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State Injury Indicators ReportSecond Edition — 1999 Data

EditorsChristopher Thomas, MS, CHES

Jacqui Butler, MPAMegan Davies, MD

Renee Johnson, RPT, MSPH

Department of Health and Human ServicesCenters for Disease Control and Prevention

National Center for Injury Prevention and Control

February 2004

Centers for Disease Control and PreventionJulie L. Gerberding, MD, MPH

Director

National Center for Injury Prevention and ControlSue Binder, MD

Director

The editors acknowledge the following individuals who helped review this report:

Robert Anderson, PhD Steve Kinchen, BS, ICSLee Annest, PhD Melvin Kohn, MD, MPHKim Blindauer, DVM, MPH James Mercy, PhDJulie Bolen, PhD Len Paulozzi, MD, PhDVictor Coronado, MD, MPH Kavitha Raman, BDS, MPHAlex Crosby, MD, MPH Richard Sattin, MD, FACPAnn Dellinger, PhD, MPH David Sleet, PhDLynda Doll, PhD Ellen Sogolow, PhDLois A. Fingerhut, MS Cecil Threat, MPHJulie Gilchrist, MD Roger Trent, PhDRobin Ikeda, MD, MPH

We also thank Jane Mitchko, Sandra Bonzo, Marilyn Kirk, and the staff of theOffice of Communication Resources, National Center for Injury Prevention and Control,

for contributing to the production of this report.

The State Injury Indicators Report, Second Edition — 1999 Data is a publication of Centers for Disease Control andPrevention, National Center for Injury Prevention and Control.

Suggested Citation: Thomas C, Butler J, Davies M, Johnson R, State Injury Indicators Report, Second Edition — 1999 Data.Atlanta (GA): Centers for Disease Control and Prevention, National Center for Injury Prevention and Control; 2004.

Arizona Department of Health ServicesArdis Decker, MPHTim Flood, MD

California Department of HealthArt Ellis, MAJennifer Harper, MSPHRoger Trent, PhD

Colorado Department ofPublic Health and Environment

Holly Hedegaard, MD, MSPHKaty Meng, PhD

Delaware Health and Social Services,Division of Public Health,Office of Emergency Medical Services

Steven Blessing, MATripthi M. Mathew, MD, MPH

Florida Department of HealthSteve Dearwater, MS

Contributors

Georgia Department of Human Resources,Division of Public Health

Kristen Mertz, MD, MPHVietdoan Nguyen, MPHManxia Wu, MD, MPHDenise Yeager

Hawaii Department of HealthDan Galanis, PhDEric Tash, MPH

Kansas Department of Healthand Environment

Carol Moyer, MPH, RNJulie Sergeant, MSEd

Kentucky Cabinet for Health Services,Department for Public Health

Michael Singleton, MS

Louisiana Department of Health and Hospitals,Office of Public Health

Giesle Hall, BS

Contributors – i

Commonwealth of Massachusetts,Department of Public Health

Patrice Cummins, MPHHolly Hackman, MD, MPHVictoria Ozonoff, PhD

Michigan Department of Community HealthFawzia AhmedLinda Scarpetta, MPH

Minnesota Department of HealthAnna Gaichas, MSMark Kinde, MPHMark PhillipsJon Roesler, MSMinnesota Hospital and Healthcare Partnership

Nebraska Health and Human ServicesKeith HansenMing Qu, MEd

New Mexico Department of HealthBarbara F. Chatterjee, MSAjoy Kumar, MBBS, MPHNew Mexico Health Policy CommissionState of New Mexico, Santa Fe, New Mexico

North Carolina Department ofHealth and Human Services

Jeanne Givens, MSSWCatherine Sanford, MSPHDorothee Schmid, MABradford Woodard, MS

North Dakota Department of HealthCarmell BarthRod Gilmore

Ohio Department of HealthNan Migliozzi, MSN

Edward Socie, MS

Oklahoma State Department of HealthPam Archer, MPHJeffrey CarlisleKristen Eberly, MPHSue Mallonee, MPH, RNTracy Mankin, MPH

Oregon Department of Human Services,Oregon Public Health Services

Janice D. Alexander, PhDMelvin Kohn, MD, MPH

Contributors – ii

South Carolina Department ofHealth and Environmental Control

Lou-Ann Carter, MSGeorgette Demian, MPHMary Glover

Texas Department of HealthTammy Sajak, MPHDavid Zane, MS

Utah Department of HealthTrisha Keller, MPH, RNMichelle Moskos, PhD, MPH, HSATong Zheng, MS

Vermont Department of HealthStephanie Courcy, MPHCaroline Dawson, MS, MPA

Washington State Department of HealthMary Le Mier, MPH

Wisconsin Department ofHealth and Family Services

Vinod Daniel, MBBS, MPHLinda Hale, RN, BSN, CEN, EMTJoseph Olson, BS

Contributors – iii

Foreword — vii

Introduction — 1Methods — 2Future Efforts — 7

1. All-Injury Indicators — 9Figures — 111a. Hospitalizations for All Injuries (Overall), 19991b. Hospitalizations for All Injuries by Sex, 19991c. Hospitalizations for All Injuries by Age, 1999

2. Traumatic Brain Injury Indicators (TBI) — 17Figures — 192a. TBI Hospitalizations (Overall), 19992b. TBI Hospitalizations by Sex, 19992c. TBI Hospitalizations by Age, 19992d. TBI Fatalities (Overall), 19992e. TBI Fatalities by Sex, 19992f. TBI Fatalities by Age, 1999

3. Drowning Indicators — 27

Figures — 293a. Near Drowning Hospitalizations (Overall), 19993b. Near Drowning Hospitalizations by Sex, 19993c. Near Drowning Hospitalizations by Age, 19993d. Drowning Fatalities (Overall), 19993e. Drowning Fatalities by Sex, 19993f. Drowning Fatalities by Age, 1999

4. Fire-Related Indicators — 37Figures — 394a. Fire-Related Hospitalizations (Overall), 19994b. Fire-Related Hospitalizations by Sex, 19994c. Fire-Related Hospitalizations by Age, 19994d. Fire-Related Fatalities (Overall), 19994e. Fire-Related Fatalities by Sex, 19994f. Fire-Related Fatalities by Age, 19994g. Percentage of Homes with Smoke Alarms Tested

in the Last Month, 1999, Behavioral Risk FactorSurveillance System

4h. Percentage of Homes without Smoke Alarms,1999, Behavioral Risk Factor Surveillance System

5. Motor Vehicle Indicators — 49Figures — 515a. Motor Vehicle Traffic and Non-Traffic

Hospitalizations (Overall), 19995b. Motor Vehicle Traffic and Non-Traffic

Hospitalizations by Sex, 19995c. Motor Vehicle Traffic and Non-Traffic

Hospitalizations by Age, 19995d. Percentage of Adults Reporting Driving After

Perhaps Having Too Much to Drink, in the PastMonth, 1999, Behavioral Risk Factor SurveillanceSystem

5e. Percentage of Adults Reporting Driving AfterPerhaps Having Too Much to Drink, in the PastMonth, by Sex, 1999, Behavioral Risk FactorSurveillance System

v

Table of Contents

vi

8. Homicide Indicators — 83Figures — 858a. Homicide (Overall), 19998b. Homicide by Sex, 19998c. Homicide by Age, 1999

9. Suicide Indicators — 91Figures — 939a. Suicide Attempt Hospitalizations (Overall), 19999b. Suicide Attempt Hospitalizations by Sex, 19999c. Suicide Attempt Hospitalizations by Age, 19999d. Suicide (Overall), 19999e. Suicide by Sex, 19999f. Suicide by Age, 19999g. Percentage of High School Students Reporting

Suicide Attempt During Past 12 Months, 1999,Youth Risk Behavior Survey

9h. Percentage of High School Students ReportingSuicide Attempt During Past 12 Months by Sex,1999, Youth Risk Behavior Survey

Appendix — Instruction for Calculating NationalPublic Health Surveillance System IndicatorsUsing 1999 Data — 103

