32 research outputs found
Sexual Behavior and Risk Perception of HIV Infection
Ethiopia is a developing country with a demographic profile dominated by a young population. Due to biological, psychological, socio cultural and economic factors, young people, particularly those aged 15-29 years, are generally at a high risk of HIV/AIDS and other reproductive health problems. This paper presented results of a cross-sectional descriptive study conducted in Bahir Dar Town, northwest Ethiopia, to assess sexual behavior and risk perception of HIV infection among youths .Both quantitative and qualitative method of data-collection methods were employed to conduct the study. For quantitative data collection, a household questioner survey was conducted among 232 youth, aged 15-29 years, within the 4kebeles (villages) of the town. Qualitative data were collected by conducting focus-group discussions and in-depth interviews with 17 participants. Descriptive statistics was used to characterize socio-economic, demographic and behavioral variables and the level of risk perception of HIV. Chi-square was used to examine the association of socio-economic, demographic and behavioral variables to HIV risk perception. Logistic regression model was used further examined to identify the prediction independent variables to risk perception. Data obtained by interview and focus group discussion were qualitatively analyzed. The minimum mean age at first sexual commencement was 16.71(+1.45) years and the maximum is 26.25(+1.18).Socio-economic and demographic variables such as Job(x²=4.7151, p=0.03), alcohol use(x²=16.8405, p=0.001), monthly income(x²=12.769,p=0.026), gender(x²=9.4788, p=0.002) and education status(x²=11.8883, p=0.003) were significantly associated with risk perception of HIV among the youth. Behavioral variables such as sex ever had (²=10.1561,p=0.001), age at first sex (x²=7.524, p=0.023), no of sexual partners(²=7.2156, p=0.002 and knowledge of HIV status(x²=16.0624, p=0.000) were also significantly associated with risk perception of HIV among the youths. IN logistic regression model, age (z=-2.13, p=0.033), education status (z=-4.36, p=0.000), marital status (z=-2.48, p=0.013), alcohol use (z=4.88, p=0.000), and knowledge of HIV status (z=-3.69, p=0.000) were significantly and independently predicted HIV risk perception. In conclusion, further research should be conducted to better understand the nature of association between the above socio-economic and demographic, and sexual behavioral variables with risk perception of HIV/AIDS Staking behaviors. Keywords: sexual behavior, risk perceptions
Sexual Behavior and Risk Perception of HIV Infection Among Youths in Bahirdar Town
Ethiopia is a developing country with a demographic profile dominated by a young population. Due to biological, psychological, socio cultural and economic factors, young people, particularly those aged 15-29 years, are generally at a high risk of HIV/AIDS and other reproductive health problems. This paper presented results of a cross-sectional descriptive study conducted in Bahir Dar Town, northwest Ethiopia, to assess sexual behavior and risk perception of HIV infection among youths .Both quantitative and qualitative method of data-collection methods were employed to conduct the study. For quantitative data collection, a household questioner survey was conducted among 232 youth, aged 15-29 years, within the 4kebeles (villages) of the town. Qualitative data were collected by conducting focus-group discussions and in-depth interviews with 17 participants. Descriptive statistics was used to characterize socio-economic, demographic and behavioral variables and the level of risk perception of HIV. Chi-square was used to examine the association of socio-economic, demographic and behavioral variables to HIV risk perception. Logistic regression model was used further examined to identify the prediction independent variables to risk perception. Data obtained by interview and focus group discussion were qualitatively analyzed. The minimum mean age at first sexual commencement was 16.71(+1.45) years and the maximum is 26.25(+1.18).Socio-economic and demographic variables such as Job(x²=4.7151, p=0.03), alcohol use(x²=16.8405, p=0.001), monthly income(x²=12.769,p=0.026), gender(x²=9.4788, p=0.002) and education status(x²=11.8883, p=0.003) were significantly associated with risk perception of HIV among the youth. Behavioral variables such as sex ever had (²=10.1561,p=0.001), age at first sex (x²=7.524, p=0.023), no of sexual partners(²=7.2156, p=0.002 and knowledge of HIV status(x²=16.0624, p=0.000) were also significantly associated with risk perception of HIV among the youths. IN logistic regression model, age (z=-2.13, p=0.033), education status (z=-4.36, p=0.000), marital status (z=-2.48, p=0.013), alcohol use (z=4.88, p=0.000), and knowledge of HIV status (z=-3.69, p=0.000) were significantly and independently predicted HIV risk perception. In conclusion, further research should be conducted to better understand the nature of association between the above socio-economic and demographic, and sexual behavioral variables with risk perception of HIV/AIDS Staking behaviors. Keywords: sexual behavior, risk perception
Towards elimination of mother-to-child transmission of HIV: performance of different models of care for initiating lifelong antiretroviral therapy for pregnant women in Malawi (Option B+).
