The Impact of Extremely Low Birth Weight Babies on the Family

• Loading metrics

Open up Access

Peer-reviewed

Inquiry Commodity

Low nascency weight and its associated hazard factors: Health facility-based instance-control study

• Anil G. C.,
• Prem Lal Basel,
• Sarswoti Singh

x

• Published: June 22, 2020
• https://doi.org/ten.1371/journal.pone.0234907

Figures

Abstruse

Groundwork

Low birth weight is a preventable public health problem. Information technology is an of import determinant of child survival and evolution, as well as long-term consequences similar the onset of non-catching affliction in the life course. A large number of mortality and morbidity tin exist prevented by addressing the factors associated with low birth weight. The main objective of this study was to identify associated risk factors of low birth weight.

Methodology

A health facility-based unmatched instance-command study was carried out from July 2018 to March 2019 among the mothers who delivered in health facilities of Dang district of Nepal from 17^th August to xvi^th Nov 2018. The full sample size for the report was 369; 123 cases and 246 controls. Cases and controls were randomly selected independent of the exposure status in the ratio of 1:2. Data regarding exposure status was assessed through interviews and medical records. Mothers who delivered outside Dang districts were excluded from the study. Ethical clearance was obtained from the Institutional Review Committee (IRC) of the Institute of Medicine, Tribhuvan Academy and written consent was taken from each participant subsequently explaining the objectives of the report.

Results

Multivariate logistic regression found that having the kitchen in the same living house (AOR 2.7, CI: ane.five–four.8), fe intake less than 180 tablets (AOR 3.2, CI: 1.vii–5.vii), maternal weight proceeds during second and third trimester less than 6.53 kg (AOR ii.half dozen, CI: ane.five–4.7), co-morbidity during pregnancy (AOR 2.4, CI: 1.three–iv.5), preterm birth (AOR 2.nine, CI: 1.4–vi.1) were the risk factors associated with low birth weight.

Determination

Having the kitchen in the same living business firm, iron intake less than 180 tablets during pregnancy, maternal weight gain less than 6.53 kg during the second and 3rd trimester, co-morbidity during pregnancy and preterm birth were the run a risk factors associated with low birth weight.

Citation: K. C. A, Basel PL, Singh S (2020) Low nascence weight and its associated hazard factors: Wellness facility-based case-command study. PLoS ONE 15(half-dozen): e0234907. https://doi.org/ten.1371/periodical.pone.0234907

Editor: Pranil Man Singh Pradhan, Tribhuvan University Plant of Medicine, NEPAL

Received: Nov 11, 2019; Accepted: June four, 2020; Published: June 22, 2020

Copyright: © 2020 K. C. et al. This is an open up access commodity distributed under the terms of the Creative Commons Attribution License, which permits unrestricted apply, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant information are inside the paper and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

World Wellness Organisation defines depression nascence weight (LBW) every bit the nascency weight less than 2500 grams irrespective of gestational historic period [1]. LBW is a valuable public health indicator of maternal wellness, diet, healthcare delivery, and poverty every bit LBW babies are at a higher risk of death and illness soon afterward birth and non-communicable disease in the life course [two]. LBW infants are 20 times more probable to develop complications and die in comparison to normal weight babies [3]. LBW babies are in the potential run a risk of cerebral deficits, motor delays, cognitive palsy, and other beliefs and psychological problem [4–eight]. The household price, likewise every bit wellness system costs, could be saved by reducing the burden of LBW [9]. The pathophysiology of low birth weight is unclear, whereas intrauterine growth retardation (IUGR) and preterm nascence considered as the cause of LBW. IUGR is the outcome of insufficient uterine–placental perfusion and fetal nutrition affecting the overall anthropometric parameter of the fetus. IUGR newborn has typical features of malnutrition. Actress-uterine infection, trauma, affliction, IUGR, fetal infection, and anomalies are the contributing factors for preterm nascency, resulting in growth retardation which ultimately results in LBW [3, 10, eleven]. LBW is considered a significant public health problem as information technology is estimated that xv% to 20% of all nascence worldwide are LBW. The prevalence of LBW varies across regions with the highest 28% in Southern asia and the lowest 6% in Eastern asia and the Pacific region [12]. The prevalence of LBW in Nepal ranges from 12% to 21.6%, [13–15]. A few descriptive and hospital-based case-control studies have been washed in Nepal [14–19]. These descriptive and hospital-based studies could not correspond the risk factors of LBW at the customs level as these studies had taken participants from hospitals only. Hence this study aims to place the associated risk factors of LBW at the community level by including the participants from the community level health facilities.

