Pre-diagnostic risk factors for brain cancer incidence and survival: insights from the Golestan Cohort Study by Parisa Rezanejad-Asl, Peyvand Parhizkar Roudsari, Negar Rezaei, Maryam Sharafkhah, Gholamreza Roshandel, Hossein Poustchi, Sadaf Sepanlou, Reza Malekzadeh

“…In the multiple model, Turkmen ethnicity (Hazard Ratio = 0.42 (0.23–0.76)), urban residence (HR = 0.46 (0.25–0.84)), overweight or obesity (HR = 0.48 (0.25–0.93)), and history of animal contact (HR = 0.43 (0.19–0.96)) were associated with a better survival. …”
Get full text

The effects of alcohol on recovery from musculoskeletal trauma and injuries by Shahrzad Bazargan-Hejazi, Vincent Arriola, Daniel Arriola, Deyu Pan, Kaveh Dehghan, Emad Alamoutifard, Elby Washington

“…Multivariate logistic regression analysis was used to assess the independent association of alcohol misuse with the outcome variables, controlling for age, gender, ethnicity, and insurance status. Results: Among 3.7 million discharges, 207623 (40.2%) had alcohol abuse, and 58.8% had alcohol dependence. …”
Get full text

Longitudinal maternal glycemia during pregnancy and placental epigenetic age acceleration by Tesfa Dejenie Habtewold, Prabhavi Wijesiriwardhana, Richard J. Biedrzycki, Cuilin Zhang, Katherine L. Grantz, Jagteshwar Grewal, Fasil Tekola-Ayele

“…Models were applied in the full cohort and stratified by race/ethnicity. Further, sensitivity analyses were performed after excluding women with GDM or preeclampsia. …”
Get full text

Perceived wildfire risk and past experiences with wildfire smoke influence public support for prescribed burning in the western conterminous United States by Christopher J Rogers, Celeste Beck, Rima Habre, Jo Kay Ghosh

“…In weighted logistic regression models, we evaluated associations between predictor variables (past experiences with smoke, wildfire risk perception) and support for prescribed burns in general or near a respondent’s neighborhood, adjusting for age, race/ethnicity, gender, education, household income, and wildland urban interface status. …”
Get full text

Utilizing A Multi-Stage Transition Model for Analysing Child Stunting in Two Urban Slum Settlements of Nairobi: A Longitudinal Analysis, 2011-2014. by Oduro, Michael S., IddiI, Samuel, Asiedu, Louis, Asiki, Gershim, Kadengye, DamazoT.

“…The shared common factors associated with all transitions to a more severe state include male gender, ethnicity (only for mild and severe transition states), child’s age, and household food insecurity. …”
Get full text

Factors Associated with Stunting in Children Under Five Years of Age: A Case of Buhara Sub County, Kabale District. by Namanya, Oliver

“…The study made the following findings in line with the objectives: low household income, child illness in the last few weeks incomplete child vaccination (p- Value = 0.005 < 0.05 and p- value = 0.001 < 0.05), the child’s guardian ethnicity with (p- value = 0.013 < 0.05 and 0.000), open defecation, indiscriminate waste disposal, 18(4.7%) 95 CI= 028311725 - .073831273) and use of unprotected water sources, were the major factors associated with stunting. …”
Get full text

Are noise and air pollution related to the incidence of dementia? A cohort study in London, England by Derek G Cook, Frank J Kelly, Iain M Carey, H Ross Anderson, David P Strachan, Richard W Atkinson, Sean D Beevers, David Dajnak, John Gulliver

“…HRs from Cox models were adjusted for age, sex, ethnicity, smoking and body mass index, with further adjustments explored for area deprivation and comorbidity.Results 2181 subjects (1.7%) received an incident diagnosis of dementia (39% mentioning Alzheimer’s disease, 29% vascular dementia). …”
Get full text

A novel model-based meta-analysis to indirectly estimate the comparative efficacy of two medications: an example using DPP-4 inhibitors, sitagliptin and linagliptin, in treatment o... by Yan Gong, James Rogers, Christian Friedrich, Sanjay Patel, Alexander Staab, Jorge Luiz Gross, Daniel Polhamus, William Gillespie, Brigitta Ursula Monz, Silke Retlich

