Title: Physical activity and multiple sclerosis: new insights regarding inactivity
Abstract: Acta Neurologica ScandinavicaVolume 126, Issue 4 p. 256-262 Original ArticleFree Access Physical activity and multiple sclerosis: new insights regarding inactivity B. M. Sandroff, B. M. Sandroff Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USASearch for more papers by this authorD. Dlugonski, D. Dlugonski Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USASearch for more papers by this authorM. Weikert, M. Weikert Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USASearch for more papers by this authorY. Suh, Y. Suh Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USASearch for more papers by this authorS. Balantrapu, S. Balantrapu Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USASearch for more papers by this authorR. W. Motl, Corresponding Author R. W. Motl Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA Robert W. Motl, 233 Freer Hall, 906 S. Goodwin Ave, Urbana, IL 61801, USA Tel.: (217) 265-0886 Fax: (217) 244-7322 e-mail: [email protected] for more papers by this author B. M. Sandroff, B. M. Sandroff Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USASearch for more papers by this authorD. Dlugonski, D. Dlugonski Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USASearch for more papers by this authorM. Weikert, M. Weikert Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USASearch for more papers by this authorY. Suh, Y. Suh Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USASearch for more papers by this authorS. Balantrapu, S. Balantrapu Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USASearch for more papers by this authorR. W. Motl, Corresponding Author R. W. Motl Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA Robert W. Motl, 233 Freer Hall, 906 S. Goodwin Ave, Urbana, IL 61801, USA Tel.: (217) 265-0886 Fax: (217) 244-7322 e-mail: [email protected] for more papers by this author First published: 03 January 2012 https://doi.org/10.1111/j.1600-0404.2011.01634.xCitations: 115AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Objectives There is increasing recognition that physical activity has beneficial consequences among persons with multiple sclerosis (MS), but there is concern regarding the current degree of physical inactivity in this population because of limitations with previous research and increased recognition of health behaviors in MS. This study compared physical activity levels between large samples of persons with mild MS and matched controls using validated measures of physical activity. Materials and methods The sample included 77 cases of MS and 77 controls matched on age, height, weight, and gender. Physical activity was assessed using five measures, namely the Godin Leisure-Time Exercise Questionnaire (GLTEQ), International Physical Activity Questionnaire (IPAQ), and activity counts per day, step counts per day, and time spent in moderate-to-vigorous physical activity (MVPA) per day by accelerometry. Results There were statistically significant differences between groups in accelerometer activity counts (t = −3.87, P = 0.0001), accelerometer step counts (t = −4.29, P = 0.0001), time spent in MVPA (t = −2.39, P = 0.01), GLTEQ scores (t = −3.83, P = 0.0001), and IPAQ scores (t = −3.42, P = 0.0001). The average effect size across all five measures was d = −0.59 and indicated that persons with MS overall were moderately less physically active than the matched controls. Conclusions The primary finding was a moderate reduction in physical activity among those with MS, but the magnitude was substantially smaller than reported in a published meta-analysis. Importantly, the degree of physical inactivity can likely be overcome through the delivery of behavioral interventions for increasing physical activity and this should translate into meaningful consequences for persons with MS. Introduction Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS; 1) with an estimated prevalence of 1 per 1000 persons in the United States 2, 3. The disease process itself causes a variety of neuropathological changes in the CNS 1, 4 and typically manifests in the heterogeneous expression of symptoms (e.g., fatigue and depression) and accumulation of physical and cognitive impairments over time. There is some evidence that those manifestations of MS can be mitigated, in part, if persons with MS engage in sufficient physical activity 5-8. To date, the existing evidence indicates that this population is substantially less physically active than the general population of adults 9, 10 and this both negates the aforementioned benefits of physical activity 11 and further increases the risk of secondary conditions (e.g., cardiovascular diseases; 12) that can accelerate the rate of disability progression 13. We believe that previous estimates regarding the extent of physical inactivity