SummaryThis paper assesses the factors influencing mistimed and unwanted pregnancies in Nepal separately using data from the 2011 Nepal Demographic and Health Survey. Women who had given birth within the five years before the survey were interviewed about the intendedness of their last pregnancy. The data were analysed with a chi-squared test, followed by multiple logistic regression analysis. Among the total 5391 participants, 11.29% and 13.13% reported their last pregnancy as mistimed and unwanted respectively. Logistic regression analysis showed that women from the hill region were more likely to report mistimed pregnancy, while women from the Western and Far-Western development regions were less likely to report mistimed pregnancy. Education status was positively correlated with the reporting of mistimed pregnancy. Women involved in agriculture, with full autonomy on household decision, with some exposure to mass media, belonging to higher age group and having third or higher parity were less likely to report mistimed pregnancy. Similarly, women from the Western development region had relatively higher odds of reporting unwanted pregnancy. Women with husbands involved in a paid job had lower odds of unwanted pregnancy. Women's autonomy was also positively correlated with unwanted pregnancy. Women with the intention to use contraceptive had lower odds of unwanted pregnancy. Interventions targeting the factors identified by this study could be useful in reduction of mistimed and unwanted pregnancies among Nepali women.
AbstractUnwanted and mistimed pregnancies impose threats on the health and well-being of the mother and child and limit the acquisition of optimal sexual and reproductive health services, especially in resource-constrained settings like the Democratic Republic of Congo (DRC). This study aimed to determine the prevalence and correlates of mistimed and unwanted pregnancies among women in the DRC. Data were drawn from the 2013–14 DRC Demographic Health Survey (EDS-RDC II). Bivariate and multivariate logistic regression analysis was performed to identify correlates of mistimed and unwanted pregnancies. Sequential logistic regression modelling including distal (place of residence), intermediate (socio-demographic and socioeconomic factors) and proximal (reproductive health and family planning) factors was performed using multivariate analysis. More than a quarter (28%) of pregnancies were reported as unintended (23% mistimed and 5% unwanted). Women who wanted no more children (aOR 1.21; CI: 1.01, 1.44) had less than 24 months of birth spacing (aOR 2.14; CI: 1.80, 2.54) and those who intended to use a family planning method (aOR 1.24; CI: 1.01, 1.52) reported more often that their last pregnancy was mistimed. Women with five or more children (aOR 2.13; CI: 1.30, 3.49), those wanting no more children (aOR 13.07; CI: 9.59, 17.81) and those with more than 48 months of birth spacing (aOR 2.31; CI: 1.26, 4.23) were more likely to report their last pregnancy as unwanted. The high rate of unintended pregnancies in the DRC shows the urgency to act on the fertility behaviour of women. The associated intermediate factors for mistimed and unwanted pregnancy indicate the need to accelerate family planning programmes, particularly for women of high parity and those who want no more children. Likewise, health promotion measures at the grassroots level to ensure women's empowerment and increase women's autonomy in health care are necessary to address the social factors associated with mistimed pregnancy.
Achieving universal health coverage (UHC) requires health financing systems that provide prepaid pooled resources for key health services without placing undue financial stress on households. Understanding current and future trajectories of health financing is vital for progress towards UHC. We used historical health financing data for 188 countries from 1995 to 2015 to estimate future scenarios of health spending and pooled health spending through to 2040.We extracted historical data on gross domestic product (GDP) and health spending for 188 countries from 1995 to 2015, and projected annual GDP, development assistance for health, and government, out-of-pocket, and prepaid private health spending from 2015 through to 2040 as a reference scenario. These estimates were generated using an ensemble of models that varied key demographic and socioeconomic determinants. We generated better and worse alternative future scenarios based on the global distribution of historic health spending growth rates. Last, we used stochastic frontier analysis to investigate the association between pooled health resources and UHC index, a measure of a country's UHC service coverage. Finally, we estimated future UHC performance and the number of people covered under the three future scenarios.
The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence no. SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law-2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. ; Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing. ; Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Aging of the National Institutes of Health (award P30AG047845), and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163). ; Peer reviewed
