1
|
Putra M, Hamidi OP, Driver C, Peek EE, Bolt MA, Gumina D, Reeves SA, Hobbins JC. Corpus Callosum Length and Cerebellar Vermian Height in Fetal Growth Restriction. Fetal Diagn Ther 2024; 51:255-266. [PMID: 38461813 DOI: 10.1159/000538123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 01/14/2024] [Indexed: 03/12/2024]
Abstract
INTRODUCTION Growth-restricted fetuses may have changes in their neuroanatomical structures that can be detected in prenatal imaging. We aim to compare corpus callosal length (CCL) and cerebellar vermian height (CVH) measurements between fetal growth restriction (FGR) and control fetuses and to correlate them with cerebral Doppler velocimetry in growth-restricted fetuses. METHODS This was a prospective cohort of FGR after 20 weeks of gestation with ultrasound measurements of CCL and CVH. Control cohort was assembled from fetuses without FGR who had growth ultrasound after 20 weeks of gestation. We compared differences of CCL or CVH between FGR and controls. We also tested for the correlations of CCL and CVH with middle cerebral artery (MCA) pulsatility index (PI) and vertebral artery (VA) PI in the FGR group. CCL and CVH measurements were adjusted by head circumference (HC). RESULTS CCL and CVH were obtained in 68 and 55 fetuses, respectively. CCL/HC was smaller in FGR fetuses when compared to control fetuses (difference = 0.03, 95% CI: [0.02, 0.04], p < 0.001). CVH/HC was larger in FGR fetuses compared to NG fetuses (difference = 0.1, 95% CI: [-0.01, 0.02], p = < 0.001). VA PI multiples of the median were inversely correlated with CVH/HC (rho = -0.53, p = 0.007), while CCL/HC was not correlated with VA PI. Neither CCL/HC nor CVH/HC was correlated with MCA PI. CONCLUSIONS CCL/HC and CVH/HC measurements show differences in growth-restricted fetuses compared to a control cohort. We also found an inverse relationship between VA PI and CVH/HC. The potential use of neurosonography assessment in FGR assessment requires continued explorations.
Collapse
Affiliation(s)
- Manesha Putra
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Odessa P Hamidi
- St. Luke's University Health Network, Bethlehem, Pennsylvania, USA
| | - Camille Driver
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Emma E Peek
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Matthew A Bolt
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado-Denver Anschutz Medical Campus, Aurora, Colorado, USA
| | - Diane Gumina
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Shane A Reeves
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - John C Hobbins
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| |
Collapse
|
2
|
Eggleston AJ, Farrington E, McDonald S, Aziz S. Portable ultrasound technologies for estimating gestational age in pregnant women: a scoping review and analysis of commercially available models. BMJ Open 2022; 12:e065181. [PMID: 36450429 PMCID: PMC9717352 DOI: 10.1136/bmjopen-2022-065181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 10/03/2022] [Indexed: 12/05/2022] Open
Abstract
OBJECTIVES To identify all available studies assessing the use of portable ultrasound devices for pregnant women, with the specific aim of finding evidence for devices used to determine gestational age and their validity when compared with conventional ultrasound machines. We also wanted to determine what portable ultrasound models are commercially available for obstetric use. DESIGN Systematic scoping review. PRIMARY AND SECONDARY OUTCOME MEASURES Extracted variables included study design, population, method of ultrasound measurement, devices used and whether studies formally validated accuracy against conventional ultrasound. RESULTS We searched four databases-Medline, Embase, CINAHL and Maternal and Infant Care. In total 56 studies from 34 countries were identified; most were observational studies. Across all studies, 27 different portable ultrasound models (from 17 manufacturers) were evaluated. Twenty-one studies assessed use of portable ultrasound for evaluating fetal characteristics or estimating gestational age, and 10 of these were formal validation studies. In total, six portable devices have been validated for gestational age estimation against a conventional ultrasound comparator. The web searches identified 102 portable devices (21 manufacturers). These were a mix of handheld devices that connected to a phone or computer, or laptop-style portable ultrasound devices. Prices ranged from US$1190 to US$30 000 and weight ranged from 0.9 kg to 13.0 kg. CONCLUSION While the number of commercially available portable ultrasound devices continues to grow, there remains a lack of peer-reviewed, quality evidence demonstrating their accuracy and validity when compared with conventional ultrasound machines. This review identified some models that may be useful in gestational age estimation in low-resource settings, but more research is required to help implement the technology at scale. TRIAL REGISTRATION NUMBER Registered via Open Science Framework (DOI: 10.17605/OSF.IO/U8KXP).