in persons with MS are upwardly biased, in part, by a set of limitations. One limitation has been the inclusion of physical activity measures with unknown evidence for the validity of scores 9, 14. For example, self-reported measures often contain items that reflect physical activity plus mobility limitations, disability, or community participation, and this would upwardly bias the magnitude of differences in physical activity between persons with MS and controls 15. We note that previous research has often included small samples of persons with MS, typically fewer than 20 cases, and did not include controls matched on age, gender, height, and weight when examining differences in physical activity. We further note that previous estimates of physical activity might not be currently accurate given the increasing awareness of health behaviors in persons with MS. Collectively, such observations motivated the present study to examine the difference in physical activity behavior using validated objective and self-reported measures of physical activity 16, 17 in a larger sample of persons with MS who had minimal disability and a sample of age, gender, height, and weight matched controls. The hypothesis was that persons with MS who had minimal disability would be less physically active than matched controls, but that the difference would be smaller than previously reported in a quantitative synthesis 10, given the emphasis on overcoming the aforementioned limitations of measurement, sample size, and matching of controls and current emphasis on health behaviors. Materials and methods Participants We recruited the sample of persons with MS through direct contact with support groups of a Midwestern chapter of the National Multiple Sclerosis Society that were located within an approximately 90-min drive of our campus. The sample of controls was recruited from within our campus and its surrounding community through the provision of public, campus-wide postings via e-mail. Persons with MS and matched controls were presented with a detailed description of the research study and were recruited based on expressing interest in participation and fulfillment of inclusion criteria. The inclusion criteria for those with MS involved a clinically definite diagnosis of MS and relapse-free during the past 30 days before testing. Additional inclusion criteria for all participants involved (i) being ambulatory with minimal assistance (i.e., able to walk unassisted or using an assistive device, including cane or crutch, but not a walker or other bilateral assistance); (ii) being 18–64 years of age; (iii) having the visual ability necessary to read 14-point font; (iv) being willing and able to wear the accelerometer over a 7-day period. The final sample consisted of 152 participants, and this included subsamples of 77 persons with MS and 77 age, height, weight, and gender matched controls. This sample size was based on an a priori power analysis for detecting a moderate effect size (Cohen's d = 0.50) with assumptions of one-tailed α = 0.05, β = 0.10 (i.e., 90% power), and group allocation ratio of 1:1. Measures Physical activity was measured using two self-reported questionnaires, namely the Godin Leisure-Time Exercise Questionnaire (GLTEQ; 18) and abbreviated International Physical Activity Questionnaire (IPAQ; 19). The GLTEQ measures the frequency of strenuous (e.g., jogging), moderate (e.g., fast walking), and mild (e.g., easy walking) physical activity for periods of more than 15 min during one's free time in a typical week. The frequencies of strenuous, moderate, and mild activities were multiplied by 9, 5, and 3 metabolic equivalents (METs), respectively, and then summed into a measure of total physical activity. The abbreviated of the IPAQ measures the frequency and duration of vigorous, moderate, and walking physical activity during a 7-day period. The respective frequencies and durations for vigorous, moderate, and walking were initially multiplied, and those resulting volumes were then multiplied by 8, 4, and 3.3 METs, respectively. This too results in a measure of overall physical activity. The GLTEQ and IPAQ have been validated in the general population of adults 18, 19 and persons with MS 16, 17, 20, 21. Physical activity was further measured using the ActiGraph model 7164 accelerometer (Health One Technologies, Fort Walton Beach, FL, USA). This accelerometer is small (5.1 × 4.1 × 1.5 cm) and light weight (43 g) and contains a piezoelectric bender element on a cantilevered arm that generates an electrical signal proportional to the force acting on it. Acceleration detection ranges in magnitude between 0.05 and 3.2 Gs, and the frequency ranges between 0.25 and 2.5 Hz. Motion outside normal human movements is rejected by a band-pass filter. The acceleration signal is digitized by an 8-bit analog-to-digital converter at a rate of 10 Hz