Rail Trespasser Fatalities

Developing Demographic Profiles

Federal Railroad

Administration

March 2008 
NOTE: 

This report has been prepared at the direction of the Federal Railroad Administration (FRA) for the 

purpose of reducing trespasser-train incidents, which contribute significantly to total annual rail-related 

deaths and injures in the United States. As part of FRA’s continuing program to diminish trespassing on 

railroad rights-of-way and associated fatalities and injuries, this study is intended to provide a basis on 

which to build outreach and educational programs and law enforcement initiatives focused on those who 

are most likely to be at risk. 

This document is disseminated under the sponsorship of FRA in the interest of information exchange. 

The United States Government assumes no liability for its contents or use thereof. The contents of this 

report reflect the view of the contractor, who is responsible for the accuracy of the data presented herein. 

The contents do not necessarily reflect the official policy of FRA. This report does not constitute a 

standard, specification, or regulation. The United States Government does not endorse products or 

manufacturers. Trade or manufacturers’ names appear herein only because they are considered essential 

to the objective of this document. 
Rail Trespasser Fatalities 

Developing Demographic Profiles 

PREPARED BY: 

Cadle Creek Consulting 

 Bruce F. George, Principal 

 1201 Rogers Road 

 Edgewater, MD 21037 

COVER PHOTOGRAPH COURTESY OF:

Brian F. Gilleran 

Federal Railroad Administration 

PROJECT MANAGER: 

Pamela Caldwell Foggin 

Federal Railroad Administration 
Table of Contents 

List of Maps, Charts, and Tables ........................................................................................ ii 

Executive Summary............................................................................................................ 1 

1. Introduction................................................................................................................. 3 

1.1 Background......................................................................................................... 3 

1.2 Concept ............................................................................................................... 4 

1.3 Objectives ........................................................................................................... 6 

2. Methodology............................................................................................................... 7 

2.1 Letters and Forms ............................................................................................... 7 

2.2 Compilation of CME/Coroner List ..................................................................... 8 

2.3 Mailings and Followups...................................................................................... 8 

2.4 Responses............................................................................................................ 9 

2.5 “No Record” Responses.................................................................................... 10 

3. Analyses.................................................................................................................... 12 

3.1 The Data............................................................................................................ 12 

4. Response Analyses ................................................................................................... 13 

4.1 Age.................................................................................................................... 13 

4.2 Gender............................................................................................................... 14 

4.3 Gender versus Age............................................................................................ 14 

4.4 Ethnicity............................................................................................................ 16 

4.5 Race................................................................................................................... 17 

4.6 Gender versus Race (and Ethnicity) ................................................................. 18 

4.7 Alcohol and/or Drugs........................................................................................ 18 

4.8 Type of Incident................................................................................................ 19 

4.9 Suicides............................................................................................................. 19 

4.10 Probable Suicides.............................................................................................. 20 

4.11 Drugs and Alcohol as a Factor Among Suicides .............................................. 21 

4.12 Proximity........................................................................................................... 21 

4.13 FRA Regions..................................................................................................... 21 

5. Market Analysis ....................................................................................................... 22 

5.1 Demographic Results....................................................................................... 23 

5.1.1 Age............................................................................................................ 23 

5.1.2 Racial and Ethnic Diversity ...................................................................... 23 

5.1.3 Families and Households .......................................................................... 24 

5.1.4 Socioeconomic Characteristics ................................................................. 24 

5.2 Tapestry Profile................................................................................................. 25 

5.2.1 Segments................................................................................................... 25 

5.2.2 Observation 1: Home Town..................................................................... 26 

5.2.3 Observation 2............................................................................................ 27 

5.2.4 Observation 3............................................................................................ 29 

5.2.5 Observation 4............................................................................................ 29 

5.2.6 Observation 5............................................................................................ 30 

5.2.7 Observation 6............................................................................................ 32 

6. Findings .................................................................................................................... 33 

7. Recommendations..................................................................................................... 35 

Appendices........................................................................................................................ 36 

 i 
List of Maps, Charts, and Tables 

Map 1: Trespasser Fatalities by State (Raw Data) .......................................................... 3 

Map 2: Trespasser Fatalities by State, Normalized by Population ................................. 4 

Map 3: Trespasser Fatalities by State, Normalized by Track Mileage........................... 5 

Map 4: Responses by Jurisdiction................................................................................... 11 

Chart 1. Age: Trespasser Fatalities vs. U.S. Population ................................................. 13 

Chart 2. Fatalities by Gender ........................................................................................... 14 

Chart 3. Fatalities by Gender and Age............................................................................. 15 

Chart 4. Male Trespassers vs. U.S. Population................................................................ 15 

Chart 5. Female Trespassers vs. U.S. Population ............................................................ 16 

Chart 6. Suicides .............................................................................................................. 20 

Chart 7. Suicides by Age and Gender.............................................................................. 20 

 

Table 1. Fatalities by Race vs. U.S. Population............................................................... 17 

Table 2. Gender vs. Race (and Ethnicity)........................................................................ 18 

Table 3. Alcohol and/or Drugs......................................................................................... 18 

Table 4. Alcohol and/or Drugs (Speculative) ................................................................. 19 

Table 5. Type of Incident................................................................................................. 19 

Table 6. Comparison of Age Distribution........................................................................ 23 

Table 7. Racial (and Ethnic) Diversity ........................................................................... 23 

Table 8. 2006 Employment within the Target Group, Age 16+ (Percent) ..................... 24 

Table 9. 2006 Household Income within the Target Group (Percent)............................. 24 

Table 10. Top Tapestry Segments and those with an Index Exceeding 100 ................... 25 

Table 11. LifeMode Groups............................................................................................. 28 

Table 12. Urbanization Groups ....................................................................................... 28 

Table 13. Result of Group Matrix, Cells with Index ≥ 100 ............................................ 32 

ii 
Executive Summary 

This study is part of a continuing program to reduce trespassing on railroad rights-of-way 

and the grievous toll of resulting deaths and injuries. Approximately 500 individuals die 

annually in the United States while trespassing on railroad rights-of-way. The ultimate 

goal of this study is to establish a foundation upon which to build an outreach or public 

education program and create law enforcement efforts focused on those most at risk. 

A three-phase process is envisaged: First, gather information regarding fatalities, 

including home addresses of the decedents; Second, conduct a demographic analysis of 

the decedents and do a market analysis of the households and neighborhoods from which 

they came (based on the addresses) in order to develop a generic profile of those at risk; 

Third, develop a public awareness program targeting those who may take such risks in 

the future. This report addresses the first two steps in this process. 

Survey forms, one for each 2002-2004 trespass fatality, were mailed to the chief medical 

examiner (CME) or coroner in whose jurisdiction the incident was reported to have 

occurred. Forms for 1,524 fatalities were sent to 471 jurisdictions. Subsequently, 279 

jurisdictions (59 percent) returned 1,056 reports (69 percent). Of the forms returned, 935 

contained some useful information (at least gender), but only 740 provided usable 

address information. As less than half of the forms were returned with usable address 

information, the market analysis must be carefully assessed. 

As such, the following findings are predicated on responses to the survey and necessarily 

exclude those fatalities that occurred in the jurisdictions that did not respond. See Map 4 

and Appendix F. Further, if one extends the findings of these analyses to all rail 

trespassers, one assumes that this subset, those who died while trespassing on rail rightsof-way in responding jurisdictions, is representative of all rail trespassers. This may not 

be the case. 

That said, we have learned from the returned forms that trespassers who die are, on 

average, 38 years old and most often Caucasian males. Approximately two-thirds were 

under the influence of alcohol and/or drugs. There is considerable regional variation. 

The gender split is 13 percent female, and 16 percent have Hispanic ethnicities. 

Trespasser fatalities are racially diverse, i.e., 78 percent White, 16 percent Black, 5 

percent Native American, and 1 percent Asian. 

Coroners used the words “suicide” or “intentional” in describing 18 percent of the 

incidents. In reviewing their descriptions, an additional 5 percent have been classified as 

probable suicides. The Federal Railroad Administration (FRA) regulations do not require 

railroads to report suicides (See Title 49 Code of Federal Regulations CFR Section 

225.15), so reported suicides inflate the trespass problem. 

The households and neighborhoods isolated by the market analysis of addresses are 

compatible with the demographic data developed regarding trespasser fatalities (with the 

exception of gender and age). The market analysis has defined a target group and 

 1 
described the types of households and neighborhoods that could be targeted most 

effectively. These are largely urban or suburban, relatively low-income and ethnically, 

culturally, and racially mixed neighborhoods with older, single-family housing units 

occupied by families slightly larger, but younger, than the general population. 

As part of its program to reduce trespassing on railroad rights-of-way, Cadle Creek 

Consulting (CCC) recommends that FRA 1) investigate alternatives for completing the 

survey, 2) use the foregoing demographic data and work with railroads to confirm (or 

refute) the assumption that those who die while trespassing are representative of all 

trespassers, 3) require reporting of all deaths among trespassers, including suicides, 4) 

work with suicide prevention interest groups to develop a response kit for distribution to 

local media outlets following railroad suicide incidents, 5) convene a meeting of principal 

stakeholders to present the report’s findings and discuss outreach options, and 6) in 

addition to publishing this report, post a downloadable version on the FRA Web site and 

allow CCC to distribute the report. 

2 
1. Introduction 

1.1 Background 

Deaths among trespassers on railroad rights-of-way (2,496 in the 5-year period 2000-

2004,1

 or approximately 500 annually) are the leading cause of fatalities attributable to 

railroad operations in the United States. As Maps 1, 2, 3, and Appendix K indicate, the 

problem is widespread. 

Map 1: Trespasser Fatalities by State (Raw Data) 

However, this data, gathered from the railroads and currently available from FRA, is 

limited to tabulations of the number of deaths and injuries, and includes little 

demographic detail. For example, the age of the decedent is included in FRA’s database, 

but the gender is omitted. 

 

1

 U.S. Department of Transportation, Federal Railroad Administration, Railroad Safety Statistics, 2004 

Annual Report, November 2005, p. 20. 

3 
1.2 Concept 

In order for the railroad industry, governments (Federal, State and local), and other 

stakeholders to address this serious issue, they must know more about the individuals 

who trespass. With such knowledge, specific educational programs, materials, and 

messages regarding the hazards and consequences of trespassing on railroad property 

may be developed and effectively distributed. Law enforcement efforts can be targeted 

more efficiently and constructively. Developing summaries and generic profiles for 

trespassers and trespass incidents could provide valuable information regarding those 

most at risk, i.e., the precise audience to be targeted with educational and enforcement 

efforts. However, market analyses require demographic details, e.g., gender and home 

address. (Knowledge of the home address facilitates the use of commercially available 

marketing databases, which are used to generate generic information regarding lifestyles, 

entertainment, and media preferences of customers, or in this case, trespassers.) 

Map 2: Trespasser Fatalities by State, Normalized by Population. 

4 
Map 3: Trespasser Fatalities by State, Normalized by Track Mileage. 

Potential sources of additional data are county coroner and State CME death reports.2 

State CMEs and county coroners receive, and/or prepare, and retain reports of deaths, 

particularly those considered to be from other than natural causes, e.g., resulting from 

severe trauma, such as an incident with a train. Such reports should include personal 

information regarding the deceased, e.g., home address, age, gender, ethnicity, as well as 

the date/time, type and location of the incident. In some States, such information is 

centralized. In others, the information is retained at the county or district level. 

Due to privacy concerns, access to such data often is limited to family members, police 

investigators, and those involved in relevant legal actions. Before access can be granted 

to other parties, assurances must be made that data will be made public only in summary 

fashion and will not be attributable to any specific incident or individual. Success in 

guaranteeing the confidentiality of specific data from public scrutiny is crucial to 

obtaining access to it. 

 

2

 Those who die while trespassing on rail rights-of-way are only a small subset of those who trespass. This 

effort assumes that they are a representative subset. 

5 
1.3 Objectives 

The overall goal of this study is to prevent trespassing on rail rights-of-way, thus 

reducing the number of deaths and injuries among trespassers. Developing summaries 

and generic demographic profiles describing the decedents in fatal trespass incidents 

should provide information regarding the at-risk audience to be targeted. For best results, 

a nationwide market analysis should begin with a database of at least 1,000 individuals. 

This study was a one-time effort, consisting of a mailed survey to collect and analyze the 

data provided by CMEs and coroners. This report includes statistical summaries 

describing, in general demographic terms, individuals who died while trespassing or as a 

result of trespassing on railroad property. 

6 
2. Methodology 

2.1 Letters and Forms 

All surveys require an introduction and a means for responding. A mailed survey 

requires a letter of introduction, a form for responding, and a return envelope. For this 

survey, two letters were included: one was an individualized letter of transmittal from 

Cadle Creek Consulting (CCC)3

 to the county coroner or CME in whose jurisdiction one 

or more trespasser fatalities occurred; the second was a letter of introduction and project 

endorsement addressed to “Our Nation’s Chief Medical Examiners and Coroners” from 

the FRA Administrator, requesting assistance in providing the data. See Appendixes B 

and C. 

Both letters sought to provide assurances that privacy would be protected and that data 

would be released in summary form only, to wit: 

The additional data that you provide ... will be used only by Cadle Creek Consulting to 

compile generalized, statistical, summary reports. ... Cadle Creek Consulting will not 

release the raw data that you provide to FRA. We intend to maintain the confidentiality 

of this requested information. [Cadle Creek Consulting] 

After gathering and processing the data, Cadle Creek Consulting will release to FRA only 

generalized, statistical, summary reports. [FRA Administrator] 

The response form, FRA F 6180.117 (5/04), as a data collection form, required approval 

from the Office of Management and Budget (OMB). Approval was received in June 

2005, and OMB No. 2130-0563 was assigned.4

The one-page response form (Report of Railroad Trespasser Death) is divided into two 

parts, top and bottom. See Appendix D. The top portion contains preprinted information 

from FRA’s files regarding a specific trespasser fatality. Location (State and county), 

date and time, reporting railroad, circumstance of the incident, and the age of the 

decedent—all as reported to FRA by the railroad—are included. The bottom portion of 

the form provides space for CMEs or coroners to complete information regarding the 

decedent and the incident, i.e., gender, ethnicity, race, home address, whether alcohol 

and/or drugs were a factor, and a brief description of the incident. 

The average time to complete the form (based on actual experience of CCC’s trial 

gathering of data from Maryland’s CME) was 5 minutes, once a file was located. 

 

3

 CCC conducted this survey and compiled and analyzed the data. 

4

 See 70 FR 36463 (June 23, 2005). 

7 
2.2 Compilation of CME/Coroner List 

Starting with FRA’s data for 2002-2004, a list was compiled of States and counties in 

which railroad-related trespass fatalities occurred. This list was used to search the Web 

for names and addresses of CMEs and coroners. Principal sources included the Web 

pages of the Federal Government’s Centers for Disease Control and of the National 

Association of County Officials. Though both were extremely useful, names and 

addresses had to be confirmed from other sources, often by phone. Many were found to 

be outdated or to be involved in multijurisdictional arrangements. Ultimately, an address 

list with 471 jurisdictions was compiled. 

2.3 Mailings and Followups 

Packages were mailed first class and contained:5

• A letter from CCC (Appendix B) addressed by name to the specific CME or 

coroner, tailored to his/her jurisdiction; 

• A generic letter of endorsement from FRA’s Administrator (Appendix C); 

• A preprinted Report of Railroad Trespasser Death form(s), one for each railroad 

trespass fatality in the subject jurisdiction between 2002 and 2004, inclusive. 

(Appendix D); and 

• An addressed envelope with first-class postage for returning completed forms. 

Subsequent contacts usually were made by the CMEs or coroner’s office seeking the 

name(s) of the decedents (or a case number), as files in many jurisdictions are retained by 

name. However, FRA’s files do not contain names, and names were not available to 

CCC. Given that most jurisdictions have an entry or receiving log that is maintained 

chronologically, it was suggested to such callers that names and/or case numbers might 

be found in these logs based on the date of the incident. This proved to be true in many, 

but not all, jurisdictions. (In several instances, names were located via the Internet by 

searching for accounts of the incident in local newspapers.) 

After completing the mailings, starting in April 2006, CCC called unresponsive 

jurisdictions, focusing on those with 10 or more incidents. This resulted in the reissuance of some mailings, at times to different individuals and/or addresses. This 

proved to be productive in only a few cases. Often, privacy concerns were cited as 

permitting only partial, if any, response. Particular concern was expressed about the 

request for home addresses. In some cases, a compromise was reached where the 

CME/coroner would provide a zip code, but not a complete address. 

Also, reservations were expressed about responding to the form’s request concerning 

whether or not alcohol and/or drugs were a factor. One coroner noted that he could attest 

 

5 Mailings began October 3, 2005. The last mailing was March 29, 2006.

8 
whether alcohol and/or drugs were present or detectable, but he could not definitively say 

whether they were a factor in the incident. The same coroner also wanted to know how 

he could determine the ethnicity of the decedent, since ethnicity is predicated on language 

and culture. For the U.S. Census, respondents answer such questions, but this may not be 

possible for a coroner even if he/she relies on appearance and/or surname. For a coroner 

to respond to the question of ethnicity requires a measure of subjective judgment. 

In the same vein, many respondents overlooked or confused race and ethnicity. Many 

indicated ethnicity as Hispanic and then skipped the question regarding race. This 

ignores the possibility of different racial subgroups within the ethnic Hispanic culture, 

e.g., a Black or Native American Hispanic. As the U.S. Census Bureau indicates in its 

definition of “ethnic origin:” “It should be noted that people of Hispanic origin may be 

of any race.”6

2.4 Responses 

After only 5 days, Utah returned nine reports on October 9, 2005. The last reports were 

received on April 24, 2006, from Calcasieu, LA (6) and Isanti, MN (1). Materials to both 

had been mailed 94 days earlier. The average response time was 24 days. (Two 

additional forms were received in December 2006, too late for inclusion in the following 

analyses.) 

Some jurisdictions requested compensation before they would reply to the survey. No 

funds were included in the contract for paying CMEs and/or coroners for providing the 

requested data. After explaining the “public” purpose of the effort and that whole files 

were not wanted, just the information indicated on the response form, a few jurisdictions 

reconsidered. Three allowed an outsider access to their files (the State of Maryland, 

Florida’s 10th District, and Riverside County, California).7

 Two jurisdictions, the State 

of New Jersey and Los Angeles County, provided computer-generated listings by e-mail. 

The State of North Carolina received the most request forms (57 forms). All but five of 

the forms were completed and returned. (North Carolina had no record of four, and the 

fifth appeared to be a duplicate.) 

Some jurisdictions did not fill out the form(s), but instead sent complete autopsy reports 

of the decedents involved. In these instances, CCC completed the forms based on the 

autopsy reports. Similarly, CCC filled out forms for both the State of New Jersey and 

Los Angeles County after cross-checking the computer printouts of railroad-related 

fatalities provided by the jurisdictions with the incident records in the FRA database. 

 

6

 Population Division, U.S. Census Bureau, Current Population Survey (CPS) - Definitions and 

Explanations, January 2004, available on the net a/o 2 August, 2006, from 

http://www.census.gov/population/www/cps/cpsdef.html.

7

 CCC went to Maryland’s CME; an Operation Lifesaver volunteer visited Riverside County; and we were 

unable to arrange for a volunteer to visit Florida’s 10th District. 

9 
10 

Forms related to 1,056 incidents (69 percent) were returned by 279 jurisdictions (59 

percent). Of these, 106 (10 percent of responses) indicated that the CME/coroner could 

find no record of the incident. 

2.5 “No Record” Responses 

Some of the factors contributing to “No Record” responses include: 

• The railroad may have misreported the location of the incident; 

• The decedent may have been transported to another jurisdiction before the official 

pronouncement of death; 

• The CME/coroner file may have been misplaced; 

• The CME/coroner may not have been notified of the incident; or 

• The coroner receiving the survey was not the coroner at the time of the incident. 

