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American Journal of Men's Health logoLink to American Journal of Men's Health
. 2017 Feb 1;11(4):1019–1027. doi: 10.1177/1557988316689498

Geography, Race/Ethnicity, and Physical Activity Among Men in the United States

Elizabeth Kelley Sohn 1,✉, Tichelle Porch 1, Sarah Hill 1, Roland J Thorpe Jr 1
PMCID: PMC5675347  PMID: 28147893

Abstract

Engaging in regular physical activity reduces one’s risk of chronic disease, stroke, cardiovascular disease, and some forms of cancer. These preventive benefits associated with physical activity are of particular importance for men, who have shorter life expectancy and experience higher rates of chronic diseases as compared to women. Studies at the community and national levels have found that social and environmental factors are important determinants of men’s physical activity, but little is known about how regional influences affect physical activity behaviors among men. The objective of this study is to examine the association between geographic region and physical activity among men in the United States, and to determine if there are racial/ethnic differences in physical activity within these geographic regions. Cross-sectional data from men who participated the 2000 to 2010 National Health Interview Survey (N = 327,556) was used. The primary outcome in this study was whether or not men had engaged in sufficient physical activity to receive health benefits, defined as meeting the 2008 Physical Activity Guidelines for Americans. Race/ethnicity and geographic region were the primary independent variables. Within every region, Hispanic and Asian men had lower odds of engaging in sufficient physical activity compared to white men. Within the Northeast, South, and West, black men had lower odds of engaging in sufficient physical activity compared to white men. The key findings indicate that the odds of engaging in sufficient physical activity among men differ significantly between geographic regions and within regions by race/ethnicity.

Keywords: physical activity, men of color, geography, health inequality/disparity

Introduction

Engaging in sufficient physical activity is associated with multiple benefits to health and quality of life (Alves et al., 2016; Lee et al., 2012; U.S. Department of Health and Human Services, 1996; Wen et al., 2011). More specifically, regular physical activity is associated with multiple preventive benefits, such as lowering one’s risk of developing chronic diseases, stroke, cardiovascular disease, some forms of cancer, and can delay all-cause mortality (Garber et al., 2011; A. C. King et al., 1995). The 2008 Physical Activity Guidelines issued by the U.S. Department of Health and Human Services recommend that adults engage in at least 150 minutes (2 hours and 30 minutes) a week of moderate-intensity, or 75 minutes (1 hour and 15 minutes) a week of vigorous-intensity aerobic physical activity, or an equivalent combination (Physical Activity Guidelines Advisory Committee, 2008). The 2008 Physical Activity Guidelines note that most health benefits occur with at least 150 minutes (2 hours and 30 minutes) a week of moderate-intensity physical activity, such as brisk walking, and additional benefits may occur with more physical activity (Physical Activity Guidelines Advisory Committee, 2008). Currently, only one in five adults in the United States engages in sufficient physical activity to meet these guidelines (Carlson, Fulton, Schoenborn, & Loustalot, 2010; Centers for Disease Control and Prevention [CDC], 2013).

Physical activity behaviors differ by gender and are shaped according to socialization, norms, and expectations associated with gender; this underscores the importance of gender as a determinant of physical activity as a health behavior (Courtenay, 2000; Griffith, Gunter, & Allen, 2011; Kelley, Kandula, Kanaya, & Yen, 2016; Millen et al., 2005). The links between physical activity and chronic disease are of particular concern for men, who have shorter life expectancy and experience higher rates of chronic diseases such as coronary heart disease and type 2 diabetes as compared to women (Caperchione et al., 2012; Griffith et al., 2011; Thorpe, Wilson-Frederick, et al., 2013). Furthermore, physical inactivity has been identified as one of the main modifiable risk factors that contribute to poor health and noncommunicable disease among men (Bull & Bauman, 2011; Malcher, 2011; Newton, Griffith, Kearney, & Bennett, 2014). However, few studies have focused on examining the determinants of physical activity specifically among men.

While men are more likely than women to engage in sufficient physical activity to meet the recommendations specified in the 2008 Physical Activity Guidelines, disparities exist in physical activity behaviors between men of different racial/ethnic groups (Blackwell, Lucas, & Clarke, 2014). Compared to white men, men of minority racial/ethnic groups are less likely to report engaging in sufficient physical activity to meet the 2008 Physical Activity Guidelines (Blackwell et al., 2014; CDC, 1999; Crespo, Smit, Andersen, Carter-Pokras, & Ainsworth, 2000; U.S. Department of Health and Human Services, 1996). The factors responsible for these racial/ethnic disparities in physical activity among men are poorly understood (Abercrombie et al., 2008; Porch et al., 2015; Thorpe, Kelley, et al., 2015). Even after accounting for individual-level characteristics, race disparities in physical activity among men persist, despite national public health initiatives geared toward promoting physical activity (Crespo et al., 2000; Kruger, Kohl, & Miles, 2007; Marshall et al., 2007).