Methodology

An unmatched instance-control study was used. This written report was conducted in Dang district of Nepal. This report was approved by the Institutional Review Committee (IRC) of Institute of Medicine (IOM) Tribhuvan University on August 19, 2018. The study population was mothers, who delivered their babies in the governmental health institutions (28 birthing centers and 3 hospitals) of Dang from 17^th August to xvi^th November 2018. The report population was divided into case and control equally per the post-obit definition.

Case

Mother delivering singleton live-born infant with birth weight less than 2500 grams without any built anomalies and were originally from Dang district.

Command

Female parent delivering singleton alive-built-in babe with birth weight more than or equal to 2500 grams without any congenital anomalies and were from the same Dang district.

The sample size was calculated using EpiInfo software version 7. This was calculated by taking power at 80%, confidence level equally 95%, the percentage of control exposed as 65.40, the odds ratio of 2.06 from the maternal weight against LBW [20], and the ratio of example to control was 1:ii. The total sample size was 369 with 123 cases and 246 controls. The eligible numbers of participants were enlisted from the maternal and neonate health register of 28 birthing centers and iii hospitals of Dang Commune. One hundred and twenty-three cases were selected from the list of 224 cases and 246 controls from the listing of 777 controls randomly independent of exposure status by generating random numbers. The 123 cases and 246 controls with the highest random number were visited with the aid of FCHV, local leaders, teachers for the data collection. Face to face interview was done with the participants for the collection of data using a semi-structured questionnaire. Information regarding weight gain, age, ANC visit, nascency weight, comorbidity, gestational age etc was taken through reviewing Antenatal Care (ANC) card and Maternal and newborn register to avoid possible recall bias. The tool was adapted from the previous studies done in Nepal [16–18, 20, 21]. The tool was translated into the Nepali linguistic communication and pretested in Dhulikhel municipality; of Kavrepalanchok commune amongst 10 per centum of sample size i.e. 12 cases and 24 controls.

Information entry was washed in Epi data Version 3.i following coding. Data analysis was done using SPSS software version 21. Bivariate associations between contained variables and low nativity weight were tested through the Chi-square test and the association was analyzed by calculating crude odds ratios (OR) at 95% confidence interval through binary logistic regression. Multivariate logistic regression was examined for the relationship between independent variables and low birth weight to address the confounding consequence. Hosmer and Lemeshow test was used to test the goodness-of-fit for regression models. The examination statistic was 0.69 (p > 0.05) that showed that the model adequately fit the information.

Upstanding clearance was obtained from the Institutional Review Committee (IRC) of the Institute of Medicine, Tribhuvan University. Permission was taken from the District Public Health Role (DPHO) Dang and respective wellness facilities. Written consent was taken from each participant after explaining the objectives of the study. Afterwards the interview, the mothers were informed nigh the importance of growth monitoring, exclusive breastfeeding, immunization, and appropriate fourth dimension of weaning.

Results

Table 1 depicts that the mean historic period of the participants was 23 years (SD 4.4 years). Getting back up from their husbands in day to day activities during pregnancy was quite mutual. The major (66.4%) fuel used during cooking was firewood and kerosene. The majority (53.1%) of the household did non have a separate kitchen. Majority (55.3%) of participants' family members did not smoke any form of cigarette. A small portion (2.two%) of participants had the addiction of smoking cigarettes during pregnancy. Two-third (67%) of participants had their meal thrice a day and 64.two% had included additional nutrient groups in their meal at the time of pregnancy. Majority (78%) of participants had attended ANC visit as per the protocol of the government of Nepal. Similarly, 73% of participants had taken 180 or more iron tablets during pregnancy. More than half of the participants had gained weight less than vi.53 kg during the 2nd and third trimester. 50-four percentages of participants had 1 kid. Majority (59.3% amid cases and 86.two% among controls) of the research participants did not face any health problems (co-morbidities) during their pregnancy and 14.6% of the babies were born before 37 weeks of gestation.

