a potential disparity in CVD risk factors among men and women in Kentucky.

However, health disparities among men and women are most notable in residents of Appalachia Kentucky. Compared with adults living in the United States, adults living in Appalachia have a higher rate of obesity, which increases the risk for many diseases including CVD.13 In 2010, the obesity rates were 1.6 times higher in Appalachian women and 1.3 times higher in Appalachian men from Kentucky compared to nationally.13 In addition, men and women from the Appalachian region of Kentucky had smoking rates approximately 1.6 and 1.8 times higher, respectively, than the national smoking rate.13 Hence, it is necessary to study the prevalence of CVD risk factors among men and women to develop appropriate interventions to minimize complications from CVD.

Poor nutrition, that is, a diet high in saturated fats and low in fruits and vegetables, is a modifiable CVD risk factor. In a study with 281,874 participants, adherence to healthy diet indicators (eg, saturated fatty acids, polyunsaturated fatty acids, monosaccharides and disaccharides, protein, cholesterol, dietary fiber, fruits, and vegetables) reduced CVD mortality.14 Poor health and nutrition may result from not having access to healthy meals, the abundance of processed meals, lack of safe places to exercise, and high costs of healthcare, which are socioeconomic factors associated with CVD risk in Appalachians.15 Furthermore, uncontrolled diabetes can increase the risk for an adverse cardiovascular event, and 12.5% of Kentuckians are diagnosed with diabetes.7

Risk for CVD increases with age. For example, researchers report that as age increases, postmenopausal women have greater CVD risk factors such as higher blood pressure, cholesterol, and weight gain compared with men their age.16 Furthermore, the largest prevalence of those diagnosed with diabetes (19.62%), a CVD risk factor, was seen among adults 65 years or older.17 These results indicate that older age increases the risk for CVD.

The atypical presentation of symptoms associated with CVD in women may inhibit women from seeking immediate care. In addition, providers who are unfamiliar with the atypical symptoms of CVD in women may fail to provide aggressive medical treatments.18 This may be explained by the higher rates of death during hospitalization after an acute myocardial infarction in younger women compared with men of the same age.19

Health beliefs and self-perception can tremendously impact health. How individuals perceive their own health is influenced by perceived susceptibility, seriousness of the condition, need for healthcare services, and engagement in self-care.20 Particularly, women are less likely than men to perceive themselves to be at risk for CVD and were less aware of the signs and symptoms of an acute myocardial infarction.21–23 For example, in a study with 1,654 participants, 17% of women were at high risk for CVD, but 60% of those high-risk women considered their risk low or moderate.23 Moreover, 23% of women at high risk and 29% of women with CVD actually scored in the middle to low range regarding knowledge of CVD, despite rating their level of knowledge high.23 These findings reveal the inconsistency between health perception of CVD and actual risk for CVD. Similarly, women were less likely to call emergency services for themselves if they perceived that they were experiencing an acute myocardial infarction, whereas women were more likely to call emergency services if someone else was experiencing an acute myocardial infarction.24 Ultimately, such studies reveal the importance of investigating CVD differences by gender. Therefore, it is imperative to understand the role that health perception has on the health of Appalachian women. Because women are less likely to perceive their risk for heart disease, they may be at greater risk for an adverse cardiovascular event.



A secondary analysis was conducted using baseline data from the study “Heart Health in Rural Kentucky,” which was a randomized, wait-listed controlled trial.25 The purpose of the parent study was to assess the effectiveness of a CVD risk-reduction intervention through self-care in residents of rural Kentucky. Participants were randomly assigned to immediate self-management intervention or delayed self-management intervention. Participants assigned to the immediate intervention group started the 12-week intervention once baseline data were collected. Those in the second group started the intervention 6 months after being selected. Data for phase 1 of the study were collected from 2009 to 2010 and data for phase 2 of the study were collected from 2010 to 2012.25 For our study, we selected 880 participants who completed baseline assessment in phase 1 or 2 and had completed data for variables included in this study. There was no conceptual framework that embraced this study.

Sample and Setting

Individuals from rural counties in the Appalachia region of Kentucky were recruited to participate in the parent study. Participants 18 years or older were included if they were either (1) diagnosed with CVD, (2) diagnosed with heart failure, or (3) had 2 or more CVD risk factors. Recruitment for the parent study occurred through word of mouth, flyers, and physician referral.


All measures were commonly used by previous researchers and were retrieved from the parent study.25


Sociodemographic information for gender, age, race/ethnicity, and marital status was collected through participant self-report.

