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Journal articles on the topic 'Sociodemographic differences'

Author: Grafiati

Published: 11 December 2022

Last updated: 19 July 2025

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1

Wen, X., K. L. Kong, R. D. Eiden, N. N. Sharma, and C. Xie. "Sociodemographic Differences and Infant Dietary Patterns." PEDIATRICS 134, no. 5 (2014): e1387-e1398. http://dx.doi.org/10.1542/peds.2014-1045.

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2

Yordanova Stoyanova, Stanislava. "SOCIODEMOGRAPHIC DIFFERENCES IN INTEREST IN ONE’S LOOKS." Anthropological Researches and Studies 10, no. 1 (2020): 53–63. http://dx.doi.org/10.26758/10.1.6.

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Cheah, Yong Kang, Chien Huey Teh, and Hock Kuang Lim. "Sociodemographic Differences in Smoking Knowledge in Malaysia." Journal of Drug Issues 49, no. 2 (2019): 355–68. http://dx.doi.org/10.1177/0022042618821195.

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The objective of the present study is to examine the sociodemographic determinants of amount of smoking knowledge in Malaysia. Data are obtained from the Global Adult Tobacco Survey (GATS). The GATS uses a multistage stratified sampling. A total of 4,153 respondents are used for analyses. The effects of sociodemographic factors on smoking knowledge are examined using a negative binomial regression. Age, wealth index, education, ethnicity, house locality, and smoking behavior are significantly associated with smoking knowledge. In particular, there are negative relationships between smoking kno

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Meyer, Katie A., David K. Guilkey, Shu Wen Ng, et al. "Sociodemographic Differences in Fast Food Price Sensitivity." JAMA Internal Medicine 174, no. 3 (2014): 434. http://dx.doi.org/10.1001/jamainternmed.2013.13922.

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Watts, Ashley L., JaiAnna F. Megahan, William E. Conlin, Mark I. Doss, and Kenneth J. Sher. "Sociodemographic differences in youth alcohol sipping's nomological network." Alcoholism: Clinical and Experimental Research 46, no. 4 (2022): 589–99. http://dx.doi.org/10.1111/acer.14790.

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6

Gustafson, Per, and Urban Fransson. "Age Differences Between Spouses: Sociodemographic Variation and Selection." Marriage & Family Review 51, no. 7 (2015): 610–32. http://dx.doi.org/10.1080/01494929.2015.1060289.

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7

Greenfield, Patricia M. "Sociodemographic Differences Within Countries Produce Variable Cultural Values." Journal of Cross-Cultural Psychology 45, no. 1 (2013): 37–41. http://dx.doi.org/10.1177/0022022113513402.

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8

Benda, Natalie C., Ruth M. Masterson Creber, Roberta Scheinmann, et al. "Sociodemographic Differences in Perspectives on Postpartum Symptom Reporting." Applied Clinical Informatics 15, no. 04 (2024): 692–99. http://dx.doi.org/10.1055/s-0044-1788328.

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Abstract Objective The overall goal of this work is to create a patient-reported outcome (PRO) and decision support system to help postpartum patients determine when to seek care for concerning symptoms. In this case study, we assessed differences in perspectives for application design needs based on race, ethnicity, and preferred language. Methods A sample of 446 participants who reported giving birth in the past 12 months was recruited from an existing survey panel. We sampled participants from four self-reported demographic groups: (1) English-speaking panel, Black/African American race, no

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Schoenfeld, Elinor R., George S. Leibowitz, Yu Wang, et al. "Geographic, Temporal, and Sociodemographic Differences in Opioid Poisoning." American Journal of Preventive Medicine 57, no. 2 (2019): 153–64. http://dx.doi.org/10.1016/j.amepre.2019.03.020.

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10

Chavarria Minera, Cindy Elizabeth, Aurelio José Figueredo, and Laura Gail Lunsford. "Do Slower Life History Strategies Reduce Sociodemographic Sex Differences?" Journal of Methods and Measurement in the Social Sciences 6, no. 1 (2015): 1. http://dx.doi.org/10.2458/jmm.v6i1.18771.

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This study examines the relations between sociodemographic sex differences and life history strategies in the populations of Mexican States. Sex differences in anatomy and behavior was measured with traits such as educational achievement, mortality, and morbidity. The data were obtained from the Instituto Nacional de Estadística y Geografía (INEGI) and sampled from thirty-one Mexican states and the Federal District (N = 32). An extension analysis was performed selecting only the sex ratio variables that had a correlation with the slow Life History factor greater than or equal to an absolute va

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Chavarria Minera, Cindy Elizabeth, Aurelio José Figueredo, and Laura Gail Lunsford. "Do Slower Life History Strategies Reduce Sociodemographic Sex Differences?" Journal of Methods and Measurement in the Social Sciences 6, no. 1 (2015): 1. http://dx.doi.org/10.2458/v6i1.18771.