“…The final model described HbA1c levels as function of time, dose, baseline HbA1c, washout status/duration and ethnicity. Other covariates showed no major impact on model parameters and were not included. …”
Get full text

Cross-sectional design and protocol for Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI) by Gerald McGwin, Linda M Zangwill, Nicholas Evans, Shannon McWeeney, Cecilia S Lee, Bhavesh Patel, Jeffrey C Edberg, Cynthia Owsley, Aaron Lee, Cecilia Lee, Sally L Baxter, Michael Snyder, Samantha Hurst, Nicole Ehrhardt, Christopher Chute, Dawn S Matthies, Julia P Owen, Amir Bahmani, Sally Baxter, Edward Boyko, Aaron Cohen, Jorge Contreras, Garrison Cottrell, Virginia de Sa, Jeffrey Edberg, Irl Hirsch, Michelle Hribar, T.Y. Alvin Liu, Bonnie Maldenado, Sara Singer, Bradley Voytek, Joseph Yracheta, Linda Zangwill

“…The fundamental rationale for promoting health resilience in T2DM stems from its high prevalence of 10.5% of the world’s adult population and its contribution to many adverse health events.Methods AI-READI is a cross-sectional study whose target enrollment is 4000 people aged 40 and older, triple-balanced by self-reported race/ethnicity (Asian, black, Hispanic, white), T2DM (no diabetes, pre-diabetes and lifestyle-controlled diabetes, diabetes treated with oral medications or non-insulin injections and insulin-controlled diabetes) and biological sex (male, female) (Clinicaltrials.org approval number STUDY00016228). …”
Get full text

Risk of SARS-CoV-2 infection before and after the Omicron wave in a cohort of healthcare workers in Ontario, Canada by Jorge L. Martinez-Cajas, Ann Jolly, Yanping Gong, Gerald Evans, Santiago Perez-Patrigeon, Bradley Stoner, T. Hugh Guan, Beatriz Alvarado

“…We employed Poisson regression for period #1 and Cox regression for period #2 to examine associations of demographic factors (age, sex, ethnicity, migration status, income insufficiency), health factors (chronic conditions, smoking history, SARS-CoV-2 vaccination status), household factors (exposure to COVID-19), occupational factors (work role, exposure to COVID-19 patients, personal protective equipment access, aerosol-generating procedures) and community exposures (use of masks, distance, hand-washing) with SARS-CoV-2 infection. …”
Get full text

Nicotine dependence is associated with an increased risk of developing chronic, non-communicable inflammatory disease: a large-scale retrospective cohort study by Khalaf Kridin, Khalaf Kridin, Khalaf Kridin, Cristian Papara, Katja Bieber, David A. De Luca, Jan Philipp Klein, Marlene A. Ludwig, Philip Curman, Philip Curman, Philip Curman, Philip Curman, Artem Vorobyev, Astrid Dempfle, Ralf J. Ludwig

“…Using propensity score matching (PSM) to control for age, sex, ethnicity, and other CID risk factors, we contrasted the risk of developing any or any of the 38 CIDs in 881,192 EHRs from individuals with nicotine dependence to PSM-matched unexposed counterparts.ResultsThe analytical pipeline was validated by demonstrating an increased risk of individuals exposed to nicotine dependence for subsequent diagnosis of myocardial infarction, malignant neoplasm of the lung, and chronic obstructive pulmonary disease. …”
Get full text

Effect of nirmatrelvir/ritonavir (Paxlovid) on hospitalization among adults with COVID-19: An electronic health record-based target trial emulation from N3C. by Abhishek Bhatia, Alexander J Preiss, Xuya Xiao, M Daniel Brannock, G Caleb Alexander, Robert F Chew, Hannah Davis, Megan Fitzgerald, Elaine Hill, Elizabeth P Kelly, Hemalkumar B Mehta, Charisse Madlock-Brown, Kenneth J Wilkins, Christopher G Chute, Melissa Haendel, Richard Moffitt, Emily R Pfaff, N3C Consortium

“…To emulate randomization, we used the clone-censor-weight technique with inverse probability of censoring weights to balance a set of covariates including sex, age, race and ethnicity, comorbidities, community well-being index (CWBI), prior healthcare utilization, month of COVID-19 index, and site of care provision. …”
Get full text