Collapse
Affiliation(s)
| | - Elise Farrington
- Medical Department, Western Health, Footscray, Victoria, Australia
| | - Steve McDonald
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Samia Aziz
- Department of Public Health, Independent University, Bangladesh, Dhaka, Dhaka District, Bangladesh
| |
Collapse
|
3
|
Qin R, Ding Y, Lu Q, Jiang Y, Du J, Song C, Lv H, Lv S, Tao S, Huang L, Xu X, Liu C, Jiang T, Wang Z, Ma H, Jin G, Xia Y, Hu Z, Zhang F, Lin Y. Associations of maternal dietary patterns during pregnancy and fetal intrauterine development. Front Nutr 2022; 9:985665. [PMID: 36185689 PMCID: PMC9520705 DOI: 10.3389/fnut.2022.985665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 08/22/2022] [Indexed: 11/13/2022] Open
Abstract
Dietary pattern is excellent in reflecting an individual's eating conditions. Longitudinal data on fetal growth can reflect the process of intrauterine growth. We aimed to evaluate the associations between maternal dietary patterns and intrauterine parameters in middle and late pregnancy. The present study was conducted within Jiangsu Birth Cohort (JBC) study. Dietary information was assessed with a food frequency questionnaire (FFQ) in the second and third trimester of gestation. B-ultrasound scans were performed to obtain fetal intrauterine parameters, including head circumference (HC), femur length (FL), abdominal circumference (AC), and estimated fetal weight (EFW). Exploratory factor analysis was used to extract dietary patterns. Multiple linear regression and linear mixed-effects model (LMM) were used to investigate the association between maternal dietary patterns and fetal growth. A total of 1,936 pregnant women were eligible for the study. We observed inverse associations of maternal “Vegetables and fish” and “Snack and less eggs” patterns during mid-pregnancy with fetal HC Z-score, respectively (“Vegetables and fish”: β = −0.09, 95% CI −0.12, −0.06; “Snack and less eggs”: β = −0.05, 95% CI −0.08, −0.02). On the contrary, “Animal internal organs, thallophyte and shellfish” pattern in the second trimester was associated with increased HC Z-scores (β = 0.04, 95% CI 0.02, 0.06). Consistently, score increase in “Vegetables and fish” pattern in the third trimester was inversely associated with the Z-scores of HC (β = −0.05, 95% CI −0.09, −0.02), while “Meat and less nuts” pattern was positively correlated with the Z-scores of HC (β = 0.04, 95% CI 0.02, 0.07). As compared to the fetus whose mothers at the lowest tertile of “Snack and less eggs” pattern in both trimesters, those whose mothers at the highest tertile demonstrated 1.08 fold (RR = 2.10, 95% CI 1.34–3.28) increased risk of small HC for gestational age (GA). No correlation was observed between maternal dietary patterns and other intrauterine parameters. Our results suggested the effects of maternal dietary patterns on fetal growth, particularly HC. These findings highlighted the adverse impact of unhealthy dietary pattern on fetal growth, might provide evidence for strategies to prevent intrauterine dysplasia and dietary guidelines during pregnancy.
