Antiretroviral therapy optimisation without genotype resistance testing : a perspective on treatment history based models by Prosperi, Mattia C. F., Sloot, Peter M. A., van de Vijver, David A. M. C., Rosen-Zvi, Michal, Altmann, André, Zazzi, Maurizio, Schülter, Eugen, Struck, Daniel, Di Giambenedetto, Simona, Kaiser, Rolf, Vandamme, Anne-Mieke, Sönnerborg, Anders

“…Further investigations are required in order to account for different demographics, subtypes and different therapy switching strategies…”
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Young people's understanding of European values: enhancing abilities, supporting participation and voice by Ross, Alistair, Loughran, Tom, Brunold, Andreas, Hartsmar, Nanny, Liljefors Persson, Bodil, Chistolini, Sandra, Dotta, Leanete Thomas, Freires, Thiago, Kõiv, Kristi, Lopes, Juliana Crespo, Pembecioğlu, Nilüfer, Pereira, Fátima, Spinthourakis, Julia Athena

“…Presentation of the analysis: A: The demographic characteristics of the survey population. …”
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Role of primary and secondary care data in atrial fibrillation ascertainment: impact on risk factor associations, patient management, and mortality in UK Biobank by Camm, CF, Von Ende, A, Gajendragadkar, PR, Pessoa-Amorim, G, Mafham, M, Allen, N, Parish, S, Casadei, B, Hopewell, JC

“…AF cases in each of the ascertainment groups had comparable baseline demographic characteristics. However, AF cases identified in hospital data alone had a higher prevalence of cardiometabolic comorbidities and lower rates of subsequent anticoagulation (PC-only: 44%, PC + HADP: 48%, HADP-only: 10%, P < 0.0001) than other groups. …”

Mediating effects of satisfaction in the relationship between motivation factors and continuous viewing intentions towards Chinese documentary programs by Mengyu, Li

“…Meanwhile, the factors of gender, age, and the year of study indicated significant effects on continuous viewing intentions among all socio-demographic factors except for subjects. At last, satisfaction as a mediating variable showed a significant effect. …”
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Global, regional, and national mortality among young people aged 10–24 years, 1950–2019: a systematic analysis for the Global Burden of Disease Study 2019 by Ward, Joseph L., Azzopardi, Peter S., Francis, Kate L., Santelli, John S., Skirbekk, Vegard, Sawyer, Susan M., Kassebaum, Nicholas J., Mokdad, Ali H., Hay, Simon I., Abd-Allah, Foad, Abdoli, Amir, Mohammad Abdollahi, Abedi, Aidin, Abolhassani, Hassan, Abreu, Lucas Guimaraes, Abrigo, Michael R. M., Abu-Gharbieh, Eman, Abushouk, Abdelrahman I., Adebayo, Oladimeji M., Adekanmbi, Victor, Adham, Davoud, Advani, Shailesh M., Afshari, Khashayar, Agrawal, Anurag, Ahmad, Tauseef, Ahmadi, Keivan, Ahmed, Anwar E., Aji, Budi, Akombi-Inyang, Blessing, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alanezi, Fahad Mashhour, Alanzi, Turki M., Alcalde-Rabanal, Jacqueline Elizabeth, Alemu, Biresaw Wassihun, Al-Hajj, Samar, Alhassan, Robert Kaba, Ali, Saqib, Alicandro, Gianfranco, Alijanzadeh, Mehran, Aljunid, Syed Mohamed, Almasi-Hashiani, Amir, Almasri, Nihad A., Al-Mekhlafi, Hesham M., Alonso, Jordi, Al-Raddadi, Rajaa M., Altirkawi, Khalid A., Alvis-Guzman, Nelson, Amare, Azmeraw T., Amini, Saeed, Aminorroaya, Arya, Amit, Arianna Maever L., Amugsi, Dickson A., Ancuceanu, Robert, Anderlini, Deanna, Andrei, Catalina Liliana, Androudi, Sofia, Ansari, Fereshteh, Ansari, Iman, Antonio, Carl Abelardo T., Anvari, Davood, Anwer, Razique, Appiah, Seth Christopher Yaw, Arabloo, Jalal, Arab-Zozani, Morteza, Ärnlöv, Johan, Asaad, Malke, Asadi-Aliabadi, Mehran, Asadi-Pooya, Ali A., Atout, Maha Moh'd Wahbi, Ausloos, Marcel, Avenyo, Elvis Korku, Avila-Burgos, Leticia, Quintanilla, Beatriz Paulina Ayala, Ayano, Getinet, Aynalem, Yared Asmare, Azari, Samad, Azene, Zelalem Nigussie, Bakhshaei, Mohammad Hossein, Bakkannavar, Shankar M., Banach, Maciej, Banik, Palash Chandra, Barboza, Miguel A., Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Basu, Sanjay, Baune, Bernhard T., Bayati, Mohsen, Bedi, Neeraj, Beghi, Ettore, Bekuma, Tariku Tesfaye, Bell, Arielle Wilder, Bell, Michelle L., Benjet, Corina, Bensenor, Isabela M., Berhe, Abadi Kidanemariam, Berhe, Kidanemaryam, Berman, Adam E., Bhagavathula, Akshaya Srikanth, Car, Lorainne Tudor