(Many coroners are in elected positions and archived records are not necessarily 

centralized.) 

Lists of the “No Record” reports, one by State and the other by railroad, are included in 

Appendices E1 and E2. It is important to note that these jurisdictions are not considered 

nonresponsive. They did respond to the survey, but had no records of the incidents. 
Map 4: Responses by Jurisdiction 

11
3. Analyses 

3.1 The Data 

Though 1,056 forms were returned, not all contained useful information. The most 

frequently completed data element was gender (935). Appendix F notes the percentage 

of useful responses (i.e., those that provided at least gender) from each State, from 

100 percent in six states (New Hampshire (1), Oklahoma (20), Oregon (19), Rhode Island 

(3), Utah (9), and Virginia (19)) and the District of Columbia (4), to 0 percent in four 

states (Delaware (8), Massachusetts (32), Maine (3), and West Virginia (15)). This 

information is important to note, as the analyses that follow are based on the responses 

from the participating jurisdictions and necessarily exclude deaths from the 

nonresponding jurisdictions.

This study’s objective of building a database for market analysis with at least 1,000 

addresses was not achieved. Of the reports received, 653 had complete addresses. An 

additional 90 had a zip code only. Many records were provided without a zip code. CCC 

used the USPS Zip Code Lookup on the Internet to complete these entries.8

 Fifteen 

forms were returned with foreign addresses,9 and 87 listed the individual’s address as 

“unknown,” “homeless,” “transient,” or of “no fixed address” and did not provide an 

address. Many responses omitted the address, citing State law or that the information 

was “privileged.” A database of only 743 addresses and/or zip codes reduces the value of 

the resulting market analysis. In discussions with a marketing analysis firm, it was 

concluded that some value might be realized on a national basis, but that attempts to 

reach conclusions for regions or individual States should be avoided. 

 

8

 See http://zip4.usps.com/zip4/welcome.jsp 9

 Foreign addresses included 14 in Mexico and 1 in Canada. Other responses, received without addresses, 

indicated one individual was from Jamaica and another from Taiwan. 

12 
4. Response Analyses 

Caveats: In considering the analyses that follow, two caveats must be kept in mind: 

First, these analyses are predicated on responses to the survey and necessarily exclude 

those jurisdictions that did not respond and the deaths that occurred in those jurisdictions. 

See Map 4 and Appendix F. 

Second, if one extends the findings of these analyses to all rail trespassers, one is 

assuming that this subset, those who died while trespassing on rail rights-of-way in 

responding jurisdictions, is representative of all rail trespassers. This may or may not be 

the case.

Chart 1. Age: Trespasser Fatalities vs. U.S. Population 

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

Percent

4 9 14 19 24 29 34 39 44 49 54 59 64 69 74 79 84 89 94 95

Age

Trespasser Fatalities U.S. Population

Source of U.S. Census Data: Julie Meyer, Age: 2000, Census 2000 Brief, (U.S. Census Bureau, 

October 2001), p. 4. 

4.1 Age 

The age of the decedent is one data element that appears in both FRA’s database and on 

the response form. CMEs/coroners corrected the preprinted age from FRA’s database 

138 times, and provided an age where FRA had none on 81 forms, a total of 219 changes. 

However, the impact on the mean age of all trespasser fatalities was minimal. The 

corrected mean age was 37.5 versus 37.3 from FRA’s raw data from the railroads. As of 

2004, the mean age of the U.S. population was 36. Therefore, the mean age of those 

who die while trespassing on railroad rights-of-way reflects the mean age of the U.S. 

population.10 However, as Chart 1 indicates, 51 percent of trespasser fatalities are 

between the ages of 30 and 49. This compares to 30.5 percent of the U.S. population in 

the same 20-year cohort. 

 

10 These numbers include all decedents, even those for which no response was received from CMEs or 

coroners. 

13 
4.2 Gender 

The data element most consistently provided by 

the CMEs and coroners was gender. Of 935 

forms with this data element completed, 811 (87 

percent) indicated “Male” and 124 (13 percent) 

indicated “Female.” The 2004 U.S. population 

was divided 50.8 percent “Female” versus 49.2 

percent “Male.” See Chart 2. 

4.3 Gender versus Age 

Based on the 922 forms in which both age and 

gender were provided, the average age of f

decedents was 38.3 years, versus 37.4 years fo

male decedents. The average age of all 922 

decedents, after applying corrections provided

by CMEs and coroners, was 37.5 years. 

Statistically, the distributions of male and 

female ages are nearly identical. Comparing these distributions as percentages (to put 

them on a comparative footing, but keep in mind that males outnumber females near

7:1) reveals some variations. The largest is a spike among female decedents in the cohort 

35-39. More than 18 percent (18.2 percent) of women decedents fall in this cohort, 

versus 11 percent of men. See Chart 3. That is more than twice the proportion of this 

cohort in the U.S. female population (8.1 percent). 

emale 

r 

ly 

Chart 2. Fatalities by Gender

Male 87%

Female 

13%

Male and female trespassers share an additional spike, though not as pronounced, in the 

cohort 40-44, each more than 15 percent (15.5 percent and 15.7 percent, respectively). 

For males, this is the largest cohort. As a percentage, female trespasser deaths first 

exceed the population percentage in the 15-19 cohort, but male trespasser deaths do not 

exceed the population percentage until the next cohort, 20-24. By the 5-year cohort, 

deaths among male trespassers do not drop to or below the population percentage again 

until the 55-59 cohort. After the 15-19 cohort, deaths among female trespassers stay at or 

near the population percentage for the next two cohorts, not exceeding the population 

percentage until the 30-34 cohort. Charts 4 and 5 provide percentage comparisons of 

trespasser fatalities to the U.S. population by gender and age. 

14 
Chart 3. Fatalities by Gender and Age

0

2

4

6

8

10

12

14

16

18

20

4 9 14 19 24 29 34 39 44 49 54 59 64 69 74 79 84 89

Age

Percent Killed

% Females % Males

Chart 4. Male Trespassers vs. U.S. Population

0

2

4

6

8

10

12

14

16

18

20

4 9 14 19 24 29 34 39 44 49 54 59 64 69 74 79 84 89

Age

Percent Killed

% Males % U.S.

15 
Chart 5. Female Trespassers vs. U.S. Population

0

2

4

6

8

10

12

14

16

18

20

4 9 14 19 24 29 34 39 44 49 54 59 64 69 74 79 84 89

Age

Percent Killed

% Female % U.S.

4.4 Ethnicity 

Hispanics or Latinos are the principal ethnic entity in the United States. This group is 

characterized by use or knowledge of the Spanish language and self-identification with a 

Latin culture. It is a self-proclaimed classification or description. (Hence, the difficulty 

cited above for a CME or coroner in responding to this question.) 

On the form, “Ethnicity” is a yes or no question (i.e., “Hispanic or Latino, 

(Ethnic/language group), Y/N.”) See Appendix D. This question was only answered on 

846 forms, 152 with “Yes” (18 percent) and 694 with “No” (82 percent). Hispanics 

represented 13 percent of the United States population as of 2004. Compared to the 

United States population as a whole, Hispanics are overrepresented among the 846 deaths 

for which CMEs and coroners provided responses. 

It is important to note that the U.S. Census Bureau reports 44.2 percent of Hispanics live 

in the West (defined by the Census Bureau as Alaska, Arizona, California, Colorado, 

Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and 

Wyoming) where Hispanics represent 24.3 percent of the population.11 Jurisdictions in 

these States returned 74.9 percent of the reporting forms, 13.5 percent above the national 

average. See Appendix F. If only FRA’s Region 7 (Arizona, California, Nevada, and 

Utah) is considered, this dichotomy is even more pronounced. The States in Region 7 

 

11 Roberto R. Ramirez and G. Patricia de la Cruz, The Hispanic Population in the United States: March 

2002, Current Population Reports, p. 20-545 (U.S. Census Bureau, Washington, DC, June 2003). 

16 
provided useful data on 78.9 percent of the forms sent. Of these, 29.5 percent indicated 

that the decedents were Hispanic. The Hispanic population of these four States is 29.7 

percent. This level of reporting from States with high proportions of Hispanics more than 

likely biases the national finding noted above. The data indicates that some effort 

directed specifically at individuals of Hispanic background is reasonable. 

4.5 Race 

Table 1. Fatalities by Race vs. U.S. Population 

Race Forms 

Returned 

Percent 

of 

Forms 

U.S. 

Population 

(x 1000)* 

Percent 

The U.S. Census Bureau divides 

our Nation’s population into 

seven racial groups.12 While the 

study follows the Census 

Bureau’s lead, the forms sent to 

CMEs and coroners only 

provided coding for five of the 

groups, omitting the subsets, 

“Other” and “Two or more,” 

which accounts for 7.9 percent of 

the U.S. population. Eliminating 

the two groups from the possible 

responses on the questionnaire 

could account for some of the 

numbers in the other categories 

being inflated. The form also 

made provision for seven 

subgroups within the “Asian” 

classification. Codes were taken 

from the Census data collection 

form. See Appendix D. 

Native 

American 37 4.5 2,476 0.9 

Black 129 15.8 34,658 12.3 

White 638 78.2 211,461 75.1 

Asian 12 1.5 10,243 3.6 

Native 

Hawaiian 0 0 399 0.1 

Other 0 0 15,359 5.5 

Two or 

more 

0 0 6,826 2.4 

TOTAL 816 100 281,422 100 

*Census 2000 

Data regarding race was provided on 816 returned forms.13 The responses reported data 

for four of the five racial groups listed on the forms sent to the CMEs. 

Within the Asian category, five different subgroups14 were noted, but the numbers are not 

large enough to merit separate consideration of each subgroup. A statistical Chi-squared 

test confirms with 99.9 percent confidence that the racial distribution of the returned 

 

12 White, Black or African American, American Indian and Alaska Native, Asian, Native Hawaiian and 

Other Pacific Islander, Some other race, and Two or more races. See Census 2000 PHC-T-6, “Population 

by Race and Hispanic or Latino Origin for the United States, Regions, Divisions, States, Puerto Rico, and 

Places of 100,000 or More Population,” available on the net a/o 14 August 2006 from 

http://www.census.gov/population/cen2000/phc-t6/tab01.pdf. 

13 On 109 forms, the CME/coroner responded to the question regarding ethnicity (5 non-Hispanic, 1 

unknown, and 103 Hispanic), but not race. These CMEs and coroners probably thought that answering the 

question regarding ethnicity obviated the need to answer the question regarding race. The 109 forms with 

ethnicity but without race are not included in the following analysis regarding race. On the flip side, 

CMEs/coroners provided race 78 times when they did not provide ethnicity. These are included in the 

following analysis. 

14 Asian Indian, 2; Chinese, 1; Filipino, 2; Japanese, 1; Other Asian, 6. 

17 
forms is different from the U.S. population, i.e., that such a distribution would not have 

been realized while taking a random sample of 816 individuals from the U.S. population. 

See Appendix G. Some targeting of the Native American and Black racial groups may be 

merited when developing public educational materials regarding trespassing. 

4.6 Gender versus Race (and Ethnicity) 

A breakdown of gender by race shows some variation between the races. Native 

American and Asian women are overrepresented when compared to the other categories. 

The number of men greatly exceeds the number of females among Hispanics. However, 

the numbers are small, especially for Asians and Native Americans, which makes 

conclusions regarding the differences suspect. The following table applies. 

Table 2. Gender vs. Race (and Ethnicity) 

Native 

American Black White Asian Hispanic* 

Female 7 15 85 3 15 

Male 30 114 553 9 137 

TOTAL 37 129 638 12 152 

RATIO 

(M/F) 4.3 7.6 6.5 3 9.1 

*Hispanics may be included in the racial divisions as well. 

4.7 Alcohol and/or Drugs 

Table 3. Alcohol 

and/or Drugs 

The form sought information regarding whether alcohol and/or 

drugs were a factor in the incident. One coroner qualified his reply 

by noting that he could state whether alcohol and/or drugs were 

present, but he could not say whether they were a factor. 

Information regarding alcohol and/or drugs was provided on 935 

forms. CMEs and coroners responded to each question with “Yes,” 

“No,” or “Unknown” (or Not Tested or Privileged). When there 

was no response, or a response other than Yes or No was entered 

by the CME/coroner, Unknown was assumed. 

Yes No 

Alcohol 357 99 

Both 96 274

Drugs 77 294

Total 530 

18 
Applying that interpretation, we can state definitely that alcohol and/or drugs were 

present in at least 56.7 percent (530) of the decedents. Less than a third of the decedents 

(274, or 29.3 percent) were reported to be free of both alcohol and drugs. See Table 3. 

No data was available for 131 decedents. (This 

number is confirmed by subtracting 530 (the 

number of decedents who tested positive for 

alcohol and/or drugs) and 274 (the number of 

decedents who tested clean) from 935 (the 

number of useful forms returned).) If we 

speculate and distribute the 131 decedents for 

whom no data was entered with respect to alcohol 

and/or drugs in the same ratios as those for whom data was reported, we raise these two 

numbers to 66 percent and 34 percent, respectively, i.e., about two-thirds of those who 

die while trespassing are involved with alcohol and/or drugs. See Table 4. 

4.8 Type of Incident 

Table 4. Alcohol and/or Drugs 

 (Speculative)

Yes No Total 

Alcohol 415 90 505 

Both 111 319 430 

Drugs 90 415 505 

Totals 616 935 

The last question on the survey form read, “What was deceased doing or trying to do, 

e.g., getting on or off train, sleeping, walking, on a trail, hunting, riding ATV, etc?” A 

4-inch blank line was provided for entering an answer. All of the 935 forms have been 

categorized into one of a dozen different categories based on the entries provided by the 

CMEs or coroners. In many instances, this required a subjective judgment on the part of 

CCC. Appendix H provides a complete list of all 935 entries. The reader may review 

these and re-categorize some of the entries and/or establish additional categories. See 

Table 5. 

Table 5. Type of Incident 

Category Explanation Number 

Across Walking or running across track(s) 62 

ATV ATV, dirt bike, snowmobile, etc. 18 

Bridge Involved a bridge or trestle 13 

Foul Play Foul play suspected 4 

Other Insufficient information to categorize 128 

Outside Appeared to be walking or standing outside track gauge 20 

Riding Riding or getting on or off train 46 

Sleeping Sleeping, lying, reclining, lounging, sitting on track or in gauge 186 

CME or coroner used the word "suicide" or "intentional" in describing 

incident Suicide 167 

Probable Probable suicide, but not so indicated by CME or coroner 49 

Vehicle Involved a truck or automobile 24 

Walking Walking, standing on track 218 

4.9 Suicides 

CMEs and coroners used the words “suicide” or “intentional” in describing 167 incidents 

(17.9 percent). See Table 5 and Appendix H. Railroads need not report to FRA suicides 

that have been confirmed “by a coroner or other public authority.” See 49 CFR 225.15. 

The fact that railroads are reporting some suicides inflates the trespass problem. It 

19 
confirms, but does not quantify what has been anecdotally known. Appendix I contains a 

list of railroads reporting suicides. 

4.10 Probable Suicides 

Compounding the suicide issue are rather compelling descriptions of trespassers’ 

activities that culminated in their demise, which indicate that suicide may have been their 

intent. CCC has noted 49 such incidents, even though this classification is largely 

subjective. These descriptions can be reviewed individually in Appendix H in the 

“Probable” category. Given CCC’s classifications, suicides and probable suicides 

together account for 23 percent of all trespasser deaths. See Chart 6. 

Chart 6. Suicides

Confirmed, 167 (18%)

Probable, 49 (5%)

Other Deaths,

719 (77%)

Chart 7 provides a graphic display of 213 confirmed and probable suicides by age and 

gender (169 male, 44 female—3 males reported without age are not included). 

Chart 7. Suicides by Age and Gender

0

5

10

15

20

25

30

35

40

4 9 14 19 24 29 34 39 44 49 54 59 64 69 74 79 84 89

Age

Number

Male Female

20 
4.11 Drugs and Alcohol as a Factor Among Suicides 

A lower incidence of drugs and/or alcohol among suicides was found when compared to 

all the trespass decedents. Of the 216 suicides and probable suicides, 62 tested positive 

for alcohol only, 23 for drugs only, and 15 for both, for a total of 100, or 46 percent. 

Seventy-nine (37 percent) tested negative for both drugs and alcohol. These numbers 

compare to 57 percent who tested positive for drugs, alcohol or both among all trespass 

decedents, including suicides. Almost 30 percent of all screened trespass decedents 

tested clean. As such, there was a lower percentage of alcohol and drugs and a higher 

percentage of “clean” tests among the suicides and probable suicides versus all trespass 

decedents. (Drug and alcohol data was not provided for 37 of these decedents.) 

4.12 Proximity 

A comparison of the county and State where the incident occurred (according to the 

railroads’ reports to FRA) and the home address information returned on 780 forms 

found that the incident occurred in the decedent’s home State 93 percent of the time. 

Seventy-eight percent of the incidents occurred in the decedent’s home county. 

4.13 FRA Regions 

Most of the foregoing data regarding forms sent and received, gender, ethnicity, race, 

alcohol and/or drugs, and activities are provided for each of FRA’s eight regions in 

Appendix J. 

21 
5. Market Analysis 15

Caveats: In considering the market analysis that follows, it is imperative that the 

following two caveats be kept in mind: 

First, this analysis is predicated on responses to the survey and necessarily excludes the 

nonresponsive jurisdictions and the deaths that occurred in them. No input was provided 

from Delaware (8 fatalities), Maine (3 fatalities), Massachusetts (32 fatalities), or West 

Virginia (15 fatalities). Fewer than half of the fatalities in Indiana (48 percent), 

Washington (42 percent), Louisiana (41 percent), Michigan (41 percent), Nebraska (40 

percent), Mississippi (28 percent), Texas (27 percent), Alabama (26 percent), and 

Arkansas (18 percent) are included. See Map 4 and Appendix F. 

Second, if one extends the findings of this analysis to all rail trespassers, one must 

assume that the trespasser fatalities analyzed in this report are representative of all rail 

trespassers. This may or may not be the case. 

The market analysis was performed by ESRI Business Information Solutions16 (ESRI) on 

behalf of CCC. Of the 763 records submitted for the market analysis, 740 were 

determined to have information that contributed to the analysis, i.e., contained usable 

address elements. Of the 740 records with usable address elements, ESRI software was 

able to match 565 addresses (74 percent) to an actual address or at least to its ZIP+4 

location.17 An additional 175 (23 percent) were matched to the dominant (or only) 

census tract within the specified zip code. 

In presenting the findings of the analysis, it is important to note that, unlike the foregoing 

analyses regarding individuals and individual incidents, the market analysis describes the 

lifestyles and life stages of the target group based on its households and/or neighborhoods 

identified through the addresses and/or zip codes found in the submitted database. The 

market analysis defines the target group by describing collectively its households and 

neighborhoods, not individuals. ESRI did not have access to the age, ethnic, or racial 

information that CCC culled from the individual forms. CCC only provided address 

information to ESRI. However, the market analysis provided by ESRI describes the age, 

ethnic, and racial information of the target group. 

 

15 See Appendix K for some background for understanding market analysis in this context. 

16 For further information about ESRI, see www.esribis.com. Total cost to CCC for this analysis was 

$1,496.25. Reports and an appended database were returned October 27-31, 2006. 

