Obesity is a growing public health concern world-wide. At the same time, knee and hip replacements are becoming an increasingly regular treatment for osteoarthritis. There are conflicting reports in the literature as to what extent body mass affects the length of stay (LOS) of patients undergoing total hip replacements. This chart review aims at examining the ­relationship between body mass index (BMI), demographic and health-related variables, and LOS. The retrospective chart review of one acute inpatient rehabilitation facility involved n = 119 patients. There was no significant association between LOS and body mass index (BMI), confirming earlier results. Insurance payer type (Medicare vs private) was statistically significant related to LOS. Moreover, there was a trend for the potential influence of race/ethnic patient background on LOS with Caucasians having shorter hospital stays. © 2010 Greenberg and Kroll, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited.</p

Greenberg, K.

Kroll, T.

Clinical Audit

English

Discovery Research Portal

                                                              University of DundeeThe relation of body mass index, demographic and health-related variables to length ofstay for patients at an acute rehabilitation hospital after total hip arthroplastyGreenberg, K.; Kroll, ThiloPublished in:Clinical AuditDOI:10.2147/CA.S6995Publication date:2010Document VersionPublisher's PDF, also known as Version of recordLink to publication in Discovery Research PortalCitation for published version (APA):Greenberg, K., & Kroll, T. (2010). The relation of body mass index, demographic and health-related variables tolength of stay for patients at an acute rehabilitation hospital after total hip arthroplasty. Clinical Audit, 2, 45-48.10.2147/CA.S6995General rightsCopyright and moral rights for the publications made accessible in Discovery Research Portal are retained by the authors and/or othercopyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated withthese rights. • Users may download and print one copy of any publication from Discovery Research Portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain. • You may freely distribute the URL identifying the publication in the public portal.Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.© 2010 Greenberg and Kroll, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited.Clinical Audit 2010:2 45–48Clinical Audit Dovepresssubmit your manuscript | www.dovepress.comDovepress 45 S h O rT  r e P O rTopen access to scientific and medical researchOpen Access Full Text Article6995The relation of body mass index, demographic and health-related variables to length of stay  for patients at an acute rehabilitation hospital after total hip arthroplastyKarin Greenberg1 Thilo Kroll21Medical rehabilitation, Inc, Pittsburgh, PA, USA; 2National rehabilitation hospital (Nrh), Washington DC, WA, USACorrespondence: Thilo Kroll School of Nursing and Midwifery, University of Dundee, 11 Airlie Place, Dundee DD1 4hJ, Scotland, UK Tel +44 (0) 1382 388 655 Fax email t.kroll@dundee.ac.ukAbstract: Obesity is a growing public health concern world-wide. At the same time, knee and hip replacements are becoming an increasingly regular treatment for osteoarthritis. There are conflicting reports in the literature as to what extent body mass affects the length of stay (LOS) of patients undergoing total hip replacements. This chart review aims at examining the  relationship between body mass index (BMI), demographic and health-related variables, and LOS. The retrospective chart review of one acute inpatient rehabilitation facility involved n = 119 patients. There was no significant association between LOS and body mass index (BMI), confirming earlier results. Insurance payer type (Medicare vs private) was statistically significant related to LOS. Moreover, there was a trend for the potential influence of race/ethnic patient background on LOS with Caucasians having shorter hospital stays.Keywords: total hip arthroplasty, obesity, rehabilitation, length of stay, body mass indexIntroductionObesity is a public health crisis both in the United States,1,2 Europe,3 and increasingly in the developing world.4 The cost of obesity management in the United States alone amounts to approximately $100 billion annually, of which approximately $52 billion are from the direct costs of health care. Approximately, 127 million adults in the United States are overweight (64.5%), 60 million obese, and 9 million severely obese.2 In 2004, 234,000 total hip replacements or arthroplasties (THAs) and 478,000 total knee arthroplasties (TKAs) were performed in the United States.5 A significant association of LOS and body mass was found in a Swedish study that examined various lifestyle factors in their contribution to systemic complications and resultant increases in LOS after total hip replacement.6 Other recent studies concluded that functional gains in inpatient rehabilitation after THA may not be affected by body mass, but confirmed increased excess costs related to obese patients.7,8 This audit examines whether patients who are overweight or obese have longer LOS in acute inpatient rehabilitation after THA compared to patients with normal or low weight, and what additional clinical or demographic variables may predict LOS.AimThe aim of the chart review was to determine the relationship between LOS and body mass, health-related variables, and demographic variables for individuals hospitalized in an acute rehabilitation hospital after THA.Clinical Audit 2010:2submit your manuscript | www.dovepress.comDovepress Dovepress46Greenberg and KrollMethodDesignA retrospective chart review of acute inpatient rehabilitation data was carried out by the lead author of this article, who is a rehabilitation medicine specialist in orthopedics.SamplingCharts were reviewed for 244 adults, aged 18 and above, who were consecutively admitted and treated at a major rehabilitation hospital on the United States East Coast with a diagnosis of THA due to fractures, arthritis, or tumors between September 1, 2002 and February 28, 2004. This start date was chosen because that was when the Registered Dietitians at the hospital began recording BMI for all inpa-tients. We excluded individuals from the review when they met one of the following exclusion criteria:•	 If primary diagnosis was not THA•	 Individuals younger than 18 years•	 Individuals with an emergent discharge•	 Individuals discharged without a treatment plan (admin-istrative discharge; discharge to another hospital).Data collection and procedureAll data were extracted using a standardized data extraction form and subsequently entered into spreadsheets. The review tool has been used in the hospital on other occasions, but has so far not been validated. The charts were then reviewed and informa-tion was collected regarding age, gender, race/ethnicity, weight, height, diagnosis,  co-morbidities, LOS, source of payment, and discharge disposition.  