Promising community-level indicators for evaluating cardiovascular health-promotion programs.

Rigorous evaluation of community-based programs can be costly, particularly when a representative sample of all members of the community are surveyed in order to assess the impact of a program on individual health behavior. Community-level indicators (CLIs), which are based on observations of aspects of the community other than those associated with individuals, may serve to supplement individual-level measures in the evaluation of community-based programs or in some cases provide a lower-cost alternative to individual-level measures. Because they are often based on observations of the community environment, CLIs also provide a way of measuring environmental changes--often an intermediate goal of community-based programs. The Centers for Disease Control and Prevention convened a panel of experts knowledgeable about community-based program evaluation and cardiovascular disease (CVD) prevention to develop a list of CLIs, and rate their feasibility, reliability and validity. The indicators developed by the panel covered tobacco use, physical activity, diet and a fourth group that were considered 'cross-cutting' because they related to all three behaviors. The indicators were subdivided into policy and regulation, information, environmental change, and behavioral outcome. For example, policy and regulation indicators included laws and ordinances on tobacco use, policies on physical education, and guidelines for menu and food preparation. These indicators provide a good starting point for communities interested in tracking CVD-related outcomes at the community level.

Recovering true risks when multilevel exposure and covariables are both misclassified.

The authors extend previous results on nondifferential exposure misclassification to the situation in which multilevel exposure and covariables are both misclassified. They show that if misclassification is nondifferential and the predictive value matrices are independent of other predictor variables it is possible to recover the true relative risks as a function of the biased estimates and the misclassification matrices alone. If the covariable is a confounder, the true relative risks may be recovered from the apparent relative risks derived from misclassified data and the misclassification matrix for the exposure variable with respect to its surrogate. If the covariable is an effect modifier, the true relative risk matrix may be recovered from the apparent relative risk matrix and misclassification matrices for both the exposure variable with respect to its surrogate and the covariable with respect to its surrogate. By varying the misclassification matrices, the sensitivity of published relative risk estimates to different patterns of misclassification can be analyzed. If it is not possible to design a study protocol that is free of misclassification, choosing surrogate variables whose predictive value is constant with respect to other predictors appears to be a desirable design objective.

Use of multiple surveys to estimate mortality among never, current, and former smokers: changes over a 20-year interval.

OBJECTIVES: This study sought to demonstrate how data from publicly available large-scale cross-sectional health surveys can be combined to analyze changes in mortality risks among never, current, and former smokers. METHODS: Data from the 1966/68 and 1986 National Mortality Followback Surveys and the 1970 and 1987 National Health Interview Surveys were used to estimate the distribution of never, current, and former smokers among the US population at risk and decedents. Standardized mortality ratios and quotients of standardized mortality ratios were used to estimate mortality risks. RESULTS: Generally, during the period from 1966 through 1986, mortality rates in the United States for most causes of death declined among all smoking groups. However, mortality rates from respiratory diseases increased for current and former smokers. CONCLUSIONS: The reported changes in never and current smoker mortality risks are similar in magnitude and direction to those reported in a previous study based on longitudinal data. The use of combined data from the National Mortality Followback Survey and the National Health Interview Survey offers several advantages as an epidemiological tool.

Identifying and defining the dimensions of community capacity to provide a basis for measurement.

Although community capacity is a central concern of community development experts, the concept requires clarification. Because of the potential importance of community capacity to health promotion, the Division of Chronic Disease Control and Community Intervention, Centers for Disease Control and Prevention (CDC), convened a symposium in December 1995 with the hope that a consensus might emerge regarding the dimensions that are integral to community capacity. This article describes the dimensions that the symposium participants suggested as central to the construct, including participation and leadership, skills, resources, social and interorganizational networks, sense of community, understanding of community history, community power, community values, and critical reflection. The dimensions are not exhaustive but may serve as a point of departure to extend and refine the construct and to operationalize ways to assess capacity in communities.

