Keith Gennuso - Academia.edu (original) (raw)

Papers by Keith Gennuso

New England Journal of Medicine

Public Health Reports

Introduction Life expectancy is a public health metric used to assess mortality. We describe life... more Introduction Life expectancy is a public health metric used to assess mortality. We describe life expectancy calculations for US counties and present methodologic considerations compared with years of potential life lost before age 75 (YPLL-75) and premature age-adjusted mortality (PAAM), 2 commonly used length-of-life metrics. Methods We used death data from the National Center for Health Statistics for 2015-2017 and other health measures from the 2019 County Health Rankings & Roadmaps. We calculated life expectancy from birth at the county level using an abridged life table and the Chiang method of variance. Studentized residuals identified counties with discordant life expectancy and YPLL-75 or PAAM values. Correlations tested associations of life expectancy with key health measures (eg, smoking, child poverty, uninsured). Results Among 3073 US counties, life expectancy ranged from 62.4 to 98.0 years, with a mean of 77.4 years. Life expectancy was strongly and negatively correlat...

Journal of Public Health Management and Practice

American Journal of Preventive Medicine

American Journal of Public Health

Annals of epidemiology, 2018

Accurate measurement of free-living physical activity is challenging in population-based research... more Accurate measurement of free-living physical activity is challenging in population-based research, whether using device-based or reported methods. Our purpose was to identify demographic predictors of discordance between physical activity assessment methods and to determine how these predictors modify the discordance between device-based and reported physical activity measurement methods. Three hundred forty-seven adults from the Survey of the Health of Wisconsin wore the ActiGraph accelerometer for 7 days and completed the Global Physical Activity Questionnaire. Multivariate linear regression was conducted to assess predictors of discordance including gender, education, body mass index, marital status, and other individual level characteristics in physical activity reporting. Seventy-seven percent of men and 72% of women self-reported meeting the U.S. Centers for Disease Control and Prevention guidelines for aerobic activity but when measured by accelerometer, only 21% of men and 1...

American Journal of Public Health

Objectives. To evaluate trends in premature death rates by cause of death, age, race, and urbaniz... more Objectives. To evaluate trends in premature death rates by cause of death, age, race, and urbanization level in the United States. Methods. We calculated cause-specific death rates using the Compressed Mortality File, National Center for Health Statistics data for adults aged 25 to 64 years in 2 time periods: 1999 to 2001 and 2013 to 2015. We defined 48 subpopulations by 10-year age groups, race/ethnicity, and county urbanization level (large urban, suburban, small or medium metropolitan, and rural). Results. The age-adjusted premature death rates for all adults declined by 8% between 1999 to 2001 and 2013 to 2015, with decreases in 39 of the 48 subpopulations. Most decreases in death rates were attributable to HIV, cardiovascular disease, and cancer. All 9 subpopulations with increased death rates were non-Hispanic Whites, largely outside large urban areas. Most increases in death rates were attributable to suicide, poisoning, and liver disease. Conclusions. The unfavorable recent trends in premature death rate among non-Hispanic Whites outside large urban areas were primarily caused by self-destructive health behaviors likely related to underlying social and economic factors in these communities.

