The Nations of Sub-saharan Africa Have Low Rates of Low-birthweight Babies.
- Research
- Open Access
- Published:
Regional trends in birth weight in low- and centre-income countries 2013–2018
Reproductive Health book 17, Commodity number:176 (2020) Cite this article
Abstruse
Background
Nativity weight (BW) is a strong predictor of neonatal outcomes. The purpose of this written report was to compare BWs between global regions (southern asia, sub-Saharan Africa, Central America) prospectively and to decide if trends exist in BW over time using the population-based maternal and newborn registry (MNHR) of the Global Network for Women'sand Children's Wellness Enquiry (Global Network).
Methods
The MNHR is a prospective observational population-based registryof 6 research sites participating in the Global Network (2013–2018), within five depression- and heart-income countries (Kenya, Zambia, India, Pakistan, and Republic of guatemala) in threeglobal regions (sub-Saharan Af rica, s Asia, Key America). The nativity weights were obtained for all infants built-in during the report period. This was done either by abstracting from the infants' health facility records or from straight measurement by the registry staff for infants born at dwelling house. After controlling for demographic characteristics, mixed-effect regression models were utilized to examine regional differences in birth weights over time.
Results
The overall BW meanswere higher for the African sites (Republic of zambia and Kenya), 3186 g (SD 463 g) in 2013 and 3149 g (SD 449 thousand) in 2018, ascompared to Asian sites (Belagavi and Nagpur, India and Pakistan), 2717 thou (SD450 g) in 2013 and 2713 g (SD 452 thousand) in 2018. The Central American site (Republic of guatemala) had a mean BW intermediate between the African and southward Asian sites, 2928 chiliad (SD 452) in 2013, and 2874 g (SD 448) in 2018. The low nativity weight (LBW) incidence was highest in the south Asian sites (Republic of india and Pakistan) and lowest in the African sites (Kenya and Republic of zambia). The size of regional differences varied somewhat over time with slight decreases in the gap in birth weights between the African and Asian sites and slight increases in the gap between the African and Cardinal American sites.
Conclusions
Overall, BWmeans by global region did not change significantly over the five-twelvemonth study flow. From 2013 to 2018, infants enrolled at the African sites demonstrated the highest BW ways overall across the entire report period, especially equally compared to Asian sites. The incidence of LBW was highest in the Asian sites (India and Islamic republic of pakistan) compared to the African and Cardinal American sites.
Trial registration The study is registered at clinicaltrials.gov. ClinicalTrial.gov Trial Registration: NCT01073475.
Background
The weight of an infant at birth (BW) is a crucial anthropometric measurement associated with infant mortality [2,3,iv]. Population BW statisticsare important measures of overall population health. However, in low- and depression-middleincome countries (LMICs), BWs are not ever measured, and when measured, they are frequently obtained and recorded inaccurately. Ideally, BW is measured within the first hours after delivery, before pregnant postnatal weight loss has occurred [1].
A newborn is divers as having normal BW if weight at birth is ≥ 2500 chiliad. Low nascence weight (LBW), as defined by the Globe Health Organization (WHO),isa weight at nativity that is less than 2500 k (upward to and including 2499 one thousand). Infants with BW < 2500 yard are farther categorized into depression birth weight (LBW), 1500–2499 thousand; very depression birth weight (VLBW), 1000–1499 g; and extremely low nativity weight (ELBW) < 1000 g [1]. There is an changed relationship betweenBW and mortality; newborns with LBW take a higher risk of neonatal mortality and are also at hazard for stunting, poor neurodevelopment, and adult-onset diseases [two,three,four]. Worldwide, an estimated 15–20% of all newbornsweigh < 2500 g at birth [5]. This translates to more than 20million births a yr. TheWHO has a goal to reduce the LBW rate by 30% past the year 2025 [six]. In certain regions, there has been an increment in the incidence of LBW deliveries [7]. LMICs comport the highest burden of LBW infants. In 2015, three-quarters of the earth'sLBWnewborns were born in three regions: southern asia (47%), eastern and southern Africa (13%) and west and central Africa (12%) [5].
In the contempo past, information from loftier-income countries such as the United States and the United Kingdom recorded an increasing trend in mean BW, with a concurrent decrease in the prevalence of LBW [viii, 9]. This finding prompts the question as to whether a similar tendency is occurring in LMICs.Exploring temporal trends in BW are important to health care policymakers, peculiarly if there are changes in or regression in medical care or nursing practices, or patterns related to health service access [10]. For case, lack of, or belatedly access to comprehensive antenatal care, which is common in LMICs [11], is correlated with a higher risk of pregnancy and newborn complications, including LBW. Improving rates of prenatal care is associated with decreases in the risk of premature nativity and LBW [12].
