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Item Some Demographic Characteristics of two rural communities in Southern Ghana(Ghana Medical Journal, 1988-09) Afari, E.A.; Nakano, T.; Owusu-Adjei, S.A study of the demographic characteristics of two rural villages in Southern Ghana in 1987 showed an average rate of natural population increase of 3.8 percent compared to 3.2 per cent recorded nationally (1984 census data). The crude death rates and Infant Mortality rates were far lower than the figures usually quoted, although the birth rate was similar to the national average. It is suggested that if such rates exist in similar villages in Ghana, then official projections are underestimates and will have grave consequences on national development plans. It appears that Primary Health Care (PHC) has succeeded in reducing deaths but has not affected births. Family planning must, therefore, receive more attention.Item Financing reproductive health services in Africa: The role of aid, insurance, user fees and general taxation(Reproductive Health, Economic Growth and Poverty Reduction in Africa: Frameworks of Analysis, 2010) Enyimayew, N.Financing Reproductive Health Services in Africa: The Role of Aid, Insurance, User fees and General Taxation Nana Enyimayew Without appropriate financial resources, scaling up effective reproductive health interventions in order to achieve the Millennium Development Goal for maternal health (MDG 5)1 will be virtually impossible. Yet little is known about how much is currently being invested in reproductive health services within African countries or whether levels of funding are changing. Estimates place the additional funding requirements to attain universal coverage at a minimum of US$7 billion per year. Other estimates suggest that even greater investments are needed. Irrespective of the precise figure, the conclusion is clear: the financing gap represents a substantial sum in relation to domestic budgets. Adequate, well-managed financing of public health systems in general continues to elude most countries. The difficulty is especially severe in low-income countries, most of which are in Africa, whose health systems struggle with meagre and inequitably distributed resources. Additionally, access to services for the most disadvantaged is usually very poor, further reducing the benefit of already scarce resources for those most in need. Success or otherwise of different health financing strategies is critical in determining the fate of such populations and therefore needs to be documented and presented to inform the development of right policies. Filling the information gaps requires appropriately designed and executed research. At minimum, reproductive health (RH) services may be defined as those activities whose primary purpose is to restore, improve and maintain the health of women and their newborns during pregnancy, childbirth and the seven-day postnatal period. This chapter provides an update of the current knowledge of financing of RH services in Africa and suggests a framework for further research in these areas. It also presents examples of national and regional efforts to adopt and implement financing policies that aim to address national objectives of access, equity, quality and appropriate utilisation of RH services to meet MDG 5 by 2015. Issues of exemptions, subsidies and efficiency are also discussed within the scope of financing RH services. A review of basic services is presented in Table 5.1. Reproductive Health, Economic Growth and Poverty Reduction in Africa 108 Table 5.1: Range of reproductive health services Category of care Interventions Antenatal care Basic antenatal care Management of severe anaemia Treatment of malaria Management of syphilis, gonorrhoea and Chlamydia Normal delivery care Clean and safe delivery Post-partum care Basic newborn care Essential obstetric care Management of eclampsia, sepsis, haemorrhage and abortion complications, plus provision of emergency caesarean section Family planning Family planning information and services Other Prevention and treatment of HIV/AIDS How Much Do Reproductive Health Services Cost? Information from various sources suggests that the per capita cost of providing a package of reproductive health services ranges between US$0.5 and US$6.0 (Weissman et al., 1999; World Bank, 1993). Global costs for reproductive health are estimated at US$7 billion dollars per year till 2015 while analyses done using the methodology of the UN Millennium Project suggest that family planning programmes in Africa alone would increase from US$270 million in 2006 to nearly US$500 million by 2015 (Cleland et al., 2006). A selection of per capita cost estimates is presented in Table 5.2. Table 5.2: Per capita cost estimates for reproductive health services Service Cost (US$) Mother and Baby package (1) 0.5 (current level of service provision) Uganda 1999 1.4–1.8 (standard level of service) WDR Global 1993 (2) 4.0 Making Motherhood Safe (3) 2.0–6.0 Range 0.5–6.0 Sources: (1) Weissman et al. (1999); (2) World Development Report (World Bank, 1993); (3) Ransom and Yinger (2002). Making Motherhood Safer. The wide range of costs reflects the practical difficulty facing service providers, researchers, policy makers and society in general in meeting the requirements for accurate estimates of reproductive health care costs. These include defining the boundaries of RH, and standardising the content and quality of a given package of care. Questions that continue to engage service providers and policy makers are; How much do reproductive health services at household, community and country level Financing Reproductive Health Services in Africa 109 cost? How much must governments and society spend on RH services to achieve national and global targets. What should be the minimum content of a standard package of care if countries in resource-constrained environments are to meet their targets? Global estimates provide a useful guide to...Item Infectious Disease Control in Ghana: Government's Interventions and Challenges to Malaria Eradication(Water and Sanitation-Related Diseases and the Environment: Challenges, Interventions, and Preventive Measures, 