Introduction: A low maternal body mass index and sub-optimal weight gain during pregnancy are long recognized risk factors for delivery of infants too small for gestational age, low birth weight as well as to increase the risk of subsequent obesity and hypertension in the off- spring. Maternal body mass index and maternal weight is positively associated with infant obesity risk. The main objective of this research was to determine the determinants of maternal body mass index and maternal weight simultaneously based on Ethiopia demographic health survey 2016 which was implemented in statistical package R. Methodology: Cross sectional study design was used from Ethiopia demographic health survey 2016. Bi-variate linear regression model was used to determine the factors that affect maternal body mass index and maternal weight simultaneously. Result: The bi-variate analysis of maternal pregnancy weight and body mass index identified that the co-variate husband educational level, preferred waiting time for birth, region, family size, frequency of watching television, maternal height, desire for more children and number of tetanus injections before pregnancy were statistically associated with maternal pregnancy weight. Moreover, educational level of husband, preferred waiting time for birth, region, family size, desire for more children, frequency of watching television and number of tetanus injections before pregnancy were statistically significant for maternal pregnancy body mass index in Ethiopia (p≤0.05). Conclusion: The risk of over pregnancy weight and body mass index increased when parent prefer high number of waiting time to birth another child in Ethiopia. In addition the risk of over pregnancy weight and body mass index increased when mother received more tetanus injection during pregnancy.
Published in | American Journal of Theoretical and Applied Statistics (Volume 8, Issue 6) |
DOI | 10.11648/j.ajtas.20190806.13 |
Page(s) | 214-220 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2019. Published by Science Publishing Group |
Bi-variate Linear Model, Ethiopian Demographic Health Survey, Body Mass Index, Pregnant Women
[1] | Nilufer Akgun, Huseyin L Keskin, Isık Ustuner, Gulden Pekcan, and Ayse F Avsar. 2017. Factors affecting pregnancy weight gain and relationships with maternal/fetal outcome in Turkey. Saudi medical journal. Vol. 38, No. 5, 2017, pp. 503-508. doi: 10.15537/smj.2017.5.19378. |
[2] | Radha Y Aras et al. 2013. Is maternal age risk factor for low birth weight? Archives of medicine and health sciences. Vol. 1, No. 1, 2013, pp. 33. doi: 10.4103/2321-4848.113558. |
[3] | Yolan Banda, Victoria Chapman, Robert L Goldenberg, Benjamin H Chi, Sten H Vermund, and Jeffrey SA Stringer. 2007. Influence of body mass index on pregnancy outcomes among HIV-infected and HIV-uninfected Zambian women. Tropical Medicine & International Health. Vol. 12, No. 7, 2007, pp. 856–861. doi: 10.1111/j.1365-3156.2007.01857.x. |
[4] | Helen Y Chu, Janet A Englund. 2014. Maternal immunization. Clinical Infectious Diseases. Vol. 59, No. 4, 2014, pp. 560–568. doi.org/10.1093/cid/ciu327 |
[5] | Agustin Conde-Agudelo, Anyeli Rosas-Bermu´dez, Ana C Kafury-Goeta. 2007. Effects of birth spacing on maternal health: a systematic review. American journal of obstetrics and gynecology. Vol. 196, No. 4, 2007, pp. 297–308. doi: 10.1016/j.ajog.2006.05.055. |
[6] | National Research Council et al. 2007. Influence of pregnancy weight on maternal and child health: workshop report. National Academies Press. |
[7] | Central Statistical Agency (CSA) and ICF International. 2012. “Ethiopia demographic and health survey 2011”. Addis Ababa, Ethiopia and Calverton, Maryland, USA: Central Statistical Agency and ICF International. |
[8] | Ashlesha Datar. 2017. The more the heavier? Family size and childhood obesity in the U.S. Social Science & Medicine. Vol. 180, 2017, pp. 143–151. doi.org/10.1016/j.socscimed.2017.03.035 |
[9] | Kara Goodrich, Mary Cregger, Sara Wilcox, Jihong Liu. 2013. A qualitative study of factors affecting pregnancy weight gain in African American women. Maternal and child health journal. Vol. 17, No. 3, 2013, pp. 432–440. doi: 10.1007/s10995-012-1011 1. |
