Frequently Asked Questions (FAQ)
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National and State Surveillance Data
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County Level Estimates Maps
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Data Sources and Methodology for County-Level Estimates of Diagnosed Diabetes
and Selected Risk Factors
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How to Read the Maps of County-Level Estimates of Diagnosed Diabetes and Selected
Risk Factors
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Methodology for Mapping County-Level Estimates of Diagnosed Diabetes and Selected
Risk Factors
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County Level Estimates Maps
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Where can I find the most current
U.S. county-level estimates?
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The Diabetes Interactive Atlases
provide the most current county-level estimates of diagnosed diabetes, obesity,
and leisure-time physical inactivity in the United States.
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Data Sources and Methodology for County-Level Estimates of Diagnosed Diabetes
and Selected Risk Factors
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What method was
used to create county-level estimates?
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The prevalence of diagnosed diabetes and selected risk factors by county was estimated
using data from CDC's Behavioral Risk Factor
Surveillance System (BRFSS) and data from the
U.S. Census Bureau’s Population Estimates Program.1
The BRFSS is an ongoing, monthly, state-based telephone survey of the adult population.
The survey provides state-specific information on behavioral risk factors and preventive
health practices. 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. Respondents were considered obese if their
body mass index was 30 or greater. Body mass index (weight [kg]/height [m]2)
was derived from self-report of height and weight. 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?"
Three years of data were used to improve the precision of the year-specific county-level
estimates of diagnosed diabetes and selected risk factors. For example, 2003, 2004,
and 2005 were used for the 2004 estimate and 2004, 2005, and 2006 were used for
the 2005 estimate. Estimates were restricted to adults 20 years of age or older
to be consistent with population estimates from the U.S. Census Bureau. The U.S.
Census Bureau provides year-specific county population estimates by demographic
characteristics—age, sex, race, and Hispanic origin.
The county-level estimates for the over 3,200 counties or county equivalents (e.g.,
parish, borough, municipio) in the 50 U.S. states, Puerto Rico and the District
of Columbia were based on indirect model-dependent estimates.2-4 The
model-dependent approach employs a statistical model that “borrows strength”
in making an estimate for one county from BRFSS data collected in other counties.
Bayesian multilevel modeling techniques were used to obtain these estimates. Separate
models were developed for each of the four census regions: West, Midwest, Northeast
and South. Multilevel Poisson regression models with random effects of demographic
variables (age 20–44, 45–64, 65+; race; sex) at the county-level were
developed. State was included as a county-level covariate. The model specification
is essentially the same as Malec, et al.3
For selected years, rates were age adjusted by calculating age specific rates for
the following three age groups, 20-44, 45-64, 65+. A weighted sum based on the distribution
of these three age groups from the 2000 census was then used to adjust the rates
by age. The weights used were as follows: 0.52, 0.31, 0.17.
Ranks for county-level data of diagnosed diabetes and selected risk factors were
based on age-adjusted prevalence rates. Models were fit using a Bayesian simulation
method known as Markov Chain Monte Carlo.2-4 As part of the model fitting
process we generated and saved two thousand draws from the distribution of each
county's age-adjusted prevalence rate. For each of these draws we sorted the counties
by prevalence and saved the counties' ranks. This gave us two thousand draws from
the distribution of each county's rank. We then used the median for the rank estimate
and the 5th and 95th percentiles for a 90% confidence interval.
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Are the same types of data
available for all years?
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County-level estimates including age-adjusted rates and rankings are available for
all years beginning in 2004 to the current year of available data. However, only
data for diagnosed diabetes prevalence is available for Puerto Rico municipios from
2004 to the current year of available data.
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Can I download the map data of
county-level estimates?
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Excel files with county estimates for the entire nation and for each state are available
for downloading. Under County Level Estimates (National Maps),
the link to download the national data is located below the national map, and under
County Level Estimates (State Maps), the link to download the state
data is located in the Options and Tools box above each state map.
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Where are the definitions
of variables that are found in the downloadable dataset of county-level estimates?
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The national-level and state-level variables with definitions are located in the
Data Dictionary, shown as a link beside each
downloadable file. Under County Level Estimates (National Maps),
the link to the downloadable file is located below the national map, and under
County Level Estimates (State Maps), the link to the downloadable file
is located in the Options and Tools box above each state map. Variables
found in the national and state datasets are the same.
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How to Read the Maps of County-Level Estimates of Diagnosed Diabetes and Selected
Risk Factors
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How do I access the various types of maps available?
