https://acawiki.org/api.php?action=feedcontributions&user=WisconsinDemographyPrelimAugust2009&feedformat=atomAcaWiki - User contributions [en]2024-03-29T09:44:09ZUser contributionsMediaWiki 1.31.12https://acawiki.org/index.php?title=Population_and_Technology_in_Preindustrial_Europe&diff=2781Population and Technology in Preindustrial Europe2009-11-19T15:08:37Z<p>WisconsinDemographyPrelimAugust2009: </p>
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<div>{{Summary<br />
|title=Population and Technology in Preindustrial Europe<br />
|authors=Ester Boserup<br />
|tags=uw-madison, wisconsin, sociology, demography, prelim, qual, WisconsinDemographyPrelimAugust2009, population, history of technology<br />
|summary=From ancient times, growth of population and increase of urbanization have provided incentives to technological improvements in agriculture, either by transfer of technology from one region to another, or by inventions in response to urgent demand for increase of output, either of land, or labor, or both. 1983. There was an escape from the Malthusian population trap. Technological improvement in agriculture could raise the productivity of land and labor, thus making it possible to feed a larger population. But, unless technological change in agriculture was rapid, as it is in industrialized societies, the escape was assumed to be only temporary, because the surplus created by technological progress would be "eaten up" by further population increase, due to improved nutrition. This neo-Malthusian theory is unrealistic for these reasons: 1. Technological progress in agriculture would not result in further pop growth in cases where factors other than insufficient food supply were the effective restraints on pop. 2. The malnourished were always the poor, and they would sometimes lose more than they gained by changes in agricultural technology, at least in the short run. 3. The Malthusian theory overlooks the effect of population increase on technological change. Such technological change is often a result of research promoted by fear of rapid population growth. Population increase has 2 different effects on systems of production: 1. diminishing returns; 2. possibility to build, finance physical and human infrastructure.<br />
|journal=Population and Development Review<br />
|pub_date=1987<br />
|volume=13<br />
|issue=4<br />
|pages=691–701<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Population_and_Technology_in_Preindustrial_Europe&diff=2780Population and Technology in Preindustrial Europe2009-11-19T15:07:52Z<p>WisconsinDemographyPrelimAugust2009: Created page with '{{Summary |title=Population and Technology in Preindustrial Europe |authors=Ester Boserup |tags=uw-madison, wisconsin, sociology, demography, prelim, qual, WisconsinDemographyPre…'</p>
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<div>{{Summary<br />
|title=Population and Technology in Preindustrial Europe<br />
|authors=Ester Boserup<br />
|tags=uw-madison, wisconsin, sociology, demography, prelim, qual, WisconsinDemographyPrelimAugust2009, population, history of technology<br />
|summary=13(4): 691–701<br />
<br />
From ancient times, growth of population and increase of urbanization have provided incentives to technological improvements in agriculture, either by transfer of technology from one region to another, or by inventions in response to urgent demand for increase of output, either of land, or labor, or both. 1983. There was an escape from the Malthusian population trap. Technological improvement in agriculture could raise the productivity of land and labor, thus making it possible to feed a larger population. But, unless technological change in agriculture was rapid, as it is in industrialized societies, the escape was assumed to be only temporary, because the surplus created by technological progress would be "eaten up" by further population increase, due to improved nutrition. This neo-Malthusian theory is unrealistic for these reasons: 1. Technological progress in agriculture would not result in further pop growth in cases where factors other than insufficient food supply were the effective restraints on pop. 2. The malnourished were always the poor, and they would sometimes lose more than they gained by changes in agricultural technology, at least in the short run. 3. The Malthusian theory overlooks the effect of population increase on technological change. Such technological change is often a result of research promoted by fear of rapid population growth. Population increase has 2 different effects on systems of production: 1. diminishing returns; 2. possibility to build, finance physical and human infrastructure.<br />
|journal=Population and Development Review<br />
|pub_date=1987<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Some_Aspects_of_the_Social_Context_of_HIV_and_Its_Effects_on_Women,_Children,_and_Families&diff=2762Some Aspects of the Social Context of HIV and Its Effects on Women, Children, and Families2009-11-19T14:41:54Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-19 02:41:54</p>
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<div>{{Summary<br />
|title=Some Aspects of the Social Context of HIV and Its Effects on Women, Children, and Families<br />
|authors=Palloni, Alberto, Lee, R.<br />
|pub_date=1992<br />
|summary=Notes: In this article, a simple framework for the study of the effects of HIV/AIDS on women is suggested. A woman's probability of contraction HIV through sexual transmission at exact age x can be expressed as the product of being expose to contact with infected male(s), G(x), and the conditional probability that if exposed to the contact at that age it will result in infection, F(x). Measurement of these factors is complicated by their dependency on women's characteristics at age x and features of the male population that enters in contact with women at that age. The value of G(x) is the product of (1) the probability of being exposed at age x to any sexual contact at all, and (2) the conditional probability of being exposed to contacts with infected men. The first factor influencing the magnitude of exposure is the timing of entrance into sexual unions or the onset of sexual activity. Exposure to sexual contact is relevant for HIV infection only if, once it begins, it leads to a non-zero probability of contacting infected male(s) the age gap is especially important. A third factor is the level of age-specific prevalence among males, which depends on their frequency of extramarital affairs and population movements (especially male migration). A fourth factor relates to women's roles and socioeconomic characteristics of the family. Finally, the norms regulating remarriage and sexual behavior of widows are also an important mechanism of infection that may affect both women and men. F(x) can also be broken down into (1) the probability of contracting the infection while using protected sexual intercourse, and (2) the probability of using protection and being exposed to the enhancing factors. These factors include being female (male-to-female transmission higher than female-to-male), presence of other STD's, and male/female status inequalities (disparities in the control over the initiation and regular establishment of sexual unions, their consummation, and their termination). The presence of HIV may remain unnoticed for very long periods of time allowing infected individuals to remain active and unknowingly infective and thereby increasing the reproductive values of the virus. However, constraints in the choices that women face produce conditions for a typical incubation process with shorter median incubation times and possibly lower variances due to an interaction between immune system dysfunction and societal rules and mores that increase the likelihood that women will engage in risky behavior. Increases in HIV could have a differential impact on social strata or classes. When HIV is transmitted through heterosexual contact, the maximum levels of sero-prevalence are generally found among young adults and very young children. The levels of paternal and maternal orphanhood at young ages will rise. Increases in adult mortality will also lead to a growing incidence of widow(er)hood. A third consequence is that barring drastic changes in remarriage rules, the dominance of the parental generation will be weakened and the relations between children and grandparents will become more influential. Fourth, in societies with a strong emphasis on descendants and a rigidly enforced norm of high fertility, a sudden upsurge in infant mortality may trigger an adaptive response towards even higher fertility thereby exacerbating women's health problems. Fifth, relatively long incubation periods combined with environments that predispose the population to repeated viral, bacterial, or protozoal infections could lead to health deterioration among the infected population in a measure that is not experienced in areas with different environments. This, in turn, could even further prematurely disable productive individuals. Finally, potential responses, including fosterage and incentives for bridewealth, may further erode women's positions.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Population_and_the_environment:_The_scientific_evidence&diff=2763Population and the environment: The scientific evidence2009-11-19T14:41:54Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-19 02:41:54</p>
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<div>{{Summary<br />
|title=Population and the environment: The scientific evidence<br />
|authors=Preston, Samuel H., Demeny, Paul, McNicoll, G.<br />
|pub_date=1998<br />
|summary=Author Role: eds.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Trends_and_Differentials_in_Disability-Free_Life_Expectancy:_Concepts,_Methods,_and_Findings&diff=2764Trends and Differentials in Disability-Free Life Expectancy: Concepts, Methods, and Findings2009-11-19T14:41:54Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-19 02:41:54</p>
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<div>{{Summary<br />
|title=Trends and Differentials in Disability-Free Life Expectancy: Concepts, Methods, and Findings<br />
|authors=Robine, Mathers, Brouard<br />
|pub_date=1996<br />
|summary=Notes: The WHO has proposed the following model of irreversible disorders: diseaseimpairmentdisabilityhandicap. Impairments are abnormalities of body structure and appearance with organ and system function, resulting from any cause at the organ level. Disabilities reflect the consequences of impairment in terms of functional performance and activity by the individual person-level. Handicaps are concerned with the disadvantages experienced by the individual as a result of impairments and disabilities related to individual's surroundings. Theories of health transition and disability Pandemic of disabilities: the postponement of death results in a worsening of the severity of chronic diseases because mortality decline is due to a decline in the fatality of chronic diseases and not a decline in their incidence or progression decline in the ratio of disability-free life expectancy to total life expectancy (DFLE/LE) Compression of morbidity: if morbidity is defined from the onset of chronic infirmity until death and if the onset can be postponed and if adult life expectancy is relatively constant, then morbidity will be compressed into a shorter period of time increase in DFLE/LE ratio. Dynamic equilibrium: the increase in life expectancy is in part explained by a slowing down in the rate of progression of chronic diseases; therefore, although the decline in mortality leads to an increase in the prevalence of chronic diseases, these diseases will in general be milder in character decline in DFLE/LE ratio, increase or leveling off in ratio of severe DFLE/LE. Using data from France from 1900 to 1990, Robine and Mathers (1993) simulated various possible trends in DFLE. They found that absolute compression of morbidity is only obtained when the prevalence of disability falls at a faster rate than mortality. (This is a sort of random thing in this summary, but it felt the same way in the article.) In a meta-analysis of comparisons of existing international data series, the authors compare 5 areas: 1. Gender differentials: Although most studies indicate that life expectancy and DFLE are greater for females, they also show that their proportion of disability-free years to total life expectancy is slightly lower than males. 2. Socioeconomic differentials: Well-known socioeconomic differences in life expectancy increase markedly when the calculations are done for DFLE 3. Causes of disability and mortality: The elimination of some causes have a greater effect than others. 4. Time trends: Overall, studies suggest that, over the last 25 years, there has been a 6-year increase in life expectancy at birth among females in developed countries. By contrast, there has been a corresponding stagnation at 63 years in DFLE. These results tend to confirm the theory of dynamic equilibrium proposed by Manton (1982). Geographical comparisons: are difficult to make. Combining the data from different countries does not allow one to reliably determine whether or not the proportion of DFLE decreases as overall life expectancy increases.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=The_Measurement_of_Wanted_Fertility&diff=2765The Measurement of Wanted Fertility2009-11-19T14:41:54Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-19 02:41:54</p>
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<div>{{Summary<br />
|title=The Measurement of Wanted Fertility<br />
|authors=Bongaarts, John<br />
|pub_date=1990<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Marital_Fertility_Decline_in_Developing_Countries:_Theories_and_Evidence&diff=2766Marital Fertility Decline in Developing Countries: Theories and Evidence2009-11-19T14:41:54Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-19 02:41:54</p>
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<div>{{Summary<br />
|title=Marital Fertility Decline in Developing Countries: Theories and Evidence<br />
|authors=Cleland, John G.<br />
|pub_date=1985<br />
|summary=Notes: á The conscious exercise of birth control within marriage is probably absent in many traditional societies. á Fertility decline due to birth control bears the hallmarks of a diffusion of a new behavioral trait, usually spreading to all sectors of society within a remarkably short span of time, regardless of the economic position of individual families. á The evidence from the study of fertility differentials, though only inferential, does not support the view that fundamental shifts in the economic role of the family unit, or of its members, particularly women and children, are necessary for marital fertility to decline. á The fact that parental education and cultural factors, denoted by language, ethnicity, or region, emerge as major independent determinants of the onset of decline is more consistent with ideational than structural theories. á The testimony of women concerning their family size preferences runs counter to the common assumption that explanations for fertility change must be sought exclusively, or even primarily, in motivations for smaller families. Within the short historical period for which relevant survey data are available, the propensity to translate preferences into appropriate behavior appears to have been more important than changes in family size preferences themselves.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Disability_and_Mortality_Among_the_Oldest-Old:_Implications_for_Current_and_Future_Health_and_Long-term_Care_Service_Needs&diff=2760Disability and Mortality Among the Oldest-Old: Implications for Current and Future Health and Long-term Care Service Needs2009-11-19T14:41:53Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-19 02:41:53</p>
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<div>{{Summary<br />
|title=Disability and Mortality Among the Oldest-Old: Implications for Current and Future Health and Long-term Care Service Needs<br />
|authors=Manton, Kenneth G., Soldo<br />
|pub_date=1992<br />