5. Motor Vehicle Figures (Continued)5f. Percentage of Adults Reporting Driving After

Perhaps Having Too Much to Drink, in the PastMonth, by Age, 1999, Behavioral Risk FactorSurveillance System

5g. Percentage of High School Students ReportingAlways Using Safety Belts, 1999, Youth RiskBehavior Survey

5h. Percentage of High School Students ReportingAlways Using Safety Belts by Sex, 1999,Youth Risk Behavior Survey

5i. Alcohol-Related Crash Deaths, 1999

6. Poisoning Indicators — 63Figures — 656a. Poisoning Hospitalizations (Overall), 19996b. Poisoning Hospitalizations by Sex, 19996c. Poisoning Hospitalizations by Age, 19996d. Poisoning Fatalities (Overall), 19996e. Poisoning Fatalities by Sex, 19996f. Poisoning Fatalities by Age, 1999

7. Firearm–Related Indicators — 73Figures — 757a. Firearm-Related Hospitalizations (Overall), 19997b. Firearm-Related Hospitalizations by Sex, 19997c. Firearm-Related Hospitalizations by Age, 19997d. Firearm-Related Fatalities (Overall), 19997e. Firearm-Related Fatalities by Sex, 19997f. Firearm-Related Fatalities by Age, 1999

The Centers for Disease Control and Prevention (CDC) Injury Center, The Council of State

and Territorial Epidemiologist (CSTE), and the State and Territorial Injury Prevention Directors’

Association (STIPDA) are pleased to bring you this second edition of the State Injury Indicators

Report with 1999 data. Twenty-six state health departments voluntarily participated in this

surveillance effort. The data inside represent continued progress toward routine surveillance

and reporting of injury indicators in all states. This second edition incorporates data from a

greater number of states and includes data on the poisoning indicator, with both gender and

age-specific rates. The indicators were calculated by using state-level data from death certificates

and hospital discharge records coupled with data from several national surveillance systems. As

more states join in this surveillance, we can present a broader picture of the burden of injuries

and better identify priorities for prevention. We look forward to increased state participation in

future reports.

vii

Foreword

Introduction – 1

Injury surveillance is one of the most important and basicelements of injury prevention and control. It helps deter-mine the magnitude of injury morbidity and mortality,the leading causes of injury, and the population groups andbehaviors associated with the greatest risk. Surveillance datais fundamental to determining program and preventionpriorities. Furthermore, this data is crucial for evaluating theeffectiveness of program activities and for identifying prob-lems that need further investigation.

Fifty-nine million injuries were reported in 1995,resulting in 37 million hospital emergency departmentvisits and 2.6 million hospital discharges. Injuries alsoaccounted for 37% of all hospital emergency departmentvisits, and about 8% of all short-stay hospital discharges.That year, 147,891 people died from injuries: 61% fromunintentional injuries, 21% from suicides, and 15% werehomicides. Death from injury is the leading cause of yearsof potential life lost before age 75 in the United States.1

The mission of public health includes prevention,mitigation, assuring that the injured have access to treat-ment, and reducing injury-related disability and death.1

Its scope encompasses injuries involving any mechanism(e.g., firearm, motor vehicle, and burn), and includes bothintentional and unintentional injuries. An important partof the public health mission is to emphasizethat injuries are preventableand to dispel the miscon-ception that injuries areunavoidable.

Recognizing the need for more comprehensive injurysurveillance data, the State and Territorial Injury PreventionDirectors’ Association (STIPDA) produced Consensus Recom-mendations for Injury Surveillance in State Health Departments in1999.2 These recommendations were developed by a workinggroup representing STIPDA; the Council of State and Territo-rial Epidemiologists (CSTE); Centers for Disease Control andPrevention (CDC) and its National Center for Injury Preven-tion and Control (NCIPC); and the National Association ofInjury Control Research Centers (NAICRC).

Consensus Recommendations identifies 14 specific injuriesand injury risk factors to be placed under surveillance byall states and 11 data sets to monitor these injuries and riskfactors. The goal is to improve state-based injury surveillanceto better support injury prevention programs and policies.By enhancing and standardizing injury surveillance at thestate level, its integration with overall public health surveil-lance as part of the National Public Health SurveillanceSystem (NPHSS)3 will be much easier. In tandem with theConsensus Recommendations, CSTE and STIPDA developedinjury indicators that were formally adopted for inclusionin NPHSS.4,5 The NPHSS injury indicators add to otherindicators developed by CSTE for chronic diseases andother areas.4

Introduction

What is an Injury Indicator?An injury indicator describes a health outcome of an injury, such as

hospitalization or death, or a factor known to be associated with an injury,such as risk or protective factor among a specified population.

Introduction – 2

MethodsBecause injury rates often vary dramatically by sex, overallage-adjusted rates for hospitalization and fatal indicatorswere calculated as the weighted average of the male andfemale rates for each indicator:

However, in low-incidence indicators, it was not alwayspossible to calculate a stable rate for females. In these cases,the overall age-adjusted rate was calculated using the sumof the male and female cases and the sum of the male andfemale populations by age within the state.

Participating states reported on 12 of the 14 injuries andrisk factors in Consensus Recommendations:

➤ motor vehicle injuries,➤ alcohol involvement in motor vehicle deaths,➤ self-reported seat belt and child safety seat use,➤ homicide,➤ suicide,➤ suicide attempts,➤ firearm injuries,➤ traumatic brain injuries,➤ fire and burn injuries,➤ self-reported smoke alarm use,➤ submersion injuries,➤ poisoning.

For some of these conditions and risk factors, multiplesources of surveillance data are recommended; therefore,two or more surveillance indicators are used.

Two conditions in Consensus Recommendations are notreported here: traumatic spinal cord injuries and injuriesfrom falls. Surveillance case definitions and recommenda-tions for data sources are not yet final for these injuries.STIPDA is convening its fourth Injury Surveillance Work-group to develop case definitions for these remaininginjuries.

States used a total of five data sets to report on21 indicators: the Fatality Analysis Reporting System (FARS),the state-based Youth Risk Behavior Survey (YRBS), theBehavioral Risk Factor Surveillance System (BRFSS), statevital records, and state hospital discharge data (HDD).

Fatality Analysis Reporting System (FARS)FARS, coordinated by the National Highway Traffic SafetyAdministration (NHTSA), contains data on all fatal trafficcrashes that occur in the 50 states, the District of Columbia,and Puerto Rico. To be included in FARS, a crash mustinvolve a motor vehicle traveling on a public roadway andresult in the death of a person (either a vehicle occupant ora non-motorist) within 30 days of the crash. The FARS filecontains a description of each fatal crash reported. Morethan 100 coded data elements characterize each crash, thevehicles, and the people involved. NHTSA considers afatal motor-vehicle crash to be alcohol-related if either adriver or non-occupant (e.g., pedestrian or bicyclist) hada blood alcohol concentration (BAC) greater than or equalto 0.01 g/dL.6

Age- Age-Adjusted Male Adjusted Female Male Population Female Population Rate Rate

+

X

=

+X

Overall Rate Male Population Female Popluation

FARS does not include non-traffic crashes, such as thoseoccurring on driveways and other private property. It alsodoes not include deaths occuring more than 30 days after themotor vehicle crash. Because BACs are not available for allpersons involved in fatal crashes, NHTSA’s estimates for thenumber of alcohol-related traffic fatalities are based on adiscriminant analysis of information from all cases for whichdriver or non-occcupant BAC data are available.6

Youth Risk Behavior Survey (YRBS)YRBS, a component of the Youth Risk Behavior SurveillanceSystem, is managed by the National Center for ChronicDisease Prevention and Health Promotion (NCCDPHP) atCDC. It is a self-administered, school-based survey con-ducted biennially in many locations throughout the countryamong ninth through twelfth-grade students. State and localdepartments of education and health conduct the survey,and CDC analyzes the data. The YRBS monitors risk behav-iors associated with the leading causes of injury and deathamong teenagers.7

YRBS data apply only to youth who attend school. Inaddition, the extent of underreporting or overreporting ofbehaviors cannot be determined, although the surveyquestions demonstrate good test-retest reliability. Interstatecomparisons must be interpreted cautiously as methodsused to collect YRBS data may vary.7

Among the 26 states included in this report, 11 con-ducted a YRBS in 1999 with overall participation rates of atleast 60%. CDC requires a minimum overall participationrate of 60% to generalize a state’s population. This reportpresents weighted data from these 11 states.