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This study examines the relations between sociodemographic sex differences and life history strategies in the populations of Mexican States. Sex differences in anatomy and behavior was measured with traits such as educational achievement, mortality, and morbidity. The data were obtained from the Instituto Nacional de Estadística y Geografía (INEGI) and sampled from thirty-one Mexican states and the Federal District (N = 32). An extension analysis was performed selecting only the sex ratio variables that had a correlation with the slow Life History factor greater than or equal to an absolute va

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Groessl, Erik J., Theodore G. Ganiats, and Andrew J. Sarkin. "Sociodemographic Differences in Quality of Life in Rheumatoid Arthritis." PharmacoEconomics 24, no. 2 (2006): 109–21. http://dx.doi.org/10.2165/00019053-200624020-00002.

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13

Stevens, Jack, Jeffrey Harman, Ann Pakalnis, Warren Lo, and Jessica Prescod. "Sociodemographic Differences in Diagnosis and Treatment of Pediatric Headache." Journal of Child Neurology 25, no. 4 (2009): 435–40. http://dx.doi.org/10.1177/0883073809343314.

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14

Bryce, C. L., D. C. Angus, R. M. Arnold, et al. "Sociodemographic Differences in Early Access to Liver Transplantation Services." American Journal of Transplantation 9, no. 9 (2009): 2092–101. http://dx.doi.org/10.1111/j.1600-6143.2009.02737.x.

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15

Martelin, T., S. Koskinen, and T. Valkonen. "Sociodemographic Mortality Differences among the Oldest Old in Finland." Journals of Gerontology Series B: Psychological Sciences and Social Sciences 53B, no. 2 (1998): S83—S90. http://dx.doi.org/10.1093/geronb/53b.2.s83.

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16

Webster, Noah J., Kristine J. Ajrouch, and Toni C. Antonucci. "Sociodemographic Differences in Humility: The Role of Social Relations." Research in Human Development 15, no. 1 (2017): 50–71. http://dx.doi.org/10.1080/15427609.2017.1414670.

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17

Goding Sauer, Ann, Priti Bandi, Debbie Saslow, Farhad Islami, Ahmedin Jemal, and Stacey A. Fedewa. "Geographic and sociodemographic differences in cervical cancer screening modalities." Preventive Medicine 133 (April 2020): 106014. http://dx.doi.org/10.1016/j.ypmed.2020.106014.

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18

Cheah, Yong Kang, Chien Huey Teh, and Hock Kuang Lim. "Sociodemographic differences in awareness of e-cigarette in Malaysia." Journal of Oncological Sciences 5, no. 2 (2019): 54–59. http://dx.doi.org/10.1016/j.jons.2019.04.001.

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19

Guagnano, Gregory A., and Nancy Markee. "Regional differences in the sociodemographic determinants of environmental concern." Population and Environment 17, no. 2 (1995): 135–49. http://dx.doi.org/10.1007/bf02208385.

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20

Almasi, Tobias, Elisabeth Exner-Grave, Daniela Ohlendorf, and Eileen M. Wanke. "Musculoskeletal and Sociodemographic Gender Differences between Vocational Ballet Students." Applied Sciences 13, no. 1 (2022): 108. http://dx.doi.org/10.3390/app13010108.

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Introduction: Studies of vocational ballet students are sparce. In particular, there is a lack of gender comparisons. The aim of the present study, therefore, was to give a musculoskeletal and sociodemographic description of the typical vocational ballet student in gender comparison. Methods: In this study, n = 414 female and n = 192 male students of the John Cranko School (JCS), aged between 5 and 22 years (Mean ± SD: 13.9 ± 3.5), were examined by an experienced orthopedist and dance physician. Results: Males started ballet (5.8/8.2 years, p < 0.001) and training at later age than females

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21

Pharr, Jennifer R., Nancy L. Lough, and Mary Angela Terencio. "Health and Sociodemographic Differences between Individual and Team Sport Participants." Sports 7, no. 6 (2019): 150. http://dx.doi.org/10.3390/sports7060150.