The economic and social standing of communities and families can determine access to important resources that influence physical activity behaviors. As such, the social and environmental conditions in which men live must be considered in explaining these important differences in physical activity behaviors (Wilson-Frederick et al., 2014). A growing body of literature has identified associations between the social, environmental, and geographic conditions in which people live and health disparities (Bleich, Thorpe, Sharif-Harris, Fesahazion, & LaVeist, 2010; Fang, Madhavan, Bosworth, & Alderman, 1998; Gaskin, Price, Brandon, & LaVeist, 2009; Kelley, Bowie, et al., 2016; LaVeist et al., 2008; LaVeist, Thorpe, Galarraga, Bower, & Gary-Webb, 2009; Robert, 1998; Roux et al., 2001; Thorpe, Bell, et al., 2015; Thorpe, Bowie, Wilson-Frederick, Coa, & LaVeist, 2013; Thorpe, Kelley, et al., 2015; Thorpe, Kennedy-Hendricks, et al., 2015). Geographic characteristics are particularly important to examine when interpreting disparities in physical activity, as substantial residential segregation by race/ethnicity exists in the United States, which contributes to variation in access to health-promoting resources such as places to participate in physical activity (Headen, 2005; LaVeist, 2005; LaVeist, Gaskin, & Trujillo, 2011; Williams & Collins, 2001). Multiple studies have suggested that at the community level, minority men are more likely to live in neighborhoods with more limited access to resources that promote physical activity (Gordon-Larsen, Nelson, Page, & Popkin, 2006; Taylor, Poston, Jones, & Kraft, 2006; Wilson, Kirtland, Ainsworth, & Addy, 2004).

Beyond the community level, there are likely to be regional variations in the social, political, and environmental forces that can influence physical activity, which has important implications for policy and programmatic interventions (Singh, Kogan, & van Dyck, 2008). Yet, research exploring the degree to which physical activity among men can vary by race and region is scarce. One study identified disparities in prevalence of leisure time physical activity by geographic region, but did not examine differences by race/ethnicity or gender (Reis et al., 2004). Another study also identified regional variation in physical activity and other healthy lifestyle behaviors, including nonsmoking, maintaining a healthy weight, and fruit/vegetable consumption but did not examine differences by race/ethnicity or gender (Troost, Rafferty, Luo, & Reeves, 2012). Another study identified regional differences in built environment and neighborhood walkability (K. E. King & Clarke, 2015), which are important determinants of physical activity but did not examine differences by race/ethnicity or gender. These regional differences in the built environment may contribute to regional variation in racial/ethnic disparities among men. Identifying subpopulations to target for preventive intervention must rely on a more nuanced understanding of the areas where disparities are most pronounced. Thus, the objective of this study was to examine whether the odds of engaging in sufficient physical activity to meet the 2008 Physical Activity Guidelines vary by geographic region and by race/ethnicity through an analysis of data drawn from a nationally representative sample of men in the United States.

Method

Data Description

This study utilized cross-sectional data from the National Health Interview Survey (NHIS), conducted annually by the National Center for Health Statistics. The NHIS is a nationally representative sample of the United States noninstitutionalized population from all 50 states and the District of Columbia and oversamples blacks, Hispanics, and Asians. The survey covers demographic characteristics, health behaviors and conditions, functional limitations, cancer screening, and health care access and utilization. The use of sampling weights yielded representative population estimates and adjusts for nonresponse. Detailed information regarding NHIS is reported elsewhere (J. Pleis & Lucas, 2009; J. R. Pleis, Schiller, & Benson, 2003).

This study combines data from the 2000 to 2010 NHIS and no major changes to the questions used in this analysis were made during that time frame. Based on the information in the survey description documentation, this analysis accounted for the changes that occurred in questions related to smoking and drinking behaviors in 2004, changes to NHIS survey weights in 2006, and changes to income questions in 2007.

This study combines data from the 2000 to 2010 NHIS. Men who responded to questions regarding their race/ethnicity, geographic region in which they lived, height and weight, and physical activity behaviors and who were aged 18 and older were included in these analyses. The resulting analytic sample consisted of 327,556 male adults.

Measures

The primary outcome in this study was whether or not men had engaged in sufficient physical activity for health benefits through any means, including leisure time physical activity, walking for transportation, and occupational physical activity, as self-reported in the NHIS questionnaire. The 2008 Physical Activity Guidelines suggest that most health benefits occur with at least 150 minutes (2 hours and 30 minutes) a week of moderate-intensity physical activity; therefore, engaging in sufficient physical activity was defined as completing at least 150 minutes/week of moderate-intensity aerobic activity or its equivalent to meet the 2008 Physical Activity Guidelines (Physical Activity Guidelines Advisory Committee, 2008).

Race/ethnicity and geographic region were the primary independent variables. The states in which men reported they lived were categorized into the regions Northeast, Midwest, South, and West. Table 1 displays this classification. Race/ethnicity was reported by men as either white, black/African American, Asian, and their ethnicity as Hispanic or not Hispanic. Race/ethnicity was then recoded as non-Hispanic white, non-Hispanic black, Hispanic, or Asian.

Table 1.

Regional Categorization of United States in the National Health Interview Survey, 2000 to 2010.

