Patient Education and Counseling 53 (2004) 95–99

Assessment of participation in physical activities and relationshipto socioeconomic and health factors

The controversial value of self-perception

Yacov Fogelmana, Boaz Blochb, Ernesto Kahanc,∗a Department of Family Practice, Haemek Medical Center, Afula and Rapaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel

b Department of Psychiatry, Haemek Medical Center, Afula and Rapaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israelc Department of Family Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel

Received 20 September 2002; received in revised form 28 January 2003; accepted 17 March 2003

Abstract

Physician counseling on physical activities for sedentary people is usually based on anamneses. The aim of the present study was toinvestigate the accuracy of self-perception of participation in physical activities, and the correlation of physical activity with backgroundfactors. A random sample of 276 individuals aged 20–65 years completed a detailed questionnaire on type and intensity of physical activityand associated socioeconomic and health factors. Physical activities were divided into work, leisure-time, and sports and rated accordingto Baecke’s four-item index. In addition, subjects answered a yes/no item that resembled the general question regarding physical activityusually asked by physicians in a typical anamnesis. About half of the population was found to lead a sedentary life-style. The lower thelevel of education, the greater the physical activity at work. Males had a higher sports index than females. Interestingly, 1.3% of those witha high questionnaire score reported on the anamnesis question that they did not engage in regular physical activity, whereas 17.5% with alow questionnaire score answered “yes” to the last item. In conclusion, self-reports on physical activity may be inaccurate and to ensureproper counseling, primary care physicians must place greater weight on the patient history.© 2003 Elsevier Science Ireland Ltd. All rights reserved.

Keywords: Physical activities; Preventive medicine; Life-style; Prevalence; Primary care; Family medicine

1. Introduction

Although recent studies have provided strong evidence ofthe health benefits of regular physical activity, most of thewestern world continues to maintain a sedentary life-style[1–4]. Current efforts to promote greater public awarenessare focused on preventing weight gain and reducing obe-sity to lessen the risk of coronary heart disease, type 2 dia-betes mellitus, some types of cancer, and osteoporosis[5–7].Physical activity also makes a significant contribution to theoverall quality of life at any age and especially in olderadults[8]. To improve physician counseling efforts, betterunderstanding of the reasons for nonparticipation in phys-ical activities across populations, particularly among thosewho are already overweight or obese, is needed. Moreover,since counseling is generally based on patient anamneses, avalid evaluation of the patient’s self-perception is required.

∗ Corresponding author. Tel.:+972-9-767-1733; fax:+972-9-766-4644.E-mail address: ekahan@post.tau.ac.il (E. Kahan).

The aim of the present study was to investigate the correla-tion of individual self-perceptions of their physical activitieswith calculated indices of the intensity of physical exercise.We also sought to identify specific groups that lead a seden-tary life-style and to analyze associated socioeconomic andhealth factors.

2. Methods and subjects

2.1. Sample

The sample size was calculated to answer the question,How large a sample is needed to estimate the proportion ofpeople who lead a sedentary life-style? About 60% of peoplein the United States report little to no leisure-time physicalactivity [9]—a rate very close to the conservative statisticaloption of 0.5 (i.e.P = 0.5 as the greatest sample size). Onthis basis, we assumed that in our population, the rate wouldbe between 0.45 and 0.55, at a 90% confidence level and a10% deviation for relative precision of the sample (that is,

0738-3991/$ – see front matter © 2003 Elsevier Science Ireland Ltd. All rights reserved.doi:10.1016/S0738-3991(03)00119-8

96 Y. Fogelman et al. / Patient Education and Counseling 53 (2004) 95–99

from 0.45 to 0.55). This yields a sample size of 271 accord-ing to the formula,N = Z2/1 − α/2P(1 − P)/0.12P . Weincreased this number to 276 in order to maintain the min-imum sample size in case some responders did not answerall the questions.

A large random sample of telephone numbers was se-lected from the telephone book of Northern Israel (areacode 04), whose population is a representative of that ofthe rest of Israel. The first 276 men and women aged20–65 years who had good understanding of Hebrew orEnglish and who agreed to participate in the study con-stituted the study group. No other exclusion criteria weredefined during formation of the study group or at datacollection.

