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A Binary Logistic Regression Model to Identify the Factors Associated with Unmet Need for Family Planning Among Married Women

机译:二元Logistic回归模型确定已婚妇女未满足计划生育需求的相关因素

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Background: Unplanned pregnancy related to unmet need is a worldwide problem that affects society and bad impact on health of the women. Contraceptive use has increased in the recent years in the developing countries like India, has the desire for smaller families, however, millions of women, more than 150 million women want to delay or avoid pregnancy but are not using any type of contraception, these women are considered to have unmet need for family planning. Aim and Objectives: Factors which are associated with unmet need for family planning among married women and test binary logistic regression model Methods: 1200 married women in the age group of 15-49 years were selected randomly from Kalaburagi from which 600 from urban and 600 from rural areas by using multistage sampling and data analyzed by using SPSS software Results: Estimated odds ratio and higher odds of having unmet need for family planning for various factors are estimated and test of significance at p0.05. Conclusion: We found, Age, Education of married women, Education of husband, Family Income, Ideal age for marriage having higher odds ratios indicate higher unmet need and logistic regression model is quite useful model for estimating unmet need for family planning.
机译:背景:与未满足的需求有关的计划外怀孕是一个世界性的问题,它影响社会并严重影响妇女的健康。近年来,在像印度这样的发展中国家,避孕药具的使用有所增加,它希望有较小的家庭,但是,数百万的妇女,超过1.5亿的妇女希望延迟或避免怀孕,但并未使用任何避孕方法,这些妇女被认为没有满足计划生育的需要。目的和目标:已婚妇女未满足计划生育需求的相关因素和检验二元逻辑回归模型方法:从Kalaburagi中随机选择1200名15-49岁年龄段的已婚妇女,其中城市600名,女性600名结果:对各种因素造成的计划生育需求未得到满足的估计几率和较高几率被估计,并且显着性检验为p <0.05。结论:我们发现,年龄,已婚妇女的受教育程度,丈夫的受教育程度,家庭收入,具有较高比值比的理想结婚年龄表明未满足的需求较高,而逻辑回归模型对于估算未满足的计划生育需求非常有用。

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