Vitamin D supplementation for term breastfed infants to prevent vitamin D deficiency and improve bone health.

Vitamin D deficiency is common worldwide, contributing to nutritional rickets and osteomalacia which have a major impact on health, growth, and development of infants, children and adolescents. Vitamin D levels are low in breast milk and exclusively breastfed infants are at risk of vitamin D insufficiency or deficiency. To determine the effect of vitamin D supplementation given to infants, or lactating mothers, on vitamin D deficiency, bone density and growth in healthy term breastfed infants. We used the standard search strategy of Cochrane Neonatal to 29 May 2020 supplemented by searches of clinical trials databases, conference proceedings, and citations. Randomised controlled trials (RCTs) and quasi-RCTs in breastfeeding mother-infant pairs comparing vitamin D supplementation given to infants or lactating mothers compared to placebo or no intervention, or sunlight, or that compare vitamin D supplementation of infants to supplementation of mothers. Two review authors assessed trial eligibility and risk of bias and independently extracted data. We used the GRADE approach to assess the certainty of evidence. We included 19 studies with 2837 mother-infant pairs assessing vitamin D given to infants (nine studies), to lactating mothers (eight studies), and to infants versus lactating mothers (six studies). No studies compared vitamin D given to infants versus periods of infant sun exposure. Vitamin D supplementation given to infants: vitamin D at 400 IU/day may increase 25-OH vitamin D levels (MD 22.63 nmol/L, 95% CI 17.05 to 28.21; participants = 334; studies = 6; low-certainty) and may reduce the incidence of vitamin D insufficiency (25-OH vitamin D < 50 nmol/L) (RR 0.57, 95% CI 0.41 to 0.80; participants = 274; studies = 4; low-certainty). However, there was insufficient evidence to determine if vitamin D given to the infant reduces the risk of vitamin D deficiency (25-OH vitamin D < 30 nmol/L) up till six months of age (RR 0.41, 95% CI 0.16 to 1.05; participants = 122; studies = 2), affects bone mineral content (BMC), or the incidence of biochemical or radiological rickets (all very-low certainty). We are uncertain about adverse effects including hypercalcaemia. There were no studies of higher doses of infant vitamin D (> 400 IU/day) compared to placebo. Vitamin D supplementation given to lactating mothers: vitamin D supplementation given to lactating mothers may increase infant 25-OH vitamin D levels (MD 24.60 nmol/L, 95% CI 21.59 to 27.60; participants = 597; studies = 7; low-certainty), may reduce the incidences of vitamin D insufficiency (RR 0.47, 95% CI 0.39 to 0.57; participants = 512; studies = 5; low-certainty), vitamin D deficiency (RR 0.15, 95% CI 0.09 to 0.24; participants = 512; studies = 5; low-certainty) and biochemical rickets (RR 0.06, 95% CI 0.01 to 0.44; participants = 229; studies = 2; low-certainty). The two studies that reported biochemical rickets used maternal dosages of oral D3 60,000 IU/day for 10 days and oral D3 60,000 IU postpartum and at 6, 10, and 14 weeks. However, infant BMC was not reported and there was insufficient evidence to determine if maternal supplementation has an effect on radiological rickets (RR 0.76, 95% CI 0.18 to 3.31; participants = 536; studies = 3; very low-certainty). All studies of maternal supplementation enrolled populations at high risk of vitamin D deficiency. We are uncertain of the effects of maternal supplementation on infant growth and adverse effects including hypercalcaemia. Vitamin D supplementation given to infants compared with supplementation given to lactating mothers: infant vitamin D supplementation compared to lactating mother supplementation may increase infant 25-OH vitamin D levels (MD 14.35 nmol/L, 95% CI 9.64 to 19.06; participants = 269; studies = 4; low-certainty). Infant vitamin D supplementation may reduce the incidence of vitamin D insufficiency (RR 0.61, 95% CI 0.40 to 0.94; participants = 334; studies = 4) and may reduce vitamin D deficiency (RR 0.35, 95% CI 0.17 to 0.72; participants = 334; studies = 4) but