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Physical Activity and Health-Related Quality of Life in Rural Adults with Chronic Disease

Peter D. Hart

Health Promotion Program, Montana State University - Northern, Havre, MT 59501

Abstract: Purpose: The purpose of this study was to examine the relationship between Physical activity (PA) and health-related quality of life (HRQOL) in a large-scale population of rural adults with chronic disease. Methods: Data for this study came from the CDC’s 2015 Behavioral Risk Factor Surveillance System (BRFSS). A total of N=65,492 rural adults 20+ years of age were included in the analysis. The main outcome variable was HRQOL as assessed by the CDC Healthy Days Index. Adults were categorized as “meeting” PA guidelines if they reported 150+ minutes of moderate-intensity PA per week and “not meeting” PA guidelines if they reported less than 150 minutes. Multiple logistic regression was used to compute odds ratios (ORs) and 95% confidence intervals (CIs) while adjusting for age, sex, race, and income. Results: Rural adults with at least one chronic disease and meeting recommended levels of PA were significantly more likely to report good HRQOL (72.5%; 70.7-74.3) than their less active counterparts (58.1%; 56.4-59.7, p<.001). Those meeting recommended levels of PA had greater odds of good HRQOL regardless of reporting diabetes (OR=1.58; 95% CI: 1.31-1.91), COPD (1.49; 1.20-1.85), cancer (1.79; 1.43-2.22), stroke (1.73; 1.30-2.31), heart disease (1.52; 1.18-1.96), or heart attack (1.68; 1.32-2.15). Additionally, the same increased odds were seen across rural adults reporting 1 (1.59; 1.34-1.88), 2 (1.64; 1.28-2.11), and 3+ (1.52; 1.13-2.05) chronic diseases. Conclusions: Results from this study indicate that meeting recommended levels of PA is strongly associated with optimal levels of HRQOL among rural adults with chronic disease.

Keywords: physical activity, chronic disease, epidemiology, health-related quality of life

Citation: Peter D. Hart, Physical Activity and Health-Related Quality of Life in Rural Adults with Chronic Disease. American Journal of Medical Sciences and Medicine, 5 (3). 62-66. January 2017. doi:10.12691/ajmsm-5-3-5

1. Introduction

Adults residing in rural regions of the Unites States (U.S.) are known to suffer from poorer health outcomes than their urban counterparts [1]. Prevalence of diabetes and coronary heart disease in rural populations is higher than other geographic regions [2]. Rural residents are also significantly more likely to die after traumatic injury, as compared to their non-rural counterparts [3]. These health disparities are also seen with health risk behaviors. The prevalence of good health behaviors (i.e., sufficient sleep, non-smoking, non-alcohol drinking, normal body weight maintenance, and meeting physical activity guidelines) is also lower in rural regions [4]. Access to proper and appropriate healthcare may be one factor explaining such rural health disparities, with rural residents suffering less quality access to healthcare providers [5,6].

Physical activity (PA), a health behavior associated with many positive health outcomes, is also associated with health-related quality of life (HRQOL) in adults [7]. Furthermore, adults with chronic disease [8] and adults residing in rural regions [9] suffer disparities in HRQOL. Given this, however, little is known regarding the association between PA and HRQOL in rural adults suffering from chronic illness. Therefore, purpose of this study was to examine the relationship between PA and HRQOL in a large-scale population of rural adults with chronic disease.

2. Methods

2.1. Participants and Design

Data for this study came from the CDC’s 2015 Behavioral Risk Factor Surveillance System (BRFSS), a large national cross-sectional survey [10]. The BRFSS is a state-based annual survey of U.S. non-institutionalized adults 18+ years of age. The BRFSS uses a complex probability sampling scheme and provides estimates that are representative of all U.S. adults. The BRFSS is designed to monitor risky health behaviors and chronic conditions associated with the nation’s leading causes of death and disease. The 2015 BRFSS included survey questions regarding fifteen core sections: 1) demographics, 2) health status, 3) health-related quality of life, 4) health care access, 5) hypertension, 6) cholesterol, 7) chronic health, 8) tobacco use, 9) alcohol consumption, 10) fruit and vegetable consumption, 11) physical activity, 12) arthritis, 13) seatbelt use, 14) immunization, and 15) HIV/AIDS [11]. This study used participant responses primarily from the demographics, HRQOL, chronic health, and physical activity cores. A total of N=65,492 adults 20+ years of age, who answered all relevant survey questions, and resided in a rural U.S. county were included [12].

2.2. Measures

HRQOL was the outcome variable for all analyses. The main independent variable was PA status (meeting or not meeting guidelines). Stratification variables consisted of chronic disease indicators of diabetes, COPD, cancer, heart disease, stroke, or heart attack. HRQOL was assessed by the CDC Healthy Days Index. Adults reporting 13 or fewer unhealthy days were considered to have “good” HRQOL and those reporting 14 or more unhealthy days were considered to have “poor” HRQOL [13]. PA was assessed based on responses to a series of questions regarding PA in the past 30 days. Participants reporting 150+ minutes of moderate-intensity PA per week were considered to have met the PA guidelines [14].

