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Hispanics

Hispanics, a diverse ethnic group with origins in Latin American countries, encompass a wide range of cultural, linguistic, and socioeconomic backgrounds.
This population faces unique health challenges and disparities, underscoring the importance of tailored research protocols to address their specific needs.
PubCompare.ai, an AI-driven platform, empowers researchers to streamline and optimize their Hispanic research process.
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Researchers can leverage the power of AI to drive meaningful insights and improve outcomes for the Hispanic community.

Most cited protocols related to «Hispanics»

We profiled the epigenetic landscape of 990 unique donors forming the control cohort of the Assessment of Risk for Colorectal Cancer Tumours in Canada (ARCTIC) project.14 (link) Fifteen μl of lymphocyte-derived DNA extracted (at an average concentration 90 ng/μl) was bisulfite-converted using the EZ-96 DNA Methylation-Gold Kit (Zymo Research, Orange, CA); 4μl of bisulfite-treated DNA was then analyzed on the HumanMethylation450 BeadChip from Illumina according to the manufacturer’s protocol. Intensities were normalized using Illumina’s internal normalization probes and algorithms, without background subtraction. Beta values with assigned detection p-values > 0.01 were treated as missing data. CpG sites with more than 1% missing data across all samples were discarded.
We removed from analysis samples that were outliers with respect to any one of the internal control probes (excluding probes designed to evaluate the background noise and probes designed to normalize the data) and samples that were not of non-Hispanic white ancestry, either self-declared or by investigation of genetic ancestry using genome-wide SNP data. After sample exclusion, we were left with 489 adult males and 357 adult females.
Publication 2013
Adult Colorectal Carcinoma Colorectal Neoplasms DNA Methylation Donors Genome Gold Health Risk Assessment Hispanics hydrogen sulfite Lymphocyte Males Malignant Neoplasms Neoplasms Reproduction Woman

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Publication 2010
Cardiovascular System Dental Health Services Diet Disabled Persons Family Structure Food Hearing Aids Hearing Impairment Hispanic or Latino Hispanics Interviewers Latinos Lung Diseases Malignant Neoplasms Mental Recall Tinnitus

