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Social Differentiation in Criminal Victimization: A Test of Routine Activities/Lifestyle Theories Author(syf 7 H U D Q F H ' 0 L H W K H 0 D U N & 6 W D I I R U G D Q G - 6 F R W W / R Q g Source: American Sociological Review , Vol. 52, No. 2 (Apr., 1987yf S S 4 Published by: American Sociological Association Stable URL: http://www.jstor.org/stable/2095447 Accessed: 05-09-2016 16:53 UTC JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at http://about.jstor.org/terms American Sociological Association, Sage Publications, Inc. are collaborating with JSTOR to digitize, preserve and extend access to American Sociological Review This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms SOCIAL DIFFERENTIATION IN CRIMINAL VICTIMIZATION: A TEST OF ROUTINE ACTIVITIES/LIFESTYLE THEORIES* TERANCE D. MIETHE MARK C. STAFFORD Virginia Polytechnic Institute J. SCOTT LONG and State University Washington State University Recent theories posit that social differentiation in the risks of criminal victimization is due to variation in routine activities/lifestyles which place some persons or their property in proximity to motivated offenders. For a sample of 107,678 residents in thirteen U.S. cities, measures of the nature and quantity of routine activities outside the home (major daytime activity, frequency of nighttime activityyf D U H L Q W U R G X F H G W R D V V H V s the mediational effects of these variables on the demographic correlates of victimization. Routine activities/lifestyle variables have relatively strong direct and mediational effects on individuals' risks of property victimization but not for violent victimization. These findings are discussed in terms of their implications for further research on the relationship between demographic variables, routine activities! lifestyles, and criminal victimization. Major changes in work and leisure activities, lifestyles, and mobility patterns have occurred in the United States in the last few decades. Since the early 1960s, rates of out-of-home travel, college attendance and labor force participation of women (especially married womenyf D Q G V L Q J O H S H U V R Q K R X V H K R O G V K D Y e increased considerably (Cohen and Felson 1979, p. 598yf 7 K R X J K P R V W R I W K H V H F K D Q J H V K D Y e improved the quality of social life, Cohen and Felson (1979yf D U J X H W K D W W K H G L V S H U V L R Q R f activity away from the household and new manufacturing technologies (e.g., decreases in the size and weight of durable consumer goodsyf correspond to temporal changes in rates of criminal victimization. The basic premise of this "routine activity" approach is that structural changes in activity patterns influence crime rates by affecting the convergence in time and space of three necessary elements for criminal victim- ization: (1yf P R W L Y D W H G R I I H Q G H U V \f suitable targets, and (3yf D E V H Q F H R I F D S D E O H J X D U G L D Q V . Although all three elements are important for direct-contact predatory violations, changes in * Direct all correspondence to Terance D. Miethe, Department of Sociology, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061. The data for this study were made available by the Inter-University Consortium for Political and Social Research. The data were originally collected by the National Institute of Justice. Neither the original collectors of the data nor the consortium bear any responsibility for the analyses or interpretations presented here. The authors would like to thank Michael Hughes, Paul Whiteley, and two anonymous ASR reviewers for helpful comments on an earlier draft of this manuscript. We also appreciate the support provided by the Center for Advanced Study in the Behavioral Sciences and by the John D. and Catherine T. MacArthur Foundation. target suitability and guardianship can affect crime rates even if offender motivation remains constant (Cohen and Felson, 1979, p. 589yf . Hindelang, Gottfredson, and Garofalo (1978yf propose a similar theory about the interrelation- ship between activity patterns and criminal victimization. According to their "lifestyle/ex- posure" approach, demographic characteristics (e.g., age, gender, income, marital statusyf D U e associated with various role expectations, which, in turn, lead to differences in lifestyles, exposure to risk, and subsequently to differ- ences in the likelihood of victimization (Hin- delang et al. 1978, p. 243yf + R Z H Y H U V L Q F e both theories presume that differences in routine activities or lifestyles mediate the demographic correlates of victimization, they are treated here as complementary approaches (see also Messner and Tardiff 1985yf . These theories have been used in recent years to explain both the temporal and social distribu- tion of victimization. For instance, Cohen and Felson (1979yf V K R Z W K D W W K H G L V S H U V L R Q R f activities away from the home is positively related to temporal variation in official rates of nonnegligent homicide, forcible rape, aggra- vated assault, robbery, and burglary. Similarly, Hindelang and his associates (Hindelang et al. 1978; Hindelang 1976yf U H S R U W W K D W K L J K H r victimization rates for males, the young, the unmarried, low-income persons, and racial/ ethnic minorities are consistent with the life- style/exposure theory because these groups have higher exposure to the risks of victimization. Routine activities/lifestyle approaches have also been used to explain the social ecology of criminal homicide (Messner and Tardiff 1985yf and differences in individuals' risks of residen- tial burglary, assault, and personal larceny 184 American Sociological Review, 1987, Vol. 52 (April:184-194yf This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms ROUTINE ACTIVITIES/LIFESTYLE AND VICTIMIZATION 185 victimization (Clarke et al. 1985; Cohen and Cantor 1981, 1980; Cohen, Kluegel, and Land 1981yf . PROBLEMS WITH PREVIOUS TESTS While variation in individual and aggregate rates of victimization is commonly attributed to differences in routine activities/lifestyles, previ- ous applications of these theories are limited in several respects. The major problems with previous tests of the theories involve the operationalization of key concepts, the lack of independent measures of lifestyle characteris- tics, and the failure to address whether variation in routine activities/lifestyles can mediate and explain the level of social differentiation in the likelihood of criminal victimization. Routine activities and lifestyles have been