Personal identifiers were removed. BMI was calculated using the equation BMI = weight [kg]/height [m2] based on  discharge assessments. The BMI is arguably the most  clinically  practical measure of obesity.9 Patients were classi-fied according to the criteria the World Health Organization10 had endorsed for adults. A BMI between 18.5–24.9 kg/m2 is considered  normal. A BMI below 18.5 kg/m2 is considered  underweight, a BMI between 25.0–29.9 kg/m2 is considered overweight, and a BMI above 30.0 kg/m2 is considered obese. Severe, morbid, or extreme obesity is $40 kg/m2.All data were then reviewed and the accuracy of data entry was checked by comparing all case data records with the spreadsheets before final data analysis. Independent variables included age, gender, race, health insurance type, number of co-morbid conditions, number of days between THA surgery and discharge from rehabilitation, discharge to home/other, and BMI. The dependent variable was LOS.Due to small numbers in the various categories of the  variables ‘body weight’ (eg, underweight, normal range, marginally overweight, overweight, very overweight), race/ethnicity (eg, Caucasian, African American, Asian  American, Hispanic American, Other) and discharge  disposition (eg, home, nursing facility, subacute facility, acute care  hospital) categories were merged prior to  cross-tabulation analyses to obtain meaningful analysis units. The recoded vari-ables consisted of the categories underweight/normal, over-weight, and obesity for ‘weight,’ Caucasian vs non-Caucasian for ‘race/ethnicity,’ and home vs other for ‘ discharge disposi-tion’. For continuous variables, the median-split method was used to produce dichotomous categories.Statistical analysisStatistical analyses were performed using the statistical software package SPSS 12.0 (SPSS Inc, Chicago, IL).  Frequencies were computed for study variables. Continuous variables were dichotomized and converted into categorical variables using the median split. Further, bivariate analyses were conducted to determine the association among BMI, demographic variables, and LOS. In these analyses, Phi (2 × 2 tables) and Cramer’s V (tables larger than 2 × 2) were calculated. The significance of differences between the two groups for LOS was determined with the Phi/Cramer’s V test. The significance level alpha was set at P , 0.05 ( two-sided). Logistic regression analysis using the enter method was computed for LOS as the dependent variable. This means that all significant independent variables based on the bivariate analysis were entered in the equation at once.ResultsSample characteristicsThe final sample size consisted of n = 119 individuals with a primary diagnosis of THA. In total, 125 individuals were excluded from the analysis. There were 83 (69.7%) women and 36 (30.3%) men. The median age was 68 years (min 22; max 90 years). The median length of stay was 10 days (min 2; max 25). The median split for LOS was used to divide individuals who stayed 0–9 and those who stayed 10 or more days in inpatient rehabilitation (Table 1).relationship between LOS and BMIThe bivariate cross-tabulation analysis shows that there was no significant association between length of stay and BMI after THA (Table 1). Interestingly, the proportion of patients in the obesity category and those with normal weight, includ-ing being underweight with a LOS of 10 days, was larger than those found for patients who were categorized as being overweight.Clinical Audit 2010:2 submit your manuscript | www.dovepress.comDovepress Dovepress47 Total hip arthroplasty, obesity and length of stay in rehabilitationrelationship between LOS and demographic and health-related variablesSimilarly, age, gender, number of co-morbid conditions, number of days between surgery date and discharge from rehabilitation, and discharge disposition (home vs other) were not associated with the LOS. Statistically significant bivariate associations for LOS were found for insurance payer type and race (Table 1). Patients receiving Medicare or Medicaid had significant longer rehabilitation stays than those with private insurance. A significantly larger propor-tion of patients receiving Medicare had a LOS of 10 days or more compared to Medicaid or privately insured patients. While nearly three-quarters of the non-Caucasian patients had a LOS of 10 days or more, only a quarter of Caucasians stayed for this duration.Logistic regression analysis showed that the odds of  having a stay of 10 days or more in acute inpatient  rehabilitation are more than five times of those insured through Medicare compared to those with private health insurance coverage (odds ratio (OR) = 5.854, confidence interval (CI): 2.018–16.982, P = .001) and more than three times higher for patients covered by Medicaid compared to private insurance (OR = 3.616, CI: 0.919–14.234, P = 0.066). Moreover, the odds of spending more than 10 days for patients who are of Caucasian background are half of those found for patients of non-Caucasian background (OR = 0.451, CI: 0.188–1.092, P = 0.078). The only statistically significant regression was found for Medicare vs private coverage.ConclusionThere was no significant association between LOS and BMI after THA. This confirms earlier findings by Jiganti et al,11 who also found no significant difference in the LOS between non-obese and obese THA patients. However, in a recent study that involved 15 United States’ hospital researchers found that LOS was 0.8–1.3 days longer in the non-obese group compared with other weight groups (P # 0.05). Hospital expenditures were significantly higher for the severely obese patients in that study.7 Previously, the same study group found a curvilinear relationship between LOS and BMI and higher total hospital charges for severely obese patients undergoing total hip arthroplasty.12 The latter finding is, however, drawn Table 1 Bivariate relationship between LOS and demographic and clinical correlates0–9 days (n = 48) $10days (n = 71) Phi/Cramer’s V PAge 0.171 0.06218–68 30 (62.5%) 32 (45.1%)69–99 18 (37.5%) 39 (54.9%)Gender -0.018 0.846Female 33 (68.8%) 50 (70.4%)Male 15 (31.2%) 21 (29.6%)race/ethnicity 0.197 0.032*Caucasian 22 (45.8%) 19 (26.8%)Non-Caucasian 26 (54.2%) 52 (73.2%)health insurance 0.336 0.001**Medicare 24 (50.0%) 52 (73.2%)Medicaid 7 (14.6%) 13 (18.3%)Private 