Table 2 shows the bivariate and multivariate assay of dependent and contained variables. In bivariate analysis; support from husband during pregnancy, use of firewood and kerosene during cooking, having kitchen in the same living house, cigarette smoking past family members, cigarette smoking by mother during pregnancy, use of additional food groups in their diet during pregnancy, 4 ANC visit as per protocol of Government of Nepal, fe tablets intake less than 180 tablets during pregnancy, weight gain during pregnancy less than half-dozen.53 kg in-between second and third trimester, mother delivering her start infant, health problem during pregnancy and preterm baby were associated with low birth weight.

In multivariate assay, having kitchen in the same living house (AOR 2.vii, CI: 1.5–iv.eight), Iron intake less than 180 tablets (AOR iii.two, CI: 1.seven–5.seven), maternal weight gain less than half dozen.53 kg during second and third trimester (AOR 2.half-dozen, CI: ane.five–4.seven), co-morbidities during pregnancy (AOR 2.iv, CI: i.3–iv.five) and preterm birth (AOR 2.9, CI: 1.4–6.1) were significantly associated at 95% conviction interval with the low birth weight. Similarly, historic period of mother, support from married man during pregnancy, apply of firewood and kerosene during cooking, smoking habit of the mother, smoking by family member, food frequency less than iii per day, use of whatsoever additional food group during pregnancy, iv ANC visit as per protocol, outset children was not associated with LBW in this study.

Give-and-take

This study analyzed the socio-demographic factors, maternal factors, and co-morbidities during recent pregnancy confronting low birth weight during delivery.

The maternal historic period is considered as a key factor for the healthy outcome of pregnancy. This study revealed no statistical association between maternal age and low nativity weight which contradicts with the study done in Nepal, that shows a higher take chances of delivering low nascence weight babies by female parent age less than 20 and more than thirty years [16, 17, eighteen]. Smoking during pregnancy had a negative result on the growth and evolution of the fetus because of chemical substances present in information technology. Nicotine present in the cigarette crusade vasoconstriction resulting in the low oxygen menstruation to the fetus and Carbon-monoxide forms carboxyhemoglobin which inhibits the oxygen release to fetal tissues [22] In bivariate analysis mother habit of smoking had a higher gamble of low birth weight in reference to the female parent who did not fume a cigarette (OR 6.3, 95% CI: 1.2–31.v). This finding is consequent with the findings of similar studies done in Bangladesh and Turkey [23, 24]. Though there was a risk, however, in that location was no meaning association betwixt smoking and depression nascence weight in multivariate assay. This could be explained probably due to the small number of smokers in the study population. Moreover, it tin as well exist explained by the social desirability bias, induced due to social stigma.

This study identified the location of the kitchen in the living house, iron intake less than 180 tablets, weight gain less than vi.53 kg during the 2nd and third trimester, comorbidity during pregnancy, and preterm nativity as the take a chance factors for low birth weight. The finding reveals that the cooking fuels namely firewood and kerosene use had a risk for LBW with reference to LPG and Biogas even so, information technology was not statistically significant. This finding contradicts to the find of the study done past Kadam Twelvemonth et al. and Washam C [25, 26], however, this study revealed that having a kitchen in the same living house (proxy of indoor air pollution) had 2.5 times higher take chances of delivering low nascency weight which may be due to, living in the same house had higher run a risk and duration of exposure to the pollutants like PM_2.5, PM_ten, NO₂, SO₂, CO caused by burning of fuels, leading to the impaired supply of oxygen, nutrition to the fetus resulting in the negative impact on the growth and development of fetus [27, 28]. The amount of exposure was non measured quantitatively in this study.

This study showed that total iron tablet intake during pregnancy was associated with the birth weight of the child. Mothers who took less than 180 tablets of iron during their pregnancy were three times more likely to evangelize low nativity weight babies with reference to mothers who took iron equal to or more than 180 tablets during their pregnancy period (AOR iii.2, CI: i.7–5.eight). This finding is similar to the studies conducted in Nepal [16, 29]. Low iron tablets intake causes the poor delivery of fe to the fetus thereby impair in proper hormonal and neuronal regulation of pregnancy and poor oxygenation to the fetus leading to the poor growth and development of the fetus [30]. However, the fe intake through diet during pregnancy was not measured in both cases and control.

The minimum standard weight gain during the 2nd and third trimester is prepare as 6.53 kg [31]. Women who gained weight less than 6.53 kg during the second and third trimester had 3 times higher take chances of delivering low birth weight baby with reference to women whose weight proceeds was 6.53 kg or in a higher place (AOR ii.viii, CI: 1.half dozen–five.0). This finding is similar to the written report done in Bangladesh [32] and Mozambique [33]. The weight gain during pregnancy is dumb due to ill health, poor sanitation, and inadequate balance nutrition which at the end hamper the proper growth and development of the infant.

