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DC Field | Value | Language |
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dc.contributor.author | Odelola, J. O. | - |
dc.contributor.author | Ige, E. F. | - |
dc.date.accessioned | 2025-01-07T13:19:49Z | - |
dc.date.available | 2025-01-07T13:19:49Z | - |
dc.date.issued | 2016-02 | - |
dc.identifier.issn | 2449-1268 | - |
dc.identifier.other | ui_art_odelola_predictive_2016 | - |
dc.identifier.other | Port Harcourt JONAPHER-SD 6(2), pp. 1-14 | - |
dc.identifier.uri | http://ir.library.ui.edu.ng/handle/123456789/9610 | - |
dc.description.abstract | The study examined socio-demographic factors as predictors of preeclampsia among pregnant women attending government hospitals in Ibadan, Oyo State. A descriptive survey research design was adopted for this study. Simple random sampling technique was used to select 460 respondents for the study. Self-developed and validated questionnaires were used to collect data. Inferential statistics of linear regression was used to test hypotheses at 0.05 alpha level. The findings revealed that age, (F(1,458) = 3.105; p<0.05), poverty (F1,458) = 24.386; p<0.05), heredity (F1,458) = 50.154; p<0.05), parity (F1,458) = 123.631; p<0.05) and sedentary lifestyle (F1,458) = 180.903; p<0.05) contributed significantly to preeclampsia. It was concluded that socio-demographic variables predicted incidence of pre-eclampsia. It was suggested that health education programme in which prevention of pre-eclampsiawill be prominent should be organised for pregnant women attending government hospitals in Oyo State, Nigeria. | en_US |
dc.language.iso | en | en_US |
dc.subject | Socio-demographic factors | en_US |
dc.subject | Pregnant women | en_US |
dc.subject | Preeclampsia | en_US |
dc.subject | Government hospitals | en_US |
dc.title | Predictive interaction of socio-demographic variables on incidence of pre-eclampsia among pregnant women attending government hospitals in Ibadan, Oyo State Nigeria | en_US |
dc.type | Article | en_US |
Appears in Collections: | scholarly works |
Files in This Item:
File | Description | Size | Format | |
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(22)ui_art_odelola_predictive_2016.pdf | 2.24 MB | Adobe PDF | View/Open |
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