INTRODUCTION: Malawi introduced a new strategy to improve the effectiveness of prevention of mother-to-child HIV transmission (PMTCT), the Option B+ strategy. We aimed to (i) describe how Option B+ is provided in health facilities in the South East Zone in Malawi, identifying the diverse approaches to service organization (the "model of care") and (ii) explore associations between the "model of care" and health facility-level uptake and retention rates for pregnant women identified as HIV-positive at antenatal (ANC) clinics. METHODS: A health facility survey was conducted in all facilities providing PMTCT/antiretroviral therapy (ART) services in six of Malawi's 28 districts to describe and compare Option B+ service delivery models. Associations of identified models with program performance were explored using facility cohort reports. RESULTS: Among 141 health facilities, four "models of care" were identified: A) facilities where newly identified HIV-positive women are initiated and followed on ART at the ANC clinic until delivery; B) facilities where newly identified HIV-positive women receive only the first dose of ART at the ANC clinic, and are referred to the ART clinic for follow-up; C) facilities where newly identified HIV-positive women are referred from ANC to the ART clinic for initiation and follow-up of ART; and D) facilities serving as ART referral sites (not providing ANC). The proportion of women tested for HIV during ANC was highest in facilities applying Model A and lowest in facilities applying Model B. The highest retention rates were reported in Model C and D facilities and lowest in Model B facilities. In multivariable analyses, health facility factors independently associated with uptake of HIV testing and counselling (HTC) in ANC were number of women per HTC counsellor, HIV test kit availability, and the "model of care" applied; factors independently associated with ART retention were district location, patient volume and the "model of care" applied. CONCLUSIONS: A large variety exists in the way health facilities have integrated PMTCT Option B+ care into routine service delivery. This study showed that the "model of care" chosen is associated with uptake of HIV testing in ANC and retention in care on ART. Further patient-level research is needed to guide policy recommendations
The burden of hypertension, diabetes mellitus, and cardiovascular risk factors among adult Malawians in HIV care: consequences for integrated services
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Spatiotemporal climate and vegetation greenness changes and their nexus for Dhidhessa River Basin, Ethiopia
Background
Understanding spatiotemporal climate and vegetation changes and their nexus is key for designing climate change adaptation strategies at a local scale. However, such a study is lacking in many basins of Ethiopia. The objectives of this study were (i) to analyze temperature, rainfall and vegetation greenness trends and (ii) determine the spatial relationship of climate variables and vegetation greenness, characterized using Normalized Difference in Vegetation Index (NDVI), for the Dhidhessa River Basin (DRB). Quality checked high spatial resolution satellite datasets were used for the study. Mann–Kendall test and Sen’s slope method were used for the trend analysis. The spatial relationship between climate change and NDVI was analyzed using geographically weighted regression (GWR) technique.
Results
According to the study, past and future climate trend analysis generally showed wetting and warming for the DRB where the degree of trends varies for the different time and spatial scales. A seasonal shift in rainfall was also observed for the basin. These findings informed that there will be a negative impact on rain-fed agriculture and water availability in the basin. Besides, NDVI trends analysis generally showed greening for most climatic zones for the annual and main rainy season timescales. However, no NDVI trends were observed in all timescales for cool sub-humid, tepid humid and warm humid climatic zones. The increasing NDVI trends could be attributed to agroforestry practices but do not necessarily indicate improved forest coverage for the basin. The change in NDVI was positively correlated to rainfall (r2 = 0.62) and negatively correlated to the minimum (r2 = 0.58) and maximum (r2 = 0.45) temperature. The study revealed a strong interaction between the climate variables and vegetation greenness for the basin that further influences the biophysical processes of the land surface like the hydrologic responses of a basin.
