Orgnal Paper. Advances n Rehabltaton 3, 6 13, 2010 DOI 10.2478/v10029-010-0002-7 Physcal actvty patterns of European 50+ populatons Mchał Myck German Insttute for Economc Research, Berln, Centre for Economc Analyss, Szczecn, Insttute for Fscal Studes, London Summary Introducton: Despte well-documented postve effects of physcal actvty on physcal and mental health, the levels of actvty n many countres reman very low. Actvty has been shown to be related to age, educaton and other ndvdual characterstcs, but t s unclear f dfferences n dstrbutons of these characterstcs across countres are enough to explan the observed cross-country dfferences. Am: The paper examnes the extent to whch dfferences n the level of physcal actvty among European 50+ populatons can be explaned by dfferences n observed ndvdual characterstcs, and to whch the dfferences between countres relate to unobserved factors and could thus be referred to as resultng from actvty habts. Materal and Methods: The analyss s based on the Survey of Health Ageng and Retrement n Europe (SHARE) for 13 countres of contnental Europe. The sample ncludes 12,652 men and 15,007 aged 50 years and older. Lnear probablty models are used to correct for dfferences n the dstrbuton of observable characterstcs. Results: From among the 13 analysed European populatons aged 50+, the level of physcal actvty s hghest n Swtzerland among men and n the Netherlands among women, wth the Polsh populaton turnng out to be the least actve. Only 38% of Polsh men and 29% of women declare vgorous physcal actvty at least once a week compared to 68% of Swss men and 67% of Dutch women. Cross-country dfferences become smaller once a number of ndvdual characterstcs are controlled for, but they cannot be explaned wthout referrng to country-specfc actvty habts. Concluson: There are sgnfcant dfferences n the level of physcal actvty among European 50+ populatons and ther large proporton cannot be explaned by dfferences n observed ndvdual characterstcs. Key words Physcal actvty 50+ populatons Ageng Health Background Ths artcle examnes the dfferences n the level of physcal actvty among ndvduals aged 50+ n Europe usng the data from the Survey of Health Ageng and Retrement n Europe (SHARE). The analyss focuses on tryng to dentfy the extent to whch the observed dfferences n the level of physcal actvty among European countres partcpatng n SHARE can be explaned by dfferences n characterstcs such as educaton, resdence and health, and to what extent these dfferences between countres and n partcular the observed low levels of physcal actvty n some countres relate to unobserved characterstcs and could thus be referred to as dfferences n actvty habts. The benefts of physcal actvty for wellbeng and health have been recognsed and documented for a long tme n epdemologcal lterature. For example Blar et al. [1] fnd that hgher levels of physcal ftness reduce allcause mortalty prmarly due to lower rsk cardovascular dseases (CVD) and cancer. Postve effects of physcal actvty on lowerng the rsk of cancer, CVD and overall mortalty have been found n numerous studes [2 5], whle Wensten et al. [6] fnd postve effects of physcal actvty on lowerng the rsk of type-2 dabetes, and Wessel et al. [7] conclude that physcal actvty acts as a potental medator of the effects of obesty on CVD. Physcal actvty also seems to have benefcal nfluence on cogntve mparment. For example Weuve et al. [8] Author s address Mchał Myck, DIW-Berln, Publc Economcs Department, MohrenStr 58, 10117 Berln e-mal: mmyck@dw.de
Physcal actvty: 50+ n Europe 7 fnd that n terms of cogntve abltes regular physcal actvty s equvalent to beng about 3 years younger. However, despte of all these documented benefcal consequences of physcal actvty, n many countres one can observe very hgh rates of non-actvty compared to other major behavoural rsks such as smokng, hgh cholesterol or alcohol abuse. As noted by Dshman [9] ths s despte the fact that physcal actvty seems to offer more opportuntes for pleasure than most other health-related behavours, and despte the relatvely undemandng levels of actvty whch can brng notceable dfferences to health. The analyss presented n ths paper tres to dentfy the key characterstcs whch determne the level of physcal actvty among ndvduals aged 50+ n several