Objectives Low birth weight (LBW) is a major public health concern, especially in developing countries, and is frequently related to child morbidity and mortality. This study aimed to identify key determinants that influence the prevalence of LBW in selected developing countries.
Methods Secondary data analysis was conducted using 10 recent Demography and Health Surveys from developing countries based on the availability of the required information for the years 2010 to 2013. Associations of demographic, socioeconomic, community-based, and individual factors of the mother with LBW in infants were evaluated using multivariate logistic regression analysis.
Results The overall prevalence of LBW in the study countries was 15.9% (range, 9.0 to 35.1%). The following factors were shown to have a significant association with the risk of having an LBW infant in developing countries: maternal age of 35 to 49 years (adjusted odds ratio [aOR], 1.7; 95% confidence interval [CI], 1.2 to 3.1; p<0.01), inadequate antenatal care (ANC) (aOR, 1.7; 95% CI, 1.1 to 2.8; p<0.01), illiteracy (aOR, 1.5; 95% CI, 1.1 to 2.7; p<0.001), delayed conception (aOR, 1.8; 95% CI, 1.4 to 2.5; p<0.001), low body mass index (aOR, 1.6; 95% CI, 1.2 to 2.1; p<0.001) and being in the poorest socioeconomic stratum (aOR, 1.4; 95% CI, 1.1 to 1.8; p<0.001).
Conclusions This study demonstrated that delayed conception, advanced maternal age, and inadequate ANC visits had independent effects on the prevalence of LBW. Strategies should be implemented based on these findings with the goal of developing policy options for improving the overall maternal health status in developing countries.
Summary
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Comparison of therapeutic interventions for recurrent pregnancy loss in association with antiphospholipid syndrome: A systematic review and network meta‐analysis Xiang Liu, Yuxuan Qiu, Esther Dawen Yu, Shang Xiang, Rui Meng, Kai fan Niu, Huili Zhu American Journal of Reproductive Immunology.2020;[Epub] CrossRef
Factors Associated with Preterm Birth and Low Birth Weight in Abu Dhabi, the United Arab Emirates Zainab Taha, Ahmed Ali Hassan, Ludmilla Wikkeling-Scott, Dimitrios Papandreou International Journal of Environmental Research and Public Health.2020; 17(4): 1382. CrossRef
Evolutionary Strategies for Body Size Michael A. Little Frontiers in Endocrinology.2020;[Epub] CrossRef
Association of maternal determinants with low birth weight babies in tea garden workers of Assam Shashi Nandar Kumar, Sheikh Raisuddin, Kh. Jitenkumar Singh, Banajit Bastia, Deepa Borgohain, Long Teron, Santanu Kumar Sharma, Arun Kumar Jain Journal of Obstetrics and Gynaecology Research.2020; 46(5): 715. CrossRef
Predictors of Low Birth Weight at Lumbini Provincial Hospital, Nepal: A Hospital-Based Unmatched Case Control Study Saneep Shrestha, Sandeep Shrestha, Upasana Shakya Shrestha, Kamala Gyawali Advances in Preventive Medicine.2020; 2020: 1. CrossRef
Wealth-related inequalities of women’s knowledge of cervical cancer screening and service utilisation in 18 resource-constrained countries: evidence from a pooled decomposition analysis Rashidul Alam Mahumud, Syed Afroz Keramat, Gail M Ormsby, Marufa Sultana, Lal B. Rawal, Khorshed Alam, Jeff Gow, Andre M. N. Renzaho International Journal for Equity in Health.2020;[Epub] CrossRef
Determinants of Low Birth Weight among Newborns Delivered at Public Hospitals in Sidama Zone, South Ethiopia: Unmatched Case-Control Study Muse Bututa Bekela, Mulugeta Shegaze Shimbre, Teshale Fikadu Gebabo, Mengesha Boko Geta, Abayneh Tunje Tonga, Eshetu Andarge Zeleke, Negussie Boti Sidemo, Agegnehu Bante Getnet Journal of Pregnancy.2020; 2020: 1. CrossRef
