Comparative analysis of the musculoskeletal health of the populations of Poland and Spain: a cross-sectional study using the International Classification of Functioning, Disability and Health

Comparative analysis of the musculoskeletal health of the populations of Poland and Spain: a cross-sectional study using the International Classification of Functioning, Disability and Health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative analysis of the musculoskeletal health of the populations of Poland and Spain: a cross-sectional study using the International Classification of Functioning, Disability and Health Agnieszka Wiśniowska-Szurlej, Agnieszka Sozańska, Sandra Jiménez Barrio, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4587742/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Background Musculoskeletal disorders affect approximately 1.71 billion people worldwide and are a growing cause of disability. The International Classification of Functioning, Disability and Health (ICF) is the current framework for describing disability and provides a codification system that can be used to compare data across populations. The availability of comparable data would allow a better understanding of the determinants of health and improve the health of the population. The aim of the study was to make an ICF-based comparison between musculoskeletal health in Poland and Spain. Methods A comparative study was conducted to identify cross-cultural differences between Poland and Spain in the prevalence of ICF entities from the brief ICF core set for post-acute musculoskeletal conditions. Two datasets from previous validation studies in these populations were used for comparison. A total of 840 people with musculoskeletal conditions were included in the study. Information was recoded into ICF qualifiers to obtain comparable data. Statistical analysis included: a) calculation of absolute and relative frequencies on the prevalence of ICF entities, and b) calculation of the level of significance using the Mann-Whitney test for quantitative variables and the Chi-square test for qualitative variables. Results Significant differences in functioning were found between the two samples, with a higher prevalence in all the ICF entities for the Spanish sample. Similarities were found in the ICF components ‘Body Functions’ and ‘environmental factors’, with the most prevalent ICF entities being ‘b280 Sensation of pain’ (86.9% in Spain and 74.2% in Poland) and ‘e225 Climate’ (58.0% and 31.8%) respectively. For ‘Activities and Participation’, differences were observed, with ‘d430 Lifting and carrying objects’ being the most common for the Spanish sample (65.4%) and ‘d450 Walking’ for the Polish sample (47.7%). Conclusions A theoretical application of the ICF has been empirically tested for the first time, a milestone in the development of this research methodology. Differences in the prevalence of ICF entities showed a better musculoskeletal health in the Polish sample. Identifying the strengths and weaknesses of different health care models has the potential to improve population health by implementing best practice-based approaches. Trial registration NCT06283407 International Classification of Functioning Disability and Health Musculoskeletal Diseases Cross-Sectional Studies Figures Figure 1 Background Approximately 1.71 billion people worldwide suffer from musculoskeletal disorders. Due to the increase in non-communicable diseases and an ageing population, the number of people suffering from musculoskeletal disorders and related functional limitations is growing rapidly [ 1 ]. Currently, they are the leading cause of disability worldwide [ 2 ]. Disability is part of a person’s existence and an integral part of the human experience. It results from the interaction between the physical consequences associated with an individual’s health status and their contextual factors, including personal and environmental factors. This understanding of disability is based on the International Classification of Functioning, Disability and Health (ICF) [ 3 ]. The ICF is an international standard for describing, recording and reporting measures of health, functioning, and disability [ 4 ]. The World Health Organization (WHO) recommends the combined use of the ICF and the International Classification of Diseases (ICD), which is intended for reporting morbidity and mortality data [ 5 ]. The ICD-11 diagnosis does not provide information on the patient’s experience of the condition, so the combined use of the ICD and ICF provides a more comprehensive picture of its impact on the patient’s daily life [ 6 ]. Developed in 2001, the ICF is a multidimensional and biopsychosocial view of people, regardless of their health status, level or cause of disability [ 7 ]. The classification describes the interaction between the changes associated with an individual’s condition (impairments of body structures and functions, activity limitations and participation restrictions) and their specific context (personal and environmental factors). One of the purposes of the classification is to serve as a common language for health care professionals to describe the functioning of people with different conditions, thus enabling comparability of research results at national and international levels [ 4 ]. The ICF is very comprehensive, covering over 1400 categories. To facilitate its clinical application, the WHO and the ICF Research Branch introduced the ICF core sets, which are brief lists of ICF entities from the entire classification that are most appropriate for specific conditions and/or clinical contexts [ 8 ]. To date, 54 ICF core sets have been developed for various conditions, circumstances and situations [ 9 ]. As of 2019, only 23 core sets had been validated [ 10 ]. In 14 countries from the WHO Collaborating Centres, the current use of the ICF was reported to be mainly in clinical settings (i.e., data recording in rehabilitation settings, assessment of functional status, and description of disability), with Australia and Sweden being the countries with the most widespread use [ 11 ]. Although the framework established by the ICF has been almost universally adopted and some selected entities have become part of the ICD-11, the use of the ICF in primary and secondary care is still limited [ 12 ]. From a public health perspective, a key challenge for policy and clinical practice is to ensure a health care system that is effective, acceptable and sustainable [ 13 ]. One of the continuing difficulties in using research to achieve public health improvement goals is the lack of comparability of reported results [ 14 ]. Information on the functioning of people with musculoskeletal conditions is needed for health management and health service planning. WHO has adopted the ICF as a model for structured information on disability and functioning, but there is a need to conduct health assessment analyses using the ICF core sets in different settings and countries [ 15 ]. To date, no work has been published comparing levels of functioning assessed using the ICF core sets across countries. The aim of the study was to compare the differences in musculoskeletal health between the Polish and Spanish populations, using the ICF as a framework. To this end, a comparative cross-section a l analysis between countries was carried out. Methods Study design A comparative study was conducted to assess cross-cultural differences in the prevalence of the ICF entities from the brief ICF core set for post-acute musculoskeletal conditions in patients from Poland and Spain. Data from two previous studies assessing the content validity of this ICF core set in both countries were used [ 16 , 17 ]. The study was published according to the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement [ 18 ]. Setting The study was carried out on representative samples from regions of Poland and Spain. In Poland, the analysis covered adults living in the south-eastern areas of the country. To ensure an even distribution of institutions in each region, 25 institutions in different parts of south-eastern Poland were selected and invited to participate in the project. Finally, after obtaining consent, the study was conducted in 15 outpatient rehabilitation facilities. In Spain, the study included adults from the region of Castilla y León (Spain) who were recruited from primary care physiotherapy services belonging to the Regional Healthcare System of Castilla y León (SACYL). These services provide community-based physiotherapy care in both urban and rural areas, and 32 of them participated in patient recruitment. This research was carried out between 2022 and 2023. Participants This study used two datasets of patients with post-acute musculoskeletal conditions. A total of 840 people (528 people from Poland and 312 people from Spain) with musculoskeletal conditions were included. All were diagnosed by a general practitioner and confirmed by the ICD-10 diagnosis given at the time of referral to rehabilitation (osteoarthritis M15-M19, rheumatoid arthritis M05-M06, spine diseases M45-54 and other soft tissues disorders M70-M79). Patients were recruited consecutively from those admitted to outpatient rehabilitation for the treatment of musculoskeletal problems. Inclusion criteria were: a) 18 years of age or older, b) musculoskeletal condition diagnosed according to ICD-10, and c) normal cognitive status allowing reliable research (Abbreviated Mental Test Score > 6). Exclusion criteria were: a) presence of mental disorders (e.g. depression or personality disorders) and b) referral from hospital services. Sample Size The size of the Polish sample was determined on the basis of statistical data on the average registered incidence (number of new patients with a given diagnosis appearing in the public health system) of musculoskeletal diseases in Podkarpackie (Poland) per 100 000 inhabitants [ 19 ]. Based on the incidence of musculoskeletal diseases, the actual percentage of people with a given disease was calculated in relation to the statistical data from the Central Statistical Office on the number of people in certain age groups in Podkarpackie (Poland), which amounted to 44 643 [ 20 ]. A sample selection calculator was then used to calculate the number of people needed for the study, assuming a maximum error of 4% and a 95% confidence level, which was 528 people. In the case of the Spanish region of Castilla y León, data on the prevalence of musculoskeletal conditions were not available, so the sample size was calculated based on the total population (2 308 174 inhabitants), using a confidence level of 90%, a standard deviation (SD) of 0.5 and a margin of error of ± 5%. Although this calculation resulted in a target sample size of 273 subjects, a total of 312 were recruited. Outcome measures Basic socio-demographic data (sex, age, education, occupation) were collected during the study. The number of existing chronic conditions was used to assess general health. A modified version of the brief ICF core set for post-acute musculoskeletal conditions was used to assess the cultural differences between the Polish and Spanish samples. The brief ICF core set for post-acute musculoskeletal conditions includes a total of 31 entities. Ten of these entities belong to the component ‘Body functions’ (b134–b780), 15 to ‘Activities and Participation’ (d155–d550) and 6 to ‘Environmental factors’ (e110–e450). According to the Polish version, the ICF entities ‘e310 Immediate family’, ‘e320 Friends’ and ‘e580 Health services, systems and policies’ were added, while ‘d415 Maintaining body position’ was removed. Thus, a total of were 33 ICF entities were used as outcome measures. To assess the impact of impairments/limitations or restrictions/barriers on musculoskeletal health in terms of functioning, each ICF entity was assessed using the ICF qualifiers (xxx.0 NO problem; xxx.1 MILD problem; xxx.2 MODERATE problem; xxx.3 SEVERE problem; xxx.4 COMPLETE problem; xxx.8 not specified and xxx.9 not applicable). In the case of the assessment of environmental factors, ICF qualifiers were assigned from the respondents’ perspective, recording only whether they had a negative impact (barriers) on their condition. These qualifiers were therefore as follows: xxx.0 NO barrier; xxx.1 MILD barrier; xxx.2 MODERATE barrier; xxx.3 SUBSTANTIAL barrier; xxx.4 COMPLETE barrier [ 4 ]. Data collection A total of 59 collaborating physiotherapists (27 in Poland and 32 in Spain) recruited participants and collected data. They were experienced professionals in the management of musculoskeletal conditions and were trained in the principles and clinical use of the ICF. In Poland, the methodology for assessing the patient’s health status was presented by members of the Polish Council for the Implementation of the International Classification of Functioning, Disability and Health. Polish physiotherapists carried out functional assessments of patients and recorded ICF qualifiers in a specific form. In Spain, collaborating physiotherapists attended a workshop conducted by a researcher trained in the ICF by the ICF Research Branch. They conducted semi-structured interviews to assess the relevance of each ICF entity in relation to the patient’s musculoskeletal condition. Statistical analysis The data were analyzed using the R program, version 4.3.3. First, a descriptive statistical analysis was performed to characterize the sample and qualifier distribution of each ICF entity using absolute and relative frequencies. Comparison of the values of qualitative variables in groups was performed using the chi-square test (with Yates’ correction for 2x2 tables) or Fisher’s exact test when the chi-square test assumptions regarding the so-called expected numbers were not met. The Mann-Whitney test was used to compare the values of quantitative variables in two groups. The significance level used in the analysis was 0.05. There were no missing data in this study, so data from all participants were included in the analyses. Ethical