European countres, and to demonstrate the degree of heterogenety between the populatons. Internatonal comparsons of partcpaton n physcal actvty should shed further lght on ts role n determnng dfferences n health between populatons, and also sgnal whch countres should pay specal attenton to popularsng physcal actvty as a means to mprovements n overall health levels. The analyss s conducted usng the data from the SHARE survey - a multdscplnary longtudnal study whch collects data on ndvduals aged 50 and over. In 2006/07 the SHARE survey collected ts frst wave of data n Poland and the Czech Republc, whch together wth Ireland joned 12 other countres n whch the data has been collected snce 2004. In these twelve countres the 2006/07 round of data collecton consttuted the second wave of the panel (the 12 countres nclude 10 countres of the EU15, Swtzerland and Israel). 1 The SHARE data consttutes a unque nfrastructure for mcro-level analyss and covers such felds as health (physcal and mental), labour market actvty, fnancal stuaton, famly relatonshps, socal actvty, mutual assstance, health care and lfe style. It s a rch data set whch facltates analyss of varous aspects of ageng n an nternatonal context. The analyss presented n ths paper focuses on only a small subset of the data, and numerous studes show further examples of how t can assst n understandng the ndvdual and socal consequences of populaton ageng (for a lst of papers llustratng the content of the SHARE database see for example Börsch- Supan, et al. [10], and Börsch-Supan et al. [11]; for examples focusng on Poland see for example Myck et al. [12]. See also a lst of publcatons avalable on the SHARE webpage: www.share-project.org). 1 For more nformaton about SHARE ncludng nformaton concernng access to the data see: www.share-project.org. For more nformaton on the Polsh part of the survey see: www.cenea.org.pl/share. Materal and Methods The analyss s based on the release-101 data from the SHARE 2006/07 survey whch n some dmensons for countres whch partcpated n the frst wave of SHARE s complemented wth nformaton from the frst wave of the survey collected n 2004/05. Indvduals aged less than 50 and observatons wth mssng crucal nformaton used n the analyss are excluded from the analyss, and the paper focuses only on countres from contnental Europe. 2 As a result the analyss s conducted on data from 13 countres (the number n parenthess gve the country specfc total number of observatons): Austra (948), Belgum (2,635), the Czech Republc (2,607), Denmark (2,015), France (2,405), Germany (2,222), Greece (2,755), Italy (2,531), the Netherlands (2,234), Poland (2,323), Span (1,447), Sweden (2,280), and Swtzerland (1,257). The total sample amounts to 27,659 ndvduals. The average age of men n the sample s 64.7, and of women s 66.1. Sample statstcs splt by country and gender are presented n Table 1. One secton of the SHARE ntervew focuses on lfe style of the respondents, and asks specfcally two questons relatng to the ntensty of physcal actvty the ndvduals undertake, namely: how often do they engage n vgorous physcal actvty, such as sports, heavy housework, or a job that nvolves physcal labour, and how often do they engage n actvtes that requre a moderate level of energy such as gardenng, cleanng the car, or dong a walk. Answers to these two questons are the prmary focus of our analyss. Informaton presented n Table 2 shows a very hgh dfferentaton n health measures among the analysed 50+ populatons, and Poland has some of the worst health statstcs n ths age group. Only 7.3% of men and 5.9% of women n Poland rate ther health status as very good or excellent, compared for example wth 19.0% and 16.4% n the Czech Republc or wth 52.6% and 53.3% n Denmark. Ths self reported measure may not be a good objectve reflecton of the actual health status and may depend on varous cultural factors, but more objectve measures of health avalable n SHARE, lke for example the lack of reported symptoms of poor health, also show Poland to have far worse ndcators than other countres. Only 20.8% of men and 13.7% of women n the sample report no symptoms of poor health n Poland, compared 2 SHARE ntervews ndvduals aged 50+ and ther spouses regardless of ther age. Ths means that some respondents can be aged below 50.
