The Link Between Everyday Discrimination, Healthcare Utilization, and Health Status Among a National Sample of Women

Background: Research has not adequately examined the potential negative effects of perceiving routine discrimination on general healthcare utilization or health status, especially among reproductive-aged women. We sought to evaluate the association between everyday discrimination, health service use, and perceived health among a national sample of women in the United States. Materials and Methods: Data were drawn from the Women's Healthcare Experiences and Preferences survey, a randomly selected, national probability sample of 1078 U.S. women aged 18?55 years. We examined associations between everyday discrimination (via a standardized scale) on frequency of health service utilization and perceived general health status using chi-square and multivariable logistic regression modeling. Results: Compared with women who reported healthcare visits every 3 years or less (reference group), each one-point increase in discrimination score was associated with higher odds of having healthcare visits annually or more often (odds ratio [OR]?=?1.36, confidence interval [95% CI]?=?1.01?1.83). Additionally, each one-point increase in discrimination score was significantly associated with lower odds of having excellent/very good perceived health (OR?=?0.65; 95% CI?=?0.54?0.80). Conclusion: Perceived discrimination was associated with increased exposure to the healthcare setting among this national sample of women. Perceived discrimination was also inversely associated with excellent/very good perceived health status.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140141/1/jwh.2015.5522.pd

MRI proton density fat fraction is robust across the biologically plausible range of triglyceride spectra in adults with nonalcoholic steatohepatitis.

BackgroundProton density fat fraction (PDFF) estimation requires spectral modeling of the hepatic triglyceride (TG) signal. Deviations in the TG spectrum may occur, leading to bias in PDFF quantification.PurposeTo investigate the effects of varying six-peak TG spectral models on PDFF estimation bias.Study typeRetrospective secondary analysis of prospectively acquired clinical research data.PopulationForty-four adults with biopsy-confirmed nonalcoholic steatohepatitis.Field strength/sequenceConfounder-corrected chemical-shift-encoded 3T MRI (using a 2D multiecho gradient-recalled echo technique with magnitude reconstruction) and MR spectroscopy.AssessmentIn each patient, 61 pairs of colocalized MRI-PDFF and MRS-PDFF values were estimated: one pair used the standard six-peak spectral model, the other 60 were six-peak variants calculated by adjusting spectral model parameters over their biologically plausible ranges. MRI-PDFF values calculated using each variant model and the standard model were compared, and the agreement between MRI-PDFF and MRS-PDFF was assessed.Statistical testsMRS-PDFF and MRI-PDFF were summarized descriptively. Bland-Altman (BA) analyses were performed between PDFF values calculated using each variant model and the standard model. Linear regressions were performed between BA biases and mean PDFF values for each variant model, and between MRI-PDFF and MRS-PDFF.ResultsUsing the standard model, mean MRS-PDFF of the study population was 17.9 ± 8.0% (range: 4.1-34.3%). The difference between the highest and lowest mean variant MRI-PDFF values was 1.5%. Relative to the standard model, the model with the greatest absolute BA bias overestimated PDFF by 1.2%. Bias increased with increasing PDFF (P < 0.0001 for 59 of the 60 variant models). MRI-PDFF and MRS-PDFF agreed closely for all variant models (R2  = 0.980, P < 0.0001).Data conclusionOver a wide range of hepatic fat content, PDFF estimation is robust across the biologically plausible range of TG spectra. Although absolute estimation bias increased with higher PDFF, its magnitude was small and unlikely to be clinically meaningful.Level of evidence3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:995-1002

MRI proton density fat fraction is robust across the biologically plausible range of triglyceride spectra in adults with nonalcoholic steatohepatitis.

BackgroundProton density fat fraction (PDFF) estimation requires spectral modeling of the hepatic triglyceride (TG) signal. Deviations in the TG spectrum may occur, leading to bias in PDFF quantification.PurposeTo investigate the effects of varying six-peak TG spectral models on PDFF estimation bias.Study typeRetrospective secondary analysis of prospectively acquired clinical research data.PopulationForty-four adults with biopsy-confirmed nonalcoholic steatohepatitis.Field strength/sequenceConfounder-corrected chemical-shift-encoded 3T MRI (using a 2D multiecho gradient-recalled echo technique with magnitude reconstruction) and MR spectroscopy.AssessmentIn each patient, 61 pairs of colocalized MRI-PDFF and MRS-PDFF values were estimated: one pair used the standard six-peak spectral model, the other 60 were six-peak variants calculated by adjusting spectral model parameters over their biologically plausible ranges. MRI-PDFF values calculated using each variant model and the standard model were compared, and the agreement between MRI-PDFF and MRS-PDFF was assessed.Statistical testsMRS-PDFF and MRI-PDFF were summarized descriptively. Bland-Altman (BA) analyses were performed between PDFF values calculated using each variant model and the standard model. Linear regressions were performed between BA biases and mean PDFF values for each variant model, and between MRI-PDFF and MRS-PDFF.ResultsUsing the standard model, mean MRS-PDFF of the study population was 17.9 ± 8.0% (range: 4.1-34.3%). The difference between the highest and lowest mean variant MRI-PDFF values was 1.5%. Relative to the standard model, the model with the greatest absolute BA bias overestimated PDFF by 1.2%. Bias increased with increasing PDFF (P < 0.0001 for 59 of the 60 variant models). MRI-PDFF and MRS-PDFF agreed closely for all variant models (R2  = 0.980, P < 0.0001).Data conclusionOver a wide range of hepatic fat content, PDFF estimation is robust across the biologically plausible range of TG spectra. Although absolute estimation bias increased with higher PDFF, its magnitude was small and unlikely to be clinically meaningful.Level of evidence3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:995-1002