Region States included
Northeast Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont
Midwest Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin
South Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia
West Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming
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Covariates included age (years), married (1 = yes; 0 = no), body mass inded (kg/m2), smoking status (0 = never, 1 = any level of former smoking, 2 = any level of current smoking), drinking status (0 = never, 1 = any level of former drinking, 2 = any level of current drinking), income level (0 = <$35,000, 1 = $35,000-75,000, 2 = >$75,000), and education level (0 = less than high school graduate; 1 = high school graduate/GED; 2 = more than high school graduate), and number of chronic conditions (0, 1, 2, 3+).

Statistical Analysis

Mean and proportional differences were calculated using analysis of variance and chi-square tests to examine demographic and health-related factors between men living in different regions of the United States. Logistic regressions were specified for the total sample and by geographic region to determine the age-adjusted proportions of health-related characteristics. Health-related characteristics were modeled as a function of geographic region after adjusting for age and survey year. Logistic regression models were used for multivariate analysis to examine the association among race/ethnicity, region, and physical activity, after adjusting for covariates described above and survey year. In the overall model comparing regions, an interaction term between race/ethnicity and region was included and identified as significant (p < .001). Analysis was therefore stratified by region and racial/ethnic differences in physical activity within each geographic region were examined. To account for the complex survey sampling design of NHIS and ensure correct standard errors, survey procedures were used in the statistical models. All p values <.05 were considered statistically significant and all tests were two-sided. All analyses were conducted using STATA 13 (StataCorp LP, 2013).

Results

The distribution of characteristics of men who participated in the 2000 to 2010 NHIS by region is provided in Table 2. Of the 327,556 male adults in the sample, 56,092 lived in the Northeast (17%), 69,925 lived in the Midwest (21%), 118,186 lived in the South (36%), and 83,353 lived in the West (25%). Additionally, of the men in the sample, 200,163 were non-Hispanic white (72%), 40,211 were non-Hispanic black (11%), 71,416 were Hispanic (14%), and 15,766 were non-Hispanic Asian (4%). The mean age for the sample was 44.8 years. In the sample, 66% of men were married, 27% had income below $35,000, and 17% had less than a high school graduate degree. With respect to demographic variables, there were also differences by region. Men in the Northeast were older than men living in other regions. The largest proportion of white men lived in the Midwest, while the largest proportions of Hispanic and Asian men lived in the West. The largest proportion of men reporting incomes greater than $75,000 was in the Northeast, while the largest proportion of men reporting incomes less than $35,000 was in the South. The largest proportion of men reporting that they had obtained less than their high school graduate degree/GED was in the South, while the largest proportion of men reporting that they had obtained their high school graduate degree/GED was in the Midwest. Across regions, there were similar proportions of men who reported being married, having annual household incomes ranging between $35,000 and $75,000, and having obtained more than a high school degree.

Table 2.

Distribution of Select Demographic Characteristics of Men Aged 18 and Older by Geographic Region, National Health Interview Survey, 2000 to 2010.

Geographic region
 p Value
Overall sample (N = 327,556) Northeast (N = 56,092) Midwest (N = 69,925) South (N = 118,186) West (N = 83,353)
Age, mean ± SE 44.8 ± 0.1 46.1 ± 0.2 44.6 ± 0.2 44.6 ± 0.2 44.2 ± 0.2 <.001
Race (%)
 White 71.8 76.8 84.4 67.2 61.1 <.001
 Black 10.6 8.8 8.0 17.1 4.1 .402
 Hispanic 13.5 10.0 5.3 13.3 26.2 <.001
 Asian 4.1 4.4 2.3 2.4 8.7 <.001
Married (%) 65.7 65.2 65.9 66.1 65.2 .844
Income (%)
 <$35,000 27.3 23.5 26.3 30.6 26.0 <.001
 $35,000-$75,000 29.5 27.1 31.4 29.7 29.2 .057
 >$75,000 20.0 22.7 20.2 17.8 21.0 <.001
 Did not respond 23.2 26.7 22.2 21.9 23.8 <.001
Education level
 Less than high school graduate 16.7 14.0 13.0 19.3 18.9 <.001
 High school graduate/GED 28.8 30.2 32.2 29.1 23.4 <.001
 More than high school graduate 54.5 55.6 54.7 51.6 57.8 .542
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Note. Mean and proportional differences were calculated using analysis of variance and chi-square tests.

Table 3 provides the distribution of age-adjusted proportions for health-related characteristics overall and by region. In the total sample, 48% of men reported engaging in sufficient physical activity, 27% of men were obese, 51% had never smoked, and 16% had never drank alcohol. Overall, 71% of men reported that they had no chronic conditions. Across regions, there were similar proportions of men who reported engaging in sufficient physical activity, being overweight, and having chronic conditions. The largest proportion of obese men lived in the Northeast while the proportion of men of healthy weight status was largest among men in the West. The proportions of men who never smoked or formerly smoked were largest in the West, while the proportion of current smokers was largest in the Northeast. The proportion of current drinkers was largest among men in the Northeast, while the proportions of former drinkers and never drinkers were largest in the West.