8 M. Myck Table 1. The SHARE sample used for analyss number of observatons and health ndcators by country Country Health: v. good No reported symptoms of poor health blood pressure (obesty) Identfed wth hgh BMI > 30 No. observatons or excellent M W M W M W M W M W Austra 393 555 0.336 0.288 0.320 0.246 0.347 0.359 0.209 0.254 Belgum 1227 1408 0.303 0.278 0.309 0.211 0.309 0.359 0.199 0.181 Czech Republc 1136 1471 0.190 0.164 0.237 0.189 0.420 0.433 0.231 0.249 Denmark 975 1040 0.526 0.533 0.357 0.278 0.332 0.320 0.133 0.144 France 1040 1365 0.221 0.196 0.282 0.207 0.287 0.297 0.174 0.146 Germany 1044 1178 0.219 0.215 0.326 0.242 0.368 0.369 0.179 0.176 Greece 1283 1472 0.422 0.307 0.439 0.267 0.325 0.375 0.178 0.225 Italy 1154 1377 0.232 0.189 0.322 0.214 0.394 0.405 0.168 0.188 Netherlands 1024 1210 0.274 0.275 0.406 0.294 0.261 0.288 0.128 0.148 Poland 1034 1289 0.073 0.059 0.208 0.137 0.383 0.490 0.215 0.298 Span 687 760 0.170 0.132 0.427 0.247 0.320 0.354 0.227 0.244 Sweden 1085 1195 0.455 0.383 0.347 0.230 0.321 0.330 0.141 0.149 Swtzerland 570 687 0.466 0.439 0.429 0.311 0.294 0.250 0.129 0.129 Total 12652 15007 0.295 0.256 0.335 0.231 0.337 0.362 0.177 0.195 Source: SHARE data 2004/5 & 2006/7, release 101. Notes: All statstcs corrected for dfferences n age dstrbutons. BMI body mass ndex. M men, W women. Health: v.good or excellent respondent declares health to be very good or excellent on a fve-level scale; to 23.7% and 18.9% respectvely n the Czech Republc and 42.9% and 31.1% n Swtzerland. When one looks at an example of a very specfc common health problem hgh blood pressure the Polsh populaton s not so dfferent from the Czech Republc, though the proporton of women reportng hgh blood pressure n Poland s stll hghest among the 13 analysed countres. Polsh women aged 50+ also have the worst obesty statstcs wth 29.8% beng obese, n comparson to 24.9% n the Czech Republc, 14.4% n Denmark and 12.9% n Swtzerland. A large proporton of Polsh men aged 50+ (21.5%) are obese whch s smlar to Span or Czech Republc, but much hgher compared to Denmark (13.3%) and Swtzerland (12.9%). These reported cross-country dfferences n the measures of health rase nterestng questons concernng the causes of such hgh varaton, whch may lay n the qualty of avalable health care or fnancal resources as much as n lfe style of ndvduals ncludng det, hazardous habts lke smokng, and the level of physcal actvty. In the last case, whle one would expect to see better health among the physcally actve ndvduals, examnng the causal relatonshp between actvty and health s not straghtforward. On the one hand, f t s ndeed the case that actvty s benefcal for health, more actve people would be more lkely to be healthy. On the other, however, f good health s a prerequste for physcal actvty, the observed postve relatonshp may overstate the mpled causal relatonshp and at least partly reflect the necessty to be healthy to be physcally actve. The avalable data at the moment do not allow us to dsentangle the effect of physcal actvty on health. What s attempted n ths paper s an examnaton of the extent to whch the observed dfferences n the level of physcal actvty can be explaned by other observable characterstcs. The analyss examnes the role of habts n determnng the observed levels of physcal actvty among the 50+. In the analyss the condtonal probablty of observng a declaraton of physcal actvty at least once a week, y, s modelled usng the lnear probablty model. Ths approach allows us to easly correct for dfferences n the dstrbuton of explanatory varables to dentfy the remanng