
pmid: 30903294
This study aimed to obtain reference values of lumbar lordosis (LL) and lower LL (LLL) from normal asymptomatic groups, determine the relationship between them and pelvic incidence (PI), and establish the predictive formula for ideal LLL in the elderly Korean population.Standing plain lateral radiographs of the whole spine, including the pelvis, were analyzed in asymptomatic adult male volunteers without back pain or prior surgery involving the spine or lower extremity. Volunteers with scoliosis, spondylolisthesis, segmental disk space narrowing, and/or compression fractures in the radiographs were excluded. The following parameters were measured: LL, LLL, and pelvic parameters including PI. The values of PI-LL and PI-LLL were calculated, and the formula using stepwise multiple regression analysis was made. A P value of < 0.05 was considered statistically significant.The study participants included 150 volunteers. All were male participants with an average age of 64.1 ± 6.4. The average value of height, weight, and body mass index was 167.0 ± 5.5 cm, 67.3 ± 9.8 kg, and 24.1 ± 3.1 kg/m2, respectively. The average LL was - 57.5° ± 9.0°, LLL was - 41.7° ± 7.0°, and PI was 48.6° ± 8.6°. The formula was established as follows: PI-LL = 0.38 × PI - 27.61 (R2 = 0.172), PI-LLL = 0.77 × PI - 28.69 (R2 = 0.516), ideal LL = 0.62 × PI + 27.61 (R2 = 0.348), and ideal LLL = 0.225 × PI + 28.63 (R2 = 0.083).The ideal values of PI-LL and PI-LLL were inconsistent, and they have a positive correlation with PI in asymptomatic elderly population. Our data would be helpful as a normal reference value of ideal LL and LLL according to PI. These slides can be retrieved under Electronic Supplementary Material.
Male, Lumbar Vertebrae, Anthropometry, Middle Aged, Thoracic Vertebrae, Radiography, Predictive Value of Tests, Reference Values, Body Composition, Animals, Humans, Regression Analysis, Pelvic Bones, Aged
Male, Lumbar Vertebrae, Anthropometry, Middle Aged, Thoracic Vertebrae, Radiography, Predictive Value of Tests, Reference Values, Body Composition, Animals, Humans, Regression Analysis, Pelvic Bones, Aged
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