PLOS ONE

The 2003-2004 and 2005-2006 cycles of the National Health and Nutrition Examination Survey (NHANE... more The 2003-2004 and 2005-2006 cycles of the National Health and Nutrition Examination Survey (NHANES) were among the first population-level studies to incorporate objectively measured physical activity and sedentary behavior, allowing for greater understanding of these behaviors. However, there has yet to be a comprehensive examination of these data in cancer survivors, including short-and long-term survivors of all cancer types. Therefore, the purpose of this analysis was to use these data to describe activity behaviors in shortand long-term cancer survivors of various types. A secondary aim was to compare activity patterns of cancer survivors to that of the general population. Cancer survivors (n = 508) and age-matched individuals not diagnosed with cancer (n = 1,016) were identified from a subsample of adults with activity measured by accelerometer. Physical activity and sedentary behavior were summarized across cancer type and demographics; multivariate regression was used to evaluate differences between survivors and those not diagnosed with cancer. On average, cancer survivors were 61.4 (95% CI: 59.6, 63.2) years of age; 57% were female. Physical activity and sedentary behavior patterns varied by cancer diagnosis, demographic variables, and time since diagnosis. Survivors performed 307 min/day of lightintensity physical activity (95% CI: 295, 319), 16 min/day of moderate-vigorous intensity activity (95% CI: 14, 17); only 8% met physical activity recommendations. These individuals also reported 519 (CI: 506, 532) minutes of sedentary time, with 86 (CI: 84, 88) breaks in sedentary behavior per day. Compared to non-cancer survivors, after adjustment for potential confounders, survivors performed less light-intensity activity (P = 0.01), were more sedentary (P = 0.01), and took fewer breaks in sedentary time (P = 0.04), though there were no differences in any other activity variables. These results suggest that cancer survivors are insufficiently active. Relative to adults of similar age not diagnosed with cancer, they engage in more sedentary time with fewer breaks. As such, sedentary behavior and light-intensity activity may be important intervention targets, particularly for those for whom moderate-tovigorous activity is not well accepted.

Medicine & Science in Sports & Exercise, 2015

Medicine & Science in Sports & Exercise, 2016

Med Sci Sport Exercise, 2009

The aim of this study was to examine the dose-response relationship between walking activity and ... more The aim of this study was to examine the dose-response relationship between walking activity and physical function (PF) in community-dwelling older adults. Physical activity (PA, pedometry), and PF (self-report and 6 minute walk test (6MWT)) was assessed in 836 individuals. Accumulated PA was categorized into 4 Groups (1=≤2500, 2=2501-5000, 3=5001-7500, and 4=≥7501 steps/d). Across individual Groups 1-4, PF scores increased from 66.9±25.0% to 73.5±23.2% to 78.8±19.7% to 81.3±20.6%, and 6MWT increased from 941.7±265.4 ft to 1154.1±248.2 ft to 1260.1±226.3 ft to 1294.0±257.9 ft. Both PF and 6MWT scores were statistically different across all Groups, apart from Groups 3 and 4. PA and ranks of Groups were highly significant predictors (p<.0001) for both PF and 6MWT. There was a positive dose-response relationship evident for both PF and 6MWT with increasing levels of PA. Low levels of PA appear to be an important indicator of poor functionality in older adults.

Preventing Chronic Disease, 2016

Introduction The objective of this observational study was to examine the key contributors to hea... more Introduction The objective of this observational study was to examine the key contributors to health outcomes and to better understand the health disparities between Delta and non-Delta counties in 8 states in the Mississippi River Delta Region. We hypothesized that a unique set of contributors to health outcomes in the Delta counties could explain the disparities between Delta and non-Delta counties. Methods Data were from the 2014 County Health Rankings for counties in 8 states (Alabama, Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, and Tennessee). We used the Delta Regional Authority definition to identify the 252 Delta counties and 468 non-Delta counties or county equivalents. Information on health factors (eg, health behaviors, clinical care) and outcomes (eg, mortality) were derived from 38 measures from the 2014 County Health Rankings. The contributions of health factors to health outcomes in Delta and non-Delta counties were examined using path analysis. Results We found similarities between Delta counties and non-Delta counties in the health factors (eg, tobacco use, diet and exercise) that significantly predicted the health outcomes of self-rated health and low birthweight. The most variation was seen in predictors of mortality; however, Delta counties shared 2 of the 3 significant predictors (ie, community safety and income) of mortality with non-Delta counties. On average across all measures, values in the Delta were 16% worse than in the non-Delta and 22% worse than in the rest of the United States. Conclusion The health status of Delta counties is poorer than that of non-Delta counties because the health factors that contribute to health outcomes in the entire region are worse in the Delta counties, not because of a unique set of health predictors.