the evidence is very uncertain. Infant BMC and radiological rickets were not reported and there was insufficient evidence to determine if maternal supplementation has an effect on infant biochemical rickets. All studies enrolled patient populations at high risk of vitamin D deficiency. Studies compared an infant dose of vitamin D 400 IU/day with varying maternal vitamin D doses from 400 IU/day to > 4000 IU/day. We are uncertain about adverse effects including hypercalcaemia. For breastfed infants, vitamin D supplementation 400 IU/day for up to six months increases 25-OH vitamin D levels and reduces vitamin D insufficiency, but there was insufficient evidence to assess its effect on vitamin D deficiency and bone health. For higher-risk infants who are breastfeeding, maternal vitamin D supplementation reduces vitamin D insufficiency and vitamin D deficiency, but there was insufficient evidence to determine an effect on bone health. In populations at higher risk of vitamin D deficiency, vitamin D supplementation of infants led to greater increases in infant 25-OH vitamin D levels, reductions in vitamin D insufficiency and vitamin D deficiency compared to supplementation of lactating mothers. However, the evidence is very uncertain for markers of bone health. Maternal higher dose supplementation (≥ 4000 IU/day) produced similar infant 25-OH vitamin D levels as infant supplementation of 400 IU/day. The certainty of evidence was graded as low to very low for all outcomes.

Tan ML ，Abrams SA ，Osborn DA 《Cochrane Database of Systematic Reviews》

Effects of oral vitamin D supplementation on linear growth and other health outcomes among children under five years of age.

Vitamin D is a secosteroid hormone that is important for its role in calcium homeostasis to maintain skeletal health. Linear growth faltering and stunting remain pervasive indicators of poor nutrition status among infants and children under five years of age around the world, and low vitamin D status has been linked to poor growth. However, existing evidence on the effects of vitamin D supplementation on linear growth and other health outcomes among infants and children under five years of age has not been systematically reviewed. To assess effects of oral vitamin D supplementation on linear growth and other health outcomes among infants and children under five years of age. In December 2019, we searched CENTRAL, PubMed, Embase, 14 other electronic databases, and two trials registries. We also searched the reference lists of relevant publications for any relevant trials, and we contacted key organisations and authors to obtain information on relevant ongoing and unpublished trials. We included randomised controlled trials (RCTs) and quasi-RCTs assessing the effects of oral vitamin D supplementation, with or without other micronutrients, compared to no intervention, placebo, a lower dose of vitamin D, or the same micronutrients alone (and not vitamin D) in infants and children under five years of age who lived in any country. We used standard Cochrane methodological procedures. Out of 75 studies (187 reports; 12,122 participants) included in the qualitative analysis, 64 studies (169 reports; 10,854 participants) contributed data on our outcomes of interest for meta-analysis. A majority of included studies were conducted in India, USA, and Canada. Two studies reported for-profit funding, two were categorised as receiving mixed funding (non-profit and for-profit), five reported that they received no funding, 26 did not disclose funding sources, and the remaining studies were funded by non-profit funding. Certainty of evidence varied between high and very low across outcomes (all measured at endpoint) for each comparison. Vitamin D supplementation versus placebo or no intervention (31 studies) Compared to placebo or no intervention, vitamin D supplementation (at doses 200 to 2000 IU daily; or up to 300,000 IU bolus at enrolment) may make little to no difference in linear growth (measured length/height in cm) among children under five years of age (mean difference (MD) 0.66, 95% confidence interval (CI) -0.37 to 1.68; 3 studies, 240 