and numerically integrated over a pre-programmed epoch interval; the epoch was 60 s in this study. The integrated value is stored in random access memory and the integrator is reset at the end of each interval. The data were retrieved from the accelerometer via a personal computer and reader interface unit and then imported into Meter Plus software for validity check (i.e., number of valid days and hours per day) and then processing of total activity counts, total step counts, and time (minutes) spent in moderate-to-vigorous physical activity (MVPA) per day. Importantly, we used MS and control group specific accelerometer cut-points of 1723 and 2017 counts per minute, respectively, for quantifying time spent in MVPA per day 22. The ActiGraph accelerometers were calibrated before, during, and after the study for meeting the manufacturer's standard of 5% of the reference value, and there is consensus evidence that accelerometers provide a valid and reliable measure of physical activity in MS 9, 15 and healthy adults 23. Protocol The protocol for this study was approved by a University Institutional Review Board. All participants provided appropriately obtained written informed consent, and then completed a demographic questionnaire. Those with MS further completed the Patient Determined Disease Steps (PDDS) scale 24 and the Multiple Sclerosis Walking Scale-12 (MSWS-12; 25). Those measures provided a description of the disability and mobility status of the sample with MS. Participants with MS further provided information regarding clinical disease course and date of diagnosis. The participants were next measured for height and weight using a scale stadiometer (Detecto model 3P7044, Webb City, MO, USA). The participants then received instructions on how to properly wear the accelerometer (i.e., worn on an elastic belt around the waist and centered on the non-dominant hip during the waking hours of the day, except while swimming, bathing, or showering, across a 7-day period) and were provided with a log to record the time spent wearing the unit over the 7-day period. Then participants received instructions on completing the GLTEQ and IPAQ after wearing the accelerometer; this directly corresponded to the period of wearing the accelerometer. The study materials were returned either in person or through the U.S. postal service using preaddressed and stamped envelopes. Participants were paid $30 upon returning the study materials. Data analysis The data were analyzed using IBM SPSS Statistics (SPSS Inc., Chicago, IL, USA), Version 19. The descriptive statistics are presented as mean ± standard deviation for continuous variables, and median along with the range of scores for ordinal variables. We initially performed independent samples t-tests for establishing the equivalence of the groups (MS vs matched controls) on age, height, and weight; an analysis was not undertaken on gender as the sample was perfectly matched on this variable. We then performed independent samples t-test for comparing differences in mean scores between groups on the five measures of physical activity (i.e., GLTEQ and IPAQ scores and overall accelerometer activity counts, step counts, and time spent in MVPA per day). The magnitude of group differences in physical activity between groups was expressed as Cohen's d (i.e., difference in mean scores between groups divided by the pooled standard deviation; 26). Values for Cohen's d of 0.2, 0.5, and 0.8 were interpreted as small, moderate, and large, respectively 26. We lastly provide bivariate correlations among scores from the five measures of physical activity using Pearson product-moment correlation coefficients for the overall sample, persons with MS, and matched controls as an indication of score validity in the present samples. Results Group equivalence The descriptive statistics for the persons with MS and matched controls are presented in Table 1. There were no statistically significant differences in age (t = 0.19, P = 0.85), height (t = −0.34, P = 0.74), or weight (t = 0.23, P = 0.82) between the groups, and the groups had an identical distribution of gender (66 females and 11 males). The sample of persons with MS further had minimal disability based on median PDDS scores and mean MSWS-12 scores. The majority of persons with MS had a relapsing-remitting clinical course and had been diagnosed for a relatively short period of time. Table 1. Descriptive and clinical characteristics of the sample with multiple sclerosis and the matched controls Variable Sample Multiple sclerosis (n = 77) Matched controls (n = 77) Age (year) 47.3 (9.7) 47.0 (10.5) Height (cm) 167.3 (9.1) 167.8 (8.9) Weight (kg) 75.2 (19.7) 74.6 (16.6) Sex (n,% female) 66, 85% 66, 85% Patient Determined Disease Steps score (mdn, range) 1 (0–6) Multiple Sclerosis Walking Scale-12 score 301.0 (27.5) Clinical course (n,% RRMS) 66, 86% MS