Background
Demographic change is a challenging development for the social systems of all member states in the European Union (EU) [
1,
2]. The feared impact of demographic change could be mitigated by healthy ageing, as older adults in good health remain longer at work or can play an active role in society through volunteer activities [
3]. Physical activity (PA) is essential for the skeletal, muscular- and digestive systems and also for circulation [
4]. In this context, PA plays a major role as it can increase life expectancy, daily living skills, overall well-being and quality of life [
5‐
8]. An estimated amount of three million premature deaths can be attributed to lack of PA, which could have been avoided through prevention and health promotion [
5,
6,
9,
10].
In the EU, the main causes of death are diseases of the cardiovascular system for which lack of PA is one of the major risk factors [
5,
6,
9,
11,
12]. Thus, lack of PA is related to one of the major cost factors in the EU health systems [
4,
6]. Sufficiently active people have previously shown to carry a lower risk of poor health or development of chronic diseases in old age [
5,
13]. Even in older adults, regular PA can still improve mental and physical health and positively affect the general ageing process [
4,
5].
The WHO recommends at least 2.5 h/week of moderate or 75 min/week of vigorous PA [
13]. In Europe, 35% of adults are considered as physically inactive and this proportion increases with age to 45% of the 60 + −year-olds [
4]. Prevalence of PA is different in the European countries, people of southern Europe are less active compared to other areas [
14]. In average, women are less active than men [
15].
Particularly with regard to increasing life expectancy in the EU, PA opportunities in everyday life of older adults require special attention in terms of promoting PA. The transition to retirement is a promising starting point for interventions promoting an active lifestyle, because people tend to establish new routines and give up previous ones. For example occupational PA opportunities, such as PA at work or active transport to workplace, are no longer relevant. Van Dyck et al. showed that this opportunity not only lasts during the actual transition to retirement, but also during the first years of retirement [
16]. In order to pursue a holistic approach to health promotion, variables of all levels should be included in accordance to Bronfenbrenners ecological systems theory [
17,
18].
Based on the three functional domains proposed by Livneh [
19] and on the classification Bauman et al. (2012) used, determinants of PA can be categorised into intrapersonal, interpersonal and extrapersonal factors. Intrapersonal factors comprise factors related to a person’s mind or self, such as health and psychological well-being. Intrapersonal factors that are negatively associated with PA are age and female gender [
20‐
23], poor health status [
20,
22,
24,
25], perceived frailty [
22,
23,
26], low socio-economic status [
20,
22], low parental socio-economic position [
27,
28] and high Body Mass Index (BMI) [
20,
22,
23]. Positively associated are sufficient PA during the life course [
20,
22,
23,
26], as well as self-efficacy and the belief in the benefits of PA [
20,
22‐
24,
26].
Interpersonal factors refer to family and marital life as well as peer and social relations. It has been shown that social support of family members, friends, sports partners and trainers are important positive factors for PA [
20,
22,
26,
29‐
32]. Additionally, social contact and a social network in neighbourhood enhance PA in older adults [
22,
33,
34]. McNeil et al. stated that social networks can influence PA positively by providing social support and establishing social norms that enable health-promoting behaviours [
35].
Extrapersonal factors are community-based and therefore beyond the personal or individual dimension, such as policies, physical and social environments. In this regard, economic conditions and societal norms are important determinants for PA in adults [
20,
22]. Likewise, built environment and walkability of a neighbourhood can influence PA in older adults negatively and also positively [
31,
36‐
39]. Moreover, a familiar neighbourhood [
40], security in the neighbourhood in terms of traffic and crime as well as access to a PA-promoting infrastructure affect PA positively [
31,
39,
40]. In this study, no extra-personal factors are included because the SHARE dataset only collected the resident of the participants and no extra-personal factors at community level.
PA-influencing factors vary between age groups. Therefore, transferability of results from other age groups is limited. There is a lack of studies explicitly dealing with factors influencing PA in older adults in Europe. This especially holds for high-quality longitudinal studies [
41,
42] and for studies using objective PA measurements [
20]. In this paper, we re-analyse the data of the Survey of Health, Ageing and Retirement in Europe (SHARE). SHARE is a longitudinal study that includes several countries using a common standard and thus allows inter-country comparisons. Although SHARE does not use objective PA measurement, but self-reported PA, the broad range of factors, the high degree of standardisation and the longitudinal nature of the data makes it a valuable resource for research.