considerations The study was designed and conducted in accordance with the tenets of the Declaration of Helsinki 1996 (modified in 2013 at the 64th Assembly of the World Medical Association in Fortaleza, Brazil). All participants provided written an informed consent. This study was registered on clinicaltrials.gov with the identifier NCT06283407 and was also approved by the Bioethics Committee of the University of Rzeszów (Resolution No. 11/02/2020) and the Ethics Committees for Clinical Research of the Spanish health areas of Burgos-Soria, León-Bierzo, Palencia, Salamanca, Segovia and Valladolid (reference code for the Burgos-Soria area was CEIm 2690). Results Sample characteristics The study included 840 people, 528 from Poland and 312 from Spain. Significant differences were found between the Polish and the Spanish samples for all characteristics except age. A higher percentage of Spanish women (73.4%) than Polish women (57.4%) participated in the study. Participants had a higher level of education in Poland, with 96.8% of participants having completed secondary education or higher, compared to 60.9% in the Spanish sample. A similar situation was observed in terms of employment status, with 69.5% of participants in Poland being actively working, compared to 56.1% in Spain. Finally, Spanish participants had a better general health status with a mean of 1.9 of chronic diseases compared to 2.8 for Polish participants. Detailed characteristics of the two samples are shown in Table 1 . Table 1 Sociodemographic characteristics of the study samples Feature Poland (N = 528) Spain (N = 312) Total (N = 840) p Sex Male 225 (42.61%) 83 (26.60%) 308 (36.67%) p < 0.001 * Female 303 (57.39%) 229 (73.40%) 532 (63.33%) Age [years] Mean (SD) 54.95 (5.64) 55.41 (12.2) 55.12 (8.67) p = 0.083 Median (quartiles) 54.50 (51–58) 56.00 (48–63) 55 (50–59) Education Primary 17 (3.22%) 122 (39.10%) 139 (16.55%) p < 0.001 * Secondary 340 (64.39%) 103 (33.01%) 443 (52.74%) University 171 (32.39%) 87 (27.88%) 258 (30.71%) Employment status Actively working 367 (69.51%) 175 (56.09%) 542 (64.52%) p < 0.001 * Not working 161 (30.49%) 137 (43.91%) 298 (35.48%) Number of comorbidities Mean (SD) 2.83 (1.57) 1.86 (1.55) 2.47 (1.63) p < 0.001 * Median (quartiles) 3 (2–4) 2 (1–3) 2 (1–3) n 528 312 840 p - Qualitative variables: chi-squared or Fisher's exact test. Quantitative variables: Mann-Whitney test * statistically significant (p < 0.05) General overview of differences between Polish and Spanish samples Statistical analysis revealed significant differences in the level of functioning between the Polish and Spanish samples were found. In the Spanish sample, subjects reported a higher prevalence of impairments/limitations/barriers in all ICF entities analized. Differences in impairments in body functions In the ICF component ‘body functions’, the highest prevalence was found in the ICF entity ‘b280 Sensation of pain’ for both samples (74.2% in the Polish sample and 86.9% in the Spanish sample). The less relevant ICF entity was ‘b620 Urination functions’, which was also consistent across samples (15.7% and 26.6%, respectively). Other categories with similar prevalence were ‘b530 Weight maintenance functions’ (57.4% and 55.1%) and ‘b134 Sleep functions’ (64.0% and 78.5%). The higher difference found for this component corresponded to the ICF entity ‘b740 Muscle endurance functions’, which was found to be problematic for 75.3% of the Spanish sample but only for 30,9% of the Polish sample (difference of 44.5% between samples). Full details of the differences in prevalence of impairments in body functions are shown in Table 2 . Table 2 Prevalence of impairments in body functions in the Polish and Spanish samples. ICF Entity Qualifier Poland (N = 528) Spain (N = 312) Total (N = 840) p b134 No problem 190 (35.98%) 67 (21.47%) 257 (30.60%) p < 0.001 * Mild problem 162 (30.68%) 58 (18.59%) 220 (26.19%) Moderate problem 112 (21.21%) 57 (18.27%) 169 (20.12%) Severe problem 48 (9.09%) 118 (37.82%) 166 (19.76%) Complete problem 16 (3.03%) 12 (3.85%) 28 (3.33%) b260 No problem 409 (77.46%) 157 (50.32%) 566 (67.38%) p < 0.001 * Mild problem 77 (14.58%) 48 (15.38%) 125 (14.88%) Moderate problem 23 (4.36%) 32 (10.26%) 55 (6.55%) Severe problem 16 (3.03%) 70 (22.44%) 86 (10.24%) Complete problem 3 (0.57%) 5 (1.60%) 8 (0.95%) b280 No problem 136 (25.76%) 41 (13.14%) 177 (21.07%) p < 0.001 * Mild problem 93 (17.61%) 41 (13.14%) 134 (15.95%) Moderate problem 190 (35.98%) 59 (18.91%) 249 (29.64%) Severe problem 106 (20.08%) 151 (48.40%) 257 (30.60%) Complete problem 3 (0.57%) 20 (6.41%) 23 (2.74%) b435 No problem 185 (35.04%) 200 (64.10%) 385 (45.83%) p < 0.001 * Mild problem 240 (45.45%) 59 (18.91%) 299 (35.60%) Moderate problem 80 (15.15%) 24 (7.69%) 104 (12.38%) Severe problem 13 (2.46%) 28 (8.97%) 41 (4.88%) Complete problem 10 (1.89%) 1 (0.32%) 11 (1.31%) b530 No problem 225 (42.61%) 140 (44.87%) 365 (43.45%) p = 0.015 * Mild problem 188 (35.61%) 59 (18.91%) 247 (29.40%) Moderate problem 83 (15.72%) 38 (12.18%) 121 (14.40%) Severe problem 27 (5.11%) 71 (22.76%) 98 (11.67%) Complete problem 5 (0.95%) 4 (1.28%) 9 (1.07%) b620 No problem 445 (84.28%) 229 (73.40%) 674 (80.24%) p < 0.001 * Mild problem 58 (10.98%) 40 (12.82%) 98 (11.67%) Moderate problem 16 (3.03%) 20 (6.41%) 36 (4.29%) Severe problem 5 (0.95%) 22 (7.05%) 27 (3.21%) Complete problem 4 (0.76%) 1 (0.32%) 5 (0.60%) b730 No problem 305 (57.77%) 62 (19.87%) 367 (43.69%) p < 0.001 * Mild problem 161 (30.49%) 75 (24.04%) 236 (28.10%) Moderate problem 48 (9.09%) 37 (11.86%) 85 (10.12%) Severe problem 12 (2.27%) 128 (41.03%) 140 (16.67%) Complete problem 2 (0.38%) 10 (3.21%) 12 (1.43%) b740 No problem 365 (69.13%) 77 (24.68%) 442 (52.62%) p < 0.001 * Mild problem 103 (19.51%) 59 (18.91%) 162 (19.29%) Moderate problem 31 (5.87%) 39 (12.50%) 70 (8.33%) Severe problem 16 (3.03%) 125 (40.06%) 141 (16.79%) Complete problem 13 (2.46%) 12 (3.85%) 25 (2.98%) b755 No problem 158 (29.92%) 181 (58.01%) 339 (40.36%) p < 0.001 * Mild problem 131 (24.81%) 51 (16.35%) 182 (21.67%) Moderate problem 125 (23.67%) 25 (8.01%) 150 (17.86%) Severe problem 66 (12.50%) 54 (17.31%) 120 (14.29%) Complete problem 48 (9.09%) 1 (0.32%) 49 (5.83%) b780 No problem 226 (42.80%) 74 (23.72%) 300 (35.71%) p < 0.001 * Mild problem 198 (37.50%) 55 (17.63%) 253 (30.12%) Moderate problem 83 (15.72%) 55 (17.63%) 138 (16.43%) Severe problem 15 (2.84%) 122 (39.10%) 137 (16.31%) Complete problem 6 (1.14%) 6 (1.92%) 12 (1.43%) Differences in Activity limitations and/or Participation restrictions The analysis of the prevalence of entities belonging to the ICF ‘activities and participation’ showed that ‘d430 Lifting and carrying objects’ was the most common entity for the Spanish sample (65.4%) and also showed the highest difference between the samples (38.7%). In the Polish sample, the most common ICF entity was ‘d450 Walking’ (47.7%), with a similar prevalence as in the Spanish sample (52.6%). The ICF entity ‘d240 Handling stress and other psychological demands’ was relevant in both samples (61.9% for Spain and 45.6% for Poland). In the Spanish sample, the ICF entities ‘d410 Changing basic body position’ and ‘d230 Carrying out daily routine’ were also important (prevalence of 62.8% and 56.7%, respectively). In the Polish sample, no other ICF entity reached a prevalence of more than 50% (see Table 3 for more details). Table 3 Prevalence of activity limitations and participation restrictions in the Polish and Spanish samples. ICF Entity Qualifier Poland (N = 528) Spain (N = 312) Total (N = 840) p d155 No problem 375 (71.02%) 178 (57.05%) 553 (65.83%) p < 0.001 * Mild problem 105 (19.89%) 48 (15.38%) 153 (18.21%) Moderate problem 34 (6.44%) 28 (8.97%) 62 (7.38%) Severe problem 10 (1.89%) 54 (17.31%) 64 (7.62%) Complete problem 4 (0.76%) 4 (1.28%) 8 (0.95%) d177 No problem 405 (76.70%) 182 (58.33%) 587 (69.88%) p < 0.001 * Mild problem 89 (16.86%) 53 (16.99%) 142 (16.90%) Moderate problem 26 (4.92%) 26 (8.33%) 52 (6.19%) Severe problem 4 (0.76%) 46 (14.74%) 50 (5.95%) Complete problem 4 (0.76%) 5 (1.60%) 9 (1.07%) d230 No problem 342 (64.77%) 135 (43.27%) 477 (56.79%) p < 0.001 * Mild problem 125 (23.67%) 65 (20.83%) 190 (22.62%) Moderate problem 42 (7.95%) 36 (11.54%) 78 (9.29%) Severe problem 11 (2.08%) 70 (22.44%) 81 (9.64%) Complete problem 8 (1.52%) 6 (1.92%) 14 (1.67%) d240 No problem 287 (54.36%) 119 (38.14%) 406 (48.33%) p < 0.001 * Mild problem 147 (27.84%) 69 (22.12%) 216 (25.71%) Moderate problem 71 (13.45%) 42 (13.46%) 113 (13.45%) Severe problem 14 (2.65%) 74 (23.72%) 88 (10.48%) Complete problem 9 (1.70%) 8 (2.56%) 17 (2.02%) d410 No problem 365 (69.13%) 116 (37.18%) 481 (57.26%) p < 0.001 * Mild problem 120 (22.73%) 61 (19.55%) 181 (21.55%) Moderate problem 25 (4.73%) 43 (13.78%) 68 (8.10%) Severe problem 13 (2.46%) 85 (27.24%) 98 (11.67%) Complete problem 5 (0.95%) 7 (2.24%) 12 (1.43%) d430 No problem 387 (73.30%) 108 (34.62%) 495 (58.93%) p < 0.001 * Mild problem 84 (15.91%) 58 (18.59%) 142 (16.90%) Moderate problem 44 (8.33%) 46 (14.74%) 90 (10.71%) Severe problem 11 (2.08%) 85 (27.24%) 96 (11.43%) Complete problem 2 (0.38%) 15 (4.81%) 17 (2.02%) d445 No problem 411 (77.84%) 166 (53.21%) 577 (68.69%) p < 0.001 * Mild problem 82 (15.53%) 53 (16.99%) 135 (16.07%) Moderate problem 24 (4.55%) 30 (9.62%) 54 (6.43%) Severe problem 9 (1.70%) 59 (18.91%) 68 (8.10%) Complete problem 2 (0.38%) 4 (1.28%) 6 (0.71%) d450 No problem 276 (52.27%) 148 (47.44%) 424 (50.48%) p < 0.001 * Mild problem 147 (27.84%) 51 (16.35%) 198 (23.57%) Moderate problem 66 (12.50%) 36 (11.54%) 102 (12.14%) Severe problem 28 (5.30%) 72 (23.08%) 100 (11.90%) Complete problem 11 (2.08%) 5 (1.60%) 16 (1.90%) d465 No problem 482 (91.29%) 196 (62.82%) 678 (80.71%) p < 0.001 * Mild problem 20 (3.79%) 34 (10.90%) 54 (6.43%) Moderate problem 17 (3.22%) 28 (8.97%) 45 (5.36%) Severe problem 7 (1.33%) 53 (16.99%) 60 (7.14%) Complete problem 2 (0.38%) 1 (0.32%) 3 (0.36%) d510 No problem 444 (84.09%) 225 (72.12%) 669 (79.64%) p < 0.001 * Mild problem 57 (10.80%) 37 (11.86%) 94 (11.19%) Moderate problem 18 (3.41%) 23 (7.37%) 41 (4.88%) Severe problem 5 (0.95%) 26 (8.33%) 31 (3.69%) Complete problem 4 (0.76%) 1 (0.32%) 5 (0.60%) d520 No problem 445 (84.28%) 215 (68.91%) 660 (78.57%) p < 0.001 * Mild problem 58 (10.98%) 44 (14.10%) 102 (12.14%) Moderate problem 12 (2.27%) 23 (7.37%) 35 (4.17%) Severe problem 4 (0.76%) 29 (9.29%) 33 (3.93%) Complete problem 9 (1.70%) 1 (0.32%) 10 (1.19%) d530 No problem 495 (93.75%) 254 (81.41%) 749 (89.17%) p < 0.001 * Mild problem 21 (3.98%) 31 (9.94%) 52 (6.19%) Moderate problem 2 (0.38%) 9 (2.88%) 11 (1.31%) Severe problem 6 (1.14%) 17 (5.45%) 23 (2.74%) Complete problem 4 (0.76%) 1 (0.32%) 5 (0.60%) d540 No problem 439 (83.14%) 198 (63.46%) 637 (75.83%) p < 0.001 * Mild problem 69 (13.07%) 52 (16.67%) 121 (14.40%) Moderate problem 11 (2.08%) 28 (8.97%) 39 (4.64%) Severe problem 5 (0.95%) 32 (10.26%) 37 (4.40%) Complete problem 4 (0.76%) 2 (0.64%) 6 (0.71%) d550 No problem 501 (94.89%) 270 (86.54%) 771 (91.79%) p < 0.001 * Mild problem 18 (3.41%) 27 (8.65%) 45 (5.36%) Moderate problem 5 (0.95%) 9 (2.88%) 14 (1.67%) Severe problem 2 (0.38%) 5 (1.60%) 7 (0.83%) Complete problem 2 (0.38%) 1 (0.32%) 3 (0.36%) Differences in barriers in Environmental Factors The most relevant environmental factor in both samples was ‘e225 Climate’, with a prevalence of 58.0% in the Spanish sample and 31.8% in the Polish sample. The prevalence of the remaining ICF entities was low in both samples, with no other entity exceeding 40% in the Spanish sample or 30% in the Polish sample. The highest difference between the samples for these factors was found for ‘e115 Products and technology for personal use in daily living’ (29.5%). More detailed information on environmental factors can be found in Table 4 . Table 4 Prevalence of barriers in Environmental Factors in the Polish and Spanish samples. ICF Entity Qualifier Poland (N = 528) Spain (N = 312) Total (N = 840) p e110 No problem 451 (85.42%) 197 (63.14%) 648 (77.14%) p < 0.001 * Mild problem 15 (2.84%) 48 (15.38%) 63 (7.50%) Moderate problem 17 (3.22%) 16 (5.13%) 33 (3.93%) Severe problem 25 (4.73%) 43 (13.78%) 68 (8.10%) Complete problem 20 (3.79%) 8 (2.56%) 28 (3.33%) e115 No problem 474 (89.77%) 188 (60.26%) 662 (78.81%) p < 0.001 * Mild problem 15 (2.84%) 53 (16.99%) 68 (8.10%) Moderate problem 14 (2.65%) 29 (9.29%) 43 (5.12%) Severe problem 20 (3.79%) 38 (12.18%) 58 (6.90%) Complete problem 5 (0.95%) 4 (1.28%) 9 (1.07%) e120 No problem 497 (94.13%) 219 (70.19%) 716 (85.24%) p < 0.001 * Mild problem 6 (1.14%) 38 (12.18%) 44 (5.24%) Moderate problem 8 (1.52%) 19 (6.09%) 27 (3.21%) Severe problem 9 (1.70%) 32 (10.26%) 41 (4.88%) Complete problem 8 (1.52%) 4 (1.28%) 12 (1.43%) e225 No problem 360 (68.18%) 131 (41.99%) 491 (58.45%) p < 0.001 * Mild problem 85 (16.10%) 46 (14.74%) 131 (15.60%) Moderate problem 50 (9.47%) 43 (13.78%) 93 (11.07%) Severe problem 21 (3.98%) 81 (25.96%) 102 (12.14%) Complete problem 12 (2.27%) 11 (3.53%) 23 (2.74%) e310 No problem 439 (83.14%) 200 (64.10%) 639 (76.07%) p < 0.001 * Mild problem 9 (1.70%) 37 (11.86%) 46 (5.48%) Moderate problem 22 (4.17%) 15 (4.81%) 37 (4.40%) Severe problem 34 (6.44%) 42 (13.46%) 76 (9.05%) Complete problem 24 (4.55%) 18 (5.77%) 42 (5.00%) e320 No problem 440 (83.33%) 207 (66.35%) 647 (77.02%) p < 0.001 * Mild problem 23 (4.36%) 39 (12.50%) 62 (7.38%) Moderate problem 23 (4.36%) 18 (5.77%) 41 (4.88%) Severe problem 28 (5.30%) 39 (12.50%) 67 (7.98%) Complete problem 14 (2.65%) 9 (2.88%) 23 (2.74%) e355 No problem 407 (77.08%) 210 (67.31%) 617 (73.45%) p < 0.001 * Mild problem 51 (9.66%) 32 (10.26%) 83 (9.88%) Moderate problem 39 (7.39%) 10 (3.21%) 49 (5.83%) Severe problem 28 (5.30%) 43 (13.78%) 71 (8.45%) Complete problem 3 (0.57%) 17 (5.45%) 20 (2.38%) e450 No problem 408 (77.27%) 218 (69.87%) 626 (74.52%) p = 0.001 * Mild problem 72 (13.64%) 23 (7.37%) 95 (11.31%) Moderate problem 28 (5.30%) 12 (3.85%) 40 (4.76%) Severe problem 16 (3.03%) 47 (15.06%) 63 (7.50%) Complete problem 4 (0.76%) 12 (3.85%) 16 (1.90%) e580 No