Epidemiology of low birth weight in Iran: A systematic review and meta-analysis Mehdi Shokri, Parviz Karimi, Hadis Zamanifar, Fatemeh Kazemi, Milad Azami, Gholamreza Badfar Heliyon.2020; 6(5): e03787. CrossRef
Social inequalities in low birthweight outcomes in Sri Lanka: evidence from the Demographic and Health Survey 2016 Gayathri Abeywickrama, Sabu S Padmadas, Andrew Hinde BMJ Open.2020; 10(5): e037223. CrossRef
Development and Validation of a Risk Score to Predict Low Birthweight Using Characteristics of the Mother: Analysis from BUNMAP Cohort in Ethiopia Hamid Y. Hassen, Seifu H. Gebreyesus, Bilal S. Endris, Meselech A. Roro, Jean-Pierre Van Geertruyden Journal of Clinical Medicine.2020; 9(5): 1587. CrossRef
Adverse fetal outcomes and its associated factors in Ethiopia: a systematic review and meta-analysis Getnet Gedefaw, Birhan Alemnew, Asmamaw Demis BMC Pediatrics.2020;[Epub] CrossRef
Wealth stratified inequalities in service utilisation of breast cancer screening across the geographical regions: a pooled decomposition analysis Rashidul Alam Mahumud, Khorshed Alam, Syed Afroz Keramat, Andre M. N. Renzaho, Md. Golam Hossain, Rezwanul Haque, Gail M. Ormsby, Jeff Dunn, Jeff Gow Archives of Public Health.2020;[Epub] CrossRef
Prenatal Mercury Exposure in Pregnant Women from Suriname’s Interior and Its Effects on Birth Outcomes Gaitree K. Baldewsingh, Jeffrey K. Wickliffe, Edward D. van Eer, Arti Shankar, Ashna D. Hindori-Mohangoo, Emily W. Harville, Hannah H. Covert, Lizheng Shi, Maureen Y. Lichtveld, Wilco C.W.R. Zijlmans International Journal of Environmental Research and Public Health.2020; 17(11): 4032. CrossRef
Level of physical activity and other maternal characteristics during the third trimester of pregnancy and its association with birthweight at term in South Ethiopia: A prospective cohort study Meseret Legesse, Jemal Haider Ali, Md Dilshad Manzar, Mohammed Salahuddin, Hamid Yimam Hassen, Frank T. Spradley PLOS ONE.2020; 15(7): e0236136. CrossRef
Determinants of low birth weight among live birth newborns delivered at public hospitals in Gamo Gofa Zone, South Ethiopia: Unmatched case control study Alemu Basazin Mingude, Woiynshet Gebretsadik, Dresilgn Misker, Gashaw Garedew Woldeamanuel SAGE Open Medicine.2020;[Epub] CrossRef
Association does not imply prediction: the accuracy of birthweight in predicting child mortality and anthropometric failure Akshay Swaminathan, Rockli Kim, S.V. Subramanian Annals of Epidemiology.2020; 50: 7. CrossRef
Factors associated with low birth weight at term: a population-based linkage study of the 100 million Brazilian cohort Ila R. Falcão, Rita de Cássia Ribeiro-Silva, Marcia F. de Almeida, Rosemeire L. Fiaccone, Aline dos S. Rocha, Naiá Ortelan, Natanael J. Silva, Enny S. Paixao, Maria Yury Ichihara, Laura C. Rodrigues, Mauricio L. Barreto BMC Pregnancy and Childbirth.2020;[Epub] CrossRef
Prevalence and Determinants of Low Birth Weight in Ethiopia: A Systematic Review and Meta-Analysis Nuradin Abusha Katiso, Getachew Mullu Kassa, Gedefaw Abeje Fekadu, Abadi Kidanemariam Berhe, Achenef Asmamaw Muche Advances in Public Health.2020; 2020: 1. CrossRef
Socioeconomic and demographic factors associated with low birth weight in Nepal: Data from 2016 Nepal demographic and health survey Benojir Ahammed, Md Maniruzzaman, Farzana Ferdausi, MdMenhazul Abedin, MdTanvir Hossain Social Health and Behavior.2020; 3(4): 158. CrossRef
Maternal exposure to Wenchuan earthquake and prolonged risk of offspring birth outcomes: a natural experiment study Qiguo Lian, Jiaying Ni, Jun Zhang, Julian Little, Shan Luo, Lin Zhang BMC Pregnancy and Childbirth.2020;[Epub] CrossRef
