# Preface
Increasingly, public sector and non-profit programs are expected to demonstrate that the services they provide work. In the area of healthy homes, that means that funders and program participants are interested in knowing whether program interventions will result in measurable improvements in health and well-being. Programs that use data to design, implement, and evaluate their interventions and to present the effectiveness of their work in reducing lead poisoning, asthma, or home injuries are much more likely to be successful in the highly competitive world of grant writing.
We have called this document a "cookbook" in order to highlight its hands-on nature. Although programs in Georgia are used throughout as examples, the datasets described here are available in most states and local areas, and they are often accessible on the Internet. The techniques for data analysis and comparison are straightforward, not only making them easy to use but also providing useful data that can be understood by all stakeholders.
Mary Jean Brown ScD, RN Chief, Healthy Homes, Lead Poisoning Prevention Branch Centers for Disease Control and Prevention Atlanta, GA

# Purpose
Budget cuts at all levels of government and decreased funding from foundations are reducing the programs and social services offered by non-profit organizations. In today's competitive grantwriting climate, data-driven demonstration of need can help your non-profit make a stronger argument for the importance of continuing/expanding services to the populations served by your organization.
This cookbook was created to introduce program managers and grant writers to available data sources on the housing-related health conditions of lead poisoning, asthma, and unintentional home injuries and to provide guidance on how to use these data to highlight milestones and successes.
The cookbook presents national, Georgia, Fulton County, Atlanta, and Atlanta Neighborhood Planning Unit-V (NPU-V)-level data as examples of comparisons of morbidity and mortality across the different geographic areas. However, most of the datasets described here are available in other areas of the country. Information in this cookbook about which organizations collect and analyze health data, along with the key staff members at those organizations, is intended to help program managers build relationships for data-sharing, learn from best practices, and develop referral networks. This cookbook also describes surveillance systems for elevated blood lead, asthma, and home injuries; the description can assist program managers in creating evaluation plans for their organizations' green and healthy homes interventions. Lastly, this cookbook discusses the overlapping risk factors that result in health disparities related to housing.

# The Healthy Homes and Lead Poisoning Prevention Branch
The Centers for Disease Control and Prevention's (CDC) Childhood Lead Poisoning Prevention Program (CLPPP) was created by the Lead Contamination Control Act of 1988 to initiate program efforts to eliminate childhood lead poisoning in the United States. The primary responsibilities are stated as follows:
- Develop programs and policies to prevent childhood lead poisoning.  Educate the public and health-care providers about childhood lead poisoning.  Provide funding to state and local health departments to determine the extent of childhood lead poisoning by screening children for elevated blood lead levels, helping to ensure that lead-poisoned infants and children receive medical and environmental followup, and develop neighborhood-based efforts to prevent childhood lead poisoning.  Support research to determine the effectiveness of prevention efforts at federal, state, and local levels.
In 2009, the CDC's Childhood Lead Poisoning Prevention Program recognized the need to address housing-related issues by use of a more comprehensive approach, and the program transitioned to the Healthy Homes and Lead Poisoning Prevention Program (HHLPPP). This name change reflects the program's new direction of implementing healthy homes initiatives that reduce or eliminate housing-related health hazards and promote housing that is healthy, safe, affordable, and accessible. In 2011, the HHLPPP funded 35 states to:  Build a consortium of strategic partners to address unsafe and/or unhealthy housing conditions.  Assure that follow-up care is provided for high-risk populations who are identified with housing-related health issues.  Develop a surveillance system that monitors blood lead levels, environmental test results, and healthy housing variables.  Develop a regulatory structure and enforcement process to prevent or control housingrelated environmental health hazards.

# Childhood Lead Poisoning

# Background
Lead is a neurotoxic chemical that is harmful to all individuals. No safe blood lead threshold in children has been established. The adverse health impacts of lead are particularly damaging to the nervous systems of developing fetuses and young children. Exposure to lead causes harm to children even at levels once thought "safe." Such exposure results in IQ reduction, learning impairment, and behavioral problems. Reduction in IQ has negative social ramifications for children with elevated blood lead levels and society at large. These problems relate to school attendance, workforce participation, wage earnings, and worker productivity . Lead poisoning is a serious health problem that can affect entire generations of American children. Because of the consequences, it robs society of our future leaders.

# Lead Paint
In the United States, the primary source of childhood lead exposure is lead-based paint and paint dust. Paint manufacturers began phasing out lead in paint in the 1950s, but lead was not banned in residential paints in the United States until 1978. Older homes are more likely to contain lead paint. Lead paint chips and dust can contaminate a home and be ingested by children when the paint is deteriorated or when home renovation projects occur .

# Diagnosis through Blood Lead Testing
Overt clinical symptoms of lead poisoning, such as abdominal pain, headaches, and low appetite, are rare at blood lead levels of less than 70 g/dL . For this reason, blood lead testing is necessary to identify asymptomatic children with elevated blood lead levels . Blood lead testing/screening can be conducted in two ways: through a capillary test, also known as a finger stick, or through a venous test (blood is drawn directly from a vein.) Elevated blood lead levels identified through a capillary test are usually confirmed through a venous test. CDC currently defines child blood lead levels of greater than or equal to 5 g/dL as elevated .