|summary=Notes: Sorry about this seemingly useless description. I wasn't sure exactly what to include since there were pages and pages of this stuff, but it seems like it could pretty much be boiled down to this: Not all elderly are the same in terms of health status and health care needs. It appears that one can define a few groups within the elderly population that are more similar according to health characteristics including an older, pretty health group, a younger quite un-healthy group, an older, seriously ill group (maybe with dementia or something), and a couple of other groups in between.... There are a number of current aging trends in the US that are historically unique: (1) the rapid growth of the oldest old; (2) increases in life expectancy at advanced ages; (3) the predominance of women at advanced ages; and (4) reduction in the age-specific mortality rates of certain major chronic degenerative diseases (e.g., stroke, ischemic heart disease). In this paper, individual health changes at advanced ages are assessed using a broad range of vital statistics, epidemiological, and longitudinal study data. A general model of health changes based upon cohort and life-course perspectives is presented. Manton and Soldo also examine the implications of changes in the health of the oldest old for social and health policy. The model of health changes at advanced ages is represented by a series of survival curves for morbidity, disability and mortality (probability of survival) one inside the other. First, the model is used to examine different perspectives on health changes at advanced ages. One perspective, argued by Strehler (1975) is that as life expectancy reaches its maximum limit, interventions would increase the productive/active life span, but time spent with a chronic disease or disabled would remain the same. In contrast, Gruenberg (1977) and Kramer (1981) suggest that increases in life expectancy will lead only to further increases of time spent diseased or disabled; the onset of morbidity and disability would remain the same while the mortality curve would shift to the right. Similarly, Golini and Egidi (1984) found evidence that for increases in the prevalence of chronic degenerative diseases. More optimistically, Fries (1980, 1983), as we all know, argued for the possibility of the compression of morbidity as we reach the limits of life expectancy. However, Feldman (1982) and Schneider and Guralnik (1988) found little insufficient for such health improvements. Finally, Riley and Bond (1983) found both a high degree of individual variability in rates of aging changes and maintenance of certain physiological functions, even into the 80s. This suggests that all 3 curves can be moved and that, for example, an appropriate allocation of resources can compress the morbid and disabled period, but not with an absolutely fixed mortality curve. This is also represented in Manton's (1982) dynamic equilibrium of morbidity and mortality. A second use of the survival curve model is as a measure or index of health status in elderly populations that summarizes the cross-sectional relation of morbidity, disability, and mortality. A third use of the model is as a device to weight actuarial calculations, not only for changes in life expectancy but also for changes in the portion of life expectancy spent in health states with different health-service needs. The next few sections of the paper treat the vital statistics and epidemiological evidence on the individual components of mortality, morbidity, and disability. Regarding mortality, Manton and Soldo ask if the survival curve has rectangularized. The answer to that question is yes if one examines the entire curve from birth; however, the apparent rectangularization seems more a function of mortality rates at early ages, having reached low levels relative to the mortality rates among the elderly, than of the mortality changes observed at advanced ages. Moreover, at advanced ages, not only has the standard deviation at age of death been constant, the distribution has shifted significantly upward. Regarding morbidity, using data from the Duke Longitudinal Study of Aging (1955-1976), Manton and Soldo use a special analysis (Grade of Membership (GoM) seems sort of like factor analysis) to identify sub-populations that have similar physiological characteristics, demographic attributes, and responses to physical measurements as they relate to morbidity. The groups are originally defined (and are created as a result of the analysis) on physical health and intellectual status; however, there are within-group similarities based on other characteristics, such as age, survival time, and social status. They found a subgroup among the extreme elderly (i.e., mean age over 80) who were healthy and unimpaired and a frail extreme elderly group with multiple chronic diseases (i.e., diabetes, hypertension, dementia, arteriosclerosis) and several functional impairments. They also tended to find a young sub-population (mean age in mid-70s) with severe acute illness and high rates of service use who had short survival. Regarding disability, using data from the 1982 and 1984 National Long Term Care Study (NLTCS), they constructed a scale of disability from items on ADL and IADL limitations. There appears to be stability in disability rates in the community at later ages; however, this is due to mortality and institutionalization of highly disabled persons. Manton and Soldo project an increase in individuals with IADL and ADL limitations from 2000 to 2040. The greatest growth will be among unmarried females aged 75 and older. Manton and Soldo performed other GoM analyses of the NLTCS sample to identify sub-populations (one set based on sociodemographic factors and functional limitations, the other set composed of the institutionalized population based on diagnosis) who represent different target populations in order to evaluate the effect of policy options on the required service mix. Although chronic disease morbidity is most likely to be associated with functional disability among the oldest old, the correlation between age and either morbidity of disability is not sufficiently strong to warrant use of the age group 85+ as a proxy for service need in a population. For these groups, the process of selective survivorship may have already claimed persons most vulnerable to the chronic degenerative diseases that are associated with the highest levels of service need. Targeting services, then, requires identifying groups that manifest a consistent pattern of both need and service use. Using the groups created from the GoM analysis of NLTCS data described above, Manton and Soldo found that the health service profile of each group is appropriate to the group's health status/need profile. At low levels of functional dependence, the need for assistance is most likely to be satisfied in a community setting through the informal caregiving of family, friends, and neighbors. The sources of informal care are quite different by sex and marital status. Men are more dependent on their spouses for informal care. Women receive more care from offspring and relatives. With age, the likelihood of formal-care services increases as it does with increasing disability. Regarding costs of community services (for individual who are not institutionalized but receive formal care), monthly out-of-pocket expenses are greatest for those over age 85. In fact, for persons aged 85+ at the highest and next-to-highest disability levels, expenses are greater than the average for all ages combined. Manton and Soldo apply the health model described above to different types of long-term care service. First, morbidity sets in, then disability, then individuals receive informal care only, then formal and informal care, then institutionalization, then mortality. This model shows that as the population ages, the disabled will not only be older and possibly require more service, but informal care providers also are more likely to be elderly themselves.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Mediating_factors_linking_population_and_environment&diff=2761Mediating factors linking population and environment2009-11-19T14:41:53Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-19 02:41:53</p>
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<div>{{Summary<br />
|title=Mediating factors linking population and environment<br />
|authors=McNicoll, G.<br />
|pub_date=1994<br />
|summary=Notes: Hardin-type transfers: Within a community, to the extent that behavior of one person or family generates negative external effects on others, there will often be some compensating transfer, offered or exacted, that on balance yields a rough degree of reciprocity tragedy of the commons, Prisoner's Dilemma. Interclass transfers: The relevant cost transfers are effectively unilateral that is, uncompensated rather than reciprocal, especially likely in a strongly stratified society. (Potential reciprocity exists.) Community-level externalities: Some spillovers extend across community boundaries, the spatial separation making it more likely that the transfers will be unilateral. (Potential reciprocity exists.) Intertemporal transfers: Most transfers across time are necessarily unilateral and do not admit even potential recourse by those on whom the costs are imposed.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Effects_of_Mortality_on_Levels_of_Kinship&diff=2759Effects of Mortality on Levels of Kinship2009-11-19T14:41:52Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-19 02:41:52</p>
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<div>{{Summary<br />
|title=Effects of Mortality on Levels of Kinship<br />
|authors=Goldman<br />
|pub_date=1986<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=The_future_of_human_longevity:_A_demographer%27s_perspective&diff=2739The future of human longevity: A demographer's perspective2009-11-17T00:36:58Z<p>WisconsinDemographyPrelimAugust2009: </p>
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<div>{{Summary<br />
|title=The future of human longevity: A demographer's perspective<br />
|authors=Wilmoth, John R.<br />
|summary=Demographers are criticized for basing predictions on past trends without taking mechanisms into account, but the criticism is only valid if we understand and can incorporate these mechanisms into alternative predictive methods. Wilmoth thinks that life expectancy gets too much emphasis. Life expectancy is deceptive in that it reflects age patterns of morbidity/mortality as well as underlying declining death rates. When put into a historical perspective, recent medical advancements (nutritional supplements, smoking) do not compare to the vast influence of past advancements like germ theory or penicillin. However, there seems to be little evidence that populations are approaching any sort of life expectancy limit (net of unforseen disaster). It seems that e0=85 in 2050 is within the realm of extrapolation from past trends. The appeal of extrapolation lies in the stability of long-term trends which reflect complex mechanisms rather than single-variable improvements in mortality. Responses: Gavrilov and Gavrilova point out that ASDRs aren't quite as steady as the aggregate death rates used by Wilmoth, and that underlying mechanisms must be researched. Olshansky and colleagues also assert that biological mechanisms must come into play when making mortality predictions. They state that extrapolation is only valid for short time windows. Miguel's summary: Demographers claim some expertise in predicting future mortality levels usually through extrapolation of past trends. Biologists and others are often critical of this approach because it seems to ignore underlying mechanisms. However, our understanding of the complex interactions of social and biological factors that determine mortality levels is still imprecise. The extrapolative approach to prediction is particularly compelling in the case of human mortality: (1) mortality decline is driven by a widespread desire for a longer, healthier life; (2) mortality has been falling steadily, and lifespan increasing, for more than 100 years in economically advanced societies; (3) these gains in longevity are the result of a complex array of changes; (4) much of this decline can be attributed to the directed actions of individuals and institutions, which is likely to continue in the future. Predictions of future life expectancy by extrapolation yield values that are not too different from what is observed today. An important issue for consideration in forecasting mortality is the time frame both the time frame of the data that form the input to an extrapolation and the time horizon of the projection itself. Although short-term fluctuations have been common, long-term mortality trends in industrialized countries have been remarkably stable. Errors result from extrapolating farther into the future than is warranted. Another common error results from an undue emphasis on trends in life expectancy. Although the increase in life expectancy has slowed down, the decline in death rates has quickened. In recent years, the extrapolative approach to mortality prediction has been challenged by assertion that future changes in average human life-span may come more or less quickly than in the past. Moreover, there are potential applications of existing technologies that may elongate life. It is even possible that technological breakthroughs will provide another source of optimism about future mortality rates. However, such scientific advances should be compared with past ones when forecasting their effects on mortality. More pessimistic scenarios of the future course of human longevity are based on notions of biological determinism or arguments about practicality, yielding the now-familiar claim that life expectancy at birth cannot exceed 85 years. Such scenarios arise from evolutionary theory, which predicts a sharp rise in death rates in post-reproductive years, because deleterious genes operating at these ages have evolved with no opposition from the forces of natural selection. However, current patterns of survival indicate that death rates in later life can be altered considerably by environmental influences, and there is little conclusive evidence that further reductions are impossible. Furthermore, trends in death rates and in maximal ages at death show no sign of approaching a finite limit. Extrapolation rides the steady course of past mortality trends, whereas popular and scientific discussions of mortality often buck these historical trends, in either an optimistic or pessimistic direction. Of course, extrapolation is not without its flaws. It could not predict the rise in mortality in the former Soviet Union after 1990 or the emergence of AIDS in Africa and elsewhere. However, such observations are less an indictment of extrapolation than a demonstration that the greatest uncertainties affecting future mortality trends derive from social and political, rather than technological, factors.<br />
|journal=Science<br />
|pub_date=1998<br />
|journal_volume=280<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Fertility,_Biology,_and_Behavior&diff=2738Fertility, Biology, and Behavior2009-11-17T00:36:13Z<p>WisconsinDemographyPrelimAugust2009: </p>
<hr />
<div>{{Summary<br />
|title=Fertility, Biology, and Behavior<br />
|authors=Bongaarts, John, Potter, R. G.<br />
|summary=The standard measure of the total fertility rate (TFR) used in demographic measure is a summary measure that can change for a variety of reasons. The TFR is composed of birth-order components, such as the first-order component (TFR1), which gives the average number of first births women would have by age 50 if they were to bear first births at the age-specific rates observed in a given year or period. The sum of all of the order components equals the total TFR. During the late 1940s and early 1950s the TFR1 exceeded 1, which would imply that women on average had more than one first birth, which is impossible. This above effect is caused by changes in the tempo of childbearing. During years in which women delay childbearing, fertility rates are depressed; and in years when childbearing is accelerated, fertility is raised. The TFR therefore, incorporates not only changes in the number of children that women have, but also the rate at which women have children. These changes are primarily period, rather than cohort based changes in fertility. They affect childbearing at all ages. Quantum effects often affect childbearing at the higher ages, because cohorts generally reduce their fertility by reducing childbearing at higher birth orders and therefore at higher ages. Bongaarts and Feeney assume that fertility may be influenced by period, age, parity, and duration since last birth, but not by cohort. Under this condition, the TFR that would be observed in a given year had there been no change in the timing of births during that year may be estimated by the following equation: TFR`i = TFRi /(1 ri) Where TFRi is the observed TFR in any given year, ri is the change in the mean age at childbearing at order i between the beginning and end of the year, and TFR`i is the TFR that would have been observed had there been no change in the timing of births. The adjusted TFR is given by: TFR` = Ó TFR`i Bongaarts and Feeney test their formula on data from the U.S. and Taiwan. In the U.S. between 1950 and 1962, declining age at childbearing pushed the unadjusted total fertility well above the adjusted values. From 1963 through 1987, increasing age at childbearing pushed unadjusted total fertility below the adjusted values. The age of childbearing is a weighted average of the mean age at childbearing for different parities, i. In Taiwan, from the mid-1970s to the early 1990s, the mean age at birth of all orders was rising, so that the tempo effects in the 1970s and 1990s amounted to about 0.25 births per woman, and 0.4 births in the 1980s. Absent of tempo changes, fertility would have been close to replacement level. A comparison between the cohort fertility rates and the adjusted TFR shows that they do follow each other closely, implying that the adjusted TFR is a good measure.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=On_the_Quantum_and_Tempo_of_Fertility&diff=2737On the Quantum and Tempo of Fertility2009-11-17T00:35:32Z<p>WisconsinDemographyPrelimAugust2009: </p>
<hr />
<div>{{Summary<br />
|title=On the Quantum and Tempo of Fertility<br />
|authors=Bongaarts, John, Feeney, Griffith<br />
|summary=The standard measure of the total fertility rate (TFR) used in demographic measure is a summary measure that can change for a variety of reasons. The TFR is composed of birth-order components, such as the first-order component (TFR1), which gives the average number of first births women would have by age 50 if they were to bear first births at the age-specific rates observed in a given year or period. The sum of all of the order components equals the total TFR. During the late 1940s and early 1950s the TFR1 exceeded 1, which would imply that women on average had more than one first birth, which is impossible. This above effect is caused by changes in the tempo of childbearing. During years in which women delay childbearing, fertility rates are depressed; and in years when childbearing is accelerated, fertility is raised. The TFR therefore, incorporates not only changes in the number of children that women have, but also the rate at which women have children. These changes are primarily period, rather than cohort based changes in fertility. They affect childbearing at all ages. Quantum effects often affect childbearing at the higher ages, because cohorts generally reduce their fertility by reducing childbearing at higher birth orders and therefore at higher ages. Bongaarts and Feeney assume that fertility may be influenced by period, age, parity, and duration since last birth, but not by cohort. Under this condition, the TFR that would be observed in a given year had there been no change in the timing of births during that year may be estimated by the following equation: TFR`i = TFRi /(1 ri) Where TFRi is the observed TFR in any given year, ri is the change in the mean age at childbearing at order i between the beginning and end of the year, and TFR`i is the TFR that would have been observed had there been no change in the timing of births. The adjusted TFR is given by: TFR` = Ó TFR`i Bongaarts and Feeney test their formula on data from the U.S. and Taiwan. In the U.S. between 1950 and 1962, declining age at childbearing pushed the unadjusted total fertility well above the adjusted values. From 1963 through 1987, increasing age at childbearing pushed unadjusted total fertility below the adjusted values. The age of childbearing is a weighted average of the mean age at childbearing for different parities, i. In Taiwan, from the mid-1970s to the early 1990s, the mean age at birth of all orders was rising, so that the tempo effects in the 1970s and 1990s amounted to about 0.25 births per woman, and 0.4 births in the 1980s. Absent of tempo changes, fertility would have been close to replacement level. A comparison between the cohort fertility rates and the adjusted TFR shows that they do follow each other closely, implying that the adjusted TFR is a good measure.<br />
