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Objective As reports indicated about 1 in 3 of women worldwide have experienced physical violence but there is no enough reports on the current status of the act in Aksum town so this study intended to identify the prevalence and factors associated with physical violence of reproductive age married women in Aksum town Tigray Ethiopia. Result A total of 398 women were enrolled in the study and making a response rate of 100%. 112 (28.1%) women had physical violence in their lifetime. Educational level of women (AOR = 2.2; 95% CI 1.28, 6.7), Occupation of women’s (AOR = 3.8; 95% CI 2.32, 12.8), age of husband (AOR = 5.2; 95% CI 2.3, 11.5), husbands having other wife (AOR = 7.8; 95% CI 4.2, 18.9) and husbands having alcohol habits (AOR = 3.8; 95% CI 1.74, 14.7) had significant association with physical violence.

Background: Universal access to safe drinking water and sanitation facilities is an essential human right, recognised in the Sustainable Development Goals as crucial for preventing disease and improving human wellbeing. Comprehensive, high-resolution estimates are important to inform progress towards achieving this goal. We aimed to produce highresolution geospatial estimates of access to drinking water and sanitation facilities. Methods: We used a Bayesian geostatistical model and data from 600 sources across more than 88 low-income and middle-income countries (LMICs) to estimate access to drinking water and sanitation facilities on continuous continent-wide surfaces from 2000 to 2017, and aggregated results to policy-relevant administrative units. We estimated mutually exclusive and collectively exhaustive subcategories of facilities for drinking water (piped water on or off premises, other improved facilities, unimproved, and surface water) and sanitation facilities (septic or sewer sanitation, other improved, unimproved, and open defecation) with use of ordinal regression. We also estimated the number of diarrhoeal deaths in children younger than 5 years attributed to unsafe facilities and estimated deaths that were averted by increased access to safe facilities in 2017, and analysed geographical inequality in access within LMICs. Findings: Across LMICs, access to both piped water and improved water overall increased between 2000 and 2017, with progress varying spatially. For piped water, the safest water facility type, access increased from 40·0% (95% uncertainty interval [UI] 39·4–40·7) to 50·3% (50·0–50·5), but was lowest in sub-Saharan Africa, where access to piped water was mostly concentrated in urban centres. Access to both sewer or septic sanitation and improved sanitation overall also increased across all LMICs during the study period. For sewer or septic sanitation, access was 46·3% (95% UI 46·1–46·5) in 2017, compared with 28·7% (28·5–29·0) in 2000. Although some units improved access to the safest drinking water or sanitation facilities since 2000, a large absolute number of people continued to not have access in several units with high access to such facilities (>80%) in 2017. More than 253 000 people did not have access to sewer or septic sanitation facilities in the city of Harare, Zimbabwe, despite 88·6% (95% UI 87·2–89·7) access overall. Many units were able to transition from the least safe facilities in 2000 to safe facilities by 2017; for units in which populations primarily practised open defecation in 2000, 686 (95% UI 664–711) of the 1830 (1797–1863) units transitioned to the use of improved sanitation. Geographical disparities in access to improved water across units decreased in 76·1% (95% UI 71·6–80·7) of countries from 2000 to 2017, and in 53·9% (50·6–59·6) of countries for access to improved sanitation, but remained evident subnationally in most countries in 2017. Interpretation: Our estimates, combined with geospatial trends in diarrhoeal burden, identify where efforts to increase access to safe drinking water and sanitation facilities are most needed. By highlighting areas with successful approaches or in need of targeted interventions, our estimates can enable precision public health to effectively progress towards universal access to safe water and sanitation. This work was primarily supported by a grant from the Gates Foundation (OPP1132415). LGA has received support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Finance