Maternal Iron Status in Pregnancy and Child Health Outcomes after Birth: A Systematic Review and Meta-Analysis
Abstract
:1. Introduction
2. Methods
2.1. Search Strategy and Study Selection
2.2. Data Extraction and Reporting
2.3. Quality Assessment and Data Analysis
3. Results
3.1. Maternal Iron Status
3.2. Quality Assessment
3.3. Child Outcome
4. Discussion
- (1)
- It is possible that maternal iron status is not associated with these outcomes because the studied outcomes vary in their sensitivity to this exposure. It could be that compensating regulatory mechanisms may in fact protect the child from disturbance of the maternal iron balance. For example, the placenta can actively transport iron from the mother to the fetus, thereby protecting the latter from iron deficiency, even at the expense of maternal iron stores [24].
- (2)
- The resulting effects may be too modest to be detected at a later age, especially in small studies. Indeed, our meta-regression on hemoglobin studies suggests weaker associations when maternal and child hemoglobin measurements are further apart. If effects are modest at a later age, the clinical impact is likely to be considered low.
- (3)
- Existing effects may have been missed due to the high heterogeneity regarding study populations, laboratory methods, and cut-offs applied. Definitions of iron deficiency varied across studies and within countries. This is inevitable as worldwide applicable definitions of iron deficiency or iron overload in pregnancy have yet to be defined.
- (4)
- Timing of measurements during pregnancy is important as iron stores change dramatically during the course of pregnancy. Trimester-specific cut-offs that consider the physiological increases in blood volume, hemodilution, and iron requirements of the placenta and fetus are needed. Results may have differed if measurements were more consistent across studies [76].
- (5)
- During pregnancy, iron supplementation, as well as individual differences in body weight, dietary intake, micronutrient deficiencies, and iron absorption, may mask effects of iron deficiency or otherwise in both mother and child [77]. Additionally, iron intake during earlier infancy including breastfeeding practices and iron enrichment or supplementation might also influence our results and might explain differences between countries [15]. These potential confounders or mediators were generally not analyzed, except for eleven studies that took breastfeeding into account.
- (6)
- Another very likely explanation is that results are biased by inflammation, which is largely not reported [78]. This is of specific relevance in regions with high prevalence of (chronic) infections, like tuberculosis, malaria, and other parasitic infections [6]. During states of inflammation, the acute phase protein ferritin rises markedly, even in the case of iron deficiency. That may explain why no effect was detected on child iron biomarkers except for sTfR, which is controlled by iron availability and not by inflammation [3].
- (7)
- Another possibility is that maternal iron effects are non-linear, as hypothesized earlier based on the U-shaped risk curve of maternal hemoglobin [13]. If iron deficiency and iron overload are both harmful, effects may be missed in linear statistical models or in studies comparing two categories that include both these extremes. We conclude that there is little evidence to support or reject a U-shaped risk curve of maternal iron status on specific outcomes.
