Survival of pregnant women & kids in Guinea Bissau
Donation protected
How does access to free obstetric care affect utilisation of obstetric care and perinatal health?
In August I am off to Guinea Bissau in west Africa for 6 months to do research. I am collaborating with Bandim Health Project (BHP) and Statens Serums Institut (Denmark, Copenhagen). BHP has no core funding and I need to finance my own research.
I would be honored if you would considered donating any amount that you can afford
Short and sweet
Guinea Bissau is one of the poorest countries in the world with a high mortality rate of expectant mothers and children. NGOs have built healthcare facilities in rural areas where women can come in for four checkups during pregnancy, give birth there and come for checkups and get their kids vaccinated after. Using data collected before and after the clinics were built I am going to find out if the clinics have had an impact on the survival of mothers and children. The goal is to find out how, where and why NGOs can invest time and money to optimise healthcare in Guinea Bissau and other countries.
The nitty gritty of the project
Background
The Bandim Health Project monitors health and survival of women and children in a nationally representative rural Health and Demographic Surveillance System (HDSS) in Guinea-Bissau. The HDSS was set up in 1989-90 with the support of UNICEF and the World Bank to collect data on health interventions and child mortality. The HDSS allows us to describe the implementation of interventions and their effects.
In 2013-14, the PIMI programme in Guinea-Bissau (Integrated Programme for the Reduction of Maternal and Child Mortality ) made prenatal consultations and facility based deliveries available free of charge at the government health centres in four of the nine health regions in Guinea-Bissau. In 2013, in Cacheu, Biombo, Oio and Farim the programme was implemented with support from the Portuguese NGO, VIDA , while theItalian NGO, AIFO implemented the programme in Gabu in 2014.
Method
The Bandim Health Project implements a Health and Demographic Surveillance System (HDSS) in Guinea-Bissau, with collection of data on pregnancies, births and use of health services. This infrastructure provides an opportunity to measure the coverage of the health services, also before the PIMI programme and thus provides an option to assess the effect of the PIMI programme on use of health services. Furthermore, the collected data allows us to characterise the users and non-users of health services and to assess the potential effect on neonatal mortality.
A long list of personal data is collected such as ethnicity, age, level of education, obstetric and gyneacological history, vaccination status, nutritional status and illnesses. Additionally information is collected on aspects such as how far the woman has to travel to the nearest clinic, do they have access to running water and other sanitation, do they have access to phones/ internet, what type of building to they live in ect.
Analysis
The analyses will focus on birth outcomes of registered pregnancies during the time periods: 2009-12 (Pre-PIMI), 2013-16 (PIMI-I: The programme implemented in the three regions Oio, Biombo and Cacheu)
For each of these periods it will be described a) proportion of pregnant women who have sought antenatal consultations, b) the proportion of women who have obtained the recommended four antenatal consultations and c) the proportion of facility births.
Analyses will compare whether the proportions of a, b and c differ by period and area using binomial regression models with cluster robust standard errors to take into account that births within a village are more similar than birth in different village clusters. Having described potential changes in coverage, I will investigate whether the perinatal mortality differ by place of birth, and whether this depends on region and period.
Outcome
Data analysis will give an insight into the coverage differs before and after the introduction of the free health services, and whether the changed availability affects determinants of the three indicators.
Ethical consideration
The collection of data by HDSS has been going on in the current form since 1990 at the request of the Ministry of Health in Guinea-Bissau and UNICEF to determine child mortality levels in rural parts of Guinea-Bissau.
Litterature
Byberg S, Ostergaard MD, Rodrigues A, et al. Analysis of risk factors for infant mortality in the 1992-3 and 2002-3 birth cohorts in rural Guinea-Bissau.
Fisker AB, Hornshoj L, Rodrigues A, et al. Effects of the introduction of new vaccines in GuineaBissau on vaccine coverage, vaccine timeliness, and child survival: an observational study. The lancet global health 2014;2(8):e478-87
Hoj L, da Silva D, Hedegaard K, et al. Factors associated with maternal mortality in rural Guinea-Bissau. A longitudinal population-based study. BJOG : an international journal of obstetrics and gynaecology 2002;109(7):792-9.
Hoj L, da Silva D, Hedegaard K, et al. Maternal mortality: only 42 days? BJOG : an international journal of obstetrics and gynaecology 2003;110(11):995-1000.
Kristensen I, Aaby P, Jensen H. Routine vaccinations and child survival: follow up study in Guinea-Bissau, West Africa. BMJ 2000;321(7274):1435-8.
Mane M, Fisker AB, Ravn H, et al. Trends and determinants of mortality in women of reproductive age in rural Guinea-Bissau, West Africa - a cohort study. BMC women's health 2013;13:48.
Storgaard L, Rodrigues A, Martins C, et al. Development of BCG Scar and Subsequent Morbidity and Mortality in Rural Guinea-Bissau. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 2015;61(6):950-9.
Nielsen BU, Byberg S, Aaby P, et al. Seasonal variation in child mortality in rural Guinea-Bissau. Trop Med Int Health 2017;22(7):846-56. doi: 10.1111/tmi.12889
Jensen H, Benn CS, Lisse IM, et al. Survival bias in observational studies of the impact of routine immunizations on childhood survival. Trop Med Int Health 2007;12(1):5-14.