Duration (years since diagnosis) 10.1 (7.3) Values represent mean (standard deviation), unless otherwise noted per variable. We further compared the equivalence of the groups for number of valid days and valid hours of accelerometer wear time. There were no significant differences for the numbers of valid days (t = −0.12, P = 0.90) and hours of wear time (t = −1.38, P = 0.16). Group differences in physical activity The descriptive statistics for the five measures of physical activity for the persons with MS and matched controls are provided in Table 2. There were statistically significant differences between groups in accelerometer activity counts (t = −3.87, P = 0.0001), accelerometer step counts (t = −4.29, P = 0.0001), and time spent in MVPA based on cut-points for accelerometer counts per minute (t = −2.39, P = 0.01); those differences were unaffected in an additional analysis of covariance that controlled for valid hours of wear time. There further were significant differences in GLTEQ (t = −3.83, P = 0.0001) and IPAQ (t = −3.42, P = 0.0001) scores between persons with MS and matched controls. The effect sizes ranged between −0.40 and −0.71 and, when averaged (d = −0.59), indicated that persons with MS overall were moderately less physically active than the matched controls. Table 2. Mean scores along with P-value and effect size for group differences on the five measures of physical activity for the sample with multiple sclerosis and the matched controls Measures Sample Multiple Sclerosis (n = 77) Matched Controls (n = 77) P-value Cohen's d Accelerometer activity counts (counts/day) 205,641 (122,313) 301,917 (169,654) 0.0001 0.66 Accelerometer step counts (steps/day) 7,698 (3,403) 10,252 (3,789) 0.0001 0.71 Accelerometer MVPA (min/day) 23.5 (25.1) 33.8 (26.2) 0.01 0.40 GLTEQ 29.1 (25.2) 45.3 (26.8) 0.0001 0.62 IPAQ 30.8 (22.4) 44.1 (24.9) 0.0005 0.56 Values represent mean (standard deviation) per measure of physical activity. MVPA, moderate-to-vigorous physical activity; GLTEQ, Godin Leisure-Time Exercise Questionnaire; IPAQ, International Physical Activity Questionnaire. Associations among measures of physical activity The bivariate correlations among scores for the five measures of physical activity for the overall sample and subsamples with MS and matched controls are provided in Table 3. The correlations were generally strong in magnitude based on Cohen's guidelines of 0.1, 0.3, and 0.5 as small, moderate, and large, respectively 26. Table 3. Correlations among scores from the five measures of physical activity in the overall sample, sample with multiple sclerosis, and the matched controls Measure 1 2 3 4 5 Overall sample 1. Accelerometer activity counts (counts/day) ― 2. Accelerometer step counts (steps/day) 0.87 ― 3. Accelerometer MVPA (min/day) 0.90 0.84 ― 4. GLTEQ 0.60 0.50 0.60 ― 5. IPAQ 0.53 0.51 0.50 0.75 ― Multiple sclerosis 1. Accelerometer activity counts (counts/day) ― 2. Accelerometer step counts (steps/day) 0.93 ― 3. Accelerometer MVPA (min/day) 0.93 0.87 ― 4. GLTEQ 0.60 0.51 0.55 ― 5. IPAQ 0.56 0.52 0.50 0.69 ― Matched controls 1. Accelerometer activity counts (counts/day) ― 2. Accelerometer step counts (steps/day) 0.82 ― 3. Accelerometer MVPA (min/day) 0.89 0.81 ― 4. GLTEQ 0.56 0.40 0.62 ― 5. IPAQ 0.46 0.43 0.46 0.77 ― MVPA, moderate-to-vigorous physical activity; GLTEQ, Godin Leisure-Time Exercise Questionnaire; IPAQ, International Physical Activity Questionnaire. Discussion There is increasing recognition that physical activity has beneficial effects on mobility and quality of life (QOL) outcomes in persons with MS who have minimal disability 5-8, but there is some inaccuracy regarding the degree of physical inactivity in this population 6. This uncertainty presents a challenge for understanding if persons with MS are engaging in sufficient amounts of physical activity for accruing the benefits of free-living physical activity and preventing secondary conditions 12 that can increase the rate of disease progression 13. To that end, this study examined free-living physical activity in a large sample of persons with MS who had minimal disability and controls who were matched on age, height, weight, and gender using validated self-report and objective measures. The most important finding was that all five measures captured statistically significant differences in free-living physical activity between persons with MS and controls, yielding an average effect size across measures of −0.59 standard deviations. Overall, this effect size indicated that persons with MS were moderately less physically active than the matched controls. The magnitude of this overall difference in physical activity is substantially and significantly smaller than the effect size of −0.96 standard deviations previously reported in a meta-analysis 9. The smaller overall difference in physical activity reported in the present study