The aims of this study are a) to determine the prevalence IPA in 65 to 75-year-olds in Europe and to identify factors associated with IPA in this age group and b) to identify longitudinal risk factors for IPA in prior active persons using the data of the Survey of Health, Ageing and Retirement in Europe (SHARE).
Methods
Study design and population
This study is conducted using data of the interdisciplinary panel Survey of Health, Ageing and Retirement in Europe (SHARE), which is performed in 19 countries of the European Union and Israel. The aim of the SHARE-project is to provide an overall picture of ageing in Europe and it gathered data on health, socio-economic status and social as well as family networks [
43]. In SHARE, non-institutionalised people aged 50+ underwent a short physical examination and were interviewed with computer assisted personal interviews (CAPI). Wave one took place in 2004/2005, wave two in 2006/2007, wave three in 2008/2009 and wave four in 2010/2011. SHARE has data of more than 60,000 individuals, the response rate in wave one was around 62%, in waves two, three and four 73%, 77% und 56% [
43]. The ten countries participating in all first four waves of SHARE were Belgium, Denmark, Germany, the Netherlands, France, Austria, Italy, Switzerland, Sweden and Spain. For further methodological details of SHARE see Börsch-Supan et al. (2013) [
43]. This study is following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement [
44]. An additional file shows this in more detail [see Additional file
1]. Inclusion criteria for this study were participation in all four waves of SHARE and belonging to the age group of 65-to-75–year-olds at the time of wave four. This resulted in a sample size of
n = 3846 (male
n = 1761, female
n = 2085).
Outcome and country of residence
Physical activity was assessed based on the following two questions: ‘How often do you engage in vigorous physical activity, such as sports, heavy housework, or a job that involves physical labour?’ and ‘How often do you engage in activities that require a low or moderate level of energy such as gardening, cleaning the car or doing a walk?’. Given possible answers were ‘More than once a week’, ‘once a week’, ‘one to three times a month’ and ‘hardly ever’ or ‘never’. Participants, who stated to engage in vigorous physical activity once a week or less were defined as
insufficient physical activity (IPA) (wave 4:
n = 2582; 67.2%). Participants engaging in vigorous physical activity more than once a week are categorized as sufficient PA and serve as control group. The WHO used IPA as measurement and defined it as less than 150 min of moderate physical activity or less than 75 min of vigorous physical activity per week [
45]. The variable
country is defined as the country of residence of the survey participants.
Covariables – Intrapersonal factors
Age was calculated from birth month and year of the participants and time of the interview in wave four. The exact age in months was divided by 12 to generate age in years.
Level of education was classified by the International Standard Classification of Education (ISCED) [
46]. For
parental education, the number of books present in the household that the participants lived in at the age of ten was used [
47].The variable was dichotomised. Zero to eleven books were classified as ‘low parental education’ and more than eleven books as ‘higher parental education’. The
financial situation was assessed with the question whether a household has trouble or not to make ends meet with the available monthly income. Four answer categories were used: ‘with great difficulty’, ‘with some difficulty’, ‘fairly easily’ and ‘easily’. The variable was dichotomised. All participants answering ‘with great difficulty’ and ‘with some difficulty’ were graded as ‘without difficulty’ and ‘fairly easily’ and ‘easily’ as without difficulties. The
number of chronic diseases was based on a multiple answer question. The numeric variable was truncated at a number of three chronic diseases.
Depression was examined with the EURO-D symptom scale, an index consisting of twelve items: depressed mood, pessimism, suicidality, guilt, sleep, interest, irritability, appetite, fatigue, concentration, enjoyment and tearfulness. The scale ranges from zero ‘not depressed’ to twelve ‘very depressed’. The variable was dichotomised according to Dewey and Prince into ‘no depression’ (0–3) and ‘depression’ (4–12) [
48].
