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Aim: To describe long-term care (LTC) use in Finland and Sweden in 2020, by reporting residential entry and exit patterns including hospital admissions and mortality, compared with the 2018-2019 period and community-living individuals., Methods: From national registers in Finland and Sweden, all individuals 70+ were included. Using the Finnish and Swedish study populations in January 2018 as the standard population, we reported changes in sex- and age-standardized monthly rates of entry into and exit from LTC facilities, mortality and hospital admission among LTC residents and community-living individuals in 2020., Results: Around 850,000 Finns and 1.4 million Swedes 70+ were included. LTC use decreased in both countries from 2018 to 2020. In the first wave (March/April 2020), Finland experienced a decrease in LTC entry rates and an increase in LTC exit rates, both more marked than Sweden. This was largely due to short-term movements. Mortality rates peaked in April and December 2020 for LTC residents in Finland, while mortality peaked for both community-living individuals and LTC residents in Sweden. A decrease in hospital admissions from LTC facilities occurred in April 2020 and was less marked in Finland versus Sweden., Conclusions: During the first wave of the pandemic mortality was consistently higher in Sweden. We also found a larger decrease in LTC use and, among LTC residents, a smaller decrease in hospital admissions in Finland than in Sweden. This study calls for assessing the health consequences of the differences observed between these two Scandinavian countries as part of the lessons from the COVID-19 pandemic., Competing Interests: Declaration of conflicting interestsThe authors have no conflicts of interest to declare.

This study aims to estimate direct health-related costs for victims of intimate partner violence (IPV) using nationwide linked data based on police reports and two healthcare registers in Finland from 2015 to 2020 ( N  = 21,073). We used a unique register dataset to identify IPV victims from the data based on police reports and estimated the attributable costs by applying econometric models to individual-level data. We used exact matching to create a reference group who had not been exposed to IPV. The mean, unadjusted, attributable healthcare cost for victims of IPV was €6,910 per individual over the 5-year period after being first identified as a victim. When adjusting for gender, age, education, occupation, and mental-health- and pregnancy-related diagnoses, the mean attributable health-related cost for the 5 years was €3,280. The annual attributable costs of the victims were consistently higher than those for nonvictims during the entire study period. Thus, our results suggest that the adverse health consequences of IPV persist and are associated with excess health service use for 5 years after exposure to IPV. Most victims of IPV were women, but men were also exposed to IPV, although the estimates were statistically significant only for female victims. Victims of IPV were over-represented among individuals outside the labor force and lower among those who were educated. The total healthcare costs of victims of IPV varied according to the socioeconomic factors. This study highlights the need for using linked register data to understand the characteristics of IPV and to assess its healthcare costs. The study results suggest that there is a significant socioeconomic gradient in victimization, which could also be useful to address future IPV prevention and resource allocation., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interests with respect to the authorship and/or publication of this article.

Aims: This study aimed to find out how place of death varied between countries with different health and social service systems. This was done by investigating typical groups (concerning age, sex and end-of-life trajectory) of older people dying in different places in Finland and Norway. Methods: The data were derived from national registers. All those who died in Finland or Norway at the age of ⩾70 years in 2011 were included. Place of death was analysed by age, sex, end-of-life trajectory and degree of urbanisation of the municipality of residence. Two-proportion z -tests were performed to test the differences between the countries. Multinomial logistic regression analyses were performed separately for both countries to find the factors associated with place of death. Results: The data consisted of 68,433 individuals. Deaths occurred most commonly in health centres in Finland and in nursing homes in Norway. Deaths in hospital were more common in Norway than they were in Finland. In both countries, deaths in hospital were more common among younger people and men. Deaths in nursing homes were commonest among frail older people, while most of those who had a terminal illness died in health centres in Finland and in nursing homes in Norway. Conclusions: Both Finland and Norway have a relatively low share of hospital deaths among older people. Both countries have developed alternatives to end-of-life care in hospital, allowing for spending the last days or weeks of life closer to home. In Finland, health centres play a key role in end-of-life care, while in Norway nursing homes serve this role.

Objective: To discover whether successful aging, understood as a multidimensional concept, predicts further survival in very old people., Method: The population sample consisted of 1,370 persons aged 90 or over in the Vitality 90+ study. Four alternative models of successful aging were constructed, each of them consisting of physical, psychological, and social dimensions. Mortality was followed up after 4 and 7 years., Results: Three out of four models significantly predicted survival at both follow-ups for the whole group. Separately, "success" in the physical, psychological, and social components was also associated with higher survival. The associations were stronger in women than in men., Discussion: Successful aging, measured using physical, psychological, and social dimensions, predicts the length of future life in nonagenarians., (© The Author(s) 2014.)

Aims: To analyse whether transitions between care settings differ between municipalities in the last 2 years of life among older people in Finland., Methods: Data were derived from Finnish national registers, and include all those who died in 2002 and 2003 at the age of 70 or older except those living in very small municipalities (n=67,027). Data include admissions and discharges from health and social care facilities (university hospitals, general hospitals, health centres, residential care facilities) and time spent outside care facilities for 730 days prior to death. Three-level negative binomial regression analyses were performed to study the effect of municipal factors on (1) the total number of all care transitions, (2) the number of transitions between home and different care facilities, and (3) transitions between different care facilities., Results: The municipality of residence had only a minor effect on the total number of care transitions, but greater variation between municipalities was found when different types of care transition were examined separately. Largest differences were found in care transitions involving specialised care. Age structure, urbanity, and economic situation of the municipality had an impact on several different care transitions., Conclusion: The total number of care transitions in 2 final years of life was approximately similar irrespective of the municipality of residence, but the findings imply differences in transitioning specialised care. Potentially, this may suggest inequality between the municipalities, but more detailed studies are needed to confirm the factors underlying these differences.

Aims: To describe and analyse municipal differences in health and social service use among old people in the last 2 years of life., Methods: The data were derived from national registers. All those who died in 2002 or 2003 at the age of ≥ 70 years were included except those who lived in very small municipalities. The services included were different types of hospitals, long-term care, and home care. The variation in service use was described by coefficients of variation (CV). To analyse local differences, three-level (individual, municipal, and regional) binary logistic and Poisson regression analyses were performed., Results: A total of 67,027 decedents from 315 municipalities in 20 hospital districts were included. There was considerable variation in service use between residents of different municipalities, especially in the types of hospital used. Of the individual-level variables age and use of other services were associated (p < 0.05) with use of all services. Of the municipal-level variables, indicators describing the service pattern in the municipality were associated with use of all services and average age of decedents with most of the services. The presence of a university hospital in the hospital district increased the probability of using university and general hospitals, but among the users increased days in university hospital and decreased days in general hospital., Conclusions: Considerable differences between municipalities exist, but these cannot be exhaustively explained. Behind the differences are probably factors which are difficult to describe and quantify, such as historical developments and political realities.