17 (35.4%) 6 (8.5%)BMI 0.073 0.725Underweight/normal 15 (31.3%) 24 (33.8%)Overweight 12 (25.0%) 21 (29.6%)Obese 21 (43.8%) 26 (36.6%)Number of comorbid conditions0.027 0.7690–5 27 (56.3%) 38 (53.5%)6# 21 (43.8%) 33 (46.5%)Number of days between surgery  date and discharge from rehab0.079 0.4020–4 36 (78.3%) 47 (71.2%)5# 10 (21.7%) 19 (28.8%)Discharge disposition 0.003 0.977home 42 (87.5%) 62 (87.3%)Other 6 (12.5%) 9 (12.7%)Notes: *P , 0.05, **P , 0.01.Clinical AuditPublish your work in this journalSubmit your manuscript here: http://www.dovepress.com/clinical-audit-journalClinical Audit is an international, peer-reviewed, open access journal focusing on the processes and outcomes of clinical audit in any area of healthcare. All aspects of patient care are addressed within the journal and practitioners from all disciplines are invited to submit their work. Areas covered include: Publication of audits; How an audit has changed practice; Practical tips on how to do audits and to avoid pitfalls; How audits have changed patient care; Calls and justifications for new audits. The manuscript management system is completely online and includes a very quick and fair peer-review system, which is all easy to use. Visit http://www.dovepress.com/testimonials.php to read real quotes from published authors.Clinical Audit 2010:2submit your manuscript | www.dovepress.comDovepress DovepressDovepress48Greenberg and Krollinto question by findings that did not suggest an overall higher resource utilization of patients who are obese and who are undergoing elective THA.13 Our study did not find a relation-ship between age or gender and LOS, however, functional outcomes may well differ for men and women and different age groups, as a recent study showed.14 Nor did we identify any significant differences for LOS in terms of number of co-morbid conditions. This finding is inconsistent with what was found in a Canadian study where LOS was clearly asso-ciated with age and co-morbid conditions.15 Others found clear evidence for increased hospital expenditures linked to co-morbid conditions in patients undergoing THA.16 Insurance type, however, appears to influence the LOS after THA. To date there is little information from other United States’ stud-ies comparing Medicare recipients with other insurance types with regard to LOS. A large recent retrospective cohort study could show that Hispanic Americans had significantly longer LOS after THA than Caucasian Americans.17 In our review, there was a trend towards significance for race/ethnicity as a predictor of LOS.The audit that was restricted to one clinical site only which presents several study limitations. Findings are not general-izable to other inpatient rehabilitation facilities. The LOS is continuously decreasing. Our study data were extracted during a very specific time only. The sample size is rather small, which did not allow for more sophisticated analysis (ie, comparisons among first time THA patients and revision surgery; different types of insurance plans, ie, fee-for-service vs managed care). Other critical variables, such as dietary habits and exercise behavior, could not be included as this data was not available as part of the hospital records. It is especially crucial to examine how insurance type may affect the rehabilitation opportunities available to individuals and related outcomes. It would be necessary to replicate findings with larger data sets and track changes over time. Larger study samples would allow for more complex statistical analyses and examination of multiple variables at once. These analy-ses are needed to determine the independent contribution of demographic, health-related, and health service variables to LOS after THA.DisclosureThe authors report no conflicts of interest in this work.References 1. Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA. 2006;295(13): 1549–1555. 2. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999–2000. JAMA. 2002;288(14): 1723–1727. 3. Berghofer A, Pischon T, Reinhold T, Apovian CM, Sharma AM, Willich SN. Obesity prevalence from a European perspective: a sys-tematic review. BMC Public Health. 2008;8:200. 4. Hossein P, Kawar B, El Nahas M. Obesity and diabetes in the developing world – a growing challenge. New Engl J Med. 2007;356(3):213–215. 5. Rasul AT, Wright J. Total joint replacement rehabilitation. 2010 Jan 20. Available from: http://emedicine.medscape.com/article/320061-overview. Accessed March 22, 2010. 6. Azodi Sadr O, Belloco R, Eriksson K, Adami J. The impact of tobacco use and body mass index on length of stay in hospital and the risk of post-operative complications among patients undergoing total hip replacement. J Bone Joint Surg. 2006;88(10):1316–1320. 7. Vincent HK, DeJong G, Mascarenas D, Vincent KR. The effect of body mass index and hip abductor brace use on inpatient rehabilita-tion outcomes after total hip arthroplasty. Am J Physical Med Rehabil. 2009;88(3):201–209. 8. Kessler S, Käfer W. Overweight and obesity: two predictors for worse early outcome in total hip replacement. Obesity. 2007;15(11):2840–2845. 9. Gelber RP, Gaziano JM, Orav EJ, Manson JE, Buring JE, Kurth T. Measures of obesity and cardiovascular risk among men and women. J Am Coll Cardiol. 2008;52(8):605–615. 10. World Health Organization (WHO). Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation. Geneva: World Health Organization; 1997. 11. Jiganti JJ, Goldstein WN, Williams CS. A comparison of the periop-erative morbidity in total joint arthroplasty in the obese and nonobese patient. Clin Orthop Relat Res. 1993;289:175–179. 12. Vincent HK, Weng JP, Vincent KR. Effect of obesity on inpatient rehabilita-tion outcomes after total hip arthroplasty. Obesity. 2007;15(2):522–530. 13. Batsis JA, Naessens JM, Keegan MT, Wagie AE, Huddleston PM, Huddleston JM. Impact of body mass on hospital resource use in total hip arthroplasty. Public Health Nutr. 2009;12(8):1122–1132. 14. Santaguida PL, Hawker GA, Hudak PL, et al. Patient characteristics affecting the prognosis of total hip and knee joint arthroplasty: a sys-tematic review. Can J Surg. 2008;51(6):428–436. 15. MacKenzie TA, Hopman WM, Mantle M. Factors influencing length of stay and health status in total hip replacement patients. Abstr Book Assoc Health Serv Res Meet. 1997;14:186–187. 16. Shah AN, Vail TP, Taylor D, Pietrobon R. Comorbid illness affects hospital costs related to hip arthroplasty. J Arthroplasty. 2004;19(6):700–705. 17. Bergés IM, Yong-Fang K, Ostir GV, Granger CV, Graham JE, Ottenbacher KJ. Gender and ethnic differences in rehabilitation outcomes after hip-replacement surgery. Am J Phys Med Rehabil. 2008;87(7):567–572.