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Both national-level and state-level views are available for county estimates. For
national-level view, click on County-Level Estimates (National Maps) on the Diabetes Data
and Trends homepage. For state-level view, you can obtain county estimates through
the Diabetes Data and Trends
homepage or the County-Level
Estimates (National Maps) homepage. On the Diabetes Data and Trends homepage, click the link State Maps
under County Level Estimates, then select the state of interest from the drop down
menu State and click GO. You can also select your state of interest
on the Diabetes Data and Trends
homepage from the drop-down menu under State Surveillance Data including County
Maps and then click GO, or click directly on the state on the U.S.
map. On the County-Level
Estimates (National Maps) homepage, you must select your state of interest
from the drop-down menu County Level Estimates—State Maps
at the bottom of the page and then click GO.
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What factors do I need to choose to display
a map?
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For national maps of county-level estimates, select a State, Indicator (e.g., diagnosed
diabetes), Year, Data Type (Percent of Adults, Age-adjusted Percent of Adults, Number
of Adults, Percent by Number of Adults, Low/High Median Rank), and Classification
(trends, quartiles), and then click GO. For state maps of county-level estimates,
select an Indicator, Year, Data Type, and Classification and then click GO. See
the next question if interested in looking at trends using these maps. For the definition
of quartiles, see the glossary.
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How can I use the maps to look at trends?
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Under the drop-down menu Classification in either the County
Level Estimates (National Maps) or County Level Estimates - State Maps
homepage, select 'trends' to look at trends in county-level estimates. The legend
categories have been set to the 2005 natural breaks categories to visualize the
change in prevalence across years. For national maps, five natural breaks were used
to view trends. For state maps, four natural breaks were used to view trends. Trends
cannot be examined using either quartiles or ranks. For definitions of natural breaks
and quartiles, see the glossary.
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Can I map two categories at the same
time?
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Maps showing county-level estimates of the percentage of adults by the number of
adults (i.e., bivariate maps) are available at the national level for the indicators
(e.g., diagnosed diabetes). On the County-Level Estimates (National Maps)
homepage, select "Percentage by the Number of Adults" from the Data Type
drop-down box to view these national bivariate maps. At the state level, however,
no bivariate maps are available at this time.
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How do I interpret the different colors in
the maps of county-level estimates?
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Colors used in the shaded area maps represent the different levels of the scale.
The lighter color represents the lowest level of the scale whereas the darker color
represents the highest level of the scale.
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How do I interpret the symbols in the maps
of county-level estimates?
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In the dot-density maps (i.e., maps showing the number of adults), the symbols used
represent the different levels of the scale. The smallest dots represent the lowest
level of the scale whereas the largest dots represent the highest level of the scale.
In the bivariate maps (i.e., maps showing percentage by number of adults), small
to large squares of different colors (blue, orange, red) were used to represent
the gradation of the percentage of adults with diabetes by the total number of adults
with diabetes. For example, for all indicators, the small blue squares indicate
the lowest percentage of adults by the lowest total number of adults. On the other
hand, the large red squares indicate the highest percentage of adults by the highest
total number of adults.
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Can I use the county maps and estimates to make
comparisons or rank counties?
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Caution should be exercised in making comparisons based on the county maps and estimates.
The estimates are intended as individual point estimates. Significance testing or
hypothesis testing may be inappropriate. The maps are presented for displaying possible
geographic patterns and stimulating further investigation, but are not intended
as formal representations of similarities and differences.
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.
One should not assume that counties mapped in different colors have significantly
different prevalence. The county estimates 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.
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How were ranks created for the data?
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Ranks for county-level data of diagnosed diabetes and selected risk factors were
based on age-adjusted prevalence rates. Models were fit using a Bayesian simulation
method known as Markov Chain Monte Carlo.2-4 As part of the model fitting
process we generated and saved two thousand draws from the distribution of each
county's age-adjusted prevalence rate. For each of these draws we sorted the counties
by prevalence and saved the counties' ranks. This gave us two thousand draws from
the distribution of each county's rank. We then used the median for the rank estimate
and the 5th and 95th percentiles for a 90% confidence interval. Note that ranks
for Puerto Rico were not included with the national dataset because Puerto Rico
ranks were not generated using the national data. Ranks for Puerto Rico are specific
to that territory.
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How can we use the county ranks?
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A county's rank is a reflection of relative burden. The associated confidence interval
quantifies the uncertainty associated with a county's rank and determines the extent
to which conclusions may be based on ranks. For example, if a county's rank confidence
interval is entirely below 1571, which is the median rank for all counties, we could
confidently place that county in the lower half of counties.