A major challenge in monitoring the incidence of LBW is that about 60% of newborn babies in LMICs are not weighed nor have BWre corded [5]. Population-based survey data often rely on retrospective maternal call back and modeled estimates, with statistical methods to adjust for underreporting and misreporting of BW. By contrast, the Global Network prospectively collectsBW data in a population-based maternal and newborn health registry (MNHR) insix sites within five LMIC'south from sub-Saharan Africa (Kenya and Zambia), south Asia (Belgavi and Nagpur India; Pakistan), and Key America (Guatemala) [13]. The purpose of this study was to examine trends and regional variation of documented BW and LBW categories over time and to explore possible factors related to those trends in the Global Network MNHR.
Methods
We performed a longitudinal accomplice analysis of all infants born to mothers enrolled in the MNHR of the Global Network between 2013 and 2018. For the analysis, all deliveries with a measured BW, obtained betwixt day 0 and mean solar day 7 were included. We excluded multiple births, miscarriages, medically terminated pregnancies, and pregnancies of women living outside the predefined study cluster (Fig. i). Nosotros too excluded from our analyses clusters within sites that started later on 2013, or were airtight prior to 2018.
Sample selection
For infants born in a health facility, the weight recorded by facility personnel was bathetic from the medical record. For infants born at domicile, study personnel visited the dwelling house and obtained the weight. These weights were measured by the study personnel, or in the case of Kenya by the hamlet elder trained for the task using standard scales [xiv]. It is however important to note that, in most sites, accurate gestational estimation was non possible, and therefore not included in the analysis.Thus, information technology is not possible to say whether the birthweights were advisable for gestational historic period or not.
Data analysis
Nosotros summarized maternal and neonatal demographic characteristics by yr of enrollment. To examine possible demographic changes over time, nosotros compared the characteristics of neonates born in 2013 to those in 2018, using t tests for continuous variables and chi-square tests for chiselled variables.
Means and standard deviations (SDs) for BW were computed by region and year. In addition, to account for possible demographic differences beyond the regions, nosotros computed adjusted hateful BWs by region and twelvemonth, controlling for the post-obit demographic characteristics: maternal age, education, parity, weight, height, infant sex, and time between birth and weight measurement. To compute the adjusted means, we fit a linear mixed-issue regression model of BWby region, yr, and region by year interaction, controlling for demographic characteristics and including sampling cluster as a random result. In improver, we tested for interactions between year and demographic characteristics to determine if birth weights changed for unlike demographic subgroups over time. In Kenya, maternal peak was not routinely measured between 2013 and 2017, hence for this and other missing values on command variables (i.e., demographic characteristics), multiple imputation techniques was utilized. Assay performed with and without imputations were similar. Given the large sample sizes, we had a high level of statistical ability, and therefore, even very pocket-size effects were found to be statistically significant. To determine whether significant changes in hateful nascence weights from 2013 to 2018 were meaningful, we examined Cohen'south d as a measure of issue size for which values of 0.ii–0.4 are considered small furnishings, 0.five–0.7 are medium furnishings, and 0.8 or higher are large furnishings.Allanalyses were conducted using SAS version ix.four.
Upstanding consideration
This study was reviewed and approved by all participating sites' ethics review committees/boards including review boards at each U.S. partner university and the data analogous center (RTI International). All women provided informed consent for participation in the study, including data collection and the follow-upward visits.
Results
Between 2013 and 2018, nosotros enrolled 355,625 pregnant women in the MNHR. Of these, 1% (N = 3254) were lost to follow up. Of the 291,085 deliveries captured in the MNHR within the study period, 265,130 (91%) met inclusion criteria (Fig. one). Of the singleton deliveries (267,697), only ane% (2567) did not accept a recorded birthweight in the MNHR.
Maternal demographic by region
Equally shown in Tabular array 1, maternal age was generally similar beyond regions, with Central American women in our sample beingslightly older than African or Asian women.African women had slightly higher percentages of women with primary or secondary schooling. African women were heavier, particularly compared to Asian women, and taller, specially as compared to Cardinal American women.
