Changes in Contact and Support Within Intergenerational Relationships in the Netherlands: a Cohort and Time-Sequential Perspective
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Introduction– An increase of Parkinson's disease (PD) mortality has been observed in various countries during the last 3 decades. An analysis was done in order to define whether this trend could be due to a cohort effect. Material & methods– The mortality from PD in Italy during the period 1963–1987 was analyzed by means of a simplified cohort method. A mortality rate ratio (MRR) was also calculated, reporting all rates to 1906–1910 birth-cohort. Results– The mean annual mortality rates from PD sharply increased during the period of the study. The MRRs increased from the cohort born between 1881 and 1885, to a maximum in the cohort born between 1906 and 1910, and then markedly decreased in the following cohorts. Conclusion– According to our findings, the increase of PD mortality could be partly ascribed to an higher risk of dying from PD experienced by the cohorts of people born in the first decade of this century.
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The aim was to determine whether the effects of age, period (from 1987 to 1997), or cohort (birth‐cohort) are the most plausible explanations for the variation in dentist utilisation over time in Spain. On the basis of three sequential Spanish National Health Surveys, the trend in the percentage of people visiting the dentist within the previous 3 months was analysed by means of a standard cohort table and by the C layton & S chifflers method. The percent of people visiting the dentist grew from 13.6% in 1987, to 17.2% in 1997. Visual examination of the cohort table, together with the fit of the age‐cohort model, indicates that cohort succession may be the best explanation for the increase. The younger the cohort, the higher the dental visit rate; this relationship was strongest for people born after 1977. The model also indicates that the rates of dental visiting tend to increase up to middle age, and then tend to decrease with age.
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Abstract This paper estimates Age–Period–Cohort models on employment rates of Dutch Disability Insurance (DI) applicants. We find that the substantial decrease in employment between 1999 and 2013 is explained by year-of-application cohort effects and that period effects are negligible. In turn, application cohort effects partly stem from increasing shares of applicants without permanent contracts. Changes in application cohort effects are largely confined to the years following two DI reforms that increased self-screening among workers. We next analyze changes in employment rates of awarded and rejected applicants and follow a Difference-in-Differences approach. Assuming common compositional cohort effects, we infer negligible effects of changes in benefit conditions.
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Mortality data from 1950 to 1986 in Australia have been used to exemplify a method of displaying trends by age and cohort in populations over time. The visual summary or synoptic method illustrated here is similar to a topographic map with age and calendar time as its ordinates. This method is complementary to conventional analyses of age-period-cohort data which lack a summary graphic view other than that provided by the trend in age-standardized rates or a three dimensional perspective plot. Mortality from ischaemic heart disease (IHD), lung cancer and motor vehicle accidents are used as examples of the method and illustrate its utility when dealing with different forms of mortality trend e.g. cross-sectional cohort, and mixed trends.
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Cohort analysis has become a popular method of examining national trends in suicide rates. Most of the studies investigating this phenomenon have reported a cohort effect to be present. Using a graphical approach, this paper places cohort analysis within the broader framework of age-period-cohort analysis. It is shown that published reports may have failed to identify cohort effects due to using only portions of the available data. With a simple mathematical model it is demonstrated that what appears to be a cohort effect may be a period effect, and conversely. It is recommended that suicide rates be examined for both period and cohort effects before conclusions are drawn regarding trends, and that the complete data set be used for this purpose.
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ABSTRACT Aggregate data on US earnings, classified by period and by age, are decomposed into age, period and cohort effects, using the Bayesian cohort models, which were developed to overcome the identification problem in cohort analysis. The main findings, obtained by comparing college and high school graduates, are threefold. First, the age effects show a downward trend for the age group of 45–49 onwards for high school graduates but do not show any such trend for college graduates. Second, the period effects show a downward trend for high school graduates but reveal no such trend for college graduates. Third, the cohort effects are negligible for both college and high school graduates.
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This study aimed to analyze the mortality of heart disease (HD), ischemic heart disease (IHD), and cerebrovascular disease (CeVD) through an age-period-cohort (APC) analysis.We used data on mortality due to cardiovascular disease from 1995 to 2018 in Japan, as determined by Vital Statistics. Age groups from 0 years to 99 years were defined by 5-year increments, and cohorts were defined for each age group of each year with a 1-year shift. We used Bayesian APC analysis to decompose the changes in the diseases' mortality rates into age, period, and cohort effects.The period effects for all diseases decreased during the analyzed periods for both men and women. The cohort effects for men increased substantially in cohorts born from around 1940 to the 1970s for all types of cardiovascular diseases. The cohort effects of HD decreased in the cohorts born in the 1970s or later for both men and women. Regarding IHD and CeVD, either a non-increase or decrease of cohort effects was confirmed for cohorts born in the 1970s or later for men, but the effects for women showed a continuously increasing trend in the cohorts born in the 1960s or later.The cohort effects for IHD and CeVD showed increasing trends in younger generations of women. This suggests that preventive approaches against cardiovascular diseases are needed, particularly for women.
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Abstract Investigations of the Swedish mortality decline during the 19th century have hardly considered the cohort-aspect. Generally, they are concerned with the question of period mortality. This is quite striking since we have mortality models which allow a separation of the cohort and period effects, and because the cohort aproach has been used in analysing other demographic phenomena during the period. 1 In textbooks as well as elsewhere, Erland Hofsten, however, has asserted the necessity of considering the cohort aspect in population analysis — In this investigation the cohort is constituted of the individuals of the age groups 0–10 years during a ten-year period.
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The aim of this study was to describe the pattern of trends in lung cancer mortality in Brazil and identify the effects of the factors age, period and cohort (APC) on mortality rates. A time series study was conducted using secondary population-based data. Lung cancer mortality rates by sex were calculated for the period 1980 to 2007. APC models were adjusted to identify the influence of age, period and cohort effects on rates. Lung cancer mortality rates are significantly higher among men. Specific rates for men over the age of 64 and for women of all ages are increasing. There was a greater increase of adjusted rates among women. With respect to the age effect, mortality risk increases with age starting with the earliest age groups. With regard to the cohort effect, there is a lesser risk of mortality among men born after 1950 and an increasing risk across all cohorts among women. The results regarding younger generations indicate that present trends are likely to continue. The cohort effect among women suggests an increasing trend in mortality rates, whereas a decrease in rates among men under the age of 65 suggests that this trend will continue. These trends reflect tobacco control measures adopted since 1986.
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