A comparison of the perioperative morbidity in total joint arthroplasty in the obese and nonobese patient. Clin Orthop Relat Res.

Comorbid illness affects hospital costs related to hip arthroplasty.

Effect of obesity on inpatient rehabilitation outcomes after total hip arthroplasty.

Factors influencing length of stay and health status in total hip replacement patients. Abstr Book Assoc Health Serv Res Meet.

Gender and ethnic differences in rehabilitation outcomes after hip-replacement surgery.

Impact of body mass on hospital resource use in total hip arthroplasty. Public Health Nutr.

Measures of obesity and cardiovascular risk among men and women.

Obesity and diabetes in the developing world – a growing challenge.

Obesity prevalence from a European perspective: a systematic review. BMC Public Health.

Organization (WHO). Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation. Geneva: World Health Organization;

Overweight and obesity: two predictors for worse early outcome in total hip replacement.

Patient characteristics affecting the prognosis of total hip and knee joint arthroplasty: a systematic review.

The effect of body mass index and hip abductor brace use on inpatient rehabilitation outcomes after total hip arthroplasty.

The impact of tobacco use and body mass index on length of stay in hospital and the risk of post-operative complications among patients undergoing total hip replacement.

Total joint replacement rehabilitation.

The relation of body mass index, demographic and health-related variables to length of stay for patients at an acute rehabilitation hospital after total hip arthroplasty