problem 415 (78.60%) 177 (56.73%) 592 (70.48%) p < 0.001 * Mild problem 50 (9.47%) 33 (10.58%) 83 (9.88%) Moderate problem 35 (6.63%) 20 (6.41%) 55 (6.55%) Severe problem 22 (4.17%) 62 (19.87%) 84 (10.00%) Complete problem 6 (1.14%) 20 (6.41%) 26 (3.10%) Discussion The aim of the study was to compare the differences in musculoskeletal health between the Polish and Spanish populations, using the ICF as a framework. Despite the potential of the ICF to provide a gold standard against which to measure different aspects of intergroup functioning, this is the first study conducted for this purpose [ 21 ]. According to our findings, there were significant differences in musculoskeletal health between the Polish and Spanish populations in all ICF entities analyzed. Regarding the different ICF domains, the main differences were found in the ICF component ‘activities and participation’. For the Polish sample, the most frequently reported ICF entity was ‘d450 Walking’ (47.7%), whereas for the Spanish sample they were ‘d430 Lifting and carrying objects’ (65.4%). The ability to walk is considered essential for most activities of daily living [ 22 ]. Typical symptoms of musculoskeletal disorders are pain, joint stiffness and reduced mobility. Pain often increases with distance covered [ 23 ]. Winter et al. showed that patients with musculoskeletal disorders have limited walking ability [ 24 ]. Jun et al. showed that people with musculoskeletal conditions often have problems with upper limb activities [ 25 ]. As activity limitations are largely dependent on the anatomical location of the musculoskeletal injury, a possible explanation for this finding is a different prevalence of such conditions between the two samples. This highlights the importance of activity assessment in clinical practice, providing clinicians with feedback on the functional problems experienced by patients on a daily basis and helping to set therapeutic goals. Regarding more general aspects of this ICF component, both populations showed a high prevalence of ICF entity ‘d240 Handling stress and other psychological demands’ (61,9% in Spain and 45.6% in Poland). Patients with musculoskeletal pain were reported to have significantly more symptoms of anxiety, depression, fatigue and insomnia. Therefore, primary care providers should consider mental health issues when treating patients with musculoskeletal conditions [ 26 ]. There were fewer differences between the samples in the ‘body functions’ component. The ICF entity 'b280 sensation of pain' was the most common ICF entity in both populations (prevalence of 78.9% in Spain and 74.2% in Poland). Other ICF entities related to movement, such as ‘b755 Involuntary movement reaction functions’ and ‘b780 Sensations related to muscles and movement functions’, were also found to be important, with small differences in prevalence between countries. The musculoskeletal system is primarily involved in locomotion, movement and the performance of physical tasks [ 27 ]. Musculoskeletal pain is a major burden and challenge for patients, families and carers because it is associated with functional limitations and loss of independence [ 28 , 29 ]. It is considered the main reason for seeking health care from primary care providers [ 30 ]. Moreover, pain associated with musculoskeletal problems leads to drug dependence, suffering, social isolation and emotional distress [ 31 ]. Another finding was the high prevalence of problems related to ‘b134 Sleep functions’, which has also been liked to musculoskeletal problems in the literature [ 32 ]. Finally, ICF entities covering the functioning of other body systems also showed a similar importance, highlighting the multidimensional nature of movement [ 33 ]. With regard to the ICF component ‘environmental factors’, it was expected that the main differences between the Polish and Spanish populations would be found here. However, the most relevant ICF entity for both samples was ‘e225 Climate’ (prevalence was 58.0% in Spain and 31.8% in Poland), a remarkable finding given the marked differences in climate between the two regions. Weather parameters, including changes in temperature, humidity and pressure, are often considered risk factors for the occurrence of chronic diseases or adverse health events [ 34 ]. Changes in weather conditions are often cited by patients with musculoskeletal disorders as an important factor in triggering the onset and development of symptoms [ 35 ]. According to the review by Beukenhorst et al, 67% of studies showed an association between pain and weather variables [ 36 ]. The authors suggested that future research should consider the extent and nature of modifiable risk factors for musculoskeletal pain and strategies for managing them [ 36 ]. In general, environmental factors had a higher prevalence in Spain, but the relative importance of ICF entities was similar in both contexts. Perhaps the greatest difficulty in conducting a cross-country study of this kind is obtaining comparable data. The ICF provides a definition of the universe of functioning and disability that allows direct comparisons of levels of functioning between groups of people. However, as each population has its own specific background, it was expected that there would be differences in socio-demographic characteristics between the samples. In our study, significant differences were found in all areas except age, which poses a challenge to comparability. Spanish women had a higher prevalence of musculoskeletal disorders than Polish women (73.4% and 57.4%, respectively). In the data collection for this study, sex was used as a descriptive measure for the samples. This means that only biological differences between men and women were considered, while other multidimensional concepts related to the concept of gender were not taken into account [ 37 ]. Although a high prevalence in women is consistent with previous studies [ 38 , 39 ], it doesn’t explain the difference found between Poland and Spain. Another finding related to the context of the two samples was the difference in education and employment status, with the Polish population having higher levels of both. A high level of education has been associated with a protective effect on the incidence of musculoskeletal problems [ 40 ] and could explain the greater impact observed in the Spanish population on the ICF entities analyzed. In the case of employment status, its effect is controversial because, although it is recommended to stay active and return to work as soon as possible to reduce chronicity and disability related to musculoskeletal problems [ 41 ], it also implies exposure to ergonomic risk factors that may lead to injury [ 42 ]. Finally, a higher number of comorbidities was observed in the Polish sample, suggesting a lower level of general health compared to the Spanish sample. This is in line with the difference in life expectancy between the two regions. According to Eurostat, the life expectancy is 83.8 years in Castilla y León (Spain) compared to 78.5 years in Podkarpackie (Poland) [ 43 ]. Roffia et al. confirmed the importance of health care expenditure and the health care system in explaining differences in life expectancy between OECD countries [ 44 ]. Spain’s consistency in developing a health system with primary care at its core differs from Poland’s health system, which is more focused on the hospital sector and limits the development of health promotion and disease prevention activities [ 45 , 46 ]. Primary health care, with its multisectoral approach to population health, can address most of the determinants of health and must therefore needs to be sufficiently developed in national health systems [ 47 ]. However, although Spain has made significant progress in general health with a strong primary care-based health system, there seems to be room for improvement in musculoskeletal health when looking at the data from Poland. There are some limitations that should be taking into account when interpretating the findings of this study. The first is that although the data collection took place during the interaction between the physiotherapist and the patient, the Polish sample is dominated by the physiotherapist’s perspective, whereas in the Spanish case a more patient-centered perspective was used. Another limitation is the different method of calculating sample sizes for the two populations. Despite this, and given that the samples were representative of the populations analyzed, we are moderately confident that this will not bias our results. Finally, the socio-demographic data in the two samples are different, but we believe that this is inherent to this type of study and is part of the process of comparing populations from different countries. Conclusions A theoretical application of the ICF has been empirically tested for the first time, which is a milestone in the development of the methodology for conducting this type of research. This study has also provided an insight into the musculoskeletal health of the Polish and Spanish populations and the impact of these conditions in terms of disability. There are many tools to assess patient functioning, but variability in measures presents challenges to data harmonization and the comparability and generalizability of findings. ICF provides a classification system that can support content harmonization and comparison of levels of functioning between different populations. Significant differences were found between the two samples, indicating better musculoskeletal health in the Polish sample. Identifying the strengths and weaknesses of different health care models has the potential to improve the health of populations by allowing a best practice-based approach to be implemented. Abbreviations ICF: The International Classification of Functioning, Disability and Health WHO: The World Health Organization ICD: The International Classification of Diseases STROBE: The Strengthening the Reporting of Observational Studies in Epidemiology Declarations Ethics approval and consent to participate The study was designed and conducted in accordance with the tenets of the Declaration of Helsinki 1996 (modified in 2013 at the 64th Assembly of the World Medical Association in Fortaleza, Brazil). This study was approved by the Bioethics Committee of the University of Rzeszów (Resolution No. 11/02/2020) and the Ethics Committees for Clinical Research of the Spanish health areas of Burgos-Soria, León-Bierzo, Palencia, Salamanca, Segovia and Valladolid (reference code for the Burgos-Soria area was CEIm 2690). Consent for publication Not applicable Availability of data and materials The datasets generated and analysed during the current study are available in the University of Rzeszow repository, https://repozytorium.ur.edu.pl/handle/item/10558 Competing interests The authors declare no conflict of interest. Funding This study was supported by a grant from the Regional Health Administration of Castilla y León (SACYL) with expedient number GRS 2489/B/22. Authors' contributions AWS: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Roles/Writing—original draft. 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Poland: Health System Review. Health Syst Transit. 2019;21(1):1-234. van Weel C, Kidd MR. Why strengthening primary health care is essential to achieving universal health coverage. CMAJ. 2018;190(15):E463–6. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 17 Jun, 2024 Submission checks completed at journal 17 Jun, 2024 First submitted to journal 15 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4587742","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":315579615,"identity":"556d5cee-3851-4072-819b-eb334c21cea7","order_by":0,"name":"Agnieszka Wiśniowska-Szurlej","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYJCCAwwMEkCKjYHhA5ifAMQFRGphnAHXYkCUZWwMzDzEaOHvX2N48OcOCzmD88cSP9u23WPgZ88xYC7Ao0XixhuDw7xnJIwNbqQdls5tK2aQ7HljwDwDn8NunN1wmLFNInHbDfYGoJYEBoMbQFt48GiRB2o5+BOk5fzx5t+WQC32hLQYnO/dcIAXpOVA2jFpRpAtEgS0GN7g/3AYqMXY/kZammXPuQQeiTPPCg7j84vc+WPJH3+21clJ9h8zvvGjLEGOvz154+OCCjzel0hA5YOj5jAeDcCIOYBFkBmvllEwCkbBKBhpAACc8lKIEwaGuwAAAABJRU5ErkJggg==","orcid":"","institution":"Institute of Health Sciences, College of Medical Sciences of the University of Rzeszow","correspondingAuthor":true,"prefix":"","firstName":"Agnieszka","middleName":"","lastName":"Wiśniowska-Szurlej","suffix":""},{"id":315579616,"identity":"4a4c1804-8785-48ff-bfed-b7db7beb2248","order_by":1,"name":"Agnieszka Sozańska","email":"","orcid":"","institution":"Institute of Health Sciences, College of Medical Sciences of the University of Rzeszow","correspondingAuthor":false,"prefix":"","firstName":"Agnieszka","middleName":"","lastName":"Sozańska","suffix":""},{"id":315579617,"identity":"ae1b6dc5-8898-4644-ba1b-50573ece2cb2","order_by":2,"name":"Sandra Jiménez Barrio","email":"","orcid":"","institution":"Faculty of Health Sciences, University of Valladolid, Soria,","correspondingAuthor":false,"prefix":"","firstName":"Sandra","middleName":"Jiménez","lastName":"Barrio","suffix":""},{"id":315579618,"identity":"b9235954-4a1d-4de3-abb6-1a69ec7b5e7f","order_by":3,"name":"Bernard Sozański","email":"","orcid":"","institution":"Institute of Medical Sciences, College of Medical Sciences of the University of Rzeszow","correspondingAuthor":false,"prefix":"","firstName":"Bernard","middleName":"","lastName":"Sozański","suffix":""},{"id":315579619,"identity":"5c62aaec-6b3f-4ab7-9088-6f1aec61686d","order_by":4,"name":"Luis Ceballos Laita","email":"","orcid":"","institution":"Faculty of Health Sciences, University of Valladolid, Soria,","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"Ceballos","lastName":"Laita","suffix":""},{"id":315579620,"identity":"c2baeca5-6dee-41cc-8d55-c367565cb7b7","order_by":5,"name":"Héctor Hernández Lázaro","email":"","orcid":"","institution":"Faculty of Health Sciences, University of Valladolid, Soria,","correspondingAuthor":false,"prefix":"","firstName":"Héctor","middleName":"Hernández","lastName":"Lázaro","suffix":""}],"badges":[],"createdAt":"2024-06-15 20:24:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4587742/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4587742/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59569102,"identity":"1cad1125-b5cf-4ad8-a0c2-b8dffd9e29cd","added_by":"auto","created_at":"2024-07-03 09:43:43","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":250671,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDistribution of qualifiers for individual categories of the ICF Core Set. A – Body Function qualifiers, B – Activity and Participation qualifiers, C – Environmental Factors qualifiers.