FAQs

Unfortunately, we do not have surveillance data on insulin use by type of diabetes. However, surveillance data are available on insulin and oral medication use among adults with diagnosed diabetes, not specifically type 1 diabetes.

No. We estimate the number and percent of the US population with diagnosed diabetes by using data from CDC’s National Health Interview Survey. The number of women with gestational diabetes is excluded from the diabetes surveillance estimates. For estimates of gestational diabetes in the United States, refer to the Diabetes Report Card[PDF -5.5 MB] or the Behavioral Risk Factor Surveillance System .

No. The data sources used for diabetes surveillance do not provide an adequate sample size of this population to produce accurate and reliable estimates. However, several states, including Minnesota, Montana, New Mexico, North Carolina, and Oklahoma have conducted surveys with an oversample of American Indians. For more information, contact the Behavioral Risk Factor Surveillance System’s state coordinators.

Currently, the US Diabetes Surveillance System includes prevalence estimates of diagnosed diabetes for Hispanics and Asians overall, and for Hispanic subgroups, such as Puerto Ricans, Mexican Americans, and Cubans, but not for Asian subgroups, such as Chinese, Filipinos, or Asian Indians. For the latest statistics about diagnosed diabetes in these groups, see the National Diabetes Statistics Report.

Prior to 1997, the National Health Interview Survey, which is used to estimate diagnosed diabetes prevalence in the United States, did not provide an adequate sample size of the Hispanic or Asian population to produce accurate and reliable estimates.

Diabetes surveillance data are updated as new data are released from CDC's Behavioral Risk Factor Surveillance System , from the US Census Bureau,  and from other data sources.

Data from CDC's Behavioral Risk Factor Surveillance System and from the US Renal Data System were used to obtain state-level estimates of diagnosed diabetes, risk factors, preventive care practices, and complications. Data from the BRFSS and from the US Census Bureau’s Population Estimates Program  were used to model the estimates of diagnosed diabetes and its risk factors at the county level. Learn more about the methods to obtain county-level estimates[PDF -158 KB].

In the Diabetes State Atlas application, state-level data are available for the 50 states, the District of Columbia, Guam, Puerto Rico, and the US Virgin Islands. In the Diabetes County Atlas application, data for counties and county equivalents (e.g., parishes, boroughs, municipalities) are available for the 50 states, the District of Columbia, and Puerto Rico.

National data on diabetes prevalence and incidence are available dating back to 1980. State-level estimates are available for all years beginning in 1994 to the current year of available data. County-level estimates, including age-adjusted rates and rankings, are available for all years beginning in 2004 to the current year of available data.  

The Diabetes Atlas, both for state-level and county-level data, show uninterrupted trend data and indicates with a colored bar or an asterisk that the BRFSS survey methodology changed in 2011. BRFSS data are used in obtaining state-level estimates and county-level estimates. However, the changes in BRFSS survey methods do not require any changes in the methods to calculate county-level estimates, and thus have no effect on county-level estimates. We would expect the county-level estimates to “improve” due to better coverage (via the addition of cell phones) of the target population.  

You can find county-level estimates of diagnosed diabetes, obesity, and leisure-time physical inactivity in the United States on the Diabetes Data and Statistics homepage or within the Diabetes State Atlas application.

In the Diabetes State Atlas application, under “Additional Data” on the top right of the page, look for the links “All States County Data” and “All States Motion Charts.” You will be able to access state and county-level data in the United States, county rankings, and maps and motion charts to examine how changes in diabetes coincide with changes in obesity over time and by geographic location.

Bayesian methods were used to obtain county-level estimates for more than 3,200 counties and county equivalents in the United States. The county-level estimates are modeled, not direct, estimates using a statistical model that “borrows strength” in making a single county estimate from surrounding counties. You can view trends in county-level data beginning in 2004. Three years of data were used to obtain a single estimate. Learn more about the methods to obtain county estimates[PDF -158 KB].

The county-level estimates are modeled, not direct, estimates that were obtained using Bayesian multilevel modeling techniques. Three years of data were used to obtain a single estimate. Learn more about the methods to obtain county estimates[PDF -158 KB].

No, the Diabetes Atlas uses data from CDC’s Behavioral Risk Factor Surveillance System (BRFSS) which is an ongoing, monthly, state-based telephone survey of the adult population aged 18 years or older in the United States.