defined as "recurrent and prevalent activities (especially formalized work, provision of food and shelter, and leisure activitiesyf Z K L F K S U R Y L G e for basic population and individual needs" (Cohen and Felson 1979, p. 593yf + H Q F H , routine activities may occur at home or away from home, although the primary activity examined in most previous studies is the amount of time spent outside the home with nonhouse- hold members (see Cohen and Felson 1979yf . Given this definition of routine activities/ lifestyles, individuals who spend more time away from home should have higher risks of victimization because of their greater suitability as a target (i.e., greater visibility and accessibil- ityyf D Q G G H F U H D V H G J X D U G L D Q V K L S + R Z H Y H U a major problem with previous indicators of lifestyle and nonhousehold activities (see Cohen et al. 1981; Cohen and Felson 1979yf L V W K D W V X F h measures fail to consider that many activities outside the home decrease target suitability and increase guardianship for some types of crime. For example, in the case of violent crime against persons, employment outside the home and school activities typically involve a physical environment that reduces a potential victim's visibility and accessibility and enhances guard- ianship through coworkers and classmates. Similarly, standard measures of nonhousehold activity usually do not consider whether activi- ties outside the home occur during the day or night (cf. Clarke et al. 1985yf < H W I R U E R W h violent and property victimization, nighttime activity outside the home should be far riskier than similar daytime activity because of fewer potential guardians at night (see also, Hindelang et al. 1978yf 7 K H J H Q H U D O S R L Q W L V W K D W P H D V X U L Q g routine activities only in terms of the total amount of time persons spend away from home is problematic unless adjustments are made for persons "exposure to risk" by considering the nature and temporal patterning of these activities (see also Clarke et al. 1985; Stafford and Galle 1984yf . A related problem with previous tests is the lack of independent measures of routine activi- ties/lifestyles. In fact, most tests of the theories have examined only the demographic correlates of victimization and its temporal/spatial loca- tion, presuming that variation in routine activi- ties or lifestyles must be the underlying cause of differential rates of victimization (Messner and Tardiff 1985; Cohen and Cantor 1980; Hin- delang et al. 1978; Hindelang 1976yf + R Z H Y H U , while various demographic characteristics should be associated with target suitability, lack of guardianship, proximity to crime, role expecta- tions and routine activities/lifestyles, an ade- quate test requires the development of indepen- dent measures of lifestyles and nonhousehold activities (e.g., amount of time spent outside the home, frequency of nighttime activity outside the homeyf : L W K R X W V H S D U D W H P H D V X U H V R f lifestyle and nonhousehold activity, it is impos- sible to determine whether some individuals have higher victimization rates because of their lifestyles, their physical proximity to a high crime neighborhood, or some combination of factors. In addition to addressing these issues, the present study also examines several fundamental questions that have been neglected in previous applications. First, to what extent do differences in routine activities/lifestyles mediate the effects of demographic variables on individuals' risk of criminal victimization? Second, is variation in the risk of victimization due to differences in routine activities/lifestyles uniform across vari- ous demographic groups? Third, do differences in routine activities/lifestyles and demographic differences among individuals provide a satisfac- tory explanation for the likelihood of criminal victimization? Fourth, are routine activity/life- style theories equally applicable to violent and property victimization? HYPOTHESES If social differentiation in the risk of victimiza- tion is explained by differences in routine activities/lifestyles, the introduction of measures of routine activities outside the home should mediate the impact of the demographic corre- lates of victimization. However, there are two distinct kinds of mediational or conditional effects. First, the mediational hypothesis under- lying our interpretation of routine activity/life- style theories would be supported if the direct effects of the various demographic variables are substantially reduced after controls are intro- duced for measures of activities outside the home. Second, the mediational hypothesis would be supported if there are substantial This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms 186 AMERICAN SOCIOLOGICAL REVIEW interactive effects between the demographic variables and measures of routine activities/ lifestyles. Either of these outcomes would suggest that differences in the nature and quantity of nonhousehold activity contribute to the level of social differentiation in individuals' risk of criminal victimization. Though previously applied to both types of crime, there are several reasons why routine activity/lifestyle variables might exhibit stronger direct and mediational effects on the risk of property victimization than violent victimiza- tion. First, violent crimes against persons are often expressive (i.e., spontaneous, impulsiveyf rather than instrumental acts (e.g., directed toward an economic endyf + H Q F H L I P R W L Y D W H d offenders engage in a conscious selection of suitable targets who lack guardianship, the spontaneous nature of most violent crimes is incongruent with the strictly rational character- ization of human behavior underlying routine activity/lifestyle theories. Second, in contrast to most property offenses, violent crimes involve a direct confrontation between victims and offend- ers (see Luckenbill 1975yf ' L I I H U H Q F H V L Q U R X W L Q e activities/lifestyles may predispose some individ- uals to riskier places, but violent victimization is probably more dependent upon the specific interpersonal and situational dynamics in a particular social setting than on simple physical exposure to a risky situation. Given these differences, general measures of routine activi- ties/lifestyle should be more predictive of the differential risk of property victimization than violent victimization. METHODS The data used in this study were collected as part of the 1975 National Crime Survey (NCSyf for thirteen major U.S. cities.2 All individuals in roughly