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The Effects of Socioeconomic Status and Health on Transitions in Living Arrangements and Mortality: A Longitudinal Analysis of Elderly Finnish Men and Women From 1997 to 2002

¹ Helsinki Collegium for Advanced Studies, Helsinki, Finland.
² Population Research Unit, Department of Sociology, University of Helsinki, Finland.

Address correspondence to Pekka Martikainen, Helsinki Collegium for Advanced Studies & Population Research Unit, Department of Sociology, University of Helsinki, P.O. Box 18, FIN-00014. E-mail: pekka.martikainen{at}helsinki.fi

	Abstract

TOP Abstract Methods Results Discussion References

 
Objectives. Objectives were to study the effects of socioeconomic factors on transitions in living arrangements and mortality for men and women.

Methods. We used a sample of Finns aged 65 years and older living alone or with a partner at the end of 1997 (N = 250,787) drawn from population registers, and followed them up for transitions in living arrangements (with partner, alone, with others, institutionalized) and death at the end of 2002.

Results. Health conditions associated with functional difficulties were major determinants of institutionalization and death and were associated with transitions between private households. Low income among men and in particular not owning a home were independently associated with institutionalization and death among those living alone or with a partner at baseline. Among those living with a partner, the transition to living alone was associated with all socioeconomic factors but most strongly with a low income and not owning a home. Transitions to living with others were associated in particular with low occupational social class and education.

Discussion. Variations in the associations of different socioeconomic indicators with living arrangement transitions imply different social pathways. However, material socioeconomic indicators dominated other measures of socioeconomic status in determining such transitions, and their effects were only partly mediated by chronic conditions.

Key Words: Living arrangements • Socioeconomic status • Finland

IT is widely acknowledged that living arrangements are important determinants of well-being (Davis, Moritz, Neuhaus, Barclay, & Gee, 1997; De Jong Gierveld & Van Tilburg, 1999; Grundy, 2001), informal care (Kemper, 1992; Lafreniere, Carriere, Martel, & Belanger, 2003), and formal institutional care (Branch & Jette, 1982; Steinbach, 1992; Wolinsky, Callahan, Fitzgerald, & Johnson, 1992) in old age. Rapid secular changes in the distribution of living arrangements may have significant implications for the well-being of elderly persons and may have cost implications for the taxpayer (Chappell, Dlitt, Hollander, Miller, & McWilliam, 2004). In particular, in developed countries the number of elderly people living alone has generally increased in the past two decades, whereas fewer live with their children (United Nations Population Division, 2005). However, at the same time the increase in life expectancy—particularly among men—and the narrowing gap in age at marriage between the sexes (Lakdawalla & Schoeni, 2003) has led to an increase in the proportion of older men and women living with a partner.

Many of the trends in living arrangements are most pronounced in North America and northwest Europe (Tomassini, Glaser, Wolf, Broese van Groenou, & Grundy, 2004; United Nations Population Division, 2005). However, on the individual level the quantum and determinants of transitions in living arrangements remain only partly understood, with the most robust evidence being from the United States (Branch & Jette, 1982; Davis et al., 1997; Hays, Pieper, & Purser, 2003; Liang, Brown, Krause, Ofstedal, & Bennett, 2005; Mutchler & Burr, 1991; Wilmoth, 1998; Wolf & Soldo, 1988; Wolinsky et al., 1992) but also from some other countries (e.g., Brown et al., 2002; Evandrou, Falkingham, Rake, Scott, and the ESRC Research Group Simulating Social Policy for an Ageing Society, 2001; Glaser, Grundy, & Lynch, 2003; Grundy & Jitlal, 2007; Nihtilä & Martikainen, 2007b; Sarma & Simpson, 2007; Tomiak, Berthelot, Guimond, & Mustard, 2000). We used a large longitudinal population registration data set to study the determinants of transitions in living arrangements and mortality among Finnish elders.

Determinants of Living Arrangements Among Elders
Some of the major determinants of transitions in living arrangements are prior living arrangements, age, and gender (e.g., Branch & Jette, 1982; Brown et al., 2002; Glaser et al., 2003; Nihtilä & Martikainen, 2007b; Steinbach, 1992; Wolinsky et al., 1992). Prior living arrangements partly determine the transition options that are possible. However, the majority of previous studies on such transitions have targeted unmarried populations or people living alone (particularly women), mainly because variability and change are more extensive in these population subgroups (Wilmoth, 1998). This is an unnecessary barrier to a broader understanding of living arrangements among elderly persons and limits the policy relevance of research findings. Our focus was on people living alone or with a spouse or partner at baseline. These two living arrangements cover the majority of elders in northwestern Europe and the United States: More than 80% of men and women older than 65 typically live alone or as a married couple, the proportion of women living alone being much higher than that of men (Tomassini et al., 2004).