|journal=Population and Development Review<br />
|pub_date=1998<br />
|journal_volume=24<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Variation_in_Vital_Rates_by_Age,_Period,_and_Cohort&diff=2734Variation in Vital Rates by Age, Period, and Cohort2009-11-17T00:22:00Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:59</p>
<hr />
<div>{{Summary<br />
|title=Variation in Vital Rates by Age, Period, and Cohort<br />
|authors=Wilmoth, John R.<br />
|journal=Sociological Methodology<br />
|summary=Notes: The analysis of age-specific vital rates is studied, and special attention is given to the problem of decomposing an array of rates into factors related to age, period, and cohort. A complete, symmetric decomposition of the data array into age, period, and cohort components is not attempted. Instead, the paper focuses on the age and period dimensions and derives an initial description of the matrix's structure with regard to changes only in those 2 directions. This 2-dimensional description is then augmented by a consideration of residual patterns that seem clearly linked to cohorts. The use of a model that is asymmetric in age, period, and cohort is justified by a detailed discussion of the problems of identification in models involving perfectly collinear independent variables. An important conclusion is that traditional modeling approaches that treat age, period, and cohort in a symmetric fashion are fundamentally flawed. This is an icky paper that I basically did not understand that attempts to decompose mathematically large arrays of age-specific mortality rates into separate age, period, and cohort components. Sorry I am not more helpful. Feel free to read it and explain it to me!<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=The_future_of_human_longevity:_A_demographer%27s_perspective&diff=2735The future of human longevity: A demographer's perspective2009-11-17T00:22:00Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:22:00</p>
<hr />
<div>{{Summary<br />
|title=The future of human longevity: A demographer's perspective<br />
|authors=Wilmoth, John R.<br />
|pub_date=1998<br />
|journal=Science<br />
|journal_volume=280<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Retirement_Against_the_Demographic_Trend:_More_Older_People_Living_Longer,_Working_Less,_and_Saving_Less&diff=2736Retirement Against the Demographic Trend: More Older People Living Longer, Working Less, and Saving Less2009-11-17T00:22:00Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:22:00</p>
<hr />
<div>{{Summary<br />
|title=Retirement Against the Demographic Trend: More Older People Living Longer, Working Less, and Saving Less<br />
|authors=Wise<br />
|journal=Demography<br />
|summary=Notes: The American population is aging rapidly and individuals are living longer. Yet Americans are saving less and older workers are leaving the labor force at younger and younger ages. In spite of the rapid aging of the population and the increase in life expectancy, the labor force participation of older Americans has decreased dramatically over the past 3 or 4 decades. The accelerated drop in labor force participation corresponds roughly to the introduction of Social Security and the adaption of employer-provided pension plans. Wise has illustrated that Social Security and employer provided pension plans provide substantial incentive to leave the labor force early. The quantitative effect of this inducement is illustrated by simulating the effects of changes in pension plan and Social Security provisions on the retirement decisions of employees in a large firm, who are covered by a typical defined benefit plan. Scheduled Social Security changes (increasing retirement age to 67, early retirement remains at 62) would have little effect on the retirement decisions of employees with a typical defined benefit pension plan like the one considered here. But if the pension plan provisions were changed to correspond to the Social Security changes, the effect would be very large. And, although not contemplated by current legislation, it is clear that an increase in the Social Security early retirement age would have a substantial effect on the early retirement rates of the large number of employees not covered by a pension plan. Health status is also an important determinant of retirement, and the effect of health status may interact with the effect of pension plan provisions. Available data also suggest that employer-provided retiree health insurance may facilitate early retirement and the insurance effect may, in turn, interact with health status and with pension plan provisions. Wise also emphasizes that personal saving cannot explain the trend toward earlier departure from the labor force. Indeed, low personal saving magnifies the pressure that population trends place on the Social Security system.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Social_Change_and_Mortality_Decline:_Women%27s_Advantage_Achieved_or_Regained%3F&diff=2725Social Change and Mortality Decline: Women's Advantage Achieved or Regained?2009-11-17T00:21:59Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:59</p>
<hr />
<div>{{Summary<br />
|title=Social Change and Mortality Decline: Women's Advantage Achieved or Regained?<br />
|authors=Vallin, Jacques<br />
|pub_date=1993<br />
|summary=Notes: Part of the excess mortality of men has always been considered to be biological. However, in many past populations and present high-mortality populations, it is often found that life expectancies at birth for the 2 sexes are nearly equal or that women suffer from an excess mortality, which reduces their life expectancy below that of men. Many demographers have argued that, at the outset of life, women are biologically superior to men. Estimates of women's inborn biological life expectancy advantage range from about 2 to 6 years. The 2 year estimate, by Pressat, is related to the difference in mortality between boys and girls during the 1st year of life in the West, a seemingly purely biological difference, which would, in the long run, produce a 2-year difference in life expectancy. In spite of women's innate advantage, in the past they have generally suffered higher mortality than men. This continued to be true until recently in the less developed countries due to maternal mortality and mortality at young ages (girls were give less care, and standards of hygiene and nutrition for them were lower as the result of an anti-feminist ideology, which regarded them as being intrinsically less valuable). In the 20th century, women's status has increased greatly. Moreover, considering recent changes in mortality women have more than merely regained their original advantage. Using data on major cause of mortality for women and men, Vallin finds from 1925 to 1929, male's higher mortality at young ages was due to infectious diseases. The reduction in the excess mortality of young women (about age 15 to 50) was caused by a trade-off between their excess mortality from infectious diseases, neoplasms, and degenerative diseases, and men's excess mortality from accidents and suicide. At ages above 55, all cause groups contributed to the excess mortality of men, but the main contribution to the difference between life expectancies came from deaths from infectious and degenerative diseases. By 1974-1978, there is no longer an excess of mortality of women in any age-cause group. In the case of infant mortality, the contribution made by deaths from hereditary and congenital diseases has become predominant and confirms that, during the first year of life, the excess mortality of boys is due almost entirely to genetic causes. In the 20s, higher male mortality is due to violence. In later life, death from malnutrition, neoplasms, and degenerative diseases, are the major contributors to higher male mortality which may be due to male-female differences in smoking, drinking, industrial pollution, and generally less healthy conditions of life for males (although there has been some convergence in these behaviors, which of course doesn't explain the increase in the male-female mortality differences). Vallin argues that women's inferior status in the past was not entirely disadvantageous because they were afforded some degree of protection. Moreover, some aspects of this protection have remained which Vallin considers to be related to women's attitudes towards life and society. Even regarding risk behaviors, women's particular behavior is less risky (i.e., they smoke fewer cigarettes a day). Moreover, their occupational distribution places them in fewer low-grade, physically demanding occupations. Finally, in general, women's attitudes to their bodies, their health, and life in general are very different from those of men. Women engage in fewer risky activities, take greater care of their health and their bodies, and are increasingly more educated than men.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Europe%27s_Second_Demographic_Transition&diff=2726Europe's Second Demographic Transition2009-11-17T00:21:59Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:59</p>
<hr />
<div>{{Summary<br />
|title=Europe's Second Demographic Transition<br />
|authors=van de Kaa, Kirk<br />
|summary=Notes: Europe's second demographic transition began around 1965. Its principal feature is the decline in fertility from somewhat above replacement level to a level well below replacement. Barring immigration, population numbers will begin to decline. In contrast to the first demographic transition, mortality and immigration have not played a role in the transition. The first demographic transition was indirectly caused by industrialization, urbanization, and secularization. It meant the disappearance of the Malthusian pattern of family formation. The age at marriage declined and so did the number of people who remained permanently single. In contrast, the indirect determinants of the second demographic transition cannot be summed up so neatly. In these societies, one's standard of living is determined by one's level and quality of education, degree of commitment to societal goals, and motivation to develop one's talents. Getting married and/or having children may involve considerable opportunity costs, most often for the female partner. Some researchers see growing secularization and the trend toward greater self-fulfillment and individualism as the underlying cause of low fertility. Some researchers see a dichotomy in Western society between progressiveness and conservatism. Between 1965 and 1986 approval for outside employment for mothers of school-age children, voluntary childlessness, cohabitation, and living-apart-together all increased. In 11 surveys in the six original EEC countries, a shift toward more progressive attitudes was evident. This shift is not independent of socioeconomic conditions, but is also insensitive to economic recessions and crises. This shift appears to have a momentum all of its own. Van de Kaa warns that pronatalist measures are likely to be unsuccessful unless they take into account the trend toward individualism. The demographic transition has involved a shift from marriage towards cohabitation, from children to adult as the focus of the family, from contraception to prevent unwanted births to a conscious decision about whether or not to have a child, and from uniform to diversified families and households. Premarital intercourse has increased steadily from cohort to cohort. These changes in behavior preceded changes in attitudes about premarital sex, therefore early on many couples legitimated their relationships through marriage, leading to a decline in the average age at marriage. Before the 1960s effective contraceptives were not readily available, so unwanted children continued to be born. However, by the early 1970s effective contraceptives were available and abortion laws were changing making fertility control possible. Increased sterilization also occurred, further reducing the number of unwanted births of higher orders. Changes in divorce laws allowed divorce to occur more frequently. Because people were able to delay childbearing, the necessity of marrying early declined and the average age at marriage increased. After awhile the pressure to marry began to decline as well, and rates of ever married declined and rates of unmarried childbearing increased. Only Denmark and Sweden have completed this transition, but several other Northern and Western European countries follow close behind. Greece, Malta, Spain, Portugal, and Yugoslavia follow behind these countries. In these countries, fertility decline has been less marked. Six Eastern European countries follow these three, while Iceland, Ireland, Albania, and Tunisia have been late completing the firs demographic transition and follow far behind the other countries in the second demographic transition. As of 1984/85 TFR were above 2.1 in only Ireland, Malta, Poland, Albania, Turkey, and the USSR. The TFR of the Federal Republic of Germany for 1984/85 was 1.29. In Eastern Europe, decline in the TFR began after a brief postwar baby boom and was generally marked between 1950 and 1965. In 1965, nearly all of the countries in Northern, Western, and Southern Europe had a TFR above 2.50. Fertility trends have been irregular in Eastern Europe. In five countries brief rises occurred due to governmental pronatalist measures. Poland appears to have experienced a spontaneous increase in the 1980s. In Denmark and Sweden fertility has exhibited an upswing since 1983. Women under age 25 have contributed a declining proportion of births to the TFR. The share of third and higher order births has declined almost everywhere, particularly after 1965. In some Northern and Western European countries the share of third and higher order births has increased due to the declining number of first and second births. In Northern, Western, and Southern Europe third or higher order births make up 20-25% of total births. In 1984 in Denmark, Norway, the UK, France, and the Federal Republic of Germany first births make up 45% of total births, while second births make up 35-37% of all births. Proportions are more varied in Eastern Europe, most likely because of governmental intervention.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Aging._It%27s_never_too_late&diff=2727Aging. It's never too late2009-11-17T00:21:59Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:59</p>
<hr />
<div>{{Summary<br />
|title=Aging. It's never too late<br />
|authors=Vaupel, James W., Carey, James R., Christensen, Kaare<br />
|pub_date=2003<br />
|journal=Science<br />
|journal_volume=301<br />
|summary=Notes: Age-specific death rates are needed for age-specific info not found in survival curves. ASDRs are strongly subject to current conditions and behaviors as they show in the natural experiment of the German reunification. Even mortality at old age is plastic. Health intervention at old age can significantly increase survival.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Heterogeneity%27s_ruses:_Some_surprising_effects_of_selection_on_population_dynamics&diff=2728Heterogeneity's ruses: Some surprising effects of selection on population dynamics2009-11-17T00:21:59Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:59</p>
<hr />
<div>{{Summary<br />
|title=Heterogeneity's ruses: Some surprising effects of selection on population dynamics<br />
|authors=Vaupel, James W., Yashin, Anatoli I.<br />
|pub_date=1985<br />
|journal=The American Statistician<br />
|journal_volume=39<br />
|summary=Notes: The article begins with a brief description of hazard rates (i.e., a cohort's rate of death or exit) and the observation that only two homogeneous subpopulations are necessary to illustrate many of heterogeneity's ruses. For instance, given a situation in which the hazard rate for subpopulation 1 is constant (i1) and higher than subpopulation 2 (i2-also constant), the mean hazard rate for the entire population will decrease steadily over time and eventually converge with the lower hazard rate (i.e., i2). So, the observation that recidivism rates for released convicts decline over time may not in fact be due to a declining propensity to commit crime. Rather, if heterogeneity is present in the simple form of one group of reformed and another group of incorrigibles, then declining recidivism rates might simply be a reflection of the higher death rate (i.e., imprisonment) of the incorrigibles. Another ruse of heterogeneity may occur when i(c)-the mean hazard for a cohort- increases steadily, drops suddenly for a brief period, and then resumes climbing, but at a slower rate. This trajectory is produced when two subcohorts have different but constantly increasing hazard rates. The cohort with the higher mortality rate is frailer, and hence becomes extinct more quickly. As the frail cohort dies out, the hazard rate drops toward the more robust cohort. When the cohort's hazard rate begins to approach the more robust cohort's hazard rate, it begins to rise again at a rate that is dominated by the robust cohort. Thus, the appearance of falling mortality within a cohort is in fact an illusion, a ruse. The mover-stayer model presents another example of a ruse introduced by heterogeneity. Assume that one subpopulation is immune to divorce (i.e., stayers) while another has a constantly increasing hazard of divorce (i.e., movers). If the hazard for the susceptible subpopulation is steadily increasing, then . . . the observed hazard for the entire population may rise and then fall. . . Does this imply that marriages are shakiest after a few years of marriage? Not necessarily . . . The same basic effect can be produced even if one group is not immune but simply at low risk. Indeed the rising-falling pattern can be produced if the hazard steadily increases for the high-risk group but steadily decreases for the low-risk group. For one group, marriages strengthen with duration, while for the other, marriages weaken-despite the appearance of the cohort curve, there is no 'seven-year itch' (p. 178). One final example: Mortality crossovers may occur when robust subcohorts from two populations (e.g., white and black robust) face equal mortality chances, but frail subcohorts face unequal chances (e.g., i-white frail < i-black frail). In such a scenario, the total black hazard is initially greater than the total white hazard due to the influence of frail blacks. But, since the frail black subcohort dies out relatively quickly, only the robust black subcohort remains. Since more of the frail white subcohort survives to later ages, it weights the total white hazard rate upward-resulting in a mortality crossover in which the total black hazard is lower than the total white hazard. Conclusions: Heterogeneity may threaten research conclusions, even when care is taken to eliminate population differences (e.g., via randomization). When should a researcher suspect substantial heterogeneity? A useful clue occurs when theory and evidence pertaining to individuals suggest a trajectory of mortality that diverges from the observed trajectory for the population. For instance, human mortality may increase exponentially, but observed mortality curves appear to level off at advanced ages: the discrepancy suggests heterogeneity (p. 184).<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Between_Zeus_and_the_Salmon:_The_Biodemography_of_Longevity&diff=2729Between Zeus and the Salmon: The Biodemography of Longevity2009-11-17T00:21:59Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:59</p>