Table 3.

Age-Adjusted Distribution of Health Related Characteristics of Men Aged 18 and Older by Geographic Region, National Health Interview Survey, 2000 to 2010.

Geographic region
 p Value
Overall sample (N = 327,556) Northeast (N = 56,092) Midwest (N = 69,925) South (N = 118,186) West (N = 83,353)
Sufficient physical activity (%) 47.7 48.2 47.9 47.6 47.4 .287
Weight status (%)
 Underweight (BMI < 18.5) 9.1 9.1 9.1 9.1 9.1 .965
 Normal (18.5 ≤ BMI < 25) 30.4 29.7 30.1 30.6 31.0 .011
 Overweight (25 ≤ BMI < 30) 41.8 41.3 41.6 41.9 42.1 .081
 Obese (BMI ≥ 30) 26.5 27.7 27.0 26.3 25.6 <.001
Smoking status (%)
 Never 51.0 48.8 50.1 51.4 52.7 <.001
 Former 22.2 23.1 22.6 22.1 21.6 <.001
 Current 23.3 24.6 23.8 23.1 22.4 <.001
Drinking status (%)
 Never 16.1 13.0 14.7 16.7 18.8 <.001
 Former 12.8 11.8 12.4 13.0 13.6 <.001
 Current 69.3 73.6 71.1 68.5 65.8 <.001
Number of chronic conditions
 None (%) 70.5 70.3 70.4 70.6 70.7 .481
 One (%) 19.6 19.9 19.7 19.5 19.3 .185
 Two (%) 5.0 5.0 5.0 5.0 5.1 .531
 Three or More (%) 2.4 2.3 2.4 2.4 2.4 .705
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Note. BMI = body mass index. Logistic regressions were specified for the total sample and by geographic region to ascertain differences in age-adjusted proportions of health-related characteristics.

When examining the relationship between region and engaging in sufficient physical activity, differences were observed. Compared to men living in the Northeast, men living in the West had greater odds of engaging in sufficient physical activity (odds ratio [OR] = 1.12, 95% confidence interval [CI; 1.04, 1.20]), men living in the Midwest had lower odds of engaging in sufficient physical activity (OR = 0.86, 95% CI [0.81, 0.92]), and men living in the South also had lower odds of engaging in sufficient physical activity (OR = 0.83, 95% CI [0.78, 0.89]) after adjusting for age, marital status, income, education, smoking and drinking status, chronic conditions, and race/ethnicity (data not displayed).

Table 4 reports the association between race, region, and odds of achieving the 2008 Guidelines for Physical Activity. Within every region, Hispanic and Asian men had lower odds of meeting federal recommendations for physical activity compared to men. Within the Northeast, South, and West, black men had lower odds of meeting federal recommendations for physical activity compared to white men. Within the Midwest, black men and white men had similar odds of meeting the federal recommendations for physical activity.

Table 4.

Association Between Race/Ethnicity and Odds of Achieving 2008 Guidelines for Physical Activity Guidelines Within Geographic Region Among Men Aged 18 and Older, National Health Interview Survey, 2000 to 2010.

Odds ratio (95% confidence interval)
Northeast Midwest South West
White Reference Reference Reference Reference
Black 0.82 [0.72, 0.92] 0.87 [0.76, 1.00] 0.92 [0.86, 0.99] 0.83 [0.72, 0.96]
Hispanic 0.58 [0.52, 0.66] 0.90 [0.78, 1.03] 0.83 [0.77, 0.90] 0.66 [0.60, 0.72]
Asian 0.44 [0.37, 0.53] 0.73 [0.58, 0.91] 0.72 [0.62, 0.84] 0.70 [0.62, 0.79]
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Note. Models included race, survey year, age, marital status, insurance status, household income, education level, body mass index, smoking and drinking status, and number of chronic conditions. Within each region, white men were the reference group against which men of other races/ethnicities are compared.

Discussion

The objective of this study was to determine whether the odds of engaging in sufficient physical activity among men in the United States, as defined by meeting the 2008 Guidelines, vary by geographic region and by race/ethnicity. The key findings indicate that the odds of engaging in sufficient physical activity among men differ significantly between geographic regions and within regions by race/ethnicity. Compared to men living in the Northeast, men living in the West had greater odds of engaging in sufficient physical activity, while men living in the Midwest and South had lower odds of engaging in sufficient physical activity after adjusting for age, marital status, income, education, smoking and drinking status, chronic conditions, and race/ethnicity. In examining differences in odds of engaging in sufficient physical activity within regions between men of different races/ethnicities, black men have lower odds of engaging in sufficient physical activity than white men in the South and West, while Hispanic men have lower odds of engaging in sufficient physical activity in the South, West, and Northeast. Asian men have lower odds of engaging in sufficient physical activity than white men in all regions.

The findings presented in this study that indicate regional variation in physical activity are consistent with those presented in other studies, which have identified higher prevalence of physical activity in the West and lower prevalence in the South, but which did not present results separately by gender or race/ethnicity (Reis et al., 2004; Troost et al., 2012). To the authors’ knowledge, this is the first study that has examined differences in physical activity among men by region and by race/ethnicity. Ultimately, these results suggest that there may be significant differences in physical activity behaviors between regions within the United States, and that those differences also vary by race/ethnicity.