# Risk Groups for Lead Poisoning
Children under six years of age are highly susceptible to lead poisoning because their hand-to mouth behaviors provide a route of ingestion for lead from the environment. In addition, since young children's nervous systems are still developing, exposure to lead results in long-term negative health and social consequences.
A study of trends in blood lead levels among US children from 1988-2004, using CDC's National Health and Nutrition Examination Survey (NHANES) data, revealed additional risk groups for lead poisoning, namely non-Hispanic blacks, low-income individuals, Medicaid recipients, and residents of pre-1950 housing .
CDC  identifies the following as high-risk groups of children who should be screened for elevated blood lead:  Residents of pre-1978 housing, and especially residents of pre-1950 housing  The poor  Members of racial/ethnic minority groups, including non-Hispanic blacks and some groups of Hispanic and Asian Americans  Those with occupationally exposed parents  Medicaid recipients

# National Housing Data
An estimated 38 million housing units have lead-based paint. Twenty-five percent of the nation's housing units (24 million) have significant lead hazards, such as deteriorated paint or lead dust. 1.2 million of these housing units are homes of low-income families (less than $30,000 per year) with children under 6 years old .

# Age of Housing
The US Census Bureau's American Housing Survey (AHS) collects national data on such housing characteristics as age of housing; structural problems; electrical, sanitation, and heating facilities; as well as residents' overall opinion of their housing . Results from the American Housing Survey are available for odd-numbered years, with the latest data available online for year 2009 at . The AHS also collects housing information for select cities and their surrounding counties. The most current AHS results for the Atlanta Metropolitan Statistical Area are for 2004  04alt.html.

# National Trends in Blood Lead Levels
The National Health and Nutrition Examination Survey (NHANES) is a study of health and nutritional status of adults and children in the United States conducted by the Centers for Disease Control and Prevention. The survey combines interviews and physical examinations of a nationally representative sample of individuals. NHANES data reveal that there has been a steady decline in elevated blood lead levels among American children 1 to 5 years old.
Though the prevalence of elevated blood lead levels has declined, even among high-risk children, disparities still exist between groups of children. According to NHANES 1999NHANES -2004 data, the average blood lead level of Non-Hispanic black children is 2.8 g/dL while Non-Hispanic white children have an average blood lead level of 1.7 g/dL. 3.3% of children residing in pre-1950s housing have blood lead levels of greater than or equal to 10 g/dL compared to 0.4% of children who live in homes built in 1978 and later. 1.8% of children who are lowincome have elevated blood lead, while 0.8% of middle to high-income children have such levels .

# Georgia, Fulton County, Atlanta, and Neighborhood Planning Unit-V (NPU-V) Data
Age of housing on the state and local level can be obtained from the US Census.   .
The following bar graph is a visual representation of data from Table 4 above. The data show that NPU-V has a greater percentage of both pre-1950 and pre-1980 housing than either Fulton County or the state of Georgia.

# NPU-V
Source: .

# Blood Lead Testing in Georgia
Most blood lead testing in Georgia is performed by private physicians during physical exams or well-child visits. A smaller number of tests may be done at county or district health departments or WIC programs. According to a federal requirement, all children enrolled in Medicaid are to be screened at approximately 12 and 24 months of age .
The Blood Lead Screening Guidelines for Georgia established in 2004 by the Georgia Department of Community Health's CLPPP  are as follows:

# Surveillance
Laboratories send all blood lead test results electronically to GA DCH's CLPPP. As of March 2009, all blood lead levels must be reported within 7 days. Elevated blood lead results of greater than or equal to 10 g/dL are faxed to CLPPP daily from labs in order to expedite follow-up with patients. The addresses of those screened for lead and those who test positive for elevated blood lead are geocoded by the Georgia Department of Public Health's GA CLPPP to determine the geographical distribution of screening and elevated blood lead levels .

# Case Management
Lead case management begins with confirmed elevated blood lead level of greater than or equal to 10 g/dL. Regional lead coordinators from health district offices inspect a child's housing for lead hazards when the child's blood lead level is greater than or equal to 10 g/dL. Case management includes the following :
 Clinical evaluation for complications of lead poisoning  Family lead education and referrals  Chelation therapy, if appropriate  Follow-up testing Case management of those with elevated blood lead levels is conducted by the Georgia Department of Public Health's CLPPP, by health care management organizations, by regional lead coordinators, and by private physicians through close communication and cooperation . Data Notes   A child can be screened only once initially within a specified period of time. All other tests are confirmatory and/or follow-up tests. Elevated blood lead data are based on the highest test result (capillary or venous) within that period of time  The listed age is the child's age when the blood specimen with the highest test result was collected  The data represent all records reported to the GA CLPPP during the year.  The listed county is the county of residence of the child at the time of screening  Data are updated annually and posted on the GA CLPPP Web site in November or December Blood Lead Data for Georgia 2009 saw a large increase in the number of children screened because that was the year lead screening was included in measures of the Healthcare Effectiveness Data and Information Set (HEDIS). HEDIS acts like a report card for health care management organizations and health care providers. For 2009, a similar jump in screenings can be seen in the following tables of Fulton County, Atlanta, and NPU-V data.     .