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Publication 2010
Central American People Hispanics Households Hypochondroplasia Latinos PER1 protein, human Population at Risk Puerto Ricans
The Religious Orders Study enrolls Catholic nuns, priests and brothers, from more than 40 groups across the United States (Figure 1). Participants are without known dementia and agree to annual clinical evaluation and brain donation (some in the Chicago area also agree to donate, spinal cord, nerve, and muscle). Each subject signs a consent form and an Anatomical Gift Act. The study was approved by the Institutional Review Board of Rush University Medical Center.
The study primarily recruits persons living communally, including employed (e.g., Teaching Orders) and retired (e.g., Missionary Orders) persons. The study includes three predominantly African American communities in New York, Baltimore, and New Orleans, and enrolls Hispanic sisters primarily from communities in and around San Antonio. All data collection forms have been translated into Spanish. Working with religious communities offers a number of advantages. First, they are altruistic and have a history of participating in research projects from which they may derive little to no personal benefit. Second, they live communally and loss of contact with participants is rare, facilitating the high follow-up and autopsy rates required to ensure internal study validity. Third, their wishes for organ donation are likely to be honored by the Superior and biological family members are unlikely to interfere with the participants’ written preference. Finally, the participants have similar education, socioeconomic and life experiences for most of their adult lives. This allows for tighter control of these potentially confounding variables in analyses of incident AD and cognitive decline.
The study design (Figure 2) supports the following analyses in a single dataset: 1) the association of neurobiologic indices with AD, MCI, and cognition proximate to death and over multiple years prior to death; 2) the association of risk factors for incident AD, incident MCI, and cognitive decline; and 3) the modeling of neurobiologic pathways linking risk factors to clinical phenotypes. The collection of parkinsonian signs and other measures of motor function allow for similar analyses to be conducted with motor function and decline, and disability.
Publication 2012
Adult African American Autopsy Biopharmaceuticals Brain Brothers Cognition Dementia Disabled Persons Disorders, Cognitive Ethics Committees, Research Family Member Hispanic or Latino Hispanics Life Experiences Missionaries Muscle Tissue Nervousness Nuns Organ Transplantation Phenotype Priests Roman Catholics Spinal Cord
Gait speed was calculated for each participant using distance in meters and time in seconds. All studies used instructions to walk at usual pace and from a standing start. The walk distance varied from 8 ft to 6 m. For 8 ft, we converted to 4-m gait speed by formula.24 (link) For 6 m, we created a conversion formula (4-m speed=−0.0341 + (6-mspeed)×0.9816 withR2=0.93, based on a cohort of 61 individuals with concurrent 4- and 6-m walks). For 15 feet (4.57 m),23 (link) speed was simply meters divided by time. Where available, data on fast gait speed (walk as fast as comfortably able25 (link)) and the Short Physical Performance Battery were obtained.26 (link) Survival for each individual used study monitoring methods, including the National Death Index and individual study follow-up. Time from gait speed baseline to death was calculated in days. Five-year survival status was confirmed for more than 99% of participants.
Additional variables include sex, age, race/ethnicity (white, black, Hispanic, other, defined by participant), height(centimeters), weight(kilograms), body mass index (BMI), calculated as weight in kilograms divided by height in meters squared (<25, 25–30, and >30), smoking (never, past, current), use of mobility aids (none, cane, walker), systolic blood pressure, self-reports of health (excellent or very good vs good, fair, or poor), hospitalization in the past year (yes/no), and physician-diagnosed medical conditions (cancer, arthritis, diabetes, and heart disease, all yes/no). Measures of self-reported functional status were not collected in all studies and varied in content and form. We created a dichotomous variable reflecting dependence in basic activities of daily living (ADLs) based on report of being unable or needing help from another person to perform any basic activity, including eating, toileting, hygiene, transfer, bathing, and dressing. For individuals independent in ADLs, we created a dichotomous variable reflecting difficulty in instrumental ADLs based on report of difficulty or dependence with shopping, meal preparation, or heavy housework due to a health or physical problem. Participants were then classified into 1 of 3 groups; dependent in ADLs, difficulty with instrumental ADLs, or independent. Physical activity data were collected in 6 studies, but time frames and items varied widely. Two studies used the Physical Activity Scale for the Elderly (PASE).27 (link) We dichotomized the PASEs core at 100.28 (link) We created operational definitions of other covariates that were reasonably consistent across studies. Covariates were identical for height, weight, BMI, and systolic blood pressure. Hospitalization within the prior year was determined largely by self-report, and chronic conditions were by self-report of physician diagnosis, with heart disease encompassing angina, coronary artery disease, heart attack, and heart failure.
Publication 2011
Acquired Immunodeficiency Syndrome Aged Angina Pectoris Arthritis Canes Chronic Condition Congestive Heart Failure Coronary Artery Disease Diabetes Mellitus Diagnosis Ethnicity Foot Heart Diseases Hispanics Hospitalization Index, Body Mass Malignant Neoplasms Myocardial Infarction Neoplasm Metastasis Performance, Physical Physical Examination Physicians Range of Motion, Articular Reading Frames Systolic Pressure Walkers

Most recents protocols related to «Hispanics»