Health Perception

To assess health perception, participants were asked, “In general, what is your health status now?” They rated their health status on a 5-point Likert scale ranging from (1) excellent to (5) poor.

Cardiovascular Disease Risk Factors

Cardiovascular disease risk factors included smoking history, physical activity, systolic and diastolic blood pressure, lipids, waist circumference, blood glucose, and BMI.

Smoking History

Participants rated their smoking history on a 4-point Likert scale ranging from (1) current smoker to (4) never smoked. Participants were also asked to report if they used smokeless tobacco (chew) using a dichotomous yes or no response.

Physical Activity

We used 1 item of the modified version of the Medical Outcome Study Specific Adherence Scale. Participants were asked if they were physically active for 30 minutes or more 4 times a week. Responses were rated on a 6-point Likert scale ranging from (1) none of the time to (6) all of the time.

Systolic and Diastolic Blood Pressure

As recommended by the American Heart Association standards,25,26 calibrated aneroid sphygmomanometer was used to measure systolic and diastolic blood pressure.


Values of total cholesterol, low-density lipoprotein, and high-density lipoprotein were collected using point-of-care testing, which is validated for use in clinical practice.25,27

Waist Circumference

A measuring tape placed around the participant's abdomen was used to measure waist circumference.

Blood Glucose (Hemoglobin A1c)

Blood glucose was measured using a fast acting blood test.

Body Mass Index

Weight was measured using a digital body weight scale and height was measured using a stadiometer. We derived BMI using the mathematical equation of kilograms divided by height in meters squared, as recommended by the Centers for Disease Control and Prevention.28


Approval for the parent study was obtained from the University of Kentucky Institutional Review Board in addition to written informed consent from all participants. The current study was deemed exempt by the institutional review board of a large university located in the Northeast.

Data Analysis

Descriptive statistics were used to describe participant characteristics for demographic and physiologic variables. To assess gender differences in smoking history, χ2 analysis was used. Age in years was dichotomized to 50 years or younger and older than 50 years as the sample mean age was 50.7 years. Independent t tests were used to compare the mean between the 2 age-group (participants ≤50 years old and those >50 years old) differences in the physiologic measures of BMI, waist circumference, systolic and diastolic blood pressure, HbA1c %, total cholesterol, and physical activity of 30 minutes or more at least 4 times a week. Along with the dichotomized demographic variables for partnered/single, smoking ever/smoking never, and white/nonwhite race, the age group differences for physiological CVD risk factors were analyzed.

A linear regression analysis was performed to assess for variables predicting the dependent variable of health perception. Given a large sample, some variables that were significantly associated with the dependent variable of health perception were retained in the final model to fully represent the underlying demographic and physiological factors' contribution to perceived health in this population. Variables were placed in the regression model based on the variable being a demographic or a physiological variable. This was done so interpretation of the effects of the independent demographic variables on the dependent variable was more easily interpretable as only those variables with the value of 1 show in the analysis given that the 0 values drop out of the regression analysis. The IBM Statistic Package for Social Sciences version 23 was used for data analysis (New York).


This study included results from 880 adults living in the Appalachia region of Kentucky. On average, participants were 50.7 years of age (SD, 13.7 years) (Table 1). Most participants were female (74.4%), white (95.2%), and obese, with a mean (SD) BMI of 33 (8.0) kg/m2. Nearly half of the participants rated their health perception as “good” (n = 447, 50.8%). Most indicated that they never smoked (n = 539, 61%), and only 35 participants (4.0%) reported using chewing tobacco.

Characteristics of Participants (N = 880)

Differences in Smoking History and Smokeless Tobacco Use Between Men and Women

There was a difference in smoking history between men and women (Table 2). We found that 48.9% of men and 65.5% of women reported that they have never smoked (P ≤ .001). There was also a difference between gender and whether participants were current smokers, ever smoked, or never smoked [x2(3, n = 880) = 25.7, P < .001]. Men were more likely to use smokeless tobacco products compared with women (94.3% vs 5.7%, respectively, P < .001) (Table 3).

Smoking History (N = 880)
Smokeless Tobacco (N = 35)

Differences in Cardiovascular Risk Factors Between Men and Women

Table 4 details gender differences for CVD risk factors. Men had higher physical activity of 30 minutes or more at least 4 times per week than women did. Men also had higher systolic and diastolic blood pressure and waist circumference than women did. By gender, cholesterol levels were significantly different, with women having higher total cholesterol levels. No significant gender differences were noted for BMI.