Behavioral Risk FactorSurveillance System (BRFSS)CDC’s National Center for Chronic Disease Prevention andHealth Promotion also manages the BRFSS. This is a broaderongoing survey. It is a state-based, random-digit-dialedtelephone survey of the noninstitutionalized U.S. populationover age 17. BRFSS monitors risk behaviors associated withthe leading causes of disease, injury, and death.8

Because BRFSS is telephone-based, population sub-groups less likely to have telephones, such as persons oflow socioeconomic status, may be underrepresented. Inaddition, data are self-reported and may be biased. For risk-reduction factors such as self-reported use or testing ofsmoke detectors, these data may not uniformly representsafe and effective use.8

State Vital RecordsDeath registration is the responsibility of individual states.The funeral director and the physician who certifies thecause of death are usually responsible for the personal andmedical information recorded on the death certificate. Thecause-of-death section on the certificate is basically the samein all states, and is organized according to World HealthOrganization (WHO) guidelines. Local registrars assurethat all deaths in their jurisdictions are registered and thatrequired information is on death certificates before sendingthem to the state registrar. State registrars number and filethe death certificates; certificates of nonresidents are sent totheir states of residence. All states send death certificate datato the National Vital Statistics System, managed by CDC’sNational Center for Health Statistics.9

Introduction – 3

Data are limited to what is reported on death certifi-cates. The degree of detail in reporting varies among juris-dictions. In general, death certificate data provide limitedinformation about circumstances of injury incidents orcontributing factors. Deaths associated with some injuries,especially suicide, may be underreported.

The number and type of cause-of-death fields to whichstates have access also vary. Two of the states contributing tothis report had access to a death certificate database listingonly the underlying cause of death. In contrast, the other24 states each had access to a database listing both underlyingcause of death and contributing causes of death. States with-out access to multiple contributing cause-of-death fieldscannot calculate fatality rates for traumatic brain injury(TBI) because the diagnostic codes that make up that casedefinition reside in the contributing cause-of-death fields.

In 1999, a new classification scheme—the TenthRevision of the International Classification of Diseases(ICD-10)—was implemented in the United States. TheNinth Revision of the ICD (ICD-9), had been in use from1979 through 1998. The ICD has been revised about everyten years since 1900. The purpose of revisions is to stayabreast of medical advances in terms of disease and injurynomenclature and etiology.10 ICD-10 differs from ICD-9 inseveral respects. ICD-10 is more detailed, containing8,000 categories compared with only 5,000 categories inICD-9. ICD-10 uses alphanumeric codes compared withnumeric codes in ICD-9. Some additions and modificationswere made to the chapters in the ICD. Some of the codingrules and rules for selecting the underlying cause of deathhave also been changed.10 These changes create a disconti-nuity in cause-of-death statistics between 1979–1998 andthose from 1999 forward.

The CDC’s National Center for Health Statistics (NCHS)is carrying out comparability studies to measure the effectsof the newly revised ICD on the comparability with theprevious revision of mortality statistics by cause of death.10

These studies involve the dual classification of a single year’smortality data, i.e., classifying the underlying cause of deathon mortality records by both the new revision and theprevious revision. The key element of a comparability studyis the comparability ratio, which is derived from the dualclassification. It is calculated by dividing the number ofdeaths classified by the new revision by the number ofdeaths classified by the previous revision. The resultingratios represent the net effect of the new revision on cause-of-death statistics. NCHS has released preliminary estimatesof comparability ratios using the “List of 113 Selected Causesof Death” (113-cause list). The number 113 refers to thenumber of mutually-exclusive categories in the list. The113-cause list actually contains a total of 135 cause-of-deathcategories, including accidents (unintentional injuries),intentional self-harm (suicide), and assault (homicide).

Preliminary results show comparability ratios for inten-tional self-harm and assault (homicide) are very close to 1.0.For unintentional injuries, a comparability ratio of 1.0303indicates an increase in death rates of 3% due to therevisions. Virtually all of this increase involves shifts fromnatural causes in ICD-9 to unintentional injuries in ICD-10resulting from changes in coding rules that assign injury asunintentional injury. Within the category unintentionalinjury, motor vehicle crashes (MVC) deserve special atten-tion. The preliminary MVC comparability ratio was 0.8527.The reason for this 15% decrease is that in ICD-10, the injurymust involve a “motor” vehicle. In ICD-9, in the absence of

Introduction – 4

the term “motor” when a vehicle crash was reported asoccurring on a highway or road, the assumption was toclassify the crash as involving a motor vehicle. The ICD-10convention does not allow this assumption and classifiessuch crashes as involving unspecified vehicles (other landtransport accidents). However, for U.S. data, it has beendecided that if the crash occurred on a highway or road,classification to motor vehicle accident is appropriate. Thischange in classification was effective in the United Stateswith the release of preliminary NCHS 1999 mortality dataand results in a revised comparability ratio of 0.9754. Thisratio is only applicable to data in which the classificationchange for motor vehicle crashes was implemented.10 Somestates’ final death files do not include this change. For thisreason, motor vehicle crash deaths are not reported as a1999 indicator. Since all the indicators are calculated fromstate databases, the rates would not be comparable.

In this report, only one state—Arizona—did not imple-ment ICD-10 for 1999 death data. Since the rates for Arizona,based on ICD-9, are not directly comparable to the ratesreported by the other 25 states, death rates for Arizona arenot displayed for 1999.

Comparability ratios can be used as factors to adjustmortality statistics for cause of death classified by ICD-9to be comparable to rates for the same causes classified byICD-10. The ICD-10 mortality rates displayed in the StateInjury Indicators Report, Second Edition — 1999 Data shouldnot be compared directly to those displayed in the firstState Injury Indicators Report, which displayed 1997 and1998 mortality rates based on ICD-9. The preliminary com-parability ratios published by NCHS can be applied to themortality indicators only for those conditions in which the

code groupings are exactly the same in both the 113-causelist and the fatal indicator definition (fatal fire-related inju-ries, homicide, and suicide).

State Hospital Discharge Data (HDD)More than half of all states maintain databases of hospitaldischarge records for all non-federal, acute care hospitalswithin their borders.11 The information collected variesfrom state to state. Many states use the standard uniformbilling form (UB-92) as the basis for their hospital dischargedatabase. Some states use only a subset of variables from theUB-92 for their databases, while a few collect additionalvariables.

The UB-92, developed by the National Uniform BillingCommittee, includes the following data elements:

➤ patient’s age,➤ sex,➤ zip code,➤ admission date,➤ length of stay,➤ total charges,➤ principal diagnosis,➤ up to eight additional diagnoses.

For diagnoses resulting from injuries, external cause ofinjury (E-code) is also coded. E-codes, which are listed inthe International Classification of Diseases-9 Clinical Modification(ICD-9 CM) describe several aspects of an injury: intention-ality; mechanism; and, for unintentional causes of injury,location of occurrence.12

Introduction – 5

Although HDD have been collected in some states formany years, their use for public health surveillance has beenlimited. HDD indicators for injury are based on a case defini-tion that is being used for only the second time by multiplestates. Each state reports comparable information aboutinjury hospitalizations. Thus, the strengths and limitationsof the case definition and data are not yet well-characterized.Several caveats should be noted:

➤ The data are generated from forms used to billfor hospital services. Quality assurance practicesfor these data vary from state to state.

➤ Not all states mandate that hospitals report HDD.Even in those that do, participation rates andrequirements vary regarding the data elements tobe reported, including the reporting of E-codes. Itis difficult to determine the hospital participationrate in HDD collection because the total number ofhospitals changes often, as they merge or close andnew ones open.

➤ Among the states in this report, there is widevariation in coding percentages for E-coding forinjury-related diagnoses; completeness rangesfrom 53% to 100%. Incomplete external causecoding not only leads to low rates of injury, butit can also introduce bias. Currently, there are fewstudies to indicate whether the underestimatespresented here are biased.