Many of the studies on the determinants of transitions in living arrangements have analyzed very broad age groups, often focusing on the combined population of all persons older than age 55. The results of such analyses are heavily influenced by the transitions of the young old, who are the most populous in such data sets. These analyses show that transitions are rare events. However, this kind of generalization is likely to best apply to those younger than the age of 65 or 70, a period of life before the onset of severe disability, illness, or institutionalization. Given the fact that these events are strongly gendered, living arrangement transitions will also be very different for men and women. We took this into account in our study by stratifying the analyses by gender and living arrangement at baseline.

Furthermore, our analyses focused on two additional explanatory factors: (a) socioeconomic status and (b) chronic illness. The emergence of poor health has, of course, major repercussions for elderly persons and may in many cases lead to transitions in living arrangements. In particular, chronic illness and functional disabilities (Aguero-Torres, von Strauss, Viitanen, Winblad, & Fratiglioni, 2001; Branch & Jette, 1982; Shapiro & Tate, 1988) are major determinants of entry into institutional care. Furthermore, functional status has been associated with household expansion (e.g., moving in with children or other relatives and adults; Hays, 2002; Hays et al., 2003).

Our study also emphasized the effects of different socioeconomic circumstances on transitions in living arrangements. Prior research in the United States in particular has indicated that low income is associated with a greater risk of entry into institutional care (Greene, Lovely, Miller, & Ondrich, 1995; Himes, Wagner, Wolf, Aykan, & Dougherty, 2000) and coresidence with others (Mutchler & Burr, 1991). Other socioeconomic characteristics are also associated with living arrangement transitions: Homeowners and those with a higher education are more likely to continue living with a spouse or partner and have a lower risk of moving into long-term institutional care (Breeze, Sloggett, & Fletcher, 1999; Liang et al., 2005; Nihtilä & Martikainen, 2007a). These effects are not always consistent, and their magnitudes vary. Attempts to explicitly compare the effects of different measures of socioeconomic status are rare, and it remains unclear whether these effects are independent of other main determinants of living arrangement transitions.

Much of the variability in results may relate to the different measures of socioeconomic position used in the different studies. Various indicators of socioeconomic position are correlated and are sometimes treated as though they are interchangeable. However, these indicators may instead be partially independent determinants of living arrangements, and they may reflect different aspects of social stratification and different causal pathways (Bartley, Sacker, Firth, & Fitzpatrick, 1999; Grundy & Holt, 2001; Lahelma, Martikainen, Laaksonen, & Aittomaki, 2004; Oakes & Rossi, 2003). Education reflects experiences of early life, when educational qualifications are usually obtained and when the seeds are sown for many behavioral patterns, attitudes, and aptitudes to obtain and make use of health knowledge, which may last until later life. Occupational social class, in contrast, mirrors experiences and exposures in adult life. These reflect status and power but may partly relate to past material conditions and exposure in the sphere of paid work. Income provides individuals and families with necessary material resources and determines their purchasing power. Given the major gender differences in the educational and labor market histories of those who are currently aged 65 and older, stratified analysis for both men and women is justified. Furthermore, many of the studies that have assessed the association between socioeconomic factors and living arrangements have been cross-sectional, and it is also unclear to what extent these effects are independent of or mediated by higher incidence of illness and disability among those lower down in the social hierarchy.

The large majority of studies on living arrangements and their transitions have investigated elderly U.S. populations. However, national variations in family setting and policy environments of elder care may mean that the transition patterns vary between countries. For example, in Finland long-term institutional care of elderly persons is more common than in southern European countries but about average in comparison with northwest Europe and the United States (Kinsella & Velkoff, 2001; Rostgaard, 2002; United Nations Population Division, 2005). This care is mainly publicly provided in nursing homes and health centers, and user fees, up to a maximum of 80%, are related to disposable income.

