Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in

No abstract

Objectives We examined the association between incorrect knowledge of ovulation and unintentional pregnancy and child among young women in sub-Saharan Africa countries. Methods Using Pearson's Chi-square, t test, multiple logistic regression, and likelihood ratio test, we analyzed Demographic and Health Survey data (2008-2017) of 169,939 young women (15-24 year). Results The range of prevalence of incorrect knowledge of ovulation was 51% in Comoros and 89.6% in Sao Tome and Principe, while unintentional pregnancy ranged between 9.4% in the Republic of Benin and 59.6% in Namibia. The multivariate result indicates a strong association between incorrect knowledge of ovulation and unintentional pregnancy (OR = 1.17; p \ 0.05) and unintentional child (OR = 1.15; p \ 0.05). Conclusions Adolescent women (15-19) generally have poor knowledge of ovulation and are more likely to report an unintentional pregnancy/child than women between ages 20-24. To reduce the burden of unintentional child/pregnancy in Africa, fertility knowledge should not only be improved on but must consider the sociocultural context of women in different countries that might affect the adoption of such intervention programs. Pragmatic efforts, such as building community support for young women to discuss and share their experiences with professionals and educate them on fertility and sexuality, are essential. Keywords Adolescence Á Reproductive health Á Knowledge of ovulation Á Fertility awareness Á Contraception Á Unintentional pregnancy Á Medical geography Á Africa This article is part of the special issue ''Sexual and reproductive health of young people-Focus Africa''. The Rudolf Geigy Foundation (Basel, Switzerland) funded the open access publication of this article.

The 2019 coronavirus disease (COVID-19) has exacerbated inequality in the United States of America (USA). Black, indigenous, and people of color (BIPOC) are disproportionately affected by the pandemic. This study examines determinants of COVID-19 case fatality ratio (CFR) based on publicly sourced data from January 1 to December 18, 2020, and sociodemographic and rural-urban continuum data from the US Census Bureau. Nonspatial negative binomial Poisson regression and geographically weighted Poisson regression were applied to estimate the global and local relationships between the CFR and predictors—rural-urban continuum, political inclination, and race/ethnicity in 2407 rural counties. The mean COVID-19 CFR among rural counties was 1.79 (standard deviation (SD) = 1.07; 95% CI 1.73-1.84) higher than the total US counties ( M = 1.69, SD = 1.18; 95% CI: 1.65-1.73). Based on the global NB model, CFR was positively associated with counties classified as “completely rural” (incidence rate ratio (IRR) = 1.24; 95% CI: 1.12-1.39) and “mostly rural” (IRR = 1.26; 95% CI: 1.15-1.38) relative to “mostly urban” counties. Nonspatial regression indicates that COVID-19 CFR increases by a factor of 8.62, 5.87, 2.61, and 1.36 for one unit increase in county-level percent Blacks, Hispanics, American Indians, and Asian/Pacific Islanders, respectively. Local spatial regression shows CFR was significantly higher in rural counties with a higher share of BIPOC in the Northeast and Midwest regions, and political inclination predicted COVID-19 CFR in rural counties in the Midwest region. In conclusion, spatial and racial/ethnic disparities exist for COVID-19 CFR across the US rural counties, and findings from this study have implications for public health. Supplementary Information The online version contains supplementary material available at 10.1007/s40615-021-01006-7.

To improve geographical accessibility to health facilities in rural Ghana, it has been recommended that additional health facilities be built. Resource constraints make this recommendation infeasible. Using location-allocation models, this paper demonstrates that in the Suhum District of Ghana substantial improvements in accessibility can be achieved with better locational choices and without additional facilities. Also, additional facilities will produce little improvement in accessibility if location is not explicitly considered. The paper demonstrates the utility of location-allocation models for improving accessibility to services in the Third World.