ten thousand households in each city were interviewed about their victimization experiences. The present analysis is restricted to those households (about 50 percent in each cityyf in which an attitude survey was also adminis- tered to each member of the household. The attitude survey elicited information about the characteristics of the household, opinions about crime, and how often respondents went out for entertainment at night and their major activity during the previous week. Excluding respon- dents who had missing information on any of the variables, the data include the victimization experiences, demographic characteristics, and major activities of 107,678 persons in 56,789 households. While more recent NCS data are available, none of the other surveys include measures of the nature and quantity of activities outside the home. Moreover, the selection of the 1975 city subsample is advantageous because supplemental data are available for a compara- ble time period on the amount of time individuals spend away from home during an average week in one of the thirteen cities (Chicagoyf 3 Variables The dependent (endogenousyf Y D U L D E O H V D U e whether or not a respondent was a victim of a violent crime and whether or not a property victimization was reported by the head of the household during 1974, that is, the year preceding the survey. Violent crimes included attempted and completed acts of assault, rob- bery, and personal larceny. Property crimes included attempted and completed burglary, household larceny, and motor vehicle theft.4 Only about 5 percent of the respondents were 1 The tendency for violent crimes to be mainly expressive acts and property crimes to be more instrumental is well documented. For further discussions of the differences between violent and property victim- ization, see Cohen et al. (1981yf + L Q G H O D Q J \f, and Repetto (1974yf . 2 The data are actually a combination of two separate NCS samples: (1yf D V D P S O H R I K R X V H K R O G V L Q W K H I L Y e largest U.S. cities and (2yf D V D P S O H R I K R X V H K R O G V L Q H L J K t impact cities. The five largest cities are New York, Philadelphia, Chicago, Detroit, and Los Angeles. The eight impact cities are Newark (N.J.yf 6 W / R X L V , Cleveland, Dallas, Atlanta, Baltimore, Denver, and Portland (Oregonyf 7 R J H W K H U W K H V H W K L U W H H Q F L W L H V F R Y H r all major geographical regions in the United States. 3These supplemental data were originally collected by Walter R. Gove and Omer R. Galle. For an extensive discussion of this sample, see Gove and Hughes (1983yf . 4 Several additional comments about the coding of the dependent variables are necessary. First, separate analy- ses were also performed on each major violent and property crime-i.e., assaults, robberies, and personal larcenies (street theftsyf Y H U V X V U H V L G H Q W L D O O D U F H Q L H s (including burglary and household theftyf D Q G P R W R r vehicle thefts, respectively. While several of the demographic correlates varied somewhat by type of violent or property crime, the crime-specific results were consistent with those based on the aggregate analysis. Specifically, no mediational effects were observed for any of the violent crimes, whereas our activity/lifestyle measures mediated the demographic correlates of each type of property victimization. Although the aggregate models are presented here without loss of generality, the crime-specific analyses are available from Terance D. Miethe upon request. Second, the units of analysis are individuals and heads of households for the analysis of the risks of violent and property victimization, respec- tively. Since most of the property crimes included here are offenses against the household but each member of the household may have reported being victimized, only data on the head of the household are examined in the case of property victimization to reduce the possibility of multiple reporting. This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms ROUTINE ACTIVITIES/LIFESTYLE AND VICTIMIZATION 187 victims of a violent crime, but 23 percent of the households experienced a property victimization (see Table 1yf . The demographic variables include family income, gender, race, marital status, and age of each respondent or the head of the household in the case of property victimization. Each of these variables is dummy coded. Income was parti- tioned near the median family income of the sample (greater or less than $10,000yf 5 D F H Z D s coded to compare whites and blacks, with other racial groups excluded. Marital status was collapsed to compare married and unmarried persons. This dummy variable for marital status is also highly related to household density since few married persons live alone. Consequently, marital status serves as a proxy measure for the availability of capable guardians (see Hindelang et al. 1978yf ) L Q D O O \ D J H R I W K H Y L F W L P Z D s dichotomized to compare persons greater or less than thirty years old.5 The variables posited to mediate the impact of demographic attributes on the likelihood of victimization are measures of the quantity and nature of routine activities outside the home. Given that victimization occurs disproportion- ately at night (see Clarke et al. 1985; Messner and Tardiff 1985; Hindelang et al. 1978yf W K e frequency of nighttime entertainment (NIGHT ACTIVITYyf Z D V W K H E H V W D Y D L O D E O H P H D V X U H R I a nonhousehold activity that should increase exposure to risk. As shown in Table 1, this variable was dichotomized to compare persons who go out for entertainment at night less or more than once a week. The second routine activity/lifestyle variable (MAJOR ACTIVITYyf compares persons whose major daily activity is performed outside the home (i.e., work, schoolyf with persons whose primary activity occurs within or near the home (i.e., unemployed, retired, homemaker, unable to workyf . While other measures of routine activities/ lifestyles have been used in previous studies (see Cohen et al. 1981; Cohen and Felson 1979yf R X r measures of the nature and quantity of activity outside the home are justifiable on several grounds. First, both work and school activity (in contrast to other activity statusesyf D U H S D W W H U Q H d and recurrent activities. Persons leave for and return from work and school at approximately the same time every weekday, making these activities quite predictable from the perspective of motivated offenders. Second, if exposure to risk is determined by the amount of time spent outside the home, our