2.2. Questionnaire

The survey was done in collaboration with the Depart-ment of Family Practice, Haemek Medical Center, Afula,the Rapaport Faculty of Medicine, Technion-Israel Insti-tute of Technology, Haifa, and the Department of FamilyMedicine, Sackler School of Medicine, Tel Aviv Univer-sity, Tel Aviv. The participants completed a questionnairebased in part on the questionnaire of Baecke et al.[10]on duration, frequency, and intensity of physical activities.There were also items on body weight, education, income,smoking habits, and symptoms during the last 30 days.The Baecke questionnaire has been frequently employedas a general measure of occupational and leisure (sport-and exercise-related and non-sport- and exercise-related)physical activity [11–15]. Its strength is consistent formen and women. Advantages include ease of adminis-tration, high reliability, and accurate assessment of bothheavy- and light-intensity activities (such as walking andbicycling) [11–15]. Physical activities were categorizedby type as work, exercise-related, or sports-related, andthe intensity of each category was graded according toBaecke’s four-item objective index[10]. The first item dealtwith whether the subject participates in physical activi-ties (yes/no), and if yes, which one he/she performs mostoften (by number of hours per week, number of monthsper year) and second most often, if any. The second itemcompared the subject with others of the same age (muchmore/more/the same/less/much less physical activity), andthe third covered sweating during physical activity (veryoften/often/sometimes/seldom/never). The first three itemswere scored on a scale of 1–5, and the mean was definedas the overall physical activity intensity, as follows: 1= nophysical activity; 2= low; 3 = medium; 4 and 5= high.In addition, subjects answered a fourth (self-perception)yes/no item formulated by a group of three primary carephysicians to resemble the question usually asked by pri-mary care physicians in a typical anamnesis. It read asfollows: taking all your physical activities (sports, work andleisure) into consideration, can you say that you participatein regular (habitual) physical activity? Participants who de-

clared themselves to be physically inactive were asked toprovide one or more reasons why.

2.3. Statistical analysis

The data were analyzed withχ2 or Fisher’s exact tests.Comparisons of continuous data with a non-normal distri-bution were done with Student’st-test. A two-tailedP-valueof 0.05 was used to define statistical significance for differ-ences between groups and to calculate confidence intervals.All analyses were done with the SPSSWIN software, ver-sion 9.01b.

3. Results

3.1. Questionnaire

3.1.1. WeightMore than half the responders considered themselves of

normal weight; 6.9% rated themselves “too thin”, 27.3%“slightly overweight”, 6.5% “fat”, and 0.7% “very fat”.

3.1.2. EducationFifteen responders completed 0–8 years of education, 134

completed 9–12 years, and 124 more than 12 years.

3.1.3. IncomeOf the entire sample, 15.6% reported no steady income

due to unemployment or were reluctant to offer their income;67% reported a monthly income of up to 5000 NIS (at thetime of the study, 4 NIS equaled US$ 1.00), and 33% morethan 5000 NIS. Income was not significantly correlated withage or gender.

3.1.4. Smoking habitsThe majority of subjects (68.1%) did not currently smoke,

though 17.7% of this subgroup had smoked in the past.

3.1.5. SymptomsThe mean number of symptoms reported within the last

month was 2.7 (±2.9).

3.1.6. Baecke’s indexAccording to the index, 48.2% of the sampled population

of 276 individuals led a sedentary life-style. Of the remain-der, 23.2% had low physical activity, 19.6% medium, and8.0% high. Only 1.0% of the subjects participated in sportsto a very high degree (score of 5).

3.1.7. Anamnesis item/barriersOne hundred thirty-two participants regarded themselves

as physically inactive. Reasons given were as follows: toolazy/not motivated/could not get started, 45%; too busy/hadother commitments, 42%; injured or disabled, 11%, and toofat, 2%. Only 4% considered physical activity to be of lowpriority.

Y. Fogelman et al. / Patient Education and Counseling 53 (2004) 95–99 97

Table 1Characteristics of population by gender

Variable Gender P-value

Male Female

Age (years) 32.42± 11.87 33.07± 11.45 0.641a

Education (years) 13.74± 2.70 13.67± 2.76 0.834a

BMI (kg/m2) 24.46± 4.33 23.61± 3.81 0.000a

Work index 2.70± 0.82 2.73± 0.59 NSa

Leisure index 2.55± 0.72 2.45± 0.63 NSa

Sports index 2.62± 0.91 2.37± 0.73 0.014a

Sports intensityTotal 135 (100) 141 (100)Sedentary 54 (40.0) 78 (55.3)Low 32 (23.7) 32 (22.7) 0.016b

Medium 31 (22.9) 24 (17.0)High 18 (13.3) 7 (4.9)

Note: All values given as mean± S.D., except sports intensity which isn (%). NS: not significant.

a t-test.b χ2-test.

3.2. Correlations

Table 1shows the distribution of the population charac-teristics by gender. Significant differences were noted forbody mass index and sports activity index (both higher formales). The women tended to be more sedentary and lesslikely to achieve a high intensity score. No correlation wasnoted between the work and leisure-time indices and gender.

Table 2shows the correlations between the three indicesand the predictive variables. Subjects with fewer years of

Table 2Correlations between physical activity indices and predictive variables

Predictive variable Indices

Work Sports Leisure

SmokingNo 2.51± 1.01 2.55± 0.87 2.49± 0.68Yes 2.60± 0.80 2.36± 0.74 2.52± 0.66

Pa 0.509 0.075 0.792

Income<5000 NIS per month 2.65± 0.76 2.47± 0.78 2.47± 0.66>5000 NIS per month 2.46± 0.98 2.42± 0.97 2.56± 0.66

Pa 0.103 0.655 0.322

Education0–12 years 2.66± 0.87 2.42± 0.78 2.52± 0.68>12 years 2.44± 0.98 2.56± 0.89 2.49± 0.67

Pa 0.059 0.184 0.784

No. of symptoms0 2.48± 1.01 2.67± 0.92 2.54± 0.681–3 2.43± 0.97 2.58± 0.79 2.51± 0.664–6 2.82± 0.82 2.16± 0.74 2.37± 0.68>7 2.73± 0.65 2.27± 0.79 2.61± 0.72

Pb 0.048 0.002 0.363

a t-test.b F-test.