<hr />
<div>{{Summary<br />
|title=Between Zeus and the Salmon: The Biodemography of Longevity<br />
|authors=Wachter<br />
|pub_date=1997<br />
|summary=Notes: Theories of Longevity Evolutionary theory of senescence: natural selection clears away genes that compromise reproduction or survival to and through ages of reproduction but leaves genes with bad effects at older ages alone. Mutation-accumulation theory: mutations deleterious to survival at older, postreproductive or postnuturant ages should accumulate over eons, since selection is not clearing them away. Antagonistic pleitropy: there are genes that have positive effects on net reproduction and negative effects on postreproductive survival, similar to disposable soma theory (Kirkwood 1977) in which organisms allocate energy between functions of reproduction and maintenance. Hayflick limit: certain types of mammalian cells transplanted to cultures only divide up to a limited # of times. Vaupel's more optimistic view: the same mechanisms built in to guarantee fail-safe completion of the reproductive mission may endow the body with residual post-completion life; preadaption the system honed by evolution to solve one problem turns out, serendipitously, to be a full-fledged good start on the solution to another problem. Empirical Challenges 1.) Hazard functions measured at extreme ages in large population from several profoundly different species do not rise indefinitely with age. In some other cases, they rise, but at decreasing rates. 2.) Human death rats in some developed societies are falling, even among the oldest-old. 3.) Selective breeding of flies, mice, and other laboratory animals has shown an extraordinary plasticity of life span in the face of selection. 4.) From studies of Drosophilia and nematodes on the relationship between heterogeneity and hazard rates at extreme ages...the observed levels of hazards at advanced ages is not produced solely by the selective effect of genetically frailer individuals dying earlier, leaving genetically more robust individuals to die at lower rates at later ages; the leveling occurs in pure-bred strains, among populations of individuals who are nearly genetically identical. The Elderly in Nature There are exceptional cases of postreproductive survival. Intergenerational transfers are also important. For example, menopause might have evolved in response to tradeoffs favoring the cessation of one's own reproduction and the channeling of effort into protecting and endowing the reproductive changes of one's offspring. Theoretical Departures Explorations of homeostatic feedback (both demographic and biological) and fluctuating environments (e.g., benefiting postponing fertility, etc.) are departing from older evolutionary theories of longevity. There also appears to be a historically contingent character of evolutionary change. Evolution may be selecting for plasticity of response to times of fest and times of famine, rather than for optimum vigor under fixed conditions.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Sex_Differences_in_Infant_and_Early_Childhood_Mortality:_Major_Causes_of_Death_and_Possible_Biological_Causes&diff=2730Sex Differences in Infant and Early Childhood Mortality: Major Causes of Death and Possible Biological Causes2009-11-17T00:21:59Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:59</p>
<hr />
<div>{{Summary<br />
|title=Sex Differences in Infant and Early Childhood Mortality: Major Causes of Death and Possible Biological Causes<br />
|authors=Waldron<br />
|pub_date=1996<br />
|summary=Notes: In developing countries, males have consistently higher mortality than females during the neonatal period. Sex differences in mortality are more variable during the post-natal period of infancy, and by early childhood, females have higher mortality than males in many developing countries. That shift from a consistent male excess to more variable sex differences in mortality is due in part to a shift with age in the major causes of death that contribute to total mortality. In the neonatal period, excess male mortality is due to perinatal conditions. In addition, males generally have higher mortality for congenital anomalies, which makes an additional but modest contribution to higher male neonatal mortality. During early childhood, infectious diseases and accidents are the biggest contributors to sex differences in mortality. Boys have higher accident mortality than girls in almost all countries. This finding may be related to the prenatal exposure of males to higher levels of testosterone which are reinforced by differences in the socialization in most cultures. Within the categories of congenital anomalies and infectious diseases, sex differences are variable. Males have higher mortality risk than females from many types of congenital anomalies, but females have higher mortality risk from congenital anomalies on the central nervous system. Sex differences in infectious disease mortality vary with age group, environmental conditions and specific type of infectious disease. In infancy, males generally have higher mortality than females from mortality types of infectious disease, whereas for young children sex differences are more variable and appear to be influenced by environmental factors, such as discrimination against females. For measles, females have tended to have higher mortality than males. The biological factors that contribute to sex differences in various causes of death are diverse, and to date only poorly understood. Consistently higher male mortality for perinatal conditions is most likely due to inherent biological disadvantages. Biological disadvantages for males may include greater risk of birth at younger gestational ages, greater immaturity of males' lungs at given gestational age, and other factors that have not yet been identified. It appears that ht biological disadvantages for males are sufficient to outweigh one well-established male advantage their higher birthweights. The causes of sex differences in congenital anomalies mortality are poorly understood, but it appears that they are influenced by multiple sex differences in development, some of which favor females and others males. It appears likely that inherent sex differences in biology contribute to sex differences in infectious disease mortality, although evidence is limited and inconsistent. Immune resistance among males may be reduced by X-linked genetic defects; however, they are very rare. Immune function among males may also be inhibited by exposure to testosterone during the prenatal period and early infancy; however, the mechanism is unclear. In general, males may have inherent disadvantages in resistance to infectious disease, but additional evidence will be required to evaluate the extent and nature of the male disadvantage in different age groups, for different types of infectious disease and under different environmental circumstances. Available evidence suggests that males have inherently greater vulnerability for mortality due to perinatal conditions and for total mortality in the neonatal period, but the assumption that males have a pervasive inherent disadvantage is incorrect for some types of congenital anomalies, and is of uncertain validity for infectious diseases and total mortality in early childhood.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=How_Many_Americans_Are_Alive_Because_of_Twentieth-Century_Improvements_in_Mortality%3F&diff=2731How Many Americans Are Alive Because of Twentieth-Century Improvements in Mortality?2009-11-17T00:21:59Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:59</p>
<hr />
<div>{{Summary<br />
|title=How Many Americans Are Alive Because of Twentieth-Century Improvements in Mortality?<br />
|authors=White, Preston, Samuel H.<br />
|pub_date=1996<br />
|summary=Notes: Introduction: Because of rapid mortality decline during the twentieth century, life expectancy in the U.S. increased from 47.3 years in 1900 to 75.7 years in 1994. In this article, White and Preston estimate the number of Americans currently alive who literally owe their lives to health progress. This calculation involves comparing the actual population to a hypothetical population in which mortality improvements did not occur (p. 416). Methods: To estimate what the population of 2000 would look like without the twentieth-century mortality improvements, the population of 1900 is projected forward using the U.S. life table of 1900. We use the standard component method of projection in five-year intervals of time and age. . . The rates of fertility and volume of immigration are assumed to be unaffected by the level of mortality. . . (p. 416). The number of immigrants are estimated for each period and projected forward using U.S. fertility and mortality rates. In addition to the two main time series, one that uses actual demographic circumstances and one that keeps mortality fixed at 1900 levels, we apportion the difference between these two by generation. For example, people alive in 1905 because of health advances between 1900 and 1905 can be identified by age and sex. This hypothetical group is then projected forward to 2000 under actual conditions of fertility and mortality. Their offspring are people who would not have been born if mortality had not improved in the first five years of the century. . . The size and traits of each of these hypothetical populations in 2000 enable us to disentangle by 'generation' the persons living by virtue of twentieth-century mortality declines. (p. 417). Data are taken from a variety of sources, including the Social Security Administration, Census Bureau, and published studies which attempt to correct flawed national statistics on deaths, population and fertility from 1900 forward. Results: If mortality had remained at 1900 levels throughout the century, holding everything else constant, the population in the year 2000 would be almost exactly half its actual size: 139 million people instead of 276 million. Half of Americans living today can attribute their being alive to mortality improvements in the twentieth century. . . Mortality reductions during the first half of the century had a much larger impact on population size in 2000 than did reductions during the second half. If mortality rates beyond 1950 were fixed at 1950 levels, the US population in 2000 would still be 94 percent of its actual size, compared to 50 percent if mortality were fixed in 1900. Mortality declines in the first half of the century were concentrated in childhood and young adulthood. Hence their impact cumulated as those whose deaths were prevented bore children (p. 420-422). Half of the hypothetically dead in 2000 are direct deaths (i.e., people who would have died without mortality improvements), but half are indirect deaths-people who never would have been born. Direct deaths are concentrated at ages above 75, whereas indirect deaths are concentrated below age 30. The structure of the population was not greatly affected by the mortality decline, except at young and particularly at old ages. As a result, the actual mean age of the population in 2000 is only .8 years greater than the projected mean age. Mortality reductions in the age interval 0-14 were responsible for 67 percent of the difference in size between the actual population and the hypothetical population. This demonstrates that saving lives at younger ages affects population growth via subsequent fertility. Finally, the sex ratio [male to female] for the entire population would have been 1.01 under 1900 mortality conditions, not the actual value of .98. This small change masks much larger changes in certain age intervals, which counteract one another for the total population. The actual sex ratio of .38 at ages 85 and up would have been .69 in the absence of twentieth-century mortality decline. . . Improvements in infant and childhood mortality have worked in the opposite direction, however. In 1900, 15 percent of males but only 12 percent of females died before their first birthday. Fewer, than 1 percent of each sex now dies in infancy. . . (pp. 427-428). This indicates that mortality improvements have disproportionately benefitted males at younger ages and females at older ages. Conclusions: Half of the population would not be alive in the absence of mortality improvements, including seven-eighths of women over age 84. The greater survival of people at very young and very old ages increased the dependency ratio by 22 percent. And women are a majority of the population because of mortality declines (p. 427).<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Race_and_health:_basic_questions,_emerging_directions&diff=2732Race and health: basic questions, emerging directions2009-11-17T00:21:59Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:59</p>
<hr />
<div>{{Summary<br />
|title=Race and health: basic questions, emerging directions<br />
|authors=Williams, David R.<br />
|pub_date=1997<br />
|journal=Annals of Epidemiology<br />
|journal_volume=7<br />
|summary=Notes: Racial categories are sociopolitical constructs and do not reflect genetic homogeneity. Nonetheless, use of racial categories captures real differences due to social inequality and racial stratification. Race is a fundamental organizing principle of society, and, therefore, affects all aspects of peoples' lives. Williams promotes the following framework for studying the relationship between race and health: BASIC CAUSES-> SOCIAL STATUS-> SURFACE CAUSES-> BIOLOGICAL PROCESSES-> HEALTH STATUS The basic causes are interrelated culture, biology/geography, economic structure, and political/legal factors (as well as racism). According to Williams, social inequality will produce new intervening mechanisms, even when more proximate health causes change, to maintain the status quo. Someone else's summary: This paper aims to (i) examine the scientific consensus on the conceptualization and meaning of race; (ii) outline why health researchers should continue to study race; and (iii) provide guidelines for future health research that can promote an enhanced understanding of the role of race (p. 322). Williams notes that older definitions of race in the social sciences treat it primarily as a biological construct. However, more recent conceptualizations of race in the social sciences tend to reject biological definitions as unscientific. Rather, race is viewed as a sociopolitical construct with strong cultural and ethnic components (p. 323). Williams proceeds to claim that the scientific consensus on race is synonymous with the new social scientific perspective, but that the biomedical and public health view of race (apparently unscientific) maintains that there are important biological elements to racial distinctions. This is problematic, in Williams's view, because the medical view of race may lead to inappropriate diagnoses and treatments. Furthermore, the genetic characteristics which produce racial differences (e.g., skin color) do not typically correlate strongly with morbidity outcomes. Some argue that since race has been delegitimized as a biological construct in the social sciences, it should no longer be included in studies of health. Williams disagrees with such a view, since race captures inequalities inherent in American society. Race is associated with a history of exploitation and oppression in the United States, and the lingering effects of discrimination and prejudice are still present both in structural inequalities (e.g., housing discrimination) and individual attitudes and behaviors. Furthermore, race is an important concept of group allegiances, as evidenced by social psychological research on in-group and out-group formation. Race is also key to understanding the formation of individual identities, particularly in a highly racialized society like the U.S. Finally, it is essential to recognize that race is strongly correlated with morbidity and mortality outcomes in the U.S. Therefore, it should be retained as a master status-a central determinant of social identity and obligations, as well as, of access to societal rewards and resources (p. 326). Williams argues that health studies which use race must become more sophisticated in terms of its measurement. Care should be taken to explore the multidimensional nature of race, and to avoid simplistic categories (e.g., black, white, other). Williams also proposes a conceptual model to serve as a general guide for research on race and health. The model links race and health through a web of structural, behavioral and biological constructs. Along with SES, gender, age and marital status, race is viewed as a form of social status that is affected directly by a host of basic causes (i.e., culture, biology, geographic origins, racism, and economic, political and legal structures). Race has a direct effect on surface causes (e.g., health practices and stress); surface causes effect biological processes (e.g., immune function); and, of course, biological processes affect health status (e.g., morbidity, mental health). Consistent with previous sociological research, Williams argues that policies designed to reduce racial differences in health must address basic causes, since a narrow focus on surface causes cannot redress more fundamental social inequalities.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=The_correspondence_between_intention_to_avoid_childbearing_and_subsequent_fertility:_a_prospective_analysis&diff=2733The correspondence between intention to avoid childbearing and subsequent fertility: a prospective analysis2009-11-17T00:21:59Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:59</p>
<hr />