participants; low-certainty evidence); probably improves length/height-for-age z-score (L/HAZ) (MD 0.11, 95% CI 0.001 to 0.22; 1 study, 1258 participants; moderate-certainty evidence); and probably makes little to no difference in stunting (risk ratio (RR) 0.90, 95% CI 0.80 to 1.01; 1 study, 1247 participants; moderate-certainty evidence). In terms of adverse events, vitamin D supplementation results in little to no difference in developing hypercalciuria compared to placebo (RR 2.03, 95% CI 0.28 to 14.67; 2 studies, 68 participants; high-certainty evidence). It is uncertain whether vitamin D supplementation impacts the development of hypercalcaemia as the certainty of evidence was very low (RR 0.82, 95% CI 0.35 to 1.90; 2 studies, 367 participants). Vitamin D supplementation (higher dose) versus vitamin D (lower dose) (34 studies) Compared to a lower dose of vitamin D (100 to 1000 IU daily; or up to 300,000 IU bolus at enrolment), higher-dose vitamin D supplementation (200 to 6000 IU daily; or up to 600,000 IU bolus at enrolment) may have little to no effect on linear growth, but we are uncertain about this result (MD 1.00, 95% CI -2.22 to 0.21; 5 studies, 283 participants), and it may make little to no difference in L/HAZ (MD 0.40, 95% CI -0.06 to 0.86; 2 studies, 105 participants; low-certainty evidence). No studies evaluated stunting. As regards adverse events, higher-dose vitamin D supplementation may make little to no difference in developing hypercalciuria (RR 1.16, 95% CI 1.00 to 1.35; 6 studies, 554 participants; low-certainty evidence) or in hypercalcaemia (RR 1.39, 95% CI 0.89 to 2.18; 5 studies, 986 participants; low-certainty evidence) compared to lower-dose vitamin D supplementation. Vitamin D supplementation (higher dose) + micronutrient(s) versus vitamin D (lower dose) + micronutrient(s) (9 studies) Supplementation with a higher dose of vitamin D (400 to 2000 IU daily, or up to 300,000 IU bolus at enrolment) plus micronutrients, compared to a lower dose (200 to 2000 IU daily, or up to 90,000 IU bolus at enrolment) of vitamin D with the same micronutrients, probably makes little to no difference in linear growth (MD 0.60, 95% CI -3.33 to 4.53; 1 study, 25 participants; moderate-certainty evidence). No studies evaluated L/HAZ or stunting. In terms of adverse events, higher-dose vitamin D supplementation with micronutrients, compared to lower-dose vitamin D with the same micronutrients, may make little to no difference in developing hypercalciuria (RR 1.00, 95% CI 0.06 to 15.48; 1 study, 86 participants; low-certainty evidence) and probably makes little to no difference in developing hypercalcaemia (RR 1.00, 95% CI 0.90, 1.11; 2 studies, 126 participants; moderate-certainty evidence). Four studies measured hyperphosphataemia and three studies measured kidney stones, but they reported no occurrences and therefore were not included in the comparison for these outcomes. Evidence suggests that oral vitamin D supplementation may result in little to no difference in linear growth, stunting, hypercalciuria, or hypercalcaemia, compared to placebo or no intervention, but may result in a slight increase in length/height-for-age z-score (L/HAZ). Additionally, evidence suggests that compared to lower doses of vitamin D, with or without micronutrients, vitamin D supplementation may result in little to no difference in linear growth, L/HAZ, stunting, hypercalciuria, or hypercalcaemia. Small sample sizes, substantial heterogeneity in terms of population and intervention parameters, and high risk of bias across many of the included studies limit our ability to confirm with any certainty the effects of vitamin D on our outcomes. Larger, well-designed studies of long duration (several months to years) are recommended to confirm whether or not oral vitamin D supplementation may impact linear growth in children under five years of age, among both those who are healthy and those with underlying infectious or non-communicable health conditions.

Huey SL ，Acharya N ，Silver A ，Sheni R ，Yu EA ，Peña-Rosas JP ，Mehta S ... -  《Cochrane Database of Systematic Reviews》

Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.

