Issues related to population ageing and older persons in general have secured a prominent role in the literature surrounding health and social policy. For example, the International Conference on Population and Development, held in 1994, recognised that the economic and social impact of population ageing is both an opportunity and a challenge to all societies (United Nations 2009).

The need for all societies to address the significant consequences of population ageing, namely the challenge of maintaining health and well-being in old age, has been reiterated worldwide (Fernández-Ballesteros 2007:15; United Nations 2009). Considering that sense of coherence (SOC) was developed in an approach that focused on factors that support human health and well-being, the study of SOC is pertinent amongst older populations.

To fully understand SOC and its development, knowledge about factors contributing its development is needed. Hence, the analysis of the impact of satisfaction with life (SWL), sociodemographic, lifestyle and health-related factors on SOC, in the multi-dimensional and multi-cultural context of ageing well, is essential.

Increasing longevity may result in growing challenges, such as longer pensions and a greater need for health care and old-age support. It also highlights the need to make the best of the opportunities that an ageing population brings (e.g. longer employment opportunities, family composition and migration trends) (Fernández-Ballesteros 2007; United Nations 2009).

Public health research has shown that social and personality factors are amongst the key determinants of health and well-being (Volanen et al. 2004:322). In this context, SOC is a global orientation that expresses the extent to which one has a pervasive, enduring, dynamic feeling of confidence that (a) the stimuli deriving from one’s internal and external environments in the course of one’s life are structured, predictable, and explicable; (b) suitable resources are available to meet the demands posed by these stimuli; and (c) these demands are challenges, worthy of investment and engagement (Antonovsky 1987:19). Moreover, Antonovsky (1979, 1987) developed his salutogenic model of health, an approach focusing on factors that support human health and well-being, rather than focusing on factors that cause disease. SOC seems to be a health-promoting resource, which strengthens resilience and develops a positive, subjective state of health (Amirkhan & Greaves, 2003; Eriksson & Lindström 2006). Growing research comprises several studies on the topic of SOC and older adults (Dragaset et al. 2008; Sagy & Antonovsky 1990; Steiner et al. 1996; Surtees et al. 2003).

Considering the relevance of living well in old age and the specific challenges for health and well-being into old age, there is a wealth of studies with regard to SOC as a predictor of health both in community and clinical settings (Antonovsky & Sagy 1985; Henje Blom et al. 2010; Kalimo et al. 2003; Kivimäki et al. 2000; Larsson & Kallenberg 1996; Sairenchi et al. 2011; Suominen et al. 2001) and psychological variables such as well-being, SWL and quality of life (Kalimo & Vuori 1990; Petrie & Brook 1992; Söderberg, Lundman & Nordberg 1997). That being said, the background predictors of SOC have been much less examined (Volanen et al. 2004:322, 2006:515); in fact, only a few earlier studies have focused on the factors promoting SOC. In spite of its psychological nature, it has been shown that sociodemographic and health-related variables may have an impact on SOC (Volanen et al. 2004, 2006), especially social class, age and work conditions (Larsson & Kallenberg 1996; Lundberg 1996; Lundberg & Nyström Peck 1994). Moreover, in a study by Larsson and Kallenberg (1996), youth, occupation, income and household size were all related to strong SOC. In addition, the level of education, occupational status and income in adulthood also promoted a strong SOC (Leppänen 1999).

Previous studies also have found a stronger SOC amongst men than women (Anson et al. 1993; Antonovsky & Sagy 1985; Larsson & Kallenberg 1996; Suominen et al. 1999). Additionally, social support had a positive effect on SOC (Larsson & Kallenberg 1996; Wolff & Ratner 1999). In brief, previous studies suggest that both sociodemographic and health factors contribute to SOC. However, partially-contrasting findings regarding, for example, the effect of age, education and living conditions on SOC, have been obtained and present no consensus in literature given that they might predict either an increase or a significant decrease in SOC (Larsson & Kallenberg 1996; Leppänen 1999; Lundberg 1996, 1997; Lundberg & Nyström Peck 1994; Suominen 1993; Suominen et al. 1999; Volanen et al. 2004; Wolff & Ratner 1999). Moreover, the authors of the present study found no previous studies regarding the effect of SWL and lifestyle factors on SOC. Furthermore, to the best knowledge of the authors there are no previous studies that explore the simultaneous impact of sociodemographic, lifestyle and health-related factors on the SOC of older adults. This research is, therefore, designed to develop a comprehensive picture of the role of SWL and sociodemographic, lifestyle and health-related factors in predicting SOC amongst the elderly.