Gender Differences in Physiologic Measures (N = 880)

Differences in Cardiovascular Risk Factors in the 2 Age Groups

To examine differences in CVD risk factors, the sample was divided into 2 age groups (≤50 years, n = 431, 49%, and >50 years, n = 449, 51%). The only demographic variable to show a significant difference was being married/partnered versus single (divorced/separated/widowed/never partnered), with those in the older than 50 years age group more likely to not be partnered compared to the 50 years or younger age group (χ21 = 4.43, P = .035). Furthermore, those in the older age group were more likely to be widowed (χ21 = 36.31, P ≤ .001).

It was an a priori expectation that the older cohort in the study would have poorer physiological measures compared with the cohort of 50 years or younger. However, the results showed this to be the case only in systolic blood pressure and HbA1c % (Table 5). The older than 50 years age group had significantly lower BMI and diastolic blood pressure and higher engagement in physical activity than those 50 years or younger. No significant age-group differences existed for waist circumference or total cholesterol.

Age-Group Differences in Physiologic Measures (N = 880)

Predicting Health Perception

As seen in Table 6, demographic results showed individuals older than 50 years were significantly more likely to have better perceived health (P = .02). Other demographic factors that improved health perception were being female and being partnered, although these did not contribute significantly in the model. Having a history of smoking significantly decreased health perception scores by 0.107 points on the 6-point scale.

Regression of Health Perception Onto Different Physiological and Health Behaviors

For physiological variables, physical activity was significantly associated with an improved health perception score (β = −.200, P ≤ .001). Holding all other variables constant, for every unit increase in the exercise scale, there was a 0.20 improvement in health perception. However, BMI and HbA1c % were associated with poorer health perception. As BMI increased, health perception increased (β = .244, P = .007). Conversely, HbA1c % values predicted worse health perception scores, revealing that an increase in HbA1c % also increased the perception score (P = .004). Variables waist circumference, systolic blood pressure, diastolic blood pressure, and total cholesterol did not contribute significantly in predicting any change in health perception.


In this study, we explored CVD risk factors in men and women. Understanding the relationship between health perception and CVD risk factors may provide insight on interventions to reduce the prevalence of CVD in men and women residing in Kentucky. Our results demonstrate that women were more likely to report physical inactivity compared with men. This is concerning because physical inactivity is a modifiable risk factor for CVD. Moreover, men from Appalachia had higher use of smokeless tobacco, which is a threat to health and well-being. Our finding is consistent with other researchers reporting that Appalachians are more likely to smoke cigarettes compared with a national sample of non-Appalachians.13

Although we hypothesized that women experience greater CVD risk factors compared with men, our results are contrary to that hypothesis. In our sample, men had higher systolic and diastolic blood pressure, HbA1c % values, and waist circumference, whereas women had higher BMI and total cholesterol level. However, our results by gender are fairly similar, which suggests that these differences may not be clinically significant. Nonetheless, our findings are still consistent with the literature that states that CVD develops 7 to 10 years later in women, implying that men may be more likely to display hallmark signs of CVD before women.29

Participants older than 50 years had slightly better BMI, diastolic blood pressure, and higher physical activity of 30 minutes or more at least 4 times per week than those 50 years or younger. Although several of the age-group differences in physiological measures were statistically significant, the differences among those older than 50 years or 50 years or younger may not be clinically significant. Nevertheless, our finding that participants older than 50 years had some better physiologic measures compared to those 50 years or younger is contrary to what we expected given that age has a positive correlation with systolic and diastolic blood pressure.30 In our sample, Appalachian adults older than 50 years had higher systolic blood pressure compared with those 50 years or younger; however, there was an opposite effect for diastolic blood pressure. It is possible that with older age, our participants may be more experienced with managing their health and may be more aware of the recommended guidelines for CVD. In addition, it is possible that our participants were already educated by their healthcare provider on the importance of maintaining a healthy lifestyle, and this could have resulted in better health indicators for those older than 50 years.

Because our results demonstrated that participants older than 50 years had better BMI, diastolic blood pressure, and higher levels of physical activity, it was not surprising that they also had better perception of their health compared with participants younger than 50 years. This suggests that better management of health can influence the perception of health. Similarly, those with higher BMI and HbA1c % values had worse health perception scores. In this case, poor management of one's health negatively influences the perception of health. Interestingly, being female and partnered resulted in better health perception. This is consistent with our findings showing that women had lower levels of CVD risk factors. With women having better health indicators, this explains why, in our sample, being female improved health perception.


