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161por Wickenden, Mary, Hart, Tim G.B., Thompson, Stephen J., Davids, Yul D., Ngungu, Mercy“…RESULTS: Nearly 2000 people responded, representing different genders, impairments, races, socio-economic status, education and ages. Findings include: (1) negative economic and emotional impacts, (2) a lack of inclusive and accessible information, (3) reduced access to services, (4) uncertainty about government and non-government agencies’ support and (5)exacerbation of pre-existing disadvantages. …”
Publicado 2023
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162por Sánchez-Tabernero, Gonzalo, Hidalgo-Muñoz, Antonio R., Galán, José Ignacio, Tabernero, Carmen“…The main objective was to test an explanatory theoretical model of uranium mining project acceptance, based on the interrelation of sociodemographic variables (e.g., age, gender, economic and educational situation, and level of knowledge about uranium energy) and cognitive variables (e.g., environmental beliefs, risk, and benefit perceptions), along with the activation of an emotional balance in response to the proposal of constructing a uranium mine. …”
Publicado 2023
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163por Luan, Anna, Meyers, Natalie, Le Thua, Trung Hau, Dang, Hoang Thom, Phu, Quoc Viet, Auten, Brieanne, Chang, James“…BACKGROUND: Reconstructive surgical capacity remains inadequate in low- and middle-income countries, resulting in chronic disability and a significant economic toll. Education and training of the local surgical workforce to sustainably expand capacity have been increasingly encouraged, but economic analyses of these interventions are lacking. …”
Publicado 2022
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164por Mathalon, Daniel H., Hoffman, Ralph E., Watson, Todd D., Miller, Ryan M., Roach, Brian J., Ford, Judith M.“…P300 differences between SA and SZ patients could not be accounted for by variation in symptom severity, socio-economic status, education, or illness duration. Although both groups show similar deficits in processing speed, SA patients do not exhibit the P300 amplitude deficits evident in SZ, consistent with an underlying pathophysiological boundary between these disorders.…”
Publicado 2010
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165por Sun, Sun, Chen, Jiaying, Johannesson, Magnus, Kind, Paul, Xu, Ling, Zhang, Yaoguang, Burström, Kristina“…All descriptive analyses by socio-economic status (educational level, income and employment status) and by clinical characteristics (discomfort during the past 2 weeks, diagnosed with chronic diseases during the past 6 months and hospitalised during the past 12 months) were stratified by sex and age group. …”
Publicado 2010
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166“…RESULTS: Adjusted for age, childhood socio-economic position, education and smoking, childhood meat eating had sex-specific associations with white blood cell count and lymphocyte count, but not granulocyte count. …”
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167“…CONCLUSION: The problem of LBW is multidimensional, and hence, we need an integrated approach incorporating medical, social, economical and educational measures to address this issue.…”
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168por Pearce, Mark S., Mann, Kay D., Martin-Ruiz, Carmen, Parker, Louise, White, Martin, von Zglinicki, Thomas, Adams, Jean“…We investigated whether birth weight, infant growth, childhood cognition and adult height, as well as a range of lifestyle, socio-economic and educational factors, were associated with white blood cell telomere length at age 49–51 years. …”
Publicado 2012
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169por Si, Tian-Mei, Zhang, Yun-shu, Shu, Liang, Li, Ke-Qing, Liu, Xie-He, Mei, Qi-Yi, Wang, Gao-Hua, Bai, Pei-Shen, Ji, Li-Ping, Cheng, Xian-Sheng, Ma, Cui, Shi, Jian-Guo, Zhang, Hong-Yan, Ma, Hong, Yu, Xin“…A multiple logistic regression analysis revealed that age, sex, professional help-seeking behaviors, duration of illness, economic status, educational level, and clinical manifestations were associated with the use of clozapine. …”
Publicado 2012