A quantitative approach and a descriptive design method refer to the structured statistical analysis of the profile (demographic data) of the participants included in the study (Babbie & Mouton 2001:49; Polit & Hungler 1995:15). Descriptive methods are not always highly structured. According to Bowling and Ebrahim (2005:120), a cross-sectional study can be described as a measurement of the frequency of a specific attribute, in a defined sample population at a certain point in time. The cross-sectional design of our study was appropriate for obtaining a snapshot of predictors of SOC amongst community-dwelling older adults, without manipulating the study environment. This design also allowed us to compare different variables (e.g. sociodemographic) and population groups at a single point in time – in this case, the elderly from four different nationalities. The information obtained is specific to this study and cannot be generalised because of the limitations posed by convenience sampling methods.

A number of participants were living with their children. This occurred amongst participants from all four nationalities studied, especially when they were not living in their country of origin.

A convenience sampling method was used to select the participants (Polit & Beck 2008:341). Participants who were not residents of any European country and who had been diagnosed with concurrent psychiatric disorders, according to DSM-IV criteria (American Psychiatric Association 1994), were excluded.

In this context, participants with previous psychiatric disease, including major illness, anxiety, depression, or with known substance abuse disorders, were excluded. This was done to remove possible confounding variables that may have had an impact on SOC. Participants were also excluded if they had difficulty in completing the Mini-Mental State Examination (MMSE) (Folstein, Folstein & McHugh 1975), which was administered to all of the participants (results summarised in Table 1).

The participants’ SOC was assessed by means of the Orientation to Life Questionnaire, which covered the three main subcomponents of SOC: comprehensibility, manageability and meaningfulness (Antonovsky 1987, 1993). The OLQ comprises 29 items which ask individuals to rate the extent to which they agree (on a seven-point Likert-type scale) to items such as: ‘How often do you have the feeling that there’s little meaning in the things you do in your daily life?’ and ‘How often do you have feelings that you’re not sure you can keep under control?’. Negative items were reverse-scored, meaning that higher scores on this scale indicate greater levels of SOC. In previous studies, the OLQ presented good psychometric properties, including the measure of internal consistency which ranged from 0.82 to 0.95 (Antonovsky 1993; Eriksson & Lindström 2006).

To evaluate the participants’ SWL – the cognitive appraisal of the participants’ overall subjective well-being – the validated version of the SWLS was applied (Diener et al. 1985). The SWLS is a five-item, self-reporting measure presented on a seven-point Likert-type scale that ranges from ‘strongly disagree’ to ‘strongly agree’. Items included such statements as ‘In most ways my life is close to my ideal’ or ‘I am satisfied with my life’. The five-item instrument presented good psychometric properties, including an alpha coefficient equaling 0.87 (Diener et al. 1985).

Sociodemographic characteristics (age, gender, marital status, professional status, educational level, living conditions and family’s annual income), as well as lifestyle and health-related characteristics (recent disease and physical exercise) were also assessed. The sociodemographic, health- and lifestyle-related variables were quantified and integrated into the structural equation model in order to assess their possible influence on the participants’ SOC.

Once informed consent had been received, the participants went through a cognitive screening assessment to determine eligibility, using the MMSE (Folstein et al. 1975). After the initial screening, the participants completed their questionnaires under the supervision of a postgraduate psychology student. They had an opportunity to seek clarification with regard to how the questionnaires should be completed, as well as with regard to any questions they found difficult to understand. A code number was given to each participant and the scores were indicated next to this number.