Aims
We used a 40% sample (N = 250,787) of Finnish men and women aged 65 years and older living alone or with a partner on December, 31, 1997, drawn from population registration data, in order to evaluate transitions in living arrangements and mortality at the end of 2002. These data had several methodological advantages that have enabled us to fill in the research gaps identified previously: (a) The data were longitudinal and thus allowed for a better assessment of causal direction, particularly in terms of the effects of socioeconomic status and health conditions on living arrangement transitions; (b) because these data were based on population registration there was practically no loss due to follow-up or self-report bias; (c) we had a uniquely large sample to study and systematically compare many possible transitions, including transitions into institutions; and (d) the data represented a non-U.S. population with a low prevalence of elder coresidence with children and universal coverage of health and social care for elderly persons; they thus allowed for the testing of previous U.S.-based results in a different social and policy context. Furthermore, given that many of the living arrangement transitions as well as the distribution of their determinants—such as the prevalence of disease or education—vary strongly between men and women, we carried out separate analyses for both.

Our specific research aims were the following:

1. To quantify transitions in living arrangements between private households (with a partner, alone, with others), institutionalization, and mortality among men and women living with a partner or living alone at baseline over a 5-year period.
   
2. To quantify the strength of the effects of different socioeconomic indicators on these transitions for men and women separately.
   
3. To estimate to what extent the effects of different socioeconomic indicators are overlapping or independent of one another.
   
4. To estimate to what extent the independent effects of different socioeconomic factors on transitions in living arrangements are mediated by chronic illness among men and women separately.
   

	METHODS

TOP Abstract Methods Results Discussion References

 
Data
The data used for these analyses consisted of a 40% random sample of the Finnish population aged 65 and older at the end of 1997 drawn from population registration data. For this study we included those (a) living with a married spouse or a cohabiting partner or (b) living alone at baseline (101,885 men and 148,902 women; this composed 89% of the total population of men and women aged 65 and older living in private households). We followed this population up for transitions in living arrangements and mortality at the end of 2002. Statistics Finland linked these data with the population registration data on sociodemographic characteristics and information on chronic health conditions at baseline. Statistics Finland provided data on basic sociodemographic characteristics and dates of death, the National Research and Development Centre for Welfare and Health (STAKES) provided information on long-term institutional care and the principal causes of prior hospitalization, and the Social Insurance Institution provided information on purchases of prescribed medication and entitlement to reimbursement for drug costs. Information on income came from the registers of the Finnish Tax Administration. Statistics Finland carried out the data linkage using personal identification codes.

Definition of Living Arrangements and Survival Status at Follow-Up
The unit of analysis we used for defining living arrangements was the household in which the person under study lived, comprising all persons living in the same dwelling unit. We thus defined subtenants (0.4% of Finns in 1990; Tilastokeskus, 1994) as part of the household, and more than one family may have lived in the same unit. We used the same criteria to define living arrangements at baseline and at follow-up.

We defined living arrangements and survival status at follow-up in the following way: (1) living with a spouse or a cohabiting partner, (2) living alone, (3) living in other private households (e.g., with children or other adults), (4) living in institutions providing long-term 24-hr care, and (5) dead.

We obtained the information on living arrangements and dates of death from the Statistics Finland population register. The stock-and-flow data of residents in institutional care (nursing homes, health centers and hospitals, and service homes) came from STAKES.

Socioeconomic Status
We used four measures of socioeconomic status: education, social class, household income, and home ownership. The three educational categories were based on the highest completed degree or certificate: tertiary education, intermediate education, and basic education or less or unknown.

We used four social classes: white collar, manual, farmer, and other. We classified unemployed and retired persons according to their previous occupations, and housewives according to the occupation of the head of the household.

Household disposable income per consumption unit covered all taxable income sources for all household members including wages, capital income, and taxable income transfers but excluding taxes. In the calculation of household consumption units the first household member was weighted as 1.0 unit and any other as 0.7 units. This corresponded to the Organisation for Economic Co-operation and Development (OECD) equivalence scale (OECD, 1982), with the exception of children younger than 18 years of age, who we weighted as adults (having coresident minor children in this kind of study population is very rare). We divided income into quartiles with cutoff points calculated from the combined data for elderly men and women.

We categorized home ownership in two classes: owner occupier and other.

Health at Baseline
In this study we used the following 18 dichotomous indicators of chronic health conditions 2 years prior to baseline: cancer, diabetes, dementia, psychosis, depressive symptoms, other mental health disorder, Parkinson's disease, other neurological disease, heart disease, stroke, chronic asthma or other similar chronic obstructive pulmonary disease, other respiratory disease, arthritis, osteoarthritis, hip fracture, other condition related to accident or violence, other hospital diagnosis, and other chronic disease that qualifies for the right to reimbursement for drug costs under the Special Refund Categories, which cover 75% or 100% of the costs of a single drug purchase. We used these as dichotomous variables in the multivariate models.