might reflect the inclusion of valid measures that do not confound the measurement of free-living physical activity with mobility impairment or physical disability, given the population under study. This might further reflect a large sample size yielding a more precise estimate or matching of the control sample on demographic and anthropometric factors that could account for variability in physical activity. Another possibility is that the emerging emphasis and awareness of health behaviors, particularly exercise, over the past decade in persons with MS 5-8 might have narrowed the previously reported disparity in physical activity by encouraging increased participation in the behavior itself. Collectively, the results indicate a better picture of physical activity in persons with MS who have minimal disability than previously reported. However, the results do still indicate that there is sufficient inactivity, thereby reducing the likelihood of mobility and QOL benefits and increasing the risks of secondary conditions. This new picture of physical activity in persons with MS who have minimal disability is particularly promising, as recent behavioral interventions delivered through the Internet have reported increasing physical activity by 0.51 27 and 0.72 28 standard deviations in minimally disabled persons with MS. This magnitude of effect would likely narrow the gap in physical activity levels between persons with MS and the general population and perhaps result in meaningful outcomes for mobility, QOL, and secondary conditions. Such behavioral interventions, therefore, represent an opportunity for meaningfully impacting the lives of persons with MS. This study documented that the degree of physical inactivity among persons with MS who have minimal disability is less than previously reported in the literature 10, but the level of inactivity is still of concern considering the well-documented lack of physical activity among the general population 29. Indeed, among adults in the general population, physical inactivity is highly prevalent and associated with increased risks of cardiovascular disease (CVD), type II diabetes, and obesity 30. These co-morbidities are similarly prevalent in persons with MS 13 and recent evidence indicates that physical inactivity is associated with a higher number of CVD signs and symptoms in persons with MS 12. On the other hand, physical activity has been linked with QOL, functionality, and symptom management in persons with MS 5-8. Collectively, this underscores the importance of further examining modifiable variables that correlate with physical activity for developing and designing behavioral interventions for increasing physical activity participation in this population. The continued search for modifiable correlates such as prevalent symptoms of MS (e.g., fatigue, depression, and pain; 31) and social-cognitive variables (e.g., self-efficacy; 32-36) will yield better targeted programs for increasing physical activity 9, 10 and improving health and wellness in the context of living with MS. Ultimately, such programs might represent a compliment for current disease modifying therapies that effectively slow the rate of disease progression, but without effectively improving walking function and QOL. Beyond comparing physical activity levels, we further examined the magnitude of associations among the five measures of physical activity in the overall sample and subsamples for verifying the validity of scores in the context of the present study. This has not been done to date 9. Importantly, there were consistent, large correlations among scores from all five measures of physical activity in the overall sample and the subsamples with MS and matched controls. The magnitude and pattern of correlations are consistent across the subsamples with and without MS and further with previous research 16, 17, 21. This pattern of results is important because it supports the interpretation of scores from all five measures as providing a measure of physical activity and thus strengthens the interpretability of differences in physical activity between persons with MS and matched controls in the present study. This further supports the generalizability of the measures of physical activity in persons with MS and the general population, and perhaps opens the door for applications in other neurological conditions. There are many strengths of the current study including large sample size, inclusion of controls matched on age, height, weight, and gender, and use of validated measures of physical activity. This study is not without limitations. The inclusion of an ActiGraph model 7164 accelerometer for measuring physical activity presents some limitations. This device is a single axis accelerometer that may not have the capacity to measure physical activity without major vertical displacement of the center of