The questionnaires were filled in by 458 older adults. Four were subsequently excluded for not providing complete information regarding their sociodemographic, health- and lifestyle-related characteristics. Some of the final 454 participants asked to be informed of the results at the end the study.

To start, the data were analysed to check for outliers and distribution forms. No missing value imputation was made. Next, the data were analysed by means of descriptive statistics for the sociodemographic, lifestyle and health-related variables, SWL and SOC. Multicollinearity between the independent variables was explored using the variance inflation factor provided by the Statistical Package for Social Sciences (SPSS) programme (version 19.0; SPSS Inc., Chicago, IL). All variables presented a value below ‘5’, indicating the absence of collinearity (Maroco 2010; Weisberg 1985). To test the structural model for SOC, a structural equation model was built relating the dependent variable (SOC) with ten independent variables (age, gender, marital status, professional status, family’s annual income, educational level, living conditions, absence of a recent disease, physical activity and SWL). The model was evaluated using SPSS and Analysis of Moment Structures (AMOS) software for Windows (version 19.0; SPSS Inc., Chicago, IL). The quality of the fit of the structural model was given by chi-square statistics (X²/df), comparative fit index (CFI), goodness of fit index (GFI) and root mean square error of approximation (RMSEA). The reference values were used the reference values currently practised in structural equation modelling (Byrne 2001; Maroco 2010).

A two-step approach was employed in order to evaluate the structural model. Firstly, the measurement model was evaluated to demonstrate an acceptable fit. Thereafter, the structural model, encompassing the dependent and the ten independent variables, was adjusted and the significance of the structural trajectories was evaluated.

In order to determine whether nationality groups diverged significantly concerning their SOC scores, group differences were evaluated by means of the one-way analysis of variance (ANOVA), followed by a post-hoc Tukey’s test. These were run and analysed using the SPSS software.

The measurement model (X²/df = 2.121; CFI = 0.962; GFI = 0.884; RMSEA = 0.050; CI = 90% [0.046; 0.054]; p = 0.535), as well as the structural model (X²/df = 1.816; CFI = 0.959; GFI = 0.877; RMSEA = 0.042; CI = 90% [0.039; 0.046]; p = 1.000), showed a good fit. Significant predictors are highlighted in Figure 1.

FIGURE 1: Structural model for Sense of Coherence and its relationship with Satisfaction with Life, sociodemographics, lifestyle- and health-related variables.

The Angolan participants, on the whole, scored higher for SOC (M = 4.77; SD = 1.001), whilst the English participants scored the lowest (M = 4.39; SD = 0.943). This led to the Angolans having a significant but not considerably higher mean average of SOC than the English and Brazilian participants. Furthermore, the ANOVA results indicated that in this community-dwelling sample, the SOC score presented significant but not substantial differences between at least two nationalities (F₍₃₎ = 5.204; p < 0.01) (see Table 2), namely between the Angolan and Brazilian or English participants and between the English and Portuguese participants (see Table 3). Post-hoc comparisons of means (Tukey’s honestly significant difference) indicated that the Angolan participants had a significantly higher SOC score than the Brazilians (MD = 0.359; p = 0.028) and the English (MD = 0.386; p = 0.013). Additionally, the Portuguese participants had a significantly higher SOC score than the English (MD = 0.336; p = 0.028) (see Table 3). No significant differences were seen when comparing the Portuguese participants’ score against the Angolans’ and Brazilians’ scores, as also seen in Table 3.

The ethical principles of respect for autonomy, non-maleficence, beneficence and justice were thus adhered to throughout the research process (Dhai & McQuoid-Mason 2011:43–44). Informed consent was received from all participants and the study protocol was approved by the Research Unit in Psychology and Health.

The participants’ private information was not shared without the individuals’ knowledge or against their will. Also, participants were informed that participation in this research was voluntary and that they could terminate their collaboration at any time, without any consequences. No private information was requested. With this in mind, the information about income was asked considering a cut-off point of 10 000 Euros (i.e. not asking for participants’ specific income), so there was no invasion of privacy. No invasive procedures were administered, nor were anthropometric, biochemical or blood measurements collected. The selection process of participants was done fairly as each participant fitting the criteria had an equal chance of being selected.