17 ZIP+4 is “the nine-digit numeric code, established in 1981, composed of two parts: (a) The initial code: 

the first five digits that identify the sectional center facility and delivery area associated with the address, 

followed by a hyphen; and (b) the four-digit expanded code: the first two additional digits designate the 

sector (a geographic area) and the last two digits designate the segment (a building, floor, etc.). ZIP+4 is a 

USPS trademark.” Source: Glossary of Postal Terms Q-Z available on the net a/o 12/23/2006 at 

http://www.usps.com/cpim/ftp/pubs/pub32/pub32q_z.html

22 
5.1 Demographic Results18

5.1.1 Age 

The age distribution within the target 

group tracks well with the U.S. 

population. The age anomalies of 

trespassers noted above are not 

reflected among the households and 

neighborhoods of the target group. The 

ages associated with trespasser 

fatalities begin to diverge from the 

national and target group norms in the 

late teens and are most pronounced 

among those of middle age, 25-44, 

when compared to either the target 

group or the U.S. population. The 

median age of those in the target group 

is 34.4, younger than the median age of 37 among trespasser fatalities.

5.1.2 Racial and Ethnic Diversity 

The racial and ethnic diversity among trespasser fatalities is confirmed in the target group 

defined by the market analysis. Native Americans, Blacks, and Hispanics are 

overrepresented in the target group (versus the U.S. population) as they are among 

trespasser fatalities. The target group contains a number of Asian households 

commensurate with the U.S. population, but which exceed the actual percentage of Asian 

trespasser fatalities. (The small number of Asians among trespasser fatalities combined 

with the small database submitted for analysis may have been insufficient to reduce the 

number of Asians in the resulting target group.) The proportion of Whites in the target 

group is lower than found in both the U.S. population and among trespasser fatalities. 

(The target group contains 14 percent of “Some Other Race Alone” and “Population of 

2+ Races” categories the response form did not allow for, and which comprise 7.9 

percent of the U.S. population.) 

Table 6. Comparison of Age Distribution 

Age 

Cohort 

U.S. 

Population 

Percentage 

a/o 2000 

Trespasser 

Fatality 

Percentage 

2002-2004 

Target 

Group 

Percentage 

a/o 2006 

0-4 6.8 0.2 7.3 

5-14 14.6 2.7 13.7 

15-19 7.2 8.1 7.5 

20-24 6.7 11.7 8.0 

25-44 30.3 47.8 29.6 

45-64 21.9 24.9 23.3 

65-84 10.9 4.0 9.2 

>84 1.5 0.5 1.5 

Source of U.S. Census Data: Julie Meyer, Age: 2000, 

Census 2000 Brief, (U.S. Census Bureau, October 

2001), p. 4. 

Table 7. Racial (and Ethnic) Diversity 

Native 

American Black White Asian Other Hispanic 

Target 

Group 3.1 16.1 63.2 3.6 14.0 22.0 

U.S. 

Population .9 12.3 75.1 3.7 7.9 13.0 

Trespasser 

Fatalities 4.5 15.8 78.2 1.5 N/A 18.0 

 

18Unless specifically noted otherwise, data is based on the U.S. Census Bureau, 2000 Census of Population 

and Housing. Data noted as 2006 are ESRI forecasts. The ESRI Customer Demographic Profile is 

included as Appendix L. 

23 
5.1.3 Families and Households 

Over a quarter (25.9 percent) of the target group households are single-person 

households, only slightly at variance from the U.S. norm of 25.8 percent. Nearly half 

(48.1 percent) are married couples with no children living at home, versus the national 

percentage of 51.7. Another 23.1 percent are comprised of married couples with their 

own children less than 18 years of age living at home (versus 23.5 percent nationally). 

The average household size of the target group as of 2006 is 2.7 (versus 2.59 nationally). 

More than four-fifths (82.2 percent) of these households are in urban settings. The 

remainder are rural. Housing units are nearly three-fifths (57.8 percent) owner-occupied 

(versus 66.2 percent nationally) with a 2006 value estimated at $158,065, versus a 

national median of $119,600 in 2000. Renter-occupied housing units (33.4 percent 

versus 33.8 percent nationally) drew a median rent of $455, versus $602 nationally. 

Nearly three-fifths (58.9 percent) of the households are in detached, single-unit 

structures. The national figure was 60.3 percent. More than half of the housing units 

occupied by the target group were built before 1969. 

5.1.4 Socioeconomic Characteristics 

In 2000, 15.3 percent of the trespasser households with income were below the poverty 

level, versus a national average of 12.4 percent. In that same year, 27.6 percent of the 

women in the target group were in the labor force, versus 57 percent nationally. 

Six years later, the unemployment rate among the target group was 10 percent. The 2006 

median household disposable income, i.e., income after taxes, was $36,006 per annum. 

The ratio of college graduates over 25 years of age in the target group when compared to 

the ratio of graduates in the U.S. was 0.737. Said another way, individuals in the target 

group are 26.3 percent less likely to have graduated from college when compared to the 

general population. Over a quarter (25.4 percent) did not graduate from high school 

compared to 80 percent of the U.S. population that did. Only 18 percent finished college, 

whereas 24 percent of the general population has at least a bachelor’s degree. 

Table 9. 2006 Household 

Income within the Target 

Group (Percent) 

<$15K 15.7 

$15-24,999K 12.2 

$25-34,999K 11.9 

$35-49,999K 15.7 

$50-74,999K 19.2 

$75-99,999K 10.6 

$100-249,999K 13.1 

$250-499,999K 1.2 

$500K+ 0.4 

Median Household 

Income $44,349 

Table 8. 2006 Employment within 

the Target Group, Age 16+ (Percent) 

Management 10.6 

Professional 17.6 

Services 18.4 

Sales/Related 11.1 

Office/Administrative Support 14.2 

Farming/Fishing/Forestry 1.2 

Construction/Extraction 7.8 

Installation/Maintenance/Repair 4.0 

Production 7.4 

Transportation/Material Moving 7.7 

24 
The average travel time to work for those in the target group who were employed was 

25.8 minutes. 

5.2 Tapestry Profile 

5.2.1 Segments 

ESRI has divided U.S. neighborhoods into 65 groups (segments). The neighborhoods in 

each group have common attributes such as “income, employment, home value, housing 

type, education, household composition, age, and other key determinants of consumer 

behavior.” The ESRI software has assigned each of the 740 trespass fatalities (those with 

usable address information) to one of these segments. By looking at these segments 

collectively, we can develop insights to the lifestyles and life stages of the neighborhoods 

where the trespasser fatalities originated (at least, where they called home) and thus 

define the segment(s) that should probably be targeted. 

Only one of the 740 trespass fatalities could not be assigned to a specific segment. 

Conversely, only 1 of the 65 segments (high rise renters) is not represented among the 

remaining 739 trespass fatalities. However, trespass fatalities were far from being evenly 

divided among the remaining 64 segments. Half (340) of the trespass fatalities were 

assigned to 15 segments. These 15 segments represent 32 percent of U.S. households. 

This provides a “Tapestry Index” of 156 for the neighborhoods from which 50 percent of 

the trespass fatalities originated.19 The following table contains the 15 segments within 

which the most trespass fatalities were identified, as well as the additional 19 segments 

that had a Tapestry Index above 100. 

Table 10. Top Tapestry Segments and those with an Index Exceeding 100 

Tapestry Descriptor* Trespass 

Fatalities % U.S. Households % Index 

53 Home Town 34 4.6 1,710,407 1.5 306 

26 Midland Crowd 28 3.8 4,135,120 3.6 104 

38 Industrious Urban Fringe 28 3.8 1,717,958 1.5 251 

32 Rustbelt Traditions 25 3.4 3,276,608 2.9 118 

48 Great Expectations 25 3.4 2,023,160 1.8 190 

42 Southern Satellites 23 3.1 3,149,400 2.8 113 

6 Sophisticated Squires 22 3.0 3,050,339 2.7 111 

41 Crossroads 21 2.8 1,690,615 1.5 191 

12 Up and Coming Families 21 2.8 3,656,024 3.2 89 

59 Southwestern Families 20 2.7 1,093,848 1.0 282 

62 Modest Income Homes 20 2.7 1,197,756 1.1 257 

24 Main Street, USA 20 2.7 2,981,883 2.6 103 

50 Heartland Communities 19 2.6 2,510,750 2.2 117 

28 Aspiring Young Families 17 2.3 2,686,945 2.4 98 

 

19 “The Tapestry Index measures the proportion of ... customers in a particular market relative to the 

proportion of base households in the market.” (Annotated Customer Tapestry Profile (ESRI, 10/31/2006), 

pg. 1.) In this instance, a Tapestry Index of 156 reflects a high concentration of the type of households (32 

percent of all households) from which half of the trespass fatalities originated. In other words, trespass 

fatalities are 1.56 times as likely to be from one of the household types found within these 15 segments 

than from the average U.S. household. 

25 
Tapestry Descriptor* Trespass 

Fatalities % U.S. Households % Index 

57 Simple Living 17 2.3 1,653,259 1.4 158 

36 Old and Newcomers 16 2.2 2,251,955 2.0 110 

52 Inner City Tenants 16 2.2 1,756,688 1.5 140 

35 International Marketplace 16 2.2 1,505,776 1.3 164 

56 Rural Bypasses 15 2.0 1,771,372 1.6 131 

60 City Dimensions 14 1.9 1,016,814 0.9 212 

64 City Commons 14 1.9 790,737 0.7 273 

21 Urban Villages 14 1.9 893,159 0.8 242 

23 Trendsetters 11 1.5 1,217,911 1.1 139 

45 City Strivers 11 1.5 851,624 0.7 199 

3 Connoisseurs 11 1.5 1,594,248 1.4 106 

34 Family Foundations 10 1.4 977,969 0.9 158 

9 Urban Chic 10 1.4 1,528,609 1.3 101 

58 Newest Residents 10 1.4 1,032,563 0.9 149 

49 Senior Sun Seekers 9 1.2 1,343,256 1.2 103 

55 College Towns 7 0.9 921,179 0.8 117 

54 Urban Rows 7 0.9 402,205 0.4 268 

47 Las Casas 7 0.9 870,381 0.8 124 

65 Social Security Set 5 0.7 749,029 0.7 103 

40 Military Proximity 2 0.3 239,516 0.2 129 

*Note: For complete and detailed descriptions of each Tapestry Segment, see 

Community Tapestry Handbook (ESRI BIS – Environmental Systems Research 

Institute Business Information Systems, 2004) available from ESRI. Call 1-800-

292-2224. 

5.2.2 Observation 1: Home Town 

By concentrating on the Home Town segment, one can address the greatest number of 

trespasser fatalities accumulated in a single segment (34) as well as the segment with the 

highest Tapestry Index, 306. The Home Town segment is described as follows: 20

Demographic

Young single-person households, married couples, and single-parent families hold the 

median age for Home Town residents to 34 years. This figure is slightly younger than the 

U.S. median; however, 24 percent of householders are over 65 years of age. Many 

families have two generations that have lived and worked in the community and children 

who plan to do the same. Home Town neighborhoods are predominantly white with some 

black population. 

Socioeconomic 

The median household income for Home Town residents is $28,800; their net worth is 

$48,800. With slightly more than 70 percent of their income derived from wages and 

salaries, they also rely on Supplemental Security Income and public assistance for 

support. Retirees draw Social Security benefits. Some draw retirement income, but very 

few have invested in the stock market. In educational attainment, 34 percent have not 

graduated from high school, compared to 20 percent nationally. Only 7 percent hold a 

bachelor’s or graduate degree, compared to 25 percent nationally. Although 

unemployment is fairly high, most of the employed find service or skilled labor jobs. 

 

20 Community Tapestry Handbook (ESRI BIS, 2004), p. 77. 

26 
The manufacturing, retail trade, construction, transportation, and support services 

industries are the primary sources of employment for these residents. 

Residential 

These low-density, settled neighborhoods in the Midwest and South rarely change. Home 

Town residents may move from one house to another, but they seldom cross the county 

line. More than 70 percent live in single-family detached homes; another 12 percent live 

in two- to four-unit structures. More than half of the homes are owner-occupied with a 

median value of $58,900. Many of those who rent live in multi-unit structures, paying 

very reasonable rates of less than $500 per month. With population declining in these 

neighborhoods, new construction is scarce. Homes are slightly run down; many housing 

units are vacant. Most homes were built before 1970. 

Preferences 

Home Town residents savor their quasi-country lifestyle by spending time outdoors, 

gardening, fishing, swimming, and walking and, when indoors, reading and playing 

cards. Many are pet owners who purchase prepackaged dry pet foods over moist foods. 

They make the most of their urban locations, enjoying nightclubs, bars, movies, 

museums, and zoos. They use the internet primarily for e-mail and games, either at 

home, work, or the local library. Their primary means of communication is still the 

telephone, and the majority of calls are local. To keep up with current events, Home 

Town households subscribe to daily and Sunday newspapers and tune in to news and 

informational channels such as CNN, Fox News, and the Discovery Channel. Movie 

channels are also popular. 

They shop for groceries at discount stores such as Wal-Mart; Kroger and Aldi are also 

favorites. Perhaps hindered by lack of choice, Home Town shoppers buy apparel at 

discount stores or small local malls; however, they are gaining confidence in internet and 

mail-order shopping. Residents do not dine out very often, but Applebee’s, Cracker 

Barrel, and Golden Corral are their restaurants of choice. 

5.2.3 Observation 2 

By concentrating on neighborhood segments with an index between 200 and 300 (in this 

instance, 6.4 percent of U.S. households), one potentially could reach the households of 

15.8 percent of trespasser fatalities. This subgroup of seven segments is highly 

urbanized: 

 38 Industrious Urban Fringe Urban, concentrated in CA, TX, AZ, FL 

 59 Southwestern Families Suburban, especially in SW, 80 percent Hispanic 

 62 Modest Income Families Older suburbs, family oriented, Black culture 

 60 City Dimensions High density, ethnically diverse, older urban 

 64 City Commons Apartment dwellers, mostly Black, metropolitan 

 21 Urban Villages Multicultural, mostly Hispanic, especially CA 

 54 Urban Rows Cities, especially mid-Atlantic, 70 percent Black 

Note: The first caveat detailed at the start of this market analysis must be kept in mind, 

i.e., that this analysis is predicated on survey responses, not on the universe of trespasser 

fatalities. Any geographic conclusions must be carefully considered.

27 
Groups 

ESRI provides two categorizations of the Tapestry Segments. One is called the 

LifeMode Group and the second is the Urbanization Group. The LifeMode Group 

divides the 65 segments into 12 categories and the Urbanization Group into 11 categories. 

Each of the 65 segments is placed in one LifeMode Group and in one Urbanization 

Group. For example, the Home Town segment is included in LifeMode Group L11—

Factories and Farms, and in the Urbanization Group U8—Suburban Periphery II. 

Segments assigned to a LifeMode Group “share an experience, such as being born in the 

same time period, or a trait such as affluence.” Urbanization Groups “share a locale, 

from the urban canyons of the largest cities to the rural lanes of villages or farms.” 

Ranked by the number of trespass fatalities, most to least, the 12 LifeMode Groups are: 

Table 11. LifeMode Groups 

Group Descriptor* Trespass 

Fatalities % U.S. Households % Index 

L8 Global Roots 92 12.4 9,442,681 8.3 150 

L11 Factories & Farms 89 12.0 10,950,099 9.6 125 

L9 Family Portrait 78 10.5 8,603,242 7.5 140 

L5 Senior Styles 71 9.6 14,231,658 12.5 77 

L2 Upscale Avenues 71 9.6 15,733,421 13.8 70 

L12 American Quilt 69 9.3 10,448,687 9.2 102 

L10 Traditional Living 65 8.8 10,086,731 8.8 99 

L1 High Society 59 8.0 14,253,275 12.5 64 

L3 Metropolis 49 6.6 6,110,287 5.4 124 

L7 High Hopes 42 5.7 4,710,105 4.1 137 

L4 Solo Acts 42 5.7 7,797,510 6.8 83 

L6 Scholars & Patriots 12 1.6 1,679,196 1.5 110 

*Note: For complete and detailed descriptions of each LifeMode Group, see 

Community Tapestry Handbook (ESRI BIS, 2004) available from ESRI. Call 

1-800-292-2224 or download from: http://www.esri.com/library/brochures/pdfs/ 

community-tapestry-handbook.pdf. 

Ranked by the number of trespass fatalities, most to least, the 11 Urbanization Groups 

are: 

Table 12. Urbanization Groups 

Group Descriptor* Trespass 

Fatalities % U.S. Households % Index 

U5 Urban Outskirts I 105 14.2 12,461,013 10.9 130 

U4 Metro Cities II 85 11.5 12,538,134 11.0 104 

U7 Suburban Periphery I 76 10.3 17,444,254 15.3 67 

U8 Suburban Periphery II 74 10.0 11,145,615 9.8 102 

U6 Urban Outskirts II 69 9.3 5,967,902 5.2 178 

U10 Rural I 65 8.8 12,662,714 11.1 79 

U3 Metro Cities I 55 7.4 12,929,151 11.3 66 

U1 Principal Urban Centers I 55 7.4 9,007,266 7.9 94 

U2 Principal Urban Centers II 54 7.3 5,463,844 4.8 152 

U11 Rural II 52 7.0 8,882,378 7.8 90 

U9 Small Towns 49 6.6 5,544,621 4.9 136 

*Note: For complete and detailed descriptions of each Urbanization Group, see 

Community Tapestry Handbook (ESRI BIS, 2004) available from ESRI. Call 1-800-

292-2224 or download from http://www.esri.com/library/brochures/pdfs/communitytapestry-handbook.pdf. 

28 
5.2.4 Observation 3 

The Home Town segment (53) noted in Observation 1 above is found in the Factories 

and Farms LifeMode Group and in the Suburban Periphery II Urbanization Group. By 

addressing the Home Town segment, some spillover benefits could be expected in the 

remainder of these two Groups. More than 22 percent of the trespasser fatalities (163 of 

739) came from neighborhoods and households within these two Groups. These two 

groups are described as follows: 

Urbanization Group: U8 Suburban Periphery II

Segments: 18, 29, 33, 40, 43, 53 

Suburban Periphery II represents the highest percentage of population in urban clusters 

(twice the U.S. median) living in metropolitan areas, in older housing, with the shortest 

commute to work. Owned, single-family homes and military quarters dominate. 

Households are a mix. Half are married couple families, and almost one-third are 

householders living alone. Median household income and home value are below the U.S. 

median, yet median net worth is slightly higher. This group is older. They prefer 

Maxwell House coffee, enjoy gambling, watch QVC, and frequent family restaurants and 

steak houses such as Chi-Chi’s and Perkins.21

LifeMode Group: L11 Factories and Farms

Segment Codes: 25, 37, 42, 53, 56 

Some might say that life has passed by the segments in the Factories and Farms

summary group. Employment in manufacturing and agricultural industries is typical in 

these small, settled communities across America’s breadbasket. The rural South and 

Rustbelt areas change very little over time, creating a climate with few employment 

opportunities, which hinders growth. Many households include married couples or 

married couples with children; median household incomes are approximately $37,000. 