Early COVID-19 and protection from Omicron in a highly vaccinated population in Ontario, Canada: a matched prospective cohort study by Altynay Shigayeva, Christopher Kandel, Lubna Farooqi, Zoe Zhong, Anne-Claude Gingras, Brenda L. Coleman, Lois Gilbert, Wayne L. Gold, Maria Major, Tony Mazzulli, Samira Mubareka, Jelena Vojicic, Jingyan Yang, Pingping Zhang, Catherine Martin, Moe H. Kyaw, John M. McLaughlin, Allison McGeer

“…Older age, non-White ethnicity, no children in household, and lower neighbourhood income were associated with reduced risk of infection. …”
Get full text

Socioeconomic correlates of mental health in Moldova: A nationally representative door-to-door survey by J.M. van Baar, C. Ciofu, F. Thompson, A.I. Luik, O. Mereanu, J. Kramer, F. Schouten, V. Condrat, L. Voorham, J. Chihai, L. Shields-Zeeman

“…Multivariable regression models were used to compare outcomes across age, gender, ethnicity, education, employment, and household income groups. …”
Get full text

Assessment of maternal healthcare services among the women of reproductive age in the rural municipality of Nepal: a cross-sectional study by Mukesh Adhikari, Manish Rajbanshi, Anita Karki, Richa Aryal, Bishnu Prasad Choulagai

“…This study demonstrated proximity to health facilities, and lower ethnic groups were deprived of maternal healthcare services. …”
Get full text

The impact of trauma and how to intervene: a narrative review of psychotraumatology over the past 15 years by Miranda Olff, Irma Hein, Ananda B. Amstadter, Cherie Armour, Marianne Skogbrott Birkeland, Eric Bui, Marylene Cloitre, Anke Ehlers, Julian D. Ford, Talya Greene, Maj Hansen, Nathaniel G. Harnett, Debra Kaminer, Catrin Lewis, Alessandra Minelli, Barbara Niles, Nicole R. Nugent, Neil Roberts, Matthew Price, Anthony N. Reffi, Soraya Seedat, Antonia V. Seligowski, Anka A. Vujanovic

“…Here, we focus on how best to address the range of negative health outcomes following trauma, how to serve individuals across the age spectrum, including the very young and old, and include considerations of sex/gender, ethnicity, and culture in diverse contexts, beyond Western, Educated, Industrialized, Rich, and Democratic (WEIRD) countries. …”
Get full text

A sex-disaggregated analysis of the prognostic value of lean type 2 diabetes mellitus in the adult population with acute myocardial infarction by Gwyneth Kong, Jaycie Koh, Jobelle Chia, Bryan Neo, Yiming Chen, Grace Cao, Bryan Chong, Mark Muthiah, Hui Wen Sim, Gavin Ng, Chieh Yang Koo, Chin Meng Khoo, Mark Yan-Yee Chan, Poay-Huan Loh, Nicholas W. S. Chew

“…Cox regression model was constructed to investigate the associations of lean and non-lean T2DM phenotypes with mortality, adjusted for age, ethnicity, previous AMI, AMI type, chronic kidney disease, angiotensin converting enzyme inhibitor or angiotensin receptor blockers, beta-blockers, and smoking status. …”
Get full text

Kombinasi K-Means dan Support Vector Machine (SVM) untuk Memprediksi Unsur Sara pada Tweet by Wiga Maulana Baihaqi, Muliasari Pinilih, Miftakhul Rohmah

“…Broadcasting in discussions that often occur on social media, often users of social media consciously or unconsciously have created content that contains issues of ethnicity, religion, race (nationality) and intergroup (SARA). …”
Get full text

High prevalence of overweight/obesity and central obesity among women in a rural district of Nepal in 2012–2013: a population-based study by Chandra Yogal, Chandra Yogal, Astrid Kamilla Stunes, Astrid Kamilla Stunes, Sunila Shakya, Biraj Karmarcharya, Rajendra Koju, Mats P. Mosti, Mats P. Mosti, Miriam K. Gustafsson, Miriam K. Gustafsson, Bjørn Olav Åsvold, Bjørn Olav Åsvold, Berit Schei, Unni Syversen, Unni Syversen

“…The majority belonged to the Adhivasi/Janajati ethnicity, were uneducated and worked in agriculture. …”
Get full text