Women who had at least ane health problem during their pregnancy were at higher risk of delivering low birth weight in comparing to women without any wellness trouble (AOR 2.6, CI: 1.4–4.eight). This finding is consistent with the study done in Nepal [17, 20]. As well, this study suggests that mother delivering baby before completion of 37 weeks of gestation had higher risk of delivering low nascency weight than the mothers who evangelize the term baby (AOR 2.six, CI: 1.2–five.5) which is in line with the written report washed in Nepal [17], Federal democratic republic of ethiopia [34] and Republic of kenya [35]. Biologically it can be explained that preterm birth was less likely to become sufficient time for maturity, growth, and nutrient intake which therefore can lead to depression nascency weight [36].

In this report, the researcher has retrieved maternal data namely gestational weight, iron tablets intake, gestational historic period, co-morbidity, frequency of ANC visits, and birth weight of a baby from ANC card and maternity register to limit the recall bias. The pick of cases and controls were based on the records of maternal and neonatal register therefore, information technology is less likely that this written report has misclassification biases both in the exposure and case-control categories. Controls were selected randomly independent of the exposure status and every bit there was no non-response in both the group, it is less likely that this report would suffer from option biases. However, the report had some limitations. The findings might be influenced by social desirability bias. The findings could not be generalized as the study was confined in the health institutions of i district. The details of comorbidity during pregnancy, the micro-nutritional condition of the mother, and the quality of ANC visit were not evaluated which may touch on the outcome of this written report.

Decision and recommendation

This written report concluded that the having the kitchen in the same living house (proxy of indoor air pollution), iron intake less than 180 tablets during pregnancy, weight gain less than 6.35 kg during the 2d and third trimester, co-morbidity during pregnancy, and preterm delivery were plant to be associated risk factors of low nascency weight. Thus, identified risk factors can be efficiently prevented through modest doable actions that a family unit can utilize and the mother tin easily deport out. Maternal health programs can exist directed towards motivating and tracking pregnant mothers for complete iron tablets intake during her pregnancy period. Intake of residue diet as per the protocol of the Regime of Nepal for healthy growth and development of the child within the uterus is of paramount importance. Family should help the mother for adequate rest, nutrition and healthy behavior to prevent chance factors identified in this study.

Supporting information

Acknowledgments

Authors would similar to give thanks Mr. Keshav Raj Pandit, Senior Public Wellness Administrator and the unabridged staff of DPHO, Dang for their kind support in the coordination with health facilities, as well equally to Female Community Health Volunteers, local leaders and teachers for their back up during data collection. The authors would also like to express sincere thank you to all enquiry participants for their valuable time and information.