Covariate selection was guided by previous literature on sociodemographic and health characteristics associated with having a USOC or HL (10 (link),11 (link)). These include baseline, age, race/ethnicity (White, Black, Hispanic, and other), sex, marital status (married/living with partner, and single/never married/divorced/widow), education (less than high school, high school diploma or equivalent, and some college or more), household income (under the poverty line, 100%–199% the poverty line, and ≥200% of the poverty line), number of chronic health conditions among heart attack, heart disease, high blood pressure, arthritis, osteoporosis, diabetes, lung disease, stroke, or cancer (0, 1–2, 3–5, or 6+), self-reported health status (Likert scale, 1 = Excellent, …, 5 = Poor), number of activities of daily living (ADLs) for which the respondent reported needing help (none, 1–2 ADLs, and 3≤ ADLs), dementia (probable, possible, and no dementia) (20 ), additional health coverage (Medigap/Medicare supplement, Medicaid, or Tricare), and depression status (based on Patient Health Questionnaire-2 scores ≥3) (21 (link)).
Despite being identified as a risk factor for loss of USOC, experiencing transportation barriers (reporting that a transportation problem restricted any activity participation in the month before the interview) was not included in the main analyses due to data availability, as a total of N = 1 804 participants had missing information.
Publication 2023
Arthritis Cerebrovascular Accident Dementia Diabetes Mellitus Dietary Supplements Ethnicity Heart Diseases High Blood Pressures Hispanics Households Insurance, Medigap Lung Diseases Malignant Neoplasms Myocardial Infarction Osteoporosis Training Programs Widow
Information on participant age, sex, race and ethnicity, education, income, insurance status, medical history, and medication use was collected through household questionnaires. Race and ethnicity was not consistently reported in the NHANES (eg, Hispanic participants were not oversampled before 2007 and non-Hispanic Asian participants were not classified until 2011).24 For consistency over time, we categorized participants as self-reported Mexican American, non-Hispanic Black, non-Hispanic White, or other race and ethnicity (eg, non-Hispanic Asian or multiple). The family income-to-poverty ratio reflected annual family income relative to the federal poverty threshold and was used as a measure of income classified into 3 groups (≤100%, 101%-399%, and ≥400%).25 (link)Weight, height, waist circumference, and blood pressure (BP) were measured at mobile examination centers by trained staff according to standardized procedures.23 Body mass index was calculated as weight in kilograms divided by height in meters squared. Three BP measurements were assessed, and systolic BP and diastolic BP were calculated as the mean of all available measurements.
Participants were asked to provide blood samples at the mobile examination centers. The samples were stored at −20 °C and sent to central laboratories to determine lipid, plasma glucose, serum insulin, and C-reactive protein levels following standard protocols.23 A subset of participants were randomly selected to attend the morning session after an overnight fast; triglycerides, fasting plasma glucose (FPG), and insulin were measured for those who fasted at least 8 hours. Insulin resistance was assessed with the homeostasis model assessment score.26 (link) Although there were changes in the laboratories, methods, and instruments used to measure lipid levels,27 (link) all laboratories participated in the CDC Lipids Standardization Program,28 thus ensuring the accuracy, precision, and comparability of lipid measurements across cycles. To account for changes in laboratory methods over time, we calibrated FPG and serum insulin measurements to early cycles using the recommended backward equations.23
Publication 2023
Asian Persons BLOOD Blood Pressure C Reactive Protein Determination, Blood Pressure Ethnicity Glucose Hispanics Homeostasis Households Index, Body Mass Insulin Insulin Resistance Lipids Mexican Americans Pharmaceutical Preparations Plasma Pressure, Diastolic Serum Systolic Pressure Triglycerides Waist Circumference
Obesity and abdominal obesity were defined as a BMI of 30.0 or more and a waist circumference of 102 cm or more for men and 88 cm or more for women. The ethnicity-specific BMI cutoff for non-Hispanic Asian individuals was not used due to the lack of classification of this subgroup in the NHANES before 2011.24 Metabolic health was defined according to the harmonized definition proposed by Lavie et al17 (link) and Ortega et al.18 (link) Adults with obesity were classified as having MHO if they had 0 of 4 MetS components29 (link),30 (link): (1) elevated BP (systolic BP ≥130 mm Hg, diastolic BP ≥85 mm Hg, or antihypertensive medication use); (2) elevated FPG (≥100 mg/dL [to convert to millimoles per liter, multiply by 0.0555] or antidiabetic medication use); (3) reduced high-density lipoprotein cholesterol (HDL-C) (<40 mg/dL for men and <50 mg/dL for women [to convert to millimoles per liter, multiply by 0.0259]); or (4) elevated triglycerides (≥150 mg/dL [to convert to millimoles per liter, multiply by 0.0113]). Waist circumference was excluded for collinearity with BMI. Since data for cholesterol medication were available only for general use but not for treatment of elevated triglycerides or reduced HDL-C specifically, we did not utilize this information to avoid overestimation of these components, consistent with previous reports on MetS.31 (link) Participants with obesity who met any of the above criteria were classified as having MUO.