# Blood Lead Data for Fulton County

# Blood Lead Data for Atlanta

# Blood Lead Data for NPU-V
Over the past five years, there have been only a handful of children in NPU-V with confirmed elevated blood lead. However, this is most likely an underestimation of the true number of NPU V children with elevated blood lead because there is an inadequate amount of screening in this geographic area. NPU-V contains proportionally more pre-1980 housing than Fulton County or the state of Georgia, with a resultant increase in children's exposure to lead paint. A study of blood lead testing in Atlanta showed a lack of correlation between testing and the risk factor of older housing , a reflection of inadequate screening.
A second factor is that the federal requirement to screen all Medicaid children for lead at 12 and 24 months of age is not comprehensively being met in Georgia . Since these insured children are not being screened at the adequate level, it can be concluded that children without health insurance are even less likely to receive a blood lead test. The Atlanta Community Access Coalition states that between 55-66% of children in the three zip codes related to NPU-V are uninsured . Children in Georgia are usually tested for lead by their primary care physicians. Those without health insurance have less access to primary care and thus are less likely to receive blood lead testing.
Finally, the Centers for Disease Control and Prevention  recommends targeted screening of high-risk children, namely those who live in older housing, are poor, are members of racial/ethnic minorities, recent immigrants, children newly adopted from oversees and refugees and have occupationally exposed parents. Children in NPU-V are considered high-risk by this CDC definition, and therefore all NPU-V children should be screened for lead in order to provide a means of understanding the true number of young people in these neighborhoods with elevated blood lead levels and to reduce their lead exposure.

# Other Data Sources to Explore
In addition to exploring the age of housing, the number of children screened for blood lead, and the number of children who tested positive for elevated blood lead, those interested in learning more about blood levels should consider exploring these other data sources:

# Asthma Background
Asthma is a chronic inflammatory disorder of the lungs and airways. The disease causes recurrent episodes of wheezing, breathlessness, chest tightness, and coughing . Asthma episodes are distressing and potentially life-threatening experiences . The breathlessness of an asthma episode can be described as trying to inhale and exhale air exclusively through a coffee stirring straw. Asthma is the most common chronic disease among children . An estimated 34 million Americans, or 11.5% of the US population, have been diagnosed with asthma in their lifetimes. 22.9 million Americans, or 7.7% of the US population, currently have asthma . Asthma costs the United States more than $30 billion every year . The adverse health and social outcomes from asthma include These key symptom indicators, combined with a spirometry or lung function test, are necessary for establishing an asthma diagnosis . It is difficult to diagnose infants and toddlers for asthma, given the many causes of wheezing in young children .

# Causes and Triggers
Two key reports from the Institute of Medicine identified the association between biological and chemical exposures in the home with asthma. House dust mites and secondhand smoke exposure for preschool-aged children are associated with the development of asthma in sensitive individuals. Indoor triggers or exposures associated with asthma episodes  are
 Cockroaches  Dust mites  Cats  Dogs  Secondhand smoke  Fungi or molds  Viral infections

# Asthma Control
Asthma is a chronic condition that can be controlled with appropriate management in the form of medications, patient health education, management of co-morbidities, environmental control measures (e.g. reducing the amount of asthma triggers in the home), and monitoring of symptoms . There are two types of asthma medications. Quick-relief medication (rescue inhalers) is used during an asthma episode. Long-term medication (corticosteroids) is used to reduce inflammation in the lungs and airways to bring about fewer and milder asthma episodes. Patients with persistent asthma require long-term control medication .

# Health Indicators for Asthma
Data sets on the national, state, and county level provide information on asthma prevalence or the number of individuals who have asthma . The two main sources of national asthma surveillance data used to generate regional, state, and county-level data are CDC's National Health Interview Survey (NHIS) and CDC's Behavioral Risk Factor Surveillance System (BRFSS). Both of these surveillance systems measure asthma prevalence using lifetime asthma diagnosis and current asthma. Since asthma is a syndrome, some individuals may have been diagnosed with asthma but do not currently experience asthma symptoms or episodes. Thus, the number and percentage of individuals who received an asthma diagnosis at some time during their lives are larger than the numbers and percentages who currently report having asthma.  .
BRFSS respondents with asthma are asked if they would like to participate in a subsequent telephone interview called the asthma call-back survey, which collects information on time since diagnosis, medication use, health care use, symptoms, risk factors, and disease management. National data and information from selected states were first collected by use of the asthma call back survey in 2003 . Georgia has participated in the asthma call-back survey since 2006.
Other health indicators that measure asthma morbidity and mortality include death records from the National Vital Statistics System, emergency department data from the National Hospital Ambulatory Medical Care Survey, and hospitalization data from the National Hospital Discharge Survey .   .

# National Asthma Prevalence Data
Note that on both of the previous two tables the number and percentage of individuals with lifetime asthma prevalence are larger than the number and percentage of those with current asthma prevalence. In addition, the data in these tables show that children are proportionally more likely to have asthma than adults.