measure of the type of major daily activity is a strong predictor of the quantity of nonhousehold activity. Specifically, analysis of the supplemental data from a sample of Chicago residents (N= 1,680yf V K R Z H G W K D W 3 percent of the variation in the total amount of time persons spend outside the home in an average week was explained solely by our dummy variable, which compares employed persons and students with all other daily activity statuses. These findings suggest that our mea- sure of daily activity status is a reasonable indicator of the relative exposure to risk due to the amount of nonhousehold activity. Third, since only 16 percent of the variation in major activity status in the NCS sample was explained by demographic characteristics, our measure of major daily activity is also fairly distinct from the individual's demographic profile. Finally, given that nighttime activity is generally consid- ered riskier than comparable daytime activity, our measure of the frequency of nighttime activity taps another dimension of relative exposure to risk and is only moderately correlated with major activity status (r=.251yf . Thus, although a definitive test of routine activities/lifestyle theories may require detailed data on the precise nature of time utilization (data that are not presently availableyf R X r measures of routine activities/lifestyles nonethe- less reflect the quantity of activity outside the home, the nature of that activity, and its relative risk. ANALYSIS AND RESULTS Given dichotomous dependent variables, a series of logit models was estimated to predict the likelihood of violent and property victimiza- tion. Specifically, three hierarchical loglinear models were estimated for each type of victimization in order to assess the mediational effects of activity/lifestyle variables: (1yf D P R G H l including only the direct effects of the demo- graphic variables (Mlyf \f a model in which the direct effects of both routine activity/lifestyle variables are added (M2yf D Q G \f an extension of model 2 that includes all two-way interactions among each activity/lifestyle variable and each 5 Alternative coding schemes were also examined for several of the demographic variables. For example, three categories of age (<30, 30-64, 65 and olderyf D Q G I D P L O y income (<$10,000, $10,000-$25,000, >$25,000yf Z H U e used to asseses the degree of nonlinearity and problems with dichotomizing these variables. Consistent with other research (e.g., Cohen et al. 1981; Cohen and Cantor 1981; 1980yf W K H U H Z D V D W H Q G H Q F \ I R U W K H R O G H U D J H J U R X S D Q d the highest income group to have slightly lower risks of violent victimization than the respective middle catego- ries, whereas the highest-income group had slightly greater risks of property victimization than the middle-income group. Thus, while collapsing the medium and high cat- egories slightly attenuates the direct effects of these vari- ables, the magnitude of bias and its impact on the overall results are minimal. The use of the dichotomous coding of these variables preserved a sufficient number of cases in each cell and, consequently, minimized problems with small (i.e., zeroyf F H O O I U H T X H Q F L H V . This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms 188 AMERICAN SOCIOLOGICAL REVIEW Table 1. Variables, Coding, and Summary Measures Proportion Variable Code VVICT PVICT Endogenous variables Victimization 0 no .947 .770 1 yes .053 .230 Exogenous variables Family income of victim 0 >$10,000 .504 .430 (INCOMEyf 0 Gender of victim 0 female .556 .353 (GENDERyf P D O H 7 Race of victim 0 white .684 .686 (RACEyf E O D F N 4 Marital status of victim 0 married .541 .510 (MARITAL STATUSyf X Q P D U U L H G 0 Age of victim 0 >30 years .642 .762 (AGEyf \ H D U V 8 Frequency of nighttime activity 0 <1 night/week .605 .638 (NIGHT ACTIVITYyf Q L J K W Z H H N 2 Major daily activity 0 other .404 .356 (MAJOR ACTIVITYyf H P S O R \ H G V F K R R O 4 VVICT denotes violent victimization and PVICT property victimization. The sample proportions reported in the table are based on 107,678 individuals and 56,789 heads of households for the analysis of violent and property victimization, respectively. bThe category unmarried includes persons who are single, separated, divorced, or widowed. c Other major daily activities include homemaking, unemployed, unable to work, and retired. demographic variable (M3yf 7 K H S D U D P H W H r estimates and the likelihood ratio chi-square test of the fit of the models (LRX2yf I R U H D F K W \ S H R f victimization are presented in Tables 2 and 3. Risk of Violent Victimization Consistent with other studies on the correlates of violent victimization (e.g., Cohen et al. 1981; Cohen and Felson 1979; Hindelang et al. 1978; Hindelang 1976yf 0 R G H O U H Y H D O V W K D W W K H R G G s of violent victimization are higher among males, low-income persons, the unmarried, and the young (Table 2yf 7 K H U H Z D V Q R V L J Q L I L F D Q W G L U H F t effect of race on the odds of violent victimiza- tion. However, this model, which contains only the main effects of demographic variables, does not adequately represent the observed data. Model 2, which includes routine activity/life- style variables, improved the fit over Model 1 (LRX2MI-M2=28.98, d.f.=2, p < .001yf E X t did not change the effects of the demographic variables. In fact, the odds of violent victimiza- tion for each social group remained quite stable across each model. However, persons who spend relatively more time engaged in nighttime activity, ceteris paribus, have higher odds of violent victimization than less active persons, but there was no significant difference based on the type of major daily activity. Several significant interactions were observed when all two-way interactions among each demographic and routine activity/lifestyle vari- able were included in the model of violent victimization (Model 3yf ) L U V W W K H H I I H F W R f nighttime activity was greater among whites than blacks and greater among males than females. Second, differential risk by the type of major daily activities was greater among blacks, the unmarried, and young persons than among their counterparts. However, a comparison of Models 2 and 3 reveals that the inclusion of the joint effects of demographic and lifestyle variables did not significantly improve the overall fit of the model (LRX2M3-M2 = 9.00, d.f. = 10, p > .10yf 7 K X V E R W K L Q W H U P V R f reducing the direct effect of the demographic variables and the lack of strong interactive