Life expectancy data

The United States Census Bureau tracks our so-called vital statistics, which include life expectancies and rates and causes of death. Because this data is compiled by census and not for purposes of proving or disproving arguments specifically relating to chemical residues, it should provide us with an unbiased perspective on the health status of the United States. The annual compilation of these statistics will be the primary source of my data. They are readily accessible to anyone who looks (www.census.gov/statab). Let s go to the source. Table 4.1 is an abstract of the life-expectancy data from 1970 projected through the year 2010. In other words, for a baby born in the tabulated year, this is how long he or she is expected to live based on past life expectancies. 

Table 4.1. Abstract of life-expectancy data from 1970.

Now the data starts to get interesting and requires some interpretation. First, recall that these people who are dying are doing so in smaller numbers and at older ages. This can be seen from the previously tabulated death rate and life expectancy data. The primary killer remains heart disease. This is not unexpected as we are talking about the cause of death for people in the last... 

Life expectancy—Many people use this term incorrectly, in that they assume it to have a fixed value throughout a person s life. However, it refers to the number of years that a person may expect to live after having reached a certain age. (Life expectancy data are derived from the vital statistics that have b n obtained from various groups of people and national populations.) It is noteworthy that the life expectancy at birth is usually less than that at age 65, because a newborn infant has yet to be exposed to the infectious diseases that threaten life, whereeis the 65 year old has already survived many of these hazards. 

Cross-comparing the risks of various activities is difficult because of the lack of a common basis of comparison, however Cohen and Lee, 1979 provide such a comparison on the basis of loss of life expectancy. Solomon and Abraham, 1979 used an index of harm in a study of 6 occupational harms - three radiological and three nonradiological to bracket high and low estimates of radiological effects. The index of harm consists of a weighting factor for parametric study the lost time in an industry and the worker population at risk. The conclusions were that the data are too imprecise for firm conclusions but it is possible for a radiation worker under pessimistic health effects assumptions to have as high index of harm as the other industries compared. 

Cold crank performance, battery life expectancy, and freedom from maintenance are generally co-affected by the separators, whereas ampere-hour capacity remains largely unaffected at a given separator thickness. The properties of the different leaf and pocket separators are compared in Table 10. These typical separator properties (lines 1-4) are reflected in the electrical results of battery tests (lines 5-8). The data presented here are based on the 12 V starter battery standard DIN 43 539-02 tests based on other standards lead to similar results. 

Since fatigue cracks often start at a random surface imperfection, considerable scatter occurs in fatigue data, increasing with the increasing lifetime wherever crack initiation occupies most of the fatigue life of a specimen. When a line of the best fit is drawn from the available data points on an S-N curve, this represents the mean life expected at any given stress level or the stress that would cause, say, 50% of the product failures in a given number of cycles. 

Estimates of the lifetime COl are needed for temporal and international comparisons and for assessment of the efficiency of prevention strategies. During the first years of HIV/AIDS treatment, direct lifetime costs were only estimated by simple projections based on retrospective data. Later, specific statistical tools were adopted to estimate life expectancy and lifetime costs. The results of lifetime estimates are very sensitive to imputed assumptions. Table 4 demonstrates some studies in this field. 

When all necessary nutrient supply systems are in balance and functioning properly, aerobic biological remediation can be relatively rapid. Gasoline components have been observed to have a half-life of days to months under well-controlled field conditions. Chemicals such as tetrachloroethylene that are best degraded under anaerobic conditions require significantly more time. Published half-lives for similar chlorinated solvents under field conditions are on the order of 300-day half-lives. Several computer programs are available that calculate the probable life expectancy of remedial projects. For best results, these programs require input of real field data. 

The US-EPA Child Specific Exposure Factors Handbook (US-EPA 2006), first published in 2002, consolidates all children s exposure factors data into one document. The document provides a summary of the available and up-to-date statistical data on various factors assessing children s exposures. These factors include drinking water consumption soil ingestion inhalation rates dermal factors including skin area and soil adherence factors consumption of fruits, vegetables, fish, meats, dairy products, homegrown foods, and breast milk activity patterns body weight consumer products and life expectancy. 

The demographic shifts in life expectancy gains further complicate any analysis of the sources of longer life. To identify the specific role of pharmaceuticals in this remarkable trend, we focus on empirical research based on data from the last 20-30 years. The role of pharmaceutical products is not obvious, however, because of simultaneously increased average income, decreased poverty, greater and faster access to medical facilities, and improved training for health professionals, all of which combine with access to new and improved pharmaceutical products to yield longer life. 