“…Background: Documentation of patterns and long-term trends in mortality in young people, which reflect huge changes in demographic and social determinants of adolescent health, enables identification of global investment priorities for this age group. …”
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Creative ageing in Singapore : a population study on participatory arts engagement and wellbeing among adults aged 50 and above by Ma, Stephanie Hilary Xinyi

“…Control variables included demographic information, self-reported health status, intensity and frequency of physical exercises. …”
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You must be myths-taken: examining belief in falsehoods during the COVID-19 health crisis by Lwin, May Oo, Sheldenkar, Anita, Tng, Pei Ling

“…However, belief in myths varied across population demographics, with ethnic minorities (Indians and Malays), females, young adults and those with lower education levels being more susceptible to myths than their counterparts (p < 0.05). …”
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Risk prediction models to guide antibiotic prescribing : a study on adult patients with uncomplicated upper respiratory tract infections in an emergency department by Wong, Joshua Guoxian, Aung, Aung-Hein, Lian, Weixiang, Lye, David Chien, Ooi, Chee-Kheong, Chow, Angela

“…Confirmatory tests were performed using the multiplex polymerase chain reaction (PCR) test for respiratory viruses and point-of-care test for Creactive protein. Demographic, clinical and laboratory data were extracted from the hospital electronic medical records.Seventy percent of the data was used for training and the remaining 30% was used for validation. …”
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Food environments and obesity: a geospatial analysis of the South Asia Biobank, income and sex inequalities by Atanasova, Petya, Kusuma, Dian, Pineda, Elisa, Anjana, Ranjit Mohan, De Silva, Laksara, Hanif, Abu A. M., Hasan, Mehedi, Hossain, Md Mokbul, Indrawansa, Susantha, Jayamanne, Deepal, Jha, Sujeet, Kasturiratne, Anuradhani, Katulanda, Prasad, Khawaja, Khadija I., Kumarendran, Balachandran, Mrida, Malay K., Rajakaruna, Vindya, Chambers, John Campbell, Frost, Gary, Sassi, Franco, Miraldo, Marisa

“…Individual-level data (demographic, socio-economic, and health characteristics) were combined with exposure to healthy and unhealthy food environments measured with geolocations of food outlets (obtained through ground-truth surveys) within 300 m buffer zones around participants' homes. …”
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Implementation of occupational safety and health management system in reducing ergonomic risk among certified and uncertified automotive industry workers by Ikpegbu, Mavis Amarachi

“…Also linear regression test revealed that there is a significant relationship between ergonomics risk and demographic factors. Therefore certification fosters the implementation of OSHMS among workers.…”
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Sociospatial reframing of walking through inclusive streets and urban heritage by Wang, Yongcheng

“…Then, to reach a wider demographic, a street-intercept survey was conducted to investigate perceived importance within a set of six different inclusive street design dimensions in relation to the movement and activity functions of streets. …”
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Exploring biomechanical variations in ankle joint injuries among Latin dancers with different stance patterns: utilizing OpenSim musculoskeletal models by Gao, Xiangli, Xu, Datao, Baker, Julien S, Teo, Ee-Chon, Liang, Minjun, Gu, Yaodong

“…Background: Dancers represent the primary demographic affected by ankle joint injuries. In certain movements, some Latin dancers prefer landing on the Forefoot (FT), while others prefer landing on the Entire foot (ET). …”
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Global, regional, and national burden of stroke and its risk factors, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021 by Feigin, VL, Abate, MD, Abate, YH, Bandyopadhyay, S, Bennett, DA, Lacey, B, Newton, CRJ

“…We also calculated burden of stroke attributable to 23 risk factors and six risk clusters (air pollution, tobacco smoking, behavioural, dietary, environmental, and metabolic risks) at the global and regional levels (21 GBD regions and Socio-demographic Index [SDI] quintiles), using the standard GBD methodology. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. …”

Associations between health literacy and health care utilization and mortality in patients with coexisting diabetes and end-stage renal disease : a prospective cohort study by Griva, Konstantina, Loong, Russel K. L., Nandakumar, Mooppil, Rajeswari, Moothathamby, Khoo, Eric Y. H., Lee, Vanessa Y. W., Kang, Augustine W. C., Osborne, Richard H., Brini, Stefano, Newman, Stanton P.