No, data on diabetes incidence and prevalence, as well as data on prevalence of obesity and physical inactivity, are provided for counties or county equivalents within Indian reservations, but not for reservations. For a map of US counties and American Indian/Alaska Native areas, see the Census Brief.

Incidence is the rate at which new events occur in a population. The numerator is the number of new events that occur in a defined period; the denominator is the population at risk of experiencing the event during this period.

Prevalence is the total number of all individuals who have an attribute or disease at a particular time (or during a particular period) divided by the population at risk of having the attribute or disease at this point in time (or midway through the period).

The crude rate is the raw or unadjusted estimate.
The age-adjusted rate is a mock estimate that helps us to compare populations that have different age distributions.

Obesity and physical inactivity are risk factors for developing type 2 diabetes. Learn more about how to prevent and control diabetes.

In the Diabetes State Atlas application, after selecting the indicator, click the play (right arrow) button below the map to start the animation and view trends. The legend categories have been set to the 2005 natural breaks to see the change in prevalence or incidence across years. You may also view trends using quartiles. For quartiles, on the left navigational bar, click the button ‘Data Filters,’ look for ‘Data Classification,’ and switch the radio button to ‘Quartiles.’ Note, however, that in quartiles the legend categories will change from year to year depending on the data distribution for that year.

In the Diabetes County Atlas application, at the top of the page, click the < and > buttons on the animation bar to view trends. The legend categories have been set to the 2005 quintiles categories to visualize the changes in prevalence or incidence across years. The button Legend Settings will allow you to select other data classification categories and the number of classes.

Yes, the Diabetes Atlas includes US maps and tables that help you compare states across the same data category. However, pay close attention to the lower and upper limits of the confidence interval, which you will find in the table, before reaching conclusions about significant differences between states.

In the Diabetes State Atlas application, after selecting the indicator, look for the wheel icon on the top right of the US map, the heat map, or the line chart. Click the icon to print the data to a PowerPoint slide that you could then 'copy and paste' to your presentation.

In the Diabetes County Atlas application, look for the button that says ‘Save’ or ‘Print’ to download the maps or other images that you see on the screen or print in pdf format.

The suggested citation: Centers for Disease Control and Prevention. Division of Diabetes Translation. US Diabetes Surveillance System. Available at http://www.cdc.gov/diabetes/data.

In the Diabetes State Atlas application, after selecting the indicator, look for the wheel icon on the top right of the US map, the heat map, or the line chart to download the CSV (Excel) files with the data that you see on the screen.

In the Diabetes County Atlas, look for the button that says 'Download Data' to download the Excel files of interest.

The suggested citation: Centers for Disease Control and Prevention. Division of Diabetes Translation. US Diabetes Surveillance System. Available at http://www.cdc.gov/diabetes/data.

The All States Motion Charts application, which you will find in both the Diabetes State Atlas and the Diabetes County Atlas applications, includes motion or bubble charts that plot obesity prevalence (x-axis) and a selected indicator (e.g., diabetes prevalence or diabetes incidence) (y-axis) and show the parallel growth of diabetes and obesity across states or counties in the United States. In the All States Motion Charts application, if you wish to view the county-level estimates and motion charts for a particular state, double click the state on the US map.

A county's rank is a reflection of its burden of the disease or condition relative to other counties. Ranks for county-level data of diagnosed diabetes (existing and new cases), obesity, and physical inactivity were based on age-adjusted rates. The confidence intervals around these ranks convey the uncertainty associated with a county's rank and need to be taken into account before reaching conclusions based on ranks. Learn more about the methods to obtain county ranks[PDF -158 KB].

For each indicator (e.g., diagnosed diabetes), confidence intervals of counties' ranks were used to identify and map counties that were either below the median rank or above the median rank for all counties. For more information about mapping county ranks, see the article Diabetes Interactive Atlas and the related Morbidity and Mortality Weekly Report.

Exercise caution when making comparisons based on the county maps and county estimates. The maps are presented for displaying possible geographic patterns and stimulating further investigation, but are not intended as formal representations of similarities and differences. Do not assume that counties mapped in different colors have significantly different prevalence.
The county-level estimates are intended as individual point estimates that are grouped in categories by various methods to produce a state or national map. This grouping does not incorporate the standard deviation or confidence interval and does not imply any formal comparison between counties.
Bayesian 95% confidence intervals and standard deviations are provided as precision indicators of the individual county-level point estimates and should be used in data analyses. Significance testing or hypothesis testing may be inappropriate.