Code 001), Conselho Nacional de Desenvolvimento Científico e Tecnológico and Fundação de Amparo à Pesquisa do Estado de Minas Gerais. OOA acknowledges the Department of Science and Innovation, National Research Foundation, and DSI/NRF Centre of Excellence for Epidemiological Modelling and Analysis, Stellenbosch, South Africa. SMAl acknowledges the Department of Health Policy and Management, Faculty of Public Health, Kuwait University and International Centre for Casemix and Clinical Coding, Faculty of Medicine, National University of Malaysia for the approval and support to participate in this research project. HTA acknowledges Aksum University. MAu and CH are partly supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. AAz acknowledges funding from the Gates Foundation (OPP1171700). ABad is supported by the Public Health Agency of Canada. TWB was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research; the EU; the Wellcome Trust; and from National Institute of Child Health and Human Development of National Institutes of Health (NIH; R01-HD084233), National Institute on Aging of NIH (P01AG041710), National Institute of Allergy and Infectious Diseases of NIH (R01-AI124389 and R01-AI112339), as well as Fogarty International Center of NIH (D43-TW009775). DABen was supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the UK Department of Health and Social Care. GBB is supported by Sistema Nacional de Investigación (SNI) de la Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT) of Panamá. FCar acknowledges UID/ MULTI/04378/2019 and UID/QUI/50006/2019 support with funding from FCT/Ministério da Ciência, Tecnologia e Ensino Superior through national funds. VMC acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia (FCT), IP, under the Norma Transitória DL57/2016/CP1334/CT0006. JDN acknowledges support from the Alexander von Humboldt Foundation. DBD acknowledges support from the Gates Foundation. KD is supported by a Wellcome Trust grant (number 201900/Z/16/Z) as part of his International Intermediate Fellowship. AGo acknowledges Sistema Nacional de Investigadores de Panamá (SNI), Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT). CH is partly supported by a grant co-funded by European Fund for Regional Development through the Operational Program for Competitiveness (project ID P_40_382). SMSI is funded by a Fellowship from National Heart Foundation of Australia and Deakin University. MJ and the Serbian part of this GBD contribution was co-funded through grant OI175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. JK is a recipient of the 2020 Benjamin V Cohen Peace Fellowship from Ball State University Center for Peace and Conflict Studies. YJK’s work was supported by the Research Management Centre, Xiamen University Malaysia, grants number XMUMRF/2018-C2/ ITCM/0001. KKr is supported by a DST PURSE grant and UGC Center of Advanced Study awarded to the Department of Anthropology, Panjab University, Chandigarh, India. BL acknowledges support from the NIHR Oxford Biomedical Research Centre and the British Heart Foundation Centre of Research Excellence, Oxford. PTNM acknowledges the Council for the Development of Social Science Research in Africa. ANA acknowledges Debre Markos University for its support in-terms of office and internet access while reviewing this paper. AMSam received a fellowship from the Egyptian Fulbright Mission programme. MMS-M acknowledges the support of the Ministry of Education, Science and Technological Development of the Republic of Serbia (contract number 175087). AShi acknowledges the support of Health Data Research UK. MRS acknowledges the Clinical Research Development Center of Imam Reza Hospital, Kermanshah university of Medical sciences for their wise advice. JBS is part of Centro de Investigación en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. RT-S was supported in part by grant PI17/00719 from Instituto de Salud Carlos III–FEDER. BU acknowledges Manipal Academy of Higher Education, Manipal. TWij acknowledges the Migraine Foundation Australia and the Department of Medicine, Faculty of Medicine, University of Rajarata, Saliyapura, Anuradhapuraya, Sri Lanka. CSW was supported by the South African Medical Research Council. SBZ received a scholarship from the Australian Government research training program in support of his academic career.

