New Data: CMS County-Level Chronic Conditions

Map showing the prevalence of diabetes among the
Medicare population by county.

 New data available in HealthLandscape!

Last month, the Centers for Medicare & Medicaid Services (CMS) released new data about Medicare fee-for-service beneficiaries who have chronic conditions. This data set is now available in HealthLandscape's Community HealthView data library.

Threshold map showing counties where diabetes prevalance
among the Medicare population exceeds 30 percent.

This data set tracks 15 chronic conditions and lists their prevalence by county:

• Alzheimer's disease, related disorders, or senile dementia
• Arthritis (including rheumatoid and osteoarthritis)
• Asthma
• Atrial fibrillation
• Cancer (breast, colorectal, lung, and prostate)
• Chronic kidney disease
• Chronic obstructive pulmonary disease (COPD)
• Depression
• Diabetes (excluding diabetic conditions
  related to pregnancy)
• Heart failure
• High cholesterol (hyperlipidemia)
• High blood pressure (hypertension)
• Ischemic heart disease
• Osteoporosis
• Stroke/transient ischemic attack 

Map showing the emergency department visit rate by county
for Medicare population with 6 or more chronic conditions.

The data set also includes data for Medicare beneficiaries who have multiple chronic conditions. It tracks:

• Prevalance by county
• Spending per capita
• Emergency department visit rate
• Hospital readmission rate

To access this data set, log in to www.HealthLandscape.org (registration is free), click "Community HealthView" on the Tools menu, and enter "chronic conditions" in the search field. You'll see the list of available data sets.

For a more detailed overview of HealthLandscape and our Community HealthView data library, click here to sign up for an "Introduction to HealthLandscape" webinar.

CDC: Diabetes Surveillance System

New data available in HealthLandscape!

We have added the most recent data from the CDC Diabetes Surveillance System to HealthLandscape, both at www.healthlandscape.org and, in Quick Map form, at beta.healthlandscape.org. Variables include the Percent of Adults who are Physically Inactive, the Percent of Adults who are Obese, and the Percent of Adults who have Diabetes.

Figure 1. Percent of Adults Who Are Physically Inactive, 2008


Figure 2. Percent of Adults Who Are Physically Inactive, 2008 (HL3)



Diabetes Data and Trends, which includes the National Diabetes Fact Sheet and the National Diabetes Surveillance System, provides resources documenting the public health burden of diabetes and its complications in the United States. The surveillance system also includes county-level estimates of diagnosed diabetes and selected risk factors for all U.S. counties to help target and optimize the resources for diabetes control and prevention.

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. 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?"

See the CDC Diabetes Surveillance System for more information.

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Small Area Income and Poverty Estimates, 2009

New data available in HealthLandscape!

Yesterday, the U.S. Census Bureau released their 2009 Small Area Income and Poverty Estimates. According to their analysis, the poverty rate for children ages 5 to 17 in families rose in 295 counties and declined in 19 counties between 2007 and 2009. Most counties saw no statistically significant change between these years.

The U.S. Census Bureau, with support from other Federal agencies, created the Small Area Income and Poverty Estimates (SAIPE) program to provide more current estimates of selected income and poverty statistics than those from the most recent decennial census.

The U.S. Census Bureau's Small Area Income and Poverty Estimates (SAIPE) program provides annual estimates of income and poverty statistics for all states, counties, and school districts. The main objective of the program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, there are hundreds of state and local programs that depend on income and poverty estimates for distributing funds and managing programs.

The SAIPE program produces the following county estimates:
• total number of people in poverty
• number of related children ages 5 to 17 in families in poverty
• number of children under age 18 in poverty
• median household income

The estimates are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, income and poverty estimates are modeled by combining survey data with population estimates and administrative records. Beginning with the SAIPE program's estimates for 2005, data from the American Community Survey (ACS) are used in the estimation procedure; all prior years used data from the Annual Social and Economic Supplements of the Current Population Survey. Further details are given in a 2007 SAIPE report, Use of ACS Data to Produce SAIPE Model-Based Estimates of Poverty for Counties [PDF 3.4M]. For more information, see Small Area Income & Poverty Estimates.