Aging Clinical and Experimental Research, 2015

Background/aims The purposes of this study were to examine the relationship between various objec... more Background/aims The purposes of this study were to examine the relationship between various objectively measured sedentary behavior (SB) variables and physical function in older adults, examine the measurement properties of an SB questionnaire, and describe the domains of SB in our sample. Methods Forty-four older adults (70 ± 8 years, 64 % female) had their SB measured via activPAL activity monitor and SB questionnaire for 1 week followed by performance-based tests of physical function. Results The pattern of SB was more important than total SB time. Where a gender by SB interaction was found, increasing time in SB and fewer breaks were associated with worse function in the males only. The SB questionnaire had acceptable test-retest reliability but poor validity compared to activPAL-measured SB. The majority of SB time was spent watching television, using the computer and reading. Discussion/conclusions This study provides further evidence for the association between SB and physical function and describes where older adults are spending their sedentary time. This information can be used in the design of future intervention to reduce sedentary time and improve function in older adults.

Journal of Aging and Physical Activity, 2014

The aim of this study was to examine the dose-response relationship between walking activity and ... more The aim of this study was to examine the dose-response relationship between walking activity and physical function (PF) in community-dwelling older adults. Physical activity (PA, pedometry) and PF (self-report [SF-36] and 6-minute walk test [6MWT]) were assessed in 836 individuals. Accumulated PA was categorized into four groups (1 = ≤ 2,500; 2 = 2,501–5,000; 3 = 5,001–7,500; and 4 = ≥ 7,501 steps/day). Across individual groups 1–4, SF-36 scores increased from 66.9 ± 25.0% to 73.5 ± 23.2% to 78.8 ± 19.7% to 81.3 ± 20.6%, and 6MWT increased from 941.7 ± 265.4 ft to 1,154.1 ± 248.2 ft to 1,260.1 ± 226.3 ft to 1,294.0 ± 257.9 ft. Both SF-36 and 6MWT scores were statistically different across all groups, apart from groups 3 and 4. PA and ranks of groups were highly significant predictors (p < .0001) for both SF-36 and 6MWT. There was a positive dose-response relationship evident for both SF-36 and 6MWT with increasing levels of PA. Low levels of PA appear to be an important indicator...

Medicine & Science in Sports & Exercise, 2008

Medicine & Science in Sports & Exercise, 2009

The aim of this study was to examine the dose-response relationship between walking activity and ... more The aim of this study was to examine the dose-response relationship between walking activity and physical function (PF) in community-dwelling older adults. Physical activity (PA, pedometry), and PF (self-report and 6 minute walk test (6MWT)) was assessed in 836 individuals. Accumulated PA was categorized into 4 Groups (1=≤2500, 2=2501-5000, 3=5001-7500, and 4=≥7501 steps/d). Across individual Groups 1-4, PF scores increased from 66.9±25.0% to 73.5±23.2% to 78.8±19.7% to 81.3±20.6%, and 6MWT increased from 941.7±265.4 ft to 1154.1±248.2 ft to 1260.1±226.3 ft to 1294.0±257.9 ft. Both PF and 6MWT scores were statistically different across all Groups, apart from Groups 3 and 4. PA and ranks of Groups were highly significant predictors (p<.0001) for both PF and 6MWT. There was a positive dose-response relationship evident for both PF and 6MWT with increasing levels of PA. Low levels of PA appear to be an important indicator of poor functionality in older adults.

American journal of preventive medicine, 2015

Although many researchers agree that multiple determinants impact health, there is no consensus r... more Although many researchers agree that multiple determinants impact health, there is no consensus regarding the magnitude of the relative contributions of individual health factors to health outcomes. This study presents a method to empirically estimate the relative contributions of health behaviors, clinical care, social and economic factors, and the physical environment to health outcomes using nationally representative county-level data and statistical approaches that account for potential sources of bias. The analyses for this study were conducted in 2014. Data were from the 2010-2013 County Health Rankings & Roadmaps. Data covered 2,996 of 3,141 U.S. counties. Ordinary least squares modeling was used as a baseline model. Multilevel latent growth curve modeling was used to estimate the relative contributions of health factors to health outcomes while accounting for measurement errors and state-specific characteristics. Almost half of the variance of health outcomes was due to stat...