This study had some limitations. Because the study was a secondary analysis of data, we did not have control over data collection or survey development. The parent study used self-reports of personal health history data, which could have influenced participants to be more or less willing to disclose certain health behaviors (eg, smoking history or use of chewing tobacco). Our findings only apply to Appalachian men and women and may not be generalizable to adults living in other regions of the United States. Overall, our results suggest that there is much opportunity to reduce CVD risk factors in the Appalachian population, which is supported by similar data regarding men and women in Kentucky and nationally.


To our knowledge, this is the first study to explore health perception and CVD risk factors among men and women from the Appalachian region of rural Kentucky. The findings of this study are relevant for nurses and their ability to provide comprehensive care to those at risk for CVD. Overall, the statistically significant findings by groups were not significantly relevant from a clinical standpoint because the results for each subcategory were relatively similar. Hence, there is a need for behavioral interventions for all age groups and genders in this population to reduce CVD risk factors and increase engagement in physical activity. In addition, how one perceives his or her health can have an important role in influencing health outcomes.31,32 Nurses have the knowledge and skills needed to educate across the lifespan and promote healthy behaviors that would improve health perception and reduce the likelihood of developing CVD. Lastly, nurses can be advocates for rural Appalachian communities where access to high-quality healthcare continues to be a barrier. Unable to attain affordable care can prevent individuals from engaging in primary and secondary preventative measures against CVD.

What’s New and Important
  • Several cardiovascular risk factors (ie, systolic and diastolic blood pressure, and waist circumference) are higher in men compared with women from Appalachia Kentucky.
  • Variables that were significant predictors of health perception were BMI, HbA1c %, smoking history, and physical activity of 30 minutes or more, at least 4 times per week.