Figure 1. Percent of Population in Poverty by County, 2009


Figure 2. Percent of Population Under 18 Years of Age in Poverty by County, 2009

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Health Insurance Coverage by County, 2007

New data available in HealthLandscape!

The US Census Bureau's Small Area Health Insurance Estimates (SAHIE) for 2007 are estimates of health insurance coverage for all counties. This dataset includes county-level estimates on the number of people and the percentages of people with and without health insurance coverage for ages 18 to 64 years. For more information, see, SAHIE.

The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. The program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program.

SAHIE released 2007 county estimates of people with and without health insurance coverage by:

• Ages 0-18; 0-64; 18-64; 40-64; and 50-64;

• Sex;

• People of all incomes and people at or below 200 percent or 250 percent of the poverty threshold; and

• Measures of uncertainty of the estimates.

This research is partially funded by the Centers for Disease Control and Prevention, National Breast and Cervical Cancer Early Detection Program (NBCCEDP). The CDC has a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold.


Figure 1. Percent of Population Uninsured by County, 2007


Figure 2. Percent of Population at or Below 200% of Poverty Uninsured by County, 2007

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Labor Force Size and Unemployment, 2009

The Local Area Unemployment Statistics (LAUS) program is a federal-state cooperative effort in which monthly estimates of total employment and unemployment are prepared. These estimates are key indicators of local economic conditions. The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation and publication of the estimates that state employment security agencies prepare under agreement with BLS.

A wide variety of customers use these estimates. Federal programs use the data for allocations to states and areas, as well as eligibility determinations for assistance. State and local governments use the estimates for planning and budgetary purposes and to determine the need for local employment and training services. Private industry, researchers, the media, and other individuals use the data to assess localized labor market developments and make comparisons across areas.

The concepts and definitions underlying LAUS data come from the Current Population Survey (CPS), the household survey that is the official measure of the labor force for the nation. State monthly model estimates are controlled in "real time" to sum to national monthly labor force estimates from the CPS. These models combine current and historical data from the CPS, the Current Employment Statistics (CES) program.

For more information, see the Local Area Unemployment Statistics Home Page.

Figure 1. Unemployment Rate by County, 2009

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BEA Regional Economic Profile, 2008

The Regional Economic Profile (Table CA30) provides general economic data that are derived from other, more detailed tables (CA05, CA05N, CA25, CA25N, and CA35). Estimates are organized by both place of residence and place of work. The place of residence profile includes estimates of total personal income, population, and per capita personal income. The place of work profile includes estimates of total earnings, total employment, and average earnings per job. For more information, see BEA Regional Economic Accounts.

Figure 1. Personal Income (Thousands of Dollars), 2008


Figure 2. Number of Non-Farm Proprietors, 2008

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BEA County Income & Employment Summary, 2008

2008 estimates from the BEA County Income and Employment Summary HealthLandscape.

Bureau of Economic Analysis data released in April of 2010 are new estimates for 2008.

The first part of Table CA04 presents the summary statistics: Personal income, nonfarm personal income, farm income, population (estimated as of July 1 of each year by the Census Bureau), and per capita personal income, which is personal income divided by population.

The second part of Table CA04 presents the derivation of personal income. Personal income is measured as the sum of wages and salaries; supplements to wages and salaries; proprietors' income; dividends, interest, and rent; and personal current transfer receipts; less contributions for government social insurance. The personal income of a local area is defined as the income received by the residents of the local area, but the estimates of wages and salaries, supplements to wages and salaries, and contributions for government social insurance by employees are based mainly on source data that are reported not by the place of residence of the income recipients but by their place of work. Accordingly, an adjustment for residence-- which is the net inflow of the earnings of wage and salary workers who are interstate commuters-- is estimated so that place-of-residence measures of earnings and personal income can be derived. Net earnings by place of residence is calculated by subtracting contributions for government social insurance from earnings by place of work and then adding the adjustment for residence. The estimates of dividends, interest, and rent, and of personal current transfer receipts are prepared by place of residence only.

