Factors Associated With Nutritional Status Of Reproductive Age Women
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Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, Lieferzeit: 11 Tage, zzgl. Versandkosten.
This study evaluates the performance of parametric Ordinary Least Square (OLS) and non-parametric regression (quantile function) method to determine factors affecting nutritional status of women of reproductive age in Nigeria. A national representative sample of women within reproductive age (15-49 years) within households in communities was obtained from the Nigeria Demographic and Health Survey (NDHS 2013). The Body Mass Index of women defined as weight/height2 was the outcome variable while the explanatory variables include age, family size, total children ever born, marital status, highest level of education, place of residence region, wealth index. OLS regression was used to determine the average effect of factors on BMI while QR was used to determine how a particular percentile of the BMI distribution was associated with covariates Analysis was done on STATA version 12 while graphs were done using R version 3.2.0. A total of 31, 828 women were included in the study. The mean age of women was 29 years (SD=7.0), 49.2% had no formal education and 23.5% belonged to the poorest wealth quintile. It was shown that only 16% of variation has been predicted by linear regression.

Lieferung aus: Deutschland, Versandkostenfrei.
Factors Associated With Nutritional Status Of Reproductive Age Women: This study evaluates the performance of parametric Ordinary Least Square (OLS) and non-parametric regression (quantile function) method to determine factors affecting nutritional status of women of reproductive age in Nigeria. A national representative sample of women within reproductive age (15-49 years) within households in communities was obtained from the Nigeria Demographic and Health Survey (NDHS 2013). The Body Mass Index of women defined as weight/height2 was the outcome variable while the explanatory variables include age, family size, total children ever born, marital status, highest level of education, place of residence region, wealth index. OLS regression was used to determine the average effect of factors on BMI while QR was used to determine how a particular percentile of the BMI distribution was associated with covariates Analysis was done on STATA version 12 while graphs were done using R version 3.2.0. A total of 31, 828 women were included in the study. The mean age of women was 29 years (SD=7.0), 49.2% had no formal education and 23.5% belonged to the poorest wealth quintile. It was shown that only 16% of variation has been predicted by linear regression. Englisch, Taschenbuch.

Lieferung aus: Deutschland, Versandkostenfrei innerhalb von Deutschland.
This study evaluates the performance of parametric Ordinary Least Square (OLS) and non-parametric regression (quantile function) method to determine factors affecting nutritional status of women of reproductive age in Nigeria. A national representative sample of women within reproductive age (15-49 years) within households in communities was obtained from the Nigeria Demographic and Health Survey (NDHS 2013). The Body Mass Index of women defined as weight/height2 was the outcome variable while This study evaluates the performance of parametric Ordinary Least Square (OLS) and non-parametric regression (quantile function) method to determine factors affecting nutritional status of women of reproductive age in Nigeria. A national representative sample of women within reproductive age (15-49 years) within households in communities was obtained from the Nigeria Demographic and Health Survey (NDHS 2013). The Body Mass Index of women defined as weight/height2 was the outcome variable while the explanatory variables include age, family size, total children ever born, marital status, highest level of education, place of residence region, wealth index. OLS regression was used to determine the average effect of factors on BMI while QR was used to determine how a particular percentile of the BMI distribution was associated with covariates Analysis was done on STATA version 12 while graphs were done using R version 3.2.0. A total of 31, 828 women were included in the study. The mean age of women was 29 years (SD=7.0), 49.2% had no formal education and 23.5% belonged to the poorest wealth quintile. It was shown that only 16% of variation has been predicted by linear regression. Sofort lieferbar Lieferzeit 1-2 Werktage.