Correlation Between Prevalence of Diabetes and Lack of Physical Activity in Alabama

By Ajay P. Peddada
2013, Vol. 5 No. 01 | pg. 1/1


Alabama was cited among the states with greatest prevalence of diabetes for the past five years (Diabetes Surveillance, 2009). There is considerable variation between the counties of Alabama with regards to prevalence of diabetes (Diabetes Surveillance, 2009). Physical inactivity besides diet and obesity is cited as a factor for the cause and progression of diabetes [2]. This study attempts to determine a connection between these observations by comparing the association between physical inactivity and diabetes in urban and rural populations of Alabama

Methods: The center for Disease Control (CDC) presented the 2009 Census data based on self reported surveys for Alabama counties with regards to Diabetes. We analyzed their data to determine the means and correlation coefficient for Physical Inactivity and Diabetes in two groups of counties of Alabama – the ten most populous (predominantly “urban”) and the ten least populated (predominantly “rural”).

Results: The mean prevalence of diabetes in the urban population was 11.7 and that for the rural population was 13.35. The mean physical inactivity index (low being more active) for the urban group was 36 and that for the rural group was 27. Both these differences between the means were not statistically significant. On the other hand, diabetes in the most populous counties was positively correlated with physical inactivity (correlation coefficient, r = 0.77 at a confidence level of 1 %) and it was not correlated in the least populous counties (r = 0.099, not significant).

Discussion: The absence of any strong correlation between the physical inactivity and diabetes prevalence in the least populous counties suggests that there may be other factors that influence diabetes in this group. There may be a difference between rural and more urban counties in Alabama with regards to the factors associated with diabetes.

Conclusions: Rural counties group exhibit almost no correlation between physical inactivity and prevalence of diabetes unlike the most populous group. This suggests that there may be a fundamental difference between the rural and urban populations with regards to factors associated with diabetes and this should be explored further to confirm and expand on this finding.


Alabama was listed among the top five states in terms of prevalence of Diabetes in the nation [1]. Factors such as diet, obesity, and physical inactivity are cited in literature as factors for the cause and progression of diabetes [2, 3, 4, 5]. It is also noted that there is considerable variation between counties of Alabama with regards to the prevalence of diabetes in that state [1]. This prompts the following question: Is the difference between the counties due to any of the factors listed above, namely, diet, obesity, physical inactivity, or is it due to some other fundamental difference between the counties?


To correlate physical inactivity and prevalence of diabetes in the ten most populated and the ten least populated counties in Alabama. We assign the label of urban for the most populous states and rural for the least populous states for convenience.


The average prevalence of diabetes and physical inactivity data for the counties of Alabama was derived from the census data for 2009. This was presented by Center for Disease Control (CDC) [1]. This data was from a self-assessment survey of the residents of the counties of Alabama. Specifically, Diabetes was assessed as follows. Respondents were considered to have diabetes if they responded "yes" to the question, "Has a doctor ever told you that you have diabetes?" Women who indicated that they only had diabetes during pregnancy were not considered to have diabetes.Physical inactivity was assessed by a CDC questionnaire as follows. Respondents were considered to be physically inactive if they answered "no" to the question, "During the past month, other than your regular job, did you participate in any physical activities or exercises such as running, calisthenics, golf, gardening, or walking for exercise?"

We calculated the averages and correlation coefficient between these two parameters for the urban (ten most populous) and relatively rural (ten least populated) counties of Alabama.


Detailed data on prevalence of diabetes and self-reported physical inactivity for the counties of Alabama as gathered by the CDC is presented in Tables 1 and 2, respectively (Appendix). The mean prevalence of diabetes in the urban population was 11.7 and that for the rural population was 13.35. This difference was not statistically significant by Student t-test. There was a lower physical inactivity in the less populated counties group (index of 27) compared to the more populated counties group (36). Again, this difference was not statistically significant.

However, the correlation coefficient (R) for the association between physical inactivity and prevalence of diabetes for the most populous counties was 0.77 (at 1 % significance) and that for the least populous counties was less than 0.099 (not significant). Standard statistical methods were followed [6]. The linear regression with y-intercept, slope, and square of the Pearson Product moment correlation coefficient (R2) are displayed in Figure 1, below:

Figure 1: Linear Regression and Scatter Plot of Prevalence of Diagnosed Diabetes and Physical Inactivity Index in the Ten Most Populated and Ten Least Populated Counties of Alabama

Figure 1


Clearly, this study has limitations. One, physical inactivity of individuals may not be truly accurate due to the variability in self-assessment. Even the prevalence in diabetes based on self-reporting may not be accurate. Second, physical inactivity of a population in a given time period could not have caused diabetes in that same time period. In other words, physical inactivity may have occurred in some individuals and diabetes may have been noted in others. Also, this study does not distinguish between Type I and Type II diabetes.

Despite these two obvious limitations, the present study still has an interesting finding. Physical inactivity was correlated positively with prevalence of diabetes in the more populous counties which is consistent with numerous other population studies [2, 3, 4, 5]. However, the absence of a similar correlation in the least populous counties suggests that there may be other factors that influence diabetes in these populations. For example, diet may be a bigger factor in this group. The important point is that there may be a difference between rural and more urban counties of Alabama with regards to factors that are associated with prevalence of diabetes. At the very least, we can state that not all counties are the same. Rural and urban populations may have different influences and that they must be treated as two different entities.