# Risk Groups for Asthma
Prevalence data of current asthma from NHIS 2006-2008 reveal that among adults females are more likely than males to have asthma. Conversely, male children are more likely to have asthma than female children. In the overall US population, children, low-income individuals (< 100% Federal Poverty Level), and African Americans are proportionally more likely to have asthma . Those who lack health insurance are at risk for asthma morbidity and mortality, since they have less access to disease management services such as regular primary care visits, education and family supports, medication, and disease monitoring. Poorly managed asthma leads to increased hospitalizations and emergency department visits . Asthma morbidity and mortality are preventable with proper disease management.

# Asthma and the Housing Connection
As much as 40% of excess asthma risk in minority children may be attributable to exposure to residential allergens . Health disparities in asthma morbidity and allergic sensitization may be due in part to substandard housing and poverty. Substandard housing is more likely to have moisture and dampness problems, poor ventilation, deteriorated carpeting, structural deficits, and cockroach/pest problems, all of which create environmental conditions that may cause asthma or may trigger an asthma episode .

# Childhood Asthma Trends in the United States
Asthma prevalence remains at historically high levels following dramatic increase from 1980 to the late 1990s .

# Figure B: Asthma prevalence among children 0-17 years of age, United States, 1980-2005
Source: .
Despite the plateau in current asthma prevalence, physician office visits for asthma problems continue to grow since the year 2000 . This can be interpreted as a trend that illustrates better asthma control for children through regular preventative/primary care visits. Since 1992, the rate of emergency department visits has remained relatively stable-at around 100 visits for asthma per 10,000 children. Hospitalization rates follow a trend similar to prevalence rates during1980-2005. Child death rates from asthma declined in the mid-2000s following a rising trend from 1980 to the mid-1990s . The decline in asthma-related deaths may be related to improved disease management.

# Georgia Asthma Prevalence Data
In 2008, approximately 297,000 (12%) Georgia children ages 0-17 had asthma, and approximately 600,000 (9%) Georgia adults had asthma .
The 2006 BFRSS data listed below show which groups of adults in Georgia are more likely than their counterparts to have asthma . For example, an estimated 13.8% of Georgia adults with less than a high school education reported having asthma, as compared to 5.8% of college graduates. These statistics support the argument that low-income individuals, those with less than a high school education, the uninsured, and African Americans in Georgia are at greater risk for asthma.

# Fulton County Asthma Prevalence Data
The data from 2000-2008 indicate that an estimated 9.2% of adults in Fulton County currently have asthma. Data from BRFSS 2000-2004 allow an estimate that 11.1% of Fulton County African American adults have asthma, compared to 4.7% of white adults . The child asthma prevalence rate for Fulton County cannot be reported because the Relative Standard of Error is greater than 30%, making the estimate unreliable . In other words, asthma surveillance data were not collected on a large enough number of Fulton County children to allow generation of a reasonably accurate child asthma prevalence rate.  .

# Asthma Emergency Room Visits
The number of ER visits provides information on one aspect of health care utilization for asthma. Knowing the rate of ER visits per 100,000 in the population for each geographic area allows for comparisons between Georgia and Fulton County, two areas with populations of differing sizes. The Georgia Department of Community Health's Online Analytical Statistical Information System (OASIS) defines de-duplicated ER visits as the number of ER patients discharged live from non-federal, acute-care inpatient facilities (hospitals) for illness . Persons are counted only once if readmitted for the same chronic condition during a calendar year. De-duplicated visits also exclude people discharged dead, healthy newborn infants, and healthy mothers giving birth to newborn infants. Thus, de-duplicated visits provide the basis for an estimate of the number of patients in each geographic area who went to the ER for asthma. For more information on OASIS variables and their definitions, please refer to  and . Age-adjusted rates of deduplicated visits are derived by a statistical method that standardizes a specific geographic area's population by using the age distribution seen in a standard population, such as the general US population. Because of age adjustment, observed differences in rates across geographic areas are not due solely to the different proportion of people in various age groups who live in those areas. The age-adjusted rates therefore make it possible for one to compare geographic areas containing different age structures. The table above, which contains age-adjusted rates, shows that Fulton County has more asthma-related ER visits than Georgia-553.8 per 100,000 in Fulton County, compared to 413.7 per 100,000 for the state as a whole. By use of such an understanding of visits, de-duplicated visits, rates, and age-adjusted rates, one can correctly interpret the asthma and home injury hospitalization and death data presented later in this report.  .
The information in this table can be used to calculate a ratio that compares asthma ER visit rates for non-Hispanic blacks and non-Hispanic whites in Georgia, as well as in Fulton County. The use of de-duplicated, age-adjusted rates ensures that the difference in rates is not due solely to differences in age structure between the black and white populations of each geographic area. In Georgia, non-Hispanic blacks were 3.4 times more likely than non-Hispanic whites to visit the ER due to asthma. This ratio was calculated by dividing 783.1 by 227.3. In Fulton County, non-Hispanic blacks were 8.4 times more likely than non-Hispanic whites to visit the ER due to asthma. This ratio was calculated by dividing 1,048.1 by 124.5. The following racial health disparity ratios for asthma hospitalizations and asthma deaths are calculated by use of the same methodology.