unexplaned country dfferences n the dependent varable. The ndcator varable for observed physcal actvty s regressed on a set of ndvdual characterstcs X and a vector of country specfc dummy varables, Z : y = β' X + γ ' Z + ε where ε s the normally dstrbuted resdual. The country-specfc dummy varables control for any dfferentaton n the level of physcal actvty whch cannot be explaned by cross-country dfferences n characterstcs X. By mposng the overall sample average values of X, X, we can compute the dfferences n the level of the dependent varables between countres controllng for the set of characterstcs X, as: (1)
Physcal actvty: 50+ n Europe 9 Table 2. Determnants (and correlates) of vgorous physcal actvty among the 50+ Dependent varable: Men Women Vgorous actvty Specfcaton 2 Specfcaton 3 Specfcaton 2 Specfcaton 3 ME SE ME SE ME SE ME SE Age 0.008 (0.007) 0.017* (0.007) 0.015* (0.006) 0.024* (0.006) Age2/100-0.016* (0.005) -0.021* (0.005) -0.021* (0.004) -0.027* (0.004) Educaton 8+ 0.027* (0.012) 0.020 (0.013) 0.027* (0.011) 0.015 (0.011) Educaton 12+ -0.016 (0.012) -0.036* (0.012) 0.039* (0.011) 0.013 (0.012) Town sze - suburbs bg cty 0.051* (0.017) 0.044* (0.017) 0.034* (0.016) 0.028 (0.016) - large town 0.024 (0.016) 0.028* (0.016) 0.023 (0.015) 0.024 (0.015) - small town 0.069* (0.016) 0.066 (0.016) 0.041* (0.015) 0.042* (0.015) - vllage 0.127* (0.015) 0.130* (0.015) 0.053* (0.014) 0.058* (0.014) Marred 0.042* (0.014) 0.028* (0.014) 0.025* (0.010) 0.018 (0.010) 1 chld 0.017 (0.019) 0.029 (0.019) 0.042* (0.018) 0.048* (0.018) 2 chldren 0.039* (0.017) 0.039* (0.018) 0.050* (0.016) 0.053* (0.016) 3 chldren 0.027 (0.019) 0.031 (0.019) 0.063* (0.017) 0.068* (0.018) 4+chldren -0.008 (0.021) 0.001 (0.021) 0.068* (0.019) 0.079* (0.020) Day gven 0.069* (0.015) 0.058* (0.015) 0.077* (0.014) 0.068* (0.015) Numercal good 0.093* (0.014) 0.077* (0.014) 0.065* (0.011) 0.048* (0.011) Easy ends meet 0.038* (0.011) 0.003 (0.011) 0.023* (0.010) -0.010 (0.010) Smoked ever -0.014 (0.011) 0.003 (0.012) Smokes now -0.050* (0.013) -0.044* (0.014) Drnks 1/week+ 0.094* (0.010) 0.073* (0.010) Health problems: - cancer -0.111* (0.025) -0.077* (0.021) - ulcer -0.005 (0.021) 0.001 (0.022) - hgh b.pressure -0.039* (0.010) -0.038* (0.010) - hgh cholesterol -0.002 (0.012) -0.006 (0.011) - dabetes -0.067* (0.015) -0.043* (0.015) - heart attack -0.138* (0.014) -0.128* (0.015) - arthrts -0.036* (0.014) -0.064* (0.010) Self ass. health - v.good or excell. 0.137* (0.011) 0.130* (0.011) Obesty -0.054* (0.013) -0.068* (0.011) Country dummes ncluded ncluded ncluded ncluded No. observatons 12652 15007 Pseudo r 2 0.0837 0.1180 0.1079 0.1361 Source: Author s estmatons usng SHARE data 2004/5 & 2006/7 for 13 countres (see Table 1 for countres ncluded and sample statstcs). Notes: Eetmates usng the probt model. * - sgnfcant at 5% (p<0,05); ME margnal effects; SE standard error. Reference categores for dummy varables: Town sze: bg cty ; Chldren: no chldren; Varable labels: Dependent varable: vgorous actvty respondent declares undertakng vgorous actvty at least once a week; Day gven respondent correctly gves the day of the month of ntervew; Numercal good the respondent correctly solves a smple arthmetc exercse; Easy ends meet the respondent declares that t s easy or very easy for the household to make ends meet ; Educaton X+ respondent has at lease X years of full tme educaton; Drnks 1/week+ respondent declares havng drunk alcohol at least once a week over the past three months. Self ass. health respondent declares very good or excellent health status on a fve-level scale.