                                                                    University of DundeeThe relation of body mass index, demographic and health-related variables to length ofstay for patients at an acute rehabilitation hospital after total hip arthroplastyGreenberg, K.; Kroll, T.Published in:Clinical AuditDOI:10.2147/CA.S6995Publication date:2010Document VersionPublisher's PDF, also known as Version of recordLink to publication in Discovery Research PortalCitation for published version (APA):Greenberg, K., & Kroll, T. (2010). The relation of body mass index, demographic and health-related variables tolength of stay for patients at an acute rehabilitation hospital after total hip arthroplasty. Clinical Audit, 2, 45-48.https://doi.org/10.2147/CA.S6995General rightsCopyright and moral rights for the publications made accessible in Discovery Research Portal are retained by the authors and/or othercopyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated withthese rights.Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Download date: 30. Oct. 2025© 2010 Greenberg and Kroll, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited.Clinical Audit 2010:2 45–48Clinical Audit Dovepresssubmit your manuscript | www.dovepress.comDovepress 45 S h O rT  r e P O rTopen access to scientific and medical researchOpen Access Full Text Article6995The relation of body mass index, demographic and health-related variables to length of stay  for patients at an acute rehabilitation hospital after total hip arthroplastyKarin Greenberg1 Thilo Kroll21Medical rehabilitation, Inc, Pittsburgh, PA, USA; 2National rehabilitation hospital (Nrh), Washington DC, WA, USACorrespondence: Thilo Kroll School of Nursing and Midwifery, University of Dundee, 11 Airlie Place, Dundee DD1 4hJ, Scotland, UK Tel +44 (0) 1382 388 655 Fax email t.kroll@dundee.ac.ukAbstract: Obesity is a growing public health concern world-wide. At the same time, knee and hip replacements are becoming an increasingly regular treatment for osteoarthritis. There are conflicting reports in the literature as to what extent body mass affects the length of stay (LOS) of patients undergoing total hip replacements. This chart review aims at examining the  relationship between body mass index (BMI), demographic and health-related variables, and LOS. The retrospective chart review of one acute inpatient rehabilitation facility involved n = 119 patients. There was no significant association between LOS and body mass index (BMI), confirming earlier results. Insurance payer type (Medicare vs private) was statistically significant related to LOS. Moreover, there was a trend for the potential influence of race/ethnic patient background on LOS with Caucasians having shorter hospital stays.Keywords: total hip arthroplasty, obesity, rehabilitation, length of stay, body mass indexIntroductionObesity is a public health crisis both in the United States,1,2 Europe,3 and increasingly in the developing world.4 The cost of obesity management in the United States alone amounts to approximately $100 billion annually, of which approximately $52 billion are from the direct costs of health care. Approximately, 127 million adults in the United States are overweight (64.5%), 60 million obese, and 9 million severely obese.2 In 2004, 234,000 total hip replacements or arthroplasties (THAs) and 478,000 total knee arthroplasties (TKAs) were performed in the United States.5 A significant association of LOS and body mass was found in a Swedish study that examined various lifestyle factors in their contribution to systemic complications and resultant increases in LOS after total hip replacement.6 Other recent studies concluded that functional gains in inpatient rehabilitation after THA may not be affected by body mass, but confirmed increased excess costs related to obese patients.7,8 This audit examines whether patients who are overweight or obese have longer LOS in acute inpatient rehabilitation after THA compared to patients with normal or low weight, and what additional clinical or demographic variables may predict LOS.AimThe aim of the chart review was to determine the relationship between LOS and body mass, health-related variables, and demographic variables for individuals hospitalized in an acute rehabilitation hospital after THA.Clinical Audit 2010:2submit your manuscript | www.dovepress.comDovepress Dovepress46Greenberg and KrollMethodDesignA retrospective chart review of acute inpatient rehabilitation data was carried out by the lead author of this article, who is a rehabilitation medicine specialist in orthopedics.SamplingCharts were reviewed for 244 adults, aged 18 and above, who were consecutively admitted and treated at a major rehabilitation hospital on the United States East Coast with a diagnosis of THA due to fractures, arthritis, or tumors between September 1, 2002 and February 28, 2004. This start date was chosen because that was when the Registered Dietitians at the hospital began recording BMI for all inpa-tients. We excluded individuals from the review when they met one of the following exclusion criteria:•	 If primary diagnosis was not THA•	 Individuals younger than 18 years•	 Individuals with an emergent discharge•	 Individuals discharged without a treatment plan (admin-istrative discharge; discharge to another hospital).Data collection and procedureAll data were extracted using a standardized data extraction form and subsequently entered into spreadsheets. The review tool has been used in the hospital on other occasions, but has so far not been validated. The charts were then reviewed and informa-tion was collected regarding age, gender, race/ethnicity, weight, height, diagnosis,  co-morbidities, LOS, source of payment, and discharge disposition.  Personal identifiers were removed. BMI was calculated using the equation BMI = weight [kg]/height [m2] based on  discharge assessments. The BMI is arguably the most  clinically  practical measure of obesity.9 Patients were classi-fied according to the criteria the World Health Organization10 had endorsed for adults. A BMI between 18.5–24.9 kg/m2 is considered  normal. A BMI below 18.5 kg/m2 is considered  underweight, a BMI between 25.0–29.9 kg/m2 is considered overweight, and a BMI above 30.0 kg/m2 is considered obese. Severe, morbid, or extreme obesity is $40 kg/m2.All data were then reviewed and the accuracy of data entry was checked by comparing all case data records with the spreadsheets before final data analysis. Independent variables included age, gender, race, health insurance type, number of co-morbid conditions, number of days between THA surgery and discharge from rehabilitation, discharge to home/other, and BMI. The dependent variable was LOS.Due to small numbers in the various categories of the  variables ‘body weight’ (eg, underweight, normal range, marginally overweight, overweight, very overweight), race/ethnicity (eg, Caucasian, African American, Asian  American, Hispanic American, Other) and discharge  disposition (eg, home, nursing facility, subacute facility, acute care  hospital) categories were merged prior to  cross-tabulation analyses to obtain meaningful analysis units. The recoded vari-ables consisted of the categories underweight/normal, over-weight, and obesity for ‘weight,’ Caucasian vs non-Caucasian for ‘race/ethnicity,’ and home vs other for ‘ discharge disposi-tion’. For continuous variables, the median-split method was used to produce dichotomous categories.Statistical analysisStatistical analyses were performed using the statistical software package SPSS 12.0 (SPSS Inc, Chicago, IL).  Frequencies were computed for study variables. Continuous variables were dichotomized and converted into categorical variables using the median split. Further, bivariate analyses were conducted to determine the association among BMI, demographic variables, and LOS. In these analyses, Phi (2 × 2 tables) and Cramer’s V (tables larger than 2 × 2) were calculated. The significance of differences between the two groups for LOS was determined with the Phi/Cramer’s V test. The significance level alpha was set at P , 0.05 ( two-sided). Logistic regression analysis using the enter method was computed for LOS as the dependent variable. This means that all significant independent variables based on the bivariate analysis were entered in the equation at once.ResultsSample characteristicsThe final sample size consisted of n = 119 individuals with a primary diagnosis of THA. In total, 125 individuals were excluded from the analysis. There were 83 (69.7%) women and 36 (30.3%) men. The median age was 68 years (min 22; max 90 years). The median length of stay was 10 days (min 2; max 25). The median split for LOS was used to divide individuals who stayed 0–9 and those who stayed 10 or more days in inpatient rehabilitation (Table 1).relationship between LOS and BMIThe bivariate cross-tabulation analysis shows that there was no significant association between length of stay and BMI after THA (Table 1). Interestingly, the proportion of patients in the obesity category and those with normal weight, includ-ing being underweight with a LOS of 10 days, was larger than those found for patients who were categorized as being overweight.Clinical Audit 2010:2 submit your manuscript | www.dovepress.comDovepress Dovepress47 Total hip arthroplasty, obesity and length of stay in rehabilitationrelationship