Diabetes surveillance data
The surveys and databases used by the US Diabetes Surveillance System to examine trends in diagnosed diabetes and its complications cannot distinguish between types of diabetes. Therefore, our estimates include data on all types of diabetes and we cannot present trends by type. Because type 2 diabetes accounts for about 90%‒95% of the cases of diagnosed diabetes in adults, trends in type 2 diabetes are likely to be similar to trends documented by the surveillance system. However, because type 1 diabetes accounts for approximately 5% of all diagnosed cases of diabetes among adults, trends documented in the surveillance system may not be reflective of trends in type 1 diabetes.
Unfortunately, we do not have surveillance data on insulin use by type of diabetes. However, national surveillance data are available on diabetes 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 Cdc-pdf[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.
The number of people with diagnosed diabetes in the US Diabetes Surveillance System and the National Diabetes Statistics Report are close but not exactly the same because the data sources, methodologies, and time periods are different. In the surveillance system, we use National Health Interview Survey (NHIS) data to estimate the U.S. population with diagnosed diabetes. In the statistics report, the estimate of the U.S. population with diagnosed diabetes comes from the National Health and Nutrition Examination Survey (NHANES) for those aged 20 years or older and from the NHIS for those younger than 20 years. We use NHANES data in the statistics report because we present the number of people with diagnosed and undiagnosed diabetes; the medical examination component in NHANES allows us to estimate the number of people with undiagnosed diabetes. From NHIS, we can only obtain estimates of diagnosed diabetes.
If looking at trend data (i.e., looking at changes over time), refer to the US Diabetes Surveillance System. The data source, NHIS, and the methodology have been consistent throughout the years. If looking at a single year, refer to the National Diabetes Statistics Report. However, the statistics report should not be used for comparison across time because the methodology for estimating the US population with diabetes has changed over time.
Data from CDC’s Behavioral Risk Factor Surveillance System and from the US Renal Data SystemExternal 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 ProgramExternal 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 Cdc-pdf[PDF -158 KB].
In the Diabetes 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.
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 Cdc-pdf[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 Cdc-pdf[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 Cdc-pdf[PDF – 3.4MB]External.
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).
Diabetes surveillance applications
In the Diabetes 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, 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 Atlas application, after selecting the indicator, look for the download 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.
In the Diabetes Atlas application, after selecting the indicator, look for the download 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 All States Motion Charts application, which you will find in the Diabetes County Atlas application, 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 ranksCdc-pdf[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.