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170por Wagner, Anita K., Graves, Amy J., Fan, Zhengyu, Walker, Saul, Zhang, Fang, Ross-Degnan, Dennis“…OBJECTIVE: Differences between women and men in political and economic empowerment, education, and health risks are well-documented. …”
Publicado 2013
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171“…Demographics (age and gender), socio-economic status (education and income), obesity, exercise, and ADL (bath, dress, toilet, transfer, heavy, shopping, meals) were measured. …”
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172por Hosseinpoor, Ahmad Reza, Bergen, Nicole, Koller, Theadora, Prasad, Amit, Schlotheuber, Anne, Valentine, Nicole, Lynch, John, Vega, Jeanette“…Inequality is multidimensional, such that the extent of inequality may vary considerably across different dimensions such as economic status, education, sex, and urban/rural residence. …”
Publicado 2014
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173por Tang, Nicole K. Y., McBeth, John, Jordan, Kelvin P., Blagojevic-Bucknall, Milisa, Croft, Peter, Wilkie, Ross“…Some [adjusted odds ratio (AOR) 1.57 (95% CI 1.15, 2.13)] and widespread [2.13 (1.66, 3.20)] pain increased the risk of insomnia onset at 3 years, after adjusting for age, gender, socio-economic class, education, anxiety, depression, sleep and co-morbidity at baseline. …”
Publicado 2015
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174por Rodrigues-de-Souza, Daiana Priscila, Palacios-Ceña, Domingo, Moro-Gutiérrez, Lourdes, Camargo, Paula Rezende, Salvini, Tania Fátima, Alburquerque-Sendín, Francisco“…The themes identified included: a) ways of perceiving and expressing pain—the participants focused constantly on their pain and anything outside it was considered secondary; b) the socio-familial environment as a modulator of pain—most participants stated that no one was able to understand the pain they were experiencing; c) religion as a modulator of pain—all Brazilian patients stated that religious belief affected the experience of pain; and d) socio-economic and educational status as a modulator of pain—the study reported that economic factors influenced the experience of pain. …”
Publicado 2016
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175“…Results from the log linear model suggest that economic status, educational level and pregnancy complications are significant predictors of OOPE. …”
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176por Hosseinpoor, Ahmad Reza, Nambiar, Devaki, Schlotheuber, Anne, Reidpath, Daniel, Ross, Zev“…The software, which contains the World Health Organization’s Health Equity Monitor database, allows the assessment of inequalities within a country using over 30 reproductive, maternal, newborn and child health indicators and five dimensions of inequality (economic status, education, place of residence, subnational region and child’s sex, where applicable). …”
Publicado 2016
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177por Aytaman, Ayse, Ojike, Nwakile, Zizi, Samantha, Pandi-Perumal, SR, Lukolic, Ismet, Bhanvadia, Amit, Nwamaghinna, Felix, Kamran, Haroon, Akivis, Alla, Bankole, Olusegun, Salifu, Moro O, McFarlane, Samy I“…CONCLUSION: Social and economic factors-education, insurance status, age, poverty level, and place of birth affect rates of vaccination among individuals with diabetes.…”
Publicado 2016
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178por Kirigia, Joses M, Sambo, Luis G, Nganda, Benjamin, Mwabu, Germano M, Chatora, Rufaro, Mwase, Takondwa“…The objective of this study was to examine the relationship between health insurance ownership and the demographic, economic and educational characteristics of South African women. …”
Publicado 2005
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179“…Results reveal that age, region, religion, socio-economic status, education, contraceptive use have significant (p<0.01) effects on women’s knowledge about HIV/AIDS. …”
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180por Cowman, Gretchen, Otipo, Shikanga, Njeru, Ian, Achia, Thomas, Thirumurthy, Harsha, Bartram, Jamie, Kioko, Jackson“…This study investigated the relationship between cholera occurrence in Kenya and various environmental and demographic factors related to water, sanitation, socio-economic status, education, urbanization and availability of health facilities during the time period 2008-2013. …”
Publicado 2017
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