We used two main register sources to assess chronic diseases and conditions: (a) the principal cause of hospitalization during 1996–1997 and (b) the right to reimbursement for drug costs under the Special Refund Categories for certain diagnosed chronic medical conditions during 1997. We categorized the persons studied as having a chronic condition if they had it according to at least one of these sources. In addition, the following six categories of medical conditions were supplemented with information on the purchase of prescription medication during 1996–1997: cancer, diabetes, depressive symptoms, other mental health problem, Parkinson's disease, and other neurological disease. The principal cause of hospitalization was based on the 10th revision of the International Classification of Diseases (STAKES, 1999), purchases of prescription medication were based on the Anatomical Therapeutic Chemical Classification (Lääkelaitos, 1997, 1998), and the right to reimbursement for drug costs was based on the Finnish disease classification of the Social Insurance Institution (1998). For more details, see Nihilä and colleagues (2007).

Statistical Methods
We based the descriptive analyses of transitions in living arrangements on direct age-standardized percentages. We carried out age adjustment in single-year age groups, with the combined male and female populations for 1997 being the standard, and assessed tests of the associations of explanatory factors with transitions by means of chi-square tests. We used multinomial logistic regression models with similar age adjustment for the explanatory analyses of the transition determinants. We present the results of the multinomial logistic regression models as odds ratios, the first category of each explanatory variable being the reference group with an odds ratio of 1. We used STATA (StataCorp, 2003) for all of the calculations.

In evaluating the study aims we adopted the following modeling strategy. In order to establish the magnitude of the associations between different socioeconomic indicators and living arrangement transitions we fitted models that included each socioeconomic indicator and age (Model 1). In the following stage we aimed to determine the effects of each indicator net of the other, and thus we fitted models with all socioeconomic indicators (Model 2). In the final stage we assessed the possible mediating effects of health by including 18 dichotomous variables describing chronic conditions (Model 3). We carried out all of the analyses separately for men and women in order to quantify the differences in the magnitude and determinants of the living arrangement transitions.

	RESULTS

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Transitions in Living Arrangements and Mortality by Gender, Age, and Living Arrangements at Baseline
The proportions of men and women living with a partner at baseline were 77% and 42%, respectively. These figures declined with age, particularly among women. In all, 58% of the men and 73% of the women living alone at baseline continued to do so at follow-up (see Table 1). Among those living alone, death was the most common transition, followed by transition to an institution. Both of these transitions were more likely among those living alone than among those living with a partner, particularly at younger ages. Repartnering was very rare, except in the youngest age groups.

A somewhat different picture emerged among the women: The most common transition of women aged 65–79 years was to living alone, whereas among the older women it was to death. Transitions to institutions were almost twice as common among the women as among the men. However, women were less likely to live with a partner and die than men and were much more likely to live alone or with others at follow-up.

Age-Adjusted Transitions in Living Arrangements by Socioeconomic Status and Health Conditions
Overall, socioeconomic variables were rather consistently associated with the transitions (see Tables 2 and 3). Having a higher education, being in a white-collar occupational social class, having a higher income, and living in owner-occupied housing were associated with a lower risk of institutionalization and death regardless of baseline living arrangement. Moreover, moving to live with others was associated with a lower social position. Among those living alone at baseline, the effects of socioeconomic factors appeared stronger among men than women, whereas there were few gender differences in these effects among those living with a partner at baseline.

As expected, most of the health conditions were associated with death and entry into institutional care; dementia, mental health problems, and stroke were particularly strongly associated with both outcomes. The effects of health on mortality were stronger for the men than for the women, whereas the opposite was true for entry into institutional care.

The transition to living alone or with others was usually associated with somewhat better health among the men and women living with a partner at baseline, whereas for those living alone at baseline the transition to living with others was often associated with poorer health.