Nativity weight difference past fourth dimension period and region
80 five percentage of infants in the sample were weighed withintwo days afterwards birth. Hateful BW past region and year are shown in Table 2. Hateful changes in BW (grams) from 2013 to 2018 by region were: Africa (36.51, SD = 456.00); Asia (3.86, SD = 451.xxx); and Central America (53.07, SD = 450.20). Change in nascency weight over time was not statistically significant for Asia (p = 0.389). While the changes in hateful BW from 2013 to 2018 were statistically meaning for Africa and Central America (p < 0.001), these changes did not reach the threshold for even a small effect based on Cohen's d, suggesting that BW mostly remained stable over time: Africa (d = 0.08), Asia (d = 0.01), and Cardinal America (d = 0.12).
Birth weights of African newborns were consistently greater than that of Central American infants, which were likewise greater than BWs of Asian neonates. This pattern remained when BW was adjusted for region, yr, and maternal demographics, although the size of the mean differences betwixt regions changed slightly over fourth dimension (Fig. 2).
Regional differences in birth weight (g) in 2013 and 2018. Adjusted ways obtained from models with the following variables: yr, region, yr × region interaction, maternal age, parity, year × parity interaction, education, maternal weight, maternal height, baby sex, and fourth dimension between birth and weight measurement
Birth weight categories past region
Consistent with the pattern seen for mean BW,the African sites had the highest percentage of normal BW (95.8%), hence the everyman percentage of all low BW categories (3.9% LBW, 0.3% VLBW, and 0.1% ELBW; Fig. 3). The Central American site was intermediate, with 84.4% normal BW and 15.6% across all LBW categories, and the Asian regional site had the lowest percentage of normal BW (79.8%) and highest percentages of births in all LBW categories (xx.2%; Fig. 3).
Distribution of nascence weight categories by region
Discussion
We examined trends, and regional differences in hateful BW, between 2013 and 2018, of all newborns from six sites in five LMICs enrolled inthe Global Network MNHR. Overall, after controlling for maternal demographic characteristics, there appeared to be a consistent blueprint of regional differences across the fourth dimension period. The mean BW was generally found to exist highest in the African regional site (Zambia and Republic of kenya) as compared to the other regional sites, of South asia (India and Pakistan) and Primal America (Guatemala). Across the study menstruation, in that location were slight changes observed in the size of these disparities over time, with the gap between the African and Asian sites decreasing, and the gap between the African and Central American sites increasing. These observations, notwithstanding, may not be generalizable to the regions on whole, since the presence of the registry in these clusters may accept exerted an influence (Hawthorne effect) on pregnancy outcomes over time.
The highest almanac LBW rates were recorded in the Asian sites at xx.2% (18.6%, 1.1%, and 0.5% for LBW, VLBW and ELBW respectively) and the Fundamental American site at 15.6% (14.7%, 0.5%, 0.4% for LBW, VLBW and ELBW respectively). This is consistent with a 2019 UNICEF report, in which the LBW rate in southern asia was 28%. All the same, the prevalence of LBW in Latin American was report to be 8.7%, which was almost half of what our study reports [5]. Like findings have besides been reported in the WHO multicenter Growth Reference Study [fifteen]. The LBW rate in the African sites in our study was four%. This event is like to the proportion (3.5%) reported in the Intergrowth21st study [16], but differs from thirteen% reported in the 2019 UNICEF written report [5]. A possible caption for this departure is that the data used for the UNICEF report were obtained from multiple sources and subjected to modeling. Up to 28% of the births in the UNICEF study hadno weight recorded, with the highest rates of missing BW data werereported to take occurred in Africa, where the rate ofmissing birthweight data was estimatedto be over 50% [5]. By contrast, in the Global Network's prospective, population-based MNHR from 2013 to 2018, 85% of the newborns were weighed at or within 2 days of birth.
Usually,the causes of LBW deliveries are multifactorial. Genetic and environmental factors play a significant role. Parity, low socioeconomic status, marital status, maternal age, nutritional status, maternal torso mass alphabetize (BMI), maternal health status, smoking, booze intake, and prevailing infections such equally from malariahave all been associated with BW outcomes [16,17,eighteen,19]. There exist regional differences in the prevalence of certain diseases, such asmalaria, which has been reported to increment the odds of LBW deliveries [xx,21,22]. Maternal genes in addition to other factors determine the intrauterine environment andmay vary with region and race [16]. In a study examining nativity outcomes ofFilipina mothers living in Canada, BW among their babies was lower compared to infants of native Canadian mothers in the same environment [23]. Maternal diseases (eastward.1000., diabetes and hypertensive illness) can besides affect weight of a newborn. Socio-economic status and other associated factors have been reported to influence BW.These determinants of BW vary across ethnic populations. Information technology is yet unclear to what extent the lower BW of some indigenous minority populations can exist explained by these determinants [24, 25].