American Journal of Preventive Medicine, 2015

The County Health Rankings (CHR) provides data for nearly every county in the U.S. on four modifi... more The County Health Rankings (CHR) provides data for nearly every county in the U.S. on four modifiable groups of health factors, including healthy behaviors, clinical care, physical environment, and socioeconomic conditions, and on health outcomes such as length and quality of life. The purpose of this study was to empirically estimate the strength of association between these health factors and health outcomes and to describe the performance of the CHR model factor weightings by state. Data for the current study were from the 2015 CHR. Thirty-five measures for 45 states were compiled into four health factors composite scores and one health outcomes composite score. The relative contributions of health factors to health outcomes were estimated using hierarchical linear regression modeling in March 2015. County population size; rural/urban status; and gender, race, and age distributions were included as control variables. Overall, the relative contributions of socioeconomic factors, health behaviors, clinical care, and the physical environment to the health outcomes composite score were 47%, 34%, 16%, and 3%, respectively. Although the CHR model performed better in some states than others, these results provide broad empirical support for the CHR model and weightings. This paper further provides a framework by which to prioritize health-related investments, and a call to action for healthcare providers and the schools that educate them. Realizing the greatest improvements in population health will require addressing the social and economic determinants of health.

Journal of Physical Activity and Health

Background: To examine the effectiveness of the American College of Sports Medicine (ACSM) and th... more Background: To examine the effectiveness of the American College of Sports Medicine (ACSM) and the American Heart Association (AHA) resistance training (RT) guidelines to improve physical function and functional classification in older adults with reduced physical abilities. Methods: Twenty-five at-risk older adults were randomized to a control (CON = 13) or 8-week resistance training intervention arm (RT = 12). Progressive RT included 8 exercises for 1 set of 10 repetitions at a perceived exertion of 5-6 performed twice a week. Individuals were assessed for physical function and functional classification change (low, moderate or high) by the short physical performance battery (SPPB) and muscle strength measures. Results: Postintervention, significant differences were found between groups for SPPB-Chair Stand [F(1,22) = 9.14, P < .01, η= .29] and SPPB-Total Score [F(1,22) = 7.40, P < .05, η = .25]. Functional classification was improved as a result of the intervention with 83...

New England Journal of Medicine

Public Health Reports

Introduction Life expectancy is a public health metric used to assess mortality. We describe life... more Introduction Life expectancy is a public health metric used to assess mortality. We describe life expectancy calculations for US counties and present methodologic considerations compared with years of potential life lost before age 75 (YPLL-75) and premature age-adjusted mortality (PAAM), 2 commonly used length-of-life metrics. Methods We used death data from the National Center for Health Statistics for 2015-2017 and other health measures from the 2019 County Health Rankings & Roadmaps. We calculated life expectancy from birth at the county level using an abridged life table and the Chiang method of variance. Studentized residuals identified counties with discordant life expectancy and YPLL-75 or PAAM values. Correlations tested associations of life expectancy with key health measures (eg, smoking, child poverty, uninsured). Results Among 3073 US counties, life expectancy ranged from 62.4 to 98.0 years, with a mean of 77.4 years. Life expectancy was strongly and negatively correlat...

Journal of Public Health Management and Practice

American Journal of Preventive Medicine

American Journal of Public Health

Annals of epidemiology, 2018

Accurate measurement of free-living physical activity is challenging in population-based research... more Accurate measurement of free-living physical activity is challenging in population-based research, whether using device-based or reported methods. Our purpose was to identify demographic predictors of discordance between physical activity assessment methods and to determine how these predictors modify the discordance between device-based and reported physical activity measurement methods. Three hundred forty-seven adults from the Survey of the Health of Wisconsin wore the ActiGraph accelerometer for 7 days and completed the Global Physical Activity Questionnaire. Multivariate linear regression was conducted to assess predictors of discordance including gender, education, body mass index, marital status, and other individual level characteristics in physical activity reporting. Seventy-seven percent of men and 72% of women self-reported meeting the U.S. Centers for Disease Control and Prevention guidelines for aerobic activity but when measured by accelerometer, only 21% of men and 1...