Most own their homes.22

5.2.5 Observation 4 

The highest index among the LifeMode Groups is the first one, Global Roots. Though 

two-thirds of the LifeMode Groups have indexes above 100, none are higher than Global 

Roots. Within the Urbanization Group, three other groups have indexes higher than the 

top group, Urban Outskirts I, and two of these groups also have indexes that are higher 

than Global Roots’ index. Both of these groups, along with Urban Outskirts I and Global 

Roots, have a significant urban and/or suburban component. The two top groups are 

described as follows: 

Urbanization Group: U5 Urban Outskirts I

Segments: 04, 24, 32, 38, 48 

The segments in Urban Outskirts I reside in higher density suburban neighborhoods 

spread across metropolitan areas. Many of these neighborhoods are part of the main hub 

of social, cultural, and economic activity within the metro area. The proximity of higher 

 

21 Ibid., ESRI, pg. 20. 

22 Ibid., ESRI, pg. 16. 

29 
density suburban areas to places of employment and entertainment venues combines the 

convenience of access with the advantage of affordable suburban living. The median 

household income of Urban Outskirts I is $49,000, on par with the national median, 

although the population is slightly younger with a median age of 34 (compared to the 

national median of 36 years). Like established suburban communities, the housing stock 

is dominated by single-family dwellings but includes rental apartments to accommodate 

younger households with growing incomes. “Do-it-yourself” (DIY) projects are popular 

here, with owners tackling home improvement basics such as patios, fencing, flooring, 

and, naturally, lawn care. Residents enjoy an active life that includes a variety of sports, 

even roller blading. The media of choice is television, with as many as four television 

sets in many homes.23

LifeMode Group: L8 Global Roots 

Segment Codes: 35, 38, 44, 47, 52, 58, 60, 61 

The common thread among the segments in Global Roots is ethnic diversity. Las Casas

and NeWest Residents represent the strong Hispanic influence in this group in addition to 

a broad mix of racial diversity found in Urban Melting Pot and High Rise Renters. In 

general, these households are young with modest incomes and tend to rent in multiunit 

dwellings. The youth of this group reflects recent immigration trends; half of all 

households have immigrated to the United States within the past 10 years. The 

households range from married couples, typically with children, to single parents to 

individuals who live by themselves. Most of these recent arrivals strive to provide a 

better future for their children, find better jobs, and achieve the dream of home 

ownership.24

5.2.6 Observation 5 

The top LifeMode Group, Global Roots, and the top Urbanization Group, Urban 

Outskirts I, have only one segment in common, Industrious Urban Fringe. This segment 

accounts for only 28 of the trespass fatalities in both groups. However, the index for the 

Industrious Urban Fringe segment is 251. A focus on this segment in the development 

of programs, materials, and outreach probably would spill over to the remainder of both 

the Urban Outskirts and Global Roots Groups. This has potential to reach the households 

of 22.9 percent of trespass fatalities (169 fatalities). The Industrious Urban Fringe

segment is described as follows: 25

Demographic 

Family is central to most Industrious Urban Fringe households. More than half of these 

households have children, primarily in married-couple households and secondarily in 

single-parent families. Multigenerational households are relatively popular. The 

comparatively low median age of 29 years reflects the high proportion of children. 

Hispanics make up 57 percent of the residents. One-quarter of Industrious Urban Fringe

residents are foreign born, bringing rich and diverse cultures to these urban outskirt 

neighborhoods. 

 

23 Ibid., ESRI, pg. 20. 

24 Ibid., ESRI, pg. 16. 

25 Ibid., ESRI, pg. 62. 

30 
Socioeconomic 

The median household income of Industrious Urban Fringe residents is $39,000, and 

median net worth is $64,000. With a large household size, their discretionary income is 

low compared with market segments of similar median income. Settled on the fringe of 

metropolitan cities, these households take advantage of their proximity to metropolitan 

cities for employment opportunities. These diverse families rely mainly on skilled and 

administrative work in the service and manufacturing industries for their livelihood. The 

education level is less than the U.S. average, and unemployment is higher. 

Residential 

Two-thirds of Industrious Urban Fringe householders own their homes. Most live in 

single-family homes. The median home value of $105,000 is about 25 percent less than 

the U.S. median. Living further out from urban centers allows many households to find 

the space to raise a family and have an affordable home. The majority of these 

neighborhoods are located in California, Texas, Arizona, and Florida. 

Preferences 

Industrious Urban Fringe households balance their budgets carefully. Mortgage 

payments take priority. They shop at Wal-Mart, Kmart, Target, and other major discount 

stores for baby and children’s products. They dine out less often than average 

households. Many have no financial investments or retirement savings other than their 

homes and are less likely to carry health insurance than average. 

Keeping in touch is important to these residents. They often have a second phone line at 

home and various phone services. Having pets, particularly dogs, is an integral part of 

their family lifestyle. They enjoy watching movies, both at theaters and at home. 

Multiple visits to movie theaters in a month are quite common. 

Newspapers and magazines are not the best media to reach the Industrious Urban Fringe

households. Television and radio are most effective. They watch television just as much 

as the average U.S. households but with a lower subscription rate to cable. They are 

heavy radio listeners. Contemporary hit and Hispanic stations dominate the radio dials. 

Construction of an 11-by-12 matrix (11 cells for the Urbanization Groups and 12 cells for 

the LifeMode Groups) highlights 11 cells (out of 43) for which both of the intersecting 

groups have indexes greater than 100 and the cell itself has an index of 100 or more. 

(Though an 11-by-12 matrix has 132 cells, in this application only 43 had values, or 

segments, assigned.) The other 32 cells were either in groups with indexes less than 100 

or themselves had indexes less than 100. The 11 cells are as follows: 

31 
Table 13. Result of Group Matrix, Cells with Index ≥ 100

Intersecting Groups Common 

Segments 

Trespass 

Fatalities Index 

L3 Metropolis 

U2 Principal Urban Centers II 45, 54 18 218 

L3 Metropolis 

U6 Urban Outskirts II 51, 62 25 162 

L6 Scholars and Patriots 

U6 Urban Outskirts II 55 7 117 

L6 Scholars and Patriots 40 2 129 U8 Suburban Periphery II 

L7 High Hopes 48 25 190 U5 Urban Outskirts I 

L8 Global Roots 52, 60 30 171 U4 Metro Cities II 

L8 Global Roots 38 28 251 U5 Urban Outskirts I 

L9 Family Portrait 64 14 273 U2 Principal Urban Centers II 

L9 Family Portrait 59 20 282 U6 Urban Outskirts II 

L11 Factories and Farms 53 34 306 U8 Suburban Periphery II 

L12 American Quilt 41 21 191 U9 Small Towns 

5.2.7 Observation 6 

A focus on any of the above group combinations with an emphasis on the common 

segment(s) should prove beneficial. Effectiveness would vary based on available 

resources, the number of households in the segment(s), the geographic concentration of 

the households/neighborhoods, the demographic diversity within the segment(s), etc. 

Two of these combinations, highlighted in red, already have been addressed in the 

preceding discussion. 

A complete copy of the Customer Tapestry Profile as provided by ESRI is attached as 

Appendix M. 

ESRI’s Customer Geographic Summary has not been included, as its value has been 

significantly diminished to a degree that it would be misleading because of the numerous 

jurisdictions that did not respond to the survey. 

32 
6. Findings 

Following is a summary of this study’s 10 principal findings regarding those killed while 

trespassing on railroad rights-of-way. 

1. The typical trespasser fatality on a railroad’s right-of-way is an inebriated, 38-

year-old white male. However, there is wide variation. 

2. The presence of alcohol and/or drugs is pervasive. Fifty-seven percent of 

decedents tested positive for alcohol and/or drugs, while only 29.3 percent tested 

negative for these substances. The remaining decedents were not tested, but if 

distributed in the same ratios, the numbers indicate that two-thirds were 

influenced by alcohol and/or drugs and about one-third were not. 

3. Of those in this study who died trespassing on railroad rights-of-way, 13 percent 

were female and 87 percent were male. 

4. Eighteen percent of the decedents were Hispanic. This varies dramatically across 

FRA’s regions. See Appendix J. Nationally, 18 percent is slightly above the 13 

percent that Hispanics represent in the U.S. population, but because of the 

incomplete reporting (which also varied by region), it is difficult to say with 

certainty that Hispanics are overrepresented. 

5. Four major racial groups were identified. Asians, at 1.5 percent, were 

underrepresented, as Asians comprise 3.6 percent of the U.S. population. Native 

Americans were overrepresented by almost five times the actual number, 4.5 

percent versus 0.9 percent of the U.S. population. Blacks were overrepresented at 

15.8 percent versus 12.3 percent of the U.S. population. This varied regionally 

and would be subject to the same qualification stated above regarding Hispanics. 

The remainder, 78.2 percent, was White. (This last figure may be somewhat 

inflated. The U.S. population includes two racial components that the survey 

form did not accommodate, i.e., “Some Other Race Alone” and “Population of 2+ 

Races.” According to census data, these two categories comprise 7.9 percent of 

the U.S. population. It is likely that some individuals were reported as White due 

to either the inability to determine race or the missing categories on the survey 

form.) 

6. CMEs and coroners described the activity of more than 43 percent of the 

decedents as walking, standing, sleeping, lying, reclining, lounging or sitting on 

the track or in the gauge, i.e., between the rails. Seven percent were walking or 

running across the track. Other activities included riding a recreational vehicle 

(ATV, dirt bike, snowmobile, etc.), standing outside the gauge but obviously too 

close, riding or getting on or off a train, driving a highway vehicle, or being on a 

bridge or trestle. Tunnels were not mentioned. Nearly 14 percent of reports did 

not provide sufficient information to categorize. See Table 5 and Appendix H. 

33 
7. The presence of a large number of suicides in the database (18 percent) was 

unexpected. Railroads are not required to report suicides to FRA. In reviewing 

CME and coroner comments, it appears an additional 5 percent of the decedents 

were probable suicides. Because the FRA does not require the railroads to report 

suicides, these numbers represent only the minimum number of suicides for the 

sample period. 

8. The market analysis used the decedents’ individual addresses to identify and 

categorize the addresses into their respective neighborhood and household 

subsets. These subsets should facilitate the development of educational and law 

enforcement outreach programs and materials focused on the “target group.” 

Here are some attributes of the target group: It is younger than the general 

population of the United States; Native Americans, Blacks, and Hispanics are 

overrepresented; It is largely urban or suburban (82.2 percent); Unemployment in 

2006 was 10 percent, and, of those households with income, 15.3 percent were 

below the poverty level, versus 12.4 percent nationally; Only 74.6 percent have 

graduated from high school and 18 percent from college, versus 80 percent and 24 

percent, respectively, in the general population. 

9. By concentrating on the 1.7 million households (1.5 percent of the Nation’s total 

households) the market analysis refers to as Home Town, the outreach would 

directly address 4.6 percent of potential trespasser fatalities as well as an 

additional 18.7 million households that are closely aligned with the Home Town

group. These households account for more than 22 percent of all trespasser 

fatalities. 

10. Another group to which the market analysis refers as the Industrious Urban 

Fringe (also 1.7 million households) has similar potential. This group is the 

source of 3.8 percent of all trespasser fatalities, and is closely aligned with groups 

that account for an additional 19.1 percent of these fatalities, yielding the potential 

to reach 22.9 percent of all trespasser fatalities. 

34 
7. Recommendations 

As part of its program to reduce trespassing on railroad rights-of-way, CCC recommends 

that FRA address each of the following six suggestions. CCC would welcome the 

opportunity to contractually participate with or support FRA in pursuit of any or all of 

these suggestions. 

1. Investigate alternatives for completing this survey. For example, ask the involved 

railroads to complete the forms for those incidents for which CMEs or coroners 

could not or did not complete, or request access to the railroads records in order to 

complete the form(s). Request assistance from the Association of American 

Railroads (AAR) and the American Short Line and Regional Railroad Association 

(ASLRRA) to assist with this one-time effort. Once the survey has been 

completed, rerun the market analysis. 

2. Using the foregoing demographic data, work with railroads to confirm (or refute) 

the assumption that those who die while trespassing are representative of all 

trespassers. 

3. Require reporting of all deaths among trespassers, including suicides. (This 

would necessitate railroad reporting officers to check with the CME or coroner in 

the jurisdiction where the death occurred to determine how the death is being 

classified. Railroad claims officers may already be doing this.) Suicides should 

be reported as suicides. The current situation, whereby some suicides are 

included in the trespass database, inflates the trespass numbers while providing 

little insight as to the actual extent of suicides by rail. 

4. Work with suicide prevention interest groups to develop a response kit for 

distribution by railroad and Government information officers to local media 

outlets following railroad suicide incidents. This would address the possibility of 

copycat incidents suggested by anecdotal information. 

5. Convene a meeting of principal stakeholders to present these findings and discuss 

outreach options, e.g., Operation Lifesaver, American Association of Suicidology, 

rail labor organizations, AAR, ASLRRA, the Rails-to-Trails Conservancy, as well 

as FRA, the Federal Highway Administration, the National Highway Traffic 

Safety Administration, and the U.S. Department of Transportation. Invite the Ad 

Council to participate. 

6. In addition to publishing this report, post a downloadable version on the FRA 

Web site. Allow CCC to distribute the report. 

35 
Appendices 

Appendix A: Trespasser Fatalities by State (2002-2004) 

 

 

Fatality 

Rate 

Fatality 

Rate 

State Fatalities 

per 

100,000 

per 1,000 

miles 

 population of track 

 

Alabama 19 0.427 5.82 

Arizona 41 0.799 23.05 

Arkansas 17 0.636 6.45 

California 261 0.771 45.53 

Colorado 11 0.256 4.00 

Connecticut 7 0.206 12.84 

Delaware 8 1.021 35.09 

District of Columbia 4 0.699 166.67 

Florida 87 0.544 30.46 

Georgia 54 0.660 11.47 

Idaho 4 0.309 2.50 

Illinois 84 0.676 11.52 

Indiana 29 0.477 6.84 

Iowa 25 0.854 6.31 

Kansas 15 0.558 3.01 

Kentucky 17 0.421 6.36 

Louisiana 34 0.761 11.44 

Maine 3 0.235 2.61 

Maryland 27 0.510 35.43 

Massachusetts 32 0.504 29.09 

Michigan 17 0.171 4.58 

Minnesota 15 0.305 3.24 

Mississippi 18 0.633 7.08 

Missouri 24 0.429 5.87 

Montana 7 0.776 2.14 

Nebraska 10 0.584 2.89 

Nevada 11 0.551 9.17 

New Hampshire 1 0.081 2.35 

New Jersey 46 0.547 50.06 

New Mexico 28 1.539 14.42 

New York 56 0.295 15.54 

North Carolina 57 0.708 17.52 

North Dakota 3 0.467 0.83 

Ohio 51 0.449 9.75 

Oklahoma 20 0.580 6.18 

Oregon 19 0.555 7.67 

Pennsylvania 55 0.448 10.82 

Rhode Island 3 0.286 29.41 

South Carolina 24 0.598 10.43 

South Dakota 4 0.530 2.18 

36 
 

 

Fatality 

Rate 

Fatality 

Rate 

State Fatalities 

per 

100,000 

per 1,000 

miles 

 population of track 

 

Tennessee 30 0.527 11.50 

Texas 136 0.652 13.13 

Utah 9 0.403 6.31 

Vermont 0 0.000 0.00 

Virginia 19 0.268 5.84 

Washington 45 0.764 14.18 

West Virginia 15 0.830 6.71 

Wisconsin 19 0.354 5.51 

Wyoming 3 0.608 1.61 

 

National Total 1,524 0.542 10.80 

37 
Appendix B: Letter of Transmittal from Cadle Creek Consulting 

38 
Appendix C: Letter of Endorsement from FRA’s Administrator 

39 
Appendix D: Report of Railroad Trespasser Death 

FRA F 6180.117 (5/04) 