Although few studies have examined regional differences in racial/ethnic disparities in physical activity, studies assessing community-level factors that affect physical activity provide insight into why disparities in physical activity may vary by region. Multiple studies have suggested that important determinants of physical activity vary by region, such as socioeconomic factors, including median household income, education, and racial makeup of neighborhoods, as well as environmental factors, such as community walkability and access to physical-activity promoting facilities (Reis et al., 2004; Troost et al., 2012). Studies have suggested that minority men more often live in places where they have less access to physical activity-promoting resources, as compared to white men, which may contribute to racial/ethnic disparities in physical activity among men (Estabrooks, Lee, & Gyurcsik, 2003; Powell, Slater, Chaloupka, & Harper, 2006). The findings presented in this study suggest that beyond this, there are regional differences in the extent to which racial/ethnic disparities in physical activity exist among men.

What remains most unclear is what drives these inter-region differences in disparities in physical activity among men. For example, this analysis suggests that black men in the South and West are less likely than white men in those regions to engage in sufficient physical activity. One explanation for this difference is that educational attainment and socioeconomic status, which are important correlates of physical activity behaviors, are lower in the South for black men compared to their white counterparts (Gillum & Ingram, 1996; MacDonald & Turner, 2015; Reis et al., 2004). Thus, the lower socioeconomic status of black men in the South and West regions may play a role in regional disparities in physical activity levels identified in this study. Little is known, however, about what is different about the Midwest, where white, black, and Hispanic men all have similar odds of engaging in sufficient physical activity, or why Asian men have lower odds of engaging in physical activity relative to white men in all regions of the United States. Investigating the interplay of these factors and how they contribute to regional and racial/ethnic variation in physical activity is an important area for future research.

There are several limitations of this study that may affect interpretations. First, NHIS is a cross-sectional survey and thus, causal inferences cannot be made. Furthermore, because NHIS relies on self-reported data, the covariates in our models and levels of physical activity may include some bias, which may vary by region and/or by race/ethnicity (Le et al., 2014). In addition, the federal guidelines for physical activity include only leisure time physical activity and excludes forms of work-related physical activity; this may contribute to lower reports of physical activity for men of lower socioeconomic status who are in blue-collar occupations, which may vary by region and race/ethnicity (Marshall et al., 2007; Sallis & Saelens, 2000). Another limitation of this study is that it did not account for whether men lived in rural versus urban areas, which may vary by region and would likely affect levels of physical activity among men (Reis et al., 2004; Zhang et al., 2014).

Despite these limitations, there are several strengths associated with this study. First, this study’s focus on men enabled the authors to examine the relationship of geographic region and physical activity in an understudied and important population and add to the growing body of literature. Additionally, this study accounted for a wide array of upstream social determinants of physical activity, such as income level and educational attainment in all regions in the United States across men of various races/ethnicities. Furthermore, this study used 11 years of NHIS data, which afforded a large sample size with ample statistical power.

Physical activity behaviors are influenced by a complex interaction of policy, environmental, intrapersonal, and interpersonal factors (Reis et al., 2004). Thus, to promote increased physical activity at a population level, strategies must target improvements to the social and physical environmental contexts for physical activity (Kumanyika et al., 2008). In documenting the regional and racial/ethnic variations in physical activity among men, the findings of this study contribute to a more nuanced understanding of the inter- and intraregional forces that may contribute to disparities in physical activity. In addition, identifying the areas where degree of disparity is highest can be used to inform resource allocation for the implementation of interventions to increase physical activity among men in high-risk geographic areas and of certain racial/ethnic backgrounds. Future research should aim to provide further exploration of how historical, social, political, and environmental contribute to disparities in physical activity among men at the inter- and intraregional levels.

Footnotes

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research conducted by the last author was supported by a grant from the National Institute on Minority Health and Health Disparities (P60MD000214) and a grant from Pfizer, Inc.