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Physical activity (PA) has been widely recognized as an avenue to improve health. Researchers have also found better health outcomes among adults who participate in sport when compared to adults who participate in other forms of PA. However, little is known about the health differences between those who participate in individual versus team sport. The purpose of the study was to identify differences in chronic diseases, conditions, or risk factors between individual and team sport participants. This study was a secondary analysis of data from the national Behavioral Risk Factor Surveillance Sy

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22

Azagba, Sunday, Keely Latham, and Lingpeng Shan. "Sociodemographic Differences in Secondhand Smoke Exposure in the United States." Health Education & Behavior 47, no. 4 (2020): 602–10. http://dx.doi.org/10.1177/1090198120925414.

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Background. Socioeconomic disparities in secondhand smoke (SHS) exposure exist among nonsmokers. The present study examined the prevalence and socioeconomic disparities of both objective and self-reported measures of SHS exposure in various indoor environments among U.S. nonsmokers. Method. Data were drawn from the 2013–2014 and 2015–2016 National Health and Nutrition Examination Survey. The prevalence of objective measures of SHS (nonsmokers with serum cotinine levels of 0.05–10 ng/mL) and the self-reported SHS exposure status in restaurants, cars, and homes other than their own were examined

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23

Agawu, Atu, Alison M. Buttenheim, Lynne Taylor, Lihai Song, Alexander G. Fiks, and Kristen A. Feemster. "Sociodemographic Differences in Human Papillomavirus Vaccine Initiation by Adolescent Males." Journal of Adolescent Health 57, no. 5 (2015): 506–14. http://dx.doi.org/10.1016/j.jadohealth.2015.07.002.

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24

Kracht, Chelsea L., Elizabeth K. Webster, and Amanda E. Staiano. "Sociodemographic Differences in Young Children Meeting 24-Hour Movement Guidelines." Journal of Physical Activity and Health 16, no. 10 (2019): 908–15. http://dx.doi.org/10.1123/jpah.2019-0018.

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Background: Little is known about variation in meeting the 24-Hour Movement Guidelines (including physical activity [PA], sleep, and screen time [ST]) in early childhood. The aim was to evaluate sociodemographic differences in meeting the 24-Hour Movement Guidelines. Methods: Parents of 3–4 year old children reported sociodemographic information and ST. Sleep and PA were measured using accelerometry, and height and weight were objectively measured. The 24-Hour Movement Guidelines include daily PA (total PA: ≥3 h; including ≥1 h of moderate to vigorous), sleep (10–13 h), and ST (≤1 h). Meeting

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25

Tadbi, Azadeh Andisheh, Davood Mehrabani, and Seyed Taghi Heydari. "Sociodemographic and Etiologic Differences of Malignant Orofacial Tumors in Iran." Journal of Craniofacial Surgery 20, no. 3 (2009): 837–40. http://dx.doi.org/10.1097/scs.0b013e3181a2d62a.

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26

Mattsson, P., T. Tomson, O. Eriksson, L. Brannstrom, and G. R. Weitoft. "Sociodemographic differences in antiepileptic drug prescriptions to adult epilepsy patients." Neurology 74, no. 4 (2010): 295–301. http://dx.doi.org/10.1212/wnl.0b013e3181cbcd5c.

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27

Blackwell, Courtney K., Traci Bekelman, Shivani Bakre, et al. "Sociodemographic differences in parental hesitancy to the COVID-19 vaccine." Vaccine 55 (May 2025): 127041. https://doi.org/10.1016/j.vaccine.2025.127041.

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28

Lo, Siu Hing, Jo Waller, Charlotte Vrinten, Lindsay Kobayashi, and Christian von Wagner. "Social Cognitive Mediators of Sociodemographic Differences in Colorectal Cancer Screening Uptake." BioMed Research International 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/165074.

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Background. This study examined if and how sociodemographic differences in colorectal cancer (CRC) screening uptake can be explained by social cognitive factors.Methods. Face-to-face interviews were conducted with individuals aged 60–70 years (n=1309) living in England as part of a population-based omnibus survey.Results. There were differences in screening uptake by SES, marital status, ethnicity, and age but not by gender. Perceived barriers (stand.b=-0.40,p<0.001), social norms (stand.b=0.33,p<0.001), and screening knowledge (stand.b=0.17,p<0.001) had independent associations with

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29

Herman, Sriyana, Syamsuriati, Rika Handayani, et al. "Differences of Maternal Sociodemographic Characteristics with Term and Preterm Birth Among 17 Hospitals In South Sulawesi." Public Health of Indonesia 11, no. 1 (2025): 75–81. https://doi.org/10.36685/phi.v11i1.917.