Some studies report a direct relationship between maternal age and BW. This human relationship was demonstrated in a large cohort study in the United Statesbetween 2005 and 2014 [17]. The majority of mothers in our accomplice were aged 20–35 years, with African sites and Asia sites having a lower maternal age compared to the Central American site. However, our Asian sites had the everyman rate of teenage pregnancies compared to the other 2 regions.
Ane limitation of our study is that not all BWs were measured on the same day, immediately after nascence. The time a newborn weight is obtained may touch the recorded BW. However, in our study, this limitation is attenuated.The vast majority of all babies included in the analysis were weighed within 48 h of nascency, and, for the entire sample, birthweights were caused within one week of delivery. Notwithstanding, regional differences in time of weighing were also observed; African sites weighed the newborns closer to time of birth as compared to the Asian and Primal American regional sites.
An additional potential source of bias in the results is the population of women who were entered into the study, only were lost to follow-upwards before the birth of the infant and measurement of BW. Our rates for loss-to-follow-upwardly were quite low (one%); withal, information technology is possible that preterm and LBW infants are over-represented amid infants lost to follow-up, resulting in bias towards larger infants in the measured and reported population. As well, stillbirth and early neonatal deaths were likely to have their birthweights estimated instead of measured.
Observer errors have been reported in some studies of BW, every bit a issue of digit preference. Every bit an example, weights ending in 5 (v) or 0 (zero) tend to be preferred, besides equally weights of multiples of 100. This is peculiarly problematic when a continuous BW variable is categorized. For instance, an baby with a measured BW of 2492 k may be recorded every bit 2500, and hence categorized as a normal BW rather than LBW. Digit preference and rounding errors may outcome in over or underestimation, and therefore may affect observed BW trends [26]. Some baby weighing scales also tend to accept readings to the nearest fifty m or nearest 100 g, and this may underestimate the LBW rates. In our cohort, the process of obtaining and documenting nascency weight is discipline to this potential error.
A last limitation of our study is that the data were prospectively obtained from relatively minor, detached geographical areas (clusters) within each state. Hence, the information may not be representative of the state or region as a whole. Nonetheless, every bit compared to other methods and information sources (eastward.chiliad., Demographic Health Surveys) we enrolled an extremely large number of participants, prospectively, and followed standard procedures in obtaining and documenting weight, across sites, throughout the written report period.
Conclusions
In a prospective, population-based, longitudinal cohort report of birthweight among three global regions, the observed BW meanshad no meaning changeover time in aggregate or past region. In add-on, theBWmeans recorded for African sites, every bit compared to the Asian sites, remained consistently higher.
The LBWrate was consistently higher in the Asian sites equally compared to the African sites. The incidence of LBW observed for the two African sites in the MNHR was lower than that reported for other global estimates.
As compared to past regional estimates of BW, those obtained in the current study were adamant from a very large sample of actual birthweights measured within sevendays of delivery. BW is impacted by a variety of complex maternal and environmental characteristics; future investigations should focus on determining the mechanistic underpinnings of regional and site differences in BW observed in this study.
Availability of information and materials
The dataset generated and analyzed during this study is not yet publicly available due to ongoing information analysis merely it will be bachelor in the NHCHDdata and specimen Hub. Request for data prior to public release will exist handled by the author.
Abbreviations
- BW:
-
Birth weight
- ELBW:
-
Extremely low birth weight
- GN:
-
Global Network for Women'due south and Children's Health Research
- LBW:
-
Low birth weight
- LMIC:
-
Low and middle-income land
- MNHR:
-
Maternal and newborn health registry
- SD:
-
Standard divergence
- VLBW:
-
Very low birth weight
- WHO:
-
Globe Health Organization
References
-
International statistical classification of diseases and related health problems. 10th revision ed. , Geneva: Globe Wellness Organization; 2010 (ISBN 978 92 4 154834 2).
-
Jornayvaz FR, Vollenweider P, Bochud M, Mooser V, Waeber One thousand, Marques-Vidal P. Low birth weight leads to obesity, diabetes and increased leptin levels in adults: the CoLaus study. Cardiovasc Diabetol. 2016;15:73.
