Approximations for Estimating Change in Life Expectancy Attributable to Air Pollution in Relation to Multiple Causes of Death Using a Cause Modified Life Table

There is considerable debate as to the most appropriate metric for characterizing the mortality impacts of air pollution. Life expectancy has been advocated as an informative measure. Although the life‐table calculus is relatively straightforward, it becomes increasingly cumbersome when repeated over large numbers of geographic areas and for multiple causes of death. Two simplifying assumptions were evaluated: linearity of the relation between excess rate ratio and change in life expectancy, and additivity of cause‐specific life‐table calculations. We employed excess rate ratios linking PM_2.5 and mortality from cerebrovascular disease, chronic obstructive pulmonary disease, ischemic heart disease, and lung cancer derived from a meta‐analysis of worldwide cohort studies. As a sensitivity analysis, we employed an integrated exposure response function based on the observed risk of PM_2.5 over a wide range of concentrations from ambient exposure, indoor exposure, second‐hand smoke, and personal smoking. Impacts were estimated in relation to a change in PM_2.5 from 19.5 μg/m³ estimated for Toronto to an estimated natural background concentration of 1.8 μg/m³. Estimated changes in life expectancy varied linearly with excess rate ratios, but at higher values the relationship was more accurately represented as a nonlinear function. Changes in life expectancy attributed to specific causes of death were additive with maximum error of 10%. Results were sensitive to assumptions about the air pollution concentration below which effects on mortality were not quantified. We have demonstrated valid approximations comprising expression of change in life expectancy as a function of excess mortality and summation across multiple causes of death.     

Thurstone scaling via binary response regression

Thurstone scaling is a widely used tool in marketing research, as well as in areas of applied psychology. The positions of the compared items, or stimuli on a Thurstone scale are estimated by averaging the quantiles corresponding to frequencies of each stimulus’s preference over the other stimuli. We consider maximum likelihood estimation for Thurstone scaling that utilizes paired comparison data. From this perspective we obtain a binary response regression with a probit or logit link. In addition to the levels on a psychological scale, the suggested approach produces standard errors, t-statistics, and other characteristics of regression quality. This approach can help in both the theoretical interpretation and the practical application of Thurstone modeling.     

The Job Demand-Control (-Support) Model and psychological well-being: A review of 20 years of empirical research

The Job Demand-Control (JDC) model (Karasek, 1979) and the Job Demand-Control-Support (JDCS) model (Johnson, and Hall, 1988) have dominated research on occupational stress in the last 20 years. This detailed narrative review focuses on the JDC(S) model in relation to psychological well-being. It covers research from 63 samples, published in the period 1979-1997. In the review a distinction is drawn between two different hypotheses prevailing in research on the models. According to the strain hypothesis of the JDC model, employees working in a high-strain job (high demands-low control) experience the lowest well-being. The buffer hypothesis states that control can moderate the negative effects of high demands on well-being. Translating these hypotheses to the expanded JDCS model, the iso-strain hypothesis predicts the most negative outcomes among workers in an iso-strain job (high demands-low control-low social support/isolation), whereas the buffer hypothesis states that social support can moderate the negative impact of high strain on well-being. Although the literature gives considerable support for the strain and iso-strain hypotheses, support for the moderating influence of job control and social support is less consistent. The conceptualization of demands and control is a key factor in discriminating supportive from nonsupportive studies. Only aspects of job control that correspond to the specific demands of a given job moderate the impact of high demands on well-being. Furthermore, certain subpopulations appear to be more vulnerable to high (iso)strain, whereas others benefit more from high control. On the basis of the results of this review, suggestions for future research and theoretical development are formulated.     

Post-neonatal mortality in Rural India: Implications of an economic model

In this paper we develop and test a theory of childhood mortality after the first month of life. Parents are assumed to have well-defined family size and sex composition objectives and to face severe budget constraints. In this set of circumstances, it is understandable that they will make allocative decisions that will affect the survival probabilities of children. These decisions and the environmental influences on mortality are the basic forces which determine whether a child will survive through the post-neonatal period. The model is tested with survey data from rural Uttar Pradesh, India. The results are consistent with the hypothetical framework discussed above. The burden of this pattern of choice is felt particularly strongly by female births.     

Opportunity/Threat Responses to Nuclear Waste Disposal Facilities1

One of the most difficult environmental policy challenges facing the United States and other societies is that of finding ways to safely dispose of hazardous and toxic substances, including nuclear waste materials. Efforts to site such facilities have been uniformly unsuccessful, due largely to strong public opposition. Although supporters of such facilities often emphasize the potential for local economic development and other opportunities, opponents focus on a variety of threats involving potential risks associated with waste disposal. Survey data collected in rural areas of Nevada and Nebraska where nuclear waste disposal facilities have been proposed reveal that respondents' positions on issues of perceived health and safety risks, trust in responsible agencies, anticipated local economic effects, and concerns about environmental contamination are key variables predicting local response. Even in areas where there may be substantial local support for economic opportunities associated with the facilities, broad-based fears about nuclear materials and a legacy of distrust in the agencies responsible for managing nuclear wastes suggest that proposals for such facilities will almost inevitably continue to generate strong public opposition.     

Family Structure Among Urban,Rural and Farm Populations: Classic Sociological Theory Revisited

Abstract As predicted by the classic sociological theories of Durkheim, Tonnies, and others, early sociological researchers found extensive differences between urban and rural residents in the United States. In recent decades, many of these differences have appeared to wane, or in some cases, totally disappear. Based on these classic theories, we maintain that many of the urban/rural differences found in the past were actually farm/nonfarm differences. Further, we argue that many of these differences continue to exist in rural America, but they have been suppressed by major demographic transitions. Utilizing Current Population Survey data on family structure, we found that there were few significant differences between urban and rural nonfarm residents, but both varied extensively from various segments of the farm population.     

Evaluation of statistical equivalence using limits of agreement and associated sample size calculation *

In this article, the Food and Drug Administration's (FDA) medical device substantial equivalence provision will be briefly introduced and some statistical methods useful for evaluating device equivalence are discussed. A sample size formula is derived for limits of agreement, which may be used to assess statistical equivalence in certain medical device situations. Simulation findings on the formula are presented, which can be used to guide sample size selections in common practical situations. Examples of the sample size procedure are given.