Description of the condition Malaria, an infectious disease transmitted by the bite of female mosquitoes from several Anopheles species, occurs in 87 countries with ongoing transmission (WHO 2020). The World Health Organization (WHO) estimated that, in 2019, approximately 229 million cases of malaria occurred worldwide, with 94% occurring in the WHO's African region (WHO 2020). Of these malaria cases, an estimated 409,000 deaths occurred globally, with 67% occurring in children under five years of age (WHO 2020). Malaria also negatively impacts the health of women during pregnancy, childbirth, and the postnatal period (WHO 2020). Sulfadoxine/pyrimethamine (SP), an antifolate antimalarial, has been widely used across sub-Saharan Africa as the first-line treatment for uncomplicated malaria since it was first introduced in Malawi in 1993 (Filler 2006). Due to increasing resistance to SP, in 2000 the WHO recommended that one of several artemisinin-based combination therapies (ACTs) be used instead of SP for the treatment of uncomplicated malaria caused by Plasmodium falciparum (Global Partnership to Roll Back Malaria 2001). However, despite these recommendations, SP continues to be advised for intermittent preventive treatment in pregnancy (IPTp) and intermittent preventive treatment in infants (IPTi), whether the person has malaria or not (WHO 2013). Description of the intervention Folate (vitamin B9) includes both naturally occurring folates and folic acid, the fully oxidized monoglutamic form of the vitamin, used in dietary supplements and fortified food. Folate deficiency (e.g. red blood cell (RBC) folate concentrations of less than 305 nanomoles per litre (nmol/L); serum or plasma concentrations of less than 7 nmol/L) is common in many parts of the world and often presents as megaloblastic anaemia, resulting from inadequate intake, increased requirements, reduced absorption, or abnormal metabolism of folate (Bailey 2015; WHO 2015a). Pregnant women have greater folate requirements; inadequate folate intake (evidenced by RBC folate concentrations of less than 400 nanograms per millilitre (ng/mL), or 906 nmol/L) prior to and during the first month of pregnancy increases the risk of neural tube defects, preterm delivery, low birthweight, and fetal growth restriction (Bourassa 2019). The WHO recommends that all women who are trying to conceive consume 400 micrograms (µg) of folic acid daily from the time they begin trying to conceive through to 12 weeks of gestation (WHO 2017). In 2015, the WHO added the dosage of 0.4 mg of folic acid to the essential drug list (WHO 2015c). Alongside daily oral iron (30 mg to 60 mg elemental iron), folic acid supplementation is recommended for pregnant women to prevent neural tube defects, maternal anaemia, puerperal sepsis, low birthweight, and preterm birth in settings where anaemia in pregnant women is a severe public health problem (i.e. where at least 40% of pregnant women have a blood haemoglobin (Hb) concentration of less than 110 g/L). How the intervention might work Potential interactions between folate status and malaria infection The malaria parasite requires folate for survival and growth; this has led to the hypothesis that folate status may influence malaria risk and severity. In rhesus monkeys, folate deficiency has been found to be protective against Plasmodium cynomolgi malaria infection, compared to folate-replete animals (Metz 2007). Alternatively, malaria may induce or exacerbate folate deficiency due to increased folate utilization from haemolysis and fever. Further, folate status measured via RBC folate is not an appropriate biomarker of folate status in malaria-infected individuals since RBC folate values in these individuals are indicative of both the person's stores and the parasite's folate synthesis. A study in Nigeria found that children with malaria infection had significantly higher RBC folate concentrations compared to children without malaria infection, but plasma folate levels were similar (Bradley-Moore 1985). Why it is important to do this review The malaria parasite needs folate for survival and growth in humans. For individuals, adequate folate levels are critical for health and well-being, and for the prevention of anaemia and neural tube defects. Many countries rely on folic acid supplementation to ensure adequate folate status in at-risk populations. Different formulations for folic acid supplements are available in many international settings, with dosages ranging from 400 µg to 5 mg. Evaluating folic acid dosage levels used in supplementation efforts may increase public health understanding of its potential impacts on malaria risk and severity and on treatment failures. Examining folic acid interactions with antifolate antimalarial medications and with malaria disease progression may help countries in malaria-endemic areas determine what are the most appropriate lower dose folic acid formulations for at-risk populations. The WHO has highlighted the limited evidence available and has indicated the need for further research on biomarkers of folate