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    Christian cor eworkshop_apr2013_to share Christian cor eworkshop_apr2013_to share Presentation Transcript

    • Impact of maternal nutritionalinterventions on short and longterm health, survival, and functionParul Christian, DrPH, MScJohns Hopkins Bloomberg School ofPublic Health, Baltimore, USACOREWorkshop Baltimore, Apr 24, 2013
    • Short-term Outcomes Birth outcomes◦ Birth weight/size; fetal growth◦ Gestational age◦ Stillbirth and perinatal mortality Neonatal and infant morbidity and mortality
    • Birth weight, FGR and preterm birth Birth weight is a cumulative measure ofintrauterine growth and gestational age◦ Low birth weight defined as <2500 g◦ Birth weight is one of the leading factorsinfluencing subsequent health and survival in lowincome countries where 90% of the 250 millionlow birth weight babies are born each year Underlying causes of LBW are◦ FGR - Fetal growth restriction (small-for-gestationalage, SGA defined as weight < 10th percentile ofstandard for a given GA)◦ Preterm birth (GA< 37 wk)
    • 4Systematic literature review &Meta-analysis- Included 5 LMIC studies- 126,176 pregnant womenApparent dose responseLIMITATIONS-No indication of etiology of anemia(iron deficiency, malaria, HIV, etc)-Timing of anemia in pregnancyModerate-Severe AnemiaRR of SGA 1.53 (1.24-1.87)
    • LBW and preterm among adolescentsGibbs et al, Pediatr Perinatal Epi 2012
    • PregNon-pregBaseline1y follow-up(∆)Baseline1y follow-up(∆)Between groupdifference in ∆, p-valueHeight (cm) MUAC (cm)Mean ± SD149.2 ± 5.4149.2 ± 5.3-0.05 ± 0.72149.4 ± 5.1149.7 ± 5.00.29 ± 0.82a<0.001a. Baseline and follow-up measurements being significantly different with p<0.001using a paired t-test<0.00123.4 ± 1.822.7 ± 1.8-0.65 ± 1.11a23.2 ± 2.023.5 ± 2.00.28 ± 0.90a<0.001BMI (kg/m2)19.3 ± 1.719.0 ± 1.7-0.35 ± 1.17a19.0 ± 2.019.3 ± 2.00.29 ± 0.98aRah et al; J Nutr 2008Influence of early pregnancy on growth and adolescentnutritional status in rural Bangladesh
    • Subramanian et al; PlosOne 2011Height of Nations: Patterns among women in 54 LMIC
    • Maternal supplementation inpregnancy to reduce SGA and LBW Balanced energy and protein (food) (Imdad &Bhutta, Pediatr Peri Epi 2012)◦ 74 g overall increase in birth weight; 100 g inmalnourished women◦ 44% reduction in SGA Iron w/wo folic acid (Imdad & Bhutta, Pediatr Peri Epi2012)◦ 20% reduction in LBW
    • Prevalence of micronutrients deficiencies inearly pregnancy in rural Nepal61.139.80.711.128.340.331.837.432.813.940.20204060%(Jiang et al; J Nutr 2005)
    • Multiple micronutrientsupplementation and birth weightRamakrishnan et al; Pediatr Peri Epi 2012
    • Multiple micronutrientsupplementation and risk of SGARamakrishnan et al; Pediatr Peri Epi 2012
    • Long-term Outcomes Linear and ponderal growth in childhood Long term survival Cardiometabolic health◦ Metabolic syndrome Cognition and motor function
    • Developmental Origins of Healthand Disease - DOHaD Previously known as the “Barker’s” or“Early/Fetal Origins” Hypothesis Early life nutritional and environmental factorsmay impact later life disease risk Most of the focus has been on the associationbetween size at birth and the risk ofcardiovascular disease and type 2 diabetes inadulthood
    • Risk of CHD by birth weightGluckman and Hanson; 2005