# Figure C: Asthma ER visits by age group, de-duplicated, Fulton County, 2008

# Number of ER Visits Age Groups
Source: .
This figure shows that young children 0-4 and 5-12 years old have more ER visits for asthma than other age groups.    .

# Asthma Hospitalizations
In Georgia, non-Hispanic blacks were twice as likely as non-Hispanic whites to be hospitalized with asthma. In Fulton County, non-Hispanic blacks were 4.3 times more likely than non-Hispanic whites to be hospitalized with asthma.

# Number of Hospitalizations Age Groups
Source: .
The age groups with the largest number of asthma-related hospitalizations are 45-59-year olds and 60-74-year-olds.

# Asthma Deaths
Deaths due to asthma are relatively rare, thanks to preventative care, ongoing treatment, and monitoring. Because a single year's asthma deaths would not be great in number, he following data tables and graphs draw upon asthma death data over a series of years, 2001-2007. Note that there are more deaths among white and black females than among their male counterparts. The difference may be related to a national trend showing a greater asthma prevalence among adult females than among adult males.
Using Health Data to Highlight Milestones: A Cookbook for Non-profit Program Managers The average number of asthma deaths per year was calculated by dividing the total of 788 deaths by the number of years between within the year range (7 years). In Georgia, non-Hispanic blacks were 2.7 times more likely than non-Hispanic whites to die from asthma. In Fulton County, non-Hispanic blacks were 3.6 times more likely than non-Hispanic whites to die from asthma. In both Georgia and Fulton County, the age-adjusted death rates from asthma are significantly greater for non-Hispanic blacks than for their white counterparts.

# Secondhand Smoke and Cigarette Smoking Prevalence
Understanding Georgia residents' level of exposure to secondhand smoke and their cigarette smoking prevalence rates is important because tobacco smoke is both a cause and a trigger for asthma. Nationally, only 32% of households with smokers have adopted smoke-free policies in the home, policies that do not allow anyone, whether residents or visitors, to smoke inside the home . In Georgia, approximately 63% of middle school students with asthma and 68% of high school students with asthma are exposed to secondhand smoke .  .
The legal age to purchase tobacco products in Georgia is 18 years old; yet, a significant number of middle and high school students are cigarette smokers.  .
Note the large percentage of adults and high school students with asthma who also smoke cigarettes.

# Data Limitations
Ideally there would be readily available asthma data at the national, state, county, Atlanta, and NPU-V levels, data that were collected in a similar manner so that one could compare the prevalence rates across the various geographic areas. Unfortunately, asthma data for Atlanta and NPU-V are not readily available. Rather, asthma prevalence information is often obtained through nationwide interviews, and accurate numbers are not available for smaller geographic areas. The best available easy-to-access local data are at the Fulton County level; that data can be accessed through the Georgia Department of Community Health's OASIS database .

# Other Data Sources to Explore
 Emory University researcher Dr. Matthew Strickland (mjstric@emory.edu). Dr.
Strickland has 2002-04 data on asthma emergency room visits from 41 metro Atlanta hospitals. Dr. Strickland obtained the data in order to conduct a research study. The data use agreement prohibits him from sharing data specific to a hospital, but he can provide information on all 41 metro Atlanta hospitals in the aggregate form. He can sort the data by using the following variables: patient age, sex, race, health insurance, and zip code. The data set has already been processed to exclude same-day repeat visits by patients for the same condition. Dr. Strickland is open to helping the Center for Working Families obtain asthma data from this data set for NPU-V zip codes 30310, 30312, and 30315. Be aware that these zip codes cover both NPU-V and the neighborhoods south of NPU-V. The asthma information, after it is sorted by patient zip code, can further be categorized by patient age. The recommended age groupings are 0-4 years old, since asthma is difficult to diagnosis in young children and an asthma diagnosis for young children may not be accurate; 5-17 years old; 18-59 years old; and 60+ years old.

# Unintentional Injuries (Accidents) in the Home

# Background
Unintentional is defined as without the intent to harm; thus, unintentional injury deaths as well as injuries exclude homicide, suicide, and forms of assault. Injury results from contact with an external force or cause. Examples of such external causes include falls, mechanical accidents, injury by chemicals and poisons, injury by temperature extremes, electricity, or radiation, or the absence of necessities such as air . Home is a place where people live independently; home therefore does not include dormitories, prisons, nursing homes, long-term care facilities, mental health institutions, shelters, and barracks. In addition to the structure of a house, the home also entails areas surrounding the house, such as the yard, garage, and driveway . Unintentional home injury is a broad category that includes injuries related to the structure of a home (i.e., poor lighting at a staircase that can result in falls) and those injuries that happen within the home (e.g., accidental medication overdose).