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How can we map the county ranks?
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For each indicator (e.g., diagnosed diabetes), confidence intervals of counties'
ranks were used to identify counties that were either below the median rank for
all counties or above the median rank for all counties. On the County Level
Estimates (National Maps) homepage, you can obtain the maps showing
counties above and below the median rank by selecting "Low/High Median Rank" from
the drop-down menu Data Type and then clicking GO. State-level
maps are not available for ranks because the counties' ranks are based on the national
estimates. For more information about mapping county ranks, see the related Morbidity
and Mortality Weekly Report http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5845a2.htm.
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Methodology for Mapping County-Level Estimates of Diagnosed Diabetes and Selected
Risk Factors
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What method was used to create the maps of
county-level estimates?
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The maps were created by merging the modeled estimates in database format, with
geographic boundary files, called shapefiles. In this manner, the statistical data
in the database were spatially referenced with their associated state and county
boundaries. As a result, the data can be viewed as a map and the user can interactively
map the geospatially-based data. The Albers Equal-Area (Continental United States)
projection was used for the national maps and the NAD 1983 UTM Zone 14N map projection
was used for the state maps.
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What color sequences were used for the
maps?
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Color schemes were chosen based upon the number of data classes or categories, the
types of data being mapped (e.g., number of adults versus percentage of adults),
consideration of the display devices to be used for the resulting maps, and the
need to avoid colors that cannot be differentiated by individuals with impaired
color-vision.5 The color schemes for the maps were selected by referring
to ColorBrewer (http://www.colorbrewer.org*),
an online tool for selecting color schemes.
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What method was used to produce
the bivariate (i.e., percentage by number) maps of county-level estimates?
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For all indicators, the data distribution for the number of adults and the percentage
of adults was based on three classes or categories of natural breaks. The gradation
of the percentage of adults by the total number of adults was mapped using small
to large symbols of three different colors for a total of nine levels. See related
information on interpreting symbols and colors in the maps.
For the definition of natural breaks, see the
glossary.
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National and State Surveillance Data
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What is the National Diabetes Fact Sheet?
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The National Diabetes Fact Sheet is a report that summarizes the latest estimates
of Americans with both diagnosed and undiagnosed diabetes. It is a collaborative
effort involving CDC and the National Diabetes Education Program and other organizations
in the U.S. Department of Health and Human Services, including the Agency for Health
Research and Quality, the Centers for Medicare and Medicaid Services, the Food and
Drug Administration, the Health Resources and Services Administration, the Indian
Health Service, the National Institute of Diabetes and Digestive and Kidney Diseases,
the National Diabetes Information Clearinghouse, and the Office of Minority Health.
The American Diabetes Association, the American Association of Diabetes Educators,
Juvenile Diabetes Research Foundation International, and U.S. Department of Veterans
Affairs are also partners in the National Diabetes Fact Sheet. The data in the fact
sheet will help national, state, and local health officials understand the health
and economic burden of diabetes and better direct efforts to reach populations hardest
hit by the disease.
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Why is there a difference
between the number of people with diagnosed diabetes in the National Diabetes Surveillance
System and the National Diabetes Fact Sheet?
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The number of people with diagnosed diabetes in the National Diabetes Surveillance
System
http://www.cdc.gov/diabetes/statistics/prev/national/figpersons.htm and
the National Diabetes Fact Sheet
http://apps.nccd.cdc.gov/ddtstrs/FactSheet.aspx 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 fact sheet, 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 the NHIS for those younger than 20 years. We use NHANES data in the fact sheet
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 National
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 Fact Sheet. However, the fact sheet should not be used for comparison across
time because the methodology for estimating the U.S. population with diabetes has
changed over time.
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What is the difference between type
1 and type 2 diabetes?
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Type 1 diabetes was previously called insulin-dependent diabetes mellitus (IDDM)
or juvenile-onset diabetes. Type 1 diabetes develops when the body's immune system
destroys pancreatic beta cells, the only cells in the body that make the hormone
insulin that regulates blood glucose. To survive, people with type 1 diabetes must
have insulin delivered by injection or a pump. This form of diabetes usually strikes
children and young adults, although disease onset can occur at any age. Type 1 diabetes
accounts for about 5% of all diagnosed cases of diabetes. Risk factors for type
1 diabetes may be autoimmune, genetic, or environmental. There is no known way to
prevent type 1 diabetes. Several clinical trials of methods to prevent type 1 diabetes
are currently in progress or are being planned.