    • Odds ratios for impaired glucosetolerance or Type II diabetes among64 yr old men in Hertfordshire(adjusted for adult BMI)Odds ratios for metabolic syndromeamong men in Hertfordshire(adjusted for adult BMI)Hales & Barker, 2001
    • DOHaD Concepts Thrifty Genotype (Neel, 1962) Thrifty Phenotype (Hales & Barker, 1992) Developmental plasticity Programming or Developmental Induction (Nathanielsz1999) Predictive adaptive response (Gluckman & Hanson, 2005) Not just “fetal” but postnatal environment isimportant Birth weight is an inadequate marker of prenataletiologic pathways
    • Hales & Barker, 2001“The Thrifty Phenotype”
    • Match-Mismatch theory of metabolic diseaseGluckman et al, Am J Hum Biol, 2007
    • Long term Consequences- Growth and body composition- Child survival- Child cardiometabolic risk
    • Maternal food supplementation and CVDrisk in 11-17 y old Gambian offspringHawkesworth et al; AJCN 2011
    • Maternal calcium supplementation and CVDrisk in11-17 y old Gambian offspringHawkesworth et al; AJCN 2011
    • Antenatal MMN supplementationeffects on children’s weight and sizeat 2 years of age in NepalIFA (n=453)Mean (SD)MMN (n=462)Mean (SD)Difference (95% CI) p-valueWAZ -1.76 (0.98) -1.63 (1.08) 0.14 (0.001, 0.27) 0.048HAZ -2.28 (1.06) -2.20 (1.12) 0.08 (-0.06, 0.22) 0.048WHZ -0.40 (1.05) -0.28 (1.12) 0.12 (-0.02, 0.26) 0.097HC (cm) 46.40 (1.43) 46.64 (1.49) 0.24 (0.06, 0.43) <0.05BP (mmHg) 101.9 (17.4) 99.4 (13.7) -2.5 (-0.5, -4.6) <0.05Vaidya et al; Lancet 2008
    • Nepal Study and Interventions(1999-2001) A double-masked, controlled, cluster randomizedtrial of antenatal and postnatal micronutrientsupplementation to examine impact on birthoutcomes and infant survival 5 supplement groups:◦ C Vitamin A (Control)◦ FA VA + Folic acid◦ FAFe Folic Acid and Iron◦ FAFeZn Folic acid, Iron and Zinc◦ MM Multiple micronutrient A cross-sectional follow-up was conducted in2006-2008 to examine growth, survival, andbiomarkers of cardiometabolic risk in theoffspring at 6-8 y of age
    • Christian et al;AJE 2009Impact of antenatal micronutrient supplementationon child survival through 7 y of age: Nepal
    • Anthropometry of children atbirth and at follow-upMeasure Birth 6-8 y oldMean (SD)Weight (kg) 2.64 (0.42) 18.05 (2.33)Length / height (cm) 47.37 (2.26) 113.49 (5.50)Weight for age z-score -1.52 (1.04) -2.09 (0.89)Length for age z-score -1.19 (1.11) -1.90 (0.88)Weight for length z-score -1.01 (1.11) --BMI for age z-score -1.49 (1.11) -1.22 (0.86)*Z-scores calculated using WHO growth standard for children <5 y (WHO 2006) and school-agedchildren (de Onis 2007)
    • Effect of maternal supplementation on childanthropometry at 6-8 y of ageControl FA FAFe FAFeZn MMn=701 n=630 n=641 n=663 n=721Mean (SD) Difference (95%CI)2Height (cm) 113.3 (5.4) 0.3 (-0.3,0.9) -0.0 (-0.6,0.6) 0.6 (0.0, 1.3)* -0.1 (-0.7,0.5)Weight (kg) 18.0 (2.2) 0.0 (-0.3, 0.3) -0.0 (-0.3, 0.3) 0.1 (-0.2, 0.4) -0.1 (-0.4, 0.2)BMI (kg/m2) 14.0 (1.1) -0.0 (-0.2, 0.1) -0.0 (-0.2, 0.1) -0.1 (-0.2, 0.0) -0.1 (-0.2, 0.1)Waist circ. (cm) 51.2 (3.0) -0.0 (-0.4, 0.4) 0.0 (-0.4, 0.4) -0.1 (-0.5, 0.3) -0.1 (-0.5, 0.3)MUAC (cm) 15.4 (1.1) 0.0 (-0.1, 0.2) -0.0 (-0.2, 0.1) -0.0 (-0.2, 0.1) 0.0 (-0.1, 0.2)Difference from control, adjusted for the age of the child at follow-up and the design effect using a GEE linear regression model. Heightand weight models additionally adjusted for birth length and birth weight, respectively.* p<0.05, difference relative to the control.Stewart et al; AJCN 2009