Participants were considered having a chronic disease if they reported ever being told by a health professional that they had diabetes, COPD, cancer, heart disease, a stroke or a heart attack. The variables age, sex, race, and income were used to describe the data as well as for covariates in adjusted models. Body mass index (BMI) was used as an additional covariate and computed from self-reported height and weight. Those respondents with BMIs less than 25 (kg/m²) were considered normal weight, those with BMIs greater than or equal to 25 but less than 30 (kg/m²) were considered overweight and those with BMIs greater than or equal to 30 (kg/m²) were considered obese.

2.3. Statistical Analysis

Prevalence estimates (%s) were computed for both HRQOL and PA status across relevant sociodemographic groups. Chi-square tests of independence were used to test for significant differences in prevalence estimates. Multiple logistic regression was used to compute odds ratios (ORs) and 95% confidence intervals (CIs) while adjusting for age, sex, race, and income [15,16]. SPSS Complex Sampling version 24 and SAS version 9.4 were used to account for the sampling design [17,18]. All significance levels were set to p=.05.

3. Results

Table 1 displays prevalence estimates for good/poor HRQOL and PA status. Majority of rural adults did not meet PA guidelines (58.7%; 57.5-59.8), with more males (46.1%; 44.3-48.0) meeting guidelines than females (37.7%; 36.2-39.2). However, majority of rural adults did report at least good HRQOL (64.3%; 63.1-65.4), with more females (38.6%; 37.1-40.1) reporting poor HRQOL than males (32.0%; 30.3-33.8). Rural adults with at least one chronic disease and meeting recommended levels of PA were significantly more likely to report good HRQOL (72.5%; 70.7-74.3) than their less active counterparts (58.1%; 56.4-59.7, p<.001).

Table 1. Prevalence of meeting and not meeting recommended levels of PA and good and poor HRQOL among rural adults with at least one chronic disease by demographic category, 2015

Table 2 displays odds of good HRQOL (as compared to poor HRQOL) for rural adults meeting PA guidelines (as compared to not meeting guidelines) across chronic disease status. Those meeting recommended levels of PA had greater odds of good HRQOL regardless of reporting diabetes (OR=1.58; 95% CI: 1.31-1.91), COPD (1.49; 1.20-1.85), cancer (1.79; 1.43-2.22), stroke (1.73; 1.30-2.31), heart disease (1.52; 1.18-1.96), or heart attack (1.68; 1.32-2.15), in the adjusted models. Additionally, the same increased odds were seen across rural adults reporting 1 (1.59; 1.34-1.88), 2 (1.64; 1.28-2.11), and 3+ (1.52; 1.13-2.05) chronic diseases.

Table 2. Odds of Good HRQOL for Rural Adults Meeting Recommended Levels of PA

Figure 1 displays the ORs and associated significance tests for PA as a predictor of HRQOL, overall and by BMI category. Overall, those meeting PA guidelines were more likely (1.91; p<.05) to report good HRQOL, as compared to their less active counterparts. Rural adults of normal body weight had the greatest odds (2.07; p<.05) of good HRQOL given they met PA guidelines and obese adults had the lowest (1.78; p<.05). Additionally, the odds associated with good HRQOL were indirectly related to BMI category (p for trend <.001).

Figure 1. Odds ratios (ORs) of good HRQOL for those meeting recommended levels of PA across BMI categories

4. Discussion

The purpose of this study was to examine the relationship between PA and HRQOL in a large-scale population of rural adults with chronic disease. The results clearly showed that meeting recommended levels of PA was indeed related to optimal levels of HRQOL, despite chronic disease status. These findings remained robust across the different chronic disease conditions (i.e., diabetes, cancer, stroke, etc.). Moreover, adults with multiple chronic illnesses appeared to receive similar benefit from recommended levels of PA. These results are consistent with randomized controlled trials that have shown increases in PA with simultaneous increases in HRQOL [19,20,21,22]. These findings are further supported by studies that have shown increased HRQOL in physically active participants with chronic diseases [23,24,25,26,27,28,29]. Finally, these results are consistent with studies that have shown significant relationships between PA and HRQOL among rural adults suffering from chronic illness [30,31].

The strengths concerning this study are worth mentioning. This study analyzed data that are representative of all U.S. rural adults 20+ years of age. Few studies researching similar PA and HRQOL relationships in this population allow for this type of generalization. Another strength was the ability to assess chronic disease states from survey data. The BRFSS is a rich survey in that it assesses several different health conditions. Therefore, this study had the ability to assign each participant a chronic disease status as well as assess the number of chronic diseases each participant reported.

This study has limitations worth mentioning before the results are completely interpreted. This study was limited to participants self-reporting whether a healthcare professional had ever told them they had a chronic disease condition. This type of assessment may introduce measurement error both in terms of participant recall accuracy as well as severity of the chronic health condition. The BRFSS questions regarding chronic conditions do not differentiate between type of healthcare provider and severity of the disease. Therefore, some participants may have been misclassified as having the condition. A clinical-based study, that provides medical examinations to subjects, may provide a more accurate chronic disease classification. Similarly, because this study used self-report data for chronic disease assessment, it’s possible that some participants suffered from certain chronic conditions during their interview but were, however, unaware they had a condition. These limitations warrant caution when interpreting the findings from this study.

5. Conclusions

Results from this study indicate that meeting recommended levels of PA is strongly associated with optimal levels of HRQOL among rural adults with chronic disease. Health promotion programs should market PA interventions to rural adults with such diseases to improve HRQOL.

Acknowledgements

No financial assistance was used to assist with this project.

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