Toward a reformulation of the neonatal mortality rate.
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Biomedical subjects
Publications and source records attributed to R G Rogers.
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This research uses a multivariate log-linear examination of a national data set to analyze the combined influences of ethnicity, age, and sex on cigarette smoking status, not only for smokers but for former smokers and current nonsmokers as well. In general, we find that demographic differences in smoking vary across several dimensions. For instance, compared to females, males are more likely to smoke and to smoke heavily. The differences between male and female cessation rates vary with ethnicity; also, males and females tend to have different ratios of former smokers to light, moderate, and heavy smokers. Mexican-Americans who smoke generally smoke small quantities of cigarettes. And Blacks are as likely as other groups not to smoke at all, and less likely than Anglos to smoke heavily. This article discusses potential future mortality effects, intervention strategies, and directions for future research.
This paper illuminates the demographic and socioeconomic factors associated with smoking statuses. It employs the 1990 National Health Interview Survey's Health Promotion and Disease Prevention Supplement and logistic regression to examine the covariates of smoking status among the U.S. adult population. Polychotomous logistic regression, which provides an alternate way to examine smoking practices, simultaneously considers multiple variables and their interactions, controls for other important covariates, produces predicted values and patterns, and allows multiple comparisons. By examining interactions, we have found that age displays distinct, often curvilinear, patterns with smoking; that compared to females, males have higher rates of cigarette consumption except at the youngest ages; that Anglos, especially Anglo males, exhibit high probabilities of cigarette consumption but also high probabilities of being former smokers; that Black males exhibit high probabilities of light smoking, but only at the older ages, and that they also exhibit high probabilities of being former light smokers; and that Mexican-American females are the least likely to currently smoke or to have ever smoked. By clearly elucidating the demographic and socioeconomic variations in smoking, arguably the most salient marker of health behavior, we can better target programs and policies geared toward the reduction of smoking-related diseases and deaths.
The prevalence of cigarette smoking in the United States has declined over the past few decades. However, some leveling-off in prevalence rates has been observed in recent years, and the rate for teenagers and young adults has even turned upward. This paper considers four alternative scenarios of future cigarette smoking patterns in the United States for the population 25 and over and measures the impact these different scenarios would have on excess mortality due to smoking and on the sex and age distributions of deaths. Scenarios reflecting higher levels of smoking prevalence produce considerably more deaths than scenarios tied to lower levels. As many as two and one-half million excess deaths would take place in the decade of the 2020's if a high prevalence, rather than low prevalence, assumption proves correct. Even when a constant prevalence, assumption proves correct. Even when a constant prevalence assumption is compared with a moderately-declining prevalence assumption, as many as one million excess deaths would be generated during that decade alone. Lowering smoking prevalence rates would also change the population sex ratio by reducing deaths for males more than deaths for females, and by contributing to the aging of the population. The results are interpreted in terms of the overall impact of smoking on mortality and with regard to public and private policy decisions related to cigarette smoking.
We present a new procedure for optimization of a threading scoring function. A scoring function is usually formulated in terms of the structural environment states that describe the protein fold model. We propose a method for the optimal selection of those structural environment states that naturally follows from the probabilistic description of the threading problem and is done prior to threading experiments. We demonstrate the selection of the optimal structural environment states for the solvent exposure of the amino acid position, and present the results of threading experiments performed using scoring functions designed with and without the optimization of the structural environment states. These results confirm that the optimal scoring function predicts the sequence-to-structure alignments most accurately. Threading experiments performed with 15 optimally designed scoring functions show that the correlation coefficient between the information content of the amino acid distribution that determines the scoring function and the accuracy of the optimal sequence-to-structure alignment is 0.94.
With today's lower mortality rates, longer expectations of life, and new medical technologies, the nation's health policy focus has shifted from emphasis on individual survival to emphasis on personal health and independent living. Using longitudinal data sets and new methodological techniques, researchers have begun to assess active life expectancies, estimating not only how long a subpopulation can expect to live beyond each age, but what fractions of the expected remaining lifetime will be lived as independent, dependent, or institutionalized. New ideas are addressed, applying recently developed multistate life table methods to Waves One and Two of the Massachusetts Health Care Panel Study. Expectations of active life are presented for those 65 and older who initially are in one of two functional states of well-being. Included are expectations of life, for those, for example, who were independent and remained so, or those who were dependent and became independent. Although public health officials are concerned about the number of elderly who cease being independent, preliminary analysis shows that a significant number of the dependent elderly regain their independence, a situation which needs to be addressed in health care planning.
This research endeavors to broaden our knowledge of smokers' characteristics within ethnic groups. Special attention is given to Mexican Americans, a group that until recently has received scant attention in comparative research on smoking. In general, we find that ethnic differences in smoking vary across several dimensions. Many Mexican American females never smoke. If they do, they begin smoking late, smoke few cigarettes per day, and are likely to quit. Although many anglo (non-Hispanic white) males and females have tried smoking, a much higher proportion of males have quit. Blacks generally display rates intermediate to Mexican Americans and anglos, with relatively low rates of cigarette consumption. Discussed in this report are potential mortality effects, possible intervention strategies, and possible directions for future research.