10 M. Myck j E( y X, Z = j) = ( ˆ β ' X + ˆ γ ' Z ) where E( y j ) s the average expected probablty of observng ndvduals nvolved n physcal actvty n country j, nj s the number of observatons for country j, and ˆβ and ˆ γ are the estmated coeffcents of the lnear probablty model. If all varaton n the model could be explaned by dfferences n X, then the values of ˆ γ would all be zero. Therefore one can expect that the larger the set of X the lower the unexplaned dfferences between the countres would be. The secton below presents results for three specfcatons: Specfcaton 1 where X conssts only of age controls (age and age 2 ); Specfcaton 2 where X conssts of age controls, controls for educaton, famly structure, for town sze, ndcators of mental ablty and self-assessment of fnancal stuaton; Specfcaton 3 where on top of the controls used n Specfcaton 2 several lfe-style controls (smokng and drnkng habts) as well as a number of controls for health status ncludng specfc dentfed health condtons, a health self assessment and a dummy for obesty are also added. The man reason to dfferentate between Specfcaton 2 and 3 s the dfference n the nature of the relatonshp between physcal actvty and the addtonal health and lfe style related varables n Specfcaton 3. Whle one can relatvely safely argue that varables ncluded n Specfcaton 2 are exogenous to physcal actvty (n the sense that physcal actvty s unlkely to determne them), t s very lkely that the addtonal varables ncluded n Specfcaton 3 may be endogenous. Ths s n fact what nj nj (2) has been documented n studes on the effect of physcal actvty on health and mortalty quoted above. Thus the results ought to be treated wth cauton frst of all they may not be nterpreted n a causal fashon, and secondly, the degree to whch between-country dfferentaton s reduced n Specfcaton 3 wll be exaggerated because of ths endogenety. Nevertheless, as the results below demonstrate even when we nclude these varables there reman sgnfcant dfferences n the level of physcal actvty between countres. Results Fgures 1 and 2 present the dfferences n vgorous actvty by country for all three specfcatons separately for men and women. Table 2 shows the margnal effects related to specfc control varables used n Specfcaton 2 and 3 estmated usng the probt model. Cross-country dfferences concernng moderate actvty are presented n Fgures 3 and 4 respectvely for men and women. These are also presented for the three Specfcatons. Fgures 1 and 2 show how bg the dfferences are between Poland and some of the EU15 countres and Swtzerland. Correctng only for dfferences n the age structure of the 50+ populatons as few as 37.9% of Polsh men and 29.1% of Polsh women declare vgorous physcal actvty ( at least once a week ). Ths compares wth 68.4% and 59.6% of Swss men and women, and 63.3% and 65.5% of men and women n the Netherlands. Among men the closest country n terms of physcal actvty to Poland s Italy (41.1%) whle among women the Czech Republc (32.8%) and Italy (33.2%). Dfferences n vgorous actvty between Poland and populatons n these countres are not statstcally sgnfcant. 70% 60% 50% 40% 30% 20% 10% 0% CH NL SE DE DK GR AT ES BE CZ FR IT PL Specfcaton 1 Specfcaton 2 Specfcaton 3 Fg. 1. Country dfferentaton of vgorous actvty for specfcatons 1-3, men Notes: Country labels: AT: Austra, BE: Belgum, CH: Swtzerland, CZ: Czech Republc, ES: Span, DE: Germany, DK: Denmark, FR: France, GR: Greece, IT: Italy, NL: Netherlands, PL: Poland, SE: Sweden. Black labels show 95% confdence ntervals.