Strengths and Limitations
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
Abbreviations
CI | Confidence Interval |
IV | Instrumental Variable |
MD | Mean Differences |
PRISMA | Preferred Reporting Items of Systematic Review and Meta-Analysis Guidelines |
SF | Serum Ferritin |
sTfR | Soluble Transferrin Receptor Concentration |
TIBC | Total Iron Binding Capacity |
TSAT | Transferrin Saturation |
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Scheme | Year | Country | Country Income | Design (S) | Risk of Bias | n | Population | Back-Ground SF, µg/L | Statistics | Mother | Child | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Iron Biomarkers | Categories Based on | Stage | Outcome | Age | ||||||||||
No association | ||||||||||||||
Rios [27] * | 1975 | USA | H | Cohort (S) | M | 26 | General | NR | T-test | SF, Fe, TSAT, TIBC | SF < 9 µg/L | PP | SF, TSAT | 6 d |
Murray [28] * | 1978 | Niger | L | Cohort | M | 49 | Famine conditions | NA | NR | Fe, TSAT | TSAT < 10% vs. TSAT > 60% | PP | SF, TSAT | 6 m |
Kilbride [29] * | 2000 | Jordan | U-M | Case control (S) | H | 195 | Refugees | 15.2 ‡ | T-test | SF, Fe, TSAT, (TIBC) | Anemia, SF < 12 µg/L | PP | SF | 3, 6, 9, 12 m |
Poyrazoğlu [30] * | 2011 | Turkey | U-M | Cohort (S) | M | 92 | General | 33 ‡ | ANOVA | SF, Fe, TSAT, TIBC | Anemia and (S) | II, PP | SF, TSAT | 3, 6, 12 m |
Hanieh [31] * | 2013 | Vietnam | L-M | Clinical trial (S) | L | 1168 | General | 28.4 § | MLR | SF, (sTfR, sTfR/SF) | (S), SF < 15 µg/L | III | SF | 6 m |
Kulik [32] * | 2016 | Poland | H | Cohort (S) | M | 44 | General | 22 ‡ | corr | SF, sTfR | SF < 15 µg/L | PP | SF | 3 d |
Matias [33] * | 2018 | Bangladesh | L-M | Clinical trial (S) | L | 1117 | General | NR | MLR | SF, sTfR | SF < 12 µg/L | III | SF | 6 m |
Positive association | ||||||||||||||
Puolakka [34] * | 1980 | Finland | H | Cohort (S) | H | 47 | General | NR | MWU | SF (Fe, TF, TSAT, TIBC) | SF < 50 µg/L | PP | SF | 6 m |
Milman [35] * | 1987 | Denmark | H | Cohort (S) | M | 56 | General | 21 † | MWU | SF (Fe, TF, TSAT) | SF < 15 µg/L | PP | SF | 5 d |
Morton [36] | 1988 | UK | H | Cohort (S) | M | 51 | General | NR | T-test | SF | SF < 10 µg/L | III | SF | 6 m |
Preziosi [37] * | 1997 | Niger | L | Clinical trial (S) | M | 197 | General | NR | T-test | SF (Fe, TSAT) | SF < 12 µg/L | II, PP | SF (Fe, TSAT) | 3, 6 m |
Liu [38] * | 2015 | China | U-M | Cohort | L | 140 | General | 19.9 ‡ | T-test | SF, sTfR | Anemia | III | sTfR (SF) | 6 m (42 d, 4 m) |
Santos [39] * | 2018 | China | U-M | Clinical trial (S) | L | 1194 | General | NR | MLR | SF, sTfR | II, III | SF, sTfR | 9 m | |
Abioye [40] * | 2019 | Philippines | L-M | Nested-cohort (S) | L | 359 | Women with schistosomiasis and anemia | 13.4 ‡ | MLR | SF, (sTfR) | SF < 12 µg/L | III | SF, (sTfR) | 6 m (12 m) |
Shukla [41] * | 2019 | India | L-M | Cohort | L | 163 | General | 62.6 ‡ | T-test, corr | SF | Anemia | PP | SF | 14 wk |