effects, there is little support for the mediational role of routine activity/lifestyle variables on the 6 The general practice in logliner analysis of searching for the best fitting model (through successively testing modifications of the saturated model by imposing one or more constraintsyf Z D V Q R W I R O O R Z H G K H U H E H F D X V H R I W K e nature of the research questions. Specifically, our primary concern was to evaluate the extent to which measures of activities/lifestyles mediate the demographic correlates of victimization. This research question requires only an estimation of three models which successively introduce controls for the direct effects of activity/lifestyle variables and two-way interactions among the activity and demographic variables. Nonethe- less, alternative models including higher-order interaction terms were also investigated. However, while this search revealed several significant higher-order interactions, the best fitting and most parsimonious model is the final model (M3yf U H S R U W H G L Q 7 D E O H V D Q G 7 K H J H Q H U D l inability to find a model that statistically fits the observed data is primarily due to the large sample sizes in this study. Under identical relative frequencies, a significant fit would be observed in the final models of violent victimization and property victimization if the sample was reduced to ten thousand observations. This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms ROUTINE ACTIVITIES/LIFESTYLE AND VICTIMIZATION 189 Table 2. Effects of Demographic and Activity/Lifestyle Variables on the Odds of Violent Victimization MI: Demographic M2: Activity M3: Interaction Effects Effects Added Effects Added Independent Variable Effecta (Ain x2yf ( I I H F W $ L Q [ \f Effect (Ain x2yf RACE .94 NSb .97 NS _C GENDER 2.17*** 2.14*** - INCOME 1.19*** 1.22*** - MARITAL STATUS 1.57*** 1.51*** - AGE 2.32*** 2.21*** - NIGHT ACTIVITY 1.26*** - MAJOR ACTIVITY .95 NS - Interactions with NIGHT ACTIVITY RACE 95*** GENDER 1.04*** INCOME 1.01 NS MARITAL STATUS 1.02 NS AGE 1.02 NS Interactions with MAJOR ACTIVITY RACE .95** GENDER .99 NS INCOME .99 NS MARITAL STATUS .94*** AGE 94*** LRX2 356.87 298.92 208.89 d.f. 122 120 110 Prob 0.00 0.00 0.00 a Effects are from dependent variable model estimated with ANOVA-like constraints. The coefficients given for Models 1 and 2 can be interpreted as how that characteristic (as opposed to not having that characteristicyf F K D Q J H V W K H R G G V R I Y L F W L P L ] D W L R Q ) R U H [ D P S O H X Q G H U 0 R G H O E H L Q J E O D F N D s opposed to white changes the odds of victimization by a factor of .94. The interaction effects in Model 3 can be interpreted similarly. For example, having high nighttime activity (as opposed to low nighttime activityyf G H F U H D V H V W K H H I I H F W R I E H L Q J E O D F N D V R S S R V H G W R Z K L W H E \ D I D F W R U R I L H , the value of NIGHT ACTIVITY with RACEyf . b"NS" means that change in x2 value is nonsignificant. c The parameter estimates and significance tests for the "main effects" are excluded in Model 3 because these effects are nonestimable functions (see Long 1984yf . *** = p<.OOl; ** = p<.Ol; * = p<.O5. demographic correlates of violent victimization. Moreover, the direct effects of the activity/life- style variables are also relatively small in comparison to the demographic attributes (see Model 2yf . Risk of Property Victimization Consistent with previous research on the corre- lates of property victimization (e.g., Cohen et al. 1981; Cohen and Cantor 1981; Hindelang 1976yf 0 R G H O U H Y H D O V W K D W W K H R G G V R I S U R S H U W y victimization are higher, ceteris paribus, in households headed by persons who are male, black, unmarried, young, and have relatively high income (Table 3yf : K L O H D O O G H P R J U D S K L c variables had significant effects on the risk of property victimization, this model fits poorly with the observed data. Inclusion of measures of routine activities/ lifestyle in the estimated model yielded several results consistent with expectations (see Model 2yf ) L U V W E R W K D F W L Y L W \ Y D U L D E O H V K D G V L J Q L I L F D Q t effects on the odds of property victimization, with those who had higher nighttime activity and those whose major activity was performed outside the home having relatively greater risks. Second, the overall fit of the model of property victimization was substantially improved when the activity variables were included (LRX2M2- M1= 169.9, d.f.=2, p < .0001yf 7 K L U G W K e net effects of several demographic variables were reduced in magnitude and significance when the routine activity/lifestyle variables were included. For example, after controlling for the higher rates of nighttime and nonhousehold major activity among males, gender differences in the likelihood of property victimization are eliminated. Similarly, income and age differ- ences dissipate somewhat once controls are introduced for higher rates of nighttime and nonhousehold activity among younger persons and lower rates of participation in these activities among lower-income persons. While not significantly improving the fit over Model 2, Model 3 shows several significant interactions among the demographic and activ- ity/lifestyle variables. Specifically, differential This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms 190 AMERICAN SOCIOLOGICAL REVIEW Table 3. Effects of Demographic and Activity/Lifestyle Variables on the Odds of Property Victimization MI: Demographic M2: Activity M3: Interaction Effects Effects Added Effects Added Independent Variable Effecta (Ain x2yf ( I I H F W $ L Q [ \f Effect (Ain x2yf RACE 1.08***b 1.12*** _C GENDER 1.12*** 1.03 NS - INCOME .71*** .83*** - MARITAL STATUS 1.64*** 1.56*** - AGE 2.11*** 1.87*** - NIGHT ACTIVITY 1.29*** - MAJOR ACTIVITY 1.37*** - Interactions with NIGHT ACTIVITY RACE .96** GENDER 1.01 NS INCOME 1.02 NS MARITAL STATUS 1.02 NS AGE .99 NS Interactions with MAJOR ACTIVITY RACE .99 NS GENDER .99 NS INCOME 1.00 NS MARITAL STATUS 1.08*** AGE .89*** LRX2 704.80 365.03 227.25 d.f. 122 120 110 Prob 0.00 0.00 0.00 Note: See notes to Table 2. risk of property victimization on the basis of the frequency of nighttime entertainment was greater among whites than blacks, whereas the effect of the location of daily activities was greater among the unmarried and older persons than among married and younger persons, respec- tively. Thus, coupled with the results of Model 2, differences in routine activities/lifestyle have notable direct effects and condition the impact of several