Hospitalization in the last twelve months shows whether participants were in a medical, surgical, psychiatric or any other specialized hospital overnight during the last twelve months before the interview. Two
grip strength measurements on each hand were recorded using a dynamometer (Smedley, S Dynamometer, TTM, Tokyo, 100 kg). The variable shows the maximum grip strength of all four measurements. To describe
limitations in activities of daily living (ADL) the activities of daily living index (ADLI) was used [
49]. The ADLI is the sum of the five tasks dressing, bathing or showering, eating, cutting up food, walking across a room and getting into or out of bed. The higher the index the more difficulties exist with these activities. The variable was dichotomised. All participants with the index value zero were graded as ‘without limitations’ and with the index value one to five as with limitations.
Body Mass Index (BMI) is based on self-reported values and is calculated as:
BMI = weight in kilogram (kg) / (height in meter (m))
2
.
Covariables – Interpersonal factors
To determine marital status the existing response categories ‘married and living together with spouse’, ‘married, living separated from spouse’ and ‘registered partnership’ were summarised in the category ‘married and registered partnership’. The dichotomous variable partner in household indicates whether a participant was living together with his partner in a household. To measure the size of family network, a score was calculated from the number of children alive, the number of parents alive and the number of siblings alive. The numeric variable number of children was truncated at a number of four children. For four or more children, four children were included into the score. A high score value indicates a large family network. From wave four of SHARE on, information on up to seven individuals with whom respondents discussed important things most often during the 12 months before the interview is available. The size of social network may include family members, friends, neighbours and others and was truncated at three network partners. The dichotomous variable perceived social support shows whether the respondent had received instrumental social support within the last 12 month. The perceived quality of social network was assessed on a scale ranging from ‘0’ (completely dissatisfied) to ‘10’ (completely satisfied), including respondents who reported to have no social network.
Statistical analyses
To identify cross-sectional associations of intra- and interpersonal factors with IPA in wave four, prevalence odds ratios (POR) and 95%-confidence intervals (95%-CI) were calculated using binary logistic regression models.
To analyse the longitudinal association over time, we calculated hazard rations (HR) with 95% confidence intervals (95%-CI) using Cox regression models in the group of sufficient PA in wave 1. IPA at wave 4 served as the outcome. To account for heterogeneity between the observed countries, we included country as random effect in our models. We omitted stratification by sex for intrapersonal factors, because in the cross-sectional analyses the effects were similar for men and women. For interpersonal factors this was not the case, therefore we stratified the analyses by sex. Model building was based on the Wald statistic. But previously we calculated all other inclusion methods (backward, forward and expected inclusion) with the result that the method did not affect the result of regression after adjustment.
All analyses were performed using the statistical analysis software IBM SPSS statistics for Windows, version 20.0 (IBM Corp. Released 2011. Armonk, NY).
Results
A high proportion of our study group completed an upper secondary education or higher (women: 45.5%; men: 58.4%, Table
1). Most participants were married (female: 68.5%; male: 84.4%). A considerably higher proportion of women than men was widowed (female: 18.2%; male: 5.2%) and lived in single households (female: 29.2%; male: 13.1%). The majority of the sample had at least one child (female: 92.1%; male: 90.9%).
Table 1
Description of the study sample
Age at wave 4: Mean (SD1) | 69.6 (3.15) | 69.7 (3.13) |
Country |
Sweden | 206 (11.7%) | 256 (12.3%) |
Denmark | 138 (7.8%) | 134 (6.4%) |
Netherlands | 193 (11.0%) | 216 (10.4%) |
Germany | 202 (11.5%) | 196 (9.4%) |
Belgium | 279 (15.8%) | 345 (16.5%) |
Austria | 95 (5.4%) | 122 (5.9%) |
Switzerland | 90 (5.1%) | 105 (5.0%) |
France | 158 (9.0%) | 230 (11.0%) |
Italy | 266 (15.1%) | 311 (14.9%) |
Spain | 134 (7.6%) | 170 (8.2%) |
Educational level |
Primary education | 442 (25.1%) | 676 (32.4%) |
Lower secondary education | 279 (15.8%) | 446 (21.4%) |
Upper secondary education | 517 (29.4%) | 510 (24.5%) |
Tertiary education | 511 (29.0%) | 439 (21.0%) |
Marital Status wave 4 |
Never married | 87 (4.9%) | 106 (5.1%) |
Married | 1486 (84.4%) | 2029 (68.5%) |
Divorced | 94 (5.3%) | 166 (8.0%) |
Widowed | 92 (5.2%) | 380 (18.2%) |
Size of household wave 4 |
1-person household | 231 (13.1%) | 609 (29.2%) |
2-person household | 1277 (72.5%) | 1292 (62.0%) |
More than 2-person household | 253 (14.4%) | 184 (8.8%) |
Lives together with partner in household wave 4 |
Yes | 1502 (85.3%) | 1387 (66.5%) |
No | 259 (14.7%) | 698 (33.5%) |
Number of children |
None | 144 (8.2%) | 152 (7.3%) |
1–2 children | 986 (55.9%) | 1130 (54.2%) |
3 and more children | 615 (35.0%) | 789 (37.9%) |
Within the 65–75 year-olds, 67.2% reported IPA with women being less active than men and an increasing trend by age group in both genders (Table
2). At baseline, prevalence of IPA in the different countries ranged from 42.1% (Germany) to 63.5% (Italy) in men and from 48.5% (Denmark) to 75.9% (Belgium) in women. The steepest increase in IPA within seven years were seen in Danish women (wave 1: 48.5%; wave 4: 66.2%) and in German men (wave 1: 42.1%; wave 4: 55.2%).