American Journal of Public Health

Objectives. To evaluate trends in premature death rates by cause of death, age, race, and urbaniz... more Objectives. To evaluate trends in premature death rates by cause of death, age, race, and urbanization level in the United States. Methods. We calculated cause-specific death rates using the Compressed Mortality File, National Center for Health Statistics data for adults aged 25 to 64 years in 2 time periods: 1999 to 2001 and 2013 to 2015. We defined 48 subpopulations by 10-year age groups, race/ethnicity, and county urbanization level (large urban, suburban, small or medium metropolitan, and rural). Results. The age-adjusted premature death rates for all adults declined by 8% between 1999 to 2001 and 2013 to 2015, with decreases in 39 of the 48 subpopulations. Most decreases in death rates were attributable to HIV, cardiovascular disease, and cancer. All 9 subpopulations with increased death rates were non-Hispanic Whites, largely outside large urban areas. Most increases in death rates were attributable to suicide, poisoning, and liver disease. Conclusions. The unfavorable recent trends in premature death rate among non-Hispanic Whites outside large urban areas were primarily caused by self-destructive health behaviors likely related to underlying social and economic factors in these communities.

PLOS ONE

The 2003-2004 and 2005-2006 cycles of the National Health and Nutrition Examination Survey (NHANE... more The 2003-2004 and 2005-2006 cycles of the National Health and Nutrition Examination Survey (NHANES) were among the first population-level studies to incorporate objectively measured physical activity and sedentary behavior, allowing for greater understanding of these behaviors. However, there has yet to be a comprehensive examination of these data in cancer survivors, including short-and long-term survivors of all cancer types. Therefore, the purpose of this analysis was to use these data to describe activity behaviors in shortand long-term cancer survivors of various types. A secondary aim was to compare activity patterns of cancer survivors to that of the general population. Cancer survivors (n = 508) and age-matched individuals not diagnosed with cancer (n = 1,016) were identified from a subsample of adults with activity measured by accelerometer. Physical activity and sedentary behavior were summarized across cancer type and demographics; multivariate regression was used to evaluate differences between survivors and those not diagnosed with cancer. On average, cancer survivors were 61.4 (95% CI: 59.6, 63.2) years of age; 57% were female. Physical activity and sedentary behavior patterns varied by cancer diagnosis, demographic variables, and time since diagnosis. Survivors performed 307 min/day of lightintensity physical activity (95% CI: 295, 319), 16 min/day of moderate-vigorous intensity activity (95% CI: 14, 17); only 8% met physical activity recommendations. These individuals also reported 519 (CI: 506, 532) minutes of sedentary time, with 86 (CI: 84, 88) breaks in sedentary behavior per day. Compared to non-cancer survivors, after adjustment for potential confounders, survivors performed less light-intensity activity (P = 0.01), were more sedentary (P = 0.01), and took fewer breaks in sedentary time (P = 0.04), though there were no differences in any other activity variables. These results suggest that cancer survivors are insufficiently active. Relative to adults of similar age not diagnosed with cancer, they engage in more sedentary time with fewer breaks. As such, sedentary behavior and light-intensity activity may be important intervention targets, particularly for those for whom moderate-tovigorous activity is not well accepted.

Medicine & Science in Sports & Exercise, 2015

Medicine & Science in Sports & Exercise, 2016

Med Sci Sport Exercise, 2009

The aim of this study was to examine the dose-response relationship between walking activity and ... more The aim of this study was to examine the dose-response relationship between walking activity and physical function (PF) in community-dwelling older adults. Physical activity (PA, pedometry), and PF (self-report and 6 minute walk test (6MWT)) was assessed in 836 individuals. Accumulated PA was categorized into 4 Groups (1=≤2500, 2=2501-5000, 3=5001-7500, and 4=≥7501 steps/d). Across individual Groups 1-4, PF scores increased from 66.9±25.0% to 73.5±23.2% to 78.8±19.7% to 81.3±20.6%, and 6MWT increased from 941.7±265.4 ft to 1154.1±248.2 ft to 1260.1±226.3 ft to 1294.0±257.9 ft. Both PF and 6MWT scores were statistically different across all Groups, apart from Groups 3 and 4. PA and ranks of Groups were highly significant predictors (p<.0001) for both PF and 6MWT. There was a positive dose-response relationship evident for both PF and 6MWT with increasing levels of PA. Low levels of PA appear to be an important indicator of poor functionality in older adults.