# Health Indicators for Injury
Several of the health indicators for injury are similar to those mentioned previously in the asthma section, namely death records from the National Vital Statistics System, emergency department data from the National Hospital Ambulatory Medical Care Survey, and hospitalization data from the National Hospital Discharge Survey. The National Electronic Injury Surveillance System is an additional source for emergency department visits data collected from emergency departments of 100 US hospitals. Non-fatal injury data are collected at the national level by use of the National Health Interview Survey (NHIS), an in-person interview that asks respondents about the number of injuries they sustained that required advice from a health care professional and that resulted in missed school/work days within a given period of time . A major difficulty in gathering unintentional home injury data is that the location where the injury occurred is not recorded for 33% of unintentional injury deaths, and data are missing regarding 25% of unintentional injuries resulting in emergency department visits. Thus, the available sources of injury data most likely underestimate the true numbers and rates of unintentional injuries that occur in the home .

# National Fatal and Non-Fatal Unintentional Injuries
More than 91,000 individuals die each year in the United States from unintentional injury. Approximately 20% of these deaths occur in the home-more than 18,000 deaths in the home per year. An estimated 28 million nonfatal unintentional injuries occur each year. Approximately 42% of these events occur in the home-nearly 12 million nonfatal home injuries per year .
Note that fatal injuries are measured by the number of deaths, while nonfatal injuries are measured by the number of events, since a person could have more than one nonfatal injury per year.   .
Note that the above listed deaths may or may not have occurred in the home. Motor vehicle injury, a type of injury outside the home, was the leading cause of unintentional injury deaths for people ages 5-34 and 55-64.  .
Georgia is ranked 8 th in unintentional home injuries when all types of home injuries are combined (falls, fires/burns, poisonings, drowning, suffocations, other).

# Falls
Falls are defined as all accidental injuries caused by an individual's losing his/her balance (definition from OASIS, #external) . The following table shows that the majority of fatal falls occur within the home.   .
This table shows the total number of fatal falls that occurred within each geographic area during 2007, but it does not denote whether these falls happened inside or outside the home. The previous table shows the percentage of fatal falls by home, other than home, or by unknown location. By combining these two pieces of information, one can estimate the number of fatal falls that happened within Georgia and Fulton County homes.
Example: Unintentional fall deaths that occurred in the home in Georgia = 580 x 0.54 = 313, a rough estimate that most likely under-states the true number of fall deaths that occur in the home because location was unknown for 11% of fall deaths at the national level. This calculation can be used to estimate the number of unintentional injury deaths that occur within homes whenever the percentage listed under the "unknown" location is not large, for example, the calculation can be used to estimate fire/burn and drowning injury deaths.  When one is gathering health data from the OASIS online database, using the variables "de duplicated visits" or "de-duplicated discharges" ensures that one is capturing only the patients who sustained a nonfatal injury and were released live from the ER or hospital. In OASIS, all hospital discharges having external causes (injuries) have been assigned their appropriate valid External Cause of Injury Code, in accordance with State and Territorial Injury Prevention Directors Association 2003 guidelines. The standards can be found at  (definition from OASIS, ) . In addition to falls, OASIS contains fatal and nonfatal injury data for poisoning, fire, and drowning.   .

# Unintentional Nonfatal Fall Injuries
Medical costs and work loss costs due to other types of fatal unintentional injuries, such as fire/burn, poisonings, drowning, and suffocations, can be calculated by use of the WISQARS cost of injury reports for the United States as a whole and by state .  .
The average medical costs and work loss costs in the above two tables refer to lifetime costs from an unintentional nonfatal fall (definition from WISQARS, ). Costs from nonfatal unintentional injury, as measured by hospitalizations and ER visits, are available from WISQARS only at the national level . Costs of unintentional nonfatal injury data are available through WISQARS for other injuries, such as fire/burn, poisonings, drowning, and suffocations.

# Cost of Unintentional Falls, Georgia and Fulton County
An estimate of costs related to nonfatal injuries at the state or county level can be calculated by use of the number of nonfatal injuries for Georgia or Fulton County multiplied by the national average medical and/or work loss costs. Costs would be even greater if medical costs are combined with work loss costs.
National average cost is based on 2005 dollars. Current costs would be greater due to inflation. 2005 dollars can be updated to current year's dollars by use of the US Department of Labor's consumer price index, which includes adjustments for inflation on both all costs and medical costs. For more information, visit  This method of calculation can be used for other types of nonfatal injuries when state or county level data on the number of injuries are available through WISQARS or OASIS. When using this method of calculation for fatal injuries, a person should use average medical costs or work loss costs generated from WISQARS cost of injury reports for Georgia, rather than national costs, to improve the accuracy of the estimated costs.

# Table 33: Risk groups for falls

# Fatal Falls, National
Nonfatal Falls, National Adults 70 years and older had the highest rates of death due to falls in the home, followed by 60 to 69 year olds Males experienced a higher rate of death from falls than females Females experienced a higher rate of nonfatal home falls than males Adults 70 years and older have the highest rates of nonfatal falls in the home Children under 5 have the second highest rate of nonfatal home falls Source: From .