Multivariate Analyses of Determinants of Transitions in Living Arrangements
Living alone at baseline
Because repartnering was relatively rare among those living alone at baseline, our focus in this section is on transitions to living with others, transitions into institutional care, and death. The age-adjusted Model 1 of Table 4 mainly confirms the associations presented in Table 2. Of the various socioeconomic indicators, having a low income and not owning a home were most consistently associated with institutionalization and death. Having a lower educational level and being in the blue-collar class were associated with institutionalization, but these effects were mostly due to having lower income and not owning a home (see Model 2): Their associations with institutionalization and death were often fully explained or attenuated by about three fourths when we added income and home ownership to the model. Income and home ownership had the strongest and most consistent effects on mortality. Some of the effects of being in the lowest income bracket and not owning a home on institutionalization and mortality were mediated by the existence of various chronic health conditions (Model 3 adjusted for 18 dichotomous indicators of chronic conditions). In the fully adjusted model, the effects of socioeconomic status on these transitions continued to be stronger among men.

Multivariate results not shown here confirmed the finding that the effects of health conditions on the transitions were strong. Because of relatively strong comorbidity these effects were attenuated after we adjusted for all chronic conditions simultaneously. Further adjustment for socioeconomic factors had little effect on most of these associations.

Living with a partner at baseline
Model 1 of Table 5 also mainly confirms the associations presented in Table 3 for those living with a partner at baseline. When we adjusted all of the socioeconomic indicators in Model 2 simultaneously, household income, and home ownership in particular, remained the strongest determinants of both entry into institutional care and mortality. The effects of both education and social class were more modest. These results were similar to those observed for men and women living alone at baseline. However, the transition to living with others was much more strongly associated with education and social class, and these effects remained strong after we adjusted for income and home ownership.

Multivariate results not shown confirmed the results presented in Table 3 that the effects of chronic conditions were strong for institutional entry and mortality. These effects were attenuated after we adjusted for other chronic conditions, but adjustment for socioeconomic factors had little effect.

	DISCUSSION

TOP Abstract Methods Results Discussion References

 
Transitions in Living Arrangements
We used a 40% sample (N = 250,787) of Finnish men and women aged 65 years and older at the end of 1997 and followed this sample up for transitions in living arrangements and mortality. At the end of the 5-year follow-up period, about 65% of the men and 59% of the women living with a partner at baseline remained in the same living arrangement. Among those living alone at baseline, the corresponding figures were 58% and 73%. Death was the most common transition in all groups except for the 65- to 79-year-old women living with a partner at baseline, for whom transition to living alone was more common. Moving to an institution was generally the second most common transition. Transitions to living with others (e.g., children and other relatives) were less common, with only 3.9% of all women and 1.5% of all men making this transition in the 5-year period.

The quantum of these transitions is difficult to compare across countries because of large differences in data sources (e.g., the definition of the study population), data quality (e.g., nonresponse), the definition of living arrangements (e.g., institutional residence), and analytical choices. However, if one takes these methodological differences into account, the evidence indicates that the stability in living arrangements in Finland is similar to that in the United States (Liang et al., 2005), the United Kingdom (Evandrou et al., 2001), and Japan (Brown et al., 2002). However, when transitions occur, the Japanese are more likely to move into coresidence with their children, a pattern that is fully consistent with more family-based care of elderly people (Brown et al., 2002).

In addition to family care, the provision of and access to public or private home-based services may also go some way in explaining national differences in transitions in living arrangements. Elderly people living in countries with comprehensive home-based services may be able to maintain independent living longer than those residing in other countries. Overall, however, evidence of national differences in home-based services is quite difficult to assess (Kinsella & Velkoff, 2001; OECD Health Project, 2005; Rostgaard, 2002). In particular, definitions of home services differ between countries and in the relevant studies, and the most commonly used measure—the proportion of elders receiving at least some care—does not capture the intensity of home services satisfactorily. Furthermore, in many countries the observed increases in home-based care may reflect a policy change away from institutional care (OECD Health Project, 2005). However, in some other countries—as in the Finnish case—home-based care appears to have declined since the early 1990s, which may be due to a policy shift from less intensive help (e.g., with cleaning) to more intensive personal care (e.g., with bathing, daily getting into and out of bed; Rostgaard, 2002). More research is needed before researchers can establish the links between home-based services and national differences in living arrangement transitions with any certainty.

Effects of Socioeconomic Factors on Transitions in Living Arrangements
Our specific aim was to study and contrast the effects of various socioeconomic factors on living arrangement transitions and to assess the independent effects of each factor after adjusting for the other factors and health status. By doing so we hoped to be able to more clearly identify the social pathways by which socioeconomic factors influence the transitions.