    • Differences in triceps and subscapular skinfolds andarm fat area among children 6-8 y by treatment-.4-.20.2Armfatareadifference(cm2)-.4-.20.2Skinfoldthicknessdifference(mm)TSF SSF AFA.Folic acidFolic acid-ironFolic acid-iron-zincMultiple micronutrientMaternal supplement group-0.25 mm (-0.44, -0.06) -0.20 mm (-0.33, -0.06) -0.18 cm2 (-0.34, -0.01)Stewart et al; AJCN 2009
    • 020406080100Meanbloodpressure(mmHg)Control FA FAFe FAFeZn MM44.555.5MeanHbA1c(%)Control FA FAFe FAFeZn MM0.1.2.3.4.5MedianHOMA-IRControl FA FAFe FAFeZn MMHbA1cBlood PressureInsulin resistance (HOMA)▬▬ Systolic▬ Diastolic
    • The risk of metabolic syndrome bymaternal supplement groupControl FA FAFe FAFeZn MMn (%) 75 (11.7) 47 (8.1) 74 (12.2) 70 (11.4) 80 (11.9)OR(95% CI)1 1.000.63*(0.41,0.97)1.02(0.70,1.49)0.95(0.65,1.40)1.00(0.69,1.45)1 Adjusted for child age at follow-up, and the design effect and for fasting statusStewart et al; J Nutr 2009
    • 1.20.40.60.81.0OddsratioFA FAFe FAFeZn MMThe risk of microalbuminuria (MA/CR≥30mg/g) by maternal supplement groupThe risk of microalbuminuria (microalbumin/creatinine ratio ≥30 mg/g. Odds ratios and 95% CI calculated adjustingfor the design effect and child age at follow-up using a GEE logistic model.0.56 (0.33, 0.93)0.77 (0.49, 1.22)0.53 (0.32, 0.89)0.70 (0.44, 1.11)Stewart et al; J Nutr 2009
    • Long term Consequences- Child cognition and motorfunction
    • 1Using multivariate regression with boot strapping to estimate 95% confidence interval adjusted for design effect;2Bonferroni adjusted p-values to adjust for multiple comparisons;3Using multivariate regression with boot strapping to estimate 95% confidence interval adjusted for design effectand adjusted for child age, sex, ever sent to school, asset score, milk and dairy intake, meat, chicken and fish intake,lower respiratory infection, diarrhea/dysentery in the past week4 P-value for the overall treatment effect usingWilks’ lamda and Lawley-Hotelling trace test derived from theMANOVA with Bonferroni correction applied to the p-valuesDifferences in test scores in the maternal iron-folic acid group relative to controlIron-folic acidAdj diff (95% CI)3p-value3UNIT 2.38 (0.06, 4.70) 0.04Failure Stroop test -0.14 (-0.23, -0.04) 0.005Backward digit test 0.36 (0.01, 0.71) 0.02% correct no_go -0.54 (-7.44, 6.35) 0.88MABC -1.47 (-3.06, 0.12) 0.07Finger tapping test 2.05 (0.87, 3.24) 0.001P-value4 0.002Christian et al; JAMA 2010
    • Discussion Nutritional interventions during pregnancy such asfood and micronutrient supplementation have beenshown to impact fetal growth although evidence for aneffect on gestational duration is limited Evidence of benefit of preconceptional and earlypregnancy interventions is limited – future research isurgently needed The need for a life-course approach for intervening isreflected in the emphasis on the first 1000 days, butshould be expanded perhaps to -365 days
    • Discussion In LMICs increasing rates of overweight andobesity among pregnant women and associatedrisks of pregnancy complications and adversebirth outcomes are of concern In countries undergoing rapid nutrition transition,the impact of nutritional advice and counselingfor appropriate weight gain, activity levels andother life style factors, and adequate nutrientintakes during pregnancy need further evaluation Long term cohort follow-ups are needed toevaluate the impact of early life interventions onlong term cognitive function and cardiometabolichealth