The third part of Table CA04 presents the summary estimates of total employment, wage and salary employment, and proprietors employment.

For more information, see BEA Regional Economic Accounts.

Figure 1. Per Capita Personal Income (Dollars), 2008


Figure 2. Non-Farm Personal Income, 2008

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Appalachian Economic Status Data Updates

Economic Status Data are now available for fiscal years 2010 and 2011.

The Appalachian region is home to 24.8 million people and consists of 420 counties across 13 states, stretching from New York and Pennsylvania in the northeast to Mississippi and Alabama in the south. Forty-two percent of the Region's population is rural, compared with 20 percent of the national population. The Appalachian population is characterized by lower levels of college completion and lower labor force participation. Southern areas of Appalachia attract better educated and higher skilled people.

In recent years, the region's economy has become more diversified, rather than relying on mining, forestry, agriculture, chemical industries, and heavy industry. In 1965, one in three Appalachians lived in poverty. In 2000, the Region's poverty rate was 13.6 percent.

The Appalachian Regional Commission (ARC) categorizes each county in the region into one of five economic levels: distressed, at-risk, transitional, competitive, and attainment. The system involves the creation of a national index of county economic status through a comparison of each county's averages for three economic indicators--three-year average unemployment rate, per capita market income, and poverty rate--with national averages. In 1965, 223 Appalachian counties were considered economically distressed. In fiscal year 2011 that number is 82. For more informatoin on how the ARC defines the economic categories, visit their website.

Figure 1. Applachian Economic Status, FY2011




The ARC uses US Bureau of Labor Statistics unemployment rates as a part of its economic classification system. The three-year average unemployment rate is a measure of long-term structural unemployment that allows for the comparison of counties across state borders. The unemployment rate is calculated by dividing the three-year sum of persons unemployed by the three-year sum of the civilian labor force.

Figure 2. Applachian Three-year Unemployment Rate 2006-2008



These data, and others for Appalachia, are now available in HealthLandscape for use in your maps. You can find these data by going to Community HealthView → United States → Appalachian Counties Economic Status.

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Commute to Work and Class of Worker

Two indicators from the American Community Survey (ACS) 2006-2008 Estimates are now available in HealthLandscape.

The data on means of transportation to work refer to the principal mode of travel or type of conveyance that the worker usually used to get from home to work during the reference week. People who used different means of transportation on different days of the week were asked to specify the one they used most often, that is, the greatest number of days. People who used more than one means of transportation to get to work each day were asked to report the one used for the longest distance during the work trip. The category "Car, Truck or Van" includes workers using a car (including company cars, but excluding taxicabs), a truck of one-ton capacity or less, or a van. The category "Public Transportation" includes workers who used a bus or trolley bus, streetcar or trolley car, subway or elevated, railroad, or ferryboat, even if each mode is not shown separately in the tabulation. The category "Other Means" includes workers who used a mode of travel that is not identified separately within the data distribution.

Figure 1. Mean Travel Time to Work


Figure 2. Percent Using Public Transportation


The ACS Estimates on class of worker categorizes people according to the type of ownership of the employing organization. For employed people, the data refer to the person’s job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people, the data refer to their last job. Respondents provided the data for the tabulations by writing on the questionnaires descriptions of their kind of business or industry and the kind of work or occupation they are doing.

Figure 3. Percent Private Wage and Salary Workers


For more information on these indicators, see American Community Survey and 2008 Subject Definitions.

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Crime by State, 2008

New data available in HealthLandscape!