# Poisoning
Poisoning is the act of ingesting or coming into contact with a harmful substance that may cause injury, illness, or death (definition from OASIS, #external). Poisoning is a broad category that includes harm from such substances as medications, narcotics, alcohol, carbon monoxide gas, pesticides, soaps, and detergents (WHO ICD codes for external causes). Data on specific types of poisonings can be obtained for the national and state level by use of CDC's WISQARS leading causes of death reports. The WISQARS database allows one to drill down by selecting unintentional injuries under an age group  poisonings  International Classification of Disease (ICD) 10 codes for each substance that caused the poisoning (). The WISQARS drilling down feature can be used with any type of unintentional injury, including falls, suffocations, drowning, etc.

# Carbon Monoxide Poisoning
Carbon monoxide, or CO, is a toxic gas that is colorless and odorless. CO is given off when fuel or other materials are burned. Breathing CO can cause severe illness or death in minutes.
CO exposure can occur from   using poorly maintained or unvented heating equipment  warming up vehicles in garages  using a gas stove or oven to heat the home  leaving chimneys clogged or blocking heating exhaust vents  running generators or gas-powered tools in enclosed areas or near windows, doors, or vents In 2006, there were 25 deaths in Georgia from CO poisoning, with an age-adjusted death rate of 0.27 per 100,000 . Georgia's CO deaths and death rates can be compared to those of other states by using the CDC's National Environmental Public Health Tracking Network online database .  .
It is necessary for one to be aware that the location is unknown for 33% of poisoning deaths; thus, using the national percentage of home or other-than-home deaths as a basis will not provide an accurate estimate of poisoning deaths that occurred in the home in Georgia.  .
Georgia and Fulton County data on unintentional nonfatal poisonings, as measured by hospitalizations and ER visits, can be obtained from the Georgia Department of Community Health's OASIS online database.

# Table 36: Risk groups for poisonings

# Fatal Poisoning, National
Nonfatal Poisoning, National Males experienced a higher rate of death than females  Children under 5 had the highest rate of nonfatal poisoning in the home Females are more likely to experience nonfatal poisoning than males  Fatal Poisoning, Georgia 35-54 year olds had the highest poisoning death rate among all age groups 40% of these deaths were caused by narcotics and hallucinogens 

# Fire/Burn
A fire injury is defined as accidental exposure to smoke, fire, and flames. A burn injury is defined as accidental contact with heat and hot substances .  .
Note that the vast majority of fatal fires/burns (90%) occur within the home.  .
An estimate of the number of fire/burn deaths that occurred within homes in Georgia can be calculated by use of the following method of combining two pieces of data, namely the number of fatal fire/burn injuries in Georgia in 2007 and the national percentage of fatal fire/burn injuries that occur within the home.
Example: Unintentional fire/burn deaths that occurred in the home in Georgia = 131 x 0.90 = 118 1.4 Source: .
One should be aware that the Georgia Department of Community Health's OASIS database contains Fire and not Fire/Burn data. Georgia and Fulton County data on unintentional nonfatal fire injuries, as measured by hospitalizations and ER visits, can be obtained from the Georgia Department of Community Health's OASIS online database. For Fire/Burn data, please refer to CDC's WISQARS database. Rates were highest among females  children under 5 years old  Children 4 years old and younger

# Risk Groups for Fires/Burns
Older adults 65 years and older African Americans and Native Americans
Poorest Americans
Persons living in substandard housing 

# Choking/Suffocation
Choking/Suffocation is defined as all accidental injuries from threats to breathing, including choking on food, vomit, or a foreign object; however, the category excludes smoke inhalation . The top causes of choking/suffocation deaths in the home are inhalation and ingestion of food that causes obstruction of the respiratory tract or suffocation, unintentional mechanical suffocation (e.g., accidental hanging except in a bed or cradle), and accidental suffocation in a bed or cradle .  .
One should be aware that the location is unknown for 62% of choking/suffocation deaths, and thus using the national percentage will not provide an accurate estimate of choking/ suffocation deaths that occurred in the home in Georgia.  .
Georgia Department of Community Health's OASIS database does not include data on choking/suffocation. Therefore, this section does not contain a Fulton County statistic on choking/suffocation deaths.
Unintentional nonfatal choking/suffocation injury data at the national level are available through CDC's WISQARS database ().

# Risk Groups for Chokings/Suffocations

# Table 43: Risk groups for chokings/suffocations
Males had a higher rate of home choking and suffocation deaths than females Children under 9 years old, especially those younger than 5, are at high risk Older adults 70+ years old are at high risk Source: .

# Drowning
Drowning is defined as suffocation as a result of being submerged in water or other fluid (definition from OASIS, #external). Drowning injuries include incidents that occur in bathtubs, swimming pools, and natural bodies of water . In Georgia, 9% of drownings occurred in bathtubs, and14% of drownings occurred in swimming pools .  .  .
An estimate of the number of drowning deaths that occurred within homes in Georgia can be calculated by use of the following method of combining two pieces of data, namely the number of fatal drowning injuries in Georgia in 2007 and the national percentage of fatal drowning injuries that occur within the home.
Example: Unintentional drowning deaths that occurred in the home in Georgia = 118 x 0.23 = 27
Georgia and Fulton County data on unintentional nonfatal drowning/submersion injuries, as measured by hospitalizations and ER visits, can be obtained from the Georgia Department of Community Health's OASIS online database.

