Abstract:The Dodowa Health and Demographic Surveillance System (DHDSS) operates in the south-eastern part of Ghana. It was established in 2005 after an initial attempt in 2003 by the Dodowa Health Research Centre (DHRC) to have an accurate population base for piloting a community health insurance scheme. As at 2010, the DHDSS had registered 111 976 residents in 22 767 households. The district is fairly rural, with scattered settlements. Information on pregnancies, births, deaths, migration and marriages using household… Show more
“…For the Dodowa HDSS site, a surveillance population of approximately 115,000 was recorded in 2011. It is approximately 40 km from Accra [33] and contains 20 CHPS compounds.…”
Background: Improving maternal health is a global challenge. In Ghana, maternal morbidity and mortality rates remain high, particularly in rural areas. Antenatal care (ANC) attendance is known to improve maternal health. However, few studies have updated current knowledge regarding determinants of ANC attendance.
Objective: This study examined factors associated with ANC attendance in predominantly rural Ghana.
Methods: We conducted a cross-sectional study at three sites (i.e. Navrongo, Kintampo, and Dodowa) in Ghana between August and September 2013. We selected 1500 women who had delivered within the two years preceding the survey (500 from each site) using two-stage random sampling. Data concerning 1497 women’s sociodemographic characteristics and antenatal care attendance were collected and analyzed, and factors associated with attending ANC at least four times were identified using logistic regression analysis.
Results: Of the 1497 participants, 86% reported attending ANC at least four times, which was positively associated with possession of national health insurance (AOR 1.64, 95% CI: 1.14–2.38) and having a partner with a high educational level (AOR 1.64, 95% CI: 1.02–2.64) and negatively associated with being single (AOR 0.39, 95% CI: 0.22–0.69) and cohabiting (AOR 0.57, 95% CI: 0.34–0.97). In site-specific analyses, factors associated with ANC attendance included marital status in Navrongo; marital status, possession of national health insurance, partners’ educational level, and wealth in Kintampo; and preferred pregnancy timing in Dodowa. In the youngest, least educated, and poorest women and women whose partners were uneducated, those with health insurance were more likely to report at least four ANC attendances relative to those who did not have insurance.
Conclusions: Ghanaian women with low socioeconomic status were less likely to report at least four ANC attendances during pregnancy if they did not possess health insurance. The national health insurance scheme should include a higher number of deprived women in predominantly rural communities.
“…For the Dodowa HDSS site, a surveillance population of approximately 115,000 was recorded in 2011. It is approximately 40 km from Accra [33] and contains 20 CHPS compounds.…”
Background: Improving maternal health is a global challenge. In Ghana, maternal morbidity and mortality rates remain high, particularly in rural areas. Antenatal care (ANC) attendance is known to improve maternal health. However, few studies have updated current knowledge regarding determinants of ANC attendance.
Objective: This study examined factors associated with ANC attendance in predominantly rural Ghana.
Methods: We conducted a cross-sectional study at three sites (i.e. Navrongo, Kintampo, and Dodowa) in Ghana between August and September 2013. We selected 1500 women who had delivered within the two years preceding the survey (500 from each site) using two-stage random sampling. Data concerning 1497 women’s sociodemographic characteristics and antenatal care attendance were collected and analyzed, and factors associated with attending ANC at least four times were identified using logistic regression analysis.
Results: Of the 1497 participants, 86% reported attending ANC at least four times, which was positively associated with possession of national health insurance (AOR 1.64, 95% CI: 1.14–2.38) and having a partner with a high educational level (AOR 1.64, 95% CI: 1.02–2.64) and negatively associated with being single (AOR 0.39, 95% CI: 0.22–0.69) and cohabiting (AOR 0.57, 95% CI: 0.34–0.97). In site-specific analyses, factors associated with ANC attendance included marital status in Navrongo; marital status, possession of national health insurance, partners’ educational level, and wealth in Kintampo; and preferred pregnancy timing in Dodowa. In the youngest, least educated, and poorest women and women whose partners were uneducated, those with health insurance were more likely to report at least four ANC attendances relative to those who did not have insurance.
Conclusions: Ghanaian women with low socioeconomic status were less likely to report at least four ANC attendances during pregnancy if they did not possess health insurance. The national health insurance scheme should include a higher number of deprived women in predominantly rural communities.
Ghana is classified as being in the malaria control phase, according to the global malaria elimination program. With many years of policy development and control interventions, malaria specific mortality among children less than 5 years old has declined from 14.4% in 2000 to 0.6% in 2012. However, the same level of success has not been achieved with malaria morbidity. The recently adopted 2015–2020 Ghana strategic action plan aims to reduce the burden of malaria by 75.0%. Planning and policy development has always been guided by evidence from field studies, and mathematical models that are able to investigate malaria transmission dynamics have not played a significant role in supporting policy development. The objectives of this study are to describe the malaria situation in Ghana and give a brief account of how mathematical modelling techniques could support a more informed malaria control effort in the Ghanaian context. A review is carried out of some mathematical models investigating the dynamics of malaria transmission in sub-Saharan African countries, including Ghana. The applications of these models are then discussed, considering the gaps that still remain in Ghana for which further mathematical model development could be supportive. Because of the collaborative approach adopted in their development, some model examples Ghana could benefit from are also discussed. Collaboration between malaria control experts and modellers will allow for more appropriate mathematical models to be developed. Packaging these models with user-friendly interfaces and making them available at various levels of malaria control management could help provide the decision making tools needed for planning and a platform for monitoring and evaluation of interventions in Ghana.
“…Likewise, transferring data from paper into a digital form is a lengthy process with a lot of room for error. Not only the content of data can be entered incorrectly, but assigning new data to the right entity or ID is an errorprone process with small typos leading to unrecognizable and ultimately squandered data (Gyapong et al, 2013;Kahn et al, 2012;Kouanda et al, 2013;Scott et al, 2012). Finally, accumulating and managing data relies heavily on obsolete database software with limited data quality assurance structures.…”
Section: Discussionmentioning
confidence: 99%
“…This integration is one of the important improved aspects within the described HDSS, resulting in organizational and scientific advantages. HDSS sites often rely on paper-based conducting of questionnaires before the data is entered in to a digital database (Derra et al, 2012;Gyapong et al, 2013;Kahn et al, 2012;Pison et al, 2014;Scott et al, 2012). The Android operating system is used on powerful tablet computers, allowing us to develop or deploy the desired software.…”
Section: Resource Allocationmentioning
confidence: 99%
“…At most INDEPTH affiliated HDSS sites the Household Registration System [HRS] is used for managing demographic and health-related data, either by digitalizing filled in paper forms or direct digital entry in the field (Derra et al, 2012;Gyapong et al, 2013;Kouanda et al, 2013;Odhiambo et al, 2012;Wanyua et al, 2013). There are also examples of HDSS sites where a different data management system is developed relying on paper or non-paper based data collection (Kahn et al, 2012;Sacoor et al, 2013;Scott et al, 2012).…”
Section: Time and Organizational Efficiencymentioning
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