Sleep hygiene practices and sleep duration in rotating-shift shiftworkers

Abstract

Alcohol, caffeine and tobacco intake, exercise, activities on going to bed, and sleep-enhancing measures were assessed in 72 rotating-shift shiftworkers to determine whether these variables differ following day shifts and night-shifts, and which are related to sleep duration. Only alcohol intake and exercise prior to sleep, and feeling drowsy when retiring, differed following the night-shift. Workers generally followed recommendations concerning alcohol intake, sleeping immediately on retiring, and exercising, but acted contrary to recommendations concerning caffeine and nicotine intake. The only behaviour clearly associated with poor sleep was smoking, which reduced sleep duration.     

Unobserved-Components Models for Seasonal Adjustment Filters

Time series models are presented, for which the seasonal-component estimates delivered by linear least squares signal extraction closely approximate those of the standard option of the widely-used Census X-11 program. Earlier work is extended by consideration of a broader class of models and by examination of asymmetric filters, in addition to the symmetric filter implicit in the adjustment of historical data. Various criteria that guide the specification of unobserved- components models are discussed, and a new preferred model is presented. Some nonstandard options in X-11 are considered in the Appendix.     

An Adjustment Factor for Mode-of-Action Uncertainty with Dual-Mode Carcinogens: The Case of Naphthalene-Induced Nasal Tumors in Rats

The U.S. Environmental Protection Agency (USEPA) guidelines for cancer risk assessment recognize that some chemical carcinogens may have a site-specific mode of action (MOA) involving mutation and cell-killing-induced hyperplasia. The guidelines recommend that for such dual MOA (DMOA) carcinogens, judgment should be used to compare and assess results using separate "linear" (genotoxic) versus "nonlinear" (nongenotoxic) approaches to low-level risk extrapolation. Because the guidelines allow this only when evidence supports reliable risk extrapolation using a validated mechanistic model, they effectively prevent addressing MOA uncertainty when data do not fully validate such a model but otherwise clearly support a DMOA. An adjustment-factor approach is proposed to address this gap, analogous to reference-dose procedures used for classic toxicity endpoints. By this method, even when a "nonlinear" toxicokinetic model cannot be fully validated, the effect of DMOA uncertainty on low-dose risk can be addressed. Application of the proposed approach was illustrated for the case of risk extrapolation from bioassay data on rat nasal tumors induced by chronic lifetime exposure to naphthalene. Bioassay data, toxicokinetic data, and pharmacokinetic analyses were determined to indicate that naphthalene is almost certainly a DMOA carcinogen. Plausibility bounds on rat-tumor-type-specific DMOA-related uncertainty were obtained using a mechanistic two-stage cancer risk model adapted to reflect the empirical link between genotoxic and cytotoxic effects of the most potent identified genotoxic naphthalene metabolites, 1,2- and 1,4-naphthoquinone. Bound-specific adjustment factors were then used to reduce naphthalene risk estimated by linear extrapolation (under the default genotoxic MOA assumption), to account for the DMOA exhibited by this compound.     

Enclaves, neighbourhood effects and employment outcomes: Ethnic minorities in England and Wales

Ethnic minorities in England and Wales are spatially concentrated in relatively-deprived urban areas. Both geographic clustering and the economic characteristics of ethnically-concentrated neighbourhoods can impact upon the opportunities and constraints facing residents of such areas. This paper explores the relationship between the existence of enclaves and the employment prospects of ethnic minorities in England and Wales. It is shown that there is considerable spatial variation in employment outcomes. There is a lower incidence of self-employment in more ethnically-concentrated urban areas, which contradicts the view of ethnic entrepreneurship as an enclave phenomenon. Unemployment rates are also higher for minorities living in more concentrated areas. Enclaves in England and Wales do not appear to offer many economic benefits to minority individuals. Received: 31 December 1999/Accepted: 27 November 2000     

Black/White Differences in Health Status and Mortality Among the Elderly

Grade of membership (GOM) representations are used to characterize and compare the health status of a very heterogeneous sample of blacks and whites in an elderly cohort of 2,806 noninstitutionalized men and women living in New Haven, Connecticut. They were interviewed in 1982 as part of the Established Populations for the Epidemiologic Study of the Elderly (EPESE). Ideal profiles based on functional disabilities, chronic diseases, and selected biomedical and behavioral risk factors are constructed empirically. Each individual in the sample is represented by a set of GOM scores, interpreted as degrees of similarity of his or her health record to each of the profiles. Four profiles emerge from GOM analyses: healthy elderly, elderly with cognitive impairment, elderly with impairment in mobility function and physical performance and with selected chronic conditions, and elderly with major limitations in activities of daily living and multiple chronic conditions. Although elderly blacks and whites generally have similar configurations of profiles, there are important differences, especially when chronic conditions are related to specific types of functional impairments. Questions about and claims for black/white mortality crossovers at older ages, usually addressed with aggregate data, are examined conditional on GOM scores that correspond to diverse combinations of disabilities (or lack thereof) together with housing characteristics of cohort members (e.g., whether they live in public housing for the elderly or in owned or rented housing in the community).     

Characteristics of U.S. cities with extreme (high or low) crime rates: Results of discriminant analyses of 1960, 1970, and 1980 data

Why do some cities have higher or lower crime rates than others? In this study we attempt to answer this fundamental question by identifying the theoretically motivated structural covariates which differentiate U.S. cities with extreme high and low crime rates. We apply discriminant function analysis across comprehensive samples of all U.S. cities with populations of greater than 25 000 in the periods 1960, 1970, and 1980 and then posit four question: are empirical findings from regression-based studies of city crime rates replicated in discriminant studies with extreme rates? Are the covariates that predict high or low crime rates unique to specific time periods? Which covariates are better able to discriminate high or low rates for specific crimes? And are specific covariates distinguishable in crime rate changes across time periods? Among our general findings, it appears that those cities with extreme high (low) crime rates tend to be the largest (smallest), most (least) economically deprived, and most (least) socially disintegrated. Associations with these latter two characteristics appear to have grown stronger over the past three census periods. The theoretical importance of these and other findings uncovered here are discussed and interpreted through Wilson's (1987) notion of concentration effects and social isolation which may have transformed inner-city areas in recent years.