Further work may be conducted by performing a retrospective case-controlled study in which a number of individuals with diabetes in the two populations (urban and rural) are followed back in time to determine other factors that may be associated with diabetes. These factors may include age of availability of health insurance and healthcare before they were diagnosed with diabetes, education, income, etc. Such a study may shed more light into the differences between the rural and urban populations, if there are truly any.


Least populous counties group exhibit almost no correlation between physical inactivity and prevalence of diabetes and the most populous counties group exhibit positive correlation between physical inactivity and prevalence of diabetes. This suggests that there may be a fundamental difference between the rural and urban populations with regards to factors associated with diabetes and should be explored further to confirm and expand on this finding.


  1. National Diabetes Surveillance System. (2009) Retrieved August 20, 2012, from the Centers for Disease Control and Prevention.
  2. Krishka A., Knowler W., et al (1989) “Development of Questionnaire to Examine Relationship of Physical Activity and Diabetes in Pima Indians”, Diabetes Care, Vol. 13 No. 4, pp 401-411
  3. Pierpaolo F., Chiara L., et al. (2006) “Exercise and Diabetes”, Acta Bio Medica, Vol. 77 No. 1, pp 14-17
  4. Chipkin S. Klugh S., et al, (2001) “Exercise in Secondary Prevention and Cardiac Rehabilitation”, Cardiology Clinics, Vol. 19 No. 3
  5. Agurs-Collins T., Ten Have T., et al (1997) “A Randomized Controlled Trial of Weight Reduction and Exercise for Diabetes Management in Older African-American Subjects”, Diabetes Care, Vol. 20 No. 10
  6. Croxton, F. (2007) Elementary statistics with applications in medicine and the biological sciences. pp. 126, 316. Dover Publications, Inc. New York


Table 1: Prevalence of Diabetes in Counties of Alabama

County Percentage
Perry County 17.8
Sumter County 16.8
Lowndes County 16.4
Greene County 16.2
Bullock County 15.6
Wilcox County 15.5
Pike County 15
Marengo County 14.8
Butler County 14.6
Choctaw County 14.3
Chambers County 14.2
Dallas County 14.2
Macon County 14.2
Conecuh County 14.1
Hale County 14
Pickens County 13.9
Montgomery County 13.5
Franklin County 13.3
Talladega County 13.3
Barbour County 13.2
Walker County 13
Calhoun County 12.9
Clarke County 12.9
Coosa County 12.8
Henry County 12.8
Clay County 12.7
Dale County 12.6
Randolph County 12.6
Coffee County 12.5
Russell County 12.5
St. Clair County 12.5
Lawrence County 12.4
Crenshaw County 12.2
Fayette County 12.2
Lauderdale County 12.2
Monroe County 12.2
Escambia County 12.1
Geneva County 12
Jackson County 12
Tallapoosa County 12
Cullman County 11.9
Elmore County 11.8
Etowah County 11.8
Tuscaloosa County 11.8
Autauga County 11.7
Colbert County 11.7
Jefferson County 11.7
Mobile County 11.6
Blount County 11.5
Washington County 11.4
Lee County 11.3
Bibb County 11.2
Cherokee County 11.2
Houston County 11.2
Madison County 11.2
Chilton County 11.1
Cleburne County 11.1
Lamar County 11.1
Covington County 10.9
Marshall County 10.9
Marion County 10.6
DeKalb County 10.3
Winston County 10.3
Morgan County 10.2
Limestone County 10
Baldwin County 9.9
Shelby County 8.3

Table 2: Prevalence of Physical Inactivity in Counties of Alabama

County Percentage
Lowndes County 37.5
Greene County 37.3
Clarke County 37.1
Escambia County 37
Walker County 36.9
Bibb County 36.8
Russell County 36.5
Franklin County 36.4
Clay County 36.2
Covington County 36
Butler County 35.9
Lawrence County 35.3
Hale County 35.2
Blount County 35.1
Chambers County 35
Conecuh County 34.9
Marengo County 34.8
St. Clair County 34.7
Cherokee County 34.6
Talladega County 34.6
Marion County 34.5
Lamar County 34.4
Wilcox County 34.4
Geneva County 34.2
Choctaw County 34.1
Perry County 34.1
Barbour County 33.8
Randolph County 33.8
Colbert County 33.7
Coosa County 33.7
Calhoun County 33.3
Dallas County 33.3
Etowah County 33.3
Cleburne County 32.8
Crenshaw County 32.5
Houston County 32.5
Pickens County 32.5
Winston County 32.4
Pike County 32.3
Sumter County 32.3
Lauderdale County 32
Washington County 32
Autauga County 31.9
Fayette County 31.8
Elmore County 31.5
Marshall County 31.5
Monroe County 31.2
Macon County 31.1
Dale County 31
Bullock County 30.9
Limestone County 30.9
Chilton County 30.4
Mobile County 30.2
Henry County 30.1
Tallapoosa County 30
Montgomery County 29.5
Jackson County 29.3
Jefferson County 28.8
Tuscaloosa County 28.8
Cullman County 28.7
Coffee County 28.2
Lee County 27.9
DeKalb County 27
Morgan County 26.6
Madison County 24.9
Baldwin County 24.2
Shelby County 23.5

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