“…After adjusting for demographic and clinical factors, the HLQ domain Actively Managing My Health remained independently associated with lower rates of hospitalization (incidence rate ratio (IRR) = 0.674, 95% CI [0.490, 0.925], p = .02) and mortality (hazard ratio = 0.382, 95% CI [0.160, 0.848], p = .02). …”
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Wage premium in Singapore. by Tan, Ruo Hui., Tan, Yan Yu., Lee, Wai Meng.

“…We carried out our survey over 200 Singaporeans and Singapore Permanent Residents between the ages of 20 to 59 based on the demographic of Singapore. This sample size allows us to properly execute both the Ordinary Least Squares and Tobit and Probit methods to draw the relationships between the variables. …”
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The association between the housing structure and continued breastfeeding in two Southern African countries by Khanyile, Ntuthuko, McLaren, Shawn, Fairbrother, Una

“…Data were extracted, with permission, from the Demographic and Health Survey(DHS), a program which provides nutrition surveillance in 90+ countries. …”
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Do dual-mobility cups reduce revision risk in femoral neck fractures compared with conventional tha designs? An international meta-analysis of arthroplasty registries by Farey, JE, Masters, J, Cuthbert, AR, Iversen, P, van Steenbergen, LN, Prentice, HA, Adie, S, Sayers, A, Whitehouse, MR, Paxton, EW, Costa, ML, Overgaard, S, Rogmark, C, Rolfson, O, Harris, IA

“…</p> <p><strong>Methods: </strong>Six member registries of the International Society of Arthroplasty Registries (from Australia, Denmark, Sweden, the Netherlands, the United Kingdom, and the United States) provided custom aggregate data reports stratified by acetabular cup type (dual-mobility or conventional THA) in primary THA for hip fracture between January 1, 2002, and December 31, 2019; surgical approach; and patient demographic data (sex, mean age, American Society of Anesthesiologists class, and BMI). …”

Predicting glaucoma progression using deep learning framework guided by generative algorithm by Hussain, Shaista, Chua, Jacqueline, Wong, Damon, Lo, Justin, Kadziauskiene, Aiste, Asoklis, Rimvydas, Barbastathis, George, Schmetterer, Leopold, Yong, Liu

“…We used OCT images, VF values, demographic and clinical data of 86 glaucoma patients with five visits over 12 months. …”
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Employment of a high throughput functional assay to define the critical factors that influence vaccine induced cross-variant neutralizing antibodies for SARS-CoV-2 by Gu, Yue, Shunmuganathan, Bhuvaneshwari, Qian, Xinlei, Gupta, Rashi, Tan, Rebecca S. W., Kozma, Mary, Purushotorman, Kiren, Murali, Tanusya M., Tan, Nikki Y. J., Preiser, Peter Rainer, Lescar, Julien, Nasir, Haziq, Somani, Jyoti, Tambyah, Paul A., Smith, Kenneth G. C., Renia, Laurent, Ng, Lisa F. P., Lye, David C., Young, Barnaby E., MacAry, Paul A.

“…These data illustrate how key virological factors such as immune escape mutations combined with host demographic factors such as age and sex of the vaccinated individual influence the strength and duration of cross-protective serological immunity for COVID-19.…”
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Global, regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990–2021: a systematic analysis from the Global Burden... by Bender, RG, Sirota, SB, Swetschinski, LR, Berkley, JA, Eyre, DW, McManigal, B, Pollard, AJ, Roberts, T, Runghien, T, Sartorius, B

“…<p><b>Findings</b></p> Globally, in 2021, we estimated 344 million (95% uncertainty interval [UI] 325–364) incident episodes of LRI, or 4350 episodes (4120–4610) per 100 000 population, and 2·18 million deaths (1·98–2·36), or 27·7 deaths (25·1–29·9) per 100 000. 502 000 deaths (406 000–611 000) were in children younger than 5 years, among which 254 000 deaths (197 000–320 000) occurred in countries with a low Socio-demographic Index. Of the 18 modelled pathogen categories in 2021, S pneumoniae was responsible for the highest proportions of LRI episodes and deaths, with an estimated 97·9 million (92·1–104·0) episodes and 505 000 deaths (454 000–555 000) globally. …”