Table 2
Longitudinal development of prevalence rates (PR) and 95%-confidence interval (95%-CI) of insufficient physical activity (IPA)
Countries | | | | Countries | | | |
Sweden (n = 206) | 52.9% (46.1–59.7) | 53.7% (46.9–60.5) | 46.6% (39.8–53.4) |
Sweden (n = 256)
| 61.7% (55.7–67.7) | 58.8% (52.8–64.8) | 64.1% (58.2–70.0) |
Denmark (n = 138) | 47.1% (38.7–55.5) | 55.1% (46.8–63.4) | 59.1% (52.4–65.8) | Denmark (n = 134) | 48.5%** (40.0–57.0) | 64.1% (55.9–72.3) | 66.2% (58.2–74.2) |
Netherlands (n = 193) | 49.2% (42.1–56.3) | 48.4% (41.3–55.5) | 52.4% (45.3–59.5) | Netherlands (n = 216) | 55.6% (49.0–62.2) | 47.9% (41.2–54.6) | 59.5% (52.9–66.1) |
Germany (n = 202) | 42.1%** (35.3–48.9) | 55.4% (48.5–62.3) | 55.2%** (48.3–62.1) | Germany (n = 196) | 49.0%** (42.0–56.0) | 60.2% (53.3–67.1) | 55.4% (48.4–62.4) |
Belgium (n = 279) | 60.9% (55.2–66.6) | 59.5% (53.7–65.3) | 63.1% (57.4–68.8) | Belgium (n = 345) | 75.9% (71.4–80.4) | 76.7% (72.2–81.2) | 80.8% (76.6–85.0) |
Austria (n = 95) | 63.2% (53.5–72.9) | 61.1% (51.2–71.0) | 58.5%** (48.5–68.5) | Austria (n = 122) | 73.0% (65.1–80.9) | 72.7% (64.8–80.6) | 81.8%** (74.9–88.7) |
Switzerland (n = 90) | 42.2% (31.9–52.5) | 42.2% (31.9–52.5) | 53.3% (42.9–63.7) | Switzerland (n = 105) | 54.3% (44.7–63.9) | 52.4% (42.8–62.0) | 67.6% (58.6–76.6) |
France (n = 158) | 59.2% (51.5–66.9) | 66.2% (58.8–73.6) | 69.4% (62.2–76.6) | France (n = 230) | 77.8% (72.4–83.2) | 80.3% (75.1–85.5) | 80.0% (74.8–85.2) |
Italy (n = 266) | 63.5% (57.7–69.3) | 66.5% (60.8–72.2) | 73.2% (67.9–78.5) | Italy (n = 311) | 71.4% (66.4–76.4) | 74.3% (69.4–79.2) | 83.3% (79.1–87.5) |
Spain (n = 134) | 61.2% (52.9–69.5) | 61.7% (53.4–70.0) | 73.7% (66.2–81.2) | Spain (n = 170) | 68.0% (61.0–75.0) | 66.3% (59.2–73.4) | 82.1% (76.3–87.9) |
Total (n = 1761) | 54.9% (52.6–57.2) | 57.8% (55.5–60.1) | 60.9% (58.6–63.2) | Total (n = 2085) | 65.4% (63.4–67.4) | 66.9% (64.9–68.9) | 73.0% (71.1–74.9) |
