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The article focuses on an examination of urban mortality using age-adjusted death rates. Authors Kent P. Schwirian and Anthony J. LaGreca attempted to assess the relative impact of demographic, environmental, and social organizational factors upon differential death rates. Their data led them to conclude that mortality may be explained largely in terms of subarea differences in age structure, social status levels, and housing conditions. With respect to ecological theory per se, and more specifically the ecosystem frame of reference, Schwirian and LaGreca have made a significant contribution. Prior to their analysis there was little research on the impact of ecological variables on mortality, especially within the perspective of neoclassical human ecology. The paper aims to demonstrate that the use of a crude, rather than an age-adjusted, death rate at best confounds the theoretical issues of the causal model, and leaves unanswered any question concerning the precise empirical impact that environmental and social variables have on urban mortality.

The article discusses the effect of alternative age adjustment procedures on the analysis of urban mortality patterns. Analyses of mortality differences among populations need a single index of the overall mortality experience of each population. The conclusions one draws about the nature of mortality's correlates are a function of the type age adjustment used. In this paper housing was more important than income in explaining variations in the crude death rate and the indirect standardized rate. However, income was more important than housing in explaining variations in the direct standardized rate. Indirect standardization in itself is not necessarily enough to eliminate the compositional effect of age. Attention must be given to the extent to which there is a correspondence between the standard population's age-specific rates and those for the population studied. Census tracts, since their populations are comparatively small, are quite subject to great fluctuations in the number of deaths per year in the different age categories.

The article presents an ecological analysis of urban mortality rates in the U.S. According to the authors much of the work taking account of the health factors has been done in a comparative perspective with the general conclusion being that improved health conditions and services and not pure economic factors have been the main influence in lowering mortality in the developing nations. The purpose of this paper is to examine the ecological correlates of neighborhood mortality levels in a large urban center. The focus is upon the identification of the relative contribution of demographic, environmental, and social organizational variables to the explanation of differences in urban subarea death rates. The authors take as their starting point the works of those social scientists who have clearly demonstrated the relationship of ecological phenomena to differential urban mortality. Past studies have shown the importance of a large number of specific variables in explaining differential aggregate community mortality levels. These specific variables may be grouped into three gross categories, such as demographic, environmental, and social organizational.

This paper presents statistical evidence, which seems to be conclusive, that there exists a particular pattern of mortality in Ceylon, India and Pakistan where, contrary to general experience, female mortality is higher than that of the males. The sex ratios of the enumerated population in these three countries are among the highest in the world, and the age pattern of the sex ratios is such that they increase from childhood to adulthood to the old ages. Abnormally high sex ratios and selective migration cannot account for this particular pattern, but there is evidence of a higher degree of under-enumeration of females than males. The main responsible factor, however, seems to be higher female mortality, in the ages of maternity as well as in childhood. This shows the need for a regional or local approach to some demographic problems. In this case, for instance, model life tables based on average international experience are not representative. [ABSTRACT FROM AUTHOR]

The sequence of births occurring in a closed female population subject to constant schedules of fertility and mortality can be represented as [Multiple line equation(s) cannot be represented in ASCII text] where only one coefficient (Q[sub 0]) and one exponent (r[sub 0]) are real. Convergence to a stable population occurs a few years after all complex components in B(t) have become negligible relative to the one real component. The rate of convergence of B(t) to a real exponential function depends on the age schedules of fertility and mortality, and on the initial age distribution. Methods of determining the coefficients and exponents of the terms of B(t) by use of a large computer are described in this paper, and various significant characteristics of the terms are given. Methods are described for visualizing how convergence would occur in a particular human population on the basis of recorded features of its fertility, mortality, and age composition. [ABSTRACT FROM AUTHOR]

In applied problems one often wishes to compare the mortality experience of two or more groups of individuals who are known not to be comparable with respect to a covariable. This paper presents an approach to this problem by assuming that the force of mortality for each individual is a function of the covariable. Extension to the case where more than one covariable is present is indicated. It is also suggested that the present method is adaptable to an actuarial type analysis. [ABSTRACT FROM AUTHOR]

Data are available to study the variation in mortality in this country occurring month by month for fully six decades. Death rates by month have been computed and published for the expanding death-registration area of the United States of 1900-1932 and for the complete nation (48 States and ultimately 50 States) from 1933 to the present. Even a cursory glance at the available data leads to the obvious conclusion that a definite pattern of seasonal variation of deaths exists. This seasonal swing is characterized by a high death rate in the early part of the year dropping to a trough in the summer months, and rising again during the latter part of the year. The general pattern is well recognized, as are similar seasonal curves for various causes of death. Despite the apparent wealth of statistical material at hand relatively little analytical matter has been produced in this country measuring seasonality of mortality as compared with the wide range of data compiled for statistical series portraying the nation's economic operations. Yet seasonal variation is receiving increasing attention in the evaluation of statistics of vital events. The very factors which make seasonal indices so valuable to economists and analysts also have proved to be of service to demographers and public health researchers. Seasonal adjustments provide refined information about current trends; they separate the seasonal components of statistical data from cyclical and irregular fluctuations; they provide indices with which to measure the significance of month to month change. Seasonal variation in the crude birth rate has been analyzed for the period 1933-40 using the link relative method [1]. Seasonal indices for 1948-54 were prepared with the aid of Univac, the high-speed electronic computer of the United States Bureau of the Census, using an adaptation of the standard ratio to moving average method [2]. The indices prepared by the Bureau of the Census became the basis for the regular computation of seasonally adjusted figures of births by the National Vital Statistics Division, U. S. Public Health Service 131. Similarly, marriage data published by the National Vital Statistics Division have been "deseasonalized" with the aid of methods developed by the Bureau of the Census [4]. This paper presents the results of an effort made with the assistance of Univac to eliminate seasonal variation from mortality data. Some of the particular problems encountered in adjusting mortality data, and the attempts to surmount these are described. [ABSTRACT FROM AUTHOR]