OMB NO. 2130-0563 

40 
Appendix E1: “No Record” Reports by State, County, and Date 

ST COUNTY DATE TIME RR INCDTNO 

AZ COCONINO 2/11/2004 3:55AM BNSF SW0204003 

AZ PINAL 5/7/2004 12:40AM UP 0504TS008 

CA FRESNO 1/14/2004 10:08AM ATK 91081 

CA KERN 6/16/2004 3:55AM BNSF NC0604106 

CA KERN 10/12/2004 3:16PM UP 1004RS007 

CA LOS ANGELE 1/24/2002 2:10PM UP 0102LA040 

CA LOS ANGELE 4/3/2002 3:05PM SCAX 403021 

CA LOS ANGELE 7/21/2002 12:55AM ATK 74392 

CA LOS ANGELE 10/5/2003 2:20PM ATK 80092 

CA MADERA 12/31/2002 1:50AM BNSF NC1202010 

CA MERCED 10/9/2004 7:58AM UP 1004RS008 

CA RIVERSIDE 6/10/2003 11:40PM BNSF SC0603018 

CA RIVERSIDE 11/17/2003 7:30PM BNSF SC1103008 

CA SACRAMENTO 8/17/2002 11:45AM UP 0802RS031 

CA SAN BERNAR 4/29/2002 9:50PM UP 0402LA055 

CA SAN LUIS O 2/22/2002 7:00AM UP 0202LA027 

CA SANTA BARB 3/28/2003 10:10AM ATK 77542 

CA SANTA BARB 10/25/2003 12:12PM ATK 90134 

CA SANTA BARB 7/2/2004 7:30PM ATK 93083 

CA VENTURA 12/31/2004 1:08PM ATK 95033 

CA YOLO 12/12/2002 1:05AM UP 1202RS033 

CO ADAMS 8/16/2002 11:15PM UP 0802DV007 

CT NEW LONDON 8/9/2002 12:30PM ATK 74702 

FL BROWARD 10/30/2002 9:55PM CSX 100220002 

FL HILLSBOROU 9/15/2002 8:07AM CSX 90220003 

GA COWETA 3/18/2004 3:53PM CSX 5355 

GA RICHMOND 6/15/2002 2:50AM CSX 60201026 

IA LINN 6/24/2003 10:54AM CIC 200304P 

IA LINN 12/4/2003 1:40PM UP 1203CB002 

IA POTTAWATTA 11/29/2003 11:25PM UP 1103CB014 

IA TAMA 7/7/2003 12:20AM UP 0703CB007 

IA WOODBURY 1/10/2004 12:31PM UP 0104CB004 

IL COOK 3/12/2002 5:38PM ATK 72550 

IL COOK 8/29/2002 10:15PM CC 158313 

IL COOK 11/22/2002 5:54AM NIRC HC005 

IL COOK 2/6/2004 3:01PM UP 0204PR009 

IL COOK 9/16/2004 5:35AM NIRC MR171X 

IL DU PAGE 9/27/2002 11:25PM BNSF CH0902027 

IL DU PAGE 10/12/2003 11:55AM WC 200925 

IL LAKE 4/4/2003 6:11PM UPME 0403CM001 

IL MACON 6/6/2003 7:07PM NS P060316473 

IL MORGAN 4/11/2003 10:00AM BNSF CH0403006 

IL PEORIA 6/29/2003 10:00AM BNSF CH0603015 

IN ELKHART 3/2/2004 9:20AM NS P030417453 

KY JEFFERSON 6/15/2002 12:51AM PAL 2002JUN01P 

LA LAFAYETTE 7/13/2002 2:50AM UP 0702LV012 

MD MONTGOMERY 5/23/2004 2:20AM CSX 4835 

MN STEARNS 8/7/2004 1:25AM BNSF TC0804003 

NC ALAMANCE 10/10/2004 7:15PM ATK 94190 

NC EDGECOMBE 7/29/2004 8:25PM CSX 5474 

NC GUILFORD 7/26/2003 6:15AM NS P070316618 

NC YADKIN 7/30/2002 12:45AM ATK 74522 

NJ ESSEX 8/19/2003 7:12AM NJTR 200308586 

NJ HUDSON 8/26/2004 2:40AM CRSH R080400519 

NJ MERCER 7/10/2002 10:51AM CRSH R070200342 

NJ MIDDLESEX 3/13/2003 6:15PM NJTR 200303227 

41 
ST COUNTY DATE TIME RR INCDTNO 

NJ MORRIS 10/10/2003 5:31AM NJTR 200310708 

NJ PASSAIC 11/7/2003 11:10AM NYSW 200300112 

NM MCKINLEY 1/29/2002 7:00AM BNSF SW0102013 

NM MCKINLEY 1/29/2002 7:00AM BNSF SW0102013 

NM MCKINLEY 1/29/2002 7:00AM BNSF SW0102013 

NM MCKINLEY 1/29/2002 7:00AM BNSF SW0102013 

NM MCKINLEY 1/29/2002 7:00AM BNSF SW0102013 

NM SANDOVAL 10/12/2002 1:22PM ATK 75515 

NM VALENCIA 6/2/2004 3:45AM BNSF SW0604100 

NV CLARK 10/6/2003 9:45PM UP 1003UT010 

NV PERSHING 7/17/2003 5:25PM UP 0703RS033 

NY HERKIMER 4/24/2002 1:10PM CSX 40230029 

NY ONONDAGA 12/29/2003 5:02PM ATK 90930 

NY SUFFOLK 1/26/2004 4:30AM LI TS20040101 

OH MADISON 3/16/2003 7:45PM CSX 30307043 

PA BUCKS 6/8/2004 11:15AM SEPA Y0406012 

PA LEHIGH 1/2/2004 11:07AM NS P010417167 

SC CHARLESTON 4/1/2002 4:55PM NS P040215196 

TN JEFFERSON 11/13/2002 6:58PM NS P110215874 

TN RHEA 1/28/2003 4:40PM NS P010316083 

TN SHELBY 3/2/2002 2:55PM NS P030215106 

TN SHELBY 3/6/2004 9:20PM NS P030417334 

TN SHELBY 9/12/2004 6:30AM CSX 7147 

TX BOSQUE 2/1/2004 5:30PM ATK 91283 

TX BOWIE 1/19/2002 3:14AM KCS 20119005 

TX CALLAHAN 2/3/2004 1:45PM UP 0204FW002 

TX CAMERON 8/27/2003 11:55PM BRG I072003 

TX CAMERON 9/19/2004 9:10PM UP 0904SA029 

TX COMAL 5/4/2003 6:00AM UP 0503SA005 

TX DENTON 10/15/2003 8:30AM BNSF TX1003006 

TX FRIO 8/21/2002 11:58AM UP 0802SA039 

TX FRIO 2/8/2004 12:15AM UP 0204SA033 

TX GUADALUPE 12/4/2004 2:25AM UP 1204SA004 

TX KENEDY 6/15/2003 12:14PM UP 0603SA036 

TX KENEDY 6/15/2003 12:16PM UP 0603SA035 

TX KENEDY 8/20/2003 2:33AM UP 0803SA016 

TX LA SALLE 3/25/2004 11:30PM UP 0304SA033 

TX MEDINA 4/25/2004 12:10AM UP 0404SA030 

TX TARRANT 2/24/2003 2:05PM UP 0203FW018 

TX VAL VERDE 2/27/2002 12:08PM UP 0202SA023 

TX VAL VERDE 9/22/2004 3:48AM UP 0904SA028 

TX WHARTON 10/12/2002 5:26AM UP 1002HO010 

TX WHARTON 8/2/2004 6:35PM UP 0804HO002 

TX WILLIAMSON 9/22/2002 5:45PM UP 0902SA025 

TX WILLIAMSON 9/22/2002 5:45PM UP 0902SA025 

WA CLARK 12/14/2002 1:25PM ATK 76225 

WA COWLITZ 9/4/2003 5:57PM UP 0903PD001 

WA COWLITZ 5/31/2004 3:30PM UP 0504PD030 

WA COWLITZ 5/31/2004 3:30PM UP 0504PD030 

WA SNOHOMISH 2/20/2002 5:50PM ATK 72343 

42 
Appendix E2: “No Record” Reports by 

 Railroad, State, County, and Date 

RR ST COUNTY DATE TIME INCDTNO 

ATK CA FRESNO 1/14/2004 10:08AM 91081 

ATK CA LOS ANGELE 7/21/2002 12:55AM 74392 

ATK CA LOS ANGELE 10/5/2003 2:20PM 80092 

ATK CA SANTA BARB 3/28/2003 10:10AM 77542 

ATK CA SANTA BARB 10/25/2003 12:12PM 90134 

ATK CA SANTA BARB 7/2/2004 7:30PM 93083 

ATK CA VENTURA 12/31/2004 1:08PM 95033 

ATK CT NEW LONDON 8/9/2002 12:30PM 74702 

ATK IL COOK 3/12/2002 5:38PM 72550 

ATK NC ALAMANCE 10/10/2004 7:15PM 94190 

ATK NC YADKIN 7/30/2002 12:45AM 74522 

ATK NM SANDOVAL 10/12/2002 1:22PM 75515 

ATK NY ONONDAGA 12/29/2003 5:02PM 90930 

ATK TX BOSQUE 2/1/2004 5:30PM 91283 

ATK WA CLARK 12/14/2002 1:25PM 76225 

ATK WA SNOHOMISH 2/20/2002 5:50PM 72343 

BNSF AZ COCONINO 2/11/2004 3:55AM SW0204003 

BNSF CA KERN 6/16/2004 3:55AM NC0604106 

BNSF CA MADERA 12/31/2002 1:50AM NC1202010 

BNSF CA RIVERSIDE 6/10/2003 11:40PM SC0603018 

BNSF CA RIVERSIDE 11/17/2003 7:30PM SC1103008 

BNSF IL DU PAGE 9/27/2002 11:25PM CH0902027 

BNSF IL MORGAN 4/11/2003 10:00AM CH0403006 

BNSF IL PEORIA 6/29/2003 10:00AM CH0603015 

BNSF MN STEARNS 8/7/2004 1:25AM TC0804003 

BNSF NM MCKINLEY 1/29/2002 7:00AM SW0102013 

BNSF NM MCKINLEY 1/29/2002 7:00AM SW0102013 

BNSF NM MCKINLEY 1/29/2002 7:00AM SW0102013 

BNSF NM MCKINLEY 1/29/2002 7:00AM SW0102013 

BNSF NM MCKINLEY 1/29/2002 7:00AM SW0102013 

BNSF NM VALENCIA 6/2/2004 3:45AM SW0604100 

BNSF TX DENTON 10/15/2003 8:30AM TX1003006 

BRG TX CAMERON 8/27/2003 11:55PM I072003 

CC IL COOK 8/29/2002 10:15PM 158313 

CIC IA LINN 6/24/2003 10:54AM 200304P 

CRSH NJ HUDSON 8/26/2004 2:40AM R080400519 

CRSH NJ MERCER 7/10/2002 10:51AM R070200342 

CSX FL BROWARD 10/30/2002 9:55PM 100220002 

CSX FL HILLSBOROU 9/15/2002 8:07AM 90220003 

CSX GA COWETA 3/18/2004 3:53PM 5355 

CSX GA RICHMOND 6/15/2002 2:50AM 60201026 

CSX MD MONTGOMERY 5/23/2004 2:20AM 4835 

CSX NC EDGECOMBE 7/29/2004 8:25PM 5474 

CSX NY HERKIMER 4/24/2002 1:10PM 40230029 

CSX OH MADISON 3/16/2003 7:45PM 30307043 

CSX TN SHELBY 9/12/2004 6:30AM 7147 

KCS TX BOWIE 1/19/2002 3:14AM 20119005 

LI NY SUFFOLK 1/26/2004 4:30AM TS20040101 

NIRC IL COOK 11/22/2002 5:54AM HC005 

NIRC IL COOK 9/16/2004 5:35AM MR171X 

NJTR NJ ESSEX 8/19/2003 7:12AM 200308586 

NJTR NJ MIDDLESEX 3/13/2003 6:15PM 200303227 

NJTR NJ MORRIS 10/10/2003 5:31AM 200310708 

NS IL MACON 6/6/2003 7:07PM P060316473 

NS IN ELKHART 3/2/2004 9:20AM P030417453 

43 
RR ST COUNTY DATE TIME INCDTNO 

NS NC GUILFORD 7/26/2003 6:15AM P070316618 

NS PA LEHIGH 1/2/2004 11:07AM P010417167 

NS SC CHARLESTON 4/1/2002 4:55PM P040215196 

NS TN JEFFERSON 11/13/2002 6:58PM P110215874 

NS TN RHEA 1/28/2003 4:40PM P010316083 

NS TN SHELBY 3/2/2002 2:55PM P030215106 

NS TN SHELBY 3/6/2004 9:20PM P030417334 

NYSW NJ PASSAIC 11/7/2003 11:10AM 200300112 

PAL KY JEFFERSON 6/15/2002 12:51AM 2002JUN01P 

SCAX CA LOS ANGELE 4/3/2002 3:05PM 403021 

SEPA PA BUCKS 6/8/2004 11:15AM Y0406012 

UP AZ PINAL 5/7/2004 12:40AM 0504TS008 

UP CA KERN 10/12/2004 3:16PM 1004RS007 

UP CA LOS ANGELE 1/24/2002 2:10PM 0102LA040 

UP CA MERCED 10/9/2004 7:58AM 1004RS008 

UP CA SACRAMENTO 8/17/2002 11:45AM 0802RS031 

UP CA SAN BERNAR 4/29/2002 9:50PM 0402LA055 

UP CA SAN LUIS O 2/22/2002 7:00AM 0202LA027 

UP CA YOLO 12/12/2002 1:05AM 1202RS033 

UP CO ADAMS 8/16/2002 11:15PM 0802DV007 

UP IA LINN 12/4/2003 1:40PM 1203CB002 

UP IA POTTAWATTA 11/29/2003 11:25PM 1103CB014 

UP IA TAMA 7/7/2003 12:20AM 0703CB007 

UP IA WOODBURY 1/10/2004 12:31PM 0104CB004 

UP IL COOK 2/6/2004 3:01PM 0204PR009 

UP LA LAFAYETTE 7/13/2002 2:50AM 0702LV012 

UP NV CLARK 10/6/2003 9:45PM 1003UT010 

UP NV PERSHING 7/17/2003 5:25PM 0703RS033 

UP TX CALLAHAN 2/3/2004 1:45PM 0204FW002 

UP TX CAMERON 9/19/2004 9:10PM 0904SA029 

UP TX COMAL 5/4/2003 6:00AM 0503SA005 

UP TX FRIO 8/21/2002 11:58AM 0802SA039 

UP TX FRIO 2/8/2004 12:15AM 0204SA033 

UP TX GUADALUPE 12/4/2004 2:25AM 1204SA004 

UP TX KENEDY 6/15/2003 12:14PM 0603SA036 

UP TX KENEDY 6/15/2003 12:16PM 0603SA035 

UP TX KENEDY 8/20/2003 2:33AM 0803SA016 

UP TX LA SALLE 3/25/2004 11:30PM 0304SA033 

UP TX MEDINA 4/25/2004 12:10AM 0404SA030 

UP TX TARRANT 2/24/2003 2:05PM 0203FW018 

UP TX VAL VERDE 2/27/2002 12:08PM 0202SA023 

UP TX VAL VERDE 9/22/2004 3:48AM 0904SA028 

UP TX WHARTON 10/12/2002 5:26AM 1002HO010 

UP TX WHARTON 8/2/2004 6:35PM 0804HO002 

UP TX WILLIAMSON 9/22/2002 5:45PM 0902SA025 

UP TX WILLIAMSON 9/22/2002 5:45PM 0902SA025 

UP WA COWLITZ 9/4/2003 5:57PM 0903PD001 

UP WA COWLITZ 5/31/2004 3:30PM 0504PD030 

UP WA COWLITZ 5/31/2004 3:30PM 0504PD030 

UPME IL LAKE 4/4/2003 6:11PM 0403CM001 

WC IL DU PAGE 10/12/2003 11:55AM 200925 

44 
Appendix F: Useful Returns 

A “Useful Return” is defined as an incident report 

on which the CME or coroner has provided at 

least the gender of the decedent. 

Forms Useful 

ST Sent Returns Percentage

DC 4 4 100.0% 

NH 1 1 100.0% 

OK 20 20 100.0% 

OR 19 19 100.0% 

RI 3 3 100.0% 

UT 9 9 100.0% 

VA 19 19 100.0% 

MD 27 26 96.3% 

NC 57 52 91.2% 

NJ 46 40 87.0% 

MN 15 13 86.7% 

CT 7 6 85.7% 

MT 7 6 85.7% 

NV 11 9 81.8% 

AZ 41 33 80.5% 

IA 25 20 80.0% 

IL 84 66 78.6% 

CA 261 203 77.8% 

NM 28 21 75.0% 

GA 54 36 66.7% 

ND 3 2 66.7% 

WY 3 2 66.7% 

KY 17 11 64.7% 

WI 19 12 63.2% 

TN 30 18 60.0% 

FL 87 48 55.2% 

CO 11 6 54.5% 

NY 56 30 53.6% 

KS 15 8 53.3% 

OH 51 27 52.9% 

PA 55 29 52.7% 

ID 4 2 50.0% 

MO 24 12 50.0% 

SC 24 12 50.0% 

SD 4 2 50.0% 

IN 29 14 48.3% 

WA 45 19 42.2% 

LA 34 14 41.2% 

MI 17 7 41.2% 

NE 10 4 40.0% 

MS 18 5 27.8% 

TX 136 37 27.2% 

AL 19 5 26.3% 

AR 17 3 17.6% 

DE 8 0 0.0% 

MA 32 0 0.0% 

ME 3 0 0.0% 

WV 15 0 0.0% 

1,524 935 61.4% 

45 
Appendix G: Chi-Square Test of Racial Diversity Among Trespasser 

Decedents Compared to Racial Diversity in the U.S. Population 

Null Hypothesis (H0): The racial make-up of the 816 killed while trespassing is 

 the same as the Nation’s racial diversity. 

Alternate Hypothesis (Ha): The racial make-up of those killed while trespassing is 

 different from the Nation’s racial diversity. 

Native 

American Black White Asian Native Hawaiian Total 

Observed 37 129 638 12 0 816

Expected 7.794 109.094 665.615 32.242 1.255* 816.000

Population 2,475,956 34,658,190 211,460,626 10,242,998 398,835 259,236,605

(O-E)2/E 109.451 3.632 1.146 12.708 1.255 128.193

Native 

American 

and 

Hawaiian* 

Black White Asian See Note Total 

Observed 37 129 638 12 816

Expected 9.049 109.094 665.615 32.242 See Note 816.000

Population 2,874,791 34,658,190 211,460,626 10,242,998 259,236,605

(O-E)2/E 86.337 3.632 1.146 12.708 103.823

Note: A legitimate Chi-square test requires that groups with an expected level of occurrence 

of less than five be combined with another group, thus Native American and Native Hawaiian 

groups have been combined for this test. 

Χ2 = 103.823. With three degrees of freedom (number of groups minus one), the Null 

Hypothesis is to be rejected if Χ2 ≥ 16.266. In this instance, the Null Hypothesis is 

overwhelmingly rejected. 

The Alternate Hypothesis is to be accepted with better than 99.9 percent certainty, i.e., 

the racial make-up of trespassers killed is different than the Nation’s racial diversity. 

46 
Appendix H: CME/Coroner Entries—“Type of Incident” 

Category Entry 

Category Explanation Number of 

Entries 

Across Walking or Running Across Track(s) 62 

ATV ATV, Dirt Bike, Snowmobiles, etc. 18 

Bridge Involved a Bridge or Trestle 13 

Foul Play Foul Play suspected 4 

Other Insufficient information to categorize 128 

Outside Appeared to be walking or standing outside track gauge 20 

Riding Riding or getting on or off train 46 

Sleeping Sleeping, laying, reclining, lounging, sitting on track or in gauge 186 

Suicide CME or coroner used the word "suicide" or "intentional" in 

describing incident 167 

Probable Probable suicide, but not so indicated by CME or coroner 49 

Vehicle Involved a truck or automobile 24 

Walking Walking, Standing on Track 218 

Across Attempting to cross over track to other side 

Across Attempting to cross tracks 

Across Attempting to cross tracks ahead of train 

Across Attempting to cross tracks between cars and train moved. 

Across crawling under unmoving train when it started to move; severed in half at waist 

Across Crossed tracks between cars of stopped train; Hit by oncoming train - accident 

Across crossing R/R track 

Across Crossing railroad tracks 

Across Crossing RR track S of milepost 602 Struck by local SEPTA commuter 

Across Crossing the tracks (ped) 

Across Crossing the tracks (walking) 

Across Crossing track (walking) 

Across Crossing tracks 

Across Crossing tracks 

Across Crossing tracks - accident 

Across Crossing tracks as a shortcut. 

Across Crossing tracks between cars of slow moving train - accident 

Across Crossing tracks between train cars or was jumping off train car. 

Across Crossing tracks on foot 

Across Crossing Tracks To Get To Port-a-John 

Across Crossing tracks, stepped in front of west bound train while distracted by east bound train 

Across deceased was crossing tracks 

Across Decedent between two stationary box cars and jumped out in front of train 

Across Decedent was attempting to (walk) cross the railroad track and was struck by eastbound train 

Engineer saw subject exit a box car (part of a standing train) and started to cross track. Engineer 

blew horn, subject turned to look at train & froze - accident Across 

Across Fell or jumped IFO Train 

Across He was either going to work or leaving. Incident happened at his work site. 

Across Jumped from stopped train into path of moving train 

Across Jumped IFO train trying to get out of the way 

Ran across tracks in non-pedestrian section. Waited for one train (east B) to pass then struck by 

west bound train - accident Across 

Across Ran across tracks, unknown reason 

Across Running across railroad tracks 

Across Running across tracks 

47 
Category Entry 

Across Running Across Tracks 

Across Running across tracks 

Across Running across tracks 

Across Running across tracks - struck by train - acute alcoholism 

Across Running from police following a burglary report 

Across seen hobbling towards tracks, moving slowly; not fully on tracks when struck 

Across Stepped onto track 

Across Stepped onto track 

Across Struck by train trying to cross tracks IFO train 

Across Struck by train while attempting to cross tracks & get up onto platform/accident 

Across Trying to cross tracks 

Across Trying to cross tracks to get to CTA platform - accident 

Across Trying to pass between cars 

Across Victim walked in front of train paying no attention to train horn. 

Victim was crossing railroad track when his right foot struck the track rail, causing him to fall into path 

of moving train. Across 

Across walked across track - hearing loss 

Across Walked around lowered crossing gate. 

Walked around pedestrian gate after one train passed on south set of tracks then was struck when 

crossing next set of tracks - accident Across 

Across Walking - attempting to cross tracks 

Across Walking Across 

Across Walking across pedestrian walk - stopped as train was stopping. Accident 

Across walking across RR tracks - undetermined 

Across Walking Across Tracks 

Across Walking Across Tracks 

Across walking across tracks 

Across Walking across tracks - accident 

Across Walking across tracks. 

Across walking with friends across RR tracks - train too close 

Across was hit by 1 train while crossing and then 2nd train seen him lying on tracks (between rails) 

ATV Accident - on bike trying to beat the train 

ATV Bicycle stuck on tracks 

ATV Died on tracks due to motorcycle accident 

ATV Driver of ATV, lost control, riding along tracks 

ATV Fell off ATV onto tracks 

ATV fell off bike, laying on tracks 

ATV Found dead in middle of tracks with bike nearby. Last seen alive 1:30PM 7/2/02 

ATV he was driving a motorcycle that collided with a train 

ATV Jumping over track with ATV 

ATV Lying on track Fell off motorcycle 

Motor cycle (dirt bike) become stuck on track - was trying to remove his motorcycle and was struck 

s/b train ATV 

ATV Motorcyclist lost control, overturned, driver struck by train, accident 

ATV N/A this was a motorcycle accident - No train/RR involvement 

ATV Riding ATV 

ATV Riding ATV on RR tracks 

ATV Rode bicycle across tracks 

ATV Snowmobile hit by hi-speed train alongside tracks 

ATV Trying to remove stalled ATV from tracks 

Bridge Decedent was hearing impaired, attempted to move off trestle 

Bridge Fishing off railroad bridge 

Bridge Jumped from Dog Creek Trestle into Shasta Lake 

Bridge Knocked off train bridge by train and fell to interstate highway below 

Bridge Sitting on tracks/trestle 

48 
Category Entry 

Bridge Struck on bridge 

Bridge Struck on RR trestle 

Bridge walking across railroad bridge 

Bridge Walking on grated walkway between two sets of tracks on a R.R. bridge - accident 

Bridge Walking on railroad bridge 

Bridge Walking on train bridge Tried to outrun train & struck 

Bridge Walking on trestle and fell when train passed 

Bridge Went on train trestle to cross over Conasauga River 

Foul Play arguing with a man when he pushed her onto tracks 

Decedent was lying in a ‘funny’ position next to the track according to engineer. Decedent had 

received blunt injuries in unknown manner Foul Play 

Foul Play Decedent was stabbed by assailants and placed on tracks 

Foul Play Lying face down Foul play suspected 

Other (unknown) 

Other ABT 1⁄2 mile E/O Turner Avenue, Ontario, accident 

Other Accident 

Other accident 

Other accident 

Other accident 

Other accident 

Other accident 

Other accident 

Other accident 

Other accident 

Other accident 

Other accident 

Other accident 

Other accident 

Other Alzheimer’s 

Other Body lying in middle of tack when found. May have been struck by earlier train 

Other Body Lying on Track - may have been struck by earlier train 

Other collision with train—accident 

Other collision with train—accident 

Other Deaf, was struck by train 

Other disoriented Alzheimer’s patient 

Other don’t know 

Other fell under wheels of moving train, ran over, accident 

Other Found beside tracks w/extensive trauma. Un-witnessed event 

Other Found between tracks in the embankment. Undetermined 

Other Found laying on tracks 

Other Found laying on tracks 

Other Found on tracks after apparently being struck by a train 

Other Heart attack—body found on tracks 

Other Hit by a train. 