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage112.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4587742/v1/8a59eedc983e1d215b832c54.jpeg"},{"id":59569771,"identity":"551527f7-314b-4f4e-afd9-41bef047387b","added_by":"auto","created_at":"2024-07-03 09:51:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1425120,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4587742/v1/8601db10-3fa6-4c14-b7ce-b511ee594aeb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative analysis of the musculoskeletal health of the populations of Poland and Spain: a cross-sectional study using the International Classification of Functioning, Disability and Health","fulltext":[{"header":"Background","content":"\u003cp\u003eApproximately 1.71\u0026nbsp;billion people worldwide suffer from musculoskeletal disorders. Due to the increase in non-communicable diseases and an ageing population, the number of people suffering from musculoskeletal disorders and related functional limitations is growing rapidly [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Currently, they are the leading cause of disability worldwide [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDisability is part of a person\u0026rsquo;s existence and an integral part of the human experience. It results from the interaction between the physical consequences associated with an individual\u0026rsquo;s health status and their contextual factors, including personal and environmental factors. This understanding of disability is based on the International Classification of Functioning, Disability and Health (ICF) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The ICF is an international standard for describing, recording and reporting measures of health, functioning, and disability [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The World Health Organization (WHO) recommends the combined use of the ICF and the International Classification of Diseases (ICD), which is intended for reporting morbidity and mortality data [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The ICD-11 diagnosis does not provide information on the patient\u0026rsquo;s experience of the condition, so the combined use of the ICD and ICF provides a more comprehensive picture of its impact on the patient\u0026rsquo;s daily life [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDeveloped in 2001, the ICF is a multidimensional and biopsychosocial view of people, regardless of their health status, level or cause of disability [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The classification describes the interaction between the changes associated with an individual\u0026rsquo;s condition (impairments of body structures and functions, activity limitations and participation restrictions) and their specific context (personal and environmental factors). One of the purposes of the classification is to serve as a common language for health care professionals to describe the functioning of people with different conditions, thus enabling comparability of research results at national and international levels [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe ICF is very comprehensive, covering over 1400 categories. To facilitate its clinical application, the WHO and the ICF Research Branch introduced the ICF core sets, which are brief lists of ICF entities from the entire classification that are most appropriate for specific conditions and/or clinical contexts [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. To date, 54 ICF core sets have been developed for various conditions, circumstances and situations [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. As of 2019, only 23 core sets had been validated [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In 14 countries from the WHO Collaborating Centres, the current use of the ICF was reported to be mainly in clinical settings (i.e., data recording in rehabilitation settings, assessment of functional status, and description of disability), with Australia and Sweden being the countries with the most widespread use [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although the framework established by the ICF has been almost universally adopted and some selected entities have become part of the ICD-11, the use of the ICF in primary and secondary care is still limited [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom a public health perspective, a key challenge for policy and clinical practice is to ensure a health care system that is effective, acceptable and sustainable [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. One of the continuing difficulties in using research to achieve public health improvement goals is the lack of comparability of reported results [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Information on the functioning of people with musculoskeletal conditions is needed for health management and health service planning. WHO has adopted the ICF as a model for structured information on disability and functioning, but there is a need to conduct health assessment analyses using the ICF core sets in different settings and countries [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. To date, no work has been published comparing levels of functioning assessed using the ICF core sets across countries.\u003c/p\u003e \u003cp\u003eThe aim of the study was to compare the differences in musculoskeletal health between the Polish and Spanish populations, using the ICF as a framework. To this end, a comparative cross-section\u003cspan refid=\"Sec17\" class=\"InternalRef\"\u003ea\u003c/span\u003el analysis between countries was carried out.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eA comparative study was conducted to assess cross-cultural differences in the prevalence of the ICF entities from the brief ICF core set for post-acute musculoskeletal conditions in patients from Poland and Spain. Data from two previous studies assessing the content validity of this ICF core set in both countries were used [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study was published according to the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSetting\u003c/h2\u003e \u003cp\u003eThe study was carried out on representative samples from regions of Poland and Spain. In Poland, the analysis covered adults living in the south-eastern areas of the country. To ensure an even distribution of institutions in each region, 25 institutions in different parts of south-eastern Poland were selected and invited to participate in the project. Finally, after obtaining consent, the study was conducted in 15 outpatient rehabilitation facilities.\u003c/p\u003e \u003cp\u003e In Spain, the study included adults from the region of Castilla y Le\u0026oacute;n (Spain) who were recruited from primary care physiotherapy services belonging to the Regional Healthcare System of Castilla y Le\u0026oacute;n (SACYL). These services provide community-based physiotherapy care in both urban and rural areas, and 32 of them participated in patient recruitment. This research was carried out between 2022 and 2023.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThis study used two datasets of patients with post-acute musculoskeletal conditions.\u003c/p\u003e \u003cp\u003eA total of 840 people (528 people from Poland and 312 people from Spain) with musculoskeletal conditions were included. All were diagnosed by a general practitioner and confirmed by the ICD-10 diagnosis given at the time of referral to rehabilitation (osteoarthritis M15-M19, rheumatoid arthritis M05-M06, spine diseases M45-54 and other soft tissues disorders M70-M79).\u003c/p\u003e \u003cp\u003ePatients were recruited consecutively from those admitted to outpatient rehabilitation for the treatment of musculoskeletal problems. Inclusion criteria were: a) 18 years of age or older, b) musculoskeletal condition diagnosed according to ICD-10, and c) normal cognitive status allowing reliable research (Abbreviated Mental Test Score\u0026thinsp;\u0026gt;\u0026thinsp;6). Exclusion criteria were: a) presence of mental disorders (e.g. depression or personality disorders) and b) referral from hospital services.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSample Size\u003c/h2\u003e \u003cp\u003eThe size of the Polish sample was determined on the basis of statistical data on the average registered incidence (number of new patients with a given diagnosis appearing in the public health system) of musculoskeletal diseases in Podkarpackie (Poland) per 100 000 inhabitants [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Based on the incidence of musculoskeletal diseases, the actual percentage of people with a given disease was calculated in relation to the statistical data from the Central Statistical Office on the number of people in certain age groups in Podkarpackie (Poland), which amounted to 44 643 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A sample selection calculator was then used to calculate the number of people needed for the study, assuming a maximum error of 4% and a 95% confidence level, which was 528 people.\u003c/p\u003e \u003cp\u003eIn the case of the Spanish region of Castilla y Le\u0026oacute;n, data on the prevalence of musculoskeletal conditions were not available, so the sample size was calculated based on the total population (2 308 174 inhabitants), using a confidence level of 90%, a standard deviation (SD) of 0.5 and a margin of error of \u0026plusmn;\u0026thinsp;5%. Although this calculation resulted in a target sample size of 273 subjects, a total of 312 were recruited.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOutcome measures\u003c/h2\u003e \u003cp\u003eBasic socio-demographic data (sex, age, education, occupation) were collected during the study. The number of existing chronic conditions was used to assess general health.\u003c/p\u003e \u003cp\u003eA modified version of the brief ICF core set for post-acute musculoskeletal conditions was used to assess the cultural differences between the Polish and Spanish samples.\u003c/p\u003e \u003cp\u003eThe brief ICF core set for post-acute musculoskeletal conditions includes a total of 31 entities. Ten of these entities belong to the component \u0026lsquo;Body functions\u0026rsquo; (b134\u0026ndash;b780), 15 to \u0026lsquo;Activities and Participation\u0026rsquo; (d155\u0026ndash;d550) and 6 to \u0026lsquo;Environmental factors\u0026rsquo; (e110\u0026ndash;e450). According to the Polish version, the ICF entities \u0026lsquo;e310 Immediate family\u0026rsquo;, \u0026lsquo;e320 Friends\u0026rsquo; and \u0026lsquo;e580 Health services, systems and policies\u0026rsquo; were added, while \u0026lsquo;d415 Maintaining body position\u0026rsquo; was removed. Thus, a total of were 33 ICF entities were used as outcome measures.\u003c/p\u003e \u003cp\u003eTo assess the impact of impairments/limitations or restrictions/barriers on musculoskeletal health in terms of functioning, each ICF entity was assessed using the ICF qualifiers (xxx.0 NO problem; xxx.1 MILD problem; xxx.2 MODERATE problem; xxx.3 SEVERE problem; xxx.4 COMPLETE problem; xxx.8 not specified and xxx.9 not applicable). In the case of the assessment of environmental factors, ICF qualifiers were assigned from the respondents\u0026rsquo; perspective, recording only whether they had a negative impact (barriers) on their condition. These qualifiers were therefore as follows: xxx.0 NO barrier; xxx.1 MILD barrier; xxx.2 MODERATE barrier; xxx.3 SUBSTANTIAL barrier; xxx.4 COMPLETE barrier [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eA total of 59 collaborating physiotherapists (27 in Poland and 32 in Spain) recruited participants and collected data. They were experienced professionals in the management of musculoskeletal conditions and were trained in the principles and clinical use of the ICF.\u003c/p\u003e \u003cp\u003eIn Poland, the methodology for assessing the patient\u0026rsquo;s health status was presented by members of the Polish Council for the Implementation of the International Classification of Functioning, Disability and Health. Polish physiotherapists carried out functional assessments of patients and recorded ICF qualifiers in a specific form.\u003c/p\u003e \u003cp\u003eIn Spain, collaborating physiotherapists attended a workshop conducted by a researcher trained in the ICF by the ICF Research Branch. They conducted semi-structured interviews to assess the relevance of each ICF entity in relation to the patient\u0026rsquo;s musculoskeletal condition.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe data were analyzed using the R program, version 4.3.3. First, a descriptive statistical analysis was performed to characterize the sample and qualifier distribution of each ICF entity using absolute and relative frequencies.\u003c/p\u003e \u003cp\u003eComparison of the values of qualitative variables in groups was performed using the chi-square test (with Yates\u0026rsquo; correction for 2x2 tables) or Fisher\u0026rsquo;s exact test when the chi-square test assumptions regarding the so-called expected numbers were not met.