Publication 2023
Adult Antidiabetics Antihypertensive Agents Asian Americans Cholesterol Ethnicity High Density Lipoprotein Cholesterol Hispanics Hypertriglyceridemia Obesity Pharmaceutical Preparations Pressure, Diastolic Systolic Pressure Waist Circumference Woman
To determine whether classification differences were consistent across growth curves, we classified HC using three different growth curves. We used growth curves that are either commonly used (Hadlock and Intergrowth-21st) and/or were designed to be representative of the U.S. population (Intergrowth-21st and National Institute of Child Health and Human Development [NICHD]) to determine the proportion of female and male fetuses classified as having microcephaly (<3rd percentile, z-score < −1.88) or macrocephaly (>97th percentile, z-score >1.88) in the data subset of our sample described above. While the Society for Maternal-Fetal Medicine (SMFM) provides recommendations for standardizing the evaluation of fetal HC in the context of Zika virus exposure (5 ), there are no universal definitions for microcephaly and macrocephaly; the 3rd and 97th percentiles were chosen because they are commonly used and because the information provided in the NICHD curves does not allow direct calculation of other potential cutpoints for microcephaly and macrocephaly. All three evaluated growth curves are sex-neutral, using a single set of curves for both sexes.
We used cubic interpolation to calculate values of the 3rd and 97th percentiles for integer values of GA in days (17 (link)). NICHD percentiles were published separately for four specific race/ethnicity groups: Asian/Pacific Islander, Hispanic, Black non-Hispanic, and White non-Hispanic. There were no published NICHD percentiles that were nonspecific for race/ethnicity. We used the mean of the four race/ethnicity-specific values at each GA to create percentiles for a fifth group, deemed “Uncategorized.” For the NICHD analyses only, we excluded the small number of ultrasounds that could not be linked with maternal data. Women with a recorded race/ethnicity that did not fit in these categories, or whose maternal data were available but missing race/ethnicity data, were evaluated using the “Uncategorized” percentiles. Although there are limits of the reliability and precision of race/ethnicity data, the EHR was the only potential source of race/ethnicity data for this population and therefore the only way to evaluate our data compared to the US-based NICHD percentiles.
Publication 2023
Asian Persons Care, Prenatal Cuboid Bone Ethnicity Females Fetus Hispanics Macrocephaly Males Microcephaly Mothers Pacific Islander Americans Racial Groups Ultrasonography Woman Zika Virus
As part of a larger research study, we recruited 22 biology and chemistry faculty at 19 U.S. institutions. These institutions represented a wide variety of public and private college and university types including: four research intensive universities, 11 primarily undergraduate institutions, and four community colleges. They ranged in size from 1,000–26,000 enrolled undergraduate students. A total of 1,478 students consented to participate in the research: 603 in the control classes, 549 in mCUREs, and 326 in cCUREs (Table 1). Students classified as URM included those traditionally under-represented in STEM disciplines: American Indian/Alaska Native, Black/African American, Hispanic/Latino, Native Hawaiian/Pacific Islander, and two or more races/ethnicities.
All MCC participating institutions received institutional review board (IRB) approval for the research study, either through their university IRB or via IRB authorization agreements with the originating institution, University of San Diego (USD) (Table 2). Participants’ informed consent were collected in written form through an informed consent document.
Publication 2023
Alaskan Natives American Indians Black or African American Ethics Committees, Research Ethnicity Faculty Hispanics Latinos Native Hawaiians Pacific Islander Americans Stem, Plant Student

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Hispanics, Latin American, Latino, Latin, Spanish-speaking, Latinx, Chicano, Hispanic American, Latino American, Ibero-American, Spanish-heritage, Spanish-origin, Latin-origin, Latin-descent, Latin-background, Latin-culture, Latin-speaking, Spanish-speaking, Latin-speaking, Iberian-American, Iberian-descent, Iberian-origin, Iberian-background, Iberian-culture, statistical analysis, data analysis, research methodology, research protocols, study design, sample size, data collection, data management, data processing, data analysis, data interpretation, reproducibility, accuracy, AI-driven, AI-powered, machine learning, natural language processing, literature review, patent search, preprint analysis, PubCompare.ai, SAS, Stata, software tools, statistical software, data analytics