<div>{{Summary<br />
|title=The correspondence between intention to avoid childbearing and subsequent fertility: a prospective analysis<br />
|authors=Williams, Lindy, Abm, Joyce, Piccinino, L. J.<br />
|pub_date=1999<br />
|journal=Family Planning Perspectives<br />
|summary=Notes: Retrospective studies of pregnancy intendedness have revealed some characteristics that can help identify which women are more likely than others to experience an unintended birth. A comparison of these findings with those from a prospective analysis may shed greater light on the characteristics associated with unintended pregnancy. Data from 1988 NSFG and a telephone reinterview of respondents conducted in 1990 were used in this work. Separate analyses were conducted of women intending to postpone childbearing for at least three years and of women intending to forgo all future childbearing. Logistic regression models were used to identify the effects of social and demographic characteristics, as well as change in marital status and certainty of intentions, on the odds of experiencing a birth in the interval between interviews. The authors find that only 10% of women intending to postpone pregnancy for more than 3 years and 8% of the respondents seeking to forgo future childbearing had a birth in the interval between the interviews (2 years). Low-income women are more likely to experience and unpredicted (unwanted) birth. Race was not significant. Women aged 20-29 were more likely than those aged 30-34 to have an unpredicted birth. Those not using contraception were 2-3 times more likely than women using an effective method to have an unpredicted birth. There are at least two potential explanations for instances where the correlates of unintended births in the prospective analysis differ from those identified in retrospective studies. Certain subgroups of women may be more likely to classify births as wanted when they are asked retrospectively; alternatively, they may be more likely to experience changes in their living conditions that alter their fertility intentions.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Care_of_the_Elderly:_Division_of_Labor_Among_the_Family,_Market_and_State&diff=2714Care of the Elderly: Division of Labor Among the Family, Market and State2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=Care of the Elderly: Division of Labor Among the Family, Market and State<br />
|authors=Soldo, Freedman<br />
|pub_date=1994<br />
|summary=Notes: As a greater proportion of the US population becomes elderly, the prevalence of disability is expected to increase dramatically. With the rise in disability, nonmedical personal care will also need to grow to keep up with the demand for assistance with chronic limitations in basic self-care activities, such as shopping, bathing, dressing, meal preparation and so on. Because nonmedical personal care is nontechnical, no single institution can claim to be singularly competent in the provision of services. This chapter examines three personal sources of personal care in the US: the family, the marketplace and the state. More specifically, the chapter considers how one source of care (e.g., the marketplace) might substitute for another form of care (e.g., the family) as demands for service increase. Substitution of Paid Providers for Family Care: For the most part, the gerontological literature has concerned itself with the substitution of market (or formal) services for family (or informal) care. . . Research on the substitution of formal care for informal care has been motivated by two related concerns. First, demographic trends portend a reduction in the supply of informal helpers, particularly the adult daughters of widowed or older persons, as the family size of the elderly declines in the next century. Second . . . is apprehension . . . if state subsidized home care benefits were to encourage family helpers to withdraw or reduce their efforts in response to a decline in the price of purchased care (p. 200). At present, the bulk of personal care is provided by family members-which is what the majority of elderly prefer. But one in four elderly rely at least in part on paid helpers, and this proportion is expected to rise considerably. Substitution of Financial for Time Transfers: This type of substitution is how the state currently responds to the care of frail elderly. That is, the state typically substitutes its own time (i.e., state employees) with Medicare and Medicaid payments made to private organizations which provide the service. But, due to insufficient data, considerably less is known about the extent to which the family commonly substitutes financial transfers for its collective time. . . Nonetheless, existing data suggest that about one-fifth of the elderly may receive either regular or episodic financial transfers from adult children (p. 207). Economic models which posit motivations for such substitutions (e.g., selfish exchange model in which the adult child may substitute money for time in order to limit close contact by maintaining separate residences), have received mixed empirical support. But, standard economic theory yields the basic insight that the higher the value of the child's time, the more likely she or he is to make a financial rather than a time transfer. As a time pressured society, this may have implications for future trends in this type of transfer. Discussion: At the time of this study, data limitations precluded sophisticated analyses of substitutions. But, Solo and Freedman anticipated that Michigan's Health and Retirement Survey (HRS) and Asset and Health Dynamics (AHEAD) would help fill some research gaps.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Marriage_Markets_and_nonmarital_fertility&diff=2715Marriage Markets and nonmarital fertility2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:58</p>
<hr />
<div>{{Summary<br />
|title=Marriage Markets and nonmarital fertility<br />
|authors=South, Scott J., Lloyd, Kim M.<br />
|pub_date=1992<br />
|journal=Demography<br />
|journal_volume=29<br />
|summary=Notes: The authors merge census microdata with vital statistics data to examine the effect of women's marriage opportunities on nonmarital fertility rates and ratios across 75 U.S. metropolitan areas. The data for this study comes from two sources: the National Center for Health Statistics (NCHS) data files on births occurring in 1980 and 1981 and the Public Use Microsamples (PUMS) of the 1980 U.S. Census. Using the NCHS data, births are tabulated by women's marital status (married or unmarried), race (white or black), age, education (years completed: 0-11, 12, or 13 or more), and metropolitan area of residence. The numbers are weighted according to the NCHS sampling frame. The data for 75 of the 100 largest SMSAs are included in the analysis. The PUMS data is used to determine the denominators for the birth rate for the above groups, and to construct a measure of 'suitable' marriage opportunities available to each category of women, where 'suitability' entails that prospective husbands and wives be currently unmarried, belong to the same race, and live in the same metropolitan area. The authors also weight the number of unmarried men (and the women available to them) by the proportional distribution of marriages in the entire U.S. occurring to those women (and men) in 1980. The variable used in the analysis is then the ratio of suitable men to suitable women. Other variables included in the analysis were the percentage of men in the numerator who report that they were not employed, AFDC payments per family, race-specific male and female median incomes for year-round full-time workers, SMSA population size, the percentage of SMSA residents who live in the central city or cities, and a dummy for being located in the South. Measures of the quantity and 'quality' of marriageable men simultaneously specific for women's age, race, education, and place of residence reveal especially poor marriage prospects for highly educated black women. The effect of mate available on nonmarital fertility is generally modest. Among white women, marriage opportunities are associated inversely with the nonmarital fertility rate, perhaps reflecting an increased likelihood that a premarital conception will be legitimated. Marriage opportunities also reduce nonmarital fertility ratios for young black and white women. The nonmarital fertility rate is lower among women whose marriage pool includes a large percentage of nonemployed males. Only a small proportion of the racial differences in nonmarital fertility appears attributable to differences in the marriage markets of black and of white women.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Age_at_last_birth_and_its_components&diff=2716Age at last birth and its components2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:58</p>
<hr />
<div>{{Summary<br />
|title=Age at last birth and its components<br />
|authors=Suchindran, C. M., Koo, H. P.<br />
|pub_date=1992<br />
|journal=Demography<br />
|summary=Notes: This paper examines the ways in which the behavior of twentieth century cohorts of American women changed simultaneously in the three components of fertility that determine age at last birth–age at first birth, spacing between subsequent births, and parity progression ratios of subsequent births–to produce changes in the timing of the completion of childbearing. It decomposes changes in the mean age at last birth among cohorts and between whites and nonwhites to changes in these three components. They use fertility rates available from vital statistics data. They covered the cohorts of 1903 to 1940 and they projected each age component of age at last birth for these cohorts, under the assumption that these cohorts would experience the fertility rates of the calendar year 1986. Results show that only ages at first birth consistently contributed to changes in age at last birth in the same direction. In general, the cohorts increased and decreased their age at first birth, birth intervals, and parity progression ratios of lower and higher birth orders in almost every possible combination so as to achieve a relatively young age at final birth. It is interesting to note that the mean age at last birth was 30.9 for the 1903 cohort, rose to 32 for the 1917 cohort and decreased rapidly to 28.2 projected to the 1943 cohort. These are relatively young mean ages. Just to give an idea the mean age at last birth in developing countries in the 1970's and 1980s were estimated in 39.5 for African countries, 36.9 in Latin America and 39 for the Middle East.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Mortality_in_England_in_the_Eighteenth_and_Nineteenth_Centuries:_A_Reply_to_Sumit_Guha&diff=2717Mortality in England in the Eighteenth and Nineteenth Centuries: A Reply to Sumit Guha2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:58</p>
<hr />
<div>{{Summary<br />
|title=Mortality in England in the Eighteenth and Nineteenth Centuries: A Reply to Sumit Guha<br />
|authors=Szreter<br />
|pub_date=1994<br />
|summary=Notes: This article is a response to Guha's critique of Szreter 1988 (in the 663 syllabus), which, of course, busts on McKeown. (Not a direct quote from the article!) Szreter's responses to Guha's 4 main critiques are: 1. According to Szreter, Guha claims that Szreters's thesis is that urban mortality in any time or place can only improve through medical or sanitary interventions. Szreter points out that his emphasis on public health measures in the later 19th and 20th centuries was period-specific. It is central to Szreter's (1988) argument that an 18th-century decline in mortality was curtailed by the new health dangers arising from an unprecedented rapidity of provincial urban growth in centers of industry, even resulting in the appearance of new kinds of disease; the disease ecology of urban England was very different in the 19th and 18th centuries. 2. Guha supports McKeown's thesis regarding standards of living and criticizes Szreter (1988) regarding the epidemiological record of respiratory TB in 19th century. However, as Szreter points out, there was no net rise in real wages in London from the 1740s to 1840s, which according to McKeown and Guha was associated with a drop in respiratory TB due to nutritional improvements. Moreover, there was a substantial absolute rise in fatal incidence of bronchitis/pneumonia/flu at the time, which Guha confirms. Moreover, the drop in respiratory TB didn't start until 1867. 3. Guha supports McKeown's analytical framework, distinguishing between those factors related to initial exposure to the micro-organisms, those related to an individual's contraction of disease symptoms, and those related to a fatal outcome. Szreter argues that although these can be formulated in language as three separable logical gates, it is not legitimate to assume that their empirical outcomes are causally independent of each other. In another misleading representation of Szreter, Guha argues that Szreter's (1988) argument was disproved by its supposed failure to account for the historical course take by infantile diarrhea mortality. However, Szreter (1988) states in his argument that such mortality is due to personal and domestic hygiene rather than classic sanitation. Therefore, it does not contradict the reduction of other infectious diseases related to improvements in public health. The continued prevalence of diarrheal diseases signified the limit of what was achievable at the strategic level alone, without a more probing and comprehensive form of social intervention against mortality, such as the public health movement, politicians, and the populace at large were finally developing around the turn of the century<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Socio-Economic_and_Cultural_Differentials_in_the_Mortality_of_Sub-Saharan_Africa&diff=2718Socio-Economic and Cultural Differentials in the Mortality of Sub-Saharan Africa2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:58</p>
<hr />
<div>{{Summary<br />
|title=Socio-Economic and Cultural Differentials in the Mortality of Sub-Saharan Africa<br />
|authors=Tabutin, Akoto<br />
|pub_date=1992<br />
|summary=Notes: Introduction: This paper reviews evidence on socioeconomic differentials in child mortality in sub-Saharan Africa and conducts an analysis of World Fertility Survey data. Socioeconomic Differentials: (1) Education: Everywhere, mortality falls as expected, more or less strongly and more or less rapidly, with an increase in the mother's education (p. 33). However, the effects of education also vary by country and age of child-educational differentials in mortality are greatest between the ages of 1-5. Father's education also has an effect, but it is typically not as pronounced as mother's education. Interestingly, in Nigeria mother's education can mitigate the deleterious effects of low income, while illiterate mothers with high income suffer relatively high child mortality. (2) Occupation: In Rwanda, The important factor in explaining the level of mortality is whether or not the father is in the agricultural category (p. 40). This basically holds true for the other countries as well, with agricultural workers exhibiting relatively high child mortality, and administrative/professional workers exhibiting relatively low child mortality. (3) Region: Even after controlling for education, large regional differences exist in all countries. This may point to resource endowments or cultural differences. (4) Place of Residence: Overall, in sub-Saharan Africa, large cities enjoy the best situation, with the exceptions of Kenya and Ghana, where child mortality in small cities is appreciably less than in metropolitan areas (p. 45). Rural areas generally have very high excess mortality, presumably due to a lack of resources and medical care. Although cities enjoy an mortality advantage, high rates of inequalities exist within cities. Importantly, Education does not really play a role except in privileged and well-provided zones (p. 48). (5) Effect of Type of Economic Activity of the Wife: Except for Ghana, female family workers showed a clearly excess mortality (p. 49). However, when women worked in clerical positions, their children benefitted from lower mortality than non-working women. (6) Religion: Catholics and Protestants exhibit lower mortality rates than Muslims, who in turn exhibit lower rates than adherents to traditional faiths. However, the introduction of control variables eliminates much of these differences. (7) Ethnicity: Even when control variables are introduced, the effects of ethnicity are strong in all nations. Analysis: A Multiple Classification Analysis of WFS data for Kenya and Cameroon is performed in order to determine the explanatory force of the aforementioned variables. Overall, ethnicity has the most explanatory power (33% in Cameroon and 39% in Kenya), followed by mother's education and father's occupation. Religion is the least significant variable. But some differences were observed between Kenya and Cameroon. For instance, education remained significant in Cameroon after the introduction of control variables, but in Kenya education was determined to be largely a function of place of residence. Conclusions: Of the variables that we used, ethnic group, maternal education, occupation and, to a lesser degree, the place of residence, turned out to be the most important. . . The ethnic group is clearly a variable that must be controlled in studies of mortality as well as in studies of fertility in Africa (p. 62).<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Family_Size_Preferences&diff=2719Family Size Preferences2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:58</p>
<hr />
<div>{{Summary<br />
|title=Family Size Preferences<br />
|authors=Thomson, Elizabeth<br />