BackgroundMissed nursing care is considered an error of omission and is defined as any aspect of required patient care that is omitted (either in part or whole) or significantly delayed. Nursing care missed in the perinatal setting can cause negative outcomes and repercussions for the quality and safety of care. This has been reported in multiple settings and countries and is tied to negative maternal outcomes. Preventing missed nursing care requires in-depth research considering the clinical setting.ObjectiveThe main aim of the study was to assess commonly missed nursing care elements, reasons, and factors for the omission in the obstetric and gynecologic units of general hospitals in Tigray 2017/18.Methods and materialsA cross-sectional study was conducted in eight randomly selected general hospitals in Tigray, Ethiopia. A total of 422 nurses and midwives were selected through simple random sampling using the staff list as a sampling frame. To identify the commonly missed nursing care and related factors, the MISSCARE survey tool was used. Descriptive, bivariate, and multivariate logistic regression analysis was performed to assess potential risk factors of nursing cares omission.ResultThe study results showed that 299 (74.6%) participants commonly missed at least one nursing care in the perinatal setting. Labor resources 386(96.3%), teamwork 365(91%), material resources 361 (90%) and communication 342 (85.3%) were the reasons identified for commonly missing care. In the multivariate analyses, sex (p-value ConclusionThe proportion of commonly missed nursing care was high. After adjusting for demographic variables, labor resources, material resources, and communication were reasons for commonly missed nursing care. Increasing male professional proportion, investing in nurses/midwives training, and harmonizing nursing service administration through appropriate working shift arrangement and timely assessment of professionals' stability and satisfaction could minimize frequent omission of nursing care.

Objective As adolescence is a stage in which human beings face once throughout a lifetime and it is the experimental period for this reason risky sexual behavior is common among young people, and it has several sexual and reproductive health consequences. But it doesn’t get enough attention the status of risky sexual behavior practice and factors’ contributing to it, so this study aimed to identify the prevalence of risky sexual behavior and factors associated with it. Results From the total respondents 115 (23.7%) had history of sexual intercourse and the mean age for sexual initiation is 15.48 ± 1.99 year. From whom 110 (98.2%) had sexual contact below the age of 18 and only 68 (60.8%) initiate first sex by their own willing. Overall 97 (19.6%) had practiced risky sexual behaviors. Students not facing peer pressure were 0.36 times less likely to develop risk sexual behavior (AOR = 0.357, 95% CI 0.172, 0.744).

Objective The aim of this study was to assess the prevalence of chronic kidney disease and to identify associated factors of chronic kidney disease among hypertensive patients. A cross-sectional study was conducted among selected 578 hypertensive patients. Data were collected using face to face interviewing questionnaires and from medical chart review. Binary logistic regression analyses were performed and analyzed using SPSS version 23.0. Result Of the total 578 hypertensive patients the prevalence of chronic kidney disease was found to be 128 (22.1%). Of these hypertensive patients, patients with uncontrolled blood pressure, overweight/obesity, dyslipidemia and diabetic mellitus, 43.3%, 33.7%, 27.3% and 28.2 respectively. After adjustment, the independent variables the significant associated factors of chronic kidney disease among hypertensive patients were age [AOR (95% CI 1.43 (1.07–1.81)], uncontrolled hypertension 4.434 [AOR (95% CI 9.45 (1.34, 14.73)], overweight/obese [AOR (95% CI 7.422 (2.72, 20.28)], dyslipidemia [AOR (95% CI) 13.749 (5.69, 33.215)], diabetic mellitus [AOR (95% CI) 2.137 (1.07, 4.26)]. In conclusion, the prevalence of chronic kidney disease was considerably high. The major associated factors of chronic kidney disease were age, uncontrolled hypertension, overweight/obese, diabetic mellitus and dyslipidemia.