➤ The percentage of E-coding for injury hospitaliza-tions is increasing in many states. When comparinghospitalization rates within one state over severalyears or between states in the same year, it is criticalto take into account the percentage of E-coding for

each year. Many states will have a factitious increasein injury hospitalization rates as their percentage ofE-coding increases.

➤ A person might be counted more than once for oneevent, as with intra-hospital transfers between services.While many states have developed probability algo-rithms to eliminate such duplications, these algorithmsdiffer, limiting comparability. Therefore, states contrib-uting to this report were asked to leave suspectedduplicates in the data set for this analysis. The ratesdisplayed in this report reflect numbers of hospitalizations,rather than numbers of people hospitalized. The exceptionsto this are California and Michigan, where HDD aregenerated in such a way that duplicate admissionswere not available for inclusion in the analysis.

➤ Unlike the system for death certificates, no standardsystem exists to forward hospitalization data onnonresidents to their states of residence. This is aparticular problem when trauma centers or otherreferral centers are just across state borders; injuredresidents may be hospitalized in the neighboring statewithout any record of their hospitalizations enteringthe HDD of their state of residence.

To remind readers of the limitations of HDD and to assistin the interpretation of HDD-based indicators, the firstfigure displaying rates calculated from HDD in each sectionof this report includes a section entitled “Factors AffectingRepresentativeness of State Hospital Discharge Data Sets forInjury Surveillance.” This section of the first figure displaysthe percentage of hospitalizations with E-codes, if the stateincludes readmissions, if they are impacted by cross-border

Introduction – 6

hospitalizations, and for the completeness of hospital partici-pation. As the use of HDD for injury surveillance has devel-oped only recently, this table will be included with anyfigure displaying rates calculated from HDD.

Future EffortsThe State Injury Indicators Report, Second Edition — 1999 Datarepresents great progress in standardizing state-based injurysurveillance reporting. Participation has grown from 12 to26 states. The report includes 12 of the 14 injuries and injuryrisk factors recommended for surveillance in ConsensusRecommendations. Future reports should include all 14, oncecase definitions have been developed for surveillance oftraumatic spinal cord injuries and falls. This report displaysdeath and hospitalization rates by sex and age, which pro-vide more detail for identifying populations at risk. Statesparticipating in this report look forward to refining currentindicators and defining new ones, as we learn from theexperience of producing each State Injury Indicators Report.

The data contained in this report are readily available inmost states through national surveillance systems such asFARS, or through analysis of state data sets, such as deathcertificates or HDD. We expect the proportion of statesrepresented in subsequent reports to increase as state injurysurveillance systems become more comprehensive.

References1. Institute of Medicine (US). Reducing the Burden of

Injury, Advancing Prevention and Treatment.Washington (DC): National Academy Press; 1999.

2. State and Territorial Injury Prevention Directors’Association (STIPDA). Consensus recommendationsfor injury surveillance in state health departments.Marietta (GA): STIPDA; 1999.

3. Meriwether RA. Blueprint for a national publichealth surveillance system for the 21st century.J Public Health Manag Pract 1996;216–23.

4. Council of State and Territorial Epidemiologists.Injury Control and Prevention Position Statement.[accessed 2003 Jul 23]. Available from URL:www.cste.org/PS/Default.htm.

5. State and Territorial Injury Prevention Directors’Association (STIPDA) resolutions, October 1999.[accessed 2003 Jul 23]. Available from URL:www.stipda.org/resol/99nphss.htm.

6. National Highway Traffic Safety Administration.Fatality Analysis System. [accessed 2003 July 23].Available from URL: www.nhtsa.dot.gov/people/ncsa/fars.html.

7. CDC. Youth risk behaviors, July 2001. [accessed 2003Jul 23]. Available from URL: www.cdc.gov/nccdphp/dash/yrbs/index.htm.

8. CDC. Behavioral Risk Factor Surveillance System,July 2001. [accessed 2003 Jul 23]. Available fromURL: www.cdc.gov/brfss.

Introduction – 7

9. CDC. Mortality Data from the National Vital StatisticsSystem. [accessed 2003 Jul 23]. Available from URL:www.cdc.gov/nchs/about/major/dvs/mortdata.htm.

10. Anderson RN, Minino AM, Hoyert DL, RosenbergHM. Comparability of cause of death betweenICD-9 and ICD-10: preliminary estimates. NationalVital Statistics Reports; 2001:49(2).

11. American Public Health Association. How states arecollecting and using cause of injury data. A report ofthe data committee, Injury Control and EmergencyHealth Services Section; 1998 Sep.

12. International Classification of Diseases 9th RevisionClinical Modification. [accessed 2003 Jul 23]. Availablefrom URL: www.cdc.gov/nchs/about/otheract/icd9/abticd9.htm.

Introduction – 8

Two other factors should be considered when interpret-ing HDD-based indicators. First, rates represent the numberof hospitalizations per 100,000 population, not patients per100,000 population. This is because individuals could havemultiple hospital stays during the year, and there is no wayto separately identify them. Second, since a small overlapwith fatal injury indicators likely exists, this report displayshospitalization rates that include deaths occurring during ahospitalization for injury.

References1. CDC. Surveys and data collection systems: national

health care survey; 2001 Jun [accessed 2003 Jul 24].Available from URL: www.cdc.gov/nchs/nhcs.htm.

2. National Hospital Discharge Survey 2000[unpublished] Fingerhut L. National Center for HealthStatistics. [personal communication] 2003.

1. All-Injury Indicators

All-Injury Indicators – 9

Surveillance of injuries resulting in hospitalization providesan important perspective on the public health burden ofinjury morbidity. National surveillance for hospitalizationsis based on analysis of the National Hospital DischargeSurvey, a national probability sample of hospital inpatientrecords.1 In 2000, there were 1.8 million injury-relateddischarges from short-stay hospitals, accounting for anestimated 6% of all hospitalizations.2

Injury hospitalization rates for males and femalesare similar for all ages combined, but differ considerablywithin certain age groups. For ages 15 to 24 years, theinjury hospitalization rate for males is 3.3 times that forfemales; for the elderly ages 75 years or older, the rate forfemales is 1.8 times that for males.2

The rates for all-injury hospitalizations displayed hererepresent hospitalizations when the principal diagnosis wasan injury as defined by the inclusion criteria in the appendix.As the inclusion criteria are based on the nature of injurycodes only, the percentage of external cause coding in astate’s hospital discharge data (HDD) does not affect thisrate. State rates for HDD-based indicators are affected by thepercentage of hospitalizations with external cause coding,the inclusion of readmissions, the impact of cross-borderhospitalizations, and the completeness of hospital participa-tion. Figure 1a contains the section entitled, “Factors Affect-ing Representativeness of State Hospital Discharge Data Setsfor Injury Surveillance” to be used when interpreting theaccompanying rates.

All-Injury Indicators Figures

1a. Hospitalizations for All Injuries (Overall), 1999

1b. Hospitalizations for All Injuries by Sex, 1999

1c. Hospitalizations for All Injuries by Age, 1999

All Injury Indicators – 11

Age Adjusted Rate per 100,000

0 500

Arizona

California

Colorado

Delaware

Florida

GeorgiaHawaii

Kansas

Kentucky

Louisiana

Massachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

900200 400 700100 300 600 800

Number Rate

28,801

165,290

23,080

3,953

95,370

36,305

6,115

16,144

14,879

—

35,012

54,624

25,570

6,645

9,477

40,274

—

—

21,592

30,654

21,382

86,727

10,252

3,156

25,499

31,572

600.7

512.5

583.1

519.8

541.8

499.0

509.6

564.4

380.1

—

514.3

553.5

519.7

360.5

564.9

507.8

—

—

611.4

894.2

552.7

430.3

540.5

507.9

444.7

572.3

FIGURE 1 .a

All Injury Indicator: Hospitalizations for , 1999All Injuries (Overall)

‡

‡

‡

‡

‡

‡

§

* Incompleteness can lead to bias.