Study | Year | Country | Country Income | Design (S) | Risk of Bias | n | Population | Back-ground SF, µg/L | Statistics | Mother | Child | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Iron Biomarkers | Categories Based on | Stage | Outcome | Age | ||||||||||
No association | ||||||||||||||
Rios [27] * | 1975 | USA | H | Cohort (S) | M | 26 | General | NR | T-test | SF, Fe, TSAT, TIBC | SF < 9 µg/L | PP | Hemoglobin | 6 d |
Murray [28] * | 1978 | Niger | L | Cohort | M | 49 | Famine conditions | NA | NR | Fe, TSAT | TSAT < 10% vs. TSAT > 60% | PP | Hemoglobin | 6 m |
Puolakka [34] * | 1980 | Finland | H | Cohort (S) | H | 47 | General | NR | MWU | SF (Fe, TF, TSAT, TIBC) | SF < 50 µg/L | PP | Hemoglobin | 6 m |
Milman [35] * | 1987 | Denmark | H | Cohort (S) | M | 56 | General | 21 † | MWU | SF (Fe, TF, TSAT) | SF < 15 µg/L | PP | Hemoglobin | 5 d |
Turkay [42] | 1995 | Turkey | U-M | Cohort | M | 27 | General | 13.5 ‡ | T-test, corr | SF, Fe, TSAT | SF < 12 µg/L | II, III | Hemoglobin | 3 m |
Preziosi [37] * | 1997 | Niger | L | Clinical trial (S) | M | 197 | General | NR | T-test | SF (Fe, TSAT) | SF < 12 µg/L | II, PP | Hemoglobin | 3, 6 m |
Poyrazoğlu [30] * | 2011 | Turkey | U-M | Cohort (S) | M | 92 | General | 33 ‡ | ANOVA | SF, Fe, TSAT, TIBC | Anemia and (S) | II, PP | Hemoglobin | 3, 6, 12 m |
Hanieh [31] * | 2013 | Vietnam | L-M | Clinical trial (S) | L | 1168 | General | 28.4 § | MLR | SF (sTfR sTfR/SF) | (S), SF < 15 µg/L | III | Hemoglobin | 6 m |
Liu [38] * | 2015 | China | U-M | Cohort | L | 140 | General | 19.9 ‡ | T-test | SF, sTfR | Anemia | III | Hemoglobin | 42 d, 4 m, 6 m |
Kulik [32] * | 2016 | Poland | H | Cohort (S) | M | 44 | General | 22 ‡ | corr | SF, sTfR | SF <15 µg/L | PP | Hemoglobin | 3 d |
Matias [33] * | 2018 | Bangladesh | L-M | Clinical trial (S) | L | 1117 | General | NR | MLR | SF, sTfR | SF <12 µg/L | III | Hemoglobin | 6 m |
Positive association | ||||||||||||||
Kilbride [29] * | 2000 | Jordan | U-M | Case control (S) | H | 195 | Refugees | 15.2 ‡ | T-test | SF, Fe, TSAT (TIBC) | Anemia, SF <12 µg/L | PP | Hemoglobin | 9, 12 m (3, 6m) |
Santos [39] * | 2018 | China | U-M | Clinical trial (S) | L | 1194 | General | NR | MLR | SF, sTfR | II, III | Hemoglobin | 9 m | |
Abioye [40] * | 2019 | Philippines | L-M | Nested-Cohort (S) | L | 359 | Women with schistosomiasis and anemia | 13.4 ‡ | MLR | SF, (sTfR) | SF <12 µg/L | III | Hemoglobin | 6 m (12 m) |
Shukla [41] * | 2019 | India | L-M | Cohort | L | 163 | General | 62.6 ‡ | T-test, corr | SF | Anemia | PP | Hemoglobin | 14 wk |
Study | Year | Country | Country Income | Design (S) | Risk of Bias | n | Population | Background SF, µg/L | Statistics | Mother | Child | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Iron Biomarkers | Categories Based on | Stage | Outcome | Age | ||||||||||
No association | ||||||||||||||
Zhou [43] | 2006 | Australia | H | Clinical trial (S) | L | 430 | General | 14 ‡ | T-test | SF | (S), SF < 12 µg/L | III | Intelligence: reasoning, memory | 4 y |
Davidson [44] | 2008 | Seychelles | H | Cohort (S) | L | 229 | General | NR | MLR | SF, sTfR | II | Psychomotor | 5, 9, 25, 30 m | |