between LOS and demographic and health-related variablesSimilarly, age, gender, number of co-morbid conditions, number of days between surgery date and discharge from rehabilitation, and discharge disposition (home vs other) were not associated with the LOS. Statistically significant bivariate associations for LOS were found for insurance payer type and race (Table 1). Patients receiving Medicare or Medicaid had significant longer rehabilitation stays than those with private insurance. A significantly larger propor-tion of patients receiving Medicare had a LOS of 10 days or more compared to Medicaid or privately insured patients. While nearly three-quarters of the non-Caucasian patients had a LOS of 10 days or more, only a quarter of Caucasians stayed for this duration.Logistic regression analysis showed that the odds of  having a stay of 10 days or more in acute inpatient  rehabilitation are more than five times of those insured through Medicare compared to those with private health insurance coverage (odds ratio (OR) = 5.854, confidence interval (CI): 2.018–16.982, P = .001) and more than three times higher for patients covered by Medicaid compared to private insurance (OR = 3.616, CI: 0.919–14.234, P = 0.066). Moreover, the odds of spending more than 10 days for patients who are of Caucasian background are half of those found for patients of non-Caucasian background (OR = 0.451, CI: 0.188–1.092, P = 0.078). The only statistically significant regression was found for Medicare vs private coverage.ConclusionThere was no significant association between LOS and BMI after THA. This confirms earlier findings by Jiganti et al,11 who also found no significant difference in the LOS between non-obese and obese THA patients. However, in a recent study that involved 15 United States’ hospital researchers found that LOS was 0.8–1.3 days longer in the non-obese group compared with other weight groups (P # 0.05). Hospital expenditures were significantly higher for the severely obese patients in that study.7 Previously, the same study group found a curvilinear relationship between LOS and BMI and higher total hospital charges for severely obese patients undergoing total hip arthroplasty.12 The latter finding is, however, drawn Table 1 Bivariate relationship between LOS and demographic and clinical correlates0–9 days (n = 48) $10days (n = 71) Phi/Cramer’s V PAge 0.171 0.06218–68 30 (62.5%) 32 (45.1%)69–99 18 (37.5%) 39 (54.9%)Gender -0.018 0.846Female 33 (68.8%) 50 (70.4%)Male 15 (31.2%) 21 (29.6%)race/ethnicity 0.197 0.032*Caucasian 22 (45.8%) 19 (26.8%)Non-Caucasian 26 (54.2%) 52 (73.2%)health insurance 0.336 0.001**Medicare 24 (50.0%) 52 (73.2%)Medicaid 7 (14.6%) 13 (18.3%)Private 17 (35.4%) 6 (8.5%)BMI 0.073 0.725Underweight/normal 15 (31.3%) 24 (33.8%)Overweight 12 (25.0%) 21 (29.6%)Obese 21 (43.8%) 26 (36.6%)Number of comorbid conditions0.027 0.7690–5 27 (56.3%) 38 (53.5%)6# 21 (43.8%) 33 (46.5%)Number of days between surgery  date and discharge from rehab0.079 0.4020–4 36 (78.3%) 47 (71.2%)5# 10 (21.7%) 19 (28.8%)Discharge disposition 0.003 0.977home 42 (87.5%) 62 (87.3%)Other 6 (12.5%) 9 (12.7%)Notes: *P , 0.05, **P , 0.01.Clinical AuditPublish your work in this journalSubmit your manuscript here: http://www.dovepress.com/clinical-audit-journalClinical Audit is an international, peer-reviewed, open access journal focusing on the processes and outcomes of clinical audit in any area of healthcare. All aspects of patient care are addressed within the journal and practitioners from all disciplines are invited to submit their work. Areas covered include: Publication of audits; How an audit has changed practice; Practical tips on how to do audits and to avoid pitfalls; How audits have changed patient care; Calls and justifications for new audits. The manuscript management system is completely online and includes a very quick and fair peer-review system, which is all easy to use. Visit http://www.dovepress.com/testimonials.php to read real quotes from published authors.Clinical Audit 2010:2submit your manuscript | www.dovepress.comDovepress DovepressDovepress48Greenberg and Krollinto question by findings that did not suggest an overall higher resource utilization of patients who are obese and who are undergoing elective THA.13 Our study did not find a relation-ship between age or gender and LOS, however, functional outcomes may well differ for men and women and different age groups, as a recent study showed.14 Nor did we identify any significant differences for LOS in terms of number of co-morbid conditions. This finding is inconsistent with what was found in a Canadian study where LOS was clearly asso-ciated with age and co-morbid conditions.15 Others found clear evidence for increased hospital expenditures linked to co-morbid conditions in patients undergoing THA.16 Insurance type, however, appears to influence the LOS after THA. To date there is little information from other United States’ stud-ies comparing Medicare recipients with other insurance types with regard to LOS. A large recent retrospective cohort study could show that Hispanic Americans had significantly longer LOS after THA than Caucasian Americans.17 In our review, there was a trend towards significance for race/ethnicity as a predictor of LOS.The audit that was restricted to one clinical site only which presents several study limitations. Findings are not general-izable to other inpatient rehabilitation facilities. The LOS is continuously decreasing. Our study data were extracted during a very specific time only. The sample size is rather small, which did not allow for more sophisticated analysis (ie, comparisons among first time THA patients and revision surgery; different types of insurance plans, ie, fee-for-service vs managed care). Other critical variables, such as dietary habits and exercise behavior, could not be included as this data was not available as part of the hospital records. It is especially crucial to examine how insurance type may affect the rehabilitation opportunities available to individuals and related outcomes. It would be necessary to replicate findings with larger data sets and track changes over time. Larger study samples would allow for more complex statistical analyses and examination of multiple variables at once. These analy-ses are needed to determine the independent contribution of demographic, health-related, and health service variables to LOS after THA.DisclosureThe authors report no conflicts of interest in this work.References 1. Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA. 2006;295(13): 1549–1555. 2. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999–2000. JAMA. 2002;288(14): 1723–1727. 3. Berghofer A, Pischon T, Reinhold T, Apovian CM, Sharma AM, Willich SN. Obesity prevalence from a European perspective: a sys-tematic review. BMC Public Health. 2008;8:200. 4. Hossein P, Kawar B, El Nahas M. Obesity and diabetes in the developing world – a growing challenge. New Engl J Med. 2007;356(3):213–215. 5. Rasul AT, Wright J. Total joint replacement rehabilitation. 2010 Jan 20. Available from: http://emedicine.medscape.com/article/320061-overview. Accessed March 22, 2010. 6. Azodi Sadr O, Belloco R, Eriksson K, Adami J. The impact of tobacco use and body mass index on length of stay in hospital and the risk of post-operative complications among patients undergoing total hip replacement. J Bone Joint Surg. 2006;88(10):1316–1320. 7. Vincent HK, DeJong G, Mascarenas D, Vincent KR. The effect of body mass index and hip abductor brace use on inpatient rehabilita-tion outcomes after total hip arthroplasty. Am J Physical Med Rehabil. 2009;88(3):201–209. 8. Kessler S, Käfer W. Overweight and obesity: two predictors for worse early outcome in total hip replacement. Obesity. 2007;15(11):2840–2845. 9. Gelber RP, Gaziano JM, Orav EJ, Manson JE, Buring JE, Kurth T. Measures of obesity and cardiovascular risk among men and women. J Am Coll Cardiol. 2008;52(8):605–615. 10. World Health Organization (WHO). Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation. Geneva: World Health Organization; 1997. 11. Jiganti JJ, Goldstein WN, Williams CS. A comparison of the periop-erative morbidity in total joint arthroplasty in the obese and nonobese patient. Clin Orthop Relat Res. 1993;289:175–179. 12. Vincent HK, Weng JP, Vincent KR. Effect of obesity on inpatient rehabilita-tion outcomes after total hip arthroplasty. Obesity. 2007;15(2):522–530. 13. Batsis JA, Naessens JM, Keegan MT, Wagie AE, Huddleston PM, Huddleston JM. Impact of body mass on hospital resource use in total hip arthroplasty. Public Health Nutr. 2009;12(8):1122–1132. 14. Santaguida PL, Hawker GA, Hudak PL, et al. Patient characteristics affecting the prognosis of total hip and knee joint arthroplasty: a sys-tematic review. Can J Surg. 2008;51(6):428–436. 15. MacKenzie TA, Hopman WM, Mantle M. Factors influencing length of stay and health status in total hip replacement patients. Abstr Book Assoc Health Serv Res Meet. 1997;14:186–187. 16. Shah AN, Vail TP, Taylor D, Pietrobon R. Comorbid illness affects hospital costs related to hip arthroplasty. J Arthroplasty. 2004;19(6):700–705. 17. Bergés IM, Yong-Fang K, Ostir GV, Granger CV, Graham JE, Ottenbacher KJ. Gender and ethnic differences in rehabilitation outcomes after hip-replacement surgery. Am J Phys Med Rehabil. 2008;87(7):567–572.