\u003c/p\u003e \u003cp\u003eThe Mann-Whitney test was used to compare the values of quantitative variables in two groups. The significance level used in the analysis was 0.05. There were no missing data in this study, so data from all participants were included in the analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003e The study was designed and conducted in accordance with the tenets of the Declaration of Helsinki 1996 (modified in 2013 at the 64th Assembly of the World Medical Association in Fortaleza, Brazil). All participants provided written an informed consent. This study was registered on clinicaltrials.gov with the identifier NCT06283407 and was also approved by the Bioethics Committee of the University of Rzesz\u0026oacute;w (Resolution No. 11/02/2020) and the Ethics Committees for Clinical Research of the Spanish health areas of Burgos-Soria, Le\u0026oacute;n-Bierzo, Palencia, Salamanca, Segovia and Valladolid (reference code for the Burgos-Soria area was CEIm 2690).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSample characteristics\u003c/h2\u003e \u003cp\u003eThe study included 840 people, 528 from Poland and 312 from Spain. Significant differences were found between the Polish and the Spanish samples for all characteristics except age.\u003c/p\u003e \u003cp\u003eA higher percentage of Spanish women (73.4%) than Polish women (57.4%) participated in the study. Participants had a higher level of education in Poland, with 96.8% of participants having completed secondary education or higher, compared to 60.9% in the Spanish sample. A similar situation was observed in terms of employment status, with 69.5% of participants in Poland being actively working, compared to 56.1% in Spain. Finally, Spanish participants had a better general health status with a mean of 1.9 of chronic diseases compared to 2.8 for Polish participants. Detailed characteristics of the two samples are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic characteristics of the study samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFeature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoland (N\u0026thinsp;=\u0026thinsp;528)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpain (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal (N\u0026thinsp;=\u0026thinsp;840)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225 (42.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83 (26.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e308 (36.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e303 (57.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e229 (73.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e532 (63.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge [years]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.95 (5.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.41 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.12 (8.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.083\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian (quartiles)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.50 (51\u0026ndash;58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.00 (48\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55 (50\u0026ndash;59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (3.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122 (39.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e139 (16.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e340 (64.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103 (33.01%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e443 (52.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171 (32.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87 (27.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e258 (30.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEmployment status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActively working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e367 (69.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e175 (56.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e542 (64.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e161 (30.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137 (43.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e298 (35.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNumber of comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.83 (1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.86 (1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.47 (1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian (quartiles)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ep - Qualitative variables: chi-squared or Fisher's exact test. Quantitative variables: Mann-Whitney test\u003c/p\u003e \u003cp\u003e* statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eGeneral overview of differences between Polish and Spanish samples\u003c/h2\u003e \u003cp\u003eStatistical analysis revealed significant differences in the level of functioning between the Polish and Spanish samples were found. In the Spanish sample, subjects reported a higher prevalence of impairments/limitations/barriers in all ICF entities analized.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDifferences in impairments in body functions\u003c/h2\u003e \u003cp\u003eIn the ICF component \u0026lsquo;body functions\u0026rsquo;, the highest prevalence was found in the ICF entity \u0026lsquo;b280 Sensation of pain\u0026rsquo; for both samples (74.2% in the Polish sample and 86.9% in the Spanish sample). The less relevant ICF entity was \u0026lsquo;b620 Urination functions\u0026rsquo;, which was also consistent across samples (15.7% and 26.6%, respectively). Other categories with similar prevalence were \u0026lsquo;b530 Weight maintenance functions\u0026rsquo; (57.4% and 55.1%) and \u0026lsquo;b134 Sleep functions\u0026rsquo; (64.0% and 78.5%).\u003c/p\u003e \u003cp\u003eThe higher difference found for this component corresponded to the ICF entity \u0026lsquo;b740 Muscle endurance functions\u0026rsquo;, which was found to be problematic for 75.3% of the Spanish sample but only for 30,9% of the Polish sample (difference of 44.5% between samples). Full details of the differences in prevalence of impairments in body functions are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of impairments in body functions in the Polish and Spanish samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICF Entity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQualifier\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoland (N\u0026thinsp;=\u0026thinsp;528)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpain (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal (N\u0026thinsp;=\u0026thinsp;840)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eb134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e190 (35.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67 (21.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e257 (30.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e162 (30.68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58 (18.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e220 (26.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112 (21.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57 (18.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e169 (20.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48 (9.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e118 (37.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e166 (19.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (3.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (3.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28 (3.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eb260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e409 (77.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e157 (50.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e566 (67.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77 (14.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48 (15.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e125 (14.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (4.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32 (10.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55 (6.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (3.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70 (22.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86 (10.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (0.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (1.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8 (0.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eb280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e136 (25.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41 (13.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e177 (21.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93 (17.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41 (13.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e134 (15.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e190 (35.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59 (18.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e249 (29.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e106 (20.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e151 (48.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e257 (30.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (0.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20 (6.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23 (2.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eb435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e185 (35.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e200 (64.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e385 (45.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e240 (45.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59 (18.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e299 (35.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80 (15.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24 (7.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e104 (12.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (2.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28 (8.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41 (4.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (1.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11 (1.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eb530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e225 (42.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e140 (44.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e365 (43.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.015 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e188 (35.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59 (18.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e247 (29.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83 (15.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38 (12.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121 (14.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27 (5.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e71 (22.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98 (11.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (1.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9 (1.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eb620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e445 (84.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e229 (73.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e674 (80.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58 (10.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40 (12.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98 (11.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (3.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20 (6.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36 (4.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22 (7.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27 (3.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5 (0.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eb730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e305 (57.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62 (19.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e367 (43.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e161 (30.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75 (24.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e236 (28.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48 (9.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37 (11.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85 (10.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (2.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e128 (41.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e140 (16.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (3.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12 (1.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eb740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e365 (69.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77 (24.68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e442 (52.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e103 (19.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59 (18.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e162 (19.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (5.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39 (12.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70 (8.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (3.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e125 (40.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e141 (16.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (2.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (3.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25 (2.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eb755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158 (29.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e181 (58.01%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e339 (40.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131 (24.