Other Hit by a train. 

Other Hit by freight train. 

Other Hit by train. 

Other Hit by train. 

Other Homeless person hit by train - accident 

Other Hypothermia. No evidence of traumatic injuries. Found next to railroad car 

Other impact with moving train—accident 

Other Intoxicated Fell downstairs in RR Yard 

Other Not hit by train - died of nat’l causes 

Other residence on RR ROW east of stated address 

49 
Category Entry 

Other run over by a train—accident 

Other Stepped off/fell from platform 

Other struck by a train 

Other Struck by a train. 

Other Struck by several trains before reported. 

Other struck by slow moving train, accident 

Other Struck by train 

Other Struck by train 

Other Struck by train while on tracks 

Other Struck by train while on tracks 

Other Struck by train while on tracks 

Other Struck by train while on tracks 

Other Struck by train. 

Other Struck by train. 

Other Struck by train. [... County] 

Other Struck by train. Found lying next to tracks. 

Other Subject was injured but survived and is still living in ... 

Other took drugs beside tracks 

Other train accident 

Other train vs. person 

Other train vs. person - found inside the rails of the main track 

Other Train was backing up and struck decedent. (Accidental) 

Other Transient in rail yard, found between rails 

Other uncertain what victim was doing on track 

Other Undetermined 

Other Undetermined manner of death 

Undetermined manner of death - Engineer reported sighting leg between rails; search located corpse 

and other parts that had been hit by train. Other 

Other Undetermined 

Other undetermined 

Other undetermined 

Other undetermined 

Other Undetermined, Could not be determined 

Other Unknown—found 

Other unknown 

Other unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other Unknown 

Other unknown 

Other unknown 

50 
Category Entry 

Other Unknown 

Other unknown 

Other Unknown 

Other Unknown - Body found by tracks w/extensive injury Unwitnessed event 

Other Unknown - Unwitnessed Event 

Other Unknown circumstances 

Other Unknown, possibly hit by an earlier train that went unnoticed until second train hit him. 

Other Unknown, possibly train watching 

Other Unknown. Found severed in half horizontally from the waist 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Other 

Outside (accident) walking outside ends of railroad ties 

Outside body found next to tracks—body in state of moderate decomposition 

Outside Found lying on west side of railroad tracks 

Outside Lying/Fell on outside of rail on Cross Ties 

Outside Playing with shopping cart/chain or rope, drug by train while entangled by chain/rope 

Outside Running beside train, fell under 84th car behind 3rd engine 

Outside Sitting on end of railroad ties 

Outside Sleeping next to tracks 

Outside Standing by rails & hit by part of projecting train 

Outside standing near tracks 

Outside standing next to rails of the track, struck by cattle guard 

Outside Standing next to the tracks (eastside) 

Outside struck by train while walking adjacent to tracks 

Outside Stumbling (intoxicated), hit side of train 

Outside Subject laying next to rail 

Outside Walking near rails, struck 

Outside Walking next to tracks on RR right of way - accident 

Outside Walking northbound on the ties just to the right of the rail 

Outside Walking on rail bed—struck by protruding board 

Outside Walking on the gravel track bed outside of the rails 

51 
Category Entry 

Probable Bending over on tracks looked up as train approached but did not move 

Probable deceased dove in front of oncoming train 

Probable Deceased had had an argument with ex-wife and sat on the railroad tracks and let train hit him. 

Probable deceased placed head on tracks in front of oncoming train 

Probable deceased ran in front of oncoming train 

Probable deceased stood on track in front of oncoming train 

Probable deceased walked into path of oncoming train 

Probable Deceased was sitting on tracks Waved to conductor before accident 

Probable Decedent did not attempt evasive action. She was struck crossing track and fell beneath the train 

Probable Decedent was seen to have jumped in front of train 

Probable Decedent was sitting on the track with arms folded. 

Probable Decedent was standing in the middle of the tracks, as the train horn sounded decedent turned his 

back and was struck from behind. 

Probable Dove under RR car 

Probable found DOA; thought to have laid his head on rail while train was stopped; head was crushed when 

train started to move 

Probable hunched over track so train would hit his head 

Probable in a crouched down position 

Probable Jogged toward tracks after horn sounded 

Probable Jumped in front of train 

Probable Jumped in front of main 

Probable Jumped in front of oncoming train 

Probable jumped in front of train 

Probable Jumped in front of train 

Probable Jumped in front of train 

Probable Jumped into path of train 

Probable Jumped onto the train tracks 

Probable Laid down IFO train 

Probable laying on the tracks holding a beer; did not move 

Probable Leaped onto tracks 

Probable Left Passenger Platform. Started walking down track in front of incoming train 

Probable Lunged into train 

Probable Placed self on train tracks 

Probable Ran in front of moving train 

Probable Running along the tracks and laid on the tracks 

Probable Sat on track facing train 

Probable seated on tracks, facing in, in the "Crash" position; never moved when train horn was blown 

Probable Standing facing train on tracks 

Probable Stepped in front of Acela (120 mph) 

Probable Stepped in front of high speed train at station 

Probable Stepped in front of train 

Probable Subject standing in the center of track - train vs. person 

Probable Walked in front of train & laid across tracks 

Probable Walked onto tracks and laid down on tracks 

Probable Walked onto tracks in front of train & turned back to train 

Probable walked out of bushes then walked in front of tracks/train 

Probable Walking along tracks, seen to lie down on tracks and put hands over head 

Probable walking near tracks, stepped onto tracks 

Probable Walking on tracks, stopped and waited for train to strike him. 

Probable Walking then stopped, stood on tracks and was hit head on by train. (Accident) 

Probable Walking, did not move out of way 

Riding Attempted to jump on train 

Riding Believe he fell from train w/sleeping bag 

Riding Climbing on train 

Riding Crawled under a stopped train. Foot got hung up on the tracks. Train started moving, rolling over 

52 
Category Entry 

decedent’s leg. 

Riding Falling from train/jumping onto 

Riding Fell from high-speed train 

Riding Fell from moving train, struck ground (rock surface), accident 

Riding Found alongside rails of a side track with rt. Leg amputated above the knee. Accident. No blood on 

track at site. Speculate may have tried to hop onto train or break into box car. 

Riding get on the train 

Riding getting on train 

Riding Jumped at train 

Riding Jumped on Train, Fell off when train crossed rough patch, Run over 

Riding Getting off train? 

Riding lost balance while walking on open, moving train "car" 

Riding riding atop a car, struck by low bridge 

Riding riding in car full of rebar, which shifted, crushing him 

Riding Riding in coal car. Car was dumped into pit. Body found when pit was cleaned. 

Riding Riding train, sleeping, fell off 

Riding sleeping/resting in train "car" 

Riding sleeping/resting in train "car" 

Riding sleeping/resting in train "car" 

Riding sleeping/resting in train "car" 

Riding sleeping/resting in train "car" 

Riding Smuggled immigrants 

Riding Smuggled immigrants found dead in railcar 

Riding Smuggled immigrants found dead in railcar 

Riding Smuggled immigrants found dead in railcar 

Riding Smuggled immigrants found dead in railcar 

Riding Smuggled immigrants found dead in railcar 

Riding Smuggled immigrants found dead in railcar 

Riding Smuggled immigrants found dead in railcar 

Riding Smuggled immigrants found dead in railcar 

Riding Smuggled immigrants found dead in railcar 

Riding Smuggled immigrants found dead in railcar 

Riding Struck while attempting to board moving train 

Riding Subject jumped from moving train, accident 

Riding Subject while grabbing onto moving train, tripped and was pulled under wheels. No reason to do so 

and was told to back away. 

Riding The decedent fell off of the train. 

Riding The decedent was jumping off of the train. 

Riding Tried to hop onto moving train 

Riding trying to either get on or off when hit 

Riding trying to get on train, slipped, severed in two at collar bone 

Riding Trying to jump onto a moving train 

Riding unsuccessfully attempted to board moving train 

Riding Vic. Fell either getting on or off train & struck his head 

Riding was trying to jump onto the train & ride it for a little ways 

Sleeping (undetermined) Sleeping on tracks 

Sleeping ?sleeping/passed out on tracks due to high alcohol level 

Sleeping Accident - lying near track 

Sleeping Accident - Seated between rails facing sideways - Train blew horn, victim moved forward as if to get 

off track, but was hit by trains 

Sleeping Accident - sleeping on catwalk 

Sleeping Accident (Sleeping on Tracks) 

Sleeping Address is a shelter—Lying on track. 

Sleeping Apparently sat down to rest, fell asleep or passed out with back to train 

Sleeping apparently sleeping 

53 
Category Entry 

Sleeping Appeared to be unconscious or sleeping on tracks. (Accidental) 

Sleeping Attempting to get up, off of tracks 

Sleeping deaf - lying unresponsive on tracks 

Sleeping deceased laid down across railroad tracks 

Sleeping Deceased laying on tracks 

Sleeping deceased sat down on train tracks 

Decedent and boyfriend had been consuming alcohol since early morning. They were sitting on 

railroad tracks arguing. Sleeping 

Sleeping Decedent lying face down between rails of main track. Decedent suffered from Alzheimer’s decease. 

Decedent purchased alcohol and carried it to railroad track. He appeared to be lying on the tracks 

non-responsive Sleeping 

Decedent was lying on tracks. Just as the train approached him he got up and tried to get off the 

track. Sleeping 

Sleeping decedent was seen sitting in the middle of tracks 

Decedent was sitting in middle of south railroad tracks. It appeared decedent tried to get up just 

before he was struck Sleeping 

Sleeping Decedent was sitting on the railroad tracks. 

Sleeping Either sitting or lying on tracks drinking 

Sleeping Found unresponsive lying on tracks. 

frequently walked on the tracks to a friend’s house, was laying on the tracks (believed to be) when 

this occurred - may have been sleeping Sleeping 

Sleeping Had fallen or was lying on the tracks 

Sleeping He was lying? Asleep on the tracks 

Sleeping intoxicated and passed out on tracks 

Sleeping Intoxicated Vic. Sitting on tracks could not move before train hit him 

Sleeping Kneeling or Sitting on tracks 

Sleeping Laid down on railroad tracks, was run over by a train. 

Sleeping Laid down on tracks 

Sleeping Laid head down on tracks 

Sleeping lay across tracks - struck by train - undetermined 

Sleeping Laid down on tracks while walking home 

Sleeping Laying across R/R tracks 

Sleeping Laying across tracks 

Sleeping laying across tracks - undetermined 

Sleeping Laying between tracks 

Sleeping Laying Down 

Sleeping Laying on his back across train tracks 

Sleeping Laying on side of tracks 

Sleeping Laying on tracks 

Sleeping Laying on tracks 

Sleeping Laying on tracks 

Sleeping Laying on tracks 

Sleeping laying on tracks 

Sleeping Laying on tracks - accident 

Sleeping Laying on tracks - accident 

Sleeping Laying on tracks (possibly sleeping) 

Sleeping Laying on tracks, possibly sleeping 

Sleeping Laying on tracks. (Accidental) 

Sleeping laying on tracks; didn’t move when horn was blown 

Sleeping Leaning with Back Against Track. Had Previously Been Struck By Train. 

Sleeping Lounging on train tracks 

Sleeping Lying across railroad tracks 

Sleeping lying across track 

Sleeping Lying across tracks 

Sleeping Lying across tracks when train struck him 

Sleeping Lying beside track w/head on rail, did not respond to horn 

54 
Category Entry 

Sleeping Lying between rails with head facing south. 

Sleeping Lying between the tracks. 

Sleeping Lying between the train track rails, when hit by train. 

Sleeping Lying Between Tracks 

Sleeping lying between tracks 

Sleeping Lying Between Tracks 

Lying between tracks for unknown reason - was conscious and looked up before being struck by 

train Sleeping 

Sleeping Lying down on tracks 

Sleeping Lying in reclined position with head on RR tracks 

Sleeping Lying on R/R tracks 

Sleeping Lying on Railroad Tracks 

Sleeping Lying on railroad tracks. 

Sleeping Lying on RR tracks 

Sleeping Lying on RR tracks 

Sleeping Lying on RR Tracks 

Sleeping Lying on the tracks 

Sleeping Lying on track 

Sleeping Lying on track 

Sleeping Lying on Tracks 

Sleeping Lying on tracks 

Sleeping Lying on tracks 

Sleeping lying on tracks 

Sleeping lying on tracks 

Sleeping Lying on tracks 

Sleeping Lying on tracks 

Sleeping Lying on tracks 

Sleeping Lying on Tracks 

Sleeping Lying on Tracks 

Sleeping Lying on Tracks 

Sleeping Lying on Tracks 

Sleeping Lying on Tracks 

Sleeping Lying on Tracks 

Sleeping Lying on tracks 

Sleeping Lying on tracks 

Sleeping Lying on tracks 

Sleeping Lying on tracks 

Sleeping Lying on tracks 

Sleeping Lying on tracks sleeping, escapee from mental hospital 

Sleeping Lying on tracks, attempted to get off, unable to get off quickly enough 

Sleeping Lying on tracks, not move in time 

Sleeping Lying on tracks, presumed asleep 

Sleeping Lying on tracks. 

Sleeping Lying on tracks. 

Sleeping Lying outside the tracks w/head on the rail 

Sleeping Lying w/head and arm on rail, did not respond to horn 

Sleeping observed lying across tracks 

Sleeping observed lying on tracks 

Sleeping Passed out/sleeping on side of tracks 

Sleeping Possibly passed out or sleeping 

Sleeping prostrate over tracks, never moved 

Sleeping Recumbent on track - Manner of death undetermined 

Sleeping Reported to be lying on tracks 

Sleeping Sat down on tracks while intoxicated 

55 
Category Entry 

Sleeping Seen attempting to move from a sitting position on tracks as train approached 

Sleeping seen lying across tracks 

Sleeping seen lying between rails in fetal position, back to the train when struck 

Sleeping Seen passed out on train track minutes prior death. 

Sleeping Seen sitting on R/R tracks @ impact 

Sleeping Seizure Fell Struck Head, Lying on tracks 

Sleeping Sitting/Lying on Tracks 

Sleeping Sitting along side tracks 

Sleeping sitting on edge of tracks 

Sleeping Sitting on or bending over tracks - undetermined 

Sleeping Sitting on Rail 

Sleeping Sitting on Railroad Tracks 

Sleeping Sitting on RR Tracks 

Sleeping Sitting on RR tracks drinking & was struck by a train. 

Sleeping Sitting on RR tracks with friends 

Sleeping Sitting on the rail 

Sleeping Sitting on the rail tracks with his feet to the inside. 

Sleeping Sitting on track 

Sleeping Sitting on track 

Sleeping Sitting on track 

Sleeping Sitting on track appeared to be asleep 

Sleeping Sitting on track, attempts to move 

Sleeping sitting on tracks 

Sleeping Sitting on tracks 

Sleeping sitting on tracks 

Sleeping Sitting on tracks 

Sleeping sitting on tracks 

Sleeping sitting on tracks 

Sleeping sitting on tracks 

Sleeping Sitting on Tracks 

Sleeping Sitting on Tracks 

Sleeping sitting on tracks 

Sleeping sitting on tracks 

Sleeping Sitting on tracks 

Sleeping Sitting on tracks 

Sleeping Sitting on tracks, intoxicated, listening to headphones 

Sleeping Sitting on tracks. (Accidental) 

Sleeping Sitting on tracks; playing game of "chicken" 

Sleeping sitting on tracks; started to get up when struck 

Sleeping sitting on train tracks 

Sleeping sleeping 

Sleeping sleeping 

Sleeping sleeping 

Sleeping sleeping 

Sleeping Sleeping between rails 

Sleeping Sleeping near RR Tracks 

Sleeping sleeping on/fall track 

Sleeping Sleeping on RR track, probably "stoned" from drugs. 

Sleeping Sleeping on track 

Sleeping sleeping on tracks 

Sleeping Sleeping on tracks 

Sleeping Sleeping on Tracks 

Sleeping Sleeping on tracks 

Sleeping Sleeping on tracks 

56 
Category Entry 

Sleeping Sleeping, drunk 

Sleeping Slept or passed out on tracks 

Sleeping Squatting on tracks talking to someone on other side of train 

Sleeping Struck by a train when he apparently laid down on railroad tracks 

Sleeping Struck by train while sitting on tracks 

Sleeping Struck commercial train while lying on the tracks. 

Sleeping subject laying on tracks, burglary tools found nearby 

Sleeping Subject lying on tracks for unknown reason 

Sleeping Subject sitting between tracks 

Sleeping Subject was laying on train tracks and failed to move as train approached. 

Sleeping The decedent fell asleep on the tracks. 

Sleeping The decedent was lying on the tracks. 

Sleeping Undetermined Manner of death - Laying on tracks, struck by train 

Sleeping Unknown, was said to be lying motionless on the center track 

Sleeping Unknown - ? Sleeping or passed out from alcohol use 

Sleeping Vic. Was sitting on train tracks & struck by oncoming train 

Sleeping Walking home after bar time. Sat cross legged on tracks to ?gaze at full moon! 

Sleeping was intoxicate and lying on tracks 

Was spray painting (tagging) by the tracks. Conductor saw decedent sitting on tracks, tried to get 

up, stumbled few times & hit by train Sleeping 

Suicide (Suicide) placed self in path of train 

Suicide (Suicide) Walking on tracks 

Suicide *Suicide* 

Appeared to deliberately get out of his car and lay on RR tracks in path of the oncoming train. 

