Demographic, biometric, and geographic comparison of clients of prostitutes and men in the US general population.

Author:Brewer, Devon D.
Position:Report
 
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Introduction

One of the first steps toward understanding the forces that underlie prostitution is to determine factors that differentiate men who patronize prostitutes from those who do not. Systematic research on this topic has involved three basic approaches: comparing convenience samples of clients with the general population, comparing clients of prostitute women who attend educational programs to discourage patronizing subsequent to their arrest or conviction for prostitution ("john schools") with men in the general population, and comparing clients who admit patronizing in surveys to those who do not. Each approach involves significant methodological problems that threaten the validity of results obtained from it.

Comparisons involving nonprobability samples of clients (Freund 1991), while useful for preliminary investigation, do not allow conclusions about clients' distinguishing characteristics to be made with confidence. Although clients arrested for patronizing seem to be representative of clients of street prostitutes overall (Brewer et al. 2006, Brewer et al. in press), comparisons involving john school attendees (Kennedy et al. 2004, Monto and McRee 2005) suffer from biased samples of arrested clients. John school participants included clients who were first-time patronizing arrestees, were offered and agreed to attend, and met other eligibility criteria (e.g., fluent in English). Such criteria inevitably lead to nonrepresentative samples of arrested clients. No more than 71% of arrested clients in Vancouver, Canada, participated in the city's john school during the period of one study (Kennedy et al. 2004). Moreover, comparisons of john school participants from selected US communities with men in the US general population (Monto and McRee 2005) introduce confounding when the general population in the studied communities differs from the nation as a whole.

In principle, comparisons of self-reported clients and non-clients in probability sample surveys (Brewer et al. 2000, Cameron and Collins 2003, Rissel et al. 2003, Ward et al. 2005) circumvent these problems. However, men substantially underreport patronizing in surveys (Turner et al. 1998, Des Jarlais et al. 1999, Brewer et al. 2000, Lau 2000, Lau et al. 2003, Rogers et al. 2005, van Griensven et al. 2006), and it is unknown whether client characteristics moderate reporting of patronizing behavior. Also, comparisons in which clients are defined as men who have ever patronized in their lifetimes (Sullivan and Simon 1998, Monto and McRee 2005, Traen et al. 2005) risk conflating cohort effects for correlates of patronizing. Such comparisons may also mistakenly identify time-varying characteristics (e.g., education, marital status, etc.) as correlates even though those characteristics may have changed between the time clients last patronized and the time they were interviewed.

In this paper, we compare clients arrested for patronizing prostitute women in several US metropolitan communities with men in the general population. These comparisons are based on temporally and geographically comparable men, and include characteristics not assessed in previous research. We also compare self-reported clients in a national probability sample survey with other men, and relate arrested and self-reported clients' distinguishing characteristics to survey data on sexual behavior. Furthermore, using data from Colorado Springs, we compare the characteristics of clients of street prostitutes to those clients who patronized prostitutes only in off-street settings.

Methods

Metropolitan areas studied

Our analyses are based on the same communities and arrest data sets as those we used for estimating client prevalence (Brewer et al. in press). In a national search for prostitution arrest records from local and state jurisdictions, we identified communities with arrest data suitable for comparison with general population data. The inclusion criteria were that the arrest records include data on: uniquely identified arrestees; prostitution arrests in law enforcement jurisdictions that comprise all or nearly all (>90%) of the prostitution arrests in the metropolitan area; arrests that have not been filtered by judicial processing (e.g., conviction or court appearance), as such procedures likely produce subsets of clients who differ in some ways from arrested clients overall; and arrestees' residential locations. Six communities met these criteria: Dallas County, TX; Harris and Galveston Counties, Texas (hereafter referred to as Houston/Galveston); Indianapolis, Indiana; Kansas City, Missouri; Portland, Oregon; and Yakima, Washington. Clients were defined on the basis of patronizing-specific prostitution charges or spatiotemporal criteria that were designed to identify men caught in stings (sets of many men arrested on prostitution charges in close spatiotemporal proximity) for data sets lacking patronizing-specific prostitution charges (Brewer et al. in press). We validated the latter criteria in data sets with both types of information (patronizing-specific charges and spatiotemporal details of arrests).