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Background:Maternal sociodemographic characteristics play a crucial role in identifying preterm labor, enabling early intervention to prevent its occurrence and recurrence. Understanding these characteristics can support the development of preventive strategies and improve maternal and neonatal health outcomes. Objective:This study aims to determine whether there are significant differences in the sociodemographic characteristics of mothers experiencing term and preterm labor across hospitals in Makassar City. Method:This study employed an observational analytical design involving 257 mothers

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30

Roudijk, Bram, A. Rogier T. Donders, Peep F. M. Stalmeier, et al. "Cultural Values: Can They Explain Differences in Health Utilities between Countries?" Medical Decision Making 39, no. 5 (2019): 605–16. http://dx.doi.org/10.1177/0272989x19841587.

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Introduction. Health utilities are widely used in health care. The distributions of utilities differ between countries; some countries more often report worse than dead health states, while mild states are valued more or less the same. We hypothesize that cultural values explain these country-related utility differences. Research Question. What is the effect of sociodemographic background, methodological factors, and cultural values on differences in health utilities? Methods and Analyses. Time tradeoff data from 28 EQ-5D valuation studies were analyzed, together with their sociodemographic va

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Phulkerd, Sirinya, Sasinee Thapsuwan, Natjera Thongcharoenchupong, Rossarin Soottipong Gray, and Aphichat Chamratrithirong. "Sociodemographic differences affecting insufficient fruit and vegetable intake: a population-based household survey of Thai people." Journal of Health Research 34, no. 5 (2020): 419–29. http://dx.doi.org/10.1108/jhr-07-2019-0150.

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PurposeThe sociodemographic determinants of insufficient fruit and vegetable (FV) consumption in the general population in Thailand remain understudied. The purpose of this study was to investigate the association between sociodemographic characteristics and insufficient FV consumption in Thailand.Design/methodology/approachThis nationally representative survey employed a cross-sectional multi-stage sampling design. A total of 6,991 individuals aged 15 years or older participated in the study. Information on participants' FV consumption and sociodemographic characteristics were collected via q

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32

Link, B. G., and J. C. Phelan. "Understanding sociodemographic differences in health--the role of fundamental social causes." American Journal of Public Health 86, no. 4 (1996): 471–73. http://dx.doi.org/10.2105/ajph.86.4.471.

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33

Štemberger-Kolnik, Tamara, Andreja Ljubič, Bojana Filej, Mojca Poredoš, and Boris Miha Kaučič. "Differences in Health Literacy of Older Adults According to Sociodemographic Characteristics." Open Access Macedonian Journal of Medical Sciences 10, E (2022): 1556–63. http://dx.doi.org/10.3889/oamjms.2022.8335.

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BACKGROUND: The research is based on the concept of health literacy. This is the “sixth vital sign” to navigating the healthcare system and raising self-efficacy in the field of healthcare. AIM: The study aim was to present the health literacy of the elderly in the Savinja statistical region in Slovenia. METHODS: The study was based on a non-experimental quantitative research approach. The study included 199 elderly people aged 65 and more, without the presence of dementia. The data were collected using the Health Literacy and Montreal Cognitive Assessment questionnaire. We used a

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34

Hidalgo, Nina Jamilette, Laura Lee McIntyre, and Ellen Hawley McWhirter. "Sociodemographic differences in parental satisfaction with an autism spectrum disorder diagnosis." Journal of Intellectual and Developmental Disability 40, no. 2 (2015): 147–55. http://dx.doi.org/10.3109/13668250.2014.994171.

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35

Landis, Rachel K., Jonathan S. Levin, Brendan Saloner, et al. "Sociodemographic differences in quality of treatment to Medicaid enrollees receiving buprenorphine." Substance Abuse 43, no. 1 (2022): 1057–71. http://dx.doi.org/10.1080/08897077.2022.2060424.

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36

El Habiby, Mahmoud, Hanan H. El Rassas, Mahmoud Morsy, Nesreen Mohsen, and Fatma Ezzat. "Gender Differences in Clinical and Sociodemographic Patterns of Substance Use Disorder." Addictive Disorders & Their Treatment 19, no. 3 (2020): 174–84. http://dx.doi.org/10.1097/adt.0000000000000198.

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37

Kühle, Anna-Maria, and Jürgen Wacker. "Sociodemographic Differences in Health Awareness and Oral Health in Pregnant Women." Geburtshilfe und Frauenheilkunde 80, no. 08 (2020): 834–43. http://dx.doi.org/10.1055/a-1205-0601.