Type 2 diabetes was previously called non-insulin-dependent diabetes mellitus (NIDDM)
or adult-onset diabetes. Type 2 diabetes accounts for about 90% to 95% of all diagnosed
cases of diabetes. It usually begins as insulin resistance, a disorder in which
the cells do not use insulin properly. As the need for insulin rises, the pancreas
gradually loses its ability to produce it. Type 2 diabetes is associated with older
age, obesity, family history of diabetes, history of gestational diabetes, impaired
glucose metabolism, physical inactivity, and race/ethnicity. African Americans,
Hispanic/Latino Americans, American Indians, and some Asian Americans and Native
Hawaiians or Other Pacific Islanders are at particularly high risk for type 2 diabetes
and its complications. Type 2 diabetes in children below the age of 10 years is
extremely rare. In youth aged 10–19 years it becomes more common, particularly
in American Indians, African Americans, and Hispanic/Latino Americans.
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Does the surveillance system provide
estimates for type 1 and type 2 diabetes?
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No questions are asked about the type of diabetes. We estimate the number and percentage
of the U.S. population with diagnosed diabetes by using data from the National Health
Interview Survey (NHIS) of the National Center for Health Statistics (NCHS), Centers
for Disease Control and Prevention (CDC). All sampled adults are asked whether a
health professional had ever told them they had diabetes. Also, parents of sampled
children are asked whether their child had diabetes.
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Can I make state-to-state comparisons?
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Yes, the Diabetes Data and Trends Web site includes a feature where you can view
state maps and tables and compare states across the same data category. However,
you cannot compare county-level data within a state or across states due to the
variability of the estimates.
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Does the surveillance system include
estimates of gestational diabetes?
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No. We estimate the number and percent of the United States population with
diagnosed diabetes by using data from the National Health Interview
Survey (NHIS) of the National Center for Health Statistics (NCHS), Centers for Disease
Control and Prevention (CDC). 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 website
Behavioral Risk Factor Surveillance System.
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Does the surveillance system include
prevalence estimates for American Indians/Alaska Natives?
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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 the contact information
of the state survey coordinators,
visit http://www2.cdc.gov/nccdphp/brfss2/coordinator.asp.
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Why is there no national diabetes surveillance
data for Hispanics prior to 1997?
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The National Health Interview Survey, which is used to estimate diabetes prevalence
in the United States, did not begin collecting data on Hispanics until 1997.
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What is the difference
between incidence and prevalence?
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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).
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What is the difference between
crude and age-adjusted rates?
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The crude rate is the raw or unadjusted estimate.
The age-adjusted rate is an artificial estimate that minimizes the effects of different
age distributions and allows comparisons between different populations. It represents
what the crude rate would have been in the study population if that population had
the same age distribution as a "standard" population. A "standard" population is
a population in which the age composition is known precisely, for example, as a
result of a census.
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How many people with type 1
diabetes use insulin pumps?
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Unfortunately, we do not have surveillance data on insulin pump use. However, surveillance
data on insulin and oral medication use among adults with diagnosed diabetes, not
specifically type 1 diabetes, are available at http://www.cdc.gov/diabetes/statistics/treating_national.htm.
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Do you have surveillance data on
reasons (e.g., lack of information about the need, inconvenience, cost, pain caused
by the lancets) why people do not perform self-monitoring of blood glucose regularly?
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We do not have surveillance data on barriers to self-monitoring of blood glucose.
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References
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- U.S. Census Bureau http://www.census.gov/popest/estimates.php
- Rao JNK. Small Area Estimation. Ch.10:223:280. John Wiley & Sons; Hoboken, New
Jersey, 2003.
- Malec D, Sedransk J, Moriarity CL, LeClere FB. Small Area Inference for Binary Variables
in the National Health Interview Survey. Journal of the American Statistical Association
1997;92(439):815–826.
- Cadwell BL, Thompson TJ, Boyle JP, Barker LE. Bayesian Small Area Estimates of Diabetes
Prevalence by U.S. County, 2005. Journal of Data Science 2010;8(1):173-188.
- Brewer, CA. Basic mapping principles for visualizing cancer data using geographic
information systems (GIS). American Journal of Preventive Medicine 2006;30(2S):S25–S36.
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* Links to non-Federal organizations found at this site are provided solely as a
service to our users. These links do not constitute an endorsement of these organizations
or their programs by CDC or the Federal Government, and none should be inferred.
CDC is not responsible for the content of the individual organization Web pages
found at these links.
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