status, particularly interactions between RBC folate concentrations and tuberculosis, human immunodeficiency virus (HIV), and antifolate antimalarial drugs (WHO 2015b). An earlier Cochrane Review assessed the effects and safety of iron supplementation, with or without folic acid, in children living in hyperendemic or holoendemic malaria areas; it demonstrated that iron supplementation did not increase the risk of malaria, as indicated by fever and the presence of parasites in the blood (Neuberger 2016). Further, this review stated that folic acid may interfere with the efficacy of SP; however, the efficacy and safety of folic acid supplementation on these outcomes has not been established. This review will provide evidence on the effectiveness of daily folic acid supplementation in healthy and malaria-infected individuals living in malaria-endemic areas. Additionally, it will contribute to achieving both the WHO Global Technical Strategy for Malaria 2016-2030 (WHO 2015d), and United Nations Sustainable Development Goal 3 (to ensure healthy lives and to promote well-being for all of all ages) (United Nations 2021), and evaluating whether the potential effects of folic acid supplementation, at different doses (e.g. 0.4 mg, 1 mg, 5 mg daily), interferes with the effect of drugs used for prevention or treatment of malaria. To examine the effects of folic acid supplementation, at various doses, on malaria susceptibility (risk of infection) and severity among people living in areas with various degrees of malaria endemicity. We will examine the interaction between folic acid supplements and antifolate antimalarial drugs. Specifically, we will aim to answer the following. Among uninfected people living in malaria endemic areas, who are taking or not taking antifolate antimalarials for malaria prophylaxis, does taking a folic acid-containing supplement increase susceptibility to or severity of malaria infection? Among people with malaria infection who are being treated with antifolate antimalarials, does folic acid supplementation increase the risk of treatment failure? Criteria for considering studies for this review Types of studies Inclusion criteria Randomized controlled trials (RCTs) Quasi-RCTs with randomization at the individual or cluster level conducted in malaria-endemic areas (areas with ongoing, local malaria transmission, including areas approaching elimination, as listed in the World Malaria Report 2020) (WHO 2020) Exclusion criteria Ecological studies Observational studies In vivo/in vitro studies Economic studies Systematic literature reviews and meta-analyses (relevant systematic literature reviews and meta-analyses will be excluded but flagged for grey literature screening) Types of participants Inclusion criteria Individuals of any age or gender, living in a malaria endemic area, who are taking antifolate antimalarial medications (including but not limited to sulfadoxine/pyrimethamine (SP), pyrimethamine-dapsone, pyrimethamine, chloroquine and proguanil, cotrimoxazole) for the prevention or treatment of malaria (studies will be included if more than 70% of the participants live in malaria-endemic regions) Studies assessing participants with or without anaemia and with or without malaria parasitaemia at baseline will be included Exclusion criteria Individuals not taking antifolate antimalarial medications for prevention or treatment of malaria Individuals living in non-malaria endemic areas Types of interventions Inclusion criteria Folic acid supplementation Form: in tablet, capsule, dispersible tablet at any dose, during administration, or periodically Timing: during, before, or after (within a period of four to six weeks) administration of antifolate antimalarials Iron-folic acid supplementation Folic acid supplementation in combination with co-interventions that are identical between the intervention and control groups. Co-interventions include: anthelminthic treatment; multivitamin or multiple micronutrient supplementation; 5-methyltetrahydrofolate supplementation. Exclusion criteria Folate through folate-fortified water Folic acid administered through large-scale fortification of rice, wheat, or maize Comparators Placebo No treatment No folic acid/different doses of folic acid Iron Types of outcome measures Primary outcomes Uncomplicated malaria (defined as a history of fever with parasitological confirmation; acceptable parasitological confirmation will include rapid diagnostic tests (RDTs), malaria smears, or nucleic acid detection (i.e. polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), etc.)) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Severe malaria (defined as any case with cerebral malaria or acute P. falciparum malaria, with signs of severity or evidence of vital organ dysfunction, or both) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Parasite clearance (any Plasmodium species), defined as the time it takes for a patient who tests positive at enrolment and is treated to become smear-negative or PCR negative. This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Treatment failure (defined as the inability to clear malaria parasitaemia or prevent recrudescence after administration of antimalarial medicine, regardless of whether clinical symptoms are resolved) (WHO 2019). This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Secondary outcomes Duration of parasitaemia Parasite density Haemoglobin (Hb) concentrations (g/L) Anaemia: severe anaemia (defined as Hb less than 70 g/L in pregnant women and children aged six to 59 months; and Hb less than 80 g/L in other populations); moderate anaemia (defined as Hb less than 100 g/L in pregnant women and children aged six to 59 months; and less than 110 g/L in others) Death from any cause Among pregnant women: stillbirth (at less than 28 weeks gestation); low birthweight (less than 2500 g); active placental malaria (defined as Plasmodium detected in placental blood by smear or PCR, or by Plasmodium detected on impression smear or placental histology). Search methods for identification of studies A search will be conducted to identify completed and ongoing studies, without date or language restrictions. Electronic searches A search strategy will be designed to include the appropriate subject headings and text word terms related to each intervention of interest and study design of interest (see Appendix 1). Searches will be broken down by these two criteria (intervention of interest and study design of interest) to allow for ease of prioritization, if necessary. The study design filters recommended by the Scottish Intercollegiate Guidelines Network (SIGN), and those designed by Cochrane for identifying clinical trials for MEDLINE and Embase, will be used (SIGN 2020). There will be no date or language restrictions. Non-English articles identified for inclusion will be translated into English. If translations are not possible, advice will be requested from the Cochrane Infectious Diseases Group and the record will be stored in the "Awaiting assessment" section of the review until a translation is available. The following electronic databases will be searched for primary studies. Cochrane Central Register of Controlled Trials. Cumulative Index to Nursing and Allied Health Literature (CINAHL). Embase. MEDLINE. Scopus. Web of Science (both the Social Science Citation Index and the Science Citation Index). We will conduct manual searches of ClinicalTrials.gov, the International Clinical Trials Registry Platform (ICTRP), and the United Nations Children's Fund (UNICEF) Evaluation and Research Database (ERD), in order to identify relevant ongoing or planned trials, abstracts, and full-text reports of evaluations, studies, and surveys related to programmes on folic acid supplementation in malaria-endemic areas. Additionally, manual searches of grey literature to identify RCTs that have not yet been published but are potentially eligible for inclusion will be conducted in the following sources. Global Index Medicus (GIM). African Index Medicus (AIM). Index Medicus for the Eastern Mediterranean Region (IMEMR). Latin American & Caribbean Health Sciences Literature (LILACS). Pan American Health Organization (PAHO). Western Pacific Region Index Medicus (WPRO). Index Medicus for the South-East Asian Region (IMSEAR). The Spanish Bibliographic Index in Health Sciences (IBECS) (ibecs.isciii.es/). Indian Journal of Medical Research (IJMR) (journals.lww.com/ijmr/pages/default.aspx). Native Health Database (nativehealthdatabase.net/). Scielo (www.scielo.br/). Searching other resources Handsearches of the five journals with the highest number of included studies in the last 12 months will be conducted to capture any relevant articles that may not have been indexed in the databases at the time of the search. We will contact the authors of included studies and will check reference lists of included papers for the identification of additional records. For assistance in identifying ongoing or unpublished studies, we will contact the Division of Nutrition, Physical Activity, and Obesity (DNPAO) and the Division of Parasitic Diseases and Malaria (DPDM) of the CDC, the United Nations World Food Programme (WFP), Nutrition International (NI), Global Alliance for Improved Nutrition (GAIN), and Hellen Keller International (HKI). Data collection and analysis Selection of studies Two review authors will independently screen the titles and abstracts of articles retrieved by each search to assess eligibility, as determined by the inclusion and exclusion criteria. Studies deemed eligible for inclusion by both review authors in the abstract screening phase will advance to the full-text screening phase, and full-text copies of all eligible papers will be retrieved. If full articles cannot be obtained, we will attempt to contact the authors to obtain further details of the studies. If such information is not obtained, we will classify the study as "awaiting assessment" until further information is published or made available to us. The same two review authors will independently assess the eligibility of full-text articles for inclusion in the systematic review. If any discrepancies occur