Linear extrapolation models of lung cancer risk associated with exposure to environmental tobacco smoke.

This paper presents a model to estimate the number of lung cancer deaths due to ETS exposure among the 1992 U.S. never-smoking population, based on downward linear extrapolation from the estimated risks of active smokers. The model uses several recently available data sources including an extensive review of the published literature on indoor concentration of ETS constituents measured under real-world conditions and data from the National Mortality Followback Survey and the National Health Interview Survey which furnish nationally representative estimates of the distribution of the U.S. population and the persons who died from lung cancer by sex, age, and smoking status. The linear extrapolation model estimates that five male and six female excess lung cancer deaths due to ETS exposure would be expected in the 1992 U.S. population of over 52 million never smokers age 35 and over. Explanations for differences between the results of our downward extrapolation model and those of others are presented.

An alternative explanation for the apparent elevated relative mortality and morbidity risks associated with exposure to environmental tobacco smoke.

Insofar as industrial and other blue collar workers are more likely to bring home toxic materials on their person, and also are more likely to smoke than those in other occupations, members of a household are more likely to be subject to paraoccupational exposure and belong to lower socioeconomic strata if the household contains a smoker than if the household does not contain a smoker. Thus observed differences in risk of mortality or morbidity ascribed to ETS on the basis of a comparison of households with and without smokers may be partly or entirely due to differences in paraoccupational exposure and socioeconomic strata. Similarly, differences in mortality and morbidity ascribed to paraoccupational exposure may be partly or entirely due to differences in ETS exposure that are also related to social class and to types of occupation. Unfortunately, there are no data now in existence that could help determine separately the effects of these major confounded variables. There exists, then, a situation in which two explanations are advanced for respiratory diseases among members of a household, each based on similar study populations but focused on different major risk variables: ETS on the one hand, socioeconomic status and paraoccupational exposure on the other. Properly focused investigations need to be initiated.

A critical examination of OSHA's assessment of risk associated with workplace exposure to environmental tobacco smoke.

In response to a request for information on indoor air quality problems, the U.S. Occupational Health and Safety Administration (OSHA) has proposed a rule addressing indoor air quality in general, and especially environmental tobacco smoke (ETS), in indoor work environments. As justification for the proposed rule, OSHA relies on a quantitative risk assessment used to provide estimates of lifetime risk of lung cancer and heart disease associated with workplace exposure to ETS. However, there are a number of concerns regarding the OSHA risk assessment. (i) The form of the underlying mathematical model used in the risk assessment is inappropriate. (ii) OSHA was highly selective in choosing what data values to use in their risk assessment. (iii) Many data values required as input to the OSHA risk assessment model are simply not known at this time. When such values are required, known, but possibly inappropriate, values were substituted. The conclusions arrived at by OSHA on the basis of this risk assessment seem unwarranted.

Correcting standardized rate ratios for imprecise classification of a polychotomous exposure variable with limited data.

The analysis of exposure misclassification has received considerable attention in the epidemiologic literature, with the result that methods for correcting many summary risk estimates for such misclassification are well known. However, the application of such methods typically requires more data than are usually published (for example, the complete set of exposure- and age-specific mortality rates). The authors show, under the assumption that exposure misclassification occurs independently of disease status and confounder level, that it is possible to obtain estimates of standardized rate ratios corrected for a given pattern of misclassification from only the published standardized risk ratios and the misclassification matrix. This technique allows readers of scientific literature to perform post hoc sensitivity analysis of published risk estimates.

Mortality from respiratory cancers (including lung cancer) among workers employed in formaldehyde industries.