Thilo Kroll

null Greenberg

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                                                                    University of DundeeThe relation of body mass index, demographic and health-related variables to length ofstay for patients at an acute rehabilitation hospital after total hip arthroplastyGreenberg, K.; Kroll, T.Published in:Clinical AuditDOI:10.2147/CA.S6995Publication date:2010Document VersionPublisher's PDF, also known as Version of recordLink to publication in Discovery Research PortalCitation for published version (APA):Greenberg, K., & Kroll, T. (2010). The relation of body mass index, demographic and health-related variables tolength of stay for patients at an acute rehabilitation hospital after total hip arthroplasty. Clinical Audit, 2, 45-48.https://doi.org/10.2147/CA.S6995General rightsCopyright and moral rights for the publications made accessible in Discovery Research Portal are retained by the authors and/or othercopyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated withthese rights. • Users may download and print one copy of any publication from Discovery Research Portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain. • You may freely distribute the URL identifying the publication in the public portal.Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Download date: 29. Oct. 2023© 2010 Greenberg and Kroll, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited.Clinical Audit 2010:2 45–48Clinical Audit Dovepresssubmit your manuscript | www.dovepress.comDovepress 45 S h O rT  r e P O rTopen access to scientific and medical researchOpen Access Full Text Article6995The relation of body mass index, demographic and health-related variables to length of stay  for patients at an acute rehabilitation hospital after total hip arthroplastyKarin Greenberg1 Thilo Kroll21Medical rehabilitation, Inc, Pittsburgh, PA, USA; 2National rehabilitation hospital (Nrh), Washington DC, WA, USACorrespondence: Thilo Kroll School of Nursing and Midwifery, University of Dundee, 11 Airlie Place, Dundee DD1 4hJ, Scotland, UK Tel +44 (0) 1382 388 655 Fax email t.kroll@dundee.ac.ukAbstract: Obesity is a growing public health concern world-wide. At the same time, knee and hip replacements are becoming an increasingly regular treatment for osteoarthritis. There are conflicting reports in the literature as to what extent body mass affects the length of stay (LOS) of patients undergoing total hip replacements. This chart review aims at examining the  relationship between body mass index (BMI), demographic and health-related variables, and LOS. The retrospective chart review of one acute inpatient rehabilitation facility involved n = 119 patients. There was no significant association between LOS and body mass index (BMI), confirming earlier results. Insurance payer type (Medicare vs private) was statistically significant related to LOS. Moreover, there was a trend for the potential influence of race/ethnic patient background on LOS with Caucasians having shorter hospital stays.Keywords: total hip arthroplasty, obesity, rehabilitation, length of stay, body mass indexIntroductionObesity is a public health crisis both in the United States,1,2 Europe,3 and increasingly in the developing world.4 The cost of obesity management in the United States alone amounts to approximately $100 billion annually, of which approximately $52 billion are from the direct costs of health care. Approximately, 127 million adults in the United States are overweight (64.5%), 60 million obese, and 9 million severely obese.2 In 2004, 234,000 total hip replacements or arthroplasties (THAs) and 478,000 total knee arthroplasties (TKAs) were performed in the United States.5 A significant association of LOS and body mass was found in a Swedish study that examined various lifestyle factors in their contribution to systemic complications and resultant increases in LOS after total hip replacement.6 Other recent studies concluded that functional gains in inpatient rehabilitation after THA may not be affected by body mass, but confirmed increased excess costs related to obese patients.7,8 This audit examines whether patients who are overweight or obese have longer LOS in acute inpatient rehabilitation after THA compared to patients with normal or low weight, and what additional clinical or demographic variables may predict LOS.AimThe aim of the chart review was to determine the relationship between LOS and body mass, health-related variables, and demographic variables for individuals hospitalized in an acute rehabilitation hospital after THA.Clinical Audit 2010:2submit your manuscript | www.dovepress.comDovepress Dovepress46Greenberg and KrollMethodDesignA retrospective chart review of acute inpatient rehabilitation data was carried out by the lead author of this article, who is a rehabilitation medicine specialist in orthopedics.SamplingCharts were reviewed for 244 adults, aged 18 and above, who were consecutively admitted and treated at a major rehabilitation hospital on the United States East Coast with a diagnosis of THA due to fractures, arthritis, or tumors between September 1, 2002 and February 28, 2004. This start date was chosen because that was when the Registered Dietitians at the hospital began recording BMI for all inpa-tients. We excluded individuals from the review when they met one of the following exclusion criteria:•	 If primary diagnosis was not THA•	 Individuals younger than 18 years•	 Individuals with an emergent discharge•	 Individuals discharged without a treatment plan (admin-istrative discharge; discharge to another hospital).Data collection and procedureAll data were extracted using a standardized data extraction form and subsequently entered into spreadsheets. The review tool has been used in the hospital on other occasions, but has so far not been validated. The charts were then reviewed and informa-tion was collected regarding age, gender, race/ethnicity, weight, height, diagnosis,  co-morbidities, LOS, source of payment, and discharge disposition.  Personal identifiers were removed. BMI was calculated using the equation BMI = weight [kg]/height [m2] based on  discharge assessments. The BMI is arguably the most  clinically  practical measure of obesity.9 Patients were classi-fied according to the criteria the World Health Organization10 had endorsed for adults. A BMI between 18.5–24.9 kg/m2 is considered  normal. A BMI below 18.5 kg/m2 is considered  underweight, a BMI between 25.0–29.9 kg/m2 is considered overweight, and a BMI above 30.0 kg/m2 is considered obese. Severe, morbid, or extreme obesity is $40 kg/m2.All data were then reviewed and the accuracy of data entry was checked by comparing all case data records with the spreadsheets before final data analysis. Independent variables included age, gender, race, health insurance type, number of co-morbid conditions, number of days between THA surgery and discharge from rehabilitation, discharge to home/other, and BMI. The dependent variable was LOS.Due to small numbers in the various categories of the  variables ‘body weight’ (eg, underweight, normal range, marginally overweight, overweight, very overweight), race/ethnicity (eg, Caucasian, African American, Asian  American, Hispanic American, Other) and discharge  disposition (eg, home, nursing facility, subacute facility, acute care  hospital) categories were merged prior to  cross-tabulation analyses to obtain meaningful analysis units. The recoded vari-ables consisted of the categories underweight/normal, over-weight, and obesity for ‘weight,’ Caucasian vs non-Caucasian for ‘race/ethnicity,’ and home vs other for ‘ discharge disposi-tion’. For continuous variables, the median-split method was used to produce dichotomous categories.Statistical analysisStatistical analyses were performed using the statistical software package SPSS 12.0 (SPSS Inc, Chicago, IL).  Frequencies were computed for study variables. Continuous variables were dichotomized and converted into categorical variables using the median split. Further, bivariate analyses were conducted to determine the association among BMI, demographic variables, and LOS. In these analyses, Phi (2 × 2 tables) and Cramer’s V (tables larger than 2 × 2) were calculated. The significance of differences between the two groups for LOS was determined with the Phi/Cramer’s V test. The significance level alpha was set at P , 0.05 ( two-sided). Logistic regression analysis using the enter method was computed for LOS as the dependent variable. This means that all significant independent variables based on the bivariate analysis were entered in the equation at once.ResultsSample characteristicsThe final sample size consisted of n = 119 individuals with a primary diagnosis of THA. In total, 125 individuals were excluded from the analysis. There were 83 (69.7%) women and 36 (30.3%) men. The median age was 68 years (min 22; max 90 years). The median length of stay was 10 days (min 2; max 25). The median split for LOS was used to divide individuals who stayed 0–9 and those who stayed 10 or more days in inpatient rehabilitation (Table 1).relationship between LOS and BMIThe bivariate cross-tabulation analysis shows that there was no significant association between length of stay and BMI after THA (Table 1). Interestingly, the proportion of patients in the obesity category and those with normal weight, includ-ing being underweight with a LOS of 10 days, was larger than those found for patients who were categorized as being overweight.Clinical Audit 2010:2 submit your manuscript | www.dovepress.comDovepress Dovepress47 Total hip arthroplasty, obesity and length of stay