References

1. 1. International Statistical Classification of Diseases and Related Health Bug- x. Disorders related to brusque gestation and low nativity weight, non elsewhere classified: World Health System; 2016.
2. ii. Agbozo F, Abubakari A, Der J, Jahn A. Prevalence of low birth weight, macrosomia and stillbirth and their relationship to associated maternal risk factors in Hohoe Municipality, Ghana. Midwifery. 2016;40:200–vi. pmid:27474932
   • View Commodity
   • PubMed/NCBI
   • Google Scholar
3. 3. UNICEF, WHO. Low Nascence Weight: Country, regional and global estimates. UNICEF, New York, 2004.
4. 4. Mathewson KJ, Chow CH, Dobson KG, Pope EI, Schmidt LA, Van Lieshout RJ. Mental wellness of extremely low nativity weight survivors: A systematic review and meta-analysis. Psychological bulletin. 2017;143(4):347–83. pmid:28191983
   • View Article
   • PubMed/NCBI
   • Google Scholar
5. five. Al Hazzani F, Al-Alaiyan S, Hassanein J, Khadawardi E. Brusk-term issue of very low-birth-weight infants in a tertiary intendance hospital in Saudi Arabia. Annals of Saudi Medicine. 2011;31(vi):581–5. pmid:22048502
   • View Article
   • PubMed/NCBI
   • Google Scholar
6. 6. Chang H-Y, Sung Y-H, Wang S-One thousand, Lung H-L, Chang J-H, Hsu C-H, et al. Short- and Long-Term Outcomes in Very Depression Birth Weight Infants with Admission Hypothermia. PloS one. 2015;10(7):e0131976. pmid:26193370
   • View Article
   • PubMed/NCBI
   • Google Scholar
7. 7. Fitzgibbons SC, Ching Y, Yu D, Carpenter J, Kenny Grand, Weldon C, et al. Mortality of necrotizing enterocolitis expressed by birth weight categories. Journal of Pediatric Surgery.44(vi):1072–6. pmid:19524719
   • View Article
   • PubMed/NCBI
   • Google Scholar
8. 8. Fan RG, Portuguez MW, Nunes ML. Noesis, behavior and social competence of preterm depression birth weight children at school age. Clinics. 2013;68(7):915–21. pmid:23917653
   • View Article
   • PubMed/NCBI
   • Google Scholar
9. 9. Sicuri E, Bardají A, Sigauque B, Maixenchs M, Nhacolo A, Nhalungo D, et al. Costs Associated with Low Birth Weight in a Rural Surface area of Southern Mozambique. PloS one. 2011;6(12):e28744. pmid:22174885
   • View Commodity
   • PubMed/NCBI
   • Google Scholar
10. 10. Sharma D, Shastri Southward, Sharma P. Intrauterine Growth Restriction: Antenatal and Postnatal Aspects. Clinical medicine insights Pediatrics. 2016;ten:67–83. pmid:27441006
    • View Article
    • PubMed/NCBI
    • Google Scholar
11. 11. Cutland CL, Lackritz EM, Mallett-Moore T, Bardaji A, Chandrasekaran R, Lahariya C, et al. Low birth weight: Case definition & guidelines for data collection, analysis, and presentation of maternal immunization safety data. Vaccine. 2017;35(48 Pt A):6492–500.
    • View Article
    • Google Scholar
12. 12. Global Nutrition Targets 2025: Low Birth Weight Policy Brief. World Health System, 2014.
13. thirteen. Ministry of Health Nepal, New ERA, and, ICF. Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health, New ERA, ICF International; 2017.
14. 14. Malla M, Joshi DR, Chhetri One thousand, Pandey P. Prevalence and contributing factors of low birth weight babies in institutional delvery. Journal of Patan Academy of Health Sciences. 2015;two(1):four.
    • View Article
    • Google Scholar
15. xv. Prajapati R, Shrestha South, Bhandari Due north. Prevalence and Associated Factors of Depression Nascence Weightamong Newborns in a Tertiary Level Hospital in Nepal. Kathmandu University Medical Periodical. 2018;16(61):4.
    • View Commodity
    • Google Scholar
16. xvi. Karuna Laxmi Shakya NS, Amod Kumar Poudyal, Rajendra Prasad Koju, Peter Oyloe and Sharad Raj Onta. Fundamental factors associated with low birth weight at term in Nepal: A Instance Control study. International Periodical of Clinical and Biomedical Research. 2015;one(2):8.
    • View Article
    • Google Scholar
17. 17. Sharma SR, Giri South, Timalsina U, Bhandari SS, Basyal B, Wagle Grand, et al. Depression nativity weight at term and its determinants in a tertiary hospital of Nepal: a example-control study. PloS one. 2015;10(four):e0123962. pmid:25853813
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
18. 18. Yadav DK, Chaudhary U, Shrestha N. Risk factors associated with low nascence weight. Periodical of Nepal Wellness Research Quango. 2011;9(2):159–64. pmid:22929846
    • View Article
    • PubMed/NCBI
    • Google Scholar
19. xix. Kandel KP, Kafle Due south. Risk Factors Associated with Depression Birth Weight among Deliveries at Bharatpur Hospital. Periodical of Nepal Health Research Council. 2017;fifteen(two):169–73. pmid:29016589