(Suicide) Suicide 

Attempting to commit suicide The body was so badly destroyed, there were no body fluids to get 

toxicology on Suicide 

Suicide Bilateral double amputee crawled onto tracks from a wheelchair - suicide 

Suicide commit suicide 

Suicide committing suicide by being run over 

Suicide Crossed tracks from west side platform to eastside platform at train station. Coroner’s rpt - suicide 

Suicide Decedent laid on railroad track, struck by train, suicide 

Suicide Dove head first into the front of the train. (Suicide) 

Suicide Dove in front of train—suicide 

Suicide Engineer saw subject lying on track with head on rail. Area inaccessible to pedestrians. Suicide 

Suicide he jumped between 2 train cars; suicide 

Suicide he sat in front of an on-coming train; suicide 

Suicide head, lying on RR tracks - suicide 

Suicide Hiding behind a building, waiting for a train. Jumped out and laid across the tracks - Suicide 

Suicide hit by a train while standing on the tracks—suicide 

Suicide Intentionally jumped from viaduct onto tracks and struck by train 

Suicide intentionally laid head on RR tracks 

Suicide Intentionally laid self in path of oncoming train 

Suicide Intentionally lay down on tracks and run over by slow moving train 

Suicide intentionally laying on tracks 

Suicide intentionally moved into the path of the train 

Suicide intentionally placed head in path of train—suicide 

Suicide Intentionally stepped in front of moving train 

Suicide Intentionally stepped in front of moving train 

Suicide Investigation determined that this death was a suicide and coroner’s jury ruled it as a suicide 

Suicide Jumped in front of train - suicide 

Suicide Jumped in front of train—suicide 

Jumped in front of train from train platform and faced train - suicide - known schizophrenia past 

suicide attempts Suicide 

Suicide Jumped in front of a moving train—suicide 

57 
Category Entry 

Suicide Kneeling on tracks, suicide 

Suicide Laid down on tracks—found on tracks—suicide 

Suicide Laid on tracks - struck by train - train vs. person/suicide by train 

Suicide Laying across tracks—Suicide 

Suicide Laying on track - committed suicide 

Suicide Laying on tracks—Suicide 

Suicide Laying/Sitting on tracks - suicide 

Suicide Lying on r/r tracks - suicide 

Suicide lying on the tracks - suicide 

Suicide lying on the tracks - suicide 

Suicide Lying on tracks - suicide 

Suicide Lying on tracks - suicide 

Suicide Lying on tracks—suicide 

Suicide No other information - suicide 

Suicide Observed seated on tracks—did not attempt to move—suicide 

Suicide Pedestrian ignored oncoming train. Stuck by train. Suicide 

Suicide Pedestrian lay on railroad tracks and was stuck by a ... train, suicide 

Suicide Pedestrian lying between railroad tracks. Struck by train/Suicide 

Suicide Pedestrian sat on tracks and was hit by train, suicide 

Suicide Pedestrian struck by train—suicide 

Suicide Pedestrian struck by train—suicide 

Suicide Pedestrian struck by train, suicide 

Suicide Pedestrian struck by train, suicide 

Pedestrian struck by train. Decedent called his ex-wife and his mother stating he was going to kill 

himself Suicide 

Suicide Pedestrian vs. Train Suicide 

Suicide Put self on RR track for suicide 

Suicide Ran over by train - suicide 

Suicide Run over by train while laying on train track, suicide 

Suicide Schizophrenia—Suicide 

Suicide Sitting between rails - made not attempt to move - suicide 

Suicide Sitting on the tracks waiting for the train. Suicide 

Suicide sitting on tracks (suicide) 

Suicide Sitting on tracks drinking - Suicide 

Suicide Sitting on tracks. (Suicide) 

Suicide Standing in the middle of the tracks. Suicide 

Suicide stepped onto tracks, turned to train - train vs. person - suicide by train 

Suicide Stepping in front of train. He was struck and drug 1⁄2 miles. Suicide. 

Suicide Stood in front of train - suicide 

Suicide Struck by oncoming train after refusing to exit tracks. Listed as suicide. 

Suicide struck by train—suicide 

Suicide Subject dove into oncoming train—suicide 

Subject has a history of depression and made previous attempt to commit suicide - Coroner’s jury 

ruled his death a suicide Suicide 

Suicide Subject intentionally walked into the path of train 

Suicide Subject seen kneeling between tracks. Suicide 

Suicide Subject stepped in front of moving train, suicide 

Suicide Subject walked to location and laid across the tracks (suicide) 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

58 
Category Entry 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide 

Suicide Suicide - Emerged from bushes to stand on track in front of oncoming train. 

Suicide Suicide - Jumped from train-station platform into path of oncoming train 

Suicide Suicide - Jumped in front of oncoming train 

Suicide Suicide - Jumped in front of oncoming train 

Suicide Suicide - jumped in front of train 

Suicide Suicide—jumped in front of train 

Suicide Suicide - jumped in front of moving train 

Suicide Suicide - Laid down on tracks in front of oncoming train. 

Suicide Suicide - Laid down on tracks. 

Suicide Suicide - laid on rail tracks 

Suicide Suicide - laid on rail tracks 

Suicide Suicide - Laid on Track 

Suicide Suicide - Laying down on tracks 

Suicide Suicide—Lying on track bed 

Suicide Suicide - Lying on tracks, struck by train 

Suicide Suicide - Stepped in path of oncoming train 

Suicide Suicide - stood in front of oncoming train 

Suicide Suicide - Stood on Tracks 

Suicide Suicide - Stood on tracks in front of oncoming train. 

Suicide Suicide - Waling in middle of tracks despite horn 

Suicide Suicide - Walked on track toward oncoming train 

Suicide Suicide—walked on tracks 

Suicide Suicide - Walking on track in path of train 

Suicide Suicide (Faced train with hands up) 

Suicide Suicide (Note found at residence) 

Suicide Suicide (Sat on Train Tracks) 

Suicide Suicide/Lay on tracks 

Suicide Suicide by train 

59 
Category Entry 

Suicide Suicide, Laying on Tracks 

Suicide Suicide, sitting on tracks drinking beer 

Suicide Suicide, walked into oncoming train 

Suicide Suicide: Jumped in front of train 

Suicide Suicide: Stood in front of train 

Suicide Suicide: Walking on Tracks 

Suicide This was ruled a suicide 

Suicide threw self in front of train (Suicide) 

Suicide Trains backing up - suicide 

Suicide Unknown, perhaps a half-hearted attempt @ suicide 

Suicide Vic. Committed suicide by train 

Suicide Waling on tracks - suicidal 

Suicide Walked into oncoming train - suicide 

Suicide Walked into path of train—Suicide 

Suicide Walked on to tracks - suicide 

Suicide walked on to tracks - suicide 

Suicide Walked on to tracks, suicide 

Suicide Walked on tracks into oncoming train - suicide 

Suicide Walked onto tracks, suicide note left 

Suicide Walked up to track and laid down on track - intentional 

Suicide Walking—suicide 

Suicide Walking along tracks - suicide 

Suicide Walking in path of train, suicide 

Suicide Walking on RR Track; COD: Suicide 

Suicide Walking on track, suicide 

Suicide Walking on tracks - suicide 

Suicide Walking on Tracks (Suicide) 

Suicide Was committing suicide - Jumped in front of train Advised girlfriend of his intentions 

Vehicle Auto Crossing Tracks 

Vehicle Car accident. 

Vehicle Car was struck by train 

Vehicle crossing tracks driver’s door struck by train 

Vehicle Drive across railroad tracks, but front tire became stuck over track. 

Vehicle Driver of semi, pulled into path of train 

Vehicle Driver of Tractor Trailer went down embankment 

Vehicle Driver of vehicle that struck train 

Driving - Road dead ends into R/R embankment - driver crashed into embankment & landed on R/R 

tracks Vehicle 

Vehicle Driving vehicle 

Vehicle driving vehicle 

Vehicle Drove onto rails from dead-end street 

Vehicle Drove vehicle onto tracks and became stuck 

Vehicle Motor vehicle accident, vehicle struck RR property 

Vehicle Parked car on tracks, disoriented, standing next to car when struck 

Vehicle Parked on tracks. He had Alzheimer’s & dementia 

Vehicle Passenger in single vehicle rollover near train tracks 

Vehicle Passenger in vehicle 

Vehicle Passenger in vehicle lost control and flipped and came to rest on CSX train tracks 

Vehicle Solo SUV rollover onto railroad tracks, later struck by Union Pacific freight train, ejected, accident 

Solo SUV rollover onto railroad tracks, later struck by westbound Union Pacific freight train, occupant 

of SUV not ejected, accident Vehicle 

There were no signal lights or crossing guards at the tracks, only a stop sign. Decedent was 

traveling too fast to stop and was struck by the train, according to the report. Vehicle 

Vehicle vehicle attempted to cross under construction crossing 

Vehicle Vehicle turned east onto railroad rails into path of westbound train 

60 
Category Entry 

Walking "Staggering" on Tracks 

Walking (accident) walking 

Walking (accident) walking 

Walking Alzheimer Patient Walking along tracks to his nearby home 

Walking Alzheimer’s patient, wandered away from care facility. Struck by train. Unwitnessed event 

Walking Collecting aluminum cans along RoW, did not respond to horn 

Walking collecting recyclables 

Walking Deaf victim. Walking on tracks was hit be oncoming train 

Deceased and two other companions were ice fishing and apparently walking back to their vehicles 

Men were West bound on railroad tracks on the East side of R.R. tracks when deceased was struck 

by train 

Walking 

Walking deceased was standing on #2 track 

Walking deceased was walking on tracks 

Walking deceased was walking on tracks 

Decedent walking in the middle of the train track. He heard horn, turned facing train and attempted 

to exit track area Walking 

Walking Decedent walking on train track. He was hit from behind by the train 

Walking Decedent was struck by a train while standing on the tracks located on Main St in East Point 

Decedent was walking eastbound on north railroad track. Conductor honked horn, but decedent kept 

walking Walking 

Walking Downs Syndrome - Walked away from group home 

Walking fell on loose stone while walking dog 

Walking fell on tracks 

Had previous stroke. Possibly fell and unable to get up before being struck by train. Known to walk 

along tracks Walking 

Walking He was walking on tracks 

Walking Hit by train while stealing diesel fly wheels - accident 

Walking Jogging along tracks - reached up and grabbed high tension power wire 

Walking Jumping up & down on the tracks 

Walking Just walking along side of the RR track 

Walking Mad & running from boy friend, foot was trapped in tracks. 

On property to retrieve his ball. As he was walking up an incline he lost his balance and grabbed 

onto a railroad telegraph wire. Victim was wet because he had been swimming. Walking 

Walking On tracks 

Walking Pedestrian hit by train unknown circumstances 

Walking Pedestrian on train tracks struck by oncoming train. 

Walking Pedestrian on/around train tracks and struck by engine of train. 

Walking Pedestrian struck by CSX train 

Walking pedestrian struck by train 

Walking Pedestrian struck by train—accident 

Walking Pedestrian struck by train—accident 

Walking Pedestrian struck by train—accident 

Walking Pedestrian struck by train, accident 

Walking Pedestrian struck by train, accident 

Walking Pedestrian struck by train, accident 

Walking Pedestrian vs. train 

Walking Pedestrian vs. Train unknown circumstances 

Walking Pedestrian walking RR track and struck by train/accident 

Walking Pedestrian walking RR track, struck by train 

Walking Picking flowers near tracks, fell on tracks 

Walking Picking up aluminum cans 

Walking Playing chicken, seeing who could stand in front of train the longest. 

Walking Playing chicken, seeing who could stand in front of train the longest. 

Walking Playing on tracks 

Walking playing on tracks 

Walking Playing on tracks with other children 

61 
Category 

Walking 

Entry 

Walking Walking 

Walking Possibly walking dog along train tracks - accident 

Walking Reportedly chasing dog 

Running down middle of CSX track, attempting to outrun train. Pedestrian struck and overrun by 

train. Walking 

Walking sleep walking 

Walking Standing next to or on tracks at R.R. station - accident 

Walking standing on rails 

Walking standing on rails 

Walking Standing on tracks 

Walking Standing on tracks 

Walking Standing on tracks 

Standing on tracks, appeared to challenge on-coming train, then tried to jump clear before struck by 

train Walking 

Walking Stealing wires—electrocuted 

Walking Struck by ... train while walking on railroad tracks 

Walking Struck by train after wandering off playground 

Walking Struck by train while playing on the railroad tracks. 

Walking Struck by train while walking across RR tracks 

Walking Struck by train while walking near tracks 

Walking Struggling with dog on tracks trying to remove 

Walking Subject walking along tracks 

Walking Subject walking between RR Tracks in train yard - accident 

Walking subject walking on tracks, struck from behind by S.B. train 

Walking Subject was walking down track, struck by train 

Walking train—pedestrian accident 

Walking Train ran over body, walking along tracks 

Walking Train vs. ped. Collision 

Walking Train vs. pedestrian 

Walking train vs. pedestrian collision—accident 

Walking train vs. pedestrian collision, drowning 

Walking Train/Pedestrian Accident 

Walking train/pedestrian accident 

Walking Transient walking on tracks 

Walking Trying to remove friend from tracks 

Walking Trying to rescue dog, both dog and decedent struck 

Walking unknown - probably walking 

Walking Unknown - Was known to walk along tracks 

Walking Unknown why dec’d was on tracks, but he was trying to jump up to the platform. 

Walking Vic walking along tracks wearing headphones, hit by train 

Walking Vic walking in middle of tracks did not respond to horn & was struck 

Walking Vic was walking along tracks was hit by oncoming train 

Walking Vic. Was struck by train while walking along tracks. 

Walking Walked along tracks - walked into path of train 

Walking Walked in Front of the train 

Walking Walked in front of train 

Walking walked into tracks/possibly was collecting cans 

Walking walked on the elevated track when struck by train - accident 

Walking Walked on to tracks, alcoholism and hearing deficit 

Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

62 
Category Entry 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking 

Walking Walking - Alzheimer’s patient 

Walking Walking/passed out on tracks - accident 

Walking Walking/Standing on tracks 

Walking Walking along railroad tracks 

Walking walking along the tracks 

Walking walking along tracks 

Walking Walking along tracks 

Walking Walking along tracks 

Walking along tracks flipping off w/b train, then struck by e/b train. Apparently not hearing e/b 

coming because of w/b approaching. Horns were used. Walking 

Walking Walking along tracks struck from behind by CSX train 

Walking Walking along tracks with 2 others, all struck - 2 died, 1 injured 

Walking Walking along tracks with 2 others, all struck - 2 died, 1 injured 

Walking Walking along tracks, struck from behind, horn was blown 1⁄2 mile before impact 

Walking Walking along tracks, train stuck him & threw him in the air 

Walking Walking along tracks. 

Walking Walking and drinking (ETOH) on train tracks when he was struck by locomotive. 

Walking Walking beside track 

Walking Walking between railroad tracks 

Walking Walking between tracks 

Walking Walking down railroad track on cross ties 

Walking walking down tracks 

Walking Walking Down Tracks with Another Person 

Walking Walking Down Tracks with Another Person 

Walking Walking from a party 

Walking Walking from grocery to residence 

Walking Walking home along tracks 

Walking walking home from a bar 

Walking home from bar while intoxicated. The route decedent traveled was parallel to the RR tracks. 

It was the most direct route between the bar and his home (about 6 city blocks). It is also possible 

the decedent was depressed over a recent separation from girl friend. 

Walking 

Walking Walking in center of Tracks 

Walking Walking in Railroad Tracks 

Walking Walking Near Railroad Tracks 

Walking Walking on R/R tracks 

Walking Walking on R/R tracks 

Walking Walking on railroad track 

Walking Walking on railroad track 

63 
Category Entry 

Walking Walking on RR ties on west side of southbound tracks - accident 

Walking Walking on RR Track returning from a Store. 

Walking Walking on the tracks 

Walking Walking on the tracks 

Walking Walking on track 

Walking Walking on track 

Walking walking on track 

Walking Walking on track 

Walking Walking on track away from approaching train 

Walking Walking on track bed 

Walking Walking on track, struck by train Headphones, listening to music 

Walking on track. Heard train whistle. Friend left track, decedent stayed on. Faced train. Might 

have tried to jump last minute. Hit by train. Walking 

Walking walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking Walking on Tracks 

Walking Walking on Tracks 

Walking Walking on Tracks 

Walking Walking on Tracks 

Walking Walking on Tracks 

Walking Walking on Tracks 

Walking Walking on tracks 

Walking walking on tracks 

Walking Walking on tracks 

Walking Walking on tracks 

Walking walking on tracks 

Walking walking on tracks 

Walking Walking on tracks 

Walking walking on tracks 

Walking Walking on tracks 

Walking walking on tracks 

Walking Walking on tracks 

Walking on tracks in High Transient/Drug use area. Stooped to pick up an unknown item (2x) when 

struck. Train sounded horn. Walking 

Walking Walking on tracks wearing CD player—hit from behind 

Walking Walking on tracks with friend 

Walking Walking on tracks with friend 

Walking Walking on tracks, wearing walkman 

Walking Walking on tracks. (Undetermined) 

Walking Walking on tracks; probably passed out intoxicated - accident 

Walking Walking on train tracks 

Walking Walking on train tracks Struck by train 

Walking walking or laying on tracks 

64 
Category Entry 

Walking Walking or lying on tracks. 

Walking Walking to work 

Walking Walking toward the train 

Walking Walking with friends struck by CSX train 

Walking Walking/hunting on RR track. Deaf. 

Walking Wandered onto Tracks 

Walking Was resident of Maple Shades Care Home. Went out to smoke and walked onto tracks of oncoming 

train 

Walking Was walking on tracks, tried to jump off tracks but jacket got caught causing him to get killed 

Walking Were on a set of RR tracks throwing rocks at a train (westbound) & were struck by an oncoming 

eastbound Union Pacific train. 

Walking Were on a set of RR tracks throwing rocks at a train (westbound) & were struck by an oncoming 

eastbound Union Pacific train. 

65 
Appendix I: Railroads Reporting Suicides 

Railroad Confirmed Probable* 

ATK 45 10 

BNSF 31 9 

BNSO 2 0 

CSX 9 5 

FEC 0 1 

GTW 1 0 

IC 1 2 

LI 2 0 

NIRC 3 0 

NJTR 2 0 

NS 13 5 

PCMZ 5 3 

SCAX 1 0 

SDNX 5 2 

SOO 0 2 

UP 45 10 

UPME 2 0 

TOTAL 167 49 

Note: Per 49 CFR 225.15, railroads 

must report trespasser deaths unless 

"a coroner or other public authority" 

has declared the decedent a suicide. 

This may not have been the case for 

those incidents classified as 

Probable. 

66 
Appendix J: FRA Regional Numbers 

FRA Region* 

I II III IV V VI VII VIII Total

Forms 

Sent 148 179 306 164 235 85 322 85 1,524 

Useful 

Returns 54.1% 58.7% 61.1% 68.3% 40.4% 58.8% 78.9% 61.2% 61.4% 

Gender 

Male 65 94 165 102 81 38 222 44 811 

Female 15 11 22 10 14 12 32 8 124 

Useful Addresses 

At least 

Zip Code 29 92 159 106 80 35 197 45 743 

Ethnicity 

Hispanic 11 5 16 5 20 15 75 5 152 

Race 

Native 

American -- -- 1 2 9 -- 16 9 37 

Black 13 21 51 17 12 -- 14 1 129 

White 54 79 121 90 61 36 161 36 638 

Asian 2 1 -- 1 -- -- 8 -- 12 

Alcohol/Drugs 

Alcohol 34 48 107 55 54 19 109 27 453 

Drugs 22 18 27 23 13 6 62 2 173 

Both 13 11 19 14 6 4 29 -- 96 

Clean 25 40 47 35 20 25 66 16 274 

Activity** 

Across 3 4 15 8 14 1 15 2 62 

ATV 2 2 3 1 3 1 6 -- 18 

Bridge 1 1 5 2 -- -- 3 1 13 

Foul Play -- -- -- -- 4 -- -- -- 4 

Other 24 25 22 12 7 5 29 4 128 

Outside 1 1 5 2 1 -- 10 -- 20 

Probable 1 5 6 11 8 -- 16 2 49 

Riding -- -- 8 1 6 11 18 2 46 

Sleeping 3 21 56 24 26 6 37 13 186 

Suicide 17 14 16 27 11 12 62 8 167 

Vehicle 1 3 4 3 4 2 6 1 24 

Walking 27 29 53 21 11 12 52 13 218 

*Note: FRA Regions are defined on the next page. 