[10] | Raquel PF Guin´e, Sofia R Fernandes, Jos´e Lu´ıs Abrantes, Ana Paula Cardoso, Manuela Ferreira. 2016. Factors affecting the body mass index in adolescents in Portuguese schools. Croatian Journal of Food Technology, Biotechnology and Nutrition Vol. 11, No. 2, 2016, pp. 58–64 |
[11] | Erica P Gunderson. 2009. Childbearing and obesity in women: weight before, during, and after pregnancy. Obstetrics and Gynecology Clinics. Vol. 36, No. 2, 2009, pp. 317-332. |
[12] | Rajat Das Gupta, Ibrahim Hossain Sajal, Mehedi Hasan, Ipsita Sutradhar, Mohammad Rifat Haider, Malabika Sarker. 2019. Frequency of television viewing and association with overweight and obesity among women of the reproductive age group in Myanmar: results from a nationwide cross-sectional survey. BMJ open Journal. Vol. 9, No. 3, 2019. doi.org/10.1136/bmjopen-2018-024680. |
[13] | David J Lilja. 2016. Linear Regression Using R: An Introduction to Data Modeling. University of Minnesota, Libraries Publishing. |
[14] | Elma Izze da Silva Magalh˜aes, Daniela Santana Maia, Carla Fabr´ıcia Arau´jo Bonfim, Michele Pereira Netto, Joel Alves Lamounier, Daniela da Silva Rocha. 2015. Prevalence and factors associated with excessive weight gain in pregnancy in health units in the southwest of Bahia. Brazilian Journal of Epidemiology. Vol. 18, No. 4, 2015, pp. 858–869. doi: 10.1590/1980-5497201500040014 |
[15] | Britta C Mullany, Stanley Becker, MJ Hindin. 2006. The impact of including husbands in antenatal health education services on maternal health practices in urban Nepal: results from a randomized controlled trial. Health education research. Vol. 22, No. 2, 2006, pp. 166–176. doi: 10.1093/her/cyl060. |
[16] | S´ev´erien Nkurunziza, S Ejaz Ahmed. 2011. Estimation strategies for the regression coefficient parameter matrix in multivariate multiple regression. Statistica Neerlandica. Vol. 6, No. 4, 2011, pp. 387–406. doi.org/10.1111/j.1467-9574.2011.00491.x. |
[17] | Alayne G Ronnenberg, Xiaobin Wang, Houxun Xing, Chanzhong Chen, Dafang Chen, Wenwei Guang, Aiqun Guang, Lihua Wang, Louise Ryan, Xiping Xu. 2003.Low preconception body mass index is associated with birth outcome in a prospective cohort of Chinese women. The Journal of nutrition. Vol. 133, No. 11, 2003, pp. 3449–3455. doi: 10.1093/jn/133.11.3449. |
[18] | Abdul Sattar, Shahbaz Baig, Naveed UR Rehman, Muhammad Badar Bashir. 2013. Factors affecting BMI. The Professional Medical Journal. Vol. 20, No. 6, 2013, pp. 956–964. |
[19] | Swati Singh, Constance E Shehu, Daniel C Nnadi, et al. 2016. The relationship between maternal body mass index and the birth weight of neonates in north-west Nigeria. Sahel Medical Journa. Vol. 19, No. 4, 2016, pp. 185-189. doi: 10.4103/1118-8561.196359. |
[20] | Tadese Ejigu Tafere, Mesganaw Fanthahun Afework, Alemayehu Woreku Yalew. 2018. Providers adherence to essential contents of antenatal care services increases birth weight in Bahir Dar city administration, North West Ethiopia: a prospective follow up study. Reproductive health. Vol. 15, 2018, No. 163. doi.org/10.1186/s12978-018-0610-8. |
APA Style
Melkamu Ayana Zeru, Kindu Kebede Gebre. (2019). Determine Joint Factors that Affect Maternal Weight and Body Mass Index Among Pregnant Women in Ethiopia: A Bi-variate Analysis. American Journal of Theoretical and Applied Statistics, 8(6), 214-220. https://doi.org/10.11648/j.ajtas.20190806.13
ACS Style
Melkamu Ayana Zeru; Kindu Kebede Gebre. Determine Joint Factors that Affect Maternal Weight and Body Mass Index Among Pregnant Women in Ethiopia: A Bi-variate Analysis. Am. J. Theor. Appl. Stat. 2019, 8(6), 214-220. doi: 10.11648/j.ajtas.20190806.13
AMA Style
Melkamu Ayana Zeru, Kindu Kebede Gebre. Determine Joint Factors that Affect Maternal Weight and Body Mass Index Among Pregnant Women in Ethiopia: A Bi-variate Analysis. Am J Theor Appl Stat. 2019;8(6):214-220. doi: 10.11648/j.ajtas.20190806.13