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Abstract Objective The aim of this study was to determine the present oral health status of pregnant women depending on selected sociodemographic differences and deduce any resulting consequences for health prevention. Methods The participantsʼ data of relevance to the study such as age, school leaving qualification, migration background, smoking habits or last dentist visit were recorded using a questionnaire. The subsequent dental check-up concentrated on open carious lesions, any initiated root canal treatments and missing teeth. Finally, the Periodontal Screening Index was recorded to diag

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Rotk, o., n. Koistine, and n. Jantune. "SOCIODEMOGRAPHIC DIFFERENCES OF THE POPULATION EXPOSURE TO FINE PARTICLES IN HELSINKI." Epidemiology 9, Supplement (1998): S88. http://dx.doi.org/10.1097/00001648-199807001-00268.

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39

Sinclair, Sarah, David Hammond, and Samantha Goodman. "Sociodemographic Differences in the Comprehension of Nutritional Labels on Food Products." Journal of Nutrition Education and Behavior 45, no. 6 (2013): 767–72. http://dx.doi.org/10.1016/j.jneb.2013.04.262.

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40

Arcan, Chrisa, Martha Y. Kubik, Jayne A. Fulkerson, and Mary Story. "Sociodemographic Differences in Selected Eating Practices among Alternative High School Students." Journal of the American Dietetic Association 109, no. 5 (2009): 823–29. http://dx.doi.org/10.1016/j.jada.2009.02.001.

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41

Wagner, Anna C., Michael J. Parks, and Megan E. Patrick. "How do high school seniors get marijuana? Prevalence and sociodemographic differences." Addictive Behaviors 114 (March 2021): 106730. http://dx.doi.org/10.1016/j.addbeh.2020.106730.

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42

Quevedo, Kathia Larissa, Alejandra Jáuregui, Claudia Nieto, et al. "Sociodemographic differences in nutrition labels effect on Chilean and Mexican youth." Revista Panamericana de Salud Pública 48 (April 4, 2024): 1. http://dx.doi.org/10.26633/rpsp.2024.33.

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Objective. To examine sociodemographic differences in the awareness, understanding, use and effect of nutrition labels among Mexican and Chilean youth. Methods. Online surveys among youth (10-17 years) were obtained in 2019 (n=2631). Participants reported their awareness, understanding, and use of their country-specific nutrition facts tables (NFT) and front-of-pack labels (FOPL) (Chile: warning labels [WLs]; Mexico: guideline daily amounts [GDA]). Additionally, participants reported their perceived healthfulness of a sweetened fruit drink after viewing one of six versions of it with different

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Shaiban, Amenah Jamal, and Sura Hameed Nayyef. "Helicobacter Pylori and Sociodemographic Characteristics Distribution." Journal for Research in Applied Sciences and Biotechnology 3, no. 1 (2024): 253–55. http://dx.doi.org/10.55544/jrasb.3.1.38.

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Introduction and Aim: Helicobacter pylori is a gram-negative bacterium that affects up to half of the world's population, particularly in poorer nations. It is the leading cause of chronic gastritis, ulcers, gastric lymphoma, and gastric cancer, with more frequent cases in children and adolescents. Transmission can occur through fecal-oral, gastro-oral, oral-oral, or sexual means. The infection is caused by H. pylori's urease activity, invasion of host gastric epithelial cells, and adherence to host cell receptors. Early treatment can enhance gastric protection. Materials and Methods: Between

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Büchi, Moritz, Natascha Just, and Michael Latzer. "Modeling the second-level digital divide: A five-country study of social differences in Internet use." New Media & Society 18, no. 11 (2016): 2703–22. http://dx.doi.org/10.1177/1461444815604154.

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Based on representative surveys on Internet use, this article advances comparative research on the second-level digital divide by modeling Internet usage disparities for five countries with narrowing access gaps. Four core Internet usage types are constructed and predicted by sociodemographic variables in a structural model. Overall, the findings confirm the recently identified shift in the digital divide from access to usage in five further countries. Results show that sociodemographics alone account for up to half of the variance in usage in these high-penetration countries, with age being t

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Setiawati, Ni Made. "Differences in Sociodemographic Characteristics of Schizophrenia Patients between Rural and Urban Areas in Badung Regency." WMJ (Warmadewa Medical Journal) 5, no. 2 (2020): 76–84. http://dx.doi.org/10.22225/wmj.5.2.1831.76-84.