All intrapersonal factors showed a significant cross-sectional association with IPA in both sexes. Strength of association was similar for men and women for almost all investigated factors. Protective factors for IPA were higher education (male: POR: 0.57: 95%-Ci: 0.46–0.70; female: POR: 0.51; 95%-CI: 0.41–0.64), education of the parents (male: POR: 0.57: 95%-Ci: 0.47–0.70; female: POR: 0.53; 95%-CI: 0.44–0.66) and grip strength in kg (male: POR: 0.95: 95%-Ci: 0.94–0.96; female: POR: 0.96; 95%-CI: 0.94–0.97). Factors increasing the risk in older adults for IPA are age (male: POR: 1.04: 95%-Ci: 1.01–1.07; female: POR: 1.05; 95%-CI: 1.02–1.09), a difficult financial situation of the household (male: POR: 1.60: 95%-Ci: 1.26–2.03; female: POR: 1.58; 95%-CI: 1.26–1.97), a higher BMI (male: POR: 1.05: 95%-Ci: 1.03–1.08; female: POR: 1.05; 95%-CI: 1.03–1.08), number of chronic diseases (male: POR: 1.34: 95%-Ci: 1.23–1.45; female: POR: 1.31; 95%-CI: 1.21–1.42), depression (male: POR: 1.24: 95%-Ci: 1.13–1.35; female: POR: 1.17; 95%-CI: 1.09–1.25) and limitations in the activities of daily living (male: POR: 2.88: 95%-Ci: 1.88–4.39; female: POR: 2.45; 95%-CI: 1.64–3.68). The greatest gender-related difference was seen for hospitalisation within the last 12 months, that was a risk factor for IPA in both sexes, but stronger in women (POR: 2.18; 95%-CI: 1.59–2.98) than in men (POR: 1.36; 95%-CI: 1.05–1.77).
Very few of the investigated
interpersonal factors had a statistically significant association with the prevalence of IPA (Table
3). A significant influence on both sexes was shown by the size of social network (POR: 0.88, 95%-CI: 0.81–0.95). All other interpersonal factors differed between sexes. In women but not in men, divorce was a protective factor for IPA (POR: 0.65; 95%-CI: 0.46–0.91). Single and widowed men had a higher risk of IPA (never married: POR: 1.92: 95%-Ci: 1.17–3.15; widowed: POR: 2.07; 95%-CI: 1.27–3.39). In men, a lower risk of IPA was seen for living together with a partner in household (POR: 0.59; 95%-CI: 0.44–0.79), the number of grandchildren (POR: 0.96; 95%-CI: 0.94–0.98), the size of family network without partner (POR: 0.94; 95%-CI: 0.90–0.99) and the perceived social support (POR: 1.44, 95%-CI: 1.01–2.07). None of these variables had a cross-sectional association with IPA in women.