mass (e.g., cycling). This device further is not water proof and does not capture aquatic activities (e.g., water aerobics or swimming) that can be common forms of physical activity in persons with MS 37. The use of self-report measures of physical activity, particularly in persons with MS, might present a possible limitation, as cognitive impairment is highly prevalent, disabling, and poorly managed in persons with MS 38. We do note that published data indicate that GLTEQ scores were not associated with a clinical measure of cognitive status provided by the Mini-Mental Status Examination in persons with MS 17. Lastly, the sample of persons with MS in this study may not be representative of persons with MS in general. Our sample was primarily female (85%), with a disproportionately larger ratio of females than males compared with the overall gender bias of the disease (i.e., females are 2–3 times more likely than males to have MS; 39). In addition, the sample of persons with MS in this study were highly ambulatory, based on scores from the PDDS, MSWS-12, and use of an assistive device, such that the magnitude of the difference in physical activity between persons with MS and the general population might be larger in samples with mobility disability. Another limitation is that we matched persons with MS and controls based on age, gender, height, and weight, but not gait or walking impairment. Future researchers should consider matching persons with MS and controls by age, gender, height, and weight as well as gait impairment when examining differences between groups in physical activity behavior. Finally, this study was advertised as an examination of physical activity metrics to both persons with MS and controls, and there might have been an upward bias of physical activity behavior in the overall combined sample. However, as both samples were exposed to the study in a similar fashion, the relationships between groups would presumably be unaffected by this potential limitation. Nevertheless, even though persons with MS and controls were presented with similar selection criteria, the samples and self-report and objectively measured physical activity data might have differed based on preconceived notions toward physical activity behavior and other possible selection biases. Conclusions This study examined differences in physical activity using validated measures in a large sample of persons with MS who had minimal disability and controls matched on age, height, weight, and gender. The primary finding was that all five measures captured statistically significant differences in free-living physical activity between persons with MS who had minimal disability and matched controls with an average effect size across measures of −0.59 standard deviations. Overall, this effect size indicated that persons with MS were moderately less physically active than the matched controls, but the magnitude of this difference in physical activity is substantially and significantly smaller than the effect size of −0.96 standard deviations previously reported in a meta-analysis 10. This confirmation of physical inactivity in persons with MS provides further evidence for the importance of developing both supervised and unsupervised interventions for increasing physical activity as a behavioral approach for managing the many consequences of MS and preventing secondary conditions that can affect the rate of disease progression. This represents a critical next step in symptom management and rehabilitation in MS. Acknowledgements We would like to acknowledge Jenna Lungaro, Katie Stover, Anna Hoban, Jason Silberman, and Jennifer Medler for their assistance in data acquisition. Conflict of Interest and Sources of Funding Statement Mr. Sandroff, Ms. Dlugonski, Ms. Weikert, Ms. Suh, Ms. Balantrapu, and Dr. Motl report no conflicts of interest. Furthermore, this study was supported, in part, by a grant from the Foundation of the Consortium of MS Centers. References 1Trapp BD, Nave K. Multiple sclerosis: an immune or neurodegenerative disorder? Annu Rev Neurosci 2008; 31: 247– 69. CrossrefCASPubMedWeb of Science®Google Scholar 2Mayr WT, Pittock SJ, McClelland RL, Jorgensen NW, Noseworthy JH, Rodriguez M. Incidence and prevalence of multiple sclerosis in Olmstead County, Minnesota, 1985–2000. Neurology 2003; 61: 1373– 7. CrossrefCASPubMedWeb of Science®Google Scholar 3Wallin MT, Page WF, Kurtzke JF. Epidemiology of multiple sclerosis in US veterans VIII. Long term survival after onset of multiple sclerosis. Brain 2000; 123: 1677– 87. CrossrefPubMedWeb of Science®Google Scholar 4Hauser SL, Oksenberg JR. 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Publication Year: 2012
Publication Date: 2012-01-03
Language: en
Type: article
Indexed In: ['crossref', 'pubmed']
Access and Citation
Cited By Count: 152
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