Table 3Correlation between objective sports intensity level and self-perception ofparticipation in physical activity

Sports intensity level Self-perception

No Yes

Sedentary 119 (73.4) 20 (17.7)Low 23 (14.1) 39 (34.5)Medium 17 (10.5) 34 (30.0)High 2 (1.2) 20 (17.7)

Total 162 (100) 113 (100)

All values given asn (%). P < 0.01 (χ2-test).

education engaged in more physical activity at work (P =0.059), and the nonsmokers had a higher sports index score(P = 0.075); however, neither of these differences reachedstrong statistical significance. There was a significant butinverse relationship between the work and sports indiceswith number of symptoms reported in the past month: thehigher the work index, the more symptoms reported, and thehigher the sports index, the fewer the symptoms.

Table 3shows the comparison between the subjective per-ception of participation in regular physical activity and thesports index. We found that 1.3% of the sample who scoredhigh believed they did not engage in regular physical activ-ity, whereas 17.5% who scored low answered yes to partic-ipating in regular physical activity.

4. Discussion and conclusion

Almost half the sample population studied (48.2%) wasfound to lead a sedentary life-style. The rate, which is un-satisfactorily high, is similar to that reported in the UnitedStates[4], and the Baltic countries (60% in Lithuania, 52% inLatvia and 43% in Estonia)[16]. In two earlier, small-scaleIsraeli surveys, a sedentary life-style was reported in 40.2and 76.8% of the population[17,18]. In the studies from theBaltics, the two most prominent reasons given for avoidingphysical activity were little to no time (54%) and laziness(46.7%) [16]. Similar results were found in another studyin Australia[19]. In our study, corresponding rates were 42and 45%.

Our gender comparison showed that women tend to bemore sedentary than men and less likely to achieve highlevels of physical activity. The same findings were reportedin other studies as well[20–22]. They may be explained byfamily roles and responsibilities as well as culture-specificfactors. For example, women with young children who alsowork outside the home may not have the time to participatein sports or leisure-time physical activities.

The slightly lower index scores for the nonsmokers sup-port the well-recognized negative effect of smoking onphysical activity [16,23]. Also in agreement with otherstudies was the direct relationship between lower level ofeducation and greater physical activity at work, and higher

98 Y. Fogelman et al. / Patient Education and Counseling 53 (2004) 95–99

level of education and greater engagement in sports activ-ities [24–26]. Accordingly, international research studieshave shown that blue-collar employees who perform higherrates of physical activity at work typically exhibit lowerrates of leisure-time physical activity[20,27]. As salary andlevel of education are also directly correlated, well-educatedindividuals might be more likely to join costly health clubsand other physical fitness facilities.

Our results showed that 17.5% of those who answeredyes to participating in regular physical activity were foundto be sedentary on analysis of their specific report of in-tensity of physical activity (Table 3). It is well known fromother studies that overweight persons tend to underreporttheir weight[28,29], probably to create a more ideal pictureof themselves. This may also be true of sedentary people,who may tend to overestimate their overall regular physicalactivity.

Our data indicated that the subjects who displayed moresymptoms had more physical activity at work, and thosewith fewer symptoms had a higher sports index. This findingimplies that sports activity may have a positive effect onhealth, or that people with fewer symptoms engage more insports because symptoms can serve as a barrier to physicalactivity. Furthermore, it has been suggested that a lack ofphysical activity can produce a kind of mental “fatigue” orreduced motivation to take on the discipline of a regularsport. This leads to a vicious cycle which further undermineshealth. These issues are too complicated to tackle using across-sectional design, and they warrant further, controlledstudies.

It should be noted that our study was performed beforethe onset of the intifada and the current wave of war anx-iety and political unrest. Therefore, these factors probablydid not influence the attitudes to physical activity in oursubjects.

4.1. Practice implications

In conclusion, our study population of northern Israel,like the majority of populations in western countries, hasa high rate of physical inactivity. Only 9% of the studygroup met the clinical recommendations for physical activ-ity of the National Heart, Lung, and Blood Institute[30].The highest rates of inactivity were noted in women andin subjects with less education. The most common barri-ers to engagement in physical activity were lack of timeand/or energy. Concerning practice implications, the highlysignificant adverse correlation between the physical activityindices and the patients’ response to the typical anamne-sis question emphasizes the need for accurate history tak-ing among primary care physicians to better target patientsat risk. Special attention should be directed at the high-riskgroups of women and poorly educated subjects. On the ba-sis of the inaccuracy of the self-reports, we suggest thatthe rate of regular physical activity may be even lower thansuspected.

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