†Subjective assessment by health department staff that a substantial proportion of state residentsinjured in-state who require hospitalization are hospitalized in a neighboring state.

‡No data available.

§Rate=[(male rate*pop) + (female rate*pop)] / (male+female pop).

ll Rates are suppressed if fewer than 20 cases were reported.

¶ Case counts are suppressed if fewer than 5 cases were reported.

Factors Affecting Representativeness of State HospitalDischarge Data Sets for Injury Surveillance

Inclusionof Readmissionand Transfers?

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

‡

Yes

Yes

Yes

Yes

Yes

‡

‡

Yes

Yes

‡

Yes

Yes

Yes

Yes

Yes

No

Percentage of HDDInjury Records with

External Cause Coding

IncompleteHospital

ParticipationState

AZ

CA

CO

DEFL

GA

HI

KS

KY

LAMA

MI

MN

NE

NM

NC

ND

OH

OK

OR

SC

TX

UT

VT

WA

WI

84.0%

100.0%

98.8%

76.0%

74.0%

91.8%

52.9%

58.0%

68.0%

‡95.3%82.3%78.4%

100.0%

48.3%

89.1%

‡

‡

65.9%

67.5%

94.1%

62.7%

89.2%

85.0%

98.9%

97.3%

Cross-BorderHospitalization

No

No

No

No

No

Unknown

No

Unknown

‡

No

No

No

Unknown

No

‡

‡

No

No

No

No

No

Yes

Yes

Yes

Yes

Yes

No

No

No

No

No

No

No

No

‡

No

No

No

No

No

‡

‡

No

No

No

No

No

No

No

Yes

Yes

Yes

* †




Males FemalesAge Adjusted Rate per 100,000

0

Arizona

California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky

Louisiana

Massachusetts

MichiganMinnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

1,000200 400 600 800

FIGURE 1 .b

All Injury Indicator: Hospitalizations for , 1999All Injuries by Sex


0

Arizona

California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky

Louisiana

Massachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

1,000200 400 600 800

Number of CasesMales Females

15,146

87,491

11,813

2,001

44,880

18,241

3,433

7,184

6,893

—

15,509

27,861

12,541

2,856

4,930

19,280

—

—

9,822

15,224

10,811

41,034

5,289

1,546

12,341

15,198

13,655

77,799

11,264

1,952

50,472

18,045

2,682

8,960

7,985

—

19,498

26,762

13,028

3,789

4,546

20,976

—

—

11,645

15,430

10,570

45,218

4,961

1,610

13,155

16,374

666.3

558.7

611.2

573.4

592.2

534.7

587.4

573.9

388.6

‡

536.9

579.3

560.7

356.1

613.0

533.6

‡

‡

631.2

957.0

605.7

415.0

555.2

556.2

462.5

614.2

536.4

466.2

554.6

469.2

494.2

465.1

432.2

555.2

372.0

‡

493.1

528.9

479.9

364.7

515.5

483.0

‡

‡

592.5

832.3

503.2

445.2

525.9

461.5

427.1

531.8

‡

‡

‡

‡

‡

‡

<1 1-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+State

Rate††

N RateN RateN RateN RateN RateN RateN Rate RateN RateN RateN

AZCACODEFL

GAHIKSKYLAMAMIMNNENMNCNDOHOKORSCTXUTVTWAWI

N

FIGURE 1C.

All Injury Indicator: Hospitalizations for All Injuries by Age**, 1999

2941,326

12736

561275

2689

116—

186335147

37110271

——

208240161521

9719

197210

383264211350283231155238220

—233252230161409250

——

434542318156212

—248319

9256,154

41799

1,983738249335642

—559

1,283519109207852

——

643714574

2,052330

45514720

299308178248263160391229311

—175238201119198201

——

348407283157194160161271

1,71521,209

1,165252

4,2071,849

418726

1,257—

1,4692,9021,376

308620

1,734——

1,1831,2711,1484,723

698152

1,2831,487

232419192247214162258187235

—182202191125224158

——

242275214151184177149194

3,92419,101

3,176538

9,0894,439

8751,7791,537

—3,2726,6073,219

7101,3304,700

——

2,4722,6912,613

11,1911,761

3782,6963,718

587408528542492400525447266

—370494471282505423

490587469368434452336490

——

3,57921,073

2,853420

9,0844,524

7901,3231,423

—3,0876,0892,528

5081,0914,737

——

1,9822,7012,6899,2651,075

2912,5472,989

569412432371460375538389262

—307424402246517389

——

475636480334326382301434

3,81116,274

3,308479

11,1995,131

7151,7421,755

—3,8147,6393,238

6261,2415,065

——

2,4243,8192,9389,9241,164

3553,1523,740

518291458368482384361408274

—374477398240446400

——

477725467304373352323431

2,72111,382

2,565374

8,5633,834

5891,3051,311

—3,0305,7782,449

515906

3,913——

1,8643,7802,2427,893

919300

2,7003,003

463277436385426375356381242

—370438390239395371

——

425774427309400331334431

1,88411,522

1,628270

6,5372,897

4131,0581,096

—2,4104,1371,788

466635

3,057——

1,5053,1341,7416,248

677249

1,8572,165

468472491427437460398482294

—486497454331424433

——

4711,038

499386497446387481

740737832707699808567905564

—841786788640768831

——

9011,773

783825889816672896

4,29923,699

3,157633

18,2565,143

8473,1012,440

—7,0368,1394,0941,2981,3736,627

——

3,6525,0653,042

13,8591,459

5464,4035,443

1,9391,8342,2851,8891,7252,0051,4972,4371,452

—2,3491,8741,9461,6162,0472,054

——

2,3833,1591,9172,0562,2742,0721,8822,198

3,12719,323

2,821467

15,7794,089

6943,1011,792

—6,4266,6093,9221,3411,1094,930

——

3,5093,3672,136

11,9031,188

4923,8404,947

4,7454,5576,0164,6054,9104,7924,0136,0053,120

—5,3334,5994,6443,9085,1304,774

——

6,1345,9844,5715,0975,7195,0534,7005,251

2,52214,227

1,863385

10,1123,386

4991,5851,510

—3,7185,0772,290

727854

4,388——

2,1473,8722,0989,148

879329

2,3073,127

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

ll



Case counts are suppressed if fewer than 5 cases were reported.¶

** Age in years.

Rate per 100,000 population.††

Traumatic Brain Injury Indicators (TBI) – 17

2. Traumatic Brain Injury Indicators (TBI)

Of all types of injury, TBI is among the most likely to causedeath or permanent disability.1 Each year in the UnitedStates, an estimated one million people are treated for TBIand released from hospital emergency departments;2

230,000 people are hospitalized for TBI and survive,3 and50,000 people die.4 An estimated 5.3 million Americans livewith a TBI-related disability.5

The risk of TBI is highest among adolescents, youngadults, and people ages 75 years and older. Motor vehiclecrashes, violence, and falls are the leading causes of TBI.Among people ages 65 years and older, falls are the leadingcause of TBI. Motor vehicle crashes are the leading causeamong persons ages 5 to 64 years. For persons of all ages,the risk of TBI among males is twice that among females.The outcome of these injuries varies greatly depending onthe cause: 91% of firearm-related TBIs result in death, and11% of fall-related TBIs are fatal.6

Nearly two-thirds of firearm-related TBIs are classifiedas suicidal intent.5 In 1990, firearms surpassed motor vehiclesas the largest single cause of death associated with TBI inthe United States.7 These data reflect the success of effortsto prevent TBI due to motor vehicle crashes and the failureto prevent such injuries due to firearms.1 Continued surveil-lance of TBI is needed to monitor trends, identify high riskgroups, prioritize prevention efforts, and to assess preven-tion programs.

Figures 2a, 2b, and 2c present TBI-related hospitaliza-tion rates in the 22 states in 1999; the range from lowest tohighest rates was almost five-fold. Figures 2d, 2e, and 2fpresent the fatal TBI data in 21 states for the same year.