-
Gu H, Wang 50, Liu L, Luo X, Wang J, Hou F, Nkomola PD, Li J, Liu Thou, Meng H, et al. A gradient human relationship between low birth weight and IQ: a meta-analysis. Sci Rep. 2017;seven(one):18035.
-
Christian P, Lee SE, Donahue Angel M, Adair LS, Arifeen SE, Ashorn P, Barros FC, Autumn CH, Fawzi WW, Hao W, et al. Risk of childhood undernutrition related to minor-for-gestational age and preterm birth in low- and middle-income countries. Int J Epidemiol. 2013;42(5):1340–55.
-
United Nations Children'south Fund (UNICEF), World Wellness Organization(WHO). UNICEF-WHO Low birthweight estimates: Levels and trends 2000–2015. Geneva: WorldHealth Organization; 2019 (Licence: CC By-NC-SA iii.0 IGO).
-
WHO. Global nutrition targets 2025: low birth weight policy brief (WHO/NMH/NHD/14.v). Geneva: Globe HealthOrganization; 2014.
-
Islam MM. Increasing incidence of infants with low birth weight in Oman. Sultan Qaboos Univ Med J. 2015;15(ii):e177-183.
-
Johnson CD, Jones S, Paranjothy South. Reducing low birth weight: prioritizing action to address modifiable take a chance factors. J Public Health (Oxf). 2017;39(1):122–31.
-
Ghosh RE, Berild JD, Sterrantino AF, Toledano MB, Hansell AL. Birth weight trends in England and Wales (1986–2012): babies are getting heavier. Curvation Dis Kid Fetal Neonatal Ed. 2018;103(three):F264–70.
-
Weinberg CR. Invited commentary: troubling trends in birth weight. Am J Epidemiol. 2016;183(i):24–5.
-
Bucher S, Marete I, Tenge C, Liechty E, Esamai F, Patel A, et al. A prospective observational description of frequency and timing of antenatal intendance attendance and coverage of selected interventions from sites in Argentine republic, Guatemala, India, Kenya, Pakistan and Republic of zambia. Reproductive Wellness. 2015;12(Suppl 2):S12.
-
Crockett AH, Heberlein EC, Smith JC, Ozluk P, Covington-Kolb South, Willis C. Furnishings of a multi-site expansion of grouping prenatal care on birth outcomes. Matern Child Health J. 2019;23(10):1424–33.
-
Bose C, Bauserman M, Goldenberg R, Goudar Southward, McClure E, Pasha O, et al. The Global Network Maternal Newborn Health Registry: a multi-national, community-based registry of pregnancy outcomes. Reprod Wellness. 2015;12(Suppl ii):S1.
-
Gisore P, Shipala E, Otieno K, Rono B, Marete I, Tenge C, et al. Customs based weighing of newborns and use of mobile phones by village elders in rural settings in Kenya: a decentralised approach to health care provision. BMC Pregnancy Childbirth. 2012;12(i):15.
-
Kiserud T, Piaggio G, Carroli Thousand, Widmer M, Carvalho J, Neerup Jensen Fifty, et al. The World Health Organization fetal growth charts: a multinational longitudinal study of ultrasound biometric measurements and estimated fetal weight. PLoS Med. 2017;14(1):e1002220.
-
Goldstein RF, Abell SK, Ranasinha S, Misso ML, Boyle JA, Harrison CL, et al. Gestational weight gain across continents and ethnicity: systematic review and meta-analysis of maternal and infant outcomes in more than ane million women. BMC Med. 2018;16(1):153.
-
Ratnasiri AWG, Parry SS, Arief VN, DeLacy IH, Halliday LA, DiLibero RJ, Basford KE. Recent trends, gamble factors, and disparities in low birth weight in California, 2005–2014: a retrospective study. Matern Wellness Neonatol Perinatol. 2018;4:15.
-
Lunde A, Melve KK, Gjessing HK, Skjaerven R, Irgens LM. Genetic and environmental influences on birth weight, birth length, caput circumference, and gestational age by utilize of population-based parent-offspring information. Am J Epidemiol. 2007;165(7):734–41.
-
Catov JM, Lee K, Roberts JM, Xu J, Simhan HN. Race disparities and decreasing birth weight: are all babies getting smaller? Am J Epidemiol. 2016;183(1):15–23.
-
Steketee RW, Nahlen BL, Parise ME, Menendez C. The burden of malaria in pregnancy in malaria-endemic areas. Am J Trop Med Hyg. 2001;64(1–two Suppl):28–35.