Physcal actvty: 50+ n Europe 11 70% 60% 50% 40% 30% 20% 10% 0% NL CH GR DE AT SE DK ES BE FR IT CZ PL Specfcaton 1 Specfcaton 2 Specfcaton 3 Fg. 2. Country dfferentaton of vgorous actvty for specfcatons 1-3, women Notes: Country labels: AT: Austra, BE: Belgum, CH: Swtzerland, CZ: Czech Republc, ES: Span, DE: Germany, DK: Denmark, FR: France, GR: Greece, IT: Italy, NL: Netherlands, PL: Poland, SE: Sweden. Black labels show 95% confdence ntervals. The dfferences are generally slghtly smaller when the exogenous characterstcs n Specfcaton 2 are controlled for, but the Polsh populaton stll turns out to be the least actve, and the overall rankng of countres s only slghtly altered. If the cross-country dfferences n physcal actvty are nterpreted as resultng from dfferences n actvty habts then for men the dfference between Poland and the Netherlands s 23.2 percentage ponts (pp), between Poland and Swtzerland s 25.4pp, between Poland and Germany s 17.1pp, and between Poland and the Czech Republc 6.3pp. Among women these dfferences are respectvely: 33.6pp, 26.7pp, 19.7pp and 2.0pp. What mproves the relatve poston of Poland wth respect to physcal actvty s the ncluson of the health and lfe-style related varables n Specfcaton 3. As noted earler, though, these results ought to be treated wth cauton, snce the explanatory varables are very lkely to be endogenous, especally n the case of obesty, hgh blood pressure or self assessment of health status. When one looks at the dfferences between countres n the level of physcal actvty corrected for these measures, results for men n Poland are very close to those n France, Belgum and Austra and are 4.8pp hgher than n Italy. For women they are n lne wth Italy and the Czech Republc. Ths would suggest, under the assumpton that physcal actvty has a smlar effect on the addtonal varables ncluded n Specfcaton 3 across countres that actvty habts of the Polsh 50+ populaton are not so much dfferent compared to the 50+ ndvduals n Italy, France of the Czech Republc. Nevertheless, even under ths rather strong assumpton, the levels of physcal actvty are sgnfcantly lower compared to such countres as Swtzerland, the Netherlands, Germany or Sweden. Cross-country dfferences n at least moderate actvty (.e. vgorous or moderate) are generally very smlar, though naturally the proportons of ndvduals nvolved n these s much hgher, are presented n Fgures 3 (men) and 4 (women). If moderate actvty s consdered, however, the level of physcal actvty s lowest n Poland regardless of the specfcaton. Lookng at Table 2 t s worth notng some of the man determnants or, especally n the case of the addtonal varables n Specfcaton 3 correlates, of vgorous physcal actvty. Results for Specfcaton 2 suggest that, as one would expect, actvty falls (at a dmnshng rate) wth age and s hgher among those wth post-prmary educaton. It s also greater among ndvduals lvng n the country sde or n small towns or suburbs. What s remarkable s that mental ablty reflected n numercal sklls and a smple mental awareness test of beng able to name the current day of the month (at the tme of ntervew) strongly correlate wth physcal actvty, even after condtonng for educaton. Ths may suggest that ether people who are mentally ft are more aware of the need to exercse, or as n the case of other health related varables that ths just reflects some of the feedback effect of physcal actvty on mental health. The frst nterpretaton gets some more justfcaton when one looks at the estmates of these coeffcents n Specfcaton 3, whch are very close to those of Specfcaton 2. Interestngly people s assessment of ther fnancal stuaton s also postvely related to the level of physcal actvty, but as we can see from Specfcaton 3 the effect dsappears once health and other lfe style varables are controlled for.