|summary=Notes: Family size preferences or desires are conceptually and empirically different from family size ideals, norms, intentions and expectations. Family size preferences or desires are the number of children wanted in one's lifetime. These preferences are unconstrained by economic or subjective factors (McClelland, 1983). PREFRENCES ARE A MEASURE OF DEMAND FOR CHILDREN. Family ideals and norms represent what is desirable for a group of people or a typical group member, rather than what is desirable for every person in the group (SOCIAL NORM). Family size intentions or expectations reflect not only family size preferences but also constraints on one's ability to achieve desired or preferred goals. Measures **fertility preferences: how many children people would like to have in their lifetime (problem is social desirability bias and rationalization of those at the end of childbearing years) or how many more children people would like to have (problem is upward bias by assuming that all previous births were wanted). Issue, spouses may have different preferences. Couple disagreement is a primary source of gaps between desires and intentions. Perception of control over fertility is also important (e.g. those who do not perceive themselves as able to control fertility may intend more children than they desire). BOTH FAMILY SIZE PREFERENCES AND INTENTIONS MAY CHANGE OVER THE LIFE COURSE and are particularly influenced by experiences with prior births. Finally, in some developing countries people give no numerical answer (Up to God).<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=The_value_of_children&diff=2720The value of children2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:58</p>
<hr />
<div>{{Summary<br />
|title=The value of children<br />
|authors=Thomson, Elizabeth<br />
|summary=Notes: The economic value of children is a key component of fertility variation and change. In preindustrial societies, children were an economic benefit from adolescence onward, however, in industrial societies children provide little or no economic value. Children also fulfill psychological needs such as: conferring adult status and social identity; expansion of the self; morality; primary group ties and affiliations; stimulation, novelty, and fun; creativity, accomplishment, competence; power, influence, effectance; social comparison or competition. Childrearing also carries potential psychological costs such as stress and worry. However, recent work has rejected psychological benefits of children as sufficient to explain why people continue to have children. Schoen proposes that children produce social capital for their parents by strengthening ties to kin, linking parents with community resources, and bringing new information, ideas, and social relationships to parental households. Parents also lose social capital because they have less time to devote to other relationships. Economic benefits of children may be enough for parents to want children while social capital and psychological benefits are just added value. Economic value of children can be measured indirectly by estimating the value of children's labor and transfers over the life course, expenditures related to childrearing, and the value of parental time that might otherwise be spent on other activities. However, even if it were possible to measure the true net value of children, parents' perceptions pf those values are what enter into fertility decisions. First order births confer the status of parenthood and adulthood. Relationship stability, parent-child interaction and kin connections are given as primary reasons for becoming a parent. First order children are associated with the highest opportunity costs. The most important value of a second child is to be a sibling to the first. The value of higher order births is primarily economic. Men on average are more concerned with the financial costs and having a son to continue the family name. Women place more importance on the work and strain of raising children, the opportunity costs of children, and the benefits for the marital relationship. Sons are valued for kinship ties and financial assistance, while daughters are valued for household and childcare help. Social and psychological benefits do not appear to differ between sons and daughters. Psychological benefits and costs of children are higher in industrialized and urban settings. Education is inversely related to economic value, while directly associated with emotional value and perceived opportunity costs of parenthood. Increasing economic status is associated with desire for increased child quality. Cultural values may serve as sources of value of children. Religious institutions and beliefs may support the value of children. The relative value of sons and daughters is associated with cultural values on gender. Lesthaeghe identifies ideation change as an independent force underlying current low fertility in Western countries. Perceived economic benefits of children are associated with larger family sizes. Psychological benefits are associated with smaller family size. These relationships are not very strong. Child values can influence only desired fertility. However, when a particular parity progression is specified, when contraception is pervasive, and when precise measures of the expected net value of children are generated, intentions strongly follow actual births.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Contraceptive_practices_and_trends_in_France&diff=2721Contraceptive practices and trends in France2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:58</p>
<hr />
<div>{{Summary<br />
|title=Contraceptive practices and trends in France<br />
|authors=Toulemon, L., Leridon, H.<br />
|summary=Notes: This article looks at trends in contraceptive practices in France between 1978 and 1994. Data is based on a sample of 5,900 households from the 1994 Fertility and Family Survey. Respondents were questioned about their contraceptive use patterns and family formation status. In order to evaluate trends, results were compared to results from two other comparable surveys from 1978 and 1988. Two-thirds of French women used some form of reversible contraceptive method in 1994. Oral contraceptive use has grown steadily in France; 40% of women aged 20-44 reported using the pill alone or combined with another method in 1994, compared with 34% in 1988, and 28% in 1978. Those ages 20-24 were the most likely to use the pill, with 59% reporting use of this method in the past month and 83% reported having ever used the pill. About 58% of these women reported also using the condom, while 32% reported using withdrawal and 12% reported using periodic abstinence. Those aged 45-49 were the least likely to use the pill with 14% reporting use of this method. Condom use has also risen during this period; 8% of women were using condoms alone or combined with another method in 1994, up from 5% in 1988 and 6% in 1978. AIDS prevention campaigns were launched in 1988. Most of the increase in condom use has occurred among younger women. In 1994, 53% of women ages 25-29 and 58% of women aged 20-24 had ever used condoms, increasing from 38% and 23% respectively in 1988. During this same period, the percent of women older than 30 who had ever used condoms remained stable at around 42%. Also in 1994, 83% of men ages 20-24 had ever used condoms, compared with 57% of those between 30 and 39. Condom use was more likely to be used during the early stages of new relationships. Condom use differed by education, profession, and place of residence for women (more educated, white collar and urban). Condom use differed by education for men as well. IUD use has declined from 19% in 1988 to 16% in 1994. This method is most commonly used by women aged 35-44; 26% of these women reported using this method. This is partly because the age range of possible users has narrowed. Medical standards in France do not allow doctors to prescribe IUDs to childless women, because of the risks of infection and subsequent sterility. Because of delayed childbearing, fewer women are eligible to receive IUDs. Both male and female sterilizations remain rare. This is most likely because surgical sterilizations, including voluntary tubal ligations and vasectomies, for contraceptive purposes are considered to be a form of mutilation in France. The typical contraceptive sequence for French women begins with 10 years of pill use, followed by use of IUD. This sequence was reported by half of all women in the 1988 survey. Socioeconomic differentials in use of various methods had disappeared by the 1994 survey.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Contraceptive_Failure,_Method-Related_Discontinuation_and_Resumption_of_Use:_results_from_the_1995_NSFG&diff=2722Contraceptive Failure, Method-Related Discontinuation and Resumption of Use: results from the 1995 NSFG2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:58</p>
<hr />
<div>{{Summary<br />
|title=Contraceptive Failure, Method-Related Discontinuation and Resumption of Use: results from the 1995 NSFG<br />
|authors=Trussell, J., Vaughan, B.<br />
|pub_date=1999<br />
|journal=Family Planning Perspectives<br />
|summary=Notes: Half of all pregnancies in the U.S. are unintended. Of these, half occur to women who were practicing contraception in the month they conceived, and others occur when couples stop use because they find their method difficult or inconvenient to use. Data from NSFG is used to compute life-table probabilities of contraceptive failure for reversible methods of contraception, discontinuation of use for a method-related reason and resumption of contraceptive use. Data indicate that within one year of starting to use a reversible method of contraception, 9% of women experience contraceptive failure 7% of those using pill, 9% male condom and 19% withdraw. During a lifetime of use of reversible methods, a typical woman will experience 1.8 contraceptive failures. Overall, 31% of women discontinue use of a reversible contraceptive for a method-related reason within six months of starting use and 44% do so within 12 months. However, 68% resume use within one month and 76% within 3 months. Using multivariate analyses the authors find that contraceptive failure is elevated among low-income women and Hispanic women. Low-income women are also less likely to resume use after discontinuation.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Mortality_Decline_in_the_20th_Century_and_Supply_of_Kin_Over_the_Life_Course&diff=2723Mortality Decline in the 20th Century and Supply of Kin Over the Life Course2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:58</p>
<hr />
<div>{{Summary<br />
|title=Mortality Decline in the 20th Century and Supply of Kin Over the Life Course<br />
|authors=Uhlenberg<br />
|pub_date=1996<br />
|journal=The Gerontologist<br />
|summary=Notes: Declining mortality over the 20th century has altered the supply of older relatives in the kin networks of persons at all stages of life. Mortality decline has also changed the supply of kin for older persons. Using period life tables for every 20 years from 1900 to 2000, Uhlenberg calculated the proportion of person who, at various stages of the life course, would have grandparents, parents, spouses, siblings and children still living. Uhlenberg simulates family composition by imposing rules of marriage and fertility (assuming there is one son and one daughter only) and the mortality conditions at the time and then looks at the resulting numbers of kin alive. Uhlenberg finds that the supply of grandparents has changed dramatically over time. Under his assumptions, mortality levels existing in 1900 imply that fewer than ? of all children began life with all 4 of their grandparents alive, and by age 30 only 21% had any surviving grandparent. By the end of the century, on the other hand, over 2/3 will have begun life with all grandparents still living and more than ? will still have at least one grandparent alive when they reached age 30. Mortality declines in the last 40 years have been especially important in increasing the supply of grandparents for persons in the post-childhood years of life. Regarding survival of older parents, the probability of having both parents alive at age 40, 50, and 60 has increased since 1900. Moreover, individuals are more likely to have a mother alive at older ages with as many as 6.5% having only a mother alive at age 70 in 2000 as compared with 1.6 in 1960 and less than 1% from 1900 to 1940. Less than 1% can expect to have only a father alive from 1900 to 2000. Regarding survival of spouses, under 1900 mortality conditions, only half of men and a third of women who survive to age 70 would still have a living spouse. By 2000, these proportions will increase to 85% and 61%, respectively. However, while decreasing death rates created large gains in potential years that men and women could expect to live in uninterrupted marriages, increasing divorce rates have had an opposite effect. Because of changes in divorce rates and death rates by 2000, the prospect of 70-year-old mean and women still living with a first spouse are quite similar under conditions in 1900 and 2000. Sibling relationships are unique in their potential longevity. Again, the magnitude in historical change is large. For example, for those who survive to 70 with a sister 3 years younger, in 1900 27% of these individuals would have their sister still living while in 2000, the proportion was 75%. Because of gender differences in declining mortality, differences in the prospects of a sister surviving, compared to a brother, grew much larger between 1920 and 1980. At older ages, where death rates are high, the difference in probability of an older sibling compared to a younger one still being alive are significant. Today, relatively few children now die before their parents. With low mortality, it is not necessary to hear more children in order to be relatively certain that one will have surviving children when one is old. Over the last century, moreover, it has become increasingly likely that when only 1 child survives, that child is a daughter. For example, women who bear sons at age 25 now are more likely to have those sons alive when they are 80 (87%) than women in 1900 were to have their sons survive the first 2 years of life (82%). And if the child is a daughter, a higher proportion are now still living when their mothers reach age 90 (86%) than were surviving for just 2 years around 1900 (85%).<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=The_Epidemiological_Transition&diff=2724The Epidemiological Transition2009-11-17T00:21:58Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:58</p>
<hr />
<div>{{Summary<br />
|title=The Epidemiological Transition<br />
|authors=United, Nations<br />
|summary=Notes: This descriptive account of the epidemiological transition begins by asserting that the process of mortality change from infectious to chronic diseases is well underway in every part of the world. In developed countries, about 90 percent of deaths are now due to non-communicable diseases. Although communicable diseases play a much larger role in developing nations, particularly in sub-Saharan Africa and India, they are generally becoming less important as the epidemiological transition proceeds. For instance, in China 73 percent of all deaths are due to non-communicable diseases; in Latin America, 56 percent. Data for this report are taken from (1) the WHO's most recent estimates (1997) of deaths by cause for both developed and developing regions, and (2) the Global Burden of Disease Study (GBD)-a 5 year project initiated in 1992. A fundamental aim of the GBD was to derive estimates of mortality for 107 causes of death by age, sex and region. Some nations, primarily those with established market economies, have sophisticated vital registration systems that made this task relatively easy and accurate. But others, particularly those in sub-Saharan Africa, have no such information. Most nations fall somewhere between these extremes. For instance, sample registration systems exist in both India and China. Where gaps exist in vital registration systems, data were taken from samples, data from population laboratories (e.g., Matlab), epidemiological studies and cause of death models. As the epidemiological transition has proceeded, life expectancy for the entire world has improved from 46.5 in 1950 to 64.3 in 1990. Gains in life expectancy have been especially impressive in developing nations, and the gap between developed and less developed regions fell from about 25.6 to 12.1 years. However, this overall improvement in developing regions masks important variation between poor nations. For instance, despite progress, child mortality remains high in some developing nations (e.g., 254 per 1,000 in Guinea) relative to others (e.g., 59 per 1,000 in Botswana). Generally speaking, India and sub-Saharan Africa still suffer from relatively high rates of infectious disease and childhood mortality, while China and nations in Latin America are leaders among developing nations in the epidemiological transition. In addition to reductions in mortality, fertility rates have been declining for both developing and developed nations. This alters the age structure of the population from relatively young to relatively old, and therefore increases the burden of non-communicable disease mortality. By the early 1990s, non-communicable diseases were responsible for close to 60 percent of deaths worldwide (p. 105). Future gains in life expectancy-particularly in developed nations-depend on trends in chronic disease mortality at older ages. The report cautions against overconfidence in forecasting, but also suggests that declines in old age mortality are likely to continue. Even where the epidemiological transition has made great progress, it is important to recognize that chronic disease profiles can vary greatly between nations/regions. For example, mortality from cerebrovascular diseases (especially stroke) is far more common in Asian nations than in North America or Europe, where cardiovascular disease is highly prevalent. These differences are likely due to different risk factor profiles among countries. Moreover, within nations, the epidemiological transition appears to have occurred along socio-economic lines, with a growing prevalence of chronic and degenerative diseases of adulthood among the better off, while communicable diseases remain relatively more prevalent among the poor (p. 107).<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Excess_Mortality_for_the_Unmarried_in_Rural_Bangladesh&diff=2703Excess Mortality for the Unmarried in Rural Bangladesh2009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=Excess Mortality for the Unmarried in Rural Bangladesh<br />
|authors=Rahman<br />
|pub_date=1993<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Cohort_Differences_in_Disability_and_Disease_Presence&diff=2704Cohort Differences in Disability and Disease Presence2009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=Cohort Differences in Disability and Disease Presence<br />
|authors=Reynolds, et al.<br />
|pub_date=1998<br />