Our results showed that income and home ownership were independently associated with institutionalization and mortality among those living alone or with a partner at baseline. The effects of education and social class were weaker, particularly after mutual adjustment for all socioeconomic indicators. Previous evidence corroborates our findings that the more material aspects of social position are strongly associated with health and mortality at older ages (Grundy & Holt, 2001; Martelin, 1994; Martikainen, Mäkelä, Koskinen, & Valkonen, 2001) as well as in middle age (Martikainen, Adda, Ferrie, Davey Smith, & Marmot, 2003; Martikainen et al., 2001). In particular, the independent association between home ownership—a measure of social position earned over decades and possibly across generations—and institutionalization and mortality indicates that the causes of these associations are likely to be related to a set of both early and current material advantages. In the case of entry into institutional care, these effects of higher income may also be associated with better quality housing and the ability to purchase home care. However, as we had no direct information on home care and informal support, particularly given by living children (Frankenberg, Chan, & Ofstedal, 2002; Grundy, 2000; Wolf & Soldo, 1988), it remains difficult to accurately estimate to what extent formal and informal support mediate the effects of these socioeconomic factors.

Although death and institutionalization are in many cases preceded by a period of ill health, the higher risk of these transitions in the lower socioeconomic groups was only partially (about 20% attenuation) explained by the chronic health conditions that we measured. There are at least two reasons why these independent effects remained. The first of these relates to our health measurement. Full and comprehensive health measurement is probably impossible in a population-based study (for a more detailed discussion, see "Methodological Issues"), and thus the unexplained effects of socioeconomic indicators may be due to unmeasured health differences between the socioeconomic groups. For example, we underestimated or lacked information on conditions that are associated with less serious functional difficulties, but we believe that the way in which we measured health covered serious life-threatening chronic diseases very well. Second, over the 5-year follow-up period health problems that were not present at baseline were likely to emerge and to contribute to the transitions that we were studying. The implication of this is that socioeconomic differences in transitions in old age are not necessarily driven by differences in long periods of disability and frailty but are often more acute (e.g., accidents at home).

The transition to living with others was associated with social class in particular. Among those living with a partner at baseline, the transition to living alone was also associated with all socioeconomic factors, but most strongly with income and home ownership. The effects of socioeconomic factors on transitions between private households were, to a large extent, independent of chronic conditions, although their effects on institutionalization and mortality were somewhat attenuated.

Overall, it appears likely that the effects of socioeconomic factors on transitions in living arrangements can be only partially explained by socioeconomic differences in chronic health conditions. Consequently, more direct material factors—such as having the money to maintain a single household and having the ability to purchase home care, and the values and preferences of elderly persons regarding their living arrangements—could also play an important role. This latter explanation may be particularly potent for understanding the effects of education and social class net of income and home ownership: Those in higher socioeconomic positions may value independent living more than those in lower positions. Although attitudes toward elder care are more family oriented in southern European countries than in northern Europe (Tomassini et al., 2004), evidence concerning socioeconomic differences in values, attitudes, and preferences in living arrangements among elders is scarce. Furthermore, the applicability of findings between countries is complicated because national differences in the perceived quality, availability, and cost of long-term care may influence responses to attitudinal questions about living arrangement preferences.

Effects of Chronic Conditions on Transitions in Living Arrangements
As expected, several chronic health conditions—particularly dementia, mental health problems, stroke, and hip fracture—were strongly associated with transitions to institutions and mortality. In the case of transitions to institutions, these findings reflect the strong impact that these chronic conditions have, with cognitive and physical functional difficulties that make independent living impossible. Because of comorbidity, these effects were attenuated after we adjusted for other health indicators.

Health also determined transitions between private households, but these effects were modest compared with the effects on the transition to institutions and on mortality. In particular, among those living with a partner at baseline only dementia was strongly associated with the transition to living with others. Consistent with the results of Liang and colleagues (2005) on U.S. adults, somewhat larger effects of chronic conditions were evident among those living alone at baseline. Our findings provide support for the idea that the effects of severely disabling chronic conditions are buffered by the presence of, and support provided by, a coresident partner.