1. American Heart Association. Heart disease and stroke statistics—at-a-glance. Accessed October 21, 2018.
2. Thompson E, Fields SA, Bors K. Appalachian women and heart health: current prevention strategies and future directions. W V Med J. 2013;109(4):76–81. Accessed September 28, 2016.
3. Ford ES, Bergmann MM, Boeing H, Li C, Capewell S. Healthy lifestyle behaviors and all-cause mortality among adults in the United States. Prev Med. 2012;55(1):23–27. doi:10.1016/j.ypmed.2012.04.016.
4. Borak J, Zaidel C, Slade M, Fields C. Mortality disparities in Appalachia: reassessment of major risk factors. J Occup Environ Med. 2012;54(2):146–156. doi:10.1097/JOM.0b013e318246f395.
5. Hendryx M. Personal and family health in rural areas of Kentucky with and without mountaintop coal mining. J Rural Health. 2013;29(s1):s79–s88. doi:10.1111/jrh.12016.
6. Appalachian Regional Commission. The Appalachian Region. Appalachian Regional Commission. Accessed December 15, 2017.
7. Behavioral Risk Factor Surveillance System (BRFSS). BRFSS prevalence & trends data in 2014. Accessed October 11, 2017.
8. Mendy VL, Vargas R. Peer reviewed: trends in major risk factors for cardiovascular disease among adults in the Mississippi Delta region, Mississippi Behavioral Risk Factor Surveillance System, 2001–2010. Prev Chronic Dis. 2015;12:E21. doi:10.5888/pcd12.140481.
9. Behavioral Risk Factor Surveillance System (BRFSS). BRFSS prevalence & trends data in 2009. Accessed October 11, 2017.
10. Behavioral Risk Factor Surveillance System (BRFSS). BRFSS prevalence & trends data in 2013. Accessed October 11, 2017.
11. Rugg SS, Bailey AL, Browning SR. Preventing cardiovascular disease in Kentucky: epidemiology, trends, and strategies for the future. J Ky Med Assoc. 2008;106(4):149–163. Accessed September 14, 2016.
12. CDC. Physical activity among adults. Accessed December 2016.
13. Schoenberg NE, Huang B, Seshadri S, Tucker TC. Trends in cigarette smoking and obesity in Appalachian Kentucky. South Med J. 2015;108(3):170–177. doi:10.14423/SMJ.0000000000000245.
14. Jankovic N, Geelen A, Streppel MT, et al. WHO guidelines for a healthy diet and mortality from cardiovascular disease in European and American elderly: the CHANCES project. Am J Clin Nutr. 2015;102(4):745–756. doi:10.3945/ajcn.114.095117.
15. Mudd-Martin G, Biddle MJ, Chung ML, et al. Rural Appalachian perspectives on heart health: social ecological contexts. Am J Health Behav. 2014;38(1):134–143. doi:10.5993/AJHB.38.1.14.
16. Kanchi R, Perlman SE, Chernov C, et al. Gender and race disparities in cardiovascular disease risk factors among New York City adults: New York City Health and Nutrition Examination Survey (NYC HANES) 2013–2014. J Urban Health. 2018;95(6):801–812. doi:10.1007/s11524-018-0287-x.
17. Bullard KM, Cowie CC, Lessem SE, et al. Prevalence of diagnosed diabetes in adults by diabetes type—United States, 2016. MMWR Morb Mortal Wkly Rep. 2018;67(12):359–361. doi:10.15585/mmwr.mm6712a2.
18. Pearson TL. Cardiovascular risk in minority and underserved women in Appalachian Tennessee: a descriptive study. J Am Assoc Nurse Pract. 2010;22(4):210–216. doi:10.1111/j.1745-7599.2010.00495.x.
19. Möller-Leimkühler AM. Gender differences in cardiovascular disease and comorbid depression. Dialogues Clin Neurosci. 2007;9(1): 71–83. Accessed September 13, 2016.
20. Slusher IL, Withrow-Fletcher C, Hauser-Whitaker M. Appalachian women: health beliefs, self-care, and basic conditioning factors. J Cult Divers. 2010;17(3):84–89. Accessed September 13, 2016.
21. Mochari-Greenberger H, Miller KL, Mosca L. Racial/ethnic and age differences in women's awareness of heart disease. J Womens Health. 2012;21(5):476–480. doi:10.1089/jwh.2011.3428.
22. Leifheit-Limson EC, D'Onofrio G, Daneshvar M, et al. Sex differences in cardiac risk factors, perceived risk, and health care provider discussion of risk and risk modification among young patients with acute myocardial infarction: the VIRGO study. J Am Coll Cardiol. 2015;66(18):1949–1957. doi:10.1016/j.jacc.2015.08.859.
23. McDonnell LA, Pipe AL, Westcott C, et al. Perceived vs actual knowledge and risk of heart disease in women: findings from a Canadian survey on heart health awareness, attitudes, and lifestyle. Can J Cardiol. 2014;30(7):827–834. doi:10.1016/j.cjca.2014.05.007.
24. Mosca L, Mochari-Greenberger H, Dolor RJ, Newby LK, Robb KJ. Twelve-year follow-up of American women's awareness of cardiovascular disease risk and barriers to heart health. Circ Cardiovasc Qual Outcomes. 2013;3(2):120–127. doi:10.1161/CIRCOUTCOMES.109.915538.
25. Mudd-Martin G, Rayens MK, Lennie TA, et al. Fatalism moderates the relationship between family history of cardiovascular disease and engagement in health-promoting behaviors among at-risk rural Kentuckians. J Rural Health. 2015;31(2):206–216. doi:10.1111/jrh.12094.
26. Pickering TG, Hall JE, Appel LJ, et al. Recommendations for blood pressure measurement in humans and experimental animals, part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. Circulation. 2005;111(5):697–716. doi:0.1161/01.CIR.0000154900.76284.F6.
27. Dale RA, Jensen LH, Krantz MJ. Comparison of two point-of-care lipid analyzers for use in global cardiovascular risk assessments. Ann Pharmacother. 2008;42(5):633–639. doi:10.1345/aph.1K688.
28. CDC. Adult BMI. Accessed April 7 2019.
29. Maas AH, Appelman YE. Gender differences in coronary heart disease. Neth Heart J. 2010;18(12):598–603. Accessed September 13, 2016.
30. Dua S, Bhuker M, Sharma P, Dhall M, Kapoor S. Body mass index relates to blood pressure among adults. N Am J Med Sci. 2014;6(2):89–95. doi:10.4103/1947-2714.127751.
31. Zahrt OH, Crum AJ. Perceived physical activity and mortality: evidence from three nationally representative US samples. Health Psychol. 2017;36(11):1017–1025. doi:10.1037/hea0000531.
32. Crum AJ, Corbin WR, Brownell KD, Salovey P. Mind over milkshakes: mindsets, not just nutrients, determine ghrelin response. Health Psychol. 2011;30(4):424–429. doi:10.1037/a0023467.

cardiovascular diseases; rural health; Appalachian region; perception

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