12 M. Myck 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% SE CH NL DE DK BE ES GR FR AT IT CZ PL Specfcaton 1 Specfcaton 2 Specfcaton 3 Fg. 3. Country dfferentaton of vgorous and/or moderate actvty for Specfcatons 1-3, men Notes: Country labels: AT: Austra, BE: Belgum, CH: Swtzerland, CZ: Czech Republc, ES: Span, DE: Germany, DK: Denmark, FR: France, GR: Greece, IT: Italy, NL: Netherlands, PL: Poland, SE: Sweden. Black labels show 95% confdence ntervals. In Specfcaton 3 we can see that current habt of smokng strongly negatvely correlates wth physcal actvty and the habt of alcohol drnkng correlates postvely. The latter may reflect some socal aspects of physcal actvty. As one would expect obese ndvduals are less lkely to engage n vgorous physcal actvty, and the level of actvty s also lower among those who have had a heart attack, who have been dentfed wth dabetes, who have hgh blood pressure and gve a low selfassessment of ther health status. In these cases, however, there s a very hgh lkelhood that the results reflect a correlaton and the estmated coeffcents strongly overestmate the causal effect of those condtons on physcal actvty. In some cases, however, the causal nterpretaton s probably more justfed. Ths would be so n the case of cancer or arthrts who are very lkely to lead to reductons of physcal actvty and whch n themselves may not be very strongly affected by physcal actvty habts from the past. 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% CH SE DK NL DE GR BE FR ES AT CZ IT PL Specfcaton 1 Specfcaton 2 Specfcaton 3 Fg. 4. Country dfferentaton of vgorous and/or moderate actvty for Specfcatons 1-3, women Notes: Country labels: AT: Austra, BE: Belgum, CH: Swtzerland, CZ: Czech Republc, ES: Span, DE: Germany, DK: Denmark, FR: France, GR: Greece, IT: Italy, NL: Netherlands, PL: Poland, SE: Sweden. Black labels show 95% confdence ntervals.
Physcal actvty: 50+ n Europe 13 Conclusons The benefts of physcal actvty for health and wellbeng have been very well documented n the lterature [1, 2, 6, 8]. Yet despte these well-know benefcal consequences the rates of non-actvty reman hgh and there are sgnfcant dfferences n the degree of physcal actvty between countres. Usng data on 50+ populatons from 13 European countres the analyss demonstrated the extent to whch crosscountry dfferences n vgorous and moderate physcal actvty can be related to a number of characterstcs and the degree to whch they may reflect habts wth regard to physcal actvty. When corrected for age and for a number of characterstcs the Polsh populatons of both men and women are the least lkely to engage n physcal actvty from among the analysed countres. Only about 29% of Polsh women and 38% of Polsh men engage n vgorous physcal actvty at least once a week compared to 68% of Swss men and 66% of Dutch women the countres of hghest degree of actvty among the respectve gender groups. When corrected for a number of exogenous characterstcs populatons of countres such as the Czech Republc or Italy and France are not far off the results for Poland, and suggest smlar atttudes to physcal exercse n these countres. The closeness of results for Poland and the Czech Republc s especally nterestng and may relate to the common hstory of the countres whch may have affected people s atttudes. The cross-country dfferences are even closer once varables whch are lkely to be endogenous to the