Conclusion
The study concluded that the trend in climate and vegetation greenness varies spatiotemporally for the DRB. Besides, the climate change and its strong relationship with vegetation greenness observed in this study will further affect the biophysical and environmental processes in the study area; mostly negatively on agricultural and water resource sectors. Thus, this study provides helpful information to device climate change adaptation strategies at a local scale
The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019
Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
Intestinal parasitic infection among household contacts of primary cases, a comparative cross-sectional study.
BackgroundIntestinal parasitic infection affects 3.5 billion people in the world and mostly affecting the low socio-economic groups. The objectives of this research works were to estimate the prevalence and determinants of intestinal parasitic infection among family members of known intestinal parasite infected patients.Methods and materialsA comparative cross-sectional study design was implemented in the urban and rural settings of Mecha district. The data were collected from August 2017toMarch 2019 from intestinal parasite infected patient household members. Epi-info software was used to calculate the sample size, 4531 household members were estimated to be included. Data were collected using interview technique, and collecting stool samples from each household contact of intestinal parasite patients. Descriptive statistics were used to estimate the prevalence of intestinal parasites among known contacts of intestinal parasite patients/family members. Binary logistic regression was used to identify the determinant factors of intestinal parasitic infection among family members.ResultsThe prevalence of intestinal parasite among household contacts of intestinal parasite-infected family members was 86.14% [95% CI: 86.14% - 87.15%]. Hookworm infection was the predominant type of infection (18.8%). Intestinal parasitic infection was associated with sex, environmental sanitation, overcrowding, personal hygiene, residence, substandard house, role in the household, source of light for the house, trimmed fingernails, family size, regular handwashing practice. Protozoa infection was associated with habit of ingesting raw vegetable, playing with domestic animals, water source and the presence of household water filtering materials.ConclusionHigh prevalence of intestinal parasitic infection was observed among household contacts of primary cases
Groundwater recharge and water table response to changing conditions for aquifers at different physiography : the case of a semi-humid river catchment, northwestern highlands of Ethiopia
A facility-based study of lipids, glucose levels and their correlates among pregnant women in public hospitals of northern Ethiopia
Background Lipids and glucose concentrations in the blood rise during pregnancy period. Poor control of these analytes results in cardio metabolic dysfunction. Despite this, there are no documented studies which investigate lipids and glucose among pregnant women in Tigrai, northern Ethiopia. Objective The objective of this study was to assess lipid and glucose levels and identify their correlates among pregnant women in Tigrai, northern Ethiopia. Method We conducted a facility-based cross sectional study comprising of systematically selected 200 pregnant women from July to October 2021. Those who were severely ill were excluded from the study. We used a structured questionnaire to collect socio-demographic and clinical characteristics of pregnant women. Lipids such as triglycerides, low density lipoprotein, cholesterol and blood glucose were also measured using Cobas C311 chemistry machine from plasma samples. The data were analyzed using SPSS version 25. Logistic regression was performed and statistical significance was declared at p-value Result Proportion of pregnant women with cholesterol, triglyceride, low density lipoprotein and blood glucose levels above the upper limit of the normal range used for clinical decision were 26.5%, 43%, 44.5% and 21%, respectively. Pregnant women’s income > = 10,000 ETB (AOR = 3.35; 95%CI: 1.46–7.66), age (AOR = 3.16; 95%CI: 1.03–9.68), gestational age 29–37 weeks (AOR = 8.02; 95%CI: 2.69–23.90) and having systolic blood pressure greater than 120 mmHg (AOR = 3.99; 95%CI: 1.64–9.75) demonstrated statistically significant association with raised levels of lipids. Conclusion and recommendation Proportion of pregnant women with out of normal range values of lipids, particularly triglycerides and low density lipoprotein, is high. Gestational age is a strong predictor of increase in blood levels for both lipids. Provision of life style related health education and dietary intake to pregnant mothers matters. Moreover, monitoring lipid profile and glucose level during antenatal care period is essential