|summary=Notes: Introduction: Most studies of health trends emphasize a period approach toward examining trends . . . A cohort approach provides a different picture of health change in a society, one in which the relative health of successive cohorts, rather than of successive years, is the focus. Period trends in health are potentially confounded by historical events and conditions that birth cohorts experience at different points in their respective life courses. . . Those for whom childhood was a period was a period of deprivation because of depression or war may experience lasting effects from these events (Barker 1994). Alternatively, cohort differences in early-life exposure to disease and pathogens may act to produce differences in later-life health (p. 578). Because existing evidence regarding changes in health across cohorts is mixed, this article attempts to provide more evidence on the levels of disability and the prevalence of major diseases among a set of cohorts that span a wide range of birth years and adult ages in the United States (p. 579). Methods: The National Health Interview Survey (NHIS), which is a ongoing household survey of the noninstitutionalized population of all ages in the US, is the source of data for this study. 599,141 adults aged 30-69 were included in the sample. Fifteen separate cohorts-each a compilation of 3 single-year cohorts-were analyzed for the years 1916 (i.e., 1915-17) to 1958 (i.e., 1957-59). Each cohort was then followed from 1982 to 1993. Long-term disability due to chronic disease or impairment was measured by questions on limitation in major activity and ability to work. Measures of diseases and other chronic conditions were used to determine cohort patterns of arthritis, asthma, bronchitis, cardiovascular diseases, diabetes, emphysema, mental disorders, musculoskeletal conditions, and orthopedic impairments; some infectious diseases were also included. Some of the analysis is presented graphically because strong cohort patterns are readily apparent in the graphs. The statistical significance of cohort differences in health indicators is determined using logistic regressions (p. 580). Results: Among men, disability is generally higher for early-born cohorts. For instance, The cohorts of 1919 and 1916 are about 34% more likely to be limited that those born in 1937 (p. 581). However, later-born cohorts (i.e., born after 1946) report somewhat more limitations. In terms of chronic diseases among men, earlier-born cohorts have higher levels of arthritis, cardiovascular diseases and emphysema, but lower levels of diabetes and orthopedic impairments. Among women, later-born cohorts report disability levels that are slightly higher than early-born cohorts, but they also report less inability to work. With the exception of arthritis, which is higher in early-born cohorts, women do not report significantly different levels of chronic diseases or infections across cohorts. When education is taken into account (by separating each cohort into a high and low education group), expected differentials emerge. Also, later-born cohorts with high education generally report fewer disabilities and chronic conditions than early-born cohorts with high education. Interestingly, however, later-born cohorts with low education actually fare worse in some respects (e.g., orthopaedic impairments) than their early-born counterparts. Conclusions: Patterns of disability and disease change are mixed. Disability appears to have declined among cohorts born in the initial decades of the 20th century, but there is some indication of increasing disability among cohorts born in the 1950s. Similarly, while cardiovascular diseases (men) and arthritis (women) have shown steady improvement across cohorts, later-born cohorts are more likely to suffer from asthma (especially women) and orthopaedic impairments.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=The_Risk_of_Being_Sick:_Mortality_Trends_in_Four_Countries&diff=2705The Risk of Being Sick: Mortality Trends in Four Countries2009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=The Risk of Being Sick: Mortality Trends in Four Countries<br />
|authors=Riley<br />
|pub_date=1990<br />
|summary=Notes: Although mortality rates in developed countries have been declining for more than a century, recent health surveys in a number of countries suggest that morbidity may be worsening. Interpreting morbidity trends depends on whether incidence (i.e., the risk of getting sick) or duration dependent prevalence (i.e., the risk of being sick over a certain span of time) is examined. Riley argues that prevalence is a more useful measure because it reflects the burden of illness and disability in a society, which has implications for the economy and health care system. In this article, Riley reviews evidence on morbidity and mortality trends in four countries (Japan, US, Britain and Hungary). Previous research often adopted the assumption of parallelism, which means that improving mortality trends imply improving morbidity trends. But Riley questions this assumption. If more people survive at given ages, it is apparent that they have avoided some of the hazards that caused death in previous periods. But it is not apparent whether they avoided ill health or whether they merely avoided death (p. 406). Moreover, the epidemiological transition implies that illnesses will become more protracted, since short-lived but fatal infectious illnesses are replaced by chronic diseases that may cause death only after a prolonged period of ill health. Data from Japan, Britain and the US all show the same phenomenon. Mortality and morbidity rates are inversely related, with the former declining and the latter increasing. Hungary, which experienced a mortality increase in the mid-1960s, also exhibits the inverse relationship, but with decreasing morbidity. In the US, the age-specific incidence of acute conditions remained about the same over the period 1962-1986, but the risk of being sick increased since average durations of ill-health increased. Despite evidence to the contrary, some optimists (e.g., Fries) maintain that since mortality is occurring at later ages, the onset of potentially fatal illnesses and injuries has been deferred. Such a view is sometimes referred to as the compression of morbidity. But pessimists counter with (1) an epidemiological argument that chronic illnesses have become more prevalent precisely because of progress made in prolonging life through early detection and management of diseases and (2) a statistical argument which points to a positive gradient in the prevalence sickness trends. In short, although the overall risk of falling sick may have diminished over the past century, the risk of being sick has increased due to increased life expectancy, the substitution of infectious diseases with chronic conditions, and improved detection and treatment of manageable but non-curable chronic conditions (e.g., diabetes and heart disease). While the pessimistic view may be correct, Riley does not approve of the negative connotation. To a substantial degree more protracted sickness constitutes an achievement, because it is a byproduct of objectives that humankind set for itself. But this is an interim achievement, one that compels us to reformulate our objectives by designing policies that will reduce sickness time without allowing mortality to increase (p. 428).<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Age_and_the_sociology_of_fertility:_How_old_is_too_old%3F&diff=2706Age and the sociology of fertility: How old is too old?2009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=Age and the Sociology of Fertility: How Old is Too Old?<br />
|authors=Rindfuss, Ronald R., Bumpass, Larry<br />
|pub_date=1978<br />
|summary=Notes: In this article Rindfuss and Bumpass argue that while age has a strong biological effect on fertility, biology is not the only way in which age affects fertility. There is also a sociological component. Age is an important consideration in a couple's decision with respect to the termination of fertility. Age also effects the choice of contraceptive method and the vigilance with which contraception is practiced. Age differentials in contraceptive failure may be interpreted as reflecting this component as well as differential fecundity. The longer that a woman postpones childbearing, the greater the likelihood that she will get involved in other ego-involved activities that consume time and energy. Postponing childbearing increases that likelihood that other members of the woman's cohort will have completed their childbearing, creating a loss of important advice and support. There is also the concern that with increasing age, the partners may not have sufficient time and energy to cope with a child. There may be normative bounds prescribing the 'proper' time for childbearing. Using data from the 1970 and 1965 National Fertility Study, the authors analyze whether or not the respondent intends to have more children, controlling for age, age of youngest child, parity, education, race, religion, age at marriage, and the length of the interval between marriage and the birth of the first child. The sample is limited to married women ages 25-34, who are without known or suspected fecundity problems. For any given parity, the proportion intending to have more children is strongly and inversely related to age. The effects of both age and age of youngest child are substantial even after all of the other variables are controlled. In other analyses about one-third of the difference in fertility by age at first marriage can be explained by differential in sterility and unwanted births. The remaining difference may be interpretable in terms of the sociological effects described above. The authors test whether these effects are the same for second marriages. The regress intended fertility in the second marriage (sum of wanted births born in 2nd marriage and additional intended children) on age, age at second marriage, number of previous children, reason for previous marital dissolution, education of wife, education of current husband, race of wife, and religion of wife. The results show that mean fertility decreases as age at second marriage increases. Even when age at first marriage, length of first marriage, and length of marital disruption are controlled, age at second marriage retains its significance. The authors conclude that changes or differences in the timing of fertility are associated with differences in the ultimate amount of childbearing. The sociological meanings of age as they affect fertility decisions are seen as the critical link in this relationship. The question how old is too old? is a question about the relative childbearing pace of one's peer, internalized ideal life cycles, and the expectations of significant others.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Living_and_dying_in_the_U.S.A.:_sociodemographic_determinants_of_death_among_blacks_and_whites&diff=2707Living and dying in the U.S.A.: sociodemographic determinants of death among blacks and whites2009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=Living and dying in the U.S.A.: sociodemographic determinants of death among blacks and whites<br />
|authors=Rogers, Richard G.<br />
|pub_date=1992<br />
|journal=Demography<br />
|journal_volume=29<br />
|summary=Notes: Rogers looks for key factors determining the black-white gap in life expectancy. He concludes that the racial gap in mortality is due to the socioeconomic disadvantages that blacks face, and that there is no race effect. He makes causal arguments for marriage and reduced fertility to decrease black mortality. This article is poorly written, simplistic in it's policy recommendations, and offensive/paternalistic.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Trends_in_socioeconomic_inequalities_in_mortality_in_developing_countries:_The_case_of_child_survival_in_Sao_Paolo,_Brazil&diff=2708Trends in socioeconomic inequalities in mortality in developing countries: The case of child survival in Sao Paolo, Brazil2009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=Trends in socioeconomic inequalities in mortality in developing countries: The case of child survival in Sao Paolo, Brazil<br />
|authors=Sastry, Narayan<br />
|pub_date=2004<br />
|journal=Demography<br />
|journal_volume=41<br />
|summary=Notes: Sastry explores inequalities in under-5 mortality in Sao Paolo, Brazil from 1970 to 1991 by household wealth and maternal education. Inequality in child mortality declined overall fro 1970-1991. When examined by HH wealth, it is revealed that the decline happened dur to a much larger drop in child mortality in lower income quintiles than in higher-income quintiles. By women's education, inequality in child mortality dropped from 1970 to 1980, then increased by 1991. Child mortality actually increased for women in higher educational classes and decreased for lower classes in the 1970s, perhaps due to increases in edu attainment. All educational levels experienced improvements after the 1970s. The effect of covariates reduced overtime to that mother's edu itself played a more important role in inequality by education. Covariates, including maternal edu, reduced the inequality in child mortality that otherwise would have been observed. So, decreasing maternal edu inequality as a policy initiative might, in turn, reduce child mortality. These conclusions do no support those made by Victoria et al. (2000) and Szreter (1997) which suggest that economic and technology growth increase health inequality. Inequality trends in Sao Paolo emerge from a complex system of sanitation improvements, education, and catching up (???) from the increased mortality of the 1960s and 1970s.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=The_cultural_significance_of_Western_fertility_trends_in_the_1980s&diff=2709The cultural significance of Western fertility trends in the 1980s2009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=The cultural significance of Western fertility trends in the 1980s<br />
|authors=Simons, J.<br />
|pub_date=1999<br />
|summary=Notes: The author adopts a scheme in which values vary in a horizontal scale from absolutism to relativism and in the vertical scale from holism to individualism. Absolutists believe that behavior in the family is subject to societal values. For relativists, the appropriateness of behavior is determined by circumstances. For holists, is important to conform to perceived expectations of the community and individualists stress the rights and needs of the individual. He then presents a good review of Lesthaeghe work. Lesthaeghe using the same data concludes that secularization, identified, as individuation, is an important factor to explain fertility decline in Europe. Simons then contest why fertility decline ceased in the 1980s and even rise in some countries, given the progress of ideas linked to post-materialism and individualism and their apparent negative influence on attitudes to procreation. Lesthaeghe answers by saying that the disappearance of restrictions on sexuality had led to more extramarital births and that the progress of pragmatism had enabled and encouraged people to have children at the age and circumstances that suited them. However, Simons seems to disagree that individualism is the unique dimension of pragmatism. He shows that ideas about sexual forms of partnership could vary independently of ideas about parenthood, and that although this represents a shift towards pragmatism, fundamentalist ideas about childbearing remained influential in most countries. Therefore, the absolutism-relativism dimension also influences pragmatism. Finally, he shows evidence from EVSSG (EUROPEAN VALUE SYSTEMS STUDY GROUP) indicating increases in the restrictiveness of attitudes of sexual relations and the growth in attachment to traditional as well as an increase in individualism.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Adolescent_Childbearing_in_Developing_Countries:_A_Global_Review&diff=2710Adolescent Childbearing in Developing Countries: A Global Review2009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=Adolescent Childbearing in Developing Countries: A Global Review<br />
|authors=Singh, Susheela<br />
|summary=Notes: This article discusses the current levels and recent trends in the rate of adolescent childbearing, the timing of the first birth, and births to unmarried women for 43 developing countries. Differences in rate of adolescent childbearing by residence and level of education are also examined. The analysis is based on nationally representative fertility surveys, the World Fertility Surveys (WFS), administered in the 1970s and the Demographic and Health Surveys (DHS), administered between 1985 and the early-1990s. The DHS covers all women in sub-Saharan Africa and Latin America, but only ever-married women in North Africa, the Near East, and Asia. The countries included in these surveys account for 73% of the population of the developing world, excluding China. WFS data is used to evaluate trends in countries for which data is available for at least two time periods. Two different measures of adolescent fertility are used to provide two different perspectives on early childbearing. These two measures are: the age-specific fertility rate for women ages 15-19 and the proportion of women who have had a child by a given adolescent period in this study, by ages 15, 18, or 20. The first measure is affected by the extent to which adolescents have more than one birth between the ages of 15-19, while the second measure describes more accurately the timing of early childbearing, but is available for women ages 20 or older only. The countries of sub-Saharan Africa have the highest levels of adolescent childbearing in the developing world. Mali and Niger have the highest rates. Latin America and the Caribbean region have the next highest levels. Five of the eight Asian countries represented have low-to-moderate rates. The other three Asian countries have higher rates (Bangladesh has rates similar to sub-Saharan Africa, while Pakistan has rates similar to Latin America and India falls between these two. Countries in the Near East and North Africa show the lowest levels of adolescent childbearing, with Tunisia showing the lowest levels. The incidence of childbearing before age 15 is substantial in several sub-Saharan African countries, with 8-15% of girls this age having had at least one birth. For women under age 18, 25-40% have had at least one birth in most sub-Saharan countries, while 15-20% have done so in most Latin American countries and in some countries of North Africa, the Near East, and Asia. Morocco, Tunisia, Philippines, Sri Lanka, Thailand, Burundi, and Rwanda have extremely low levels of early childbearing. Substantial declines in adolescent fertility have occurred in North Africa and Asia, but levels are still high in some countries. Declines are beginning to occur in sub-Saharan Africa, but current levels are still high most countries in this region, and the proportion of births to unmarried adolescents is increasing in a few countries. Declines are largest in Kenya and Senegal. Increases are found in Uganda. Large declines are found in North Africa and Asia in all countries except the Philippines and Sri Lanka, both of which had low levels to begin with. In Latin America, where the level of teenage childbearing is moderate, declines are less prevalent and some small increases have occurred. Declines occurred in the Dominican Republic, Ecuador, Mexico, and Peru. Increases have occurred in Brazil and Columbia. Especially in Latin America, declines in childbearing have been much greater among older women than among adolescents. Higher education (measures in two ways: proportion who had no schooling, a primary-level education, and a secondary-level education; and by the proportion of those who had fewer than seven years of schooling versus that of those who had more than seven years of schooling) is associated with lower rates of adolescent childbearing, but other socioeconomic changes cancel or reduce this effect in several countries. Brazil has a very low rate for adolescents with secondary schooling, compared to other countries. Level of adolescent childbearing is generally lower in urban areas than in rural areas, but there are a number of exceptions (e.g. Namibia, Sri Lanka, Trinidad, Tobago, and Turkey). Urban Botswanan women experienced a greater increase in adolescent childbearing than did rural Botswanan women. Differences by residence are generally smaller than differences by education levels. Moderate-to-high proportions of adolescent mother say that their pregnancy was unplanned or mistimed.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Trends_in_sexual_activity_among_adolescent_American_Women:_1982-1995&diff=2711Trends in sexual activity among adolescent American Women: 1982-19952009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=Trends in sexual activity among adolescent American Women: 1982-1995<br />