Ugeskrift for læger om Bandim Health Project (Danish)
https://www.bandim.org/
In August I am off to Guinea Bissau in west Africa for 6 months to do research. I am collaborating with Bandim Health Project (BHP) and Statens Serums Institut (Denmark, Copenhagen). BHP has no core funding and I need to finance my own research.
I would be honored if you would considered donating any amount that you can afford
Short and sweet
Guinea Bissau is one of the poorest countries in the world with a high mortality rate of expectant mothers and children. NGOs have built healthcare facilities in rural areas where women can come in for four checkups during pregnancy, give birth there and come for checkups and get their kids vaccinated after. Using data collected before and after the clinics were built I am going to find out if the clinics have had an impact on the survival of mothers and children. The goal is to find out how, where and why NGOs can invest time and money to optimise healthcare in Guinea Bissau and other countries.
The nitty gritty of the project
Background
The Bandim Health Project monitors health and survival of women and children in a nationally representative rural Health and Demographic Surveillance System (HDSS) in Guinea-Bissau. The HDSS was set up in 1989-90 with the support of UNICEF and the World Bank to collect data on health interventions and child mortality. The HDSS allows us to describe the implementation of interventions and their effects.
In 2013-14, the PIMI programme in Guinea-Bissau (Integrated Programme for the Reduction of Maternal and Child Mortality ) made prenatal consultations and facility based deliveries available free of charge at the government health centres in four of the nine health regions in Guinea-Bissau. In 2013, in Cacheu, Biombo, Oio and Farim the programme was implemented with support from the Portuguese NGO, VIDA , while theItalian NGO, AIFO implemented the programme in Gabu in 2014.
Method
The Bandim Health Project implements a Health and Demographic Surveillance System (HDSS) in Guinea-Bissau, with collection of data on pregnancies, births and use of health services. This infrastructure provides an opportunity to measure the coverage of the health services, also before the PIMI programme and thus provides an option to assess the effect of the PIMI programme on use of health services. Furthermore, the collected data allows us to characterise the users and non-users of health services and to assess the potential effect on neonatal mortality.
A long list of personal data is collected such as ethnicity, age, level of education, obstetric and gyneacological history, vaccination status, nutritional status and illnesses. Additionally information is collected on aspects such as how far the woman has to travel to the nearest clinic, do they have access to running water and other sanitation, do they have access to phones/ internet, what type of building to they live in ect.
Analysis
The analyses will focus on birth outcomes of registered pregnancies during the time periods: 2009-12 (Pre-PIMI), 2013-16 (PIMI-I: The programme implemented in the three regions Oio, Biombo and Cacheu)
For each of these periods it will be described a) proportion of pregnant women who have sought antenatal consultations, b) the proportion of women who have obtained the recommended four antenatal consultations and c) the proportion of facility births.
Analyses will compare whether the proportions of a, b and c differ by period and area using binomial regression models with cluster robust standard errors to take into account that births within a village are more similar than birth in different village clusters. Having described potential changes in coverage, I will investigate whether the perinatal mortality differ by place of birth, and whether this depends on region and period.
Outcome
Data analysis will give an insight into the coverage differs before and after the introduction of the free health services, and whether the changed availability affects determinants of the three indicators.
Ethical consideration
The collection of data by HDSS has been going on in the current form since 1990 at the request of the Ministry of Health in Guinea-Bissau and UNICEF to determine child mortality levels in rural parts of Guinea-Bissau.
Litterature
Byberg S, Ostergaard MD, Rodrigues A, et al. Analysis of risk factors for infant mortality in the 1992-3 and 2002-3 birth cohorts in rural Guinea-Bissau.
Fisker AB, Hornshoj L, Rodrigues A, et al. Effects of the introduction of new vaccines in GuineaBissau on vaccine coverage, vaccine timeliness, and child survival: an observational study. The lancet global health 2014;2(8):e478-87
Hoj L, da Silva D, Hedegaard K, et al. Factors associated with maternal mortality in rural Guinea-Bissau. A longitudinal population-based study. BJOG : an international journal of obstetrics and gynaecology 2002;109(7):792-9.
Hoj L, da Silva D, Hedegaard K, et al. Maternal mortality: only 42 days? BJOG : an international journal of obstetrics and gynaecology 2003;110(11):995-1000.
Kristensen I, Aaby P, Jensen H. Routine vaccinations and child survival: follow up study in Guinea-Bissau, West Africa. BMJ 2000;321(7274):1435-8.
Mane M, Fisker AB, Ravn H, et al. Trends and determinants of mortality in women of reproductive age in rural Guinea-Bissau, West Africa - a cohort study. BMC women's health 2013;13:48.
Storgaard L, Rodrigues A, Martins C, et al. Development of BCG Scar and Subsequent Morbidity and Mortality in Rural Guinea-Bissau. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 2015;61(6):950-9.
Nielsen BU, Byberg S, Aaby P, et al. Seasonal variation in child mortality in rural Guinea-Bissau. Trop Med Int Health 2017;22(7):846-56. doi: 10.1111/tmi.12889
Jensen H, Benn CS, Lisse IM, et al. Survival bias in observational studies of the impact of routine immunizations on childhood survival. Trop Med Int Health 2007;12(1):5-14.
Ugeskrift for læger om Bandim Health Project (Danish)
https://www.bandim.org/
Organizer
Camilla Vilhelmsen Field
Organizer
Odense M