A joint study on effects of formaldehyde exposure in industrial populations by the National Cancer Institute and the Formaldehyde Institute, Inc. (Blair et al. [1986]: J Natl Cancer Inst 76: 1071-1084; Blair and Stewart [1989]: J Occup Med 31: 881, Blair et al. [1990]: Am J Ind Med 17:683-700) reported no significant elevation in risk ratios standardized to the general population. Using the same data as Blair et al., we compared more exposed to less exposed workers to compute relative risk for respiratory and lung cancers using a multivariate, log-linear model incorporating factors for job type (hourly vs. salaried), cumulative exposure (0.1-0.5, 0.5-2, 2+ vs. < 0.1 ppm/years), length of exposure (1-5, 5-10, 10+ vs. < 1 years), and age. Models were fit for all workers, all males, all workers less than 65 years of age, and for all males less than 65 years of age. Hourly workers have a significantly elevated relative risk when compared to salaried workers. While only high levels of cumulative exposure show a significant elevation in relative lung cancer risk, trend analyses of the coefficients of a log-linear model show a significant trend of increasing risk with increasing formaldehyde exposure. The significantly elevated respiratory and lung cancer risk for workers younger than 65 may indicate a shift of respiratory cancer mortality towards younger ages among those occupationally exposed to formaldehyde.(ABSTRACT TRUNCATED AT 250 WORDS)

Comments on the Health Effects Institute-Asbestos Research (HEI-AR) report: "Asbestos in public and commercial buildings," with emphasis on risk assessment methods used.

A Health Effects Institute--Asbestos Research Report calculates the risk of exposure to environmental asbestos fibers (EAF) by downward extrapolation from the mortality of workers exposed for 20 years. This extrapolation is improper because 1) relative risks of asbestos exposure very likely are not linearly progressive; 2) the composition of EAF may not be equivalent to that in mining or fabricating; 3) the same environmental asbestos concentration probably represents different exposure doses for different populations; and 4) health effects of asbestos exposure on children, seniors, patients, the institutionalized, the handicapped, and the chronically ill may not be the same as those of healthy workers. Evidence of asbestos-related disease among family members of exposed workers demonstrates that the risk observed for EAF is substantially larger than that estimated from downward extrapolation and suggests a basis for an alternative approach to estimating asbestos-related health risks. Such epidemiologic procedures are well established and ought to form the basis for detecting the health effects of EAF. It is also unclear which industry supports HEI-AR.

Risk attribution and tobacco-related deaths.

The number of deaths that would not have occurred had an exposure or trait been absent is generally estimated by observing mortality rates in sample populations of exposed and nonexposed persons and applying them to the population of interest. Three methods used to estimate deaths due to tobacco use are evaluated. Each method requires estimates of certain absolute and relative risks, and the published estimates based on them assume that the absolute and relative risks observed in the two large American Cancer Society prospective studies can be applied to the US population or to populations in developed countries. Computations using large representative samples of US decedents and of the entire US population for these methods result in estimated numbers of deaths for the US population that are substantially lower than those based on Cancer Prevention Survey-I or Cancer Prevention Survey-II. Computations also showed that controlling for confounding from two smoking-related variables results in still lower estimates of the number of excess deaths. Consequently, published results that ignore confounding and are based on nonrepresentative data overstate the contribution of smoking. It is imperative that estimates of excess deaths be based on representative data and control for relevant confounders.

Computation of relative risk based on simultaneous surveys: an alternative to cohort and case-control studies.

If the same information on the distribution of risk factors is available for both the general population and a subset distinguished by some disease outcome, it becomes possible to derive relative risk estimates applicable to the entire population with the assurance that the data upon which the estimates are based is representative of that population. To illustrate this approach, data from the 1986 National Mortality Follow-back Survey and the 1987 National Health Interview Survey were used to compute rate ratios for several causes of death for work in dirtyier as compared with cleaner occupations by three methods commonly employed in cohort and case-control studies: the usual standardized rate ratio, the Mantel-Haenszel estimate of the rate ratio, and a multiplicative model fit to an appropriate cross-classification. Properly placed questions in appropriate surveys might very well serve as a substitute for cohort studies and could be performed at less cost and with less overall effort, and completed in a shorter time. Moreover, this approach is less subject to problems of representativeness than cohort and case-control studies.