References

  1. Abercrombie L. C., Sallis J. F., Conway T. L., Frank L. D., Saelens B. E., Chapman J. E. (2008). Income and racial disparities in access to public parks and private recreation facilities. American Journal of Preventive Medicine, 34, 9-15. [DOI] [PubMed] [Google Scholar]
  2. Alves A. J., Viana J. L., Cavalcante S. L., Oliveira N. L., Duarte J. A., Mota J., . . . Ribeiro F. (2016). Physical activity in primary and secondary prevention of cardiovascular disease: Overview updated. World Journal of Cardiology, 8, 575-583. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Blackwell D. L., Lucas J. W., Clarke T. C. (2014). Summary health statistics for U.S. adults: National Health Interview Survey, 2012. Vital and Health Statistics: Series 10, 260, 1-161. [PubMed] [Google Scholar]
  4. Bleich S. N., Thorpe R. J., Jr., Sharif-Harris H., Fesahazion R., LaVeist T. A. (2010). Social context explains race disparities in obesity among women. Journal of Epidemiology and Community Health, 64, 465-469. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bull F. C., Bauman A. E. (2011). Physical inactivity: The “Cinderella” risk factor for noncommunicable disease prevention. Journal of Health Communication, 16(Suppl. 2), 13-26. [DOI] [PubMed] [Google Scholar]
  6. Caperchione C. M., Vandelanotte C., Kolt G. S., Duncan M., Ellison M., George E., Mummery W. K. (2012). What a man wants: Understanding the challenges and motivations to physical activity participation and healthy eating in middle-aged Australian men. American Journal of Men’s Health, 6, 453-461. doi: 10.1177/1557988312444718 [DOI] [PubMed] [Google Scholar]
  7. Carlson S. A., Fulton J. E., Schoenborn C. A., Loustalot F. (2010). Trend and prevalence estimates based on the 2008 physical activity guidelines for Americans. American Journal of Preventive Medicine, 39, 305-313. [DOI] [PubMed] [Google Scholar]
  8. Centers for Disease Control and Prevention. (1999). Neighborhood safety and the prevalence of physical inactivity—selected states, 1996. Morbidity and Mortality Weekly Report, 48, 143-146. [PubMed] [Google Scholar]
  9. Centers for Disease Control and Prevention. (2013). Adult participation in aerobic and muscle-strengthening physical activities: United States, 2011 Morbidity and Mortality Weekly Report, 62, 326-330. doi:mm6217a2 [PMC free article] [PubMed] [Google Scholar]
  10. Courtenay W. H. (2000). Constructions of masculinity and their influence on men’s well-being: A theory of gender and health. Social Science & Medicine, 50, 1385-1401. [DOI] [PubMed] [Google Scholar]
  11. Crespo C. J., Smit E., Andersen R. E., Carter-Pokras O., Ainsworth B. E. (2000). Race/ethnicity, social class and their relation to physical inactivity during leisure time: Results from the third national health and nutrition examination survey, 1988-1994. American Journal of Preventive Medicine, 18(1), 46-53. [DOI] [PubMed] [Google Scholar]
  12. Estabrooks P. A., Lee R. E., Gyurcsik N. C. (2003). Resources for physical activity participation: Does availability and accessibility differ by neighborhood socioeconomic status? Annals of Behavioral Medicine, 25, 100-104. [DOI] [PubMed] [Google Scholar]
  13. Fang J., Madhavan S., Bosworth W., Alderman M. H. (1998). Residential segregation and mortality in New York City. Social Science & Medicine, 47, 469-476. [DOI] [PubMed] [Google Scholar]
  14. Garber C. E., Blissmer B., Deschenes M. R., Franklin B. A., Lamonte M. J., Lee I. M., . . . American College of Sports Medicine. (2011). American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Medicine and Science in Sports and Exercise, 43, 1334-1359. doi: 10.1249/MSS.0b013e318213fefb [DOI] [PubMed] [Google Scholar]
  15. Gaskin D. J., Price A., Brandon D. T., LaVeist T. A. (2009). Segregation and disparities in health services use. Medical Care Research and Review, 66, 578-589. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Gillum R. F., Ingram D. D. (1996). Relation between residence in the Southeast region of the United States and stroke incidence. The NHANES I Epidemiologic Followup Study. American Journal of Epidemiology, 144, 665-673. [DOI] [PubMed] [Google Scholar]
  17. Gordon-Larsen P., Nelson M. C., Page P., Popkin B. M. (2006). Inequality in the built environment underlies key health disparities in physical activity and obesity. Pediatrics, 117, 417-424. [DOI] [PubMed] [Google Scholar]
  18. Griffith D. M., Gunter K., Allen J. O. (2011). Male gender role strain as a barrier to African American men’s physical activity. Health Education & Behavior, 38, 482-491. doi: 10.1177/1090198110383660 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Headen S. (2005). Minority populations and health: An introduction to health disparities in the United States. Preventing Chronic Disease, 2(4), A17. [Google Scholar]
  20. Kelley E. A., Bowie J. V., Griffith D. M., Bruce M., Hill S., Thorpe R. J., Jr. (2016). Geography, race/ethnicity, and obesity among men in the United States. American Journal of Men’s Health, 10, 228-236. doi: 10.1177/1557988314565811 [DOI] [PubMed] [Google Scholar]