Methodological Issues
One problem with these data is that we had no direct information on living children (Frankenberg et al., 2002; Grundy, 2000; Wolf & Soldo, 1988) and limited information on complex households. A more specific problem was that one of our living arrangement categories at follow-up—living with others—included those who were living with their children as well as those who were living with other relatives or other adults. Confirmatory analyses on another data set of these participants showed that of the households classified as "other," 62% were two-person households. In about 56% of these households the elder was living with a child who had no family of his or her own, and in the rest of the households the coresident was usually of approximately the same age as the index person. A further 19% of "other" households were three-person households. In about 30% of these households the elder was living with children with no family of their own, whereas a further 50% were living with a younger family (one of the members of this younger family was likely to be a child of the elderly person). This proportion was even higher in households with more than three members. We thus feel that we were justified in considering these "other" households as mainly consisting of close relatives.

Our measure of living arrangement transition may have been problematic because it only considered states at baseline and at the end of the follow-up; thus, all transitions occurring between these two remained unobserved. Analyses of first transitions would have overcome this problem. However, although our data allowed us to date institutional entry and death on a daily basis, they allowed us to assess transitions between private households only on an annual basis. Although such data did not allow us to carry out full analyses of first transitions, we did carry out confirmatory analyses. As might have been expected, these results showed that in the case of first transitions, those between private households and those to institutional care became more common, and death correspondingly became less common (in comparison with transitions measured only between baseline and the end of the follow-up). However, the effects of socioeconomic factors on first transitions were very similar.

We based our data on disease prevalence on registration data on hospital and medication use. In general, the prevalence rates we found were quite close to those derived from population-based clinical examinations and other sources (e.g., Aromaa & Koskinen, 2004). The two most notable exceptions were for dementia and osteoarthritis, both of which were underestimated in our study. Information on both conditions was based on hospital-use data and was thus likely to represent the most severe cases. Similarly, our study could not capture cancers that were not being actively treated or that had been cured. The chronic disease data were thus likely to underestimate physical and cognitive functional difficulties in the population (for a more thorough discussion, see Nihtilä et al., 2007).

Large population-based datasets linking different administrative registers carry several major advantages. In the analyses of the association between health and living arrangements it is often uncertain which of the two factors precedes the other. Using longitudinal registration data with detailed information on transitions in living arrangements and various chronic health conditions and socioeconomic indicators at baseline allowed us to assess these effects reliably. Furthermore, the data did not suffer from loss to follow-up, missing values, misreporting, or lack of power, which may be serious problems with survey-based data.

Conclusions
We have shown that socioeconomic conditions and chronic health problems are important determinants of transitions in living arrangements and mortality among Finnish men and women aged 65 years and older. Health conditions—particularly those that can be associated with both physical and mental functional difficulties—are, of course, major determinants of institutionalization and death, but they are also associated with transitions in living arrangements between private households. Whereas material socioeconomic indicators are more closely associated with transitions to institutions and mortality, education, and particularly social class, seem to be major determinants of transitions to living with others, possibly reflecting the values and preferences of elders regarding their living arrangement choices. Among those living with a partner at baseline, the transition to living alone is associated with all of the socioeconomic indicators.

Our results show that the associations between different socioeconomic factors and living arrangement transition are only partly mediated by differences in chronic health conditions. Although socioeconomic indicators reflecting the material conditions of life appear to dominate over other measures of socioeconomic status as determinants of elder transitions, variations in these associations imply that different transitions are determined by different social pathways. Because for most individuals home ownership more than any other measure of socioeconomic position reflects wealth accumulated over the life course, it is likely that the causes of the associations with living arrangement transition are also related to the accumulation of early and current material benefits and, for example, to the security of returning back to owner-occupied housing after extended stays in hospital or long-term care. However, to the extent that the socioeconomic circumstances associated with household income—and direct material factors, such as the ability to purchase home care and better quality housing—are modifiable, these results may provide opportunities for reducing the risk of premature institutionalization and death in the elderly population.

	Acknowledgments

 
We are grateful to the National Research and Development Centre for Welfare and Health (STAKES), the Social Insurance Institution, and Statistics Finland (Permission TK 53-576-04 and TK 53-499-05) for making the data available to us. This study was supported by the Academy of Finland (Grants 210752 and 205631). The research was part of the European Union-funded project Major Ageing and Gender Issues in Europe.

P. Martikainen planned the study, supervised the data analysis, and wrote the paper. E. Nihtilä helped plan the study and analyses and revised the paper. H. Moustgaard performed the statistical analyses and contributed to the writing of the paper.

	Footnotes

 
Decision Editor: Kenneth F. Ferraro, PhD

Received for publication July 24, 2007. Accepted for publication January 10, 2008.

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TOP Abstract Methods Results Discussion References

 

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