scholarly journals Racial/Ethnic Variation in the Association of Lipid-Related Genetic Variants With Blood Lipids in the US Adult Population

2011 ◽  
Vol 4 (5) ◽  
pp. 523-533 ◽  
Author(s):  
Man-huei Chang ◽  
Renée M. Ned ◽  
Yuling Hong ◽  
Ajay Yesupriya ◽  
Quanhe Yang ◽  
...  
2019 ◽  
pp. 1-24 ◽  
Author(s):  
Pamela Joshi ◽  
Maura Baldiga ◽  
Alison Earle ◽  
Rebecca Huber ◽  
Theresa Osypuk ◽  
...  

2012 ◽  
Vol 16 (S1) ◽  
pp. 14-26 ◽  
Author(s):  
Candice M. Belanoff ◽  
Beth M. McManus ◽  
Adam C. Carle ◽  
Marie C. McCormick ◽  
S. V. Subramanian

2021 ◽  
Vol 8 ◽  
Author(s):  
Magda Shaheen ◽  
Katrina M. Schrode ◽  
Deyu Pan ◽  
Dulcie Kermah ◽  
Vishwajeet Puri ◽  
...  

Non-alcoholic fatty liver disease (NAFLD) is spreading worldwide, with a racial/ethnic disparity. We examined the gender role in the racial/ethnic difference in NAFLD in the US population. We analyzed data for 3,292 individuals ≥18 years old from NHANES 2017–2018, a representative sample of the non-institutionalized adult population in the US. Exclusions were subjects with elevated transferrin level, chronic hepatitis B or C, excessive alcohol use, or prescription medications that might cause hepatic steatosis. NAFLD was diagnosed by FibroScan® using controlled attenuation parameter (CAP) values: S0 <238, S1 = 238–259, S2 = 260–290, S3 >290. Data were analyzed using Chi square and multinomial regression. The overall prevalence of NAFLD was 47.9% [S2 = 16.1%, and S3 = 31.8%]. The prevalence of S3 was highest among Mexican Americans (46%), lowest among Blacks (22.7%), 29.9% in other Hispanics and 32.1% in Whites (p < 0.05). It was higher among Mexican American males (54.1%) compared to Mexican American females (37.7%) (p < 0.05). In the adjusted model, Mexican Americans were two times more likely than Whites to have S2 and S3 (p < 0.05). Only male Mexican Americans had higher odds of S2 and S3 relative to male White (p < 0.05). Males had higher odds of S3 relative to non-menopausal females (p < 0.05). There was no difference in the odds of S2 or S3 NAFLD among the menopausal females with or without hormone therapy relative to non-menopausal females (p > 0.05). While Mexican Americans had the highest prevalence of severe NAFLD relative to the other racial/ethnic groups, only male Mexican Americans, but not females, had higher likelihood of both moderate and severe NAFLD relative to Whites. Interventions that specifically target Mexican American males are needed to increase awareness about NAFLD and its prevention.


2021 ◽  
Vol 12 ◽  
pp. 215013272110165
Author(s):  
Elaine Seaton Banerjee ◽  
Kyle Shaak ◽  
Nicole Burgess ◽  
Melanie Johnson ◽  
Beth Careyva

Introduction/Objectives: Diabetes and prediabetes impact nearly half of the US adult population and are associated with significant health risks but may be underdiagnosed. Effective screening may improve diagnosis and give patients opportunity to manage their disease. The purpose of this study was to determine screening rates, identify characteristics predictive of screening, and evaluate correct diagnosis of diabetes and prediabetes. Methods: Retrospective chart review of 71 433 patients eligible for diabetes screening, defined by completing A1c test within the 3-year study period. Results: A total of 31.3% of eligible patients received diabetes screening. Factors associated with screening include older age, female sex, non-white race, Hispanic ethnicity, Medicare or Medicaid insurance, higher BMI, and having a medical comorbidity. History of prediabetes or gestational diabetes were the strongest predictors for diabetes screening, but history of gestational diabetes was under-documented. Of those screened, 10.4% had a result consistent with diabetes and 51.8% had a result consistent with prediabetes. However, 52.9% of these patients had a missed diagnosis. Conclusions: Findings of this study indicate the need for uniform coverage for diabetes screening for all insurances, increased documentation of gestational diabetes to improve screening for patients with this history, and improving accurate diagnosis after screening is completed.


2021 ◽  
Vol 118 ◽  
pp. 106873
Author(s):  
Nina Mulia ◽  
Yu Ye ◽  
Katherine J. Karriker-Jaffe ◽  
Libo Li ◽  
William C. Kerr ◽  
...  

2021 ◽  
pp. 1357633X2110259
Author(s):  
Kristin N Gmunder ◽  
Jose W Ruiz ◽  
Dido Franceschi ◽  
Maritza M Suarez

Introduction As coronavirus disease 2019 (COVID-19) hit the US, there was widespread and urgent implementation of telemedicine programs nationwide without much focus on the impact on patient populations with known existing healthcare disparities. To better understand which populations cannot access telemedicine during the coronavirus disease 2019 pandemic, this study aims to demographically describe and identify the most important demographic predictors of telemedicine visit completion in an urban health system. Methods Patient de-identified demographics and telemedicine visit data ( N = 362,764) between March 1, 2020 and October 31, 2020 were combined with Internal Revenue Service 2018 individual income tax data by postal code. Descriptive statistics and mixed effects logistic regression were used to determine impactful patient predictors of telemedicine completion, while adjusting for clustering at the clinical site level. Results Many patient-specific demographics were found to be significant. Descriptive statistics showed older patients had lower rates of completion ( p < 0.001). Also, Hispanic patients had statistically significant lower rates ( p < 0.001). Overall, minorities (racial, ethnic, and language) had decreased odds ratios of successful telemedicine completion compared to the reference. Discussion While telemedicine use continues to be critical during the coronavirus disease 2019 pandemic, entire populations struggle with access—possibly widening existing disparities. These results contribute large datasets with significant findings to the limited research on telemedicine access and can help guide us in improving telemedicine disparities across our health systems and on a wider scale.


Obesity ◽  
2017 ◽  
Vol 25 (9) ◽  
pp. 1540-1548
Author(s):  
Sandra A. Tsai ◽  
Lan Xiao ◽  
Nan Lv ◽  
Ying Liu ◽  
Jun Ma

2008 ◽  
Vol 19 (1) ◽  
pp. 46-50 ◽  
Author(s):  
M. Sundaram ◽  
J. Mohanakrishnan ◽  
K.G. Murugavel ◽  
E.M. Shankar ◽  
S. Solomon ◽  
...  

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