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51 (16.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e182 (21.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125 (23.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25 (8.01%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e150 (17.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66 (12.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54 (17.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120 (14.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48 (9.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49 (5.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eb780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e226 (42.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74 (23.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e300 (35.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e198 (37.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55 (17.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e253 (30.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83 (15.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55 (17.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e138 (16.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (2.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e122 (39.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e137 (16.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (1.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 (1.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12 (1.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eDifferences in Activity limitations and/or Participation restrictions\u003c/h2\u003e \u003cp\u003eThe analysis of the prevalence of entities belonging to the ICF \u0026lsquo;activities and participation\u0026rsquo; showed that \u0026lsquo;d430 Lifting and carrying objects\u0026rsquo; was the most common entity for the Spanish sample (65.4%) and also showed the highest difference between the samples (38.7%). In the Polish sample, the most common ICF entity was \u0026lsquo;d450 Walking\u0026rsquo; (47.7%), with a similar prevalence as in the Spanish sample (52.6%).\u003c/p\u003e \u003cp\u003eThe ICF entity \u0026lsquo;d240 Handling stress and other psychological demands\u0026rsquo; was relevant in both samples (61.9% for Spain and 45.6% for Poland). In the Spanish sample, the ICF entities \u0026lsquo;d410 Changing basic body position\u0026rsquo; and \u0026lsquo;d230 Carrying out daily routine\u0026rsquo; were also important (prevalence of 62.8% and 56.7%, respectively). In the Polish sample, no other ICF entity reached a prevalence of more than 50% (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e for more details).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of activity limitations and participation restrictions in the Polish and Spanish samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICF Entity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQualifier\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoland (N\u0026thinsp;=\u0026thinsp;528)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpain (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal (N\u0026thinsp;=\u0026thinsp;840)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e375 (71.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e178 (57.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e553 (65.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105 (19.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48 (15.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e153 (18.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34 (6.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28 (8.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62 (7.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (1.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54 (17.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64 (7.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (1.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8 (0.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e405 (76.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e182 (58.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e587 (69.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89 (16.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53 (16.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e142 (16.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 (4.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26 (8.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52 (6.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46 (14.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50 (5.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (1.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9 (1.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e342 (64.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e135 (43.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e477 (56.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125 (23.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65 (20.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e190 (22.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42 (7.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36 (11.54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78 (9.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (2.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70 (22.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81 (9.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (1.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 (1.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14 (1.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e287 (54.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e119 (38.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e406 (48.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147 (27.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69 (22.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e216 (25.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71 (13.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42 (13.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e113 (13.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (2.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74 (23.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88 (10.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (1.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (2.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17 (2.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e365 (69.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e116 (37.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e481 (57.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120 (22.73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61 (19.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e181 (21.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (4.73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43 (13.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68 (8.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (2.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85 (27.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98 (11.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7 (2.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12 (1.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e387 (73.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e108 (34.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e495 (58.93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84 (15.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58 (18.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e142 (16.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44 (8.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46 (14.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90 (10.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (2.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85 (27.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96 (11.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15 (4.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17 (2.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e411 (77.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e166 (53.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e577 (68.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82 (15.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53 (16.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e135 (16.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (4.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30 (9.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54 (6.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (1.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59 (18.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68 (8.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (1.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6 (0.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e276 (52.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e148 (47.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e424 (50.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147 (27.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51 (16.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e198 (23.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66 (12.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36 (11.54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102 (12.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (5.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72 (23.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100 (11.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (2.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (1.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16 (1.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e482 (91.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e196 (62.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e678 (80.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (3.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34 (10.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54 (6.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17 (3.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28 (8.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45 (5.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (1.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53 (16.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60 (7.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (0.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e444 (84.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e225 (72.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e669 (79.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (10.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37 (11.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94 (11.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (3.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23 (7.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41 (4.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26 (8.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31 (3.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5 (0.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e445 (84.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e215 (68.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e660 (78.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58 (10.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44 (14.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102 (12.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (2.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23 (7.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35 (4.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29 (9.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33 (3.93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (1.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10 (1.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e495 (93.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e254 (81.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e749 (89.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (3.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31 (9.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52 (6.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (2.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11 (1.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (1.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17 (5.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23 (2.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5 (0.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e439 (83.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e198 (63.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e637 (75.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69 (13.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52 (16.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121 (14.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (2.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28 (8.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39 (4.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32 (10.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37 (4.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (0.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6 (0.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ed550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e501 (94.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e270 (86.54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e771 (91.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (3.