**Note: Category definitions are provided in Table 5. 

67 
Region I 

Connecticut

Maine 

Massachusetts 

New Hampshire 

New Jersey 

New York 

Rhode Island 

Vermont 

Region II 

Delaware 

Washington, 

D.C. 

Maryland 

Ohio 

Pennsylvania 

Virginia 

West Virginia

Region III 

Alabama 

Florida 

Georgia 

Region IV 

Illinois 

Indiana 

Michigan 

Kentucky Minnesota 

Mississippi Wisconsin

North 

Carolina 

South 

Carolina 

Tennessee 

Region V Region VI Region VII Region VIII 

Arkansas Colorado Arizona Alaska 

Louisiana Iowa California Idaho 

New Mexico Kansas Nevada Montana 

Oklahoma Missouri Utah North Dakota 

Texas Nebraska Hawaii South Dakota 

Oregon 

Washington 

Wyoming 

68 
Appendix K: Market Analysis Based on “Customer” Addresses 

The following is excerpted from the 94-page Community Tapestry Handbook (ESRI BIS 

– Environmental Systems Research Institute Business Information Systems, 2004). As 

one reads these excerpts and considers the instant application (establishing an outreach to 

potential trespassers), one should interpret “customers,” “preferred groups” and 

“prospects” to be those most likely to trespass on rail rights-of-way and thus most at risk, 

i.e., the “target group.” In this instance, addresses are those of the trespassers 

(“customers”) in our “customer” database who have died while trespassing. The 

“marketing approach” will be a public information program regarding the facts and 

hazards of trespassing with the intention of dissuading potential trespassers in the target 

group. 

For the past 30 years, companies, agencies, and organizations have used 

segmentation to divide and group their markets to more precisely target only 

their best customers and prospects. This targeting method is superior to using 

"scattershot" methods that might attract these preferred groups. Segmentation 

explains customer diversity, simplifies marketing campaigns, describes lifestyle 

and life stage, and incorporates a wide range of data. 

Segmentation systems operate on the theory that people with similar tastes, 

lifestyles, and behaviors seek others with the same tastes (hence the phrase, 

"like seeks like"). These behaviors can be measured, predicted, and targeted. 

The CommunityTM TapestryTM segmentation system combines the who of lifestyle 

demography with the where of local neighborhood geography to create a model 

of various lifestyle classifications or segments of actual neighborhoods with 

addresses – distinct behavioral market segments. 

... 

What is Tapestry? 

Tapestry represents the fourth generation of market segmentation systems that 

began 30 years ago. The 65-segment Tapestry system classifies U.S. 

neighborhoods based on their socioeconomic and demographic composition. 

The power of Tapestry allows you to profile consumers in a number of ways 

including 

... 

● Customer addresses or site locations. 

Tapestry’s versatility provides several methods of dividing the 65 segments into 

summary groups for a broader view of U.S. neighborhoods. 

● LifeMode: 12 summary groups based on lifestyle and life stage 

● Urbanization: 11 summary groups based on geographic and physical 

features along with income. 

... 

Tapestry’s 65 distinct market segments profile the diversity of the American 

population and also provide two ways to summarize and simplify these 

69 
differences – LifeMode summary groups and Urbanization summary groups. 

Segments within a LifeMode summary group share an experience, such as being 

born in the same time period, or a trait such as affluence. Urbanization 

summary groups share a locale, from the urban canyons of the largest cities to 

the rural lanes of villages or farms. 

Who Should Use Tapestry Segmentation? 

All companies, government agencies, and organizations need to understand 

their consumers/constituents to supply them with the right products and 

services and to reach them via their preferred media. 

... 

Customer Profiling 

A cornerstone of business success is a thorough knowledge of customers. All 

companies realize that this knowledge is key to developing effective marketing 

programs as they mine the information from their customer databases. ... A 

customer profile can reveal the demographics, lifestyles, and product 

preferences of a company’s customers. If a company knows who its customers 

are, it can respond to their needs with better messaging, products, and 

services. Address information in a customer database is necessary to begin the 

profiling process. 

... use ... segmentation and the creation of customer profiles when ... 

● Directing advertising with the right message to the right audience 

● Targeting direct mail and other promotions to the most responsive 

recipients 

A customer profile illuminates and helps define customer behaviors. The 

profile will pinpoint your core customer groups as well as groups with 

opportunity. ... use customer profiling to develop 

● Insight into the lifestyle characteristics of your best customers 

● A "picture" or map of where these customers live 

● Plans to target previously unserved neighborhoods and develop new 

opportunities 

● Strategies that attract customers to stores to purchase your products and 

services 

... targeted special offers to neighborhoods with a density of these potential 

customers. 

... media targeting programs. Knowing what your customers like to read, 

watch, and listen to is invaluable information. ... The following are some 

typical media targeting applications: 

● Rank media preferences. 

... 

70 
● Analyze and rank markets based on Tapestry segmentation profiles or 

demographics targeted by age, income, lifestyle preference, and lifestage. 

... 

By aligning communication channels with what the customer wants, companies 

can improve their direct mail and other marketing methods. ... Sending 

different messages to ... distinctly different audiences .... 

... the more information companies can learn about their customers, the better 

they can serve them, keep them, and find more like them. 

71 
Appendix L: Customer Demographic Profile 

 

File: H:\Projects\Cadle Creek\gEOCODE\MrktgAnaldb2_out.xls 

Number of Records: 763 

DEMOGRAPHIC CHARACTERISTICS 

Annual Compound Growth Rates

 2000-2006 2006-2011

 Population 1.2 1.2 

 Households 1.2 1.3 

 Families 0.9 1.0 

 Per Capita Income 4.0 3.6 

 Percent

2006 Population by Race/Ethnicity 

 White Alone 63.2% 

 Black Alone 16.1% 

 American Indian Alone 3.1% 

 Asian or Pacific Islander Alone 3.6%

 Some Other Race Alone 10.8% 

 Population of 2+ Races 3.2% 

 Hispanic Origin * 22.0% 

 Diversity Index ** 72.0 

2006 Population by Age

 0-4 7.3 

 5-14 13.7 

 15-19 7.5 

 20-24 8.0 

 25-44 29.6 

 45-64 23.3 

 65-84 9.2 

 85+ 1.5 

 Median Age 34.4 

 Age Dependency Index *** 46.4 

2000 Household Type 

 Nonfamily Households: 1-Person 25.9 

 Married-couple Families 48.1 

 Married-couple Fam. w/Own Children <18 

2000 Median Year Householder Move in 1995 

2000 % Population by Place of Birth: 

 Foreign Born 11.9 

2006 Average Household Size 2.70 

HOUSING CHARACTERISTICS 

 Percent

2000 Housing Units 

Urban 82.2 

 Rural 17.8 

2000 Specified Owner Occupied Housing Units 

 with a Mortgage 68.8 

2006 Housing Units 

 Owner-Occupied 57.8 

 Renter-Occupied 33.4 

2000 Housing Units by Units in Structure 

 

1 Unit - Detached 58.9 

 1 Unit - Attached 5.9 

 2-9 Units 15.2 

 10+ Units 10.6 

 Mobile and Other 9.4 

2000 Housing Units by Year Structure Built 

 Structure Built 1990 or Later 14.8 

 Structure Built 1989 or Earlier 85.2 

 Median Year Structure Built 1968 

 

2006 Owner Occupied Housing Units: 

 Median Home Value $158,065 

2000 Specified Renter Occupied Housing Units: 

 Median Contract Rent $455 

 23.1 

2000 Population 5+ by Residence in 1995: 

 Different House - Same County 26.5 

. Data Note: Detail may not sum to totals due to rounding. 

Source: U.S. Bureau of the Census, 2000 Census of Population and Housing. ESRI forecasts for 2006 and 2011. 

* Persons of Hispanic Origin may be of any race. 

** The Diversity Index summarizes racial and ethnic diversity. The index shows the likelihood that two persons, chosen at 

random from the same area, belong to different race or ethnic groups. 

*** The Age Dependency Index is the ratio of population age <15 plus age 65+ to the working age population age 15-64, times 100. 

NOTE: Page slightly reformatted to fit document layout: Copyright © 2006 ESRI Phone: (800) 292-2224

 Different County, State, or Country 22.1 

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Number of Records: 763 

SOCIOECONOMIC CHARACTERISTICS 

 Percent

 

2000 Pop 25+ by Educational Attainment 

 Less than High School Graduate 25.4 2006 Employed Civilian Pop 16+ High School Grad/Some College 56.6 

 Management 10.6 College Grad or More 18.0 

 Education Index * 73.7 Professional 17.6 

 Services 18.4 

2006 Household Income Sales/Related 11.1 <$15K 15.7 Office/Administrative Support 14.2 $15-24,999K 12.2 Farming/Fishing/Forestry 1.2 $25-34,999K 11.9 Construction/Extraction 7.8 $35-49,999K 15.7 Installation/Maintenance/Repair 4.0 $50-74,999K 19.2 Production 7.4 $75-99,999K 10.6 Transportation/Material Moving 7.7 $100-249,999K 13.1 Unemployment Rate 10.0 $250-499,999K 1.2 

 $500K+ 0.4 2000 Women in Labor Force 27.6 Median Household Income $44,349 2000 Women in Labor Force w/Children 2.0 

 Median Disposable Income $36,006 2000 Average Travel Time to Work (in minutes) 

 25.8 2000 Households w/Income < Poverty Level 15.3 

 2006 Median Net Worth $75,977 

Data Note: Income is expressed in current dollars. Detail may not sum to totals due to rounding. 

Source: U.S. Bureau of the Census, 2000 Census of Population and Housing. ESRI forecasts for 2006 and 2011. 

* The Education Index is the ratio of percent college graduates to the U.S. percent of college graduates, times 100. 

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Appendix M: Customer Tapestry Profile 

 

File: H:\Projects\Cadle Creek\gEOCODE\MrktgAnaldb2_out.xls 

Number of Records: 763 

By LifeMode Group

 Customers Penetration U.S. 

 Tapestry Description Number % Per 100 Number % Index

L8: Global Roots 92 12.4 0.00 9,442,681 8.3 150 

L11: Factories & Farms 89 12.0 0.00 10,950,099 9.6 125 

L9: Family Portrait 78 10.5 0.00 8,603,242 7.5 140 

L5: Senior Styles 71 9.6 0.00 14,231,658 12.5 77 

L2: Upscale Avenues 71 9.6 0.00 15,733,421 13.8 70 

L12: American Quilt 69 9.3 0.00 10,448,687 9.2 102 

L10: Traditional Living 65 8.8 0.00 10,086,731 8.8 99 

L1: High Society 59 8.0 0.00 14,253,275 12.5 64 

L3: Metropolis 49 6.6 0.00 6,110,287 5.4 124 

L7: High Hopes 42 5.7 0.00 4,710,105 4.1 137 

L4: Solo Acts 42 5.7 0.00 7,797,510 6.8 83 

L6: Scholars & Patriots 12 1.6 0.00 1,679,196 1.5 110 

Total 740 100.0 0.00 114,049,635 100.0 100 

Segment 66, Unclassified, is not included in the Summary Table. 

NOTE: Page slightly reformatted to fit document layout: Copyright © 2006 ESRI Phone: (800) 292-2224 

Pages 2-4 of the Customer Tapestry Profile by LifeMode Group have been withdrawn. They are identical to pages 

2-4 of the Customer Tapestry Profile by Urbanization Group which follows. 

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Number of Records: 763 

By Urbanization Group

 Customers Penetration U.S. 

 Tapestry Description Number % Per 100 Number % Index

U5: Urban Outskirts I 105 14.2 0.00 12,461,013 10.9 130 

U4: Metro Cities II 85 11.5 0.00 12,538,134 11.0 104 

U7: Suburban Periphery I 76 10.3 0.00 17,444,254 15.3 67 

U8: Suburban Periphery II 74 10.0 0.00 11,145,615 9.8 102 

U6: Urban Outskirts II 69 9.3 0.00 5,967,902 5.2 178 

U10: Rural I 65 8.8 0.00 12,662,714 11.1 79 

U3: Metro Cities I 55 7.4 0.00 12,929,151 11.3 66 

U1: Principal Urban Centers ! 55 7.4 0.00 9,007,266 7.9 94 

U2: Principal Urban Centers II 54 7.3 0.00 5,463,844 4.8 152 

U11: Rural II 52 7.0 0.00 8,882,378 7.8 90 

U9: Small Towns 49 6.6 0.00 5,544,621 4.9 136 

Total 740 100.0 0.00 114,049,635 100.0 100 

Segment 66, Unclassified, is not included in the Summary Table. 

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Number of Records: 763 

 Customers Penetration U.S. 

 Tapestry Description Number % Per 100 Number % Index

 53 Home Town 34 4.6 0.00 1,710,407 1.5 306 

 26 Midland Crowd 28 3.8 0.00 4,135,120 3.6 104 

 38 Industrious Urban Fringe 28 3.8 0.00 1,717,958 1.5 251 

 32 Rustbelt Traditions 25 3.4 0.00 3,276,608 2.9 118 

 48 Great Expectations 25 3.4 0.00 2,023,160 1.8 190 

 42 Southern Satellites 23 3.1 0.00 3,149,400 2.8 113 

 6 Sophisticated Squires 22 3.0 0.00 3,050,339 2.7 111 

 41 Crossroads 21 2.8 0.00 1,690,615 1.5 191 

 12 Up and Coming Families 21 2.8 0.00 3,656,024 3.2 89 

 59 Southwestern Families 20 2.7 0.00 1,093,848 1.0 282 

 62 Modest Income Homes 20 2.7 0.00 1,197,756 1.1 257 

 24 Main Street, USA 20 2.7 0.00 2,981,883 2.6 103 

 50 Heartland Communities 19 2.6 0.00 2,510,750 2.2 117 

 28 Aspiring Young Families 17 2.3 0.00 2,686,945 2.4 98 

 57 Simple Living 17 2.3 0.00 1,653,259 1.4 158 

 36 Old and Newcomers 16 2.2 0.00 2,251,955 2.0 110 

 52 Inner City Tenants 16 2.2 0.00 1,756,688 1.5 140 

 35 International Marketplace 16 2.2 0.00 1,505,776 1.3 164 

 25 Salt of the Earth 15 2.0 0.00 3,156,113 2.8 73 

 18 Cozy and Comfortable 15 2.0 0.00 3,233,637 2.8 71 

 56 Rural Bypasses 15 2.0 0.00 1,771,372 1.6 131 

 17 Green Acres 14 1.9 0.00 3,547,328 3.1 61 

 60 City Dimensions 14 1.9 0.00 1,016,814 0.9 212 

 64 City Commons 14 1.9 0.00 790,737 0.7 273 

 21 Urban Villages 14 1.9 0.00 893,159 0.8 242 

 13 In Style 13 1.8 0.00 2,829,431 2.5 71 

 46 Rooted Rural 12 1.6 0.00 2,798,799 2.5 66 

 23 Trendsetters 11 1.5 0.00 1,217,911 1.1 139 

 45 City Strivers 11 1.5 0.00 851,624 0.7 199 

 29 Rustbelt Retirees 11 1.5 0.00 2,409,449 2.1 70 

 3 Connoisseurs 11 1.5 0.00 1,594,248 1.4 106 

 34 Family Foundations 10 1.4 0.00 977,969 0.9 158 

 9 Urban Chic 10 1.4 0.00 1,528,609 1.3 101 

 58 NeWest Residents 10 1.4 0.00 1,032,563 0.9 149 

 33 Midlife Junction 10 1.4 0.00 2,850,271 2.5 54 

 16 Enterprising Professionals 9 1.2 0.00 1,907,082 1.7 73 

 19 Milk and Cookies 9 1.2 0.00 2,169,474 1.9 64 

 49 Senior Sun Seekers 9 1.2 0.00 1,343,256 1.2 103 

 31 Rural Resort Dwellers 8 1.1 0.00 1,824,153 1.6 68 

 7 Exurbanites 8 1.1 0.00 2,791,637 2.4 44 

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 Customers Penetration U.S.

 Tapestry Description Number % Per 100 Number % Index 

 2 Suburban Splendor 7 0.9 0.00 1,954,442 1.7 55 

 4 Boomburbs 7 0.9 0.00 2,461,404 2.2 44 

 10 Pleasant-ville 7 0.9 0.00 1,974,932 1.7 55 

 55 College Towns 7 0.9 0.00 921,179 0.8 117 

 54 Urban Rows 7 0.9 0.00 402,205 0.4 268 

 47 Las Casas 7 0.9 0.00 870,381 0.8 124 

 39 Young and Restless 6 0.8 0.00 1,628,063 1.4 57 

 8 Laptops and Lattes 6 0.8 0.00 1,163,283 1.0 79 

 65 Social Security Set 5 0.7 0.00 749,029 0.7 103 

 51 Metro City Edge 5 0.7 0.00 1,101,860 1.0 70 

 22 Metropolitans 5 0.7 0.00 1,353,601 1.2 57 

 30 Retirement Communities 3 0.4 0.00 1,701,199 1.5 27 

 5 Wealthy Seaboard Suburbs 3 0.4 0.00 1,604,831 1.4 29 

 63 Dorms to Diplomas 3 0.4 0.00 518,501 0.5 89 

 27 Metro Renters 3 0.4 0.00 1,536,298 1.3 30 

 14 Prosperous Empty Nesters 3 0.4 0.00 2,099,353 1.8 22 

 11 Pacific Heights 3 0.4 0.00 712,402 0.6 65 

 40 Military Proximity 2 0.3 0.00 239,516 0.2 129 

 15 Silver and Gold 2 0.3 0.00 1,063,028 0.9 29 

 37 Prairie Living 2 0.3 0.00 1,162,807 1.0 27 

 43 The Elders 2 0.3 0.00 702,335 0.6 44 

 44 Urban Melting Pot 1 0.1 0.00 775,196 0.7 20 

 66 Unclassified 1 0.1 0.04 2,743 0.0 5619 

 20 City Lights 1 0.1 0.00 1,203,241 1.1 13 

 1 Top Rung 1 0.1 0.00 796,374 0.7 19 

 61 High Rise Renters 0 0.0 0.00 767,305 0.7 0 

 Total 740 100.0 0.00 114,049,635 100.0 100 

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Number of Records: 763 

RankTapestry Description Customers U.S. Index

 1 53 Home Town 4.6% 1.5% 306 

 2 38 Industrious Urban Fringe 3.8% 1.5% 251 

 3 26 Midland Crowd 3.8% 3.6% 104 

 4 48 Great Expectations 3.4% 1.8% 190 

 5 32 Rustbelt Traditions 3.4% 2.9% 118 

 Subtotal 18.9% 11.3% 168 

 6 42 Southern Satellites 3.1% 2.8% 113 

 7 6 Sophisticated Squires 3.0% 2.7% 111 

 8 41 Crossroads 2.8% 1.5% 191 

 9 12 Up and Coming Families 2.8% 3.2% 89 

 10 59 Southwestern Families 2.7% 1.0% 282 

 Subtotal 14.5% 11.1% 130 

 11 62 Modest Income Homes 2.7% 1.1% 257 

 12 24 Main Street, USA 2.7% 2.6% 103 

 13 50 Heartland Communities 2.6% 2.2% 117 

 14 57 Simple Living 2.3% 1.4% 158 

 15 28 Aspiring Young Families 2.3% 2.4% 98 

 Subtotal 12.6% 9.7% 130 

 16 35 International Marketplace 2.2% 1.3% 164 

 17 52 Inner City Tenants 2.2% 1.5% 140 

 18 36 Old and Newcomers 2.2% 2.0% 110 

 19 56 Rural Bypasses 2.0% 1.6% 131 

 20 25 Salt of the Earth 2.0% 2.8% 73 

 Subtotal 10.5% 9.2% 115 

 Total 56.5% 41.2% 137 

Note: Segments with an index higher than 100 are listed in blue. 

Subtotals are shown for every 5 classifications. 

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