Most arrests in these communities occurred in stings with female police officers working as decoys. There is little a client can do to detect a decoy or avoid arrest once a negotiation for a sex act and price has been completed; similarly, police exercise very little discretion or control over which clients are ultimately arrested. According to vice detectives we talked with in several jurisdictions (including some not included in the present analysis), arresting agencies used many different female officers as decoys at any one time and these officers served in this role for relatively short periods (generally 1-2 years) before rotating out of the duty. Decoys' general appearance was made to resemble that of prostitute women working in the community at that time. Stings were conducted in areas with high numbers of visible street prostitutes and complaints about prostitution (Baker 2004, Brewer et al. in press). Consequently, arrested clients approximate a representative sample of clients of street prostitute women in a community, weighted by frequency of patronizing activity.

We defined metropolitan areas by the counties that included the arresting jurisdictions (Dallas County, Texas; Harris and Galveston Counties, Texas; Marion County, Indiana; Jackson County, Missouri [Kansas City extends over 4 counties, but all arrests by Kansas City police were within Jackson County]; Multnomah County, Oregon; Yakima County, Washington). We classified arrestees as residents of these counties based on geocoding of their residential addresses with ArcMap 8.3 (Environmental Research Systems Institute, Inc.) and spatial merging with 2000 Census county boundary shape files. Across data sets, 97-100% of arrests had geocodable arrestee residential addresses and most arrested clients were local residents of the counties studied (55-85%).

For most comparisons, we used arrest data from Census years and years adjacent. Specifically, these periods were 1998-2002 for Dallas and Houston/Galveston, 1989-91 and 1999-2001 for Indianapolis, 2000 for Kansas City, 1989-91 and 1999-2001 for Portland, and 1988-92 for Yakima. For most comparisons, we included only those adult (age >= 18) clients who resided in the counties listed previously. In those few cases where a client had been arrested multiple times in the period (Brewer et al. in press), we used data from his first arrest only.

General population data

We compared clients with the general population in the 1990 and 2000 Censuses (http://factfinder.census.gov/) for each of the corresponding counties in terms of demographic and geographic characteristics (age, race/Hispanic ethnicity, education, marital status, and distance between residence and arrest location). For Dallas, Houston/Galveston, and Portland, we compared arrested clients' biometric characteristics (height, weight, and body mass index [BMI]) with data from the National Health and Nutrition Examination Surveys (NHANES III, 1988-94, and NHANES 1999-2002) (Ogden et al. 2004). The NHANES are based on complex, stratified, multistage cluster samples of the noninstitutionalized U.S. population, and the summary data are stratified by sex, age, and race/Hispanic ethnicity. We compared arrested Portland clients' vehicle characteristics (age and type) with those reported by householders residing in the 8-county Portland-Salem Consolidated Metropolitan Statistical Area (CMSA) who participated in the 2001 National Household Travel Survey (NHTS) and the 1990 and 1995 Nationwide Personal Transportation Surveys (NPTS) (http://npts.ornl.gov/). These cross-sectional, random digit dial telephone surveys are based on nationally representative samples of households with telephones and at least one adult member who spoke English or Spanish. For these comparisons, we included Portland clients who resided in the CMSA. Client arrest data were drawn from the period extending from 12 months before the beginning of the transportation survey data collection to 12 months after the survey data collection had ended. (Survey data collection periods ranged from 12 to 15 months.) See the Appendix for details on coding procedures for specific variables.

General Social Survey data

We compared the demographics (age, race, education, and marital status) of self-acknowledged clients and other male respondents in the 1988-2002 General Social Survey (GSS) (http://sda.berkeley.edu/archive.htm), a regular national household probability sample survey of US households (Davis and Smith 1994)...

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