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      Safer sex negotiation and parity among women in sub-Saharan Africa

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          Abstract

          Women’s ability to negotiate for safer sex has effects on their sexual and reproductive health. This study investigated the association between safer sex negotiation and parity among women in sub-Saharan Africa. The data were sourced from the Demographic and Health Surveys of 28 sub-Saharan African countries conducted from 2010 to 2019. A total of 215,397 women aged 15–49 were included in the study. Multilevel logistic analysis was conducted to examine the association between safer sex negotiation and parity among women in sub-Saharan Africa. The results were presented as adjusted odds ratios (aOR) and the significance level set at p<0.05. The overall prevalences of safer sex negotiation and high parity among women in sub-Saharan Africa were 82.7% and 52.1%, respectively. The prevalence of high parity ranged from 32.3% in Chad to 72.1% in Lesotho. The lowest prevalence of safer sex negotiation was in Chad (16.8%) while the highest prevalence was recorded in Rwanda (99.7%). Women who had the capacity to negotiate for safer sex were less likely to have high parity compared with those who had no capacity to negotiate for safer sex (aOR = 0.78, CI: 0.75–0.81). Other factors that were associated with high parity were age, educational level, marital status, exposure to media, contraceptive use, religion, wealth quintile, sex of household head, and place of residence. The study identified significant association between safer sex negotiation and high parity among women of reproductive age in sub-Saharan Africa. It is worth noting that women’s ability to negotiate for safer sex could reduce high parity among women in sub-Saharan Africa. Therefore, policies and programmes aimed at birth control or reducing high parity among women could be targeted at improving their capacity to negotiate for safer sex through education.

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          The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies

          Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study’s generalizability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, case-control and cross-sectional studies. We convened a two-day workshop, in September 2004, with methodologists, researchers and journal editors to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results and discussion sections of articles. Eighteen items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available on the web sites of PLoS Medicine, Annals of Internal Medicine and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.
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            Demographic and health surveys: a profile.

            Demographic and Health Surveys (DHS) are comparable nationally representative household surveys that have been conducted in more than 85 countries worldwide since 1984. The DHS were initially designed to expand on demographic, fertility and family planning data collected in the World Fertility Surveys and Contraceptive Prevalence Surveys, and continue to provide an important resource for the monitoring of vital statistics and population health indicators in low- and middle-income countries. The DHS collect a wide range of objective and self-reported data with a strong focus on indicators of fertility, reproductive health, maternal and child health, mortality, nutrition and self-reported health behaviours among adults. Key advantages of the DHS include high response rates, national coverage, high quality interviewer training, standardized data collection procedures across countries and consistent content over time, allowing comparability across populations cross-sectionally and over time. Data from DHS facilitate epidemiological research focused on monitoring of prevalence, trends and inequalities. A variety of robust observational data analysis methods have been used, including cross-sectional designs, repeated cross-sectional designs, spatial and multilevel analyses, intra-household designs and cross-comparative analyses. In this profile, we present an overview of the DHS along with an introduction to the potential scope for these data in contributing to the field of micro- and macro-epidemiology. DHS datasets are available for researchers through MEASURE DHS at www.measuredhs.com.
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              Fertility, mortality, migration, and population scenarios for 195 countries and territories from 2017 to 2100: a forecasting analysis for the Global Burden of Disease Study

              Summary Background Understanding potential patterns in future population levels is crucial for anticipating and planning for changing age structures, resource and health-care needs, and environmental and economic landscapes. Future fertility patterns are a key input to estimation of future population size, but they are surrounded by substantial uncertainty and diverging methodologies of estimation and forecasting, leading to important differences in global population projections. Changing population size and age structure might have profound economic, social, and geopolitical impacts in many countries. In this study, we developed novel methods for forecasting mortality, fertility, migration, and population. We also assessed potential economic and geopolitical effects of future demographic shifts. Methods We modelled future population in reference and alternative scenarios as a function of fertility, migration, and mortality rates. We developed statistical models for completed cohort fertility at age 50 years (CCF50). Completed cohort fertility is much more stable over time than the period measure of the total fertility rate (TFR). We modelled CCF50 as a time-series random walk function of educational attainment and contraceptive met need. Age-specific fertility rates were modelled as a function of CCF50 and covariates. We modelled age-specific mortality to 2100 using underlying mortality, a risk factor scalar, and an autoregressive integrated moving average (ARIMA) model. Net migration was modelled as a function of the Socio-demographic Index, crude population growth rate, and deaths from war and natural disasters; and use of an ARIMA model. The model framework was used to develop a reference scenario and alternative scenarios based on the pace of change in educational attainment and contraceptive met need. We estimated the size of gross domestic product for each country and territory in the reference scenario. Forecast uncertainty intervals (UIs) incorporated uncertainty propagated from past data inputs, model estimation, and forecast data distributions. Findings The global TFR in the reference scenario was forecasted to be 1·66 (95% UI 1·33–2·08) in 2100. In the reference scenario, the global population was projected to peak in 2064 at 9·73 billion (8·84–10·9) people and decline to 8·79 billion (6·83–11·8) in 2100. The reference projections for the five largest countries in 2100 were India (1·09 billion [0·72–1·71], Nigeria (791 million [594–1056]), China (732 million [456–1499]), the USA (336 million [248–456]), and Pakistan (248 million [151–427]). Findings also suggest a shifting age structure in many parts of the world, with 2·37 billion (1·91–2·87) individuals older than 65 years and 1·70 billion (1·11–2·81) individuals younger than 20 years, forecasted globally in 2100. By 2050, 151 countries were forecasted to have a TFR lower than the replacement level (TFR <2·1), and 183 were forecasted to have a TFR lower than replacement by 2100. 23 countries in the reference scenario, including Japan, Thailand, and Spain, were forecasted to have population declines greater than 50% from 2017 to 2100; China's population was forecasted to decline by 48·0% (−6·1 to 68·4). China was forecasted to become the largest economy by 2035 but in the reference scenario, the USA was forecasted to once again become the largest economy in 2098. Our alternative scenarios suggest that meeting the Sustainable Development Goals targets for education and contraceptive met need would result in a global population of 6·29 billion (4·82–8·73) in 2100 and a population of 6·88 billion (5·27–9·51) when assuming 99th percentile rates of change in these drivers. Interpretation Our findings suggest that continued trends in female educational attainment and access to contraception will hasten declines in fertility and slow population growth. A sustained TFR lower than the replacement level in many countries, including China and India, would have economic, social, environmental, and geopolitical consequences. Policy options to adapt to continued low fertility, while sustaining and enhancing female reproductive health, will be crucial in the years to come. Funding Bill & Melinda Gates Foundation.
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                Author and article information

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                Journal
                Journal of Biosocial Science
                J. Biosoc. Sci.
                Cambridge University Press (CUP)
                0021-9320
                1469-7599
                January 2023
                January 06 2022
                January 2023
                : 55
                : 1
                : 74-86
                Article
                10.1017/S0021932021000651
                34986926
                4051d303-a2a7-4ef0-93dd-cbf22124a91b
                © 2023

                https://creativecommons.org/licenses/by/4.0/

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