• Eur Spine J · Jan 2017

    On the relevance of surrogate parameter deduction in biomedical research: mediated regression analysis for variance explanation of cervical range of motion.

    • Daniel Niederer, Lutz Vogt, Jan Wilke, and Winfried Banzer.
    • Department of Sports Medicine, Goethe-University Frankfurt/Main, Ginnheimer Landstraße 39, 60487, Frankfurt Am Main, Germany. niederer@sport.uni-frankfurt.de.
    • Eur Spine J. 2017 Jan 1; 26 (1): 162-166.

    PurposeResearch on cervical range of motion (ROM) often includes age and body mass index (BMI) as potential variables to explain inter-individual variances. The BMI may not be a predictor of ROM but an age-affected surrogate parameter: the described effect of BMI on ROM is, thus, suspected being partially or completely mediated by age.MethodsHealthy and adult volunteers (n = 139, 65 female, age 19-75 years, BMI 24.2 ± 3.8 kg m-2) performed five repetitive maximal cervical movements in the sagittal plane to assess maximal ROM (primary outcome). After the examination of underlying assumptions, data were analysed by mediation regression analyses using a SPSS-macro provided by Hayes. ROM represented the outcome variable, independent variable was BMI and mediator variable was age. Total as well as direct and indirect effects were calculated: (1) for all subjects included and (2) for subject with a BMI <35 kg m-2.ResultsAnalysis including all subjects revealed both a direct (-1.1, s e .46, p < .05, 95 %CI -2; -1.7) and an existing indirect effect (mediated by age, -2.4, s e .33, p < .05, 95 %CI -3.1; -1.8) of BMI on ROM. Analysis without obese 2 subjects showed no direct effect of BMI (effect -1, s e .54, p > .05, 95 %CI -2.1; +.1) but a systematic indirect effect, mediated by age, on ROM (effect -2.4, s e .33, p < .001, 95 %CI -3.1; -1.8).ConclusionsAfter the withdrawal of the surrogate parameter BMI, age explains 53 % of maximal ROM. No impact of BMI on ROM was detected after excluding highly obese participants. Our results illustrate the relevance of including each supposable predictor in causal mediation models development.

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