# Risk Groups for Drowning

# National
Children younger than 5 years old had a higher rate of drowning in the home than all other age groups Males had a higher rate of home drowning than females  African Americans  The State of Georgia as a whole Drowning was the second leading cause of unintentional injury deaths for children 1 to 4 years old Black males had the highest drowning rate (3.2 per 100,000 in population), followed by white males 

# Data Limitations
Similar to the data limitations described in the asthma section, unintentional home injury data are not readily available at the Atlanta and NPU-V levels. Fatal injury data are collected through national and state vital statistics, but often the location of the fatal injury is not included on death records, making it difficult to determine if the event happened within the home. A main surveillance system for nonfatal injuries is a nationally representative in-person interview called the National Health Interview Survey, which is not designed to provide data specific to such smaller geographic areas such as states, counties, and cities. The best available, easy-to-access local data on fire, drowning, fall, and poisoning injuries are at the Fulton County level; that data can be accessed through the Georgia Department of Community Health's OASIS database. CDC's WISQARS database has Georgia-level data for fire/burn, drowning, suffocation, fall, and poisoning injuries.  US Consumer Product Safety Commission () Injury information related to such consumer products as bedding, toys, cribs, and appliances.

# Other Data Sources to Explore
 The Georgia Poison Control Center fields calls on poisonings and helps consumers with pill identification, in addition to answering questions on environmental health issues. Data on calls to the Center can be sorted by unintentional or intentional injury, type of poisoning, and zip code of caller. For more information, please contact the following individuals: o Dr. Robert Geller RGELLER@georgiapoisoncenter.org o Tanneshia Sherrer TSHERRER@georgiapoisoncenter.org o Stephanie Hon SHON@georgiapoisoncenter.org o anthony.oloni@phiconcorp.com o rgorodetsky@georgiapoisoncenter.org  The Georgia Department of Community Health's Smoke Alarm Installation and Fire Safety Education Program is a rural-oriented program that uses firefighters who go door-to-door installing smoke alarms in homes of low-income residents. The program identifies homes at high risk for fire as those with the following characteristics: o Homes poorly maintained o Homes with inadequate heating or wiring o Homes with large numbers of children under 5 years old and adults over 65 years old o Homes located in low-income neighborhoods, homes inhabited by predominately minority residents, and homes with high turn-over in residents Contact Steve Davidson (sdavidson@dhr.state.ga.us) for more information about the program and how to adapt the program's lessons learned to an urban setting. The table above visually represents the convergence of various at-risk populations that are disproportionally affected by childhood lead poisoning, asthma, and unintentional home injuries.

# Conclusion
As the use of color patterns illustrates, African Americans are a risk group for lead poisoning as well as asthma and home injuries. This racial health disparity is related to the ongoing discrimination experienced by African Americans in the United States. Discrimination, combined with segregated communities where substandard housing is concentrated in lowincome or predominately minority neighborhoods, causes African Americans to have more exposure to lead paint, mold, pests, and housing without adequate safety devices such as smoke alarms.
The table also illustrates the importance of addressing health and housing from a holistic approach, rather than by focusing on each health issue separately. The national Green and Healthy Homes Initiative (GHHI) seeks to improve health through primary prevention interventions that address the environmental exposures and safety issues related to homes. By building collaborations and bringing multiple resources to bear, GHHI's one-touch model includes housing improvements to end lead exposure, reduce indoor asthma triggers, and prevent injuries, along with weatherization and structural renovations to homes of low-income residents.
The convergence of at-risk groups lends support to GHHI's comprehensive approach that draws upon the resources and expertise of non-profit organizations, philanthropy, government agencies, and for-profit companies for synergy to tackle the interconnectedness of health and housing problems.  Similar maps can be generated by use of 2010 census data once that information is available.

# Figure H: Percent of Rental Housing pre Census Tract
This map shows the percentage of rental housing in each census tract of NPU-V. The percentage was calculated by use of 2000 census data of total renter-occupied housing units divided by total housing units.

# Figure I: Percentage of Pre-1980 Housing per Census Tract
This map shows the percentage of pre-1980 housing in each census tract of NPU-V. The percentage was calculated by use of 2000 census data of total housing units that are pre-1950 + 1950s + 1960s + 1970s divided by total housing units.

# Figure J: Percent of Pre-1950 Housing per Census Tract
This map shows the percentage of pre-1950 housing in each census tract of NPU-V. The percentage was calculated by use of 2000 census data of total pre-1950 housing units divided by total housing units.

# Figure K: Percent of Households with Incomes less than $20,000 per year
This map shows the percentage of households with incomes less than $20,000 per year in each census tract of NPU-V. The percentage was calculated by use of 2000 census data of total households with incomes of less than $10,000 + $10,000 to $14,999 + $15,000 to $19,999 divided by total households.

# Figure L: Percent of Children 0 to 5 years old Living below Poverty per Census Tract
This map shows the percentage of children 0 to 5 years old living below poverty in each census tract of NPU-V. The percentage was calculated by use of 2000 census data of total children 0 to 5 years old living below poverty divided by total children 0 to 5 years old.