Exploring the association between adverse maternal circumstances and low birth weight in neonates: a nationwide population-based study in Bangladesh Md Mostaured Ali Khan, Md Golam Mustagir, Md Rafiqul Islam, Md Sharif Kaikobad, Hafiz TA Khan BMJ Open.2020; 10(10): e036162. CrossRef
Regional trends in birth weight in low- and middle-income countries 2013–2018 Irene Marete, Osayame Ekhaguere, Carla M. Bann, Sherri L. Bucher, Paul Nyongesa, Archana B. Patel, Patricia L. Hibberd, Sarah Saleem, Robert L. Goldenberg, Shivaprasad S. Goudar, Richard J. Derman, Ana L. Garces, Nancy F. Krebs, Elwyn Chomba, Waldemar A. Reproductive Health.2020;[Epub] CrossRef
Modeling the Effect of Mother's Characteristics on the Weight of a Newborn Oluwafemi Samson Balogun, Donald Douglas Atsa'am, Toluwalase Janet Akingbade, Emmanuel Awuni Kolog, Richard O. Agjei, Samuel Nii Odoi Devine International Journal of Childbirth.2020; 10(4): 206. CrossRef
Maternal determinants of low birth weight among Indian children: Evidence from the National Family Health Survey-4, 2015-16 Ankita Zaveri, Pintu Paul, Jay Saha, Bikash Barman, Pradip Chouhan, William Joe PLOS ONE.2020; 15(12): e0244562. CrossRef
Risk of low birth weight and exposure to type of cooking fuel in India Shekhar Chauhan , Ratna Patel International Journal of Pregnancy & Child Birth.2020; 6(1): 8. CrossRef
Low birth weight in Jordan: a hospital-based study Khitam Mohammed, Insaf Shaban, Nemeh Al-Akour, Manal Kassab, Debra Creedy The Journal of Maternal-Fetal & Neonatal Medicine.2020; 33(18): 3050. CrossRef
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Maternal dietary patterns and risk of adverse pregnancy (hypertensive disorders of pregnancy and gestational diabetes mellitus) and birth (preterm birth and low birth weight) outcomes: a systematic review and meta-analysis Kelemu Tilahun Kibret, Catherine Chojenta, Ellie Gresham, Teketo K Tegegne, Deborah Loxton Public Health Nutrition.2019; 22(3): 506. CrossRef
Early Identification of Preterm Neonates at Birth With a Tablet App for the Simplified Gestational Age Score (T-SGAS) When Ultrasound Gestational Age Dating Is Unavailable: Protocol for a Validation Study Archana B Patel, Kunal Kurhe, Amber Prakash, Savita Bhargav, Suchita Parepalli, Elizabeth V Fogleman, Janet L Moore, Dennis D Wallace, Hemant Kulkarni, Patricia L Hibberd JMIR Research Protocols.2019; 8(3): e11913. CrossRef
Spatial smoothing of low birth weight rate in Bangladesh using Bayesian hierarchical model Mohammad Samsul Alam, Syed Shahadat Hossain, Farha Ferdous Sheela Journal of Applied Statistics.2019; 46(10): 1870. CrossRef
Determinants and adverse perinatal outcomes of low birth weight newborns delivered in Hawassa University Comprehensive Specialized Hospital, Ethiopia: a cohort study Melaku Desta, Mesfin Tadese, Bekalu Kassie, Mihrete Gedefaw BMC Research Notes.2019;[Epub] CrossRef
Risk factors for low birth weight in hospitals of North Wello zone, Ethiopia: A case-control study Tesfahun Mulatu Wachamo, Nigus Bililign Yimer, Asmamaw Demis Bizuneh, Eduardo Ortiz-Panozo PLOS ONE.2019; 14(3): e0213054. CrossRef
How does birth weight affect health and human capital? A short‐ and long‐term evaluation Marie Baguet, Christelle Dumas Health Economics.2019; 28(5): 597. CrossRef
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The Relationship Between Food Insecurity and Anthropometric Measures at Birth in Low Income Households Asieh Ahmadihoseini, Nasrin Omidvar, Mohsen Nematy, Mohammad Safarian, Maryam Salehi Iranian Journal of Pediatrics.2019;[Epub] CrossRef
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Measuring perinatal and postpartum quality of life of women and associated factors in semi-urban Bangladesh Rashidul Alam Mahumud, Nausad Ali, Nurnabi Sheikh, Raisul Akram, Khorshed Alam, Jeff Gow, Abdur Razzaque Sarker, Marufa Sultana Quality of Life Research.2019; 28(11): 2989. CrossRef