The paper by Cochrane, St. Leger, and Moore (1978) typifies the issues associated with many early studies. Specifically, they relied on cross sections with multiple countries and often limited the analysis to simple correlations. Because determinants of life expectancy are multifactorial, national studies are more likely to detect differences than international studies. It is also critically important to include adequate control variables. In fact, a later study (Cremieux, Ouellette, and Meilleur 1999) based on extensive national data suggests that a 10% increase in health care spending reduces infant mortality by 0.5% for males and 0.4% for females while increasing life expectancy by half a year for males and three months for females. The current study uses similar modeling and data hence, results on the effect of pharmaceuticals reported below can be put in perspective relative to the overall effect of health care spending from that earlier research. 

In their updated 2004 study, Miller and Freeh used more recent data to conduct a similar cross-sectional analysis with some additional control variables (e.g., obesity rates) and found very similar results on life expectancy... 

In a later similar study, Cremieux et al. (2005) used Canadian data to examine the relationship between pharmaceutical spending and infant mortality. This study examined determinants of life expectancy as well. The explanatory variables included food intake, alcohol and tobacco... 

Although life expectancy is the best available general measure of health outcomes, no life tables exist by disease. We constructed an alternative measure of disease-specific life expectancy by computing the proportion of deaths that occurred above certain ages, such as 65, using data on deaths by disease category from a time series of mortality data obtained from the Department of Health in Taiwan. ... 

This measure is likely to be a reasonable proxy for disease-specific health outcomes for two reasons. First, the proportion of deaths occurring above a certain age can be interpreted as the probability of survival until that age, for example, age 65 (Lichtenberg 2005b). Second, there is a statistically positive relationship between life expectancy at birth and the proportion of deaths occurring above a specific age, based on comparisons of time series data within a country or cross-sectional data across countries. For example, with life expectancy at birth on the vertical axis and the proportion of deaths occurring above age 65 for the whole population at the horizontal axis using time series data from Taiwan for 1971-2002, there is a significantly positive relationship, for both males and females (Fig. 13.4). Life expectancy at birth increases as the age at death increases. 

Using data shown in Figure 13.4, we used ordinary least squares to estimate the effect of the probability of survival to age 65 on life expectancy at birth and found a significantly positive association between these two measures a 10% increase in probability of survival to age 65 was associated with a 1.3% increase in life expectancy. This result, combined with the estimates in Tables 13.2 and 13.3, implies that a 10% increase in the stock of pharmaceutical innovation would lead to an increase in life expectancy at birth by 0.10% (i.e., 0.8% X 1.3%) to 0.18% (1.4% x 1.3%). 

Organization for Economic Cooperation and Development. 2004. Table 1. Life Expectancy in Years, in OECD Health Data 2004, 3rd ed. Available at www.oecd.org. 

Shaw, James W., Wihiam C. Horrace, and Ronald J. Vogel. 2005. The Determinants of Life Expectancy An Analysis of the OECD Health Data. Southern Economic Journal 71(4) 768-783. 

The availability of, and analytical data for, these standards arc prerequisites for quantitative and qualitative analysis of the yield of modified sialic acids from periodate-borohydride-treated cells, and, correspondingly, for evaluation of the influence of such modifications on the biological behavior of cells. In such an experiment, related to a study of the life expectancy of rabbit erythrocytes, the simultaneous analysis of Neu5Ac, Neu5Gc, and their C7 and C8 analogs from rab-... 

These data would suggest that, although there is some loss of ascorbic acid during the normal shelf life of orange juice in plastic-coated paper cartons, this processed product represents a significant source of ascorbic acid in the diet of any consumer at any time during its dated life expectancy (as indicated by the... 

Early clinical studies are performed in cancer patients in hospitals instead of healthy volunteers, and in specialized Phase I units. Selection criteria for patients entered into cetuximab Phase I studies included various important factors such as disease state, life expectancy (>3 months), prior treatment, organ function, age, tumor type and target (i.e., EGFR expression). Therefore, pharmacokinetic (PK) data obtained from these individuals is confounded by numerous factors, a fact usually absent in conventional studies with tightly controlled, well-selected healthy subjects performed for non-oncologic drags. 

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