Collapse
Affiliation(s)
- Rui Qin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ye Ding
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Maternal, Child and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Qun Lu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yangqian Jiang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jiangbo Du
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Ci Song
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Hong Lv
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Siyuan Lv
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Toxicology and Nutritional Science, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Shiyao Tao
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Lei Huang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xin Xu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Cong Liu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Tao Jiang
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Zhixu Wang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Hongxia Ma
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Guangfu Jin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Yankai Xia
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Feng Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Obstetrics and Gynecology Hospital, National Health Commission (NHC) Key Laboratory of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Fudan University, Shanghai, China
- Feng Zhang
| | - Yuan Lin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
- Department of Maternal, Child and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, China
- State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
- *Correspondence: Yuan Lin
| |
Collapse
|
4
|
Ren JY, Zhu M, Wang G, Gui Y, Jiang F, Dong SZ. Quantification of Intracranial Structures Volume in Fetuses Using 3-D Volumetric MRI: Normal Values at 19 to 37 Weeks' Gestation. Front Neurosci 2022; 16:886083. [PMID: 35645723 PMCID: PMC9133784 DOI: 10.3389/fnins.2022.886083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/11/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveThe purpose of this study is to establish a reference of intracranial structure volumes in normal fetuses ranging from 19 to 37 weeks' gestation (mean 27 weeks).Materials and MethodsA retrospective analysis of 188 MRI examinations (1.5 T) of fetuses with a normal brain appearance (19–37 gestational weeks) from January 2018 to December 2021 was included in this study. Three dimensional (3-D) volumetric parameters from slice-to-volume reconstructed (SVR) images, such as total brain volume (TBV), cortical gray matter volume (GMV), subcortical brain tissue volume (SBV), intracranial cavity volume (ICV), lateral ventricles volume (VV), cerebellum volume (CBV), brainstem volume (BM), and extra-cerebrospinal fluid volume (e-CSFV), were quantified by manual segmentation from two experts. The mean, SD, minimum, maximum, median, and 25th and 75th quartiles for intracranial structures volume were calculated per gestational week. A linear regression analysis was used to determine the gestational weekly age-related change adjusted for sex. A t-test was used to compare the mean TBV and ICV values to previously reported values at each gestational week. The formulas to calculate intracranial structures volume derived from our data were created using a regression model. In addition, we compared the predicted mean TBV values derived by our formula with the expected mean TBV predicted by the previously reported Jarvis' formula at each time point. For intracranial volumes, the intraclass correlation coefficient (ICC) was calculated to convey association within and between observers.ResultsThe intracranial volume data are shown in graphs and tabular summaries. The male fetuses had significantly larger VV compared with female fetuses (p = 0.01). Measured mean ICV values at 19 weeks are significantly different from those published in the literature (p < 0.05). Means were compared with the expected TBV generated by the previously reported formula, showing statistically differences at 22, 26, 29, and 30 weeks' gestational age (GA) (all p < 0.05). A comparison between our data-derived formula and the previously reported formula for TBV showed very similar values at every GA. The predicted TBV means derived from the previously reported formula were all within the 95% confidence interval (CI) of the predicted means of this study. Intra- and inter-observer agreement was high, with an intraclass correlation coefficient larger than 0.98.ConclusionWe have shown that the intracranial structural volume of the fetal brain can be reliably quantified using 3-D volumetric MRI with a high degree of reproducibility and reinforces the existing data with more robust data in the earlier second and third stages of pregnancy.
Collapse
Affiliation(s)
- Jing-Ya Ren
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ming Zhu
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Guanghai Wang
- Pediatric Translational Medicine Institution, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- MOE-Shanghai Key Laboratory of Children's Environmental Health, School of Medicine, Xinhua Hospital, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China
| | - Yiding Gui
- Pediatric Translational Medicine Institution, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- MOE-Shanghai Key Laboratory of Children's Environmental Health, School of Medicine, Xinhua Hospital, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China