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Several studies have found differences in the incidence of schizophrenia in rural and urban areas. Most of the studies found that schizophrenia incidence was higher in urban areas. The purpose of this study was to determine differences in sociodemographic characteristics of schizophrenic patients according to rural or urban conditions in their homes. An observational, cross-sectional analytic, study conducted. The sample in this study were 503 people who had been diagnosed with schizophrenia recorded at community health centres in Badung Regency until October 2019. Sociodemographic data of pat

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Herman, Sriyana, Budi Santoso, and Hermanto Tri Djoewono. "DIFFERENCES OF MATERNAL SOCIODEMOGRAPHIC CHARACTERISTICS WITH SPONTANEOUS PRETERM BIRTH AMONG HOSPITALS IN INDONESIA: A COMPARATIVE STUDY." Public Health of Indonesia 4, no. 4 (2018): 146–53. http://dx.doi.org/10.36685/phi.v4i4.215.

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Background: Maternal sociodemographic characteristics can be used to prevent preterm birth.Objective: To identify differences in maternal sociodemographic characteristics with spontaneous preterm birth among hospitals in East Java, Indonesia.Methods: This was a descriptive study with comparative design in 134 mothers who experienced preterm birth at eight hospitals. Data were analyzed using Independent samples t-test.Result: Sixteen variables were significantly different in maternal sociodemographic characteristics with spontaneous preterm birth among eight hospitals, namely: gestational age (

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47

Eckert, G. J., R. Jackson, and M. Fontana. "Sociodemographic Variation of Caries Risk Factors in Toddlers and Caregivers." International Journal of Dentistry 2010 (2010): 1–17. http://dx.doi.org/10.1155/2010/593487.

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Objectives. Dental caries is the most common chronic childhood disease, with numerous identified risk factors. Risk factor differences could indicate the need to target caregiver/patient education/preventive care intervention strategies based on population and/or individual characteristics. The purpose of this study was to evaluate caries risk factors differences by race/ethnicity, income, and education.Methods. We enrolled 396 caregiver-toddler pairs and administered a 105-item questionnaire addressing demographics, access to care, oral bacteria transmission, caregiver's/toddler's dental and

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Parvu, Simona. "Sociodemographic Determinants and Students’ Perception Regarding Legislative Changes." Journal of Medicine and Life 13, no. 1 (2020): 16–20. http://dx.doi.org/10.25122/jml-2019-0082.

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The frequency of legislation changes and their utility is a subject of interest and always under debate with pro and contra arguments. In the current study, the perception of students regarding medical legislation changes was analyzed. In general, no statistically significant differences were found between the sub-groups of students, thus underlining a unitary perception. The general perception is that changes in legislation are made too often. Moreover, only a small part of the analyzed group agrees on the utility of these changes. Finally, it seems that income is the main driver for students

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Zijlmans, Jendé L., Sander Lamballais, Meike W. Vernooij, M. Arfan Ikram, and Annemarie I. Luik. "Sociodemographic, Lifestyle, Physical, and Psychosocial Determinants of Cognitive Reserve." Journal of Alzheimer's Disease 85, no. 2 (2022): 701–13. http://dx.doi.org/10.3233/jad-215122.

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Background: Cognitive reserve aims to explain individual differences in the susceptibility to the functional impact of dementia in the presence of equal amount of neuropathological damage. It is thought to be shaped by a combination of innate individual differences and lifetime exposures. Which determinants are associated with cognitive reserve remains unknown. Objective: The objective of this study was to investigate the associations of sociodemographic, lifestyle, physical, and psychosocial determinants with cognitive reserve, and potential sex differences. Methods: This cross-sectional stud

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Więch, Paweł, Dariusz Bazaliński, Izabela Sałacińska, and Monika Binkowska-Bury. "Relationship of selected sociodemographic factors and body composition in an open population of Rzeszów inhabitants participating in a health promoting event." Polish Journal of Public Health 126, no. 2 (2016): 68–71. http://dx.doi.org/10.1515/pjph-2016-0014.

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Abstract Introduction. The structure of the human body may vary greatly, depending on a number of factors, sociodemographic ones in particular. An analysis of the body composition makes it possible to assess the existing differences and provides broader insight into the multidimensional changes occuring to the human body. Aim. An investigation of the relationship between selected sociodemographic factors and body composition in an open population of Rzeszów residents. Material and methods. The study was performed on a group of 101 adults, aged 30-83. Their body composition was examined using b

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