level of physcal actvty, such as other lfe style varables or health ndcators are controlled for. These naturally strongly correlate wth physcal actvty but are lkely to have been affected by the level of actvty n the past. Thus the degree of the resultng reducton n cross country dfferences n the level of physcal actvty when controllng for such varables s most lkely overstated. References 1. Blar SN, Kohl HWIII, Paffenbarger RS Jr., Clark DG, Cooper KH, Gbbons LW. Physcal Ftness and All-Cause Mortalty. A Prospectve Study of Healthy Men and Women. JAMA 1989; 262: 2395-2401. 2. Lttman AJ, Vogt LF, Beresford SAA, Wess NS. Recreatonal Physcal Actvty and Endometral Cancer Rsk, AmJEpd 2001; 154: 924-933. 3. Gregg EW, Cauley JA, Stone K, Thompson TJ, Bauer DC, Cummngs SR, Ensrud KE. Relatonshp of Changes n Physcal Actvty and Mortalty Among Older Women. JAMA 2003; 289: 2379-2386. 4. Mchaud DS, Govannucc E, Wllett WC, Coldtz GA, Stampfer MJ, Fuchs CS. Physcal Actvty, Obesty, Heght, and the Rsk of Pancreatc Cancer. JAMA 2001; 286: 921-929. 5. Sesso HD, Paffenbarger RS, Ha T, Lee IM. Physcal Actvty and Cardovascular Dsease Rsk n Mddle-aged and Older Women, AmJEpd 1999; 150: 408-416. 6. Wensten AR, Sesso HD, Lee IM, Cook NR, Manson JE, Burng JE, Gazano JM. Relatonshp of Physcal Actvty vs Body Mass Index Wth Type 2 Dabetes n Women. JAMA 2004; 292: 1188-1194. 7. Wessel TR, Arant CB, Olson MB, Johnson BD, Res SE, Sharaf BL, Shaw LJ, Handberg, E, Sopko G, Kelsey SF, Pepne CJ, Merz CNB. Relatonshp of Physcal Ftness vs Body Mass Index Wth Coronary Artery Dsease and Cardovascular Events n Women. JAMA 2004; 292: 1179-1187. 8. Weuve J, Kang JH, Manson JE, Breteler MMB, Ware JH, Grodsten F. Physcal Actvty, Includng Walkng, and Cogntve Functon n Older Women. JAMA 2004; 292: 1454-1461. 9. Dshman RK. Multdscplnary Perspectves on Health- Related Qualty of Lfe. QLR 2003; 12: 43-49. 10. Börsch-Supan A, Brugavn A, Jürges H, Mackenbach Johan, Segrst J, Weber G, edtors. Health, Ageng and Retrement n Europe. Frst Results from the Survey of Health, Ageng and Retrement n Europe. Mannhem: Mannhem Research Insttute for the Economcs of Ageng (MEA); 2005. 11. Börsch-Supan A, Brugavn A, Jürges H, Kapteyn A, Mackenbach J, Segrst J, Weber G, edtors. Health, Ageng and Retrement n Europe (2004-2007). Startng the Longtudnal Dmenson. Mannhem: Mannhem Research Insttute for the Economcs of Ageng (MEA); 2008. 12. Myck M, Czapńsk J, Dorabalsk W, Gls-Januszewska A, Kalbarczyk M, Kula G, Ncńska A, Topór-Mądry R, Wśnewsk M. Lfe and work of the 50+ generaton n Poland n comparson wth other European countres. CenEA Research Notes 2009 [RN0209]. Avalable from: URL: http://www.cenea.org.pl Acknowledgements The frst two waves of the "SHARE: 50+ n Europe" survey has been fnanced prmarly by the European Commsson, DG Research, under the 5 th and 6 th Framework Programme (projects: QLK6-CT-2001-00360; RII-CT- 2006-062193; CIT5-CT-2005-028857), by the US Natonal Insttute on Agng (grants no.: U01 AG09740-13S2; P01 AG005842; P01 AG08291; P30 AG12815; Y1-AG-4553-01; OGHA 04-064; R21 AG025169), and other natonal nsttutons. Early analyss of Polsh SHARE data has beneftted from support by the Polsh Mnstry of Scence and Hgher Educaton through Specal Research Programmes (nr 347/6.PRUE/2007/7). Ths support s gratefully acknowledged. I would also lke to thank an anonymous referee and the edtors for many useful suggestons.