@article{10.11648/j.ajtas.20190806.13, author = {Melkamu Ayana Zeru and Kindu Kebede Gebre}, title = {Determine Joint Factors that Affect Maternal Weight and Body Mass Index Among Pregnant Women in Ethiopia: A Bi-variate Analysis}, journal = {American Journal of Theoretical and Applied Statistics}, volume = {8}, number = {6}, pages = {214-220}, doi = {10.11648/j.ajtas.20190806.13}, url = {https://doi.org/10.11648/j.ajtas.20190806.13}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20190806.13}, abstract = {Introduction: A low maternal body mass index and sub-optimal weight gain during pregnancy are long recognized risk factors for delivery of infants too small for gestational age, low birth weight as well as to increase the risk of subsequent obesity and hypertension in the off- spring. Maternal body mass index and maternal weight is positively associated with infant obesity risk. The main objective of this research was to determine the determinants of maternal body mass index and maternal weight simultaneously based on Ethiopia demographic health survey 2016 which was implemented in statistical package R. Methodology: Cross sectional study design was used from Ethiopia demographic health survey 2016. Bi-variate linear regression model was used to determine the factors that affect maternal body mass index and maternal weight simultaneously. Result: The bi-variate analysis of maternal pregnancy weight and body mass index identified that the co-variate husband educational level, preferred waiting time for birth, region, family size, frequency of watching television, maternal height, desire for more children and number of tetanus injections before pregnancy were statistically associated with maternal pregnancy weight. Moreover, educational level of husband, preferred waiting time for birth, region, family size, desire for more children, frequency of watching television and number of tetanus injections before pregnancy were statistically significant for maternal pregnancy body mass index in Ethiopia (p≤0.05). Conclusion: The risk of over pregnancy weight and body mass index increased when parent prefer high number of waiting time to birth another child in Ethiopia. In addition the risk of over pregnancy weight and body mass index increased when mother received more tetanus injection during pregnancy.}, year = {2019} }
TY - JOUR T1 - Determine Joint Factors that Affect Maternal Weight and Body Mass Index Among Pregnant Women in Ethiopia: A Bi-variate Analysis AU - Melkamu Ayana Zeru AU - Kindu Kebede Gebre Y1 - 2019/11/08 PY - 2019 N1 - https://doi.org/10.11648/j.ajtas.20190806.13 DO - 10.11648/j.ajtas.20190806.13 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 214 EP - 220 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20190806.13 AB - Introduction: A low maternal body mass index and sub-optimal weight gain during pregnancy are long recognized risk factors for delivery of infants too small for gestational age, low birth weight as well as to increase the risk of subsequent obesity and hypertension in the off- spring. Maternal body mass index and maternal weight is positively associated with infant obesity risk. The main objective of this research was to determine the determinants of maternal body mass index and maternal weight simultaneously based on Ethiopia demographic health survey 2016 which was implemented in statistical package R. Methodology: Cross sectional study design was used from Ethiopia demographic health survey 2016. Bi-variate linear regression model was used to determine the factors that affect maternal body mass index and maternal weight simultaneously. Result: The bi-variate analysis of maternal pregnancy weight and body mass index identified that the co-variate husband educational level, preferred waiting time for birth, region, family size, frequency of watching television, maternal height, desire for more children and number of tetanus injections before pregnancy were statistically associated with maternal pregnancy weight. Moreover, educational level of husband, preferred waiting time for birth, region, family size, desire for more children, frequency of watching television and number of tetanus injections before pregnancy were statistically significant for maternal pregnancy body mass index in Ethiopia (p≤0.05). Conclusion: The risk of over pregnancy weight and body mass index increased when parent prefer high number of waiting time to birth another child in Ethiopia. In addition the risk of over pregnancy weight and body mass index increased when mother received more tetanus injection during pregnancy. VL - 8 IS - 6 ER -