Preventing Chronic Disease, 2016

Introduction The objective of this observational study was to examine the key contributors to hea... more Introduction The objective of this observational study was to examine the key contributors to health outcomes and to better understand the health disparities between Delta and non-Delta counties in 8 states in the Mississippi River Delta Region. We hypothesized that a unique set of contributors to health outcomes in the Delta counties could explain the disparities between Delta and non-Delta counties. Methods Data were from the 2014 County Health Rankings for counties in 8 states (Alabama, Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, and Tennessee). We used the Delta Regional Authority definition to identify the 252 Delta counties and 468 non-Delta counties or county equivalents. Information on health factors (eg, health behaviors, clinical care) and outcomes (eg, mortality) were derived from 38 measures from the 2014 County Health Rankings. The contributions of health factors to health outcomes in Delta and non-Delta counties were examined using path analysis. Results We found similarities between Delta counties and non-Delta counties in the health factors (eg, tobacco use, diet and exercise) that significantly predicted the health outcomes of self-rated health and low birthweight. The most variation was seen in predictors of mortality; however, Delta counties shared 2 of the 3 significant predictors (ie, community safety and income) of mortality with non-Delta counties. On average across all measures, values in the Delta were 16% worse than in the non-Delta and 22% worse than in the rest of the United States. Conclusion The health status of Delta counties is poorer than that of non-Delta counties because the health factors that contribute to health outcomes in the entire region are worse in the Delta counties, not because of a unique set of health predictors.

Aging Clinical and Experimental Research, 2015

Background/aims The purposes of this study were to examine the relationship between various objec... more Background/aims The purposes of this study were to examine the relationship between various objectively measured sedentary behavior (SB) variables and physical function in older adults, examine the measurement properties of an SB questionnaire, and describe the domains of SB in our sample. Methods Forty-four older adults (70 ± 8 years, 64 % female) had their SB measured via activPAL activity monitor and SB questionnaire for 1 week followed by performance-based tests of physical function. Results The pattern of SB was more important than total SB time. Where a gender by SB interaction was found, increasing time in SB and fewer breaks were associated with worse function in the males only. The SB questionnaire had acceptable test-retest reliability but poor validity compared to activPAL-measured SB. The majority of SB time was spent watching television, using the computer and reading. Discussion/conclusions This study provides further evidence for the association between SB and physical function and describes where older adults are spending their sedentary time. This information can be used in the design of future intervention to reduce sedentary time and improve function in older adults.

Journal of Aging and Physical Activity, 2014

The aim of this study was to examine the dose-response relationship between walking activity and ... more The aim of this study was to examine the dose-response relationship between walking activity and physical function (PF) in community-dwelling older adults. Physical activity (PA, pedometry) and PF (self-report [SF-36] and 6-minute walk test [6MWT]) were assessed in 836 individuals. Accumulated PA was categorized into four groups (1 = ≤ 2,500; 2 = 2,501–5,000; 3 = 5,001–7,500; and 4 = ≥ 7,501 steps/day). Across individual groups 1–4, SF-36 scores increased from 66.9 ± 25.0% to 73.5 ± 23.2% to 78.8 ± 19.7% to 81.3 ± 20.6%, and 6MWT increased from 941.7 ± 265.4 ft to 1,154.1 ± 248.2 ft to 1,260.1 ± 226.3 ft to 1,294.0 ± 257.9 ft. Both SF-36 and 6MWT scores were statistically different across all groups, apart from groups 3 and 4. PA and ranks of groups were highly significant predictors (p < .0001) for both SF-36 and 6MWT. There was a positive dose-response relationship evident for both SF-36 and 6MWT with increasing levels of PA. Low levels of PA appear to be an important indicator...