Only questionnaires, and no other content, were completed by the respondents, and no risk or hazards were involved. Questionnaires were completed in the participants’ homes. The participants, therefore, did not incur any financial expense (Burns & Grove 2001:196; DENOSA 1998:23). Benefits for the participants included being given an opportunity to indicate their perspectives on SOC and SWL in a positive, supportive environment, in order to contribute to the scientific knowledge about what contributes to ageing well.

Unexpectedly, marital status was unrelated to SOC amongst our participants. Conversely, Volanen and her colleagues (2004) found that a poor relationship with a partner was a major threat to SOC. Moreover, the bearing of the quality of family relationships and family life on SOC has been neglected in the SOC literature (Volanen et al. 2004). The family’s income and educational level were also unrelated with SOC, which again did not corroborate previous literature. SOC is primarily an attitude held by people who are well-educated and occupy higher socioeconomic positions (Geyer 1997). That being said, it seems necessary that SOC needs to be regarded from a wider viewpoint, including life spheres other than just people’s socioeconomic and educational characteristics.

Although previous research indicated the positive effects of an active professional status on older adults’ SOC, our outcomes did not suggest this potential relation. Having poor working conditions and a passive job might weaken one’s SOC (Larsson & Kallenberg 1996; Lundberg 1996; Volanen et al. 2004). Furthermore, as suggested in previous studies, success in fulfilling challenges may yield more ‘positive subjective age’ (Kleinspehn-Ammerlahn, Kotter-Grühn & Smith 2008:384; Ward 2010) and productive activities should contribute to the well-being of older adults (Wahrendorf & Siegrist 2010:67).

Very few studies approached the health factors that affect SOC. There are, however, many studies about the predictive nature of SOC toward health (Eriksson & Lindström 2006; Larsson & Kallenberg 1996; Lundberg 1996; Söderberg, Lundman & Nordberg 1997; Volanen et al. 2004, 2006). Our findings corroborated these studies, as the absence of recent disease and the practice of physical activity were positively and significantly related to SOC amongst our participants. In fact, as also stated by Antonovsky (1987), a stronger SOC is associated with better perceived health in general, a relationship that has been manifested in previous studies, regardless of age, sex, ethnicity, nationality and study design (Antonovsky 1993; Eriksson & Lindström 2006). Previous studies have found SOC to be associated with health and it may also be a potential reason or mediating process for psychosocial and socioeconomic inequalities in health (Anson et al. 1993; Suominen et al. 1999; Vahtera & Pentti 1995). Additionally, a healthy lifestyle was frequently indicated as contributing to ageing well (Bowling 2007; Smith et al. 2002).

To the best of our knowledge, the absence of recent disease and the presence of physical activity have not been shown to be predictors of SOC in other research. However, in this study, these two variables are, in fact, very strong positive predictors of SOC. Specifically, older adults that reported physical activity showed a higher SOC score than those that did not perform any sort of physical activity. Physical engagement has been found to increase the cognitive function of older adults and to provide an opportunity for social interactions and civic life, as well as to develop a personal sense of meaning (Park et al. 2007; Wilson et al. 2002). It is therefore possible that this factor is associated in part with social support, sense of purpose and self-esteem, which were not controlled for in this research and could possibly promote the increase of SOC.

In this sample, the relationship between SWL and SOC was positive and significant after controlling for all the sociodemographic, health and lifestyle-related characteristics mentioned above. Although SWL had the weakest positive impact on SOC, it can also be hypothesised that SWL was associated with the accomplishment of relevant goals in life, as suggested in previous literature (Nimrod & Kleiber 2007; Ryff 1989). It seems appropriate to mention that the SWLS measures primarily the cognitive aspects of well-being and our results suggest that this cognitive-focused measuring instrument shows a significant relationship with SOC. The fact that SWL predicted SOC emphasises the importance of a positive cognitive appraisal. Additionally, SWL has been identified, along with physical well-being and health promotion, as being essential for successful ageing (Brown, Bowling & Flynn 2004). In this context, we hypothesised that SWL and cognitive-based interventions with older adults might enhance their SOC.