Figure 2d illustrates a more than three-fold differencebetween the lowest and highest rates. The ratio of hospi-talized cases to death certificate-identified cases rangesfrom 1.4:1 to 7.6:1. As noted previously, cases of injuryresulting in hospitalization and subsequent death maybe included in both HDD and death certificate data. Maleshave higher rates of death and hospitalization than females.The highest rates of TBI death and hospitalization are seenamong persons ages 65 years and older. (Table 2c and 2f.)

Limitation: The case inclusion criteria for TBI hospi-talization in this report requires that an injury be listed inthe principal diagnostic field and a TBI diagnosis in anydiagnostic field. In contrast, the hospital-based CDC TBIsurveillance definition requires that a TBI be listed in anyof the diagnostic fields. Hospitalization rates based onCDC’s TBI surveillance definition will be higher than theTBI hospitalizations indicators shown here.8,9 The TBI fatalindicator uses the same definition as the death file-basedCDC TBI surveillance definition, so the death rates shouldbe similar. Four states did not have access to state multiplecause-of-death files and so were not able to calculate thefatal TBI indicator.

References1. CDC. Epidemiology of traumatic brain injury in the

United States [Online]. 2000 May [accessed 2003Jul 24]. Available from URL: www.cdc.gov/ncipc/factsheets/tbi.htm.

2. Guerrero J, Thurman DJ, Sniezek JE. Emergencydepartment visits associated with traumatic braininjury: United States, 1995–1996. Brain Inj 2000;14(2):181–6.

3. Thurman DJ, Guerrero J. Trends in hospitalizationassociated with traumatic brain injury. JAMA 1999;282(10):954–7.

4. CDC. National Center for Health Statistics. MultipleCause of Death Public Use Data, 1996 [unpublished].2003.

5. Thurman DJ, Alverson CA, Dunn KA, Guerrero J,Sniezek JE. Traumatic brain injury in the UnitedStates: a public health perspective. J Head TraumaRehabil 1999;14(6):602–15.

6. CDC. National Center for Injury Prevention andControl. State health department traumatic braininjury data; Alaska, Arizona, California (reportingSacramento County only), Colorado, Louisiana,Maryland, Missouri, New York, Oklahoma, RhodeIsland, South Carolina, and Utah, 1997 [unpublished].2003.

7. Sosin DM, Sniezek JE, Waxweiler RJ. Trends in deathassociated with brain injury, 1979–1992. JAMA 1995;273:1778–80.


8. Thurman DJ, Sniezek JE, Johnson D, Greenspan A,Smith SM. Guidelines for surveillance of centralnervous system injury. Atlanta (GA): Centers forDisease Control and Prevention; 1995.

9. Langlois JA, Kegler SR, Butler JA, Gotsch KE,Johnson RL, Reichard AA, et al. Traumatic braininjury-related hospital discharges, results from a14-state surveillance system, 1997. Atlanta (GA):CDC. MMWR Surveillance Summaries 2003;52(SS-04):1–18.

Traumatic Brain Injury Indicators Figures

2a. TBI Hospitalizations (Overall), 1999

2b. TBI Hospitalizations by Sex, 1999

2c. TBI Hospitalizations by Age, 1999

2d. TBI Fatalities (Overall), 1999

2e. TBI Fatalities by Sex, 1999

2f. TBI Fatalities by Age, 1999



0 80

Arizona

California

Colorado

Delaware

Florida

GeorgiaHawaii

Kansas

Kentucky

Louisiana

Massachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

14040 6020 100 120

Number Rate

FIGURE 2 .a

TBI Indicator: TBI Hospitalizations , 1999(Overall)

94.5

72.2

82.9

124.6

73.8

59.1

84.6

72.3

44.4

—

56.8

75.8

73.4

30.4

61.8

57.1

—

—

74.3

72.3

—

25.7

75.6

57.2

49.0

67.4

4,498

23,499

3,392

931

11,956

4,409

999

1,978

1,711

—

3,674

7,344

3,518

538

1,050

4,487

—

—

2,540

2,421

—

5,165

1,620

339

2,787

3,593

‡

‡

‡

‡

‡

‡

‡

‡









Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

‡

Yes

Yes

Yes

Yes

Yes

‡

‡

Yes

Yes

‡

Yes

Yes

Yes

Yes

Yes

No



IncompleteHospital

ParticipationState

AZ

CA

CO

DE

FL

GA

HI

KS

KY

LA

MA

MI

MN

NE

NM

NC

ND

OH

OK

OR

SC

TX

UT

VT

WA

WI

84.0%

100.0%

98.8%

76.0%

74.0%

91.8%

52.9%

58.0%

68.0%

‡

95.3%

82.3%

78.4%

100.0%

48.3%

89.1%

‡

‡

65.9%

67.5%

94.1%

62.7%

89.2%

85.0%

98.9%

97.3%


No

No

No

No

No

Unknown

No

Unknown

‡

No

No

No

Unknown

No

‡

‡

No

No

No

No

No

Yes

Yes

Yes

Yes

Yes

No

No

No

No

No

No

No

No

‡

No

No

No

No

No

‡

‡

No

No

No

No

No

No

No

Yes

Yes

Yes

* †


0 100

Arizona

California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky

Louisiana

Massachusetts

MichiganMinnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

17550 15025 75 125

FIGURE 2 .b

TBI Indicator: TBI Hospitalizations by Sex, 1999


0

ArizonaCaliforniaColoradoDelaware

FloridaGeorgiaHawaiiKansas

KentuckyLouisiana

MassachusettsMichigan

MinnesotaNebraska

New MexicoNorth Carolina

North DakotaOhio

OklahomaOregon

South CarolinaTexasUtah

VermontWashington

Wisconsin

10025 50 75


2,988

15,959

2,213

585

7,543

2,826

671

1,239

1,078

—

2,265

4,771

2,275

311

710

2,816

—

—

1,546

1,583

—

3,226

1,027

224

1,806

2,310

1,510

7,540

1,179

346

4,409

1,579

328

739

632

—

1,409

2,573

1,242

227

340

1,663

—

—

975

838

—

1,915

592

115

981

1,283

128.4

99.0

108.3

164.0

100.5

79.2

115.6

96.2

59.4

‡

77.2

99.2

99.6

38.5

84.7

75.6

‡

‡

96.8

98.0

‡

32.6

95.5

79.9

65.4

91.5

61.2

45.3

57.1

87.4

48.6

40.1

53.8

49.1

30.3

‡

37.8

53.5

48.0

22.7

38.2

39.4

‡

‡

52.9

47.0

‡

18.9

55.8

35.4

32.7

44.1

‡

‡

‡

‡

‡

‡

‡‡




Rate††

<1 1-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+State


AZCACODEFL


N

FIGURE 2C.

