How to compare interpretatively different models for the conditional variance function

This study considers regression-type models with heteroscedastic Gaussian errors. The conditional variance is assumed to depend on the explanatory variables via a parametric or non-parametric variance function. The variance function has usually been selected on the basis of the log-likelihoods of fitted models. However, log-likelihood is a difficult quantity to interpret – the practical importance of differences in log-likelihoods has been difficult to assess. This study overcomes these difficulties by transforming the difference in log-likelihood to easily interpretative difference in the error of predicted deviation. In addition, methods for testing the statistical significance of the observed difference in test data log-likelihood are proposed.     

Bayes Estimates for the Price and Income Elasticities of Alcoholic Beverages in Finland From 1955 to 1980

The Lindley–Smith theory of Bayes estimates for multiple regression equations with exchangeability between the regression coefficients of the individual equations is extended to the case in which a first-order autoregressive process generates the regression coefficients. The ensuing formulas are applied to study monthly Finnish consumption of alcohol. The point of this application is that exchangeability between the regression coefficients is less than we can assess beforehand when there is a natural ordering, in this case according to chronological time, of the equations. Still, the general task of the Lindley–Smith estimators, to consider the combined data when estimating individual regression coefficients, is a relevant one.     

Health Effects Caused by Primary Fine Particulate Matter (PM2.5) Emitted from Buses in the Helsinki Metropolitan Area, Finland

Fine particle (PM(2.5)) emissions from traffic have been associated with premature mortality. The current work compares PM(2.5)-induced mortality in alternative public bus transportation strategies as being considered by the Helsinki Metropolitan Area Council, Finland. The current bus fleet and transportation volume is compared to four alternative hypothetical bus fleet strategies for the year 2020: (1) the current bus fleet for 2020 traffic volume, (2) modern diesel buses without particle traps, (3) diesel buses with particle traps, and (4) buses using natural gas engines. The average population PM(2.5) exposure level attributable to the bus emissions was determined for the 1996-1997 situation using PM(2.5) exposure measurements including elemental composition from the EXPOLIS-Helsinki study and similar element-based source apportionment of ambient PM(2.5) concentrations observed in the ULTRA study. Average population exposure to particles originating from the bus traffic in the year 2020 is assumed to be proportional to the bus emissions in each strategy. Associated mortality was calculated using dose-response relationships from two large cohort studies on PM(2.5) mortality from the United States. Estimated number of deaths per year (90% confidence intervals in parenthesis) associated with primary PM(2.5) emissions from buses in Helsinki Metropolitan Area in 2020 were 18 (0-55), 9 (0-27), 4 (0-14), and 3 (0-8) for the strategies 1-4, respectively. The relative differences in the associated mortalities for the alternative strategies are substantial, but the number of deaths in the lowest alternative, the gas buses, is only marginally lower than what would be achieved by diesel engines equipped with particle trap technology. The dose-response relationship and the emission factors were identified as the main sources of uncertainty in the model.     

Ageing of a giant: a stochastic population forecast for China, 2006–2060

This paper presents a stochastic population forecast for China with a special emphasis on population ageing. The so-called scaled model for error was used to quantify the uncertainty attached to the population predictions. Data scarcity was a major problem in the specification of the expected error of the population forecast. Therefore, the error structures estimated for European countries were used with some modifications, taking into account the large size and heterogeneity of the Chinese population. The stochastic forecast confirms the expectation of extremely rapid population ageing during the first half of the twenty-first century in China. The old age dependency ratio (OADR) will certainly increase. Simply maintaining the current demographic rates (no international migration) would drive the OADR to 0.42 in 2060, four times the current level. Including expected declines in mortality and net outmigration in the projection would increase the median OADR in 2060 to 0.59, with a 80% prediction interval of [0.47, 0.75]. In particular, the oldest-old population will grow much faster than any other age group. This development has major implications for policy-making in China.