-
McGregor IA, Wilson ME, Billewicz WZ. Malaria infection of the placenta in The gambia, West Africa; its incidence and human relationship to stillbirth, birthweight and placental weight. Trans R Soc Trop Med Hyg. 1983;77(2):232–44.
-
Brabin BJ. An analysis of malaria in pregnancy in Africa. Bull Earth Health Organ. 1983;61(half-dozen):1005–xvi.
-
De Souza LR, Urquia ML, Sgro M, Ray JG. 1 size does not fit all: differences in newborn weight among mothers of Philippine and other Due east Asian origin. J Obstetr Gynaecol Canada. 2012;34(11):1026–37.
-
Martinson ML, Reichman NE. Socioeconomic inequalities in low birth weight in the United states of america, the United Kingdom, Canada, and Australia. Am J Public Health. 2016;106(iv):748–54.
-
Mahumud RA, Sultana Grand, Sarker AR. Distribution and determinants of depression birth weight in developing countries. J Prev Med Public Health. 2017;50(1):18–28.
-
Emmerson AJ, Roberts SA. Rounding of birth weights in a neonatal intensive intendance unit over 20 years: an analysis of a large cohort study. BMJ Open. 2013;three(12):e003650.
Acknowledgements
The Authors gratefully acknowledge the contributions of the communities, women, and children who agreed to participate in this study, as well as the difficult-working efforts of the field staff at each Global Network site.
About this supplement
This commodity has been published every bit role of Reproductive Health, Volume 17 Supplement iii, 2020: Global Network MNH. The total contents of the supplement are bachelor at https://reproductive-health-journal.biomedcentral.com/articles/supplements/book-17-supplement-3.
Funding
Publication of this supplement is funded by grants from Eunice Kennedy Shriver National Institute of Child Wellness and Human Development NICHD to the participating sites and to RTI International.
Author information
Affiliations
Contributions
IK participated in the data collection, drafted the manuscript and finalized the manuscript, OE revised, reviewed and and approved the manuscript, CM performed statistical analysis reviewed and approved the manuscript, SB written report coordination, reviewed and approved the manuscript, PN participated in data drove report coordination,reviewed and approved the manuscript, AP participated in study design and coordination, reviewd and approved the manuscript, PH study dsign and coordination,reviewed and approved the manuscript, SS study design,coordination, reviewed and approved the manuscript, RG participated in written report design,coordination,review and approval of the manuscript, SS participated in study design,coordination, review and approval of manuscript, RJ participated in written report pattern, coordination, review and approval of manuscript, AL participated in written report blueprint, coordination, review and approval of the manuscript, NF participated in study blueprint, coordination, review and approval of manuscript, EC coordination of the written report, review of manuscript and approval, WA participated in report design, coordination, review and approval of manuscript, AL participated in written report coordination review and blessing of manuscript, MB participated in study pattern, coordination review and approval of manuscript, MK participated in study design coordination, review and approval of the manuscript, JL participated in information management, statistical assay, review and approving of manuscript, EM participated in data management, review and approving of the manuscript, Fe participated in study design, coordination review and approval of the manuscript. All authors read and approved the final manuscript.
Respective author
Ideals declarations
Ethics approval and consent to participate
At each site, institutional review boards or ethics committess approved the study. All women provided written informed consent before the start.
Consent for publication
The article was approved for publication by NICHD through its clearance mechanism.
Competing interests
The authors have no competing interest.
Boosted information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits employ, sharing, adaptation, distribution and reproduction in any medium or format, equally long as you requite appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were fabricated. The images or other tertiary party material in this article are included in the commodity's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/iv.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made bachelor in this article, unless otherwise stated in a credit line to the data.
Reprints and Permissions
About this article
Cite this article
Marete, I., Ekhaguere, O., Bann, C.M. et al. Regional trends in birth weight in depression- and heart-income countries 2013–2018. Reprod Health 17, 176 (2020). https://doi.org/ten.1186/s12978-020-01026-2
-
Received:
-
Accepted:
-
Published:
-
DOI : https://doi.org/x.1186/s12978-020-01026-ii
Keywords
- Nascence weight
- Global network
- Low nascence weight
- Neonatal bloodshed
- Newborns
Source: https://reproductive-health-journal.biomedcentral.com/articles/10.1186/s12978-020-01026-2
0 Response to "The Nations of Sub-saharan Africa Have Low Rates of Low-birthweight Babies."
Post a Comment