TBI Indicator: TBI Hospitalizations by Age**, 1999

143622

6527

261127

154037—

104148

696

38119

——7542—

16153

98388

186.5123.6108.0262.2131.5106.7

—107.0

70.3—

130.2111.6107.9

—141.2109.8

——

156.394.9

—48.2

115.6—

104.3133.6

2121,187

10828

328156

536780—97

206116

1032

137——

107101

—295

939

105102

68.559.546.170.243.533.883.345.738.7

—30.338.145.0

—30.632.4

——

58.057.6

—22.654.8

—32.938.4

4334,379

29860

902396

98163139

—231592322

48124355

——

275225

—595208

28258298

58.686.649.058.745.934.760.442.026.0

—28.641.144.719.444.732.3

——

56.348.7

—19.054.732.629.938.9

8993,045

733187

1,857880146419328

—539

1,416637114222880

——

508443

—1,192

43460

546740

134.465.0

121.9188.3100.5

79.387.7

105.256.9

—61.0

105.993.245.384.379.3

——

100.896.7

—39.2

106.971.768.097.6

6423,054

476123

1,380586121194228

—395925422

55147623

——

273296

—716164

26297390

102.159.772.1

108.669.948.682.457.042.0

—39.364.567.026.769.751.2

——

65.469.7

—25.849.734.135.156.7

6502,337

523147

1,507667101243215

—443

1,131498

49118563

——

268328

—637174

40327435

88.341.872.4

112.964.849.951.056.933.6

—43.570.661.218.842.444.4

——

52.762.2

—19.555.839.633.550.1

4242,418

38099

1,096433

98155138

—308731338

3894

347——

196249

—449131

32266298

72.158.964.5

102.054.642.359.245.225.5

—37.655.453.917.641.032.9

——

44.651.0

—17.656.935.332.942.8

2601,463

19855

808273

59105116

—244466200

2970

278——

145145

—253

8736

183204

64.659.959.787.054.043.356.847.831.1

—49.256.050.720.646.739.3

——

45.448.0

—15.663.864.438.145.3

2811,573

18465

951277

67150137

—357542244

3967

358——

181182

—290

8334

193304

82.481.582.2

119.365.766.176.185.651.2

—80.884.084.034.360.267.8

——

76.083.3

—26.283.984.356.287.1

3612,121

25792

1,640368144247189

—551720399

8385

496——

297237

—319116

35313430

162.8164.1186.0274.5155.0143.4245.5194.1112.5

—184.0165.8189.6103.3126.7153.8

——

193.8147.8

—47.3

180.8132.8133.8173.7

1931,300

17048

1,226246

97195104

—405463273

6753

331——

215173

—258

7630

216304

292.8306.5362.6473.3381.5288.3560.9377.6181.1

—336.1322.2323.3195.3245.1320.5

——

375.8307.5

—110.5365.8307.0264.4321.2

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

‡

ll

ll

ll

ll

ll




** Age in years.


FIGURE 2 .d

TBI Indicator: TBI Fatalities , 1999(Overall)


0 20

Arizona

California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky

Louisiana

Massachusetts

MichiganMinnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

3510 305 15 25

Number Rate

—

4,139

938

—

2,933

1,616

130

569

739

1,163

562

1,585

795

404

—

1,729

71

—

865

—

1,045

3,620

429

114

1,151

1,030

—

13.4

24.5

—

18.3

21.8

11.1

21.3

19.7

31.2

9.0

16.8

17.1

23.7

—

22.5

11.0

—

26.1

—

27.5

18.0

22.2

19.5

20.8

19.6

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0

Arizona

California

Colorado

Delaware

Florida

GeorgiaHawaii

Kansas

Kentucky

Louisiana

Massachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

6020 40

FIGURE 2 .e

TBI Indicator: TBI Fatalities by Sex, 1999


0 10

Arizona

California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky

LouisianaMassachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

166 144


10 30 50

‡

20.8

35.9

‡

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32.8

17.4

32.4

30.8

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25.9

34.5

‡

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15.6

‡

39.0

‡

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32.4

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—

3,144

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—

2,176

1,162

99

410

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869

383

1,155

564

275

—

1,255

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—

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—

733

2,602

304

86

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—

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268

—

757

454

31

159

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294

179

429

231

129

—

474

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—

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—

312

1,018

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28

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304

2 8 12

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<1 1-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+State


AZCACODEFL


N

FIGURE 2 .f

TBI Indicator: TBI Fatalities by Age**, 1999

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Rate††




** Age in years.


Drowning Indicators – 27

3. Drowning Indicators

Drowning is the second leading cause of injury death amongU.S. children ages 1 to 14 years. It is also in the top 10 causesof injury death for all ages. In 2000, 4,073 drowningsoccurred in the United States, the majority of which wereunintentional (85.5%); 8.8% were intentional; 5.7% wereundetermined.1 Men are at higher risk than women (4:1),and blacks are at a higher risk than whites (1.4:1).2

Nationally, drowning rates are highest for two agegroups: children under five years of age, and persons15 to 19 years of age. In one California study, for every childwho drowned another 4 were hospitalized, and 16 receivedemergency department care for near drowning.3 Neardrowning can be costly and can result in lifelong disability.

Among adolescents and adults, risk factors for drown-ing include drinking alcohol, swimming alone, and notwearing a personal flotation device while engaged in watersports or recreation. For children under five, unexpectedaccess to water or brief lapses in adult supervision areimplicated in most drowning incidents.4

Infants commonly drown in bathtubs. As these youngchildren become more mobile, small water containers suchas buckets and toilets also pose drowning risks. Most tod-dlers and preschoolers drown in residential backyard pools.The percentage of drowning in open water such as lakes,rivers, and the ocean increases with age.5

Despite technological advancements in medical care,hospital treatment often does little to change the outcomeof a submersion injury. Prevention is key, since the window

of opportunity to prevent brain damage or death is so small.Strategies to prevent drownings among infants and childrenfocus on environmental changes:

➤ proper fencing of home pools,

➤ drainage of buckets,

➤ close supervision of children in bathtubs,

➤ public education and training in CPR.

Figures 3a, 3b, and 3c, which present the near drowninghospitalization data for 22 states in 1999, illustrate an eight-and-a-half fold difference between the lowest and highesthospitalization rates. In four states, the number of drowninghospitalizations was too low to calculate a stable rate. Figures3d, 3e, and 3f present the drowning death data for 25 statesin 1999. This figure shows over a four-fold differencebetween the lowest and highest rates. In three states, thenumber of drowning deaths in 1999 was too low to calculatea stable rate. Exposure to aquatic environments also variesby state and should be considered along with these ratedifferences.

In states where data are available by sex, males havehigher rates of death and hospitalization than females. Thehighest death rates by age group are among 1 to 4 year olds,but events are infrequent and only states with large popula-tions (California, Florida, and Texas) were able to calculatestable rates for this age group. Nine states showed relativelyhigh death rates for 15 to 24 year olds. The highest hospital-ization rates were among 1 to 4 year olds, followed by 5 to14 year olds, consistent with the 1990 study cited earlier. 3

The ratio of death versus hospitalizations for near-drowning ranges from 1:0.4 to 1:1.7. Similar ratios werereported in the previous State Injury Indicators Report using1997 and 1998 data. Hospitalization for submersion injuriesappears to be a more common outcome among children14 years old and under than it is for adults.

References1. CDC. Web-based Injury Statistics Query and Report-

ing System (WISQARS) [Online]. 2002. NationalCenter for Injury Prevention and Control, Centersfor Disease Control and Prevention (producer).[accessed 2003 Jul 28]. Available from URL:www.cdc.gov/ncipc/wisqars.

2. Division of Unintentional Injury Preventiondowning fact sheet [accessed 2003 Jul 28]. Availablefrom: URL: www.cdc.gov/ncipc/factsheets/drown.htm.

3. Wintemute GJ. Childhood drowning and near-drowning in the U.S. Am J Dis Child 1990;144.

4. Fletemeyer JR, Freas SJ, editors. Drowning: newperspectives on intervention and prevention.Boca Raton: CRC Press; 1998.

5. Brenner RA, Trumble AC, Smith GS, et al. Wherechildren drown, U.S., 1995. Pediatrics 2001;10(1):85–9.



Drowning Indicators Figures

3a. Near Drowning Hospitalizations (Overall), 1999

3b. Near Drowning Hospitalizations by Sex, 1999

3c. Near Drowning Hospitalizations by Age, 1999

3d. Drowning Fatalities (Overall), 1999

3e. Drowning Fatalities by Sex, 1999

3f. Drowning Fatalities by Age, 1999


0 4

Arizona

California

Colorado

Delaware

Florida

GeorgiaHawaii

Kansas

Kentucky

Louisiana

Massachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

62 31 5

Number Rate

FIGURE 3 .a

Drowning Indicator: Near Drowning Hospitalizations , 1999(Overall)

11660537—

33278602616—3594637

—66——393940

12526—4154

2.21.80.9—

2.31.05.21.0——

0.60.91.3——

0.8——

1.21.21.00.60.9—

0.71.1

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IncompleteHospital

ParticipationState

AZ

CA

CO

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GA

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KS

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LAMA

MI

MN

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WI

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* †


0

Arizona

California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky

Louisiana

Massachusetts

MichiganMinnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

63 51 2 4

FIGURE 3 .b

Drowning Indicator: Near Drowning Hospitalizations by Sex, 1999


0 3

Arizona

California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky

Louisiana

Massachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

541 2


73

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20

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<1 1-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+State


AZCACODEFL


N

FIGURE 3C.

