A comparative study of the effect of health insurance on women's use of health facility delivery: Evidence from demographic health survey in Benin Republic.

Studies in the Benin Republic have identified contextual factors that determine health facility delivery among women of reproductive age. However, it is not certain if the same set of factors predicts facility delivery for women who enrolled in health insurance and those who did not. The study seeks to compare the determinants of health facility delivery for mothers under health insurance and those that are not in the Benin Republic. The study used data for 33,078 women of reproductive age, drawn from the most recent Benin demographic and health survey (2017-18). The characteristics of the women were described using simple proportions and frequency. Binary Logistic regression was used to examine determinants of health facility delivery for both groups of women. The result showed that only 0.7% of the women were under health insurance coverage. The prevalence of health facility delivery was high in the enrolled group but not in the unenrolled group (98.3% vs. 87.8%). The uniform determinants of health facility delivery across the two groups were household wealth, education, employment, land/house ownership, media exposure, a minimum of four antenatal contacts, and place of residence. To improve the coverage of health facility delivery, a multi-pronged approach should be used to improve household socioeconomic status, encourage media use among women, expand education opportunities for women, and specifically target rural women in Benin.

Modeling Adaptation Strategies against Climate Change Impacts in Integrated Rice-Wheat Agricultural Production System of Pakistan.

There are numerous anticipated effects of climate change (CC) on agriculture in the developing and the developed world. Pakistan is among the top ten most prone nations to CC in the world. The objective of this analysis was to quantify the economic impacts of CC on the agricultural production system and to quantify the impacts of suggested adaptation strategies at the farm level. The study was conducted in the Punjab province's rice-wheat cropping system. For this purpose, climate modeling was carried out by using two representative concentration pathways (RCPs), i.e., RCPs 4.5 and 8.5, and five global circulation models (GCMs). The crop modeling was carried out by using the Agricultural Production Systems Simulator (APSIM) and the Decision Support System for Agrotechnology Transfer (DSSAT) crop simulation models (CSMs), which were tested on the cross-sectional data of 217 farm households collected from the seven strata in the study area. The socio-economic impacts were calculated using the Multidimensional Impact Assessment Tradeoff Analysis Model (TOA-MD). The results revealed that CC's net economic impact using both RCPs and CSMs was negative. In both CSMs, the poverty status was higher in RCP 8.5 than in RCP 4.5. The adaptation package showed positive results in poverty reduction and improvement in the livelihood conditions of the agricultural households. The adoption rate for DSSAT was about 78%, and for APSIM, it was about 68%. The adaptation benefits observed in DSSAT were higher than in APSIM. The results showed that the suggested adaptations could have a significant impact on the resilience of the atmospheric changes. Therefore, without these adaptation measures, i.e., increase in sowing density, improved cultivars, increase in nitrogen use, and fertigation, there would be negative impacts of CC that would capitalize on livelihood and food security in the study area.