demographic variables on the likeli- hood of property victimization. Activity-Specific Risk of Victimization To further examine the conditional effects of routine activity/lifestyle differences, activity- specific odds of victimization were computed for each demographic group. These activity- specific odds were computed from the table of expected values under Model 3 (our best-fitting modelyf 6 S H F L I L F D O O \ I R U H D F K L Q G H S H Q G H Q t variable, the table of expected values was collapsed over all other variables except the activity variables and the demographic variable in question. For example, the activity-specific odds of victimization for each racial group were found by collapsing the expected frequencies over all other demographic variables except race and computing the odds of victimization within each activity configuration (i.e., all combina- tions of MAJOR ACTIVITY and NIGHT ACTIVITYyf $ V L P L O D U S U R F H G X U H Z D V X V H G W o compute the odds of victimization for all other demographic groups. These predicted activity- specific odds for each type of victimization are presented in Table 4.7 As shown in the top panel of Table 4, there are several trends when activity-specific odds of violent victimization are compared within and 7 These activity-specific odds are averaged over the independent variables that have been collapsed. For example, the odds of victimization are higher for black males than black females, but these within-race differ- ences are lost when the odds of victimization for blacks are reported. Though collapsing over cells results in a loss of information, these average odds are used in Table 4 to simplify the discussion. However, the activity- specific odds of victimization were also examined separately for each of the thirty-two combinations of demographic variables (25yf : K L O H W K H D F W L Y L W \ V S H F L I L c odds differed in magnitude for each demographic configuration, the relative patterning of the results (i.e., in terms of identifying the activity configurations with the greatest and least riskyf Z H U H O D U J H O \ F R Q V L V W H Q W Z L W K W K R V e presented here. The expected odds of victimization by activity status for each of the thirty-two demographic configurations are available from Terance D. Miethe upon request. This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms ROUTINE ACTIVITIES/LIFESTYLE AND VICTIMIZATION 191 Table 4. Predicted Odds of Violent and Property Victimization for Each Demographic Group by Activity Status IN/LOWa IN/HIGH OUT/LOW OUT/HIGH Demographic Group Odds (Ratioyf E 2 G G V 5 D W L R \f Odds (Ratioyf 2 G G V 5 D W L R \f Violent victimization BLACK .050 .099 .048 .075 (1.52yf \f (1.00yf \f WHITE .033 .061 .048 .083 MALE .058 .125 .059 .104 (1.81yf \f (1.69yf \f FEMALE .032 .042 .035 .051 LOW INCOME .043 .087 .054 .100 (1.48yf \f (1.26yf \f HIGH INCOME .029 .054 .043 .071 UNMARRIED .053 .113 .058 .100 (1.89yf \f (1.41yf \f MARRIED .028 .035 .041 .056 YOUNG .077 .123 .074 .108 (2.57yf \f (2.06yf \f OLD .030 .034 .036 .046 Property victimization BLACK .249 .397 .330 .444 (1.37yf \f (1.20yf \f WHITE .182 .305 .274 .446 MALE .187 .315 .267 .410 (.84yf \f (.72yf \f FEMALE .223 .354 .370 .553 LOW INCOME .205 .335 .303 .494 (.92yf \f (1.06yf \f HIGH INCOME .224 .321 .287 .416 UNMARRIED .222 .369 .385 .583 (1.23yf \f (1.57yf \f MARRIED .180 .270 .246 .321 YOUNG .481 .607 .436 .604 (2.78yf \f (1.70yf \f OLD .173 .230 .257 .344 IN and OUT refer to major daily activities that are performed in or near the home and outside the home, respectively. The coding for this variable is identical to MAJOR ACTIVITY (see Table 1yf / 2 : D Q G + , * + U H I H U W R W K H I U H T X H Q F \ R I Q L J K W W L P H D F W L Y L W \ D Q G W K H F R G L Q J I R U W K H V H F D W H J R U L H V L s identical to the variable NIGHT ACTIVITY. bThe odds and the ratio of the odds were derived from the expected cell frequencies under Model 3 for both violent and property victimization. Odds refers to the odds of victimization for each group (see text for discussion of how these odds were computedyf 5 D W L R U H I H U V W R W K H U D W L R R I W K e odds of victimization for each demographic pair. For example, the value of 1.52 in the first column is found by taking the average odds of victimization for blacks in the IN/LOW category (.050yf D Q G G L Y L G L Q J W K L V E \ W K H D Y H U D J H R G G V I R U Z K L W H V L Q W K L V D F W L Y L W \ F D W H J R U \ \f. across categories of demographic variables. First, for nearly all demographic groups (except blacks and younger personsyf S H U V R Q V Z K R K D d relatively low nighttime activity and whose major activity occurred within the home had the lowest risk of violent victimization. However, among the highest-risk category, there was far more variation due to the type of daily activity across demographic groups. Specifically, in combination with high nighttime activity, major daily activity in or near the home is associated with the greatest risk of violent victimization among blacks, males, the unmarried, and the young, whereas daily activity outside the home combined with high nighttime activity has the greatest risk for other groups. Second, the odds of violent victimization are relatively constant across activity statuses for females and both age groups but vary considerably by activity catego- ries for the other demographic groups. Finally, for all demographic pairs (e.g., blacks versus whites, males versus femalesyf V R F L D O G L I I H U H Q W L - ation in the risk of victimization is greatest among persons whose major daytime activity occurs near the home and who have relatively high nighttime activity. For instance, within this This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms 192 AMERICAN SOCIOLOGICAL REVIEW activity configuration, the predicted odds of violent victimization are at least three times higher among males, the unmarried, and the young than among their counterparts. There are also several trends in the activity- specific odds of property victimization for each demographic group. (Table 4yf ) L U V W Z L W K R Q e exception (young personsyf S H U V R Q V Z L W K O R w daytime and nighttime activity outside the home have the lowest risk of property victimization, whereas persons whose daytime and nighttime activity places them outside the home are predicted to have the greatest risks. Second, there is less variation in the expected likelihood of property victimization by activity status in households headed by persons who are either