Drowning Indicator: Near Drowning Hospitalizations by Age**, 1999

—11.1

————————————————————————

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** Age in years.


FIGURE 3 .d

Drowning Indicator: Drowning Fatalities , 1999(Overall)


0

Arizona

California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky

Louisiana

Massachusetts

MichiganMinnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

3.01.5 2.50.5 1.0 2.0

Number Rate

—

416

55

10

360

147

36

31

56

120

43

132

72

25

32

123

13

112

49

66

74

314

27

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74

—

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—

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1.3

1.5

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0

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California

Colorado

Delaware

Florida

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Kansas

Kentucky

Louisiana

Massachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

62 4

FIGURE 3 .e

Drowning Indicator: Drowning Fatalities by Sex, 1999


0 0.6

Arizona

California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky

Louisiana

Massachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

1.00.4 0.80.2


1 3 5

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<1 1-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+State


AZCACODEFL


N

FIGURE 3 .f

Drowning Indicator: Drowning Fatalities by Age**, 1999

—8

——6

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** Age in years.


Fire-Related Indicators – 37

4. Fire-Related Indicators

The United States has the fourth highest overall fire deathrate of all industrialized countries.1 Residential fires causeabout 85% of all civilian fire-related deaths.2 In 2000,379,500 residential fires in the United States claimed thelives of 3,445 people and injured another 17,400.2 Cookingis the leading cause of home fires,2 while smoking-relatedfires are the leading cause of home fire deaths.3

Residential fires disproportionately affect youngchildren, older adults, African-Americans, and NativeAmericans. The southern region of the United States hasthe highest fire death rate. Contributing factors may includerural poverty, a lower prevalence of functional smoke alarms,and a greater use of portable heating equipment.4

Working smoke alarms reduce the chance of dying ina house fire by 40% to 50%.5 One large-scale smoke alarmgiveaway program reduced the incidence of fire-relatedinjury rates by 80% in its target area.4 However, about25% of U.S. households lack working smoke alarms.6

Figures 4a, 4b, and 4c represent the 1999 combinedresidential and non-residential fire-related hospitalizationdata for 22 states. There were too few hospitalizations inthree states to calculate stable rates and four states did notprovide hospitalization data. Reported fire-related hospi-talization rates ranged from 2.2 per 100,000 population to7.4 per 100,000 population.

Figures 4d, 4e, and 4f represent the 1999 combinedresidential and non-residential fire-related fatality data for25 states. For seven states, there were too few deaths to

calculate stable rates and one state did not provide data onfatalities. The reported fire-related fatality rates ranged from0.7 per 100,000 population to 2.4 per 100,000 population.

Fire-related hospitalization rates were 1.3 to 6.6 timeshigher than the death rate among the states reporting bothrates. Males had higher rates than females for both deathsand hospitalizations. Age-specific rates of fire-relatedfatalities and hospitalizations could not be calculated formany of the age categories because of small numbers. Whenrates could be calculated, they tended to be highest amongadults 75 years of age and older and among children agesone to four years.

Figure 4g represents the percentage of homes in whichall the smoke alarms had been tested within the past month,as is currently recommended,5 for 25 states. The proportionof these homes ranged from 21.7% (Minnesota) to 42.4%(Oklahoma). In 1999, 33.5% of U.S. homeowners reportedthat they tested all their smoke alarms within the pastmonth.7 Only nine of the 25 states had a proportion higherthan the national average.

Figure 4h presents the percentage of homes withoutsmoke alarms in 25 states. The proportion of homes lackingany smoke alarms ranged from 1.3% (Oregon) to 13.0%(Hawaii). Nationally, 3.9% of U.S. homes had no smokealarms in 1999.7 Of the 25 states, 13 had a higher percentageof homes without a smoke alarm than the national average.

References1. World Fire Statistics Center. U.N. fire statistics study.

Prepared for the U.N. Committee on Human Settle-ments. 2001 Sep.

2. Ahrens M. The U.S. fire problem overview report:leading causes and other patterns and trends.Quincy (MA): National Fire Protection Association;2001 June.

3. Karter MJ. Fire loss in the United States during 2000.Quincy (MA): National Fire Protection Association;2001.

4. Mallonee S, Istre G, Rosenberg M, Reddish-DouglasM, Jordan F, Silverstein P, et al. Surveillance andprevention of residential-fire injuries. N Eng J Med1996;335:27–31.

5. Ahrens M. U.S. experience with smoke alarms andother fire alarms. Quincy (MA): National FireProtection Association; 2001 Sep.

6. Smith CL. Smoke detector operability survey–reporton findings. Bethesda (MD): U.S. Consumer ProductSafety Commission; 1993 Nov.

7. Centers for Disease Control and Prevention, Divisionof Adult and Community Health, National Center forChronic Disease Prevention and Health Promotion,Behavioral risk factor surveillance system onlineprevalence data [online] 1999. [accessed 2003 Nov 28].Available from URL: apps.nccd.cdc.gov/brfss.



Fire-Related Indicators Figures

4a. Fire-Related Hospitalizations (Overall), 1999

4b. Fire-Related Hospitalizations by Sex, 1999

4c. Fire-Related Hospitalizations by Age, 1999

4d. Fire-Related Fatalities (Overall), 1999

4e. Fire-Related Fatalities by Sex, 1999

4f. Fire-Related Fatalities by Age, 1999

4g. Percentage of Homes with Smoke Alarms Tested in the Last Month, 1999 Behavioral Risk Factor Surveillance System

4h. Percentage of Homes without Smoke Alarms, 1999 Behavioral Risk Factor Surveillance System


0 4

Arizona

California

Colorado

Delaware

Florida

GeorgiaHawaii

Kansas

Kentucky

Louisiana

Massachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

82 31 5 7

Number Rate

FIGURE 4 .a

Fire-Related Indicator: Fire-Related Hospitalizations (Overall), 1999

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FIGURE 4 .b

Fire-Related Indicator: Fire-Related Hospitalizations by Sex, 1999


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FIGURE 4C.

Fire-Related Indicator: Fire-Related Hospitalizations by Age**, 1999

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FIGURE 4 .d

Fire-Related Indicator: Fire-Related Fatalities , 1999(Overall)

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California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky

Louisiana

Massachusetts

MichiganMinnesota

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North Dakota

Ohio

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Washington

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Michigan

Minnesota

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North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

41 3

FIGURE 4 .e

Fire-Related Indicator: Fire-Related Fatalities by Sex, 1999


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Florida

Georgia

Hawaii

Kansas

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Michigan

Minnesota

Nebraska

New Mexico

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Ohio

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Texas

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FIGURE 4 .f

Fire-Related Indicator: Fire-Related Fatalities by Age**, 1999

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Rate††




** Age in years.


Percent

0

Arizona

California

Colorado

Delaware

Florida

GeorgiaHawaii

Kansas

Kentucky

Louisiana

Massachusetts

Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

4510 20 30 40

FIGURE 4 .gFire-Related Indicator: Percentage of Homes

with Smoke Alarms Tested in the Last Month, 1999Behavioral Risk Factor Surveillance System

Percent

0

Arizona

California

Colorado

Delaware

Florida

Georgia

Hawaii

Kansas

Kentucky


Michigan

Minnesota

Nebraska

New Mexico

North Carolina

North Dakota

Ohio

Oklahoma

Oregon

South Carolina

Texas

Utah

Vermont

Washington

Wisconsin

153 6 9 125 15 25 35

35.2

31.1

22.2

33.0

33.0

30.2

22.7

34.7

40.6

37.6

31.4

39.1

21.7

32.4

28.8

‡

23.6

33.3

42.4

27.4

40.8

29.9

26.4

35.3

26.2

35.5

5.7

4.1

6.7

1.9

6.6

5.0

13.0

4.8

4.6

11.4

2.6

2.0

1.8

7.3

10.2

‡

3.8

3.2

5.7

1.3

2.6

9.4

5.9

3.5

2.2

1.8

FIGURE 4 .hFire-Related Indicator: Percentage of Homes

without Smoke Alarms, 1999,Behavioral Risk Factor Surveillance System

Note: No data available for North Carolina.

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