between the studies selected by the two review authors, a third review author will provide arbitration. Each trial will be scrutinized to identify multiple publications from the same data set, and the justification for excluded trials will be documented. A PRISMA flow diagram of the study selection process will be presented to provide information on the number of records identified in the literature searches, the number of studies included and excluded, and the reasons for exclusion (Moher 2009). The list of excluded studies, along with their reasons for exclusion at the full-text screening phase, will also be created. Data extraction and management Two review authors will independently extract data for the final list of included studies using a standardized data specification form. Discrepancies observed between the data extracted by the two authors will be resolved by involving a third review author and reaching a consensus. Information will be extracted on study design components, baseline participant characteristics, intervention characteristics, and outcomes. For individually randomized trials, we will record the number of participants experiencing the event and the number analyzed in each treatment group or the effect estimate reported (e.g. risk ratio (RR)) for dichotomous outcome measures. For count data, we will record the number of events and the number of person-months of follow-up in each group. If the number of person-months is not reported, the product of the duration of follow-up and the number of children evaluated will be used to estimate this figure. We will calculate the rate ratio and standard error (SE) for each study. Zero events will be replaced by 0.5. We will extract both adjusted and unadjusted covariate incidence rate ratios if they are reported in the original studies. For continuous data, we will extract means (arithmetic or geometric) and a measure of variance (standard deviation (SD), SE, or confidence interval (CI)), percentage or mean change from baseline, and the numbers analyzed in each group. SDs will be computed from SEs or 95% CIs, assuming a normal distribution of the values. Haemoglobin values in g/dL will be calculated by multiplying haematocrit or packed cell volume values by 0.34, and studies reporting haemoglobin values in g/dL will be converted to g/L. In cluster-randomized trials, we will record the unit of randomization (e.g. household, compound, sector, or village), the number of clusters in the trial, and the average cluster size. The statistical methods used to analyze the trials will be documented, along with details describing whether these methods adjusted for clustering or other covariates. We plan to extract estimates of the intra-cluster correlation coefficient (ICC) for each outcome. Where results are adjusted for clustering, we will extract the treatment effect estimate and the SD or CI. If the results are not adjusted for clustering, we will extract the data reported. Assessment of risk of bias in included studies Two review authors (KSC, LFY) will independently assess the risk of bias for each included trial using the Cochrane 'Risk of bias 2' tool (RoB 2) for randomized studies (Sterne 2019). Judgements about the risk of bias of included studies will be made according to the recommendations outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). Disagreements will be resolved by discussion, or by involving a third review author. The interest of our review will be to assess the effect of assignment to the interventions at baseline. We will evaluate each primary outcome using the RoB2 tool. The five domains of the Cochrane RoB2 tool include the following. Bias arising from the randomization process. Bias due to deviations from intended interventions. Bias due to missing outcome data. Bias in measurement of the outcome. Bias in selection of the reported result. Each domain of the RoB2 tool comprises the following. A series of 'signalling' questions. A judgement about the risk of bias for the domain, facilitated by an algorithm that maps responses to the signalling questions to a proposed judgement. Free-text boxes to justify responses to the signalling questions and 'Risk of bias' judgements. An option to predict (and explain) the likely direction of bias. Responses to signalling questions elicit information relevant to an assessment of the risk of bias. These response options are as follows. Yes (may indicate either low or high risk of bias, depending on the most natural way to ask the question). Probably yes. Probably no. No. No information (may indicate no evidence of that problem or an absence of information leading to concerns about there being a problem). Based on the answer to the signalling question, a 'Risk of bias' judgement is assigned to each domain. These judgements include one of the following. High risk of bias Low risk of bias Some concerns To generate the risk of bias judgement for each domain in the randomized studies, we will use the Excel template, available at www.riskofbias.info/welcome/rob-2-0-tool/current-version-of-rob-2. This file will