Rioux [45] | 2011 | Canada | H | Cohort (S) | M | 63 | General | NR | MLR | SF | SF < 10 µg/L | III | Cognition | 6 m |
Lewis [46] | 2014 | UK | H | Cohort (S) | L | 11,696 | General | NA | MLR | IV | Cognition | 8 y | ||
Tran [47] | 2014 | Vietnam | L-M | Cohort | L | 418 | General | 17.3 ‡ | MLR | SF | SF < 15 µg/L | I, III | Motor | 6 m |
Lou [48] | 2015 | China | U-M | Cohort | L | 69 | General | 17.4 ‡ | ANCOVA | SF | SF < 16 µg/L | III | Auditory brainstem response | 3, 10 m |
Mireku [49] | 2016 | Benin | L | Cohort (S) | L | 636 | General | NR | MLR | SF | II, PP | Cognition, motor, language, visual, perception | 12 m | |
Higher maternal iron status associated with adverse child outcome | ||||||||||||||
Hanieh [31] * | 2013 | Vietnam | L-M | Clinical trial (S) | L | 713 | General | 28.4 § | MLR | SF, (sTfR, sTfR/SF) | (S), SF < 15 µg/L | III | Cognition, language, motor | 6 m |
Higher maternal iron status associated with better child outcome | ||||||||||||||
Vaughn [50] | 1986 | USA | H | Cohort (S) | H | 115 | General | NR | T-test | TIBC (SF, Fe) | Irritability | III | (Neonatal behavior), Irritability | 3d (5 m) |
Hernández [51] | 2011 | Spain | H | Cohort (S) | L | 216 | General | NR | MLR | SF, TSAT | SF < 12 µg/L | I, II, III | Neonatal behavior | Neonatal period |
Tran [52] | 2013 | Vietnam | L-M | Cohort | L | 378 | General | NR | MLR | SF | SF < 15 µg/L | I, III | Cognition | 6 m |
Koubaa [53] | 2015 | Sweden | H | Cohort | L | 116 | Women with eating disorders | 42.7 ‡ | corr | SF | SF < 20 µg/L | I | Memory | 5 y |
Park [54] | 2016 | Philippines | L-M | Nested-cohort | L | 370 | Women with schistosomiasis | 6.2 § | MLR | SF, sTfR/SF (sTfR) | III | Cognition, language, motor | 12 m | |
Berglund [55] | 2017 | Spain | H | Cohort (S) | L | 331 | General | 16.7 ‡ | ANCOVA | SF, TSAT | SF < 15 µg/L | III, PP | Cognition, language, motor | 18 m |
Santos [39] * | 2018 | China | U-M | Clinical trial (S) | L | 1194 | General | NR | MLR | SF, sTfR | II, III | Motor | 9 m | |
Choudhury [56] | 2015 | India | L-M | Cohort | L | 90 | General | 36.9 ‡ | MLR | SF | PP | Auditory brainstem response | 24 to 48 h | |
ElAlfy [57] | 2018 | Egypt | L-M | Case control | L | 100 | General | 55.6 ‡ | T-test | SF (Fe, TSAT, TIBC) | SF < 15 µg/L | PP | Auditory brainstem response | 48 h, 3 m |
Arija [58] | 2019 | Spain | H | Cohort (S) | L | 2032 | General | NR | MLR | SF | SF < 12 µg/L | I | Memory, attention, flexibility and inhibition | 7 y |
Kupsco [59] | 2020 | Mexico | U-M | Cohort (S) | L | 571 | General | 36.7 ‡ | GAM | SF | SF < 15 µg/L | II, III, PP | Memory, motor, cognition | 4–6 y |
Santa-Marina [60] | 2020 | Spain | H | Cohort | L | 1095 | General | 35.9 ‡ | PRM | SF | I | Symptoms of Attention deficit/hyperactivity disorder | 4–5 y |
Study | Year | Country | Country Income | Design (S) | Risk of Bias | n | Population | Back-ground SF, µg/L | Statistics | Mother | Child | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Iron Biomarkers | Categories Based on | Stage | Outcome | Age | ||||||||||