    • View Article
    • PubMed/NCBI
    • Google Scholar
20. 20. Bhaskar RK, Deo KK, Neupane U, Chaudhary Bhaskar S, Yadav BK, Pokharel HP, et al. A Instance Command Study on Risk Factors Associated with Depression Birth Weight Babies in Eastern Nepal. International journal of pediatrics. 2015;2015:807373. pmid:26783406
    • View Article
    • PubMed/NCBI
    • Google Scholar
21. 21. Shakya KL, Shrestha N, Kisiju P, Onta SR. Association of Maternal Factors with Low Birth Weight in Selected Hospitals of Nepal. Periodical of Nepal Wellness Research Council. 2015;13(30):121–5. pmid:26744196
    • View Article
    • PubMed/NCBI
    • Google Scholar
22. 22. Lambers DS, Clark KE. The maternal and fetal physiologic effects of nicotine. Seminars in Perinatology. 1996;20(2):115–26. pmid:8857697
    • View Article
    • PubMed/NCBI
    • Google Scholar
23. 23. Hosain GM, Chatterjee N, Begum A, Saha SC. Factors associated with low birthweight in rural People's republic of bangladesh. Journal of tropical pediatrics. 2006;52(2):87–91. pmid:16014761
    • View Article
    • PubMed/NCBI
    • Google Scholar
24. 24. Atessahin E, Pirincci E. Take chances Factors Associated with Low Birth Weight Infants Built-in in Elazig, Eastern of Turkey. Iranian periodical of public health. 2015;44(ix):1299–300. pmid:26587509
    • View Article
    • PubMed/NCBI
    • Google Scholar
25. 25. Kadam YR, Mimansa A, Chavan PV, Gore Advertizing. Effect of prenatal exposure to kitchen fuel on birth weight. Indian periodical of customs medicine: official publication of Indian Association of Preventive & Social Medicine. 2013;38(4):212–vi.
    • View Commodity
    • Google Scholar
26. 26. Washam C. Cooking with wood may fuel low birth weight: kitchen smoke puts babies at risk. Environmental wellness perspectives. 2008;116(4):A173–A.
    • View Article
    • Google Scholar
27. 27. Boy E, Bruce N, Delgado H. Nascency weight and exposure to kitchen woods fume during pregnancy in rural Republic of guatemala. Environmental wellness perspectives. 2002;110(1):109–14. pmid:11781172
    • View Article
    • PubMed/NCBI
    • Google Scholar
28. 28. Oliveira BFAd, Ignotti E, Hacon SS. A systematic review of the physical and chemic characteristics of pollutants from biomass burning and combustion of fossil fuels and health effects in Brazil. Cadernos de Saúde Pública. 2011;27:1678–98. pmid:21986597
    • View Article
    • PubMed/NCBI
    • Google Scholar
29. 29. Bondevik GT, Lie RT, Ulstein M, Kvåle M. Maternal hematological status and risk of depression nativity weight and preterm delivery in Nepal. Acta Obstetricia et Gynecologica Scandinavica. 2001;80(5):402–8. pmid:11328215
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
30. xxx. Bristles JL. Micronutrient Deficiencies in the Start Months of Life: Karger Publishers; 2004.
31. 31. Coffey D. Prepregnancy body mass and weight gain during pregnancy in India and sub-Saharan Africa. Proceedings of the National Academy of Sciences. 2015;112(eleven):3302–vii.
    • View Commodity
    • Google Scholar
32. 32. Hassoune S, Bassel South, Nani S, Elbouri H, Zine K, Maaroufi A. [Maternal factors associated with depression birth weight: case-control study in a Moroccan public hospital]. The Pan African medical journal. 2015;20:303. pmid:26161226
    • View Article
    • PubMed/NCBI
    • Google Scholar
33. 33. Osman North, Challis K, Cotiro 1000, Nordahl Thousand, Berström S. Perinatal result in an obstetric cohort of Mozambican women. Journal of tropical pediatrics. 2001;47(1):30–viii. pmid:11245348
    • View Article
    • PubMed/NCBI
    • Google Scholar
34. 34. Gebremedhin Grand, Ambaw F, Admassu E, Berhane H. Maternal associated factors of depression birth weight: a infirmary based cross-sectional mixed study in Tigray, Northern Ethiopia. BMC pregnancy and childbirth. 2015;15:222. pmid:26382941
    • View Article
    • PubMed/NCBI
    • Google Scholar
35. 35. Muchemi OM, Echoka East, Makokha A. Factors associated with low nascence weight among neonates born at Olkalou District Hospital, Central Region, Kenya. The Pan African medical periodical. 2015;20:108. pmid:26090056
    • View Commodity
    • PubMed/NCBI
    • Google Scholar
36. 36. Negrato CA, Gomes MB. Depression birth weight: causes and consequences. Diabetology & Metabolic Syndrome. 2013;v(1):49.
    • View Article
    • Google Scholar

kirchnersuchoson.blogspot.com

Source: https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0234907

Bagikan Artikel ini