Assessing the impact of antenatal care utilization on low birthweight in India: Analysis of the 2015–2016 National Family Health Survey Pintu Paul, Ankita Zaveri, Pradip Chouhan Children and Youth Services Review.2019; 106: 104459. CrossRef
Low birth weight: prevalence and associated factors among newborns at hospitals in Kambata-Tembaro zone, southern Ethiopia 2018 Abebe Alemu, Mulatu Abageda, Biruk Assefa, Getnet Melaku Pan African Medical Journal.2019;[Epub] CrossRef
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Determinants of low birth weight among neonates born in Amhara Regional State Referral Hospitals of Ethiopia: unmatched case control study Getnet Asmare, Nigusie Berhan, Mengistu Berhanu, Animut Alebel BMC Research Notes.2018;[Epub] CrossRef
Both maternal and paternal risk factors for term singleton low birthweight infants in rural Chinese population: a population-based, retrospective cohort study Shi Chen, Yingying Yang, Yimin Qu, Yun Zou, Huijuan Zhu, Hongbo Yang, Fengying Gong, Linjie Wang, Yu Jiang, Bill Q. Lian, Cynthia Liu, Chengsheng Yan, Jianqiang Li, Qing Wang, Shi-kun Zhang, Hui Pan Scientific Reports.2018;[Epub] CrossRef
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Pre-pregnancy body mass index (BMI) and maternal gestational weight gain are positively associated with birth outcomes in rural Malawi Austrida Gondwe, Per Ashorn, Ulla Ashorn, Kathryn G. Dewey, Kenneth Maleta, Minyanga Nkhoma, John Mbotwa, Josh M. Jorgensen, Jacobus P. van Wouwe PLOS ONE.2018; 13(10): e0206035. CrossRef
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Low birth weight and its associated factors in Ethiopia: a systematic review and meta-analysis Aklilu Endalamaw, Eshetu Haileselassie Engeda, Daniale Tekelia Ekubagewargies, Getaneh Mulualem Belay, Mekuriaw Alemayehu Tefera Italian Journal of Pediatrics.2018;[Epub] CrossRef
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OBJECTIVE To examine the relationship between hypertension prevalence and the four commonest anthropometric measurements for obesity(body mass index(BMI), wasit-hip ratio(WHR), waist circumference(WC) and body fat in Korean adults. METHODS: We studied the cross-sectional association of the anthropometric indices and blood pressure in 1,197 individuals( who were participants in the population-based cohort study). Hypertension was defined as blood pressure 160/95 mmHg or current use of antihypertensive medication. Informations on life-style factors were obtained from personal interview. RESULTS: There were close associations between BMI, WHR and WC with blood pressure in both men and women. After age adjustment, BMI and WC showed significantly positive correlation with systolic and diastolic blood pressure levels in both men and women. Odds ratio(ORs) of being hypertensive were estimated comparing the highest to the lowest quantile, adjusting for age, smoking status, alcohol intake levels, education attainment. The simultaneously adjusted ORs of being hypertensive, comparing the highest vs the lowest categories, was for BMI 2.0(95% confidence interval(CI)=0.9-3.2) in men and 3.2 (95% CI=1.7-6.1) in women, for WC 2.1(95% CI=1.0-4.4) in men and 3.1(95% CI=1.6-5.9) in women, for fat(%) 4.2(95% CI=1.9-9.5) in men and 2.1(95% CI=1.2-3.6) in women. CONCLUSION: In addition to measures of overall obesity(BMI) as well as central obesity(WHR, WC), body fat(%) was independently associated with prevalence of hypertension. Among obesity indices, body fat was the most predictor variable in hypertensive state in male and BMI was in female.
