TY - JOUR
T1 - Low-Density Lipoprotein Estimated by Various Equations in Patients With Obesity
AU - Oswald, Johannes
AU - Bregulla, Iris
AU - Broder, Monika
AU - Reiter, Raphael
AU - Eberhardt, Julian
AU - Gomahr, Julian
AU - Schaffler-Schaden, Dagmar
N1 - Oswald, Bregulla, Schaffler: Institute of General Practice, Family Medicine and Preventive Medicine, Paracelsus Medical Private University, Strubergasse 21, Salzburg 5020, Austria Center for Public Health and Healthcare Research, Paracelsus Medical Private University, Strubergasse 21, Salzburg 5020,
Austria; Reiter: Department of Geriatric
Medicine, Christian-Doppler-Klinik, Paracelsus Medical Private University, Ignaz-Harrer-Straße 79, Salzburg 5020, Austria; Eberhardt: First Department of
Medicine, Paracelsus Medical Private University, Müllner Hauptstrasse 48, Salzburg 5020, Austria; Gomahr: Department of Pediatrics, Paracelsus Medical
Private University, Müllner Hauptstraße 48, Salzburg 5020, Austri
PY - 2026
Y1 - 2026
N2 - Background and Aims: Reducing atherogenic lipoproteins to lower cardiovascular risk is a key objective in obesity treatment. Accurate lipoprotein measurements are essential for determining the need for therapy and guiding its management. To identify the best equation for estimating LDL cholesterol, LDL measured directly (LDL-D) is compared to LDL calculated using equations developed by Friedewald (LDL-F), Martin (LDL-M) and Sampson/NIH (LDL-S). This study also examines the change of LDL and apolipoprotein B levels during a multidisciplinary obesity treatment programme. Methods: This retrospective observational study included 308 adult patients with obesity who participated in a single-centre, multidisciplinary treatment programme using meal replacement (Optifast-professional). This study employed Pearson's correlations, repeated-measures analyses of variance (ANOVA) and a paired t-test and also compared calculated values against desirable bias and total allowable error. Results: The absolute values of LDL-M and LDL-S showed less bias and correlated better with LDL-D than LDL-F. All equations significantly underestimated absolute LDL values: LDL-F (mean -12.43 mg/dL, p < 0.001), LDL-M (mean -10.05 mg/dL, p < 0.001) and LDL-S (mean -9.49 mg/dL, p < 0.001). LDL-F also underestimated the change occurring during the programme (3.81 mg/dL; p = 0.017). All equations performed poorly against desirable bias and total allowable error. LDL-D, LDL-F, LDL-M, LDL-S and ApoB levels all decreased significantly, and these decreases remained significant after excluding patients taking lipid-lowering medications. Conclusions: LDL estimation equations systematically underestimated LDL in individuals with obesity. Among these, the Martin equation most accurately captured changes in LDL. Consequently, it appears to be the most suitable estimation method. However, direct measurement should remain the preferred method. The multidisciplinary meal replacement programme significantly reduced LDL cholesterol and ApoB.
AB - Background and Aims: Reducing atherogenic lipoproteins to lower cardiovascular risk is a key objective in obesity treatment. Accurate lipoprotein measurements are essential for determining the need for therapy and guiding its management. To identify the best equation for estimating LDL cholesterol, LDL measured directly (LDL-D) is compared to LDL calculated using equations developed by Friedewald (LDL-F), Martin (LDL-M) and Sampson/NIH (LDL-S). This study also examines the change of LDL and apolipoprotein B levels during a multidisciplinary obesity treatment programme. Methods: This retrospective observational study included 308 adult patients with obesity who participated in a single-centre, multidisciplinary treatment programme using meal replacement (Optifast-professional). This study employed Pearson's correlations, repeated-measures analyses of variance (ANOVA) and a paired t-test and also compared calculated values against desirable bias and total allowable error. Results: The absolute values of LDL-M and LDL-S showed less bias and correlated better with LDL-D than LDL-F. All equations significantly underestimated absolute LDL values: LDL-F (mean -12.43 mg/dL, p < 0.001), LDL-M (mean -10.05 mg/dL, p < 0.001) and LDL-S (mean -9.49 mg/dL, p < 0.001). LDL-F also underestimated the change occurring during the programme (3.81 mg/dL; p = 0.017). All equations performed poorly against desirable bias and total allowable error. LDL-D, LDL-F, LDL-M, LDL-S and ApoB levels all decreased significantly, and these decreases remained significant after excluding patients taking lipid-lowering medications. Conclusions: LDL estimation equations systematically underestimated LDL in individuals with obesity. Among these, the Martin equation most accurately captured changes in LDL. Consequently, it appears to be the most suitable estimation method. However, direct measurement should remain the preferred method. The multidisciplinary meal replacement programme significantly reduced LDL cholesterol and ApoB.
KW - Friedewald
KW - Martin-Hopkins
KW - Sampson/NIH
KW - apolipoprotein B
KW - calculated LDL cholesterol
KW - Diagnostic tests
KW - Low-density lipoprotein cholesterol
KW - Meal replacement
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=pmu_pure&SrcAuth=WosAPI&KeyUT=WOS:001768367200001&DestLinkType=FullRecord&DestApp=WOS_CPL
U2 - 10.1155/jobe/4315375
DO - 10.1155/jobe/4315375
M3 - Original Article
C2 - 42144850
SN - 2090-0708
VL - 2026
JO - JOURNAL OF OBESITY
JF - JOURNAL OF OBESITY
IS - 1
M1 - 4315375
ER -