  21. Kelley E. A., Kandula N., Kanaya A., Yen I. H. (2016) Neighborhood walkability and walking for transport among south Asians in the MASALA study. Journal of Physical Activity & Health, 13, 514–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. King A. C., Jeffery R. W., Fridinger F., Dusenbury L., Provence S., Hedlund S. A., Spangler K. (1995). Environmental and policy approaches to cardiovascular disease prevention through physical activity: Issues and opportunities. Health Education & Behavior, 22, 499-511. [DOI] [PubMed] [Google Scholar]
  23. King K. E., Clarke P. J. (2015). A disadvantaged advantage in walkability: Findings from socioeconomic and geographical analysis of national built environment data in the United States. American Journal of Epidemiology, 181(1), 17-25. doi: 10.1093/aje/kwu310 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Kruger J., Kohl H., III, Miles I. (2007). Prevalence of regular physical activity among adults—United States, 2001 and 2005. Morbidity and Mortality Weekly Report, 56, 1209-1212. [PubMed] [Google Scholar]
  25. Kumanyika S. K., Obarzanek E., Stettler N., Bell R., Field A. E., Fortmann S. P., . . . American Heart Association Council on Epidemiology and Prevention, Interdisciplinary Committee for Prevention. (2008). Population-based prevention of obesity: The need for comprehensive promotion of healthful eating, physical activity, and energy balance: A scientific statement from American Heart Association Council on Epidemiology and Prevention, Interdisciplinary Committee for Prevention (formerly the Expert Panel on Population and Prevention Science). Circulation, 118, 428-464. doi: 10.1161/CIRCULATIONAHA.108.189702 [DOI] [PubMed] [Google Scholar]
  26. LaVeist T. A. (2005). Disentangling race and socioeconomic status: A key to understanding health inequalities. Journal of Urban Health, 82(2 Suppl. 3), iii26-iii34. doi: 10.1093/jurban/jti061 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. LaVeist T. A., Gaskin D., Trujillo A. (2011). Segregated spaces, risky places: The effects of racial segregation on health inequalities. Washington, DC: Joint Center for Political and Economic Studies. [Google Scholar]
  28. LaVeist T. A., Thorpe R., Jr., Bowen-Reid T., Jackson J., Gary T., Gaskin D., Browne D. (2008). Exploring health disparities in integrated communities: Overview of the EHDIC study. Journal of Urban Health, 85(1), 11-21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. LaVeist T. A., Thorpe R. J., Jr., Galarraga J. E., Bower K. M., Gary-Webb T. L. (2009). Environmental and socio-economic factors as contributors to racial disparities in diabetes prevalence. Journal of General Internal Medicine, 24, 1144-1148. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Le A., Judd S. E., Allison D. B., Oza-Frank R., Affuso O., Safford M. M., . . . Howard G. (2014). The geographic distribution of obesity in the US and the potential regional differences in misreporting of obesity. Obesity, 22, 300-306. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Lee I. M., Shiroma E. J., Lobelo F., Puska P., Blair S. N., Katzmarzyk P. T., Lancet Physical Activity Series Working Group. (2012). Effect of physical inactivity on major non-communicable diseases worldwide: An analysis of burden of disease and life expectancy. Lancet, 380, 219-229. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. MacDonald G., Turner M. (2015). Poverty, race, and place: Map your metro. Retrieved from http://www.urban.org/urban-wire/poverty-race-and-place-map-your-metro
  33. Malcher G. (2011). The state of men’s health in Europe. British Medical Journal, 343, d7054. doi: 10.1136/bmj.d7054 [DOI] [PubMed] [Google Scholar]
  34. Marshall S. J., Jones D. A., Ainsworth B. E., Reis J. P., Levy S. S., Macera C. A. (2007). Race/ethnicity, social class, and leisure-time physical inactivity. Medicine and Science in Sports and Exercise, 39(1), 44-51. doi: 10.1249/01.mss.0000239401.16381.37 [DOI] [PubMed] [Google Scholar]
  35. Millen B. E., Quatromoni P. A., Pencina M., Kimokoti R., Nam B., Cobain S., . . . D’Agostino R. B. (2005). Unique dietary patterns and chronic disease risk profiles of adult men: The Framingham nutrition studies. Journal of the American Dietetic Association, 105, 1723-1734. [DOI] [PubMed] [Google Scholar]
  36. Newton R., Griffith D., Kearney W., Bennett G. (2014). A systematic review of weight loss, physical activity and dietary interventions involving African American men. Obesity Reviews, 15(Suppl. 4), 93-106. [DOI] [PubMed] [Google Scholar]
  37. Physical Activity Guidelines Advisory Committee. (2008). Physical Activity Guidelines Advisory Committee report, 2008. Washington, DC: U.S. Department of Health and Human Services. [Google Scholar]
  38. Pleis J., Lucas J. (2009). Summary health statistics for US adults, National Health Interview Survey, 2007. Vital and Health Statistics: Series 10, 240, 1-159. [PubMed] [Google Scholar]
  39. Pleis J. R., Schiller J. S., Benson V. (2003). Summary health statistics for U.S. adults: National Health Interview Survey, 2000. Vital Health and Statistics: Series 10, 215, 1-132. [PubMed] [Google Scholar]