This study was conducted to evaluate the association of various lifestyle with blood pressure. The data were obtained from the individuals who got routine health examination in Department of Occupational Medicine, Yeungnam University Hospital from June to September, 1996. Among these people, we selected 130 cases of hypertensives(97 males, 33 females) and 150 normotensives(70 males, 80 females) and study was conducted. The authors collected the information of the risk factors related to hypertension such as age, family history of hypertension, fasting blood sugar, serum total cholesterol, alcohol consumption(g/week), smoking history, relative amount of salt intake(low, moderate, high), the frequency of weekly meat consumption, BMI, daily coffee consumption(cups/day) and the frequency of regular exercise(frequency/week) through questionnaire and laboratory test. By simple analysis, BMI was significantly associated with hypertension in male(p<0.05), and the frequency of weekly meat consumption was significantly associated with hypertension in female(p<0.05). Using logistic regression model, elevated odds ratio was noted for fasting blood sugar, serum total cholesterol, family history of hypertension, alcohol consumption, salt intake and BMI, and reduced odds ratio was noted for coffee consumption and exercise in male but fasting blood sugar(odds ratio=1.022, 95% CI=1.000-1.044), family history in both of parents(odds ratio=3.301, 95% CI=1.864-4.738), salt intake(odds ratio=1.690, 95% CI=1.082-2.298) and BMI(odds ratio=1.204, 95% CI=1.065-1.343) were statistically significant(p<0.05). In female, elevated odds ratio was noted in serum total cholesterol, family history of hypertension, BMI and meat consumption. Of all these variables, the family history of hypertension in either of parents(odds ratio=4.981, 95% CI=3.650-6.312), family history in both of parents(odds ratio=16.864, 95% CI=14.577-19.151), BMI(odds ratio=1.167, 95% CI=1.016-1.318) and meat consumption(odds ratio=2.048, 95% CI=1.133-2.963) showed statistically significant association with hypertension in female(p<0.05).
Work-related low back pain is one of the major factors that cause the loss of working power especially in actively working age, therefore controlling the work-related low back pain is one of the major issues in the field of industrial safety and health. This study was performed for detecting the risk factors and proposing the efficient control program of the work-related low back pain. The subjects were male workers employed at the manufacturing industry in Pusan with longer than 6 month's working duration. The data was collected by self-reported questionnaire and interview from May 1 to October 31, 1992. The contents of questionnaire were as follows : the experience of low back within the recent one month, general characteristics(age, marital status, education level, religion, regular exercise), physical characteristics(height, weight), employment status(working duration, daily working hours, rest during work, satisfaction for the job), type of work and working environments(posture, forward bending, lifting and movement, satisfaction for table and chair). The result was analyzed for 608 entire respondents by case-control comparative method. The number of cases was 152 with a history of work-related low back pain, so the relative frequency of self-reported work-related low back pain was 25.0%, and the number of controls was 344 without any history of low back pain. As a result, two characteristics of the employment status(working duration, satisfaction for the job) and all characteristics of type of work and working environments showed a statistical significance between the case and control groups(p<0.01). The Odds ratios of these variables for Work-related low back pain were calculated. They were 7.88 for the satisfaction for chair, 7.86 for lifting and movement, 3.31 for satisfaction for table, and 2.22 for bending forward(p<0.01). And for the multivariate logistic regression analysis confirmed that unsatisfaction for table was independent risk factor for Work-related low back pain. In summary, though this study was based upon the self-reported questionnaire and the subjective complaints, the satisfaction for chair, lifting and movement, satisfaction for table, and bending forward concerned with the type of work and working environments were considered as the main factors causing the work-related low back pain, and the work-related low back pain may be preventable by the ergonomic control of these factors.