The respondents were asked to assess their quality of life on a scale with lines (0-100 points), on the basis of which later an aggregate was developed, where the results between 0-40 points were evaluated low, 41-60 points average and 61-100 points as high quality of life. The respondents were divided according to their age similarly to other studies into groups with 5-year intervals, only the oldest respondents in the age of 85-101 years were gathered to one group due to their small number.

The questionnaire started with general data (gender, age, education, working, marital status, income, etc), which were followed by questions about subjective health assessments. II part of the questionnaire contained questions through which the elderly gave subjective assessments about their mental state, quality of life, emergence of fatigue and stress, relations with
relatives and friends.

The received quantitative data was analysed by using comparative frequency distribution of percentages (answers in different social groups were compared). In order to find differences, the Pearson’s correlation coefficient r was used and the respective probability p. In order to see to what extent different indicators or assessments can influence changes in the quality of life, ANOVA analysis was used (Levene’s test for equality of variances (F) and its probability p).

Since the age structure of Estonian population indicates in terms of gender that women dominate in older age groups, it was ensured that also in the study of 65+ there were 70 percent of women and 30 percent of men. The dominance of women is especially evident in the oldest age groups of respondents. Among the respondents the youngest was 65 and the oldest 101, who was a male and born in 1909 (see Figure 1).

Figure 1

Figure 1. Age distribution of respondents by gender (%)

Most of the respondents lived in Tallinn (76%) and had secondary or secondary specialised or higher education (79%). In terms of nationality Estonians dominated (65%), one-fifth were Russians and 7 percent belonged to another nationality – they were Ukrainians, Byelorussians, Tatars, Finnish or Jews.

Since the life-expectancy of men is shorter than that of women in Estonia (in 2009 the life-expectancy for women was 80 and for men 69 years), then this was expected to affect also marital status and, indeed, among men 76% of respondents were married and among women much less (p<0.001). Due to this 44 percent of women lived alone (p<0.001).

One-sixth assessed their quality of life with less than 40 points and one-fourth with more than 71 points. The rest of the assessments remained in the groups between those two.

Figure 2

Figure 2. Assessments of respondents’ quality of life during the last month (%)

Figure 2 shows that the range 41-50 was mentioned the most (often the assessment was complemented with the word – on average). Low assessments 0-10 and especially 11-20, were very scarce. Also maximum assessments were given seldom – only 4 percent of respondents assessed their quality of life with the score 81-90, but with maximum score of 91-100 even 7 percent.

But which indicators influence the quality of life of the elderly the most. In our study the quality of life indicator correlated most strongly with the following variables:

In case of all correlations the probability is p<0.001. It can be said that our data, as it emphasises the economic condition, health assessments, self-esteem evaluations and social relations, confirms largely the conclusions made by Allardt (1993) and Bowling (2002) (7; 8). So according to Bowling the feeling of wellbeing can be measured through the following indicators:

Compared with men, women had somewhat lower score of quality of life, but this difference was not statistically important. The analysis of age indicator showed that in younger age groups there were more respondents with higher quality of life (p<0.001). In case of education, income and health assessment there was a direct link that in case of higher score also the amount of respondents with higher quality of life was larger (p<0.001).

Since quality of life is strongly related with subjective health assessments, then the health of men and women in different age groups was studied.

There were among women considerably more those respondents whose assessment regarding health was bad and somewhat less those whose assessment was good or excellent (p<0.01). The same tendency was apparent also in the survey of Estonian population – in the 1993, 2003 as well as 2008 surveys the average health assessments of men were on a 5-point scale little higher than those of women – e.g. 3.61 and 3.51 in 2008 respectively (9).

As to age, it became apparent that the older the age-group under study, the less there were respondents who answered good about their health (p<0.001). The amount of respondents with good or excellent health decreased step-by-step with increasing age – from 20 percent among 65-69-years-old up to 6 percent in the age group of 85 and older.

Working in an older age is extremely important in terms of material security as in present-day Estonia people are forced to work longer due to relatively low old-age pension. Older people who live alone (in the study 37%) find it especially hard to cope. Also the need of older people to realise themselves professionally and the desire to maintain social relations has to be taken into account. In the population survey „Estonia 2008” the respondents were asked to assess, that if their material situation enables it, would they continue to work full-time. 27 percent of working male pensioners wanted to continue working as did 22 percent of female pensioners (10). Working in the pension age is supported also by legislation as working pensioners are able to receive at the same time wage and full pension.

Quality of life indicator has strong connection with the amount of income (p<0.001). It is in fact like an aggregate that contains the possibility to work, good health and higher level of education. These three factors form a strong chain the parts of which are closely connected and influence each other (in all cases p<0.001).