Cardiovascular and bone outcomes | ||||||||||||||
Ganpule [61] | 2006 | India | L-M | Cohort (S) | L | 797 | General | NR | MLR | SF | SF < 12 µg/L | II | Bone mass | 6 y |
Alwan [62] | 2012 | UK | H | Cohort | L | 348 | General | NA | MLR | IV | Blood pressure, adiposity | 40–41 y | ||
Alwan [63] | 2015 | UK | H | Cohort (S) | L | 362 | General | 37.5 ‡ | MLR | SF, sTfR, sTfR/sF | SF < 15 µg/L | I | Arterial Stiffness | 6 wk |
Pulmonary outcomes | ||||||||||||||
Nwaru [64] * | 2014 | UK | H | Cohort (S) | L | 157 | General | 28.4 ‡ | MLR | SF, sTfR, sTfR/sF | SF < 15 µg/L | I, PP | Wheeze, allergy | 1, 2, 5, 10 y |
Nwaru [64] * | 2014 | UK | H | Cohort (S) | L | 157 | General | 28.4 ‡ | MLR | SF, sTfR, sTfR/sF | SF < 15 µg/L | I, PP | Lung function | 1, 2, 5, 10 y |
Bédard [65] | 2018 | UK | H | Cohort (S) | L | 6002 | General | NA | MLR | IV | Lung function | 7.5 y | ||
Miscellaneous outcomes | ||||||||||||||
Abioye [66] | 2016 | Tanzania | L | Cohort (S) | L | 600 | General | 47.5 † | MLogR | SF, sTfR | SF ≤ 12 µg/L | I, II, PP | Infant mortality | 6 w |
Hanieh [67] | 2015 | Vietnam | L-M | Nested-cohort (S) | L | 1046 | General | 28 † | MLR | SF | I, III | Infant growth | 6 w, 6 m | |
Goldenberg [68] | 1998 | USA | H | Nested-cohort | L | 223 | Women with PRM | 38.3 ‡ | MLogR | SF | II, PP | Neonatal sepsis | Neonatal period | |
Størdal [69] | 2018 | Norway | H | Case control (S) | L | 94,209 | General | NA | CPHR | IV | Diabetes type 1 | 8 to 17 y | ||
Dai [70] | 2015 | Turkey | U-M | Case control | M | 254 | General | 24.3 ‡ | T-test | SF, Fe | Stage of ROP | III | Retinopathy of prematurity | Infancy |
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Quezada-Pinedo, H.G.; Cassel, F.; Duijts, L.; Muckenthaler, M.U.; Gassmann, M.; Jaddoe, V.W.V.; Reiss, I.K.M.; Vermeulen, M.J. Maternal Iron Status in Pregnancy and Child Health Outcomes after Birth: A Systematic Review and Meta-Analysis. Nutrients 2021, 13, 2221. https://doi.org/10.3390/nu13072221
Quezada-Pinedo HG, Cassel F, Duijts L, Muckenthaler MU, Gassmann M, Jaddoe VWV, Reiss IKM, Vermeulen MJ. Maternal Iron Status in Pregnancy and Child Health Outcomes after Birth: A Systematic Review and Meta-Analysis. Nutrients. 2021; 13(7):2221. https://doi.org/10.3390/nu13072221
Chicago/Turabian StyleQuezada-Pinedo, Hugo G., Florian Cassel, Liesbeth Duijts, Martina U. Muckenthaler, Max Gassmann, Vincent W. V. Jaddoe, Irwin K. M. Reiss, and Marijn J. Vermeulen. 2021. "Maternal Iron Status in Pregnancy and Child Health Outcomes after Birth: A Systematic Review and Meta-Analysis" Nutrients 13, no. 7: 2221. https://doi.org/10.3390/nu13072221
APA StyleQuezada-Pinedo, H. G., Cassel, F., Duijts, L., Muckenthaler, M. U., Gassmann, M., Jaddoe, V. W. V., Reiss, I. K. M., & Vermeulen, M. J. (2021). Maternal Iron Status in Pregnancy and Child Health Outcomes after Birth: A Systematic Review and Meta-Analysis. Nutrients, 13(7), 2221. https://doi.org/10.3390/nu13072221