A life course approach: research orientations and future challenges

The need to study lifelong changes in health and functioning has resulted in increasing emphasis on a life course approach in different fields of inquiry. The aim of this approach is to explore how biological, psychological, and social risk factor trajectories, acting across the entire life course, influence age-related diseases, functional decline, and disability. The importance of the first years of life upon later development and adult characteristics was generally recognized already in the first half of the twentieth century, but it was not until the 1990s that different strands of medical and social research converge in the field of life course epidemiology, in which epidemiological processes are approached using different models such as biological programming, critical periods, pathways, and accumulation. The biological programming model holds that organ development in utero and early infancy determines the maximum functional capacity that an individual can attain and influences the development of certain chronic diseases later in life. The critical period model extends the idea to include child development and key social transitions over the entire life course. The pathway model focuses on the cumulative effect of life events along the developmental trajectories, with early advantage or disadvantage setting a person on a pathway to a later etiologically important exposure. The accumulation model describes the underlying social, behavioral, and biological processes that drive the impact of the life course on health. The growing focus on life course determinants of aging also has implications for studies of long-term changes in physical activity and their role in determining both gains and losses of health and functioning with aging. A life course approach presents great challenges for the continued development of testable theoretical models and effective study design and analysis.     

Estimation of Exposure Time Distributions

In many demographic analyses, such as the assessment of environmental cancer risks, one may be interested not only in the age-by-state distribution of the population but also in the distribution of the population by time spent in a given state. States can represent geographic areas, marital statuses, labor force participation, or states of epidemiologic exposure. Recursive formulas for the calculation of the distribution of the population according to exposure time are derived under time-invariant state transition rates. Although populations can have identical growth rates and identical age-by-state distributions, they can have very different distributions by exposure time. An application to the analysis of carcinogenic exposure states is given, using data from Finland. The effect of population heterogeneity on the estimated exposure time distributions is studied.     

Study on a resource allocation formula for social services in Finland

This article considers how a specific need-based resource allocation formula for children's day care, income support, child welfare and other social services was developed. The formula is needed for the municipal allocation of state subsidies for social services, and the work was performed for the Ministry of Social Welfare and Health. Cross-sectional data were collected from the 436 Finnish municipalities and 37 small areas within the six largest cities. Because of the simultaneous relationship between supply and demand of services, two-stage least-square estimation and structural equations models were used in the analysis. After the effect of supply was removed from the service utilisation data, group-need factors (municipal variables) were found for these services. The new formula is financially and administratively feasible, transparent and reasonably simple.     

Social and health‐care priorities of local politicians in Finland: do the attitudes of politicians reflect the actual processes in municipalities?

The aim of this study was to find out whether elected politicians' attitudes influence policy-making processes in terms of social and health-care resource allocation. A preliminary hypothesis was developed on the basis of previous empirical findings on the attitudes of politicians. If health-care costs decreased during the period 1993–1999, then secondary care costs should have increased and vice versa; if the total amount of resources increased, then secondary care must have been allocated fewer resources. However, the results of this study showed that the actual resource-allocation processes did not reflect the attitudes of local politicians. Expenditure on secondary health care increased during this period, while primary health-care services were allocated fewer resources. Analysing the actual decision-making processes rather than investigating attitudes to priority setting may prove more useful in gaining a better understanding of priority-setting processes and the mechanisms used in different contexts.     

Correlates of Sexual Abuse in a Sample of Adolescent Girls Admitted to Psychiatric Inpatient Care

We examined correlations of child sexual abuse among 300 adolescent girls in psychiatric inpatient treatment. Diagnostic and Statistical Manual of Mental Disorders (4th ed.)-based psychiatric diagnoses were obtained from the Schedule for Affective Disorder and Schizophrenia for School-Age Children—Present and Lifetime and from data on family and behavioral characteristics from the European Addiction Severity Index (EuropASI). A total of 79 girls (26.3%) had experienced child sexual abuse during their lifetime. Child sexual abuse was associated with an adolescent’s home environment, sibling status, smoking, posttraumatic stress disorder diagnosis, self-mutilating behavior, and suicidal behavior. At least 62% of the perpetrators were acquaintances of the victims. Correlates of child sexual abuse can be used to identify child sexual abuse victims and persons at heightened risk for child sexual abuse.