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Concern about the potential for indoor air pollution has prompted recent surveys of radon and NO/sub 2/ concentrations in homes and personal exposure studies of volatile organics, carbon monoxide and pesticides, to name a few. The statistical problems in designing sample surveys that measure the physical environment are diverse and more complicated than those encountered in traditional surveys of human attitudes and attributes. This paper addresses issues encountered when designing indoor air quality (IAQ) studies. General statistical concepts related to target population definition, frame creation, and sample selection for area household surveys and telephone surveys are presented. The implications of different measurement approaches are discussed, and response rate considerations are described.

Theoreticians have used the concepts of lifestyle and routine activities to account for the occurrence of personal crime victimization. Research has not usually used direct measures of these concepts, however, instead relying on demographic variables such as age and sex as proxy indicators. This paper analyzes the relationship of various job activities (delivering passengers or goods, traveling out of town, dealing face-to-face with customers, and working irregular hours) to the risk of violent and theft-damage personal crime victimization, and to the risk of such victimization at work. Logistic regression models show that delivery of passengers or goods and dealing with the public are robustly associated with violent victimization. None of the four job activities are consistently associated with theft-damage victimization risk. The results illustrate the importance of using direct measures of life-style or routine activities to examine exposure to the risk of victimization. The findings also suggest the need to elaborate further the notion of exposure, and to develop a second generation of victimization theory.

Recognizing that household respondents have difficulty recalling past events, the National Medical Care Expenditure Survey incorporated a record check component. For 12,000 persons included in the Medical Provider Survey, two data sources exist for health care events: household survey responses and provider record abstractions. This investigation compared medical conditions associated with the 35,000 visits, to conclude that agreement between sources was weak. Households tended to report fewer conditions per visit and familiar conditions, whereas providers reported related but different diagnoses. Levels of provider agreement with household reports ranged from 1% for upper extremity and shoulder impairments to 86% for pregnancy care and delivery. Over all 63 categories, providers concurred with household condition reports 40% of the time. Broader categories created by collapsing conditions substantially increased agreement levels. Analyses of household-provider agreement suggest that questionnair...