black, married, young, older, or have higher income than in other social groups. Third, the activity configurations that exhibit the most social differentiation in the risk of property victimization vary considerably across demo- graphic groups. For example, blacks have greater risks than whites within most activity categories, but there are no racial differences among persons with high levels of both daytime and nighttime activity outside the home. In contrast, households headed by women or unmarried persons have higher risks than their counterparts across activity categories, but differences by gender and marital status are most pronounced in households in which the head's major daily activity occurs outside the home regardless of the frequency of nighttime activity. DISCUSSION Social differentiation in the likelihood of victimization is commonly attributed to differ- ences in routine activities/lifestyles that place suitable targets who lack guardianship in proximity to motivated offenders. In this study, routine activities/lifestyles are conceptualized as daytime and nighttime activities which contrib- ute to greater exposure to the risk of victimiza- tion. A person's exposure to risk is assumed to be a function of the nature and quantity of activities outside the home. Consequently, persons who are employed or in school should have greater exposure to risk because these activities involve significantly more time outside the home, more physical exposure to other persons, and more patterned and predictable behavior than other daily activities. Given that nighttime activity is usually considered riskier than comparable daytime activity (see Messner and Tardiff 1985; Hindelang et al. 1978yf W K e frequency of nighttime activity outside the home is considered a lifestyle characteristic that is also associated with greater exposure to risk. Our results are consistent with predictions about the direct and mediational effects of routine activi- ty/lifestyle variables for the risk of property victimization but not for violent victimization. There are several possible explanations for the poorer performance of routine activity/lifestyle variables in explaining violent victimization. First, given that acts of interpersonal violence commonly occur near the home and are committed by persons who are related or other primary group members (e.g., friends, cowork- ersyf R X U D J J U H J D W H P H D V X U H R I Y L R O H Q W Y L F W L P L ] D - tion may have suppressed the impact of activity/lifestyle variables. However, separate analyses for persons victimized by strangers and nonstrangers, as well as the location of victimization (near home or away from homeyf , yielded results similar to those presented above. Alternatively, problems with the validity of our measures of activities/lifestyles can also be dismissed because these measures exhibited the expected direct and mediational effects on the likelihood of property victimization. A more reasonable interpretation of the results has to do with the nature of most violent victimizations. Specifically, as mentioned ear- lier, many violent crimes are expressive acts (spontaneous, impulsiveyf Z K L F K G H I \ W K H U D - tional characterization of criminal motivation underlying routine activity/lifestyle approaches. Similarly, violent crimes are relatively infre- quent acts and involve a direct confrontation between victims and offenders. It is this spontaneous and situational nature of violent crimes that may account for the poor perfor- mance of routine activity/lifestyle theories. If so, it is also unlikely that more refined measures of routine activities and situational data on the context of victimization would improve our ability to explain this type of victimization. While more predictive of property than violent victimization, current versions of routine activity/lifestyle theories are also incapable of explaining why the risk of victimization is stable across activity categories for some social groups but varied for other (Table 4yf ) R U L Q V W D Q F H Z K y are the predicted odds of violent victimization fairly uniform across activity statuses for females, younger and older persons, but vary considerbly across levels of activity outside the home for whites, low-income persons, and high-income persons? Similarly, how would a routine activity/lifestyle approach explain the relative stability of property victimization across activity statuses for households in which the head is black, high-income, married, young or old, whereas there is notable variation across levels of activity outside the home among other groups of persons? As these findings suggest, routine activity/lifestyle approaches may only be appropriate for explaining the likelihood of property victimization, and, even for these This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms ROUTINE ACTIVITIES/LIFESTYLE AND VICTIMIZATION 193 crimes, differences in routine activities/lifestyles that affect target suitability, guardianship, and exposure to motivated offenders may not be able to account for the relative risk of victimization for all subsets of persons. CONCLUSIONS Several changes in the opportunity structure and activity patterns in the United States have taken place in recent years. As noted by Cohen and Felson (1979, p. 598yf W K H U H K D Y H E H H Q P D M R r increases in out-of-home travel, single-person households, college attendance and labor force participation among women (especially married womenyf D Q G W K H S H U F H Q W R I K R X V H K R O G V O H I t unattended during the day. The market for durable consumer goods (e.g., televisions, stereos/radios, tape recordersyf K D V L Q F U H D V H d because of changes in the age structure and the rise in single-person households. The portability of these products (through decreasing size and weightyf K D V D O V R L Q F U H D V H G V L Q F H W K H H D U O \ s (Cohen and Felson 1979, p. 599yf $ E D V L c premise underlying routine activities/lifestyle theories is that these changes in activity patterns increase target suitability and decrease guardian- ship, and therefore affect the social and temporal distribution of victimization. How- ever, four major issues surrounding routine activities/lifestyle theories of victimization war- rant further investigation. First, greater theoretical attention needs to be devoted to the relative weight and importance of the three major components of routine activity/ lifestyle theories (target suitability, capable guardianship, motivated offendersyf $ V R X r results indicate, persons who may be more suitable