Table 3
Cross-sectional association of intra- and interpersonal factors for insufficient physical activity (IPA) in 65–75-years-olds
Intrapersonal factors |
Age in years | 1.04** | 1.01–1.07 | 1.05*** | 1.02–1.09 |
Higher Education (yes/no) | 0.57*** | 0.46–0.70 | 0.51*** | 0.41–0.64 |
Books at the age of 10 years (yes/no) | 0.57*** | 0.47–0.70 | 0.53*** | 0.44–0.66 |
Difficult financial situation of household (yes/no) | 1.60*** | 1.26–2.03 | 1.58*** | 1.26–1.97 |
Number of chronic diseases | 1.34*** | 1.23–1.45 | 1.31*** | 1.21–1.42 |
Depression (yes/no) | 1.24*** | 1.13–1.35 | 1.17*** | 1.09–1.25 |
Hospitalization in the last 12 months (yes/no) | 1.36* | 1.05–1.77 | 2.18*** | 1.59–2.98 |
Grip strength in kg | 0.95*** | 0.94–0.96 | 0.96*** | 0.94–0.97 |
Limitations in the Activities of Daily Living (yes/no) | 2.88*** | 1.88–4.39 | 2.45*** | 1.64–3.68 |
Body Mass Index (BMI) in kg/m2 | 1.05*** | 1.03–1.08 | 1.05*** | 1.03–1.08 |
Interpersonal factors |
Marital Status |
Married | reference | | reference | |
Never married | 1.92** | 1.17–3.15 | 1.56 | 0.95–2.58 |
Divorced | 0.94 | 0.62–1.44 | 0.65** | 0.46–0.91 |
Widowed | 2.07** | 1.27–3.39 | 1.21 | 0.93–1.57 |
Household size | 1.06 | 0.93–1.22 | 1.03 | 0.90–1.18 |
Partner in household (yes/no) | 0.59*** | 0.44–0.79 | 0.93 | 0.76–1.14 |
Size of family network | 0.94** | 0.90–0.99 | 0.98 | 0.94–1.03 |
Number of grandchildren | 0.96** | 0.94–0.98 | 1.00 | 0.98–1.02 |
Size of social network1 | 0.88*** | 0.81–0.95 | 0.88** | 0.81–0.95 |
Perceived social support1 | 1.44* | 1.01–2.07 | 1.32 | 0.98–1.78 |
Perceived quality of social network1 | 0.97 | 0.89–1.05 | 0.98 | 0.90–1.06 |
Longitudinally, we found a protective effect on IPA for higher education (HR: 0.80; 95%-CI: 0.67–0.95) and grip strength (HR: 0.99; 95%-CI: 0.98–0.99) at baseline (Table
4). Whereas the number of chronic diseases (HR: 0.80; 95%-CI: 0.67–0.95), depression (HR: 1.31; 95%-CI: 1.10–1.56) and BMI (HR: 1.02; 95%-CI: 1.00–1.04) at baseline were statistically significant risk factors for IPA seven years later. In a fully adjusted model only grip strength (HR: 0.99; 95%-CI: 0.98–0.99) and BMI (HR: 1.03; 95%-CI: 1.01–1.05) remained statistically significant.
Table 4
Longitudinal intrapersonal factors of insufficient physical activity (IPA) at age 65–75 in prior active persons1
Intrapersonal factors |
Age in years | 1.01 | 0.99–1.03 | – | – |
Higher Education (yes/no) | 0.80** | 0.67–0.95 | – | – |
Books at the age of 10 years (yes/no) | 0.95 | 0.81–1.11 | – | – |
Difficult financial situation of household (yes/no) | 1.11 | 0.93–1.32 | – | – |
Number of chronic diseases | 1.09** | 1.03–1.16 | – | – |
Depression (yes/no) | 1.31** | 1.10–1.56 | – | – |
Hospitalization in the last 12 month (yes/no) | 1.12 | 0.88–1.43 | – | – |
Grip strength in kg | 0.99*** | 0.98–0.99 | 0.99*** | 0.98–0.99 |
Limitations in the Activities of Daily Living (yes/no) | 1.10 | 0.75–1.62 | – | – |
Body Mass Index (BMI) in kg/m2 | 1.02* | 1.00–1.04 | 1.03** | 1.01–1.05 |
For the interpersonal factors in the longitudinal analyses, it was found that the only factor showing an influence on IPA in previously active 65–75 year-olds was living together with the partner in one household at baseline (Table
5, HR: 0.74; 95%-CI: 0.56–0.97). This influence was only shown in men.
Table 5
Longitudinal interpersonal factors of insufficient physical activity (IPA) at age 65–75 in prior active persons1
Interpersonal factors |
Marital Status |
Married | reference | | reference | |
Never married | 0.69 | 0.43–1.11 | 1.00 | 0.85–1.19 |
Divorced | 0.82 | 0.42–1.60 | 1.04 | 0.78–1.38 |
Widowed | 0.88 | 0.47–1.67 | 0.93 | 0.70–1.23 |
Household size | 0.93 | 0.81–1.07 | 1.05 | 0.92–1.19 |
Partner in household (yes/no) | 0.74* | 0.56–0.97 | 1.03 | 0.83–1.27 |
Size of family network | 0.98 | 0.96–1.01 | 1.01 | 0.98–1.03 |
Number of grandchildren | 0.99 | 0.97–1.02 | 1.02 | 0.99–1.05 |