Assessment of Regression Models for Adjustment of Iron Status Biomarkers for Inflammation in Children with Moderate Acute Malnutrition in Burkina Faso

被引:21
作者
Cichon, Bernardette [1 ,2 ]
Ritz, Christian [1 ]
Fabiansen, Christian [1 ]
Christensen, Vibeke Brix [1 ,3 ]
Filteau, Suzanne [4 ]
Friis, Henrik [1 ]
Kaestel, Pernille [1 ]
机构
[1] Univ Copenhagen, Dept Nutr Exercise & Sports, Frederiksberg, Denmark
[2] Doctors Borders Denmark, Copenhagen, Denmark
[3] Rigshosp, Dept Pediat, Copenhagen, Denmark
[4] London Sch Hyg & Trop Med, Fac Epidemiol & Populat Hlth, London, England
关键词
inflammation; alpha(1)-acid glycoprotein; correction factors; C-reactive protein; iron deficiency; regression analysis; serum ferritin; soluble transferrin receptor; young children; SOLUBLE TRANSFERRIN RECEPTOR; ACUTE-PHASE RESPONSE; FERRITIN CONCENTRATIONS; INCREASED ERYTHROPOIESIS; PLASMA FERRITIN; SERUM FERRITIN; ACUTE MALARIA; DEFICIENCY; ANEMIA; WOMEN;
D O I
10.3945/jn.116.240028
中图分类号
R15 [营养卫生、食品卫生]; TS201 [基础科学];
学科分类号
100403 ;
摘要
Background: Biomarkers of iron status are affected by inflammation. In order to interpret them in individuals with inflammation, the use of correction factors (CFs) has been proposed. Objective: The objective of this study was to investigate the use of regression models as an alternative to the CF approach. Methods: Morbidity data were collected during clinical examinations with morbidity recalls in a cross-sectional study in children aged 6-23 mo with moderate acute malnutrition. C-reactive protein (CRP), alpha(1)-acid glycoprotein (AGP), serum ferritin (SF), and soluble transferrin receptor (sTfR) were measured in serum. Generalized additive, quadratic, and linear models were used to model the relation between SF and sTfR as outcomes and CRP and AGP as categorical variables (model 1; equivalent to the CF approach), CRP and AGP as continuous variables (model 2), or CRP and AGP as continuous variables and morbidity covariates (model 3) as predictors. The predictive performance of the models was compared with the use of 10-fold crossvalidation and quantified with the use of root mean square errors (RMSEs). SF and sTfR were adjusted with the use of regression coefficients from linear models. Results: Crossvalidation revealed no advantage to using generalized additive or quadratic models over linear models in terms of the RMSE. Linear model 3 performed better than models 2 and 1. Furthermore, we found no difference in CFs for adjusting SF and those from a previous meta-analysis. Adjustment of SF and sTfR with the use of the best-performing model led to a 17% point increase and <1% point decrease, respectively, in estimated prevalence of iron deficiency. Conclusion: Regression analysis is an alternative to adjust SF and may be preferable in research settings, because it can take morbidity and severity of inflammation into account. In clinical settings, the CF approach may be more practical. There is no benefit from adjusting sTfR. This trial was registered at www.controlled-trials.com as ISRCTN42569496.
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收藏
页码:125 / 132
页数:8
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