as targets and generally lack guardian- ship are not necessarily those who are more likely to be victimized by property or violent crimes. For instance, based on target suitability alone, some demographic groups should be at high risk because they are more physically visible and accessible due to greater activity outside the home (males, unmarried or young personsyf R U D U H P R U H Y D O X D E O H D V W D U J H W V H J , older and high-income persons who have more valuable propertyyf < H W V R P H R I W K H V H J U R X S s (e.g. males, young personsyf Z R X O G E H O H V s suitable targets even if they were more visible and frequented riskier places because of their presumed greater physical ability to resist an attack and serve as their own guardians. If capable guardianship is the major determi- nant of victimization, persons who are currently unmarried should be especially vulnerable. Older persons and those with higher income should also be at greater risk because of the inability to serve as their own guardian (due either to less physical strength or greater activity outside the home, which should make their household property more vulnerableyf , Q F R Q - trast, if the principle of homogamy (Cohen et al. 1981yf D Q G H [ S R V X U H W R P R W L Y D W H G R I I H Q G H U V D U e the more important predictors of victimization, persons who are young, male, lower-income, or racial/ethnic minorities should be more prone to violent and property victimization. Yet, if these factors are the major determinants of victimiza- tion, how does one explain why the risk of victimization for some groups (e.g., young personsyf L V U H O D W L Y H O \ V W D E O H D F U R V V D F W L Y L W y categories, whereas for others who are in residential proximity to motivated offenders (e.g., low-income personsyf W K H U H L V J U H D W H r variability in risk across activity categories? As illustrated by these predictions and our results, an a priori determination of high-risk social groups requires a more systematic treatment of the interrelationships among the necessary conditions of victimization, as well as an assessment of the relative importance of each component. In their present form, routine activities/lifestyle theories are basically unfalsifi- able since the social distribution of victimization can easily be construed as consistent with at least one component of the theories. Second, as the proximate cause of victimiza- tion in both lifestyle and routine activity theories, the notion of "exposure to risk" requires further exploration. Cohen et al. (1981, p. 507yf G H I L Q H H [ S R V X U H D V W K H S K \ V L F D l visibility and accessibility of persons or objects to potential offenders." However, several earlier studies treat exposure to risk as a two-step process. Specifically, Cavan and Ranck (1938yf note the difference between "predisposing" (i.e., structuralyf D Q G S U H F L S L W D W L Q J L H V L W X D - tionalyf I D F W R U V 7 K H Q R W L R Q R I D O H D W R U \ U L V N " (Strodtbeck and Short 1964yf D O V R L P S O L H V a similar relationship between structural features and situational aspects of human behavior. When applied to theories of victimization, physical visibility, accessibility, and residential proximity to motivated offenders would be considered predisposing factors, whereas the absence of guardianship, target suitability, and the various situational dynamics involving victim and offender transactions would be considered precipitating factors. The advantage of this alternative conception of exposure to risk is that it may explain why some persons who are in close residential proximity to motivated offenders and who spend relatively more time outside the household do not have a greater likelihood of victimization. Third, although offender motivation is largely neglected or assumed to be constant, routine activities/lifestyle theories adopt a rational conception of criminal behavior (e.g., Clarke et al. 1985; Cohen et al. 1981; Cohen et al. 1980yf . This content downloaded from 146.201.32.11 on Mon, 05 Sep 2016 16:53:16 UTC All use subject to http://about.jstor.org/terms 194 AMERICAN SOCIOLOGICAL REVIEW Specifically, criminal victimization occurs when motivated offenders in close proximity to potential victims make a rational selection of suitable targets who lack guardianship. How- ever, while this image of criminal behavior may be consistent with the etiology of instrumental crimes (e.g., property offensesyf W K H H [ S U H V V L Y e and spontaneous nature of many violent crimes is largely inconsistent with the "rational behav- ior" postulate underlying routine activity/life- style theories. In fact, the increase in rates of interpersonal violence among strangers since the mid-1960s (see USDJ 1984yf D Q G W K H V X E V H T X H Q t increases in "random" violence suggest that the fundamental premise underlying these theories of victimization may be less applicable over time. As our models of violent victimization imply, alternative theories of criminal victimiza- tion (e.g., structural strain, status threats, frustration/aggression approachesyf P D \ E H P R U e appropriate than routine activities/lifestyle theo- ries in explaining the extent and social distribu- tion of violent victimization (see also Luckenbill 1975; Strodtbeck and Short 1964yf . Finally, our findings on the direct and mediational effects of routine activity/lifestyle variables on the likelihood of property victim- ization suggest a parallel between aggregate and individual rates of this type of victimization. Coupled with studies of temporal changes in rates of property victimization (Cohen et al. 1981; 1980; Cohen 1981; Cohen and Felson 1979yf G L I I H U H Q F H V L Q U R X W L Q H D F W L Y L W L H V O L I H V W \ O H s are also associated with greater risks of property victimization at the individual level of analysis. However, it is unclear whether aggregate changes in routine activities over time translate into comparable changes in individuals' risk of victimization. Consequently, whether social trends that improve the quality of life for some groups (e.g., increased educational attainment and labor force participation among womenyf also produce a greater risk of victimization among these individuals remains a question for further research. REFERENCES Cavan, Ruth S. and K.H. Ranck. 1938. The Family and the Depression: A Study of One Hundred Chicago Families. Chicago: University of Chicago Press. Clarke, Ronald, Paul Ekblow, Mike Hough, and Pat Mayhew. 1985. 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