The FBI collects these data through the Uniform Crime Reporting (UCR) Program.

Data provides the rate of selected offenses per 100,000 inhabitants for each state.

Any comparisons of crime among different locales should take into consideration relevant factors in addition to the area's crime statistics. Variables Affecting Crime provides more details concerning the proper use of UCR statistics.

For more information, see 2008 Crime in the United States, Data Declaration.


Figure 1. Violent Crime Per 100,000 Inhabitants, 2008



Figure 2. Property Crime Per 100,000 Inhabitants, 2008

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USDA Food Environment Atlas

New data available in HealthLandscape!

County-level data from the USDA Food Environment Atlas is now available in HealthLandscape. The Food Environment Atlas includes data on proximity to food stores and restaurants, food prices, nutrtion-related assistance programs, health, and community characteristics. These factors interact to influence food choices and diet quality. The Atlas was developed to centralize food- and nutrition-related information and provide a spatial overview of these statistics.

The Atlas is made up of three main categories. The Food Choices category includes information on access to healthy and affordable food. Some examples of indicators in this category include access and proximity to a grocery store, the number of fast-food restaurants, access to local foods, food assistance program participation, and availability of local foods.

Figure 1. Percent of Households with No Car and > 1 Mile from Grocery Store


Figure 2. WIC-Authorized Stores per 1000 Population


Figure 3. Number of Fast Food Restaurants



Health and Well-Being indicators contain information on the community's health and diets, including rates of diabetes and obesity, and physical activity levels.

Figure 4. Adult Obesity Rate



Community Characteristics are aspects of the community that can have an influence on the food environment, including the demographic composition, income and poverty statistics, and the number of recreation and fitness centers available to the population.

Figure 5. Percent of Students Free-Lunch Eligible

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Internet Crime Complaints and Perpetrators by State, 2009

New data available in HealthLandscape!

HealthLandscape now contains 2009 data for Internet Crime Complaints by State and Internet Crime Perpetrators by State. The internet crime complaints data are 2009 state rates based on filings with the Internet Crime Complaint Center (IC3). The internet crime perpetrators data are based only on filings where the perpetrator's residence could be identified by IC3. The IC3, which began operation on May 8, 2000 as the Internet Fraud Complaint Center, was established as a partnership between the National White Collar Crime Center (NW3C) and the Federal Bureau of Investigation (FBI) to serve as a vehicle to receive, process, and refer criminal complaints regarding the rapidly expanding arena of cyber crime. IC3 was intended for and continues to serve the broader law enforcement community, including federal, state, and local agencies, which employ key participants in the growing number of Cyber Crime Task Forces. Since its inception, IC3 has received complaints across a wide variety of cyber crime matters, including online fraud (in its many forms), intellectual property rights matters, computer intrusions (hacking), economic espionage (theft of trade secrets), child pornography, international money laundering, identity theft, and a growing list of additional criminal matters.

For more informtion, see IC3, NW3C and FBI. The full reports for 2009 and all previous years are available for download from the annual reports section of the IC3 website.

In 2009, the IC3 website received 336,655 complaints (22.3% increase from 2008). Just over one-third of complainants resided in one of the four most populated states: California, Florida, Texas, or New York. While Alaska, Colorado, and the District of Columbia had a relatively small absolute number of complaints, they did have some of the highest per capita rates of complainants in the United States.

Figure 1. Percent of Total Individual Complaints by State, 2009



Figure 2. Complainants per 100,000 People by State, 2009








The state of residence for perpetrators was only reported 33% of the time. Among the complaints for which perpetrator information is available, more than half resided in one of the following states: California, Florida, New York, the District of Columbia, Texas, and Washington. The District of Columbia, Nevada, Washington, Montana, Utah, Delaware, Florida, and Wyoming had the highest per capita rates.

Figure 3. Percent of Perpetrators by State, 2009



Figure 4. Perpetrators per 100,000 People by State, 2009

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