2011-10) Fobil, J.N.; May, J.; Kraemer, A.Introduction Ghana Malaria Control Initiatives-Past and Present Successes, Challenges, and Weaknesses of Control Strategies Conclusion and Recommendations ReferencesItem Knowledge and use of information and communication technology by health sciences students of the University of Ghana(Ghana Medical Journal, 2016-09) Dery, S.; Vroom, F.D.; Godi, A.; Afagbedzi, S.; Dwomoh, D.Background: Studies have shown that ICT adoption contributes to productivity and economic growth. It is therefore important that health workers have knowledge in ICT to ensure adoption and uptake of ICT tools to enable efficient health delivery. Objective: To determine the knowledge and use of ICT among students of the College of Health Sciences at the University of Ghana. Methods: This was a cross-sectional study conducted among students in all the five Schools of the College of Health Sciences at the University of Ghana. A total of 773 students were sampled from the Schools. Sampling proportionate to size was then used to determine the sample sizes required for each school, academic programme and level of programme. Simple random sampling was subsequently used to select students from each stratum. . Results: Computer knowledge was high among students at almost 99%. About 83% owned computers (p < 0.001) and self-rated computer knowledge was also 87 % (p <0.001). Usage was mostly for studying at 93% (p< 0.001). Conclusions: This study shows students have adequate knowledge and use of computers. It brings about an opportunity to introduce ICT in healthcare delivery to them. This will ensure their adequate preparedness to embrace new ways of delivering care to improve service delivery.Item Counting adolescents in: the development of an adolescent health indicator framework for population-based settings(Elsevier Ltd., 2023) Manu, A.Changing realities in low- and middle-income countries (LMICs) in terms of inequalities, urbanization, globalization, migration, and economic adversity shape adolescent development and health, as well as successful transitions be tween adolescence and young adulthood. It is estimated that 90% of adolescents live in LMICs in 2019, but inade quate data exist to inform evidence-based and concerted policies and programs tailored to address the distinctive developmental and health needs of adolescents. Population-based data surveillance such as Health and Demographic Surveillance Systems (HDSS) and school-based surveys provide access to a well-defined population and provide cost-effective opportunities to fill in data gaps about adolescent health and well-being by collecting population representative longitudinal data. The Africa Research Implementation Science and Education (ARISE) Network, therefore, systematically developed adolescent health and well-being indicators and a questionnaire for measuring these indicators that can be used in population-based LMIC settings. We conducted a multistage collaborative and iterative process led by network members alongside consultation with health-domain and adolescent health experts globally. Seven key domains emerged from this process: socio-demographics, health awareness and behaviors; nutrition; mental health; sexual and reproductive health; substance use; and healthcare utilization. For each domain, we generated a clear definition; rationale for inclusion; sub-domain descriptions, and a set of questions for mea surement. The ARISE Network will implement the questionnaire longitudinally (i.e., at two time-points one year apart) at ten sites in seven countries in sub-Saharan Africa and two countries in Asia. Integrating the questionnaire within established population-based data collection platforms such as HDSS and school settings can provide measured experiences of young people to inform policy and program planning and evaluation in LMICs and improve adolescent health and well-beingItem Associated factors of diet quality among people living with HIV/AIDS in Ghana(BMC Nutrition, 2024) Abdulai, K.; Torpey, T.; Kotoh, A.M.; Laar, A.Introduction : Nutrition is a very important element of a comprehensive care for people living with HIV/AIDS (PLHIV), especially in resource-constrained settings where malnutrition and food insecurity are common. Dietary diversity is a useful indication of nutritional adequacy (diet quality) in people of all ages. An optimally diverse diet strengthens the body’s immune system. Objective This study aimed to assess diet quality and its associated factors among PLHIV. Methods A facility-based cross-sectional study design was employed to select 440 PLHIV from two hospitals in the Eastern Region of Ghana. Dietary intakes were determined using 24-hour recall. A stadiometer and bioimpedance analysis machine were used to obtain anthropometric and body composition data. Diet quality was assessed using FAO’s individual dietary diversity score (IDDS) as a proxy. SPSS version 20 was used for analysis. Odds ratios and ordinal logistic regression were used to identify factors associated with diet quality among the PLHIV. P-value was set at 0.05. Results Most of the PLHIV (73%) consumed from ‘Starchy staple” food group. Less than 20% of the study sample consumed ‘Fruits’ and ‘Vegetables’ (17% and 14% respectively) a day before the survey. The mean IDDS was 4.11 (SD=1.29). Overall, most of the PLHIV (56%) had medium IDDS which is equivalent to “diet needing improvement’, 14% had higher IDDS (good diet), whiles about 31% of the participants actually had poor diet (lower IDDS). Associated factors of diet quality were age (AOR=0.966: 95%CI: 0.936–0.997: p=0.031), married (AOR=4.634: 95%CI: 1.329– 16.157: p=0.0016), separated (AOR=0.0203: 95%CI: .036–0.994: p=0.049), and daily meal frequency (AOR=0.441: 95%CI: .478–1.948: p=0.020). Overall, the model accounts for about 20% of the variation in diet quality of the participants (pseudo-R square=0.196). Conclusion This study demonstrates that most of the PLHIV did not consume good diet which may have an implication on their immune system, which is already under attack by HIV, and probably emerging infections. Age, marital status, and meal frequency were the variables that predicted diet quality among the study participants.