Better education guarantees higher income that raises the quality of life. Working in its turn increases, if accompanied by good health, income that is one of the strongest correlations of the study. This condition enables people to eat and dress better, spend free time according to their wishes, it decreases worries over every-day coping. In short – it enables a better quality of life.

In terms of working it is apparent that as expected people in younger age groups worked more (p<0.001). Nevertheless, it should be noted that after the age of 75 every tenth person worked. And although the number of respondents is too small to generalise, it is interesting to mention that among men of that age 11 percent worked and among women only 0.2 percent. Since older men had somewhat better subjective health assessments than older women, it can be said to account also for larger number of those who worked (p<0.001).

Family is a place where a person finds and expects the most encouragement, comfort and security and help if needed. The analysis showed how the families of our respondents met this wish or longing. The population survey „Estonia 2008” has shown that among different areas of life (working life, family life, and use of free time, economic situation, and health) the elderly are the most happy with family life. Even more – 92-93 percent of the elderly are contented with the relationship with their children (11).

Figure 3

Table 1. Number of close friends, degree of trusting people and feeling lonely depending on marital status (%)

Those who were married or lived in co-habitation had the most close friends – almost every second person had more than five friends (see table 1). Also two out of three who were married or lived in co-habitation trusted other people. It is therefore understandable that among married respondents there were, when compared to other groups, more those people who have never felt lonely – almost every second. There was a strong correlation between quality of life and being married (p<0.005). These answers conform the importance of marriage in an older age, as it is important to have a companion who helps you and supports you physically, materially as well as mentally, with whom it is possible to share every-day joys and worries when one grows old.

Figure 4

Table 2. Marital status and self-esteem characterising the life of respondents (%)

Marital status influenced the quality of life from very different sides. The proportion of married people was in many negative evaluations less than those who were single or divorced/widowed (see table 2). More than every fourth of them had often had insomnia because of worries and hardships (27%), but in comparison groups as much as 35-38 percent; they felt to a lesser extent unhappy and depressed (22 %). It was especially apparent that among those who were married only every tenth person had problems with loneliness. It was also the group with the highest income (26%). And all these aspects formed in an aggregated way a higher indicator of quality of life (44%).

Data of the survey pointed to the low self-esteem of the elderly. Among women there were more those respondents who had often felt that they did not matter for others (17% of men, 21% of women), or had felt worthless and useless (19% and 27% respectively). The older the person, the more there were answers where people felt that they were not important for others (among 65-69-years-old 16%, among the 85+ group 26%). There was also the tendency that people felt in an older age more often worthless (in age 65-69 group 21% felt so, but in the 85+ group 33%).

Below we present data about self-esteem, communication and need for help of respondents with different quality of life (see table 3).

Figure 5

Table 3. Assessments about self-esteem, communication and need for help in the groups of low and high quality of life (%, p)

Respondents with higher quality of life were in a more favourable position in terms of all indicators that were studied – there were less people among them who according to their own opinion are not important for others or who have felt useless or worthless or are more than usual tired or in stress. They also saw an objective and meaning to their lives. Among them every second respondent visited events outside home (went to theatre, cinema, church, sport events) at least once-twice in a month. There was frequent communication with friends and relatives – they were visited or went to see others. During the last two years every second person had found no new friends, but in the low quality of life group it was three out of four. Only 4 percent of the respondents of higher quality of life were in need of constant help, among lower quality of life group 30%.

In order to explain the accurate influence of different indicators for the quality of life we have used the ANOVA procedure (see table 4).

Figure 6

Table 4. Influence of socio-demographic and self-esteem for quality of life (ANOVA F, p, R)

Out of all socio-demographic characteristics the changes in quality of life were influenced by health the most (to the extent of 21%). The impact of other factors - gender, education, age and income – was below 5 percent. Health + working aggregate had the same impact as health by itself (21%). If we added to the model in addition to health also age factor, the ability to explain increased somewhat (23%), the same was seen if we analysed together health and income (23%).

The highest ability to explain was reached when the model contained health + number of people in household + marital status (28%). The result reflects the importance of immediate environment and family atmosphere in the assessment quality of life.

All socio-demographic characteristics played an important role in the changes of quality of life. At the same time an important aspect should be noted – their influence was always connected to health evaluations. It can, therefore, be said that health condition is the most important factor influencing quality of life.

It is important to analyse also the impact of people’s self-esteem for quality of life. For example self-esteem assessments like – I feel tired and stressed; I feel useless and worthless; I feel lonely; I have had insomnia due to worries and hardships. But at the same time it has to be acknowledged that when the strength of impact of socio-demographic characteristics for the changes in quality of life was between 21-28%, then self-esteem evaluations, although also important, had noticeably lower impact (12-23%).