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27 (8.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45 (5.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (2.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14 (1.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (1.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7 (0.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (0.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDifferences in barriers in Environmental Factors\u003c/h2\u003e \u003cp\u003eThe most relevant environmental factor in both samples was \u0026lsquo;e225 Climate\u0026rsquo;, with a prevalence of 58.0% in the Spanish sample and 31.8% in the Polish sample. The prevalence of the remaining ICF entities was low in both samples, with no other entity exceeding 40% in the Spanish sample or 30% in the Polish sample. The highest difference between the samples for these factors was found for \u0026lsquo;e115 Products and technology for personal use in daily living\u0026rsquo; (29.5%). More detailed information on environmental factors can be found in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of barriers in Environmental Factors in the Polish and Spanish samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICF Entity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQualifier\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoland (N\u0026thinsp;=\u0026thinsp;528)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpain (N\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal (N\u0026thinsp;=\u0026thinsp;840)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ee110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e451 (85.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e197 (63.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e648 (77.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (2.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48 (15.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63 (7.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17 (3.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16 (5.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33 (3.93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (4.73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43 (13.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68 (8.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (3.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (2.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28 (3.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ee115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e474 (89.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e188 (60.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e662 (78.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (2.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53 (16.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68 (8.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (2.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29 (9.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43 (5.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (3.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38 (12.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58 (6.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (1.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9 (1.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ee120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e497 (94.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e219 (70.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e716 (85.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (1.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38 (12.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44 (5.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (1.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19 (6.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27 (3.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (1.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32 (10.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41 (4.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (1.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (1.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12 (1.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ee225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e360 (68.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e131 (41.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e491 (58.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85 (16.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46 (14.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e131 (15.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50 (9.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43 (13.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93 (11.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (3.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81 (25.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102 (12.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (2.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (3.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23 (2.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ee310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e439 (83.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e200 (64.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e639 (76.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (1.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37 (11.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46 (5.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (4.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15 (4.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37 (4.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34 (6.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42 (13.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76 (9.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (4.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18 (5.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42 (5.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ee320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e440 (83.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e207 (66.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e647 (77.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (4.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39 (12.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62 (7.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (4.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18 (5.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41 (4.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (5.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39 (12.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67 (7.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (2.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (2.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23 (2.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ee355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e407 (77.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e210 (67.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e617 (73.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51 (9.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32 (10.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83 (9.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39 (7.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (3.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49 (5.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (5.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43 (13.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71 (8.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (0.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17 (5.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20 (2.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ee450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e408 (77.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e218 (69.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e626 (74.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72 (13.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23 (7.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95 (11.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (5.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (3.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40 (4.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (3.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47 (15.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63 (7.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (3.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16 (1.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ee580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e415 (78.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e177 (56.73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e592 (70.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001 *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50 (9.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33 (10.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83 (9.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35 (6.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20 (6.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55 (6.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (4.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62 (19.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84 (10.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplete problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (1.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20 (6.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26 (3.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe aim of the study was to compare the differences in musculoskeletal health between the Polish and Spanish populations, using the ICF as a framework. Despite the potential of the ICF to provide a gold standard against which to measure different aspects of intergroup functioning, this is the first study conducted for this purpose [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to our findings, there were significant differences in musculoskeletal health between the Polish and Spanish populations in all ICF entities analyzed. Regarding the different ICF domains, the main differences were found in the ICF component \u0026lsquo;activities and participation\u0026rsquo;. For the Polish sample, the most frequently reported ICF entity was \u0026lsquo;d450 Walking\u0026rsquo; (47.7%), whereas for the Spanish sample they were \u0026lsquo;d430 Lifting and carrying objects\u0026rsquo; (65.4%). The ability to walk is considered essential for most activities of daily living [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Typical symptoms of musculoskeletal disorders are pain, joint stiffness and reduced mobility. Pain often increases with distance covered [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Winter et al. showed that patients with musculoskeletal disorders have limited walking ability [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Jun et al. showed that people with musculoskeletal conditions often have problems with upper limb activities [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. As activity limitations are largely dependent on the anatomical location of the musculoskeletal injury, a possible explanation for this finding is a different prevalence of such conditions between the two samples. This highlights the importance of activity assessment in clinical practice, providing clinicians with feedback on the functional problems experienced by patients on a daily basis and helping to set therapeutic goals. Regarding more general aspects of this ICF component, both populations showed a high prevalence of ICF entity \u0026lsquo;d240 Handling stress and other psychological demands\u0026rsquo; (61,9% in Spain and 45.6% in Poland). Patients with musculoskeletal pain were reported to have significantly more symptoms of anxiety, depression, fatigue and insomnia. Therefore, primary care providers should consider mental health issues when treating patients with musculoskeletal conditions [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere were fewer differences between the samples in the \u0026lsquo;body functions\u0026rsquo; component. The ICF entity 'b280 sensation of pain' was the most common ICF entity in both populations (prevalence of 78.9% in Spain and 74.2% in Poland). Other ICF entities related to movement, such as \u0026lsquo;b755 Involuntary movement reaction functions\u0026rsquo; and \u0026lsquo;b780 Sensations related to muscles and movement functions\u0026rsquo;, were also found to be important, with small differences in prevalence between countries. The musculoskeletal system is primarily involved in locomotion, movement and the performance of physical tasks [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Musculoskeletal pain is a major burden and challenge for patients, families and carers because it is associated with functional limitations and loss of independence [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It is considered the main reason for seeking health care from primary care providers [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Moreover, pain associated with musculoskeletal problems leads to drug dependence, suffering, social isolation and emotional distress [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Another finding was the high prevalence of problems related to \u0026lsquo;b134 Sleep functions\u0026rsquo;, which has also been liked to musculoskeletal problems in the literature [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Finally, ICF entities covering the functioning of other body systems also showed a similar importance, highlighting the multidimensional nature of movement [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWith regard to the ICF component \u0026lsquo;environmental factors\u0026rsquo;, it was expected that the main differences between the Polish and Spanish populations would be found here. However, the most relevant ICF entity for both samples was \u0026lsquo;e225 Climate\u0026rsquo; (prevalence was 58.0% in Spain and 31.8% in Poland), a remarkable finding given the marked differences in climate between the two regions. Weather parameters, including changes in temperature, humidity and pressure, are often considered risk factors for the occurrence of chronic diseases or adverse health events [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Changes in weather conditions are often cited by patients with musculoskeletal disorders as an important factor in triggering the onset and development of symptoms [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. According to the review by Beukenhorst et al, 67% of studies showed an association between pain and weather variables [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The authors suggested that future research should consider the extent and nature of modifiable risk factors for musculoskeletal pain and strategies for managing them [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In general, environmental factors had a higher prevalence in Spain, but the relative importance of ICF entities was similar in both contexts.