TY - JOUR
T1 - Is Nutrition Specific Quality of Life Associated With Nutritional Status?
AU - Feasel-Aklilu, Sarah
AU - Marcus, Andrea
AU - Parrott, J. Scott
AU - Peters, Emily
AU - Byham-Gray, Laura
N1 - Funding Information:
The authors thank the collaborating nephrologists, clinical managers, and registered dietitian nutritionists at Fresenius Medical Care facilities in Newark, NJ area, Centers for Dialysis Care and University Hospitals in Cleveland, OH area, and Penn State-Hershey Medical Center, in Hershey, PA. The authors would also like to thank the research staff at Frenova Renal Research LLC and our student research assistants at each study site for their contributions. Finally, they would like to acknowledge the contributions of their colleague, Rosa Hand, MS RDN at Case Western Reserve University. Research reported in this publication was supported by the National Institute of Diabetes and Digestive Kidney Diseases of the National Institutes of Health under award numbers 1R15DK090593-01A1, 6R15DK090593-02, and 3R15DK090593-02S1.
Publisher Copyright:
© 2018 National Kidney Foundation, Inc.
PY - 2018/7
Y1 - 2018/7
N2 - Objective: The study purpose was to explore the relationship between nutritional status, as measured by Subjective Global Assessment (SGA), and Health Related Quality of Life measured using the Nutrition Specific Quality of Life (NS-QoL), tool among participants on maintenance hemodialysis (MHD). The study aim was to determine if NS-QoL may be an adjuvant tool for detecting changes in nutritional status among patients on MHD. Design, Setting, and Subjects: This is a cross-sectional, secondary analysis of data from a multi-center study. Participants were adult (>18) men and women on MHD (n = 145) recruited from 3 institutions in the Northeastern United States. Methods: Statistical tests were conducted to determine the relationship between key demographic characteristics (age, sex, dialysis vintage, gender, and ethnicity) and SGA and NS-QoL. Spearman's correlation examined the relationship between the independent variable, SGA and the dependent variable, NS-QoL. A univariate general linear model was conducted to adjust for confounding variables. Main Outcome Measure: The relationship between overall SGA score and composite NS-QoL score. Results: The sample consisted of 85 men (58.6%), with a mean age of 55.3 ± 11.9 years, who were largely African–American (84.1%) and non-Hispanic (77.2%). Mean SGA score was 5.5 ± 1.0, and the mean NS-QoL composite score was 9.51 ± 3.77. No key demographic characteristics had a statistically significant relationship with SGA, whereas sex (P <.001) and race (P =.015) both had statistically significant relationships with NSQoL. After adjusting for the variables of race and sex, NS-QoL score was positively correlated with SGA composite score (P =.042); as NS-QoL score increased so did the SGA score. Conclusion: The present study found a positive linear correlation between NS-QoL composite score and SGA, as well as 5 SGA subcomponent scores and NS-QoL. These findings indicate that NS-QoL can complement the SGA to provide information about a patient's nutritional status.
AB - Objective: The study purpose was to explore the relationship between nutritional status, as measured by Subjective Global Assessment (SGA), and Health Related Quality of Life measured using the Nutrition Specific Quality of Life (NS-QoL), tool among participants on maintenance hemodialysis (MHD). The study aim was to determine if NS-QoL may be an adjuvant tool for detecting changes in nutritional status among patients on MHD. Design, Setting, and Subjects: This is a cross-sectional, secondary analysis of data from a multi-center study. Participants were adult (>18) men and women on MHD (n = 145) recruited from 3 institutions in the Northeastern United States. Methods: Statistical tests were conducted to determine the relationship between key demographic characteristics (age, sex, dialysis vintage, gender, and ethnicity) and SGA and NS-QoL. Spearman's correlation examined the relationship between the independent variable, SGA and the dependent variable, NS-QoL. A univariate general linear model was conducted to adjust for confounding variables. Main Outcome Measure: The relationship between overall SGA score and composite NS-QoL score. Results: The sample consisted of 85 men (58.6%), with a mean age of 55.3 ± 11.9 years, who were largely African–American (84.1%) and non-Hispanic (77.2%). Mean SGA score was 5.5 ± 1.0, and the mean NS-QoL composite score was 9.51 ± 3.77. No key demographic characteristics had a statistically significant relationship with SGA, whereas sex (P <.001) and race (P =.015) both had statistically significant relationships with NSQoL. After adjusting for the variables of race and sex, NS-QoL score was positively correlated with SGA composite score (P =.042); as NS-QoL score increased so did the SGA score. Conclusion: The present study found a positive linear correlation between NS-QoL composite score and SGA, as well as 5 SGA subcomponent scores and NS-QoL. These findings indicate that NS-QoL can complement the SGA to provide information about a patient's nutritional status.
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U2 - 10.1053/j.jrn.2017.12.011
DO - 10.1053/j.jrn.2017.12.011
M3 - Article
C2 - 29631758
AN - SCOPUS:85044988106
SN - 1051-2276
VL - 28
SP - 283
EP - 291
JO - Journal of Renal Nutrition
JF - Journal of Renal Nutrition
IS - 4
ER -