Considering the cross-national and cultural diversity of our participants, the highest scores were achieved by Angolan participants, whilst the English produced the lowest mean SOC scores. One possible explanation for these results could be that cultural, national and ethnic differences may influence the process of ageing (Barak 2009; Löckenhoff et al. 2009; Torres 2003). Therefore, as expected given the significant but not substantial culture-related differences amongst the four nationalities studied, our results indicated a diversity of SOC. Moreover, we hypothesised that a specifically African definition of being old, in part due to a recent past of war and poverty (World Health Organization 2003) might have led Angolan participants to a higher appreciation of their sense of purpose, social support and self-esteem, which could promote the increase of SOC.

Although a diverse sample of participants was recruited, the propensity for this study to be generalised is limited by our use of a convenience sampling method. As stated, the study was confined to European residents. The sample size (namely, 454 participants) was, however, deemed to be adequate for this type of statistical analysis given current practice in structural equation modelling, which is to apply a rule of thumb yardstick of ten subjects per manifest variable (Kline 2005; Maroco 2010). Further research may be improved by using larger sample sizes in order to increase the strength of the investigation (Howell 2004). Furthermore, although significant differences were found between groups, these were not substantial. Further research with larger samples may increase the reliability of these findings, as their clinical relevance has yet to be determined. These findings need to be interpreted for practical use in order to avoid overrating of differences, although the results did seem to show a statistical significance. Given the existence of various cultural and national influences in the European context, the inclusion of race and ethnicity as variables in future research could enhance the understanding of specific factors and the role that those play in predicting SOC in older adults.

Furthermore, the psycho-emotional factors behind SOC, such as meaningful relationships and interpersonal attachment, self-esteem and sense of purpose need to be studied more deeply in future research. Further longitudinal studies are needed in order to confirm the stability of the found predictors.

In spite of the limitations, we think that the findings of this study contribute to a better understanding of SOC in older adults. Firstly, the data came from a varied cross-national sample of the European older population. Secondly, the study examined a broad range of factors, including not only sociodemographic ones, but also health and lifestyle factors.

This study also provides a basis for further research, specifically, in designing and implementing effective intervention programmes for older adults, which include physical activity, prevention of disease and SWL, in order to contribute to a better SOC, as suggested by our outcomes.

Overall, the findings suggest that SOC seems to be affected positively by physical activity, the absence of recent disease and SWL.

Physical activity is the strongest positive predictor of SOC. Older adults that reported physical activity showed higher SOC scores as compared with those who did not perform physical activity. The absence of recent disease and SWL are also significant positive predictors of SOC. The structural model explored in this study accounts for 57.5% of the variability of SOC.

To the best of our knowledge, there are no previous studies exploring the simultaneous impact of sociodemographic, lifestyle- and health-related factors on SOC in older adults and, in particular, including the effects of the cognitive dimension of subjective well-being (SWL) on SOC in these older adults. This research also emphasises the importance of SWL on SOC and contributes with a structural model that integrates SWL and sociodemographic, lifestyle- and health-related factors. Our study therefore presents new data with regard to the specific impact of physical activity, absence of recent disease and SWL on SOC in the elderly.

Our findings also emphasise the fact that there are cross-national differences regarding SOC and lend further support to the idea that cultural and ethnical differences may influence this variable. In fact, the potential of older people for ageing well in different cultures is still relatively unexplored, as is the underdeveloped potential of the SOC concept in this population. Considering that ageing is a multi-dimensional concept, sociodemographic, cultural, national and ethnic differences may influence the process of ageing (Barak 2009; Löckenhoff et al. 2009; Torres 2003). With this is mind, this study’s outcomes could be useful for health care professionals when dealing with cross-national differences (e.g., physical activity, SWL promotion and disease prevention) amongst older populations. In brief, we assert that the results of this study are an original contribution for a better understanding of what actually predicts SOC in older adults, within the multi-dimensional and cross-national context of age and the ageing process, in combination with an approach focused on health and well-being in older populations.

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