\u003c/p\u003e \u003cp\u003ePerhaps the greatest difficulty in conducting a cross-country study of this kind is obtaining comparable data. The ICF provides a definition of the universe of functioning and disability that allows direct comparisons of levels of functioning between groups of people. However, as each population has its own specific background, it was expected that there would be differences in socio-demographic characteristics between the samples. In our study, significant differences were found in all areas except age, which poses a challenge to comparability.\u003c/p\u003e \u003cp\u003eSpanish women had a higher prevalence of musculoskeletal disorders than Polish women (73.4% and 57.4%, respectively). In the data collection for this study, sex was used as a descriptive measure for the samples. This means that only biological differences between men and women were considered, while other multidimensional concepts related to the concept of gender were not taken into account [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Although a high prevalence in women is consistent with previous studies [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], it doesn\u0026rsquo;t explain the difference found between Poland and Spain.\u003c/p\u003e \u003cp\u003eAnother finding related to the context of the two samples was the difference in education and employment status, with the Polish population having higher levels of both. A high level of education has been associated with a protective effect on the incidence of musculoskeletal problems [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and could explain the greater impact observed in the Spanish population on the ICF entities analyzed. In the case of employment status, its effect is controversial because, although it is recommended to stay active and return to work as soon as possible to reduce chronicity and disability related to musculoskeletal problems [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], it also implies exposure to ergonomic risk factors that may lead to injury [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFinally, a higher number of comorbidities was observed in the Polish sample, suggesting a lower level of general health compared to the Spanish sample. This is in line with the difference in life expectancy between the two regions. According to Eurostat, the life expectancy is 83.8 years in Castilla y Le\u0026oacute;n (Spain) compared to 78.5 years in Podkarpackie (Poland) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Roffia et al. confirmed the importance of health care expenditure and the health care system in explaining differences in life expectancy between OECD countries [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Spain\u0026rsquo;s consistency in developing a health system with primary care at its core differs from Poland\u0026rsquo;s health system, which is more focused on the hospital sector and limits the development of health promotion and disease prevention activities [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Primary health care, with its multisectoral approach to population health, can address most of the determinants of health and must therefore needs to be sufficiently developed in national health systems [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. However, although Spain has made significant progress in general health with a strong primary care-based health system, there seems to be room for improvement in musculoskeletal health when looking at the data from Poland.\u003c/p\u003e \u003cp\u003eThere are some limitations that should be taking into account when interpretating the findings of this study. The first is that although the data collection took place during the interaction between the physiotherapist and the patient, the Polish sample is dominated by the physiotherapist\u0026rsquo;s perspective, whereas in the Spanish case a more patient-centered perspective was used. Another limitation is the different method of calculating sample sizes for the two populations. Despite this, and given that the samples were representative of the populations analyzed, we are moderately confident that this will not bias our results. Finally, the socio-demographic data in the two samples are different, but we believe that this is inherent to this type of study and is part of the process of comparing populations from different countries.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eA theoretical application of the ICF has been empirically tested for the first time, which is a milestone in the development of the methodology for conducting this type of research. This study has also provided an insight into the musculoskeletal health of the Polish and Spanish populations and the impact of these conditions in terms of disability. There are many tools to assess patient functioning, but variability in measures presents challenges to data harmonization and the comparability and generalizability of findings. ICF provides\u003c/p\u003e \u003cp\u003ea classification system that can support content harmonization and comparison of levels of functioning between different populations. Significant differences were found between the two samples, indicating better musculoskeletal health in the Polish sample. Identifying the strengths and weaknesses of different health care models has the potential to improve the health of populations by allowing a best practice-based approach to be implemented.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eICF: The International Classification of Functioning, Disability and Health\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWHO: The World Health Organization\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eICD: The International Classification of Diseases\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSTROBE: The Strengthening the Reporting of Observational Studies in Epidemiology\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was designed and conducted in accordance with the tenets of the Declaration of Helsinki 1996 (modified in 2013 at the 64th Assembly of the World Medical Association in Fortaleza, Brazil). This study was approved by the Bioethics Committee of the University of Rzesz\u0026oacute;w (Resolution No. 11/02/2020) and the Ethics Committees for Clinical Research of the Spanish health areas of Burgos-Soria, Le\u0026oacute;n-Bierzo, Palencia, Salamanca, Segovia and Valladolid (reference code for the Burgos-Soria area was CEIm 2690).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are available in the University of Rzeszow repository, https://repozytorium.ur.edu.pl/handle/item/10558\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by a grant from the Regional Health Administration of Castilla y Le\u0026oacute;n (SACYL) with expedient number GRS 2489/B/22.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAWS: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Roles/Writing\u0026mdash;original draft. Prepared Figure 1 and Tables 1,2,3 and 4, Writing\u0026mdash;review \u0026amp; editing. AS: Validation, Supervision, Roles/Writing\u0026mdash;original draft, Writing\u0026mdash;review \u0026amp; editing. SJB: Data curation, Writing\u0026mdash;review \u0026amp; editing. BS: Validation, Writing\u0026mdash;review \u0026amp; editing. LCL: Data curation, Writing\u0026mdash;review \u0026amp; editing. HHL Data curation, Formal analysis, Funding acquisition, Methodology, Visualization, Roles/Writing\u0026mdash;original draft, Writing\u0026mdash;review \u0026amp; editing. The authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. Musculoskeletal health. 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CMAJ. 2018;190(15):E463\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-research-methodology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmrm","sideBox":"Learn more about [BMC Medical Research Methodology](http://bmcmedresmethodol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmrm/default.aspx","title":"BMC Medical Research Methodology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"International Classification of Functioning, Disability and Health, Musculoskeletal Diseases, Cross-Sectional Studies","lastPublishedDoi":"10.21203/rs.3.rs-4587742/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4587742/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMusculoskeletal disorders affect approximately 1.71\u0026nbsp;billion people worldwide and are a growing cause of disability. The International Classification of Functioning, Disability and Health (ICF) is the current framework for describing disability and provides a codification system that can be used to compare data across populations. The availability of comparable data would allow a better understanding of the determinants of health and improve the health of the population. The aim of the study was to make an ICF-based comparison between musculoskeletal health in Poland and Spain.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA comparative study was conducted to identify cross-cultural differences between Poland and Spain in the prevalence of ICF entities from the brief ICF core set for post-acute musculoskeletal conditions. Two datasets from previous validation studies in these populations were used for comparison. A total of 840 people with musculoskeletal conditions were included in the study. Information was recoded into ICF qualifiers to obtain comparable data. Statistical analysis included: a) calculation of absolute and relative frequencies on the prevalence of ICF entities, and b) calculation of the level of significance using the Mann-Whitney test for quantitative variables and the Chi-square test for qualitative variables.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSignificant differences in functioning were found between the two samples, with a higher prevalence in all the ICF entities for the Spanish sample. Similarities were found in the ICF components \u0026lsquo;Body Functions\u0026rsquo; and \u0026lsquo;environmental factors\u0026rsquo;, with the most prevalent ICF entities being \u0026lsquo;b280 Sensation of pain\u0026rsquo; (86.9% in Spain and 74.2% in Poland) and \u0026lsquo;e225 Climate\u0026rsquo; (58.0% and 31.8%) respectively. For \u0026lsquo;Activities and Participation\u0026rsquo;, differences were observed, with \u0026lsquo;d430 Lifting and carrying objects\u0026rsquo; being the most common for the Spanish sample (65.4%) and \u0026lsquo;d450 Walking\u0026rsquo; for the Polish sample (47.7%).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eA theoretical application of the ICF has been empirically tested for the first time, a milestone in the development of this research methodology. Differences in the prevalence of ICF entities showed a better musculoskeletal health in the Polish sample. Identifying the strengths and weaknesses of different health care models has the potential to improve population health by implementing best practice-based approaches.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e \u003cp\u003eNCT06283407\u003c/p\u003e","manuscriptTitle":"Comparative analysis of the musculoskeletal health of the populations of Poland and Spain: a cross-sectional study using the International Classification of Functioning, Disability and Health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-03 09:43:38","doi":"10.21203/rs.3.rs-4587742/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2024-06-17T19:35:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-17T19:34:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Research Methodology","date":"2024-06-15T20:23:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-research-methodology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmrm","sideBox":"Learn more about [BMC Medical Research Methodology](http://bmcmedresmethodol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmrm/default.aspx","title":"BMC Medical Research Methodology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5a94bca0-1ea9-437d-a9cc-8c464a71c6b7","owner":[],"postedDate":"July 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-07-03T09:43:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-03 09:43:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4587742","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4587742","identity":"rs-4587742","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}