Introduction Adherence to insulin therapy is a critical factor for adequate control of diabetes mellitus. Despite the multiple well-known benefits of adherence to insulin therapy, poor adherence remains to be a common cause of diabetes mellitus-related complications. A better management of diabetes mellitus requires determining the level of patient adherence and identifying why non-adherence to insulin therapy occurs. Therefore, this study was designed to assess the level of adherence to insulin therapy and associated factors among diabetes mellitus patients. Methods The study was conducted from May 1 to July 1, 2018, using a cross-sectional study design. Interviewer-administered questionnaire was employed for data collection and systematic random sampling technique was used to select study participants. The collected data were entered using Epi data version 3.1.1 and exported to SPSS version 22 for analysis. Logistic analysis was carried out to check the level of association between adherence to insulin therapy and the independent variables with significance level of 0.05 at 95% confidence interval. Results 273 respondents were selected with a 100% response rate. Near to one-fourth (24.2%) of the respondents were adherent to their insulin therapy. The study revealed that good knowledge of diabetes mellitus [AOR=6.51; 95% CI [1.58, 26.71], age [>30 years] [AOR=2.63; 95% CI [1.27, 5.42], knowledge regarding insulin self-injection [AOR=4.21; 95%CI [1.06,16.65], favorable attitude towards insulin injection [AOR=2.14; 95% CI [1.04,4.41], free-of-cost insulin therapy [AOR= 4.62, 95% CI [1.06,16.65], having of glucometer at home [AOR= 2.82, 95% CI [1.12,7.09], and being a member of Ethiopian diabetic association [AOR= 5.41, 95% CI [2.31,12.64] were found to significantly affect adherence to insulin therapy. Conclusion Nearly one-fourth of the study participants were adherent to their insulin therapy. Good knowledge and favorable attitude towards insulin injection, good knowledge regarding diabetes mellitus, being a member of the Ethiopian Diabetes Association, age greater than thirty years old, free-of-cost insulin therapy and having glucometer at home were found to be significant predictors of adherence to insulin therapy.

Introduction Hypertension, among diabetic patients, is a worldwide public-health challenge and a leading modifiable risk factor for other cardiovascular diseases. The main purpose of this study was to identify determinants of hypertension among diabetic patients. Methods Data were collected from January to March 2018 using an interviewer-administered structured questionnaire. Data collectors and supervisors were trained before the period of data collection. The questionnaire was pretested on 5% of the sample at Suhul hospital. Bivariable logistic regression was employed to examine the crude associations between the outcome variable and determinant variables. This was followed by multivariable analysis to examine the determinants of hypertension among diabetic patients by selecting variables which had p value ≤0.2 in the bivariable analysis. Results The age range of the respondents was 18-80 years, with the median age of 51.56±14.92 years. Not attending diabetes mellitus education sessions (AOR=2.61, 95% CI (1.12,6.1), duration since diagnosis with diabetes (AOR=8.52; 95% CI (1.97, 36.84), poor glycemic control (AOR=22.99, 95CI (5.92,89.28), overweight (AOR=4.84, 95%CI (1.42,16.51), and non-adherence to diabetes medication (AOR=4.66, 95% CI (2.22,9.79), diet (AOR=9.70,95% CI (3.34,28.22), exercise (AOR= 5.47, 95% CI (2.35,12.75), and self-monitoring blood glucose (AOR=6.62, 95% CI (3.16, 13.86) were found to be the determinants of hypertension among diabetic patients. Conclusion This research concludes that longer duration with diabetes, nonattendance of diabetes education sessions, poor glycemic control, and not-adherence to antidiabetic medications, diet, exercise and self-monitoring blood glucose were found to be the determinants of hypertension among diabetic patients.

Objective Nursing care is one of the most important components of health care and patient expectation toward nursing care is being rising. Accordingly, patients’ expectation needs to be managed adequately in order to improve outcomes and decrease liability through their perception. To improve the outcome based on the expectation of patients, we need to consider patients’ perception to the care they received. So this study aims to identifies the perceptions toward nursing care and their associated factors. Result From a total of 281 admitted patients 151 (53.7%) were females; 136 (48.4%) were found in the age group of 21–30 years with mean age of 30 (11 ± SD) years. The mean score of overall perception were 62.6 ± 17.9 (95% CI 60.79–64.37). Among all 154 (54.8%) participants had poor perception to nursing care. Occupation, ward and expectation had association with perception. Patient’s level of perception towards nursing care was poor (54.7%) and ward where patients admitted, expectation of patients, occupation of patients and duration of hospital stay were significantly associated with patients’ perception. So that health institutions and nurses should focus on perception of their clients.