  40. Porch T. C., Bell C. N., Bowie J. V., Usher T., Kelly E. A., LaVeist T. A., Thorpe R. J., Jr. (2015). The role of marital status in physical activity among African American and white men. American Journal of Men’s Health, 10, 526-532. doi:1557988315576936 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Powell L. M., Slater S., Chaloupka F. J., Harper D. (2006). Availability of physical activity-related facilities and neighborhood demographic and socioeconomic characteristics: A national study. American Journal of Public Health, 96, 1676-1680. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Reis J. P., Bowles H. R., Ainsworth B. E., Dubose K. D., Smith S., Laditka J. N. (2004). Nonoccupational physical activity by degree of urbanization and U.S. geographic region. Medicine and Science in Sports and Exercise, 36, 2093-2098. doi:00005768-200412000-00013 [DOI] [PubMed] [Google Scholar]
  43. Robert S. A. (1998). Community-level socioeconomic status effects on adult health. Journal of Health and Social Behavior, 39(1), 18-37. [PubMed] [Google Scholar]
  44. Roux A. V. D., Merkin S. S., Arnett D., Chambless L., Massing M., Nieto F. J., . . . Watson R. L. (2001). Neighborhood of residence and incidence of coronary heart disease. New England Journal of Medicine, 345, 99-106. [DOI] [PubMed] [Google Scholar]
  45. Sallis J. F., Saelens B. E. (2000). Assessment of physical activity by self-report: Status, limitations, and future directions. Research Quarterly for Exercise and Sport, 71(2 Suppl.), S1-S14. [PubMed] [Google Scholar]
  46. Singh G. K., Kogan M. D., van Dyck P. C. (2008). A multilevel analysis of state and regional disparities in childhood and adolescent obesity in the United States. Journal of Community Health, 33(2), 90-102. [DOI] [PubMed] [Google Scholar]
  47. StataCorp LP. (2013). Stata statistical software (Release 13 ed). College Station, TX: Author. [Google Scholar]
  48. Taylor W. C., Poston W. S. C., Jones L., Kraft M. K. (2006). Environmental justice: Obesity, physical activity, and healthy eating. Journal of Physical Activity and Health, 3(Suppl. 1), S30. [DOI] [PubMed] [Google Scholar]
  49. Thorpe R. J., Jr., Bell C. N., Kennedy-Hendricks A., Harvey J., Smolen J. R., Bowie J. V., LaVeist T. A. (2015). Disentangling race and social context in understanding disparities in chronic conditions among men. Journal of Urban Health, 92(1), 83-92. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Thorpe R. J., Jr., Bowie J. V., Wilson-Frederick S. M., Coa K. I., LaVeist T. A. (2013). Association between race, place, and preventive health screenings among men: Findings from the Exploring Health Disparities in Integrated Communities study. American Journal of Men’s Health, 7, 220-227. doi: 10.1177/1557988312466910; 10.1177/1557988312466910 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Thorpe R. J., Jr., Kelley E., Bowie J. V., Griffith D. M., Bruce M., LaVeist T. (2015). Explaining racial disparities in obesity among men: Does place matter? American Journal of Men’s Health, 9, 464-472. doi:1557988314551197 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Thorpe R. J., Jr., Kennedy-Hendricks A., Griffith D. M., Bruce M. A., Coa K., Bell C. N., . . . LaVeist T. A. (2015). Race, social and environmental conditions, and health behaviors in men. Family & Community Health, 38, 297-306. doi: 10.1097/FCH.0000000000000078 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Thorpe R. J., Jr., Wilson-Frederick S. M., Bowie J. V., Coa K., Clay O. J., LaVeist T. A., Whitfield K. E. (2013). Health behaviors and all-cause mortality in African American men. American Journal of Men’s Health, 7(4 Suppl.), 8S-18S. doi: 10.1177/1557988313487552 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Troost J. P., Rafferty A. P., Luo Z., Reeves M. J. (2012). Temporal and regional trends in the prevalence of healthy lifestyle characteristics: United States, 1994-2007. American Journal of Public Health, 102, 1392-1398. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. U.S. Department of Health and Human Services. (1996). Physical activity and health: A report of the Surgeon General. Atlanta, GA: Author. [Google Scholar]
  56. Wen C. P., Wai J. P. M., Tsai M. K., Yang Y. C., Cheng T. Y. D., Lee M. C., . . . Wu X. (2011). Minimum amount of physical activity for reduced mortality and extended life expectancy: A prospective cohort study. Lancet, 378, 1244-1253. [DOI] [PubMed] [Google Scholar]
  57. Williams D. R., Collins C. (2001). Racial residential segregation: A fundamental cause of racial disparities in health. Public Health Reports, 116, 404-416. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Wilson D. K., Kirtland K. A., Ainsworth B. E., Addy C. L. (2004). Socioeconomic status and perceptions of access and safety for physical activity. Annals of Behavioral Medicine, 28(1), 20-28. [DOI] [PubMed] [Google Scholar]
  59. Wilson-Frederick S. M., Thorpe R. J., Jr., Bell C. N., Bleich S. N., Ford J. G., LaVeist T. A. (2014). Examination of race disparities in physical inactivity among adults of similar social context. Ethnicity & Disease, 24, 363-369. [PMC free article] [PubMed] [Google Scholar]
  60. Zhang X., Holt J. B., Lu H., Onufrak S., Yang J., French S. P., Sui D. Z. (2014). Neighborhood commuting environment and obesity in the United States: An urban–rural stratified multilevel analysis. Preventive Medicine, 59, 31-36. [DOI] [PubMed] [Google Scholar]

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