| | - Fan Jiang
- Pediatric Translational Medicine Institution, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- MOE-Shanghai Key Laboratory of Children's Environmental Health, School of Medicine, Xinhua Hospital, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China
| | - Su-Zhen Dong
- Department of Radiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- *Correspondence: Su-Zhen Dong
| |
Collapse
|
5
|
Kohl PL, Gyimah EA, Diaz J, Kuhlmann FM, Dulience SJL, Embaye F, Brown DS, Guo S, Luby JL, Nicholas JL, Turner J, Chapnick M, Pierre JM, Boncy J, St Fleur R, Black MM, Iannotti LL. Grandi Byen-supporting child growth and development through integrated, responsive parenting, nutrition and hygiene: study protocol for a randomized controlled trial. BMC Pediatr 2022; 22:54. [PMID: 35062907 PMCID: PMC8780724 DOI: 10.1186/s12887-021-03089-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/22/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Poor child growth and development outcomes stem from complex relationships encompassing biological, behavioral, social, and environmental conditions. However, there is a dearth of research on integrated approaches targeting these interwoven factors. The Grandi Byen study seeks to fill this research gap through a three-arm longitudinal randomized controlled trial which will evaluate the impact of an integrated nutrition, responsive parenting, and WASH (water, sanitation and hygiene) intervention on holistic child growth and development. METHODS We will recruit 600 mother-infant dyads living in Cap-Haitien, Haiti and randomize them equally into one of the following groups: 1) standard well-baby care; 2) nutritional intervention (one egg per day for 6 months); and 3) multicomponent Grandi Byen intervention (responsive parenting, nutrition, WASH + one egg per day for 6 months). Primary outcomes include child growth as well as cognitive, language, motor, and social-emotional development. The study also assesses other indicators of child health (bone maturation, brain growth, diarrheal morbidity and allergies, dietary intake, nutrient biomarkers) along with responsive parenting as mediating factors influencing the primary outcomes. An economic evaluation will assess the feasibility of large-scale implementation of the interventions. DISCUSSION This study builds on research highlighting the importance of responsive parenting interventions on overall child health, as well as evidence demonstrating that providing an egg daily to infants during the complementary feeding period can prevent stunted growth. The multicomponent Grandi Byen intervention may provide evidence of synergistic or mediating effects of an egg intervention with instruction on psychoeducational parenting and WASH on child growth and development. Grandi Byen presents key innovations with implications for the well-being of children living in poverty globally. TRIAL REGISTRATION NCT04785352 . Registered March 5, 2021 at https://clinicaltrials.gov/.
Collapse
Affiliation(s)
- Patricia L Kohl
- Brown School, Washington University in St. Louis, 1 Brookings Dr., Campus Box 1196, St. Louis, MO, 63130, USA
| | - Emmanuel A Gyimah
- Brown School, Washington University in St. Louis, 1 Brookings Dr., Campus Box 1196, St. Louis, MO, 63130, USA.
| | - Jenna Diaz
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Washington University School of Medicine in St. Louis, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
| | - F Matthew Kuhlmann
- Division of Infectious Diseases, Washington University School of Medicine in St. Louis, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
| | - Sherlie Jean-Louis Dulience
- Brown School, Washington University in St. Louis, 1 Brookings Dr., Campus Box 1196, St. Louis, MO, 63130, USA
| | - Fithi Embaye
- Brown School, Washington University in St. Louis, 1 Brookings Dr., Campus Box 1196, St. Louis, MO, 63130, USA
| | - Derek S Brown
- Brown School, Washington University in St. Louis, 1 Brookings Dr., Campus Box 1196, St. Louis, MO, 63130, USA
| | - Shenyang Guo
- Brown School, Washington University in St. Louis, 1 Brookings Dr., Campus Box 1196, St. Louis, MO, 63130, USA
| | - Joan L Luby
- Department of Psychiatry, Washington University School of Medicine in St. Louis, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
| | - Jennifer L Nicholas
- Department of Radiology, School of Medicine, Case Western Reserve University, 10900 Euclid Ave., Cleveland, OH, 44106, USA
| | - Jay Turner
- McKelvey School of Engineering, Washington University in St. Louis, 1 Brookings Dr., St. Louis, MO, 63130, USA
| | - Melissa Chapnick
- Brown School, Washington University in St. Louis, 1 Brookings Dr., Campus Box 1196, St. Louis, MO, 63130, USA
| | - Joseline Marhone Pierre
- Unité de Coordination du Programme National d'Alimentation et de Nutrition, Ministère de la Santé Publique et de la Population, 1, Angle Avenue Maïs Gaté et, Rue Jacques Roumain, Port-au-Prince, Haiti
| | - Jacques Boncy
- Laboratoire National de Santé Publique, Ministère de la Santé Publique et de la Population, 1, Angle Avenue Maïs Gaté et, Rue Jacques Roumain, Port-au-Prince, Haiti
| | | | - Maureen M Black
- Department of Pediatrics, University of Maryland School of Medicine, 655 W. Baltimore Street, Baltimore, MD, 21201, USA
| | - Lora L Iannotti
- Brown School, Washington University in St. Louis, 1 Brookings Dr., Campus Box 1196, St. Louis, MO, 63130, USA
| |
Collapse
|