Medicine & Science in Sports & Exercise, 2008

Medicine & Science in Sports & Exercise, 2009

The aim of this study was to examine the dose-response relationship between walking activity and ... more The aim of this study was to examine the dose-response relationship between walking activity and physical function (PF) in community-dwelling older adults. Physical activity (PA, pedometry), and PF (self-report and 6 minute walk test (6MWT)) was assessed in 836 individuals. Accumulated PA was categorized into 4 Groups (1=≤2500, 2=2501-5000, 3=5001-7500, and 4=≥7501 steps/d). Across individual Groups 1-4, PF scores increased from 66.9±25.0% to 73.5±23.2% to 78.8±19.7% to 81.3±20.6%, and 6MWT increased from 941.7±265.4 ft to 1154.1±248.2 ft to 1260.1±226.3 ft to 1294.0±257.9 ft. Both PF and 6MWT scores were statistically different across all Groups, apart from Groups 3 and 4. PA and ranks of Groups were highly significant predictors (p<.0001) for both PF and 6MWT. There was a positive dose-response relationship evident for both PF and 6MWT with increasing levels of PA. Low levels of PA appear to be an important indicator of poor functionality in older adults.

American journal of preventive medicine, 2015

Although many researchers agree that multiple determinants impact health, there is no consensus r... more Although many researchers agree that multiple determinants impact health, there is no consensus regarding the magnitude of the relative contributions of individual health factors to health outcomes. This study presents a method to empirically estimate the relative contributions of health behaviors, clinical care, social and economic factors, and the physical environment to health outcomes using nationally representative county-level data and statistical approaches that account for potential sources of bias. The analyses for this study were conducted in 2014. Data were from the 2010-2013 County Health Rankings & Roadmaps. Data covered 2,996 of 3,141 U.S. counties. Ordinary least squares modeling was used as a baseline model. Multilevel latent growth curve modeling was used to estimate the relative contributions of health factors to health outcomes while accounting for measurement errors and state-specific characteristics. Almost half of the variance of health outcomes was due to stat...

American Journal of Preventive Medicine, 2015

The County Health Rankings (CHR) provides data for nearly every county in the U.S. on four modifi... more The County Health Rankings (CHR) provides data for nearly every county in the U.S. on four modifiable groups of health factors, including healthy behaviors, clinical care, physical environment, and socioeconomic conditions, and on health outcomes such as length and quality of life. The purpose of this study was to empirically estimate the strength of association between these health factors and health outcomes and to describe the performance of the CHR model factor weightings by state. Data for the current study were from the 2015 CHR. Thirty-five measures for 45 states were compiled into four health factors composite scores and one health outcomes composite score. The relative contributions of health factors to health outcomes were estimated using hierarchical linear regression modeling in March 2015. County population size; rural/urban status; and gender, race, and age distributions were included as control variables. Overall, the relative contributions of socioeconomic factors, health behaviors, clinical care, and the physical environment to the health outcomes composite score were 47%, 34%, 16%, and 3%, respectively. Although the CHR model performed better in some states than others, these results provide broad empirical support for the CHR model and weightings. This paper further provides a framework by which to prioritize health-related investments, and a call to action for healthcare providers and the schools that educate them. Realizing the greatest improvements in population health will require addressing the social and economic determinants of health.

Journal of Physical Activity and Health

Background: To examine the effectiveness of the American College of Sports Medicine (ACSM) and th... more Background: To examine the effectiveness of the American College of Sports Medicine (ACSM) and the American Heart Association (AHA) resistance training (RT) guidelines to improve physical function and functional classification in older adults with reduced physical abilities. Methods: Twenty-five at-risk older adults were randomized to a control (CON = 13) or 8-week resistance training intervention arm (RT = 12). Progressive RT included 8 exercises for 1 set of 10 repetitions at a perceived exertion of 5-6 performed twice a week. Individuals were assessed for physical function and functional classification change (low, moderate or high) by the short physical performance battery (SPPB) and muscle strength measures. Results: Postintervention, significant differences were found between groups for SPPB-Chair Stand [F(1,22) = 9.14, P < .01, η= .29] and SPPB-Total Score [F(1,22) = 7.40, P < .05, η = .25]. Functional classification was improved as a result of the intervention with 83...