scholarly journals What has women’s reproductive health decision-making capacity and other factors got to do with pregnancy termination in sub-Saharan Africa? evidence from 27 cross-sectional surveys

PLoS ONE ◽  
2020 ◽  
Vol 15 (7) ◽  
pp. e0235329
Author(s):  
Abdul-Aziz Seidu ◽  
Bright Opoku Ahinkorah ◽  
Edward Kwabena Ameyaw ◽  
Amu Hubert ◽  
Wonder Agbemavi ◽  
...  
PLoS ONE ◽  
2020 ◽  
Vol 15 (7) ◽  
pp. e0235601
Author(s):  
Bright Opoku Ahinkorah ◽  
John Elvis Hagan ◽  
Abdul-Aziz Seidu ◽  
Francis Sambah ◽  
Faustina Adoboi ◽  
...  

2012 ◽  
Vol 17 (5) ◽  
pp. 797-808 ◽  
Author(s):  
Cynthia Fair ◽  
Lori Wiener ◽  
Sima Zadeh ◽  
Jamie Albright ◽  
Claude Ann Mellins ◽  
...  

protocols.io ◽  
2018 ◽  
Author(s):  
Kate Grindlay ◽  
Phyllis Dako ◽  
Thoai D ◽  
Gillian Eva ◽  
Leonard Gobah ◽  
...  

2020 ◽  
Author(s):  
Abdul-Aziz Seidu ◽  
Joseph Kojo Oduro ◽  
Bright Opoku Ahinkorah ◽  
Eugene Budu ◽  
Francis Appiah ◽  
...  

Abstract IntroductionGlobal commitment to stop HIV and ensure access to HIV treatment call for women empowering as these efforts play a major role in mother to child transmission. We explored the association between women decision-making capacity and HIV testing in sub-Saharan Africa (SSA). Materials and methodsWe used data from current Demographic and Health Surveys (DHS) conducted between January 1, 2010 and December 31, 2016 in 30 countries within SSA. At the descriptive level, we calculated the prevalence of women who had undergone HIV testing and decision-making capacity in each of the countries as well as prevalence of HIV testing across their socio-demographic characteristics. We used Binary Logistic Regression to explore the likelihood of HIV testing by decision-making capacity and socio-demographic characteristics at 5% margin of error. The results were presented as Crude Odds Ratios (CORs) and Adjusted Odds Ratios (AORs). ResultsWe found that overall, 10.0% of women had decision-making with Nigeria (4.5%) and Zimbabwe (21.3%) recording the least and the highest respectively. In terms of HIV testing, the prevalence of HIV testing in the 30 SSA countries was 64.4%, with Guinea (12.8%) having the least. The highest occurred in Lesotho (99%) and Rwanda (99%). Women who had capacity to make decisions had higher likelihood of HIV testing [AOR=1.04, CI=1.02–1.09]. Women from Rwanda had the highest likelihood of HIV testing [AOR=53.92, CI=41.31–70.37] with women from Guinea having the least likelihood [AOR=0.10, CI=0.08–0.11]. Other determinants to HIV testing were level of education, wealth status, believing that a healthy-looking person can have HIV, watching television almost every day, age and place of residence.Conclusion SSA countries intending to improve HIV testing need to incorporate women decision-making capacity strategies in terms of education and counselling into the available policies. This is essential because our study indicates that as women are able to make decisions in their households, the possibility for them to test for their HIV status increases.


2021 ◽  
pp. 073346482110247
Author(s):  
Guillermo Salinas-Escudero ◽  
María Fernanda Carrillo-Vega ◽  
Carmen García-Peña ◽  
Silvia Martínez-Valverde ◽  
Luis David Jácome-Maldonado ◽  
...  

Objective: To determine the association of frailty with out-of-pocket expenses (OOPEs) during the last year of life of Mexican older adults. Methods: Cross-sectional secondary analysis of the Mexican Health and Aging Study (MHAS), a representative population-based cohort study. Health care expenses were estimated, and a probit model was used to estimate the probability that older adults had OOPE. A general linear model was applied to explain OOPE magnitudes. Results: A total of 55.8% of individuals reported having OOPE with a mean of 3,261 USD. Average OOPE for hospitalization during the last year of life was 7,011.9 USD. Older adults taking their own medical decisions during the last year of life expended less than those who did not. Conclusion: No affiliation to health services, frailty, and health decision-making by others increased the probability of OOPE. The magnitude is determined by age, hospitalization, medical visits, affiliation, frailty, and health decision-making by others.


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