in rehabilitationrelationship between LOS and demographic and health-related variablesSimilarly, age, gender, number of co-morbid conditions, number of days between surgery date and discharge from rehabilitation, and discharge disposition (home vs other) were not associated with the LOS. Statistically significant bivariate associations for LOS were found for insurance payer type and race (Table 1). Patients receiving Medicare or Medicaid had significant longer rehabilitation stays than those with private insurance. A significantly larger propor-tion of patients receiving Medicare had a LOS of 10 days or more compared to Medicaid or privately insured patients. While nearly three-quarters of the non-Caucasian patients had a LOS of 10 days or more, only a quarter of Caucasians stayed for this duration.Logistic regression analysis showed that the odds of  having a stay of 10 days or more in acute inpatient  rehabilitation are more than five times of those insured through Medicare compared to those with private health insurance coverage (odds ratio (OR) = 5.854, confidence interval (CI): 2.018–16.982, P = .001) and more than three times higher for patients covered by Medicaid compared to private insurance (OR = 3.616, CI: 0.919–14.234, P = 0.066). Moreover, the odds of spending more than 10 days for patients who are of Caucasian background are half of those found for patients of non-Caucasian background (OR = 0.451, CI: 0.188–1.092, P = 0.078). The only statistically significant regression was found for Medicare vs private coverage.ConclusionThere was no significant association between LOS and BMI after THA. This confirms earlier findings by Jiganti et al,11 who also found no significant difference in the LOS between non-obese and obese THA patients. However, in a recent study that involved 15 United States’ hospital researchers found that LOS was 0.8–1.3 days longer in the non-obese group compared with other weight groups (P # 0.05). Hospital expenditures were significantly higher for the severely obese patients in that study.7 Previously, the same study group found a curvilinear relationship between LOS and BMI and higher total hospital charges for severely obese patients undergoing total hip arthroplasty.12 The latter finding is, however, drawn Table 1 Bivariate relationship between LOS and demographic and clinical correlates0–9 days (n = 48) $10days (n = 71) Phi/Cramer’s V PAge 0.171 0.06218–68 30 (62.5%) 32 (45.1%)69–99 18 (37.5%) 39 (54.9%)Gender -0.018 0.846Female 33 (68.8%) 50 (70.4%)Male 15 (31.2%) 21 (29.6%)race/ethnicity 0.197 0.032*Caucasian 22 (45.8%) 19 (26.8%)Non-Caucasian 26 (54.2%) 52 (73.2%)health insurance 0.336 0.001**Medicare 24 (50.0%) 52 (73.2%)Medicaid 7 (14.6%) 13 (18.3%)Private 17 (35.4%) 6 (8.5%)BMI 0.073 0.725Underweight/normal 15 (31.3%) 24 (33.8%)Overweight 12 (25.0%) 21 (29.6%)Obese 21 (43.8%) 26 (36.6%)Number of comorbid conditions0.027 0.7690–5 27 (56.3%) 38 (53.5%)6# 21 (43.8%) 33 (46.5%)Number of days between surgery  date and discharge from rehab0.079 0.4020–4 36 (78.3%) 47 (71.2%)5# 10 (21.7%) 19 (28.8%)Discharge disposition 0.003 0.977home 42 (87.5%) 62 (87.3%)Other 6 (12.5%) 9 (12.7%)Notes: *P , 0.05, **P , 0.01.Clinical AuditPublish your work in this journalSubmit your manuscript here: http://www.dovepress.com/clinical-audit-journalClinical Audit is an international, peer-reviewed, open access journal focusing on the processes and outcomes of clinical audit in any area of healthcare. All aspects of patient care are addressed within the journal and practitioners from all disciplines are invited to submit their work. Areas covered include: Publication of audits; How an audit has changed practice; Practical tips on how to do audits and to avoid pitfalls; How audits have changed patient care; Calls and justifications for new audits. The manuscript management system is completely online and includes a very quick and fair peer-review system, which is all easy to use. Visit http://www.dovepress.com/testimonials.php to read real quotes from published authors.Clinical Audit 2010:2submit your manuscript | www.dovepress.comDovepress DovepressDovepress48Greenberg and Krollinto question by findings that did not suggest an overall higher resource utilization of patients who are obese and who are undergoing elective THA.13 Our study did not find a relation-ship between age or gender and LOS, however, functional outcomes may well differ for men and women and different age groups, as a recent study showed.14 Nor did we identify any significant differences for LOS in terms of number of co-morbid conditions. This finding is inconsistent with what was found in a Canadian study where LOS was clearly asso-ciated with age and co-morbid conditions.15 Others found clear evidence for increased hospital expenditures linked to co-morbid conditions in patients undergoing THA.16 Insurance type, however, appears to influence the LOS after THA. To date there is little information from other United States’ stud-ies comparing Medicare recipients with other insurance types with regard to LOS. A large recent retrospective cohort study could show that Hispanic Americans had significantly longer LOS after THA than Caucasian Americans.17 In our review, there was a trend towards significance for race/ethnicity as a predictor of LOS.The audit that was restricted to one clinical site only which presents several study limitations. Findings are not general-izable to other inpatient rehabilitation facilities. The LOS is continuously decreasing. Our study data were extracted during a very specific time only. The sample size is rather small, which did not allow for more sophisticated analysis (ie, comparisons among first time THA patients and revision surgery; different types of insurance plans, ie, fee-for-service vs managed care). Other critical variables, such as dietary habits and exercise behavior, could not be included as this data was not available as part of the hospital records. It is especially crucial to examine how insurance type may affect the rehabilitation opportunities available to individuals and related outcomes. It would be necessary to replicate findings with larger data sets and track changes over time. Larger study samples would allow for more complex statistical analyses and examination of multiple variables at once. These analy-ses are needed to determine the independent contribution of demographic, health-related, and health service variables to LOS after THA.DisclosureThe authors report no conflicts of interest in this work.References 1. Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA. 2006;295(13): 1549–1555. 2. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999–2000. JAMA. 2002;288(14): 1723–1727. 3. Berghofer A, Pischon T, Reinhold T, Apovian CM, Sharma AM, Willich SN. Obesity prevalence from a European perspective: a sys-tematic review. BMC Public Health. 2008;8:200. 4. Hossein P, Kawar B, El Nahas M. Obesity and diabetes in the developing world – a growing challenge. New Engl J Med. 2007;356(3):213–215. 5. Rasul AT, Wright J. Total joint replacement rehabilitation. 2010 Jan 20. Available from: http://emedicine.medscape.com/article/320061-overview. Accessed March 22, 2010. 6. Azodi Sadr O, Belloco R, Eriksson K, Adami J. The impact of tobacco use and body mass index on length of stay in hospital and the risk of post-operative complications among patients undergoing total hip replacement. J Bone Joint Surg. 2006;88(10):1316–1320. 7. Vincent HK, DeJong G, Mascarenas D, Vincent KR. The effect of body mass index and hip abductor brace use on inpatient rehabilita-tion outcomes after total hip arthroplasty. Am J Physical Med Rehabil. 2009;88(3):201–209. 8. Kessler S, Käfer W. Overweight and obesity: two predictors for worse early outcome in total hip replacement. Obesity. 2007;15(11):2840–2845. 9. Gelber RP, Gaziano JM, Orav EJ, Manson JE, Buring JE, Kurth T. Measures of obesity and cardiovascular risk among men and women. J Am Coll Cardiol. 2008;52(8):605–615. 10. World Health Organization (WHO). Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation. Geneva: World Health Organization; 1997. 11. Jiganti JJ, Goldstein WN, Williams CS. A comparison of the periop-erative morbidity in total joint arthroplasty in the obese and nonobese patient. Clin Orthop Relat Res. 1993;289:175–179. 12. Vincent HK, Weng JP, Vincent KR. Effect of obesity on inpatient rehabilita-tion outcomes after total hip arthroplasty. Obesity. 2007;15(2):522–530. 13. Batsis JA, Naessens JM, Keegan MT, Wagie AE, Huddleston PM, Huddleston JM. Impact of body mass on hospital resource use in total hip arthroplasty. Public Health Nutr. 2009;12(8):1122–1132. 14. Santaguida PL, Hawker GA, Hudak PL, et al. Patient characteristics affecting the prognosis of total hip and knee joint arthroplasty: a sys-tematic review. Can J Surg. 2008;51(6):428–436. 15. MacKenzie TA, Hopman WM, Mantle M. Factors influencing length of stay and health status in total hip replacement patients. Abstr Book Assoc Health Serv Res Meet. 1997;14:186–187. 16. Shah AN, Vail TP, Taylor D, Pietrobon R. Comorbid illness affects hospital costs related to hip arthroplasty. J Arthroplasty. 2004;19(6):700–705. 17. Bergés IM, Yong-Fang K, Ostir GV, Granger CV, Graham JE, Ottenbacher KJ. Gender and ethnic differences in rehabilitation outcomes after hip-replacement surgery. Am J Phys Med Rehabil. 2008;87(7):567–572.

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The relation of body mass index, demographic and health-related variables to length of stay for patients at an acute rehabilitation hospital after total hip arthroplasty

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