|authors=Singh, Susheela, Darroch, Jacqueline E.<br />
|pub_date=1999<br />
|journal=Family Planning Perspectives<br />
|journal_volume=31<br />
|summary=Notes: Data from NSFG (National Survey of Family Growth) is used to show that the proportion of adolescent women who ever had sexual intercourse increased somewhat during the 1970s and 1980's (32% in 1971 and 53% in 1988), but this upward trend stabilized between the late 1980's and mid 1990s (the result may have been influenced by a change in the question that clearly stated heterosexual intercourse. Oral and anal sex was excluded). For several reasons (STDs, unwanted teenage pregnancy) this general increase brings social concern. However, it is important to mention that there has been little change in the proportion currently sexually active in the last 3 months (reduction in the continuity). Differences in teenage sexual behavior across poverty and racial and ethnic subgroups were large in early 1980's, but narrowed between 1982 and 1995. Blacks and Hispanics have higher rates than Whites.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Infant_Mortality_in_the_United_States:_Trends,_Differentials,_and_Projections,_1950_through_2010&diff=2712Infant Mortality in the United States: Trends, Differentials, and Projections, 1950 through 20102009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=Infant Mortality in the United States: Trends, Differentials, and Projections, 1950 through 2010<br />
|authors=Singh, Susheela, Yu<br />
|pub_date=1995<br />
|journal=American Journal of Public Health<br />
|summary=Notes: This study examined long-term trends and differences in infant mortality in the US from 1950 to 1991 according to race and ethnicity, education, family income, and cause of death. Forecasts are made through the year 2010. Log-linear regression models were applied to data from the National Vital Statistics System, National Linked Birth and Infant Death files, the National Maternal and Infant Health Survey, the National Natality Survey, and the National Infant Mortality Survey to model and forecast infant mortality. Although the infant mortality rate in the US has declined steadily since 1933, it is consistently higher than that for many other industrialized countries. The relatively unfavorable international standing of the US in terms of infant mortality rates stems in large part from the substantial racial disparity in infant survival and associated socioeconomic inequality that have existed in the country for a long period. Dramatic declines in the US infant mortality rate have occurred in the past 4 decades, largely as a result of declines in mortality from pneumonia and influenza, respiratory distress syndrome, prematurity and low birthweight, congenital anomalies, and accidents. Despite the overall reductions, however, substantial racial/ethnic, educational, and income differences in infant mortality still exist. In fact, black-white disparity in IMR increased from 1950 to 1991. Between 1951 and 1990, neonatal mortality declined much faster than postnatal mortality in the total population. White babies followed the trend of the whole population while black babies experienced a more rapid decline of postnatal mortality than of neonatal mortality. Like infant mortality, neonatal mortality has seen an increasing racial inequality over time; while postnatal mortality has seen a narrowing of black-white differentials, especially in the last 30 years. Amongst other racial/ethnic groups, Japanese, Chinese, Cuban, Central/South American, and Mexican infants had lower infant mortality than white infants while Puerto Rican, Hawaiian, and American Indians (and blacks, of course, who have the highest infant mortality of all), had higher infant mortality than whites. Infant mortality is inversely associated with maternal education and family income. However, the black-white infant mortality disparity was greater as higher levels of maternal education and the racial disparity generally increased across all educational levels during 1964 through 1987. Moreover, the racial disparity appeared to have increased between 1964 and 1988 for the middle income and highest income categories. Congenital anomalies were the leading cause of infant death for the total population in 1991, accounting for 1 in 5 infant deaths, followed by SIDS, prematurity and low birthweight, and respiratory distress syndrome. For black babies, the leading cause was prematurity/low birthweight (which increase by about 9% from 1981 to 1991) followed by SIDS and congenital anomalies. The long-term downward trend in US infant mortality has not benefited Blacks and Whites equally. The Black-White disparity in infant mortality has not only persisted but increased over time and is not expected to diminish in the near future. Educational inequalities have also widened, and racial disparities have generally increased across all educational levels.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Race,_Socioeconomic_Status,_and_Health_in_Late_Life&diff=2713Race, Socioeconomic Status, and Health in Late Life2009-11-17T00:21:57Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:57</p>
<hr />
<div>{{Summary<br />
|title=Race, Socioeconomic Status, and Health in Late Life<br />
|authors=Smith, Kington<br />
|pub_date=1997<br />
|summary=Notes: This paper has 2 goals: (1) to examine racial and ethnic disparities in health outcomes among older American using 2 important new data sets (the Health and Retirement Survey, HRS ages51-61, and the Asset and Health Dynamics Among the Oldest Old, AHEAD, ages 70+), and (2) to she light on the central issues of the underlying causes of the strong relationship between socioeconomic status and health outcomes. Although their results are consistent with other research suggesting an important role for socioeconomic status as a factor accounting for racial and ethnic differences (most mortality and health differentials between blacks and whites disappear with the introduction of controls for socioeconomic characteristics), their results indicate that the relationship among race and ethnicity, socioeconomic status, and health is far more complex than many current analyses recognize. Smith and Kington found that blacks had substantially higher rats of hypertension, stroke, and diabetes (and in some cases, arthritis) and lower rates for diseases of the lung and for a heart attack within the previous 5 years (men only). Moreover, blacks have higher values on some risk factors that may explain the association between socioeconomic status and health such as smoking, drinking, lack of exercise, and obesity. (Whites, however, have higher rates of exposure to dangerous chemicals or other hazards at work.) In a number of models exploring the relationship between socioeconomic status and health, the authors find that education is highly associated with health (above and beyond income). Health risk factors are highly related to health (especially BMI). Income and wealth appear to have nonlinear relationships with health (the effects weaken as one moves up the income and wealth distribution). However, the effects of income and wealth differ depending on the source such as welfare, retirement, etc. There are 2 important dimensions of economic status income and wealth each with distinct conceptual and empirical associations with health. The association of some common measures of socioeconomic status with health status is highly nonlinear. For example, the association of both income and wealth with self-reported general health status is strongest among the poorest households and is relatively weak among the most affluent members of society. Both of these issues may affect how we account for racial and ethnic differences in health in later life. Finally, there is compelling evidence that the feedbacks from health to current socioeconomic status are quantitatively strong and should not be ignored in empirical investigations. In particular, the entire association between current household income and health among households with a member in his or her fifties appears to reflect causation from health to income rather than from income to health.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Are_Educational_Differentials_in_Adult_Mortality_Increasing_in_the_United_States%3F&diff=2699Are Educational Differentials in Adult Mortality Increasing in the United States?2009-11-17T00:21:56Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:56</p>
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<div>{{Summary<br />
|title=Are Educational Differentials in Adult Mortality Increasing in the United States?<br />
|authors=Preston, Samuel H., Elo, Irma T.<br />
|pub_date=1995<br />
|journal=Journal of Aging and Health<br />
|summary=Notes: Using data from the National Longitudinal Mortality Survey (NLMS), the authors compare the size of educational mortality differentials in the 1980s (1979-1985) to estimates for 1960. The measures the authors use are the slope index of inequality (an estimate of how much change in death rates is associated with moving up the educational ladder), the relative index of inequality (the absolute expected change in death rates in moving from the lowest to the highest levels of schooling), and the index of dissimilarity (the minimum proportion of deaths that would have to be redistributed to equalize the distributions of deaths and population, thereby eliminating all educational differences in mortality, like Gini coefficient). Their results are consistent with previous findings that show a widening of educational differentials in mortality for White men. In both age intervals (ages 25-64 and 65-74), each of the three measures indicates that educational inequality in mortality was greater in 1979-85 than 1960. For White females however, both the absolute and relative measure of inequality at ages 25-64 suggest that educational differentials in mortality have narrowed rather than expanded since 1960. For women aged 65-74, the results are more mixed. The absolute measure of inequality declines, while both relative measures increase. Being at the low wend of the educational distribution in 1979-7985 was associated with a smaller absolute penalty in death rates than in 1960, but a larger relative penalty (only possible b/c of falling death rates for all women). The widening of relative inequality has, however, been substantially less for older women than for older men. The largest increase in inequality on any measure between 1960 and 1979-1985 occurred for men aged 65-74. However, the magnitude of increase is somewhat uncertain due to coding problem in the 1960 data. The authors argue that less-educated women may have suffered from less mortality inequality than less educated men as a result of women's increased labor force participation from 1960 to 1985 and the introduction of Medicaid (which women may be more readily eligible for b/c AFDC, etc.). However, more educated women gained more in terms of income, etc, with their higher levels of labor force participation and Medicare made medical services available to all elderly (the group in which the largest mortality differences are found).<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=African-American_mortality_at_older_ages:_Results_of_a_matching_study&diff=2700African-American mortality at older ages: Results of a matching study2009-11-17T00:21:56Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:56</p>
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<div>{{Summary<br />
|title=African-American mortality at older ages: Results of a matching study<br />
|authors=Preston, Samuel H., Elo, Irma T., Rosenwaike, Ira, Hill, Mark<br />
|pub_date=1996<br />
|journal=Demography<br />
|journal_volume=33<br />
|summary=Notes: Preston and colleagues follow up Preston & Elo (1994) who find that death certificates for blacks (especially women) in the 1960 census underreport age. The current study matches 1980 and 1985 death certificates to 1900, 1910, and 1920 Censuses to reexamine the black mortality crossover in which it appears that blacks have higher death rates than whites at younger ages and lower death rates at older ages. The authors focus on the age at death entered on the death certificate (rather than the age implied by dates on records) b/c that is what NCHS uses for national mortality estimates. Age at death below age 90 was understated for men and women, while age at death was over-stated for men and women over 90. Discrepancies were concentrated around one year for early censuses, but were more concentrated around 2+ years when soc sec records are used for comparison. After adjustment w/age-specific growth rates, the only crossover still present was the 90+ age group. This may or may not be an error. The death certificates are ultimately shown to be the cause of the crossover error. The same pattern may be true for whites, but whites were not analyzed. Even if the pattern of misreporting is the same for whites, the age-mortality structure may not produce a crossover even if data corrections are made.<br />
}}</div>WisconsinDemographyPrelimAugust2009https://acawiki.org/index.php?title=Demographic_Conditions_Responsible_for_Population_Aging&diff=2701Demographic Conditions Responsible for Population Aging2009-11-17T00:21:56Z<p>WisconsinDemographyPrelimAugust2009: BibTeX auto import 2009-11-17 12:21:56</p>
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<div>{{Summary<br />
|title=Demographic Conditions Responsible for Population Aging<br />
|authors=Preston, Samuel H., Himes, Eggers<br />
|pub_date=1989<br />
|journal=Demography<br />
|summary=Notes: This article develops and applies 2 expressions for the rate of change of a population's mean age. In one, equation (1), aging is shown to be negatively related to contemporary birth rates and death rates. [Where Ap is mean age of pop, AD is mean age at death, b is birth rate, d is death rate, dAp/dt is derivative of mean age of pop with respect to time.] This equation shows the time derivative of the mean age to be a function of contemporary birth and death rates and the mean ages of people living and dying. In a general sense, aging occurs when vital rates are too low/not intense enough, as illustrated through applications to the US, the Netherlands, and Japan. Comparing the US and Japan, for example, Japan has a substantially lower death rate and the US has higher in-migration and slightly higher birth rates. The other expression, equation (4), relates the rate of aging to a population's demographic history, in particular to changes in mortality, migration, and the annual number of births. [Where r(a,t) is growth rate of pop aged a at time t, and c(a,t) is proportion of pop aged a at time t.] This equation shows the derivative to be a function of age-specific growth rates, which can in turn be traced to the history of change in births and in mortality and migration rates. Applications to the US and Sweden show that the dominant factor in current aging in these countries is a history of declining mortality. Migration also contributes significantly but in the opposite directions in the 2 countries keeping the US younger and helping to age Sweden. The 2 approaches are integrated after recognizing that the rate of change in the mean age is equal to the covariance between age and age-specific growth rates. A decomposition of this covariance shows that the 2 seemingly unrelated expressions contain exactly the same information about the age pattern of growth rates. A population's history appears in equation (1) in both the Ap and AD terms and in the rates of birth and death, which are affected by age distribution. Contemporary rates of birth and death figure into equation (4) through the r(a,t) function, which reflects all differences between past and present rates of mortality and migration as well as the growth rates of births up to and including the present. In conclusion, the rate of change of a population's mean age is equal to the covariance between age and age-specific growth rates. Since the age-specific growth rate can be expressed in terms of either 3 additive elements reflecting the population's demographic history, or 2 additive elements representing contemporary conditions, the rate of aging can also be expressed in 2 different ways as the sum of covariance terms. Through these equations, we can conclude that populations are aging when birth rates and death rates are sufficiently low that a positive correlation exists between age and age-specific growth rates<br />
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