be stored on a scientific data website, available to readers. Risk of bias in cluster randomized controlled trials For the cluster randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 1b (bias arising from the timing of identification or recruitment of participants) and its related signalling questions. To generate the risk of bias judgement for each domain in the cluster RCTs, we will use the Excel template available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-cluster-randomized-trials. This file will be stored on a scientific data website, available to readers. Risk of bias in cross-over randomized controlled trials For cross-over randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 2 (bias due to deviations from intended interventions), and Domain 3 (bias due to missing outcome data), and their respective signalling questions. To generate the risk of bias judgement for each domain in the cross-over RCTs, we will use the Excel template, available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-crossover-trials, for each risk of bias judgement of cross-over randomized studies. This file will be stored on a scientific data website, available to readers. Overall risk of bias The overall 'Risk of bias' judgement for each specific trial being assessed will be based on each domain-level judgement. The overall judgements include the following. Low risk of bias (the trial is judged to be at low risk of bias for all domains). Some concerns (the trial is judged to raise some concerns in at least one domain but is not judged to be at high risk of bias for any domain). High risk of bias (the trial is judged to be at high risk of bias in at least one domain, or is judged to have some concerns for multiple domains in a way that substantially lowers confidence in the result). The 'risk of bias' assessments will inform our GRADE evaluations of the certainty of evidence for our primary outcomes presented in the 'Summary of findings' tables and will also be used to inform the sensitivity analyses; (see Sensitivity analysis). If there is insufficient information in study reports to enable an assessment of the risk of bias, studies will be classified as "awaiting assessment" until further information is published or made available to us. Measures of treatment effect Dichotomous data For dichotomous data, we will present proportions and, for two-group comparisons, results as average RR or odds ratio (OR) with 95% CIs. Ordered categorical data Continuous data We will report results for continuous outcomes as the mean difference (MD) with 95% CIs, if outcomes are measured in the same way between trials. Where some studies have reported endpoint data and others have reported change-from-baseline data (with errors), we will combine these in the meta-analysis, if the outcomes were reported using the same scale. We will use the standardized mean difference (SMD), with 95% CIs, to combine trials that measured the same outcome but used different methods. If we do not find three or more studies for a pooled analysis, we will summarize the results in a narrative form. Unit of analysis issues Cluster-randomized trials We plan to combine results from both cluster-randomized and individually randomized studies, providing there is little heterogeneity between the studies. If the authors of cluster-randomized trials conducted their analyses at a different level from that of allocation, and they have not appropriately accounted for the cluster design in their analyses, we will calculate the trials' effective sample sizes to account for the effect of clustering in data. When one or more cluster-RCT reports RRs adjusted for clustering, we will compute cluster-adjusted SEs for the other trials. When none of the cluster-RCTs provide cluster-adjusted RRs, we will adjust the sample size for clustering. We will divide, by the estimated design effects (DE), the number of events and number evaluated for dichotomous outcomes and the number evaluated for continuous outcomes, where DE = 1 + ((average cluster size 1) * ICC). The derivation of the estimated ICCs and DEs will be reported. We will utilize the intra-cluster correlation coefficient (ICC), derived from the trial (if available), or from another source (e.g., using the ICCs derived from other, similar trials) and then calculate the design effect with the formula provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). If this approach is used, we will report it and undertake sensitivity analysis to investigate the effect of variations in ICC. Studies with more than two treatment groups If we identify studies with more than two intervention groups (multi-arm studies), where possible we will combine groups to create a single pair-wise comparison or use the methods set out in the Cochrane Handbook to avoid double counting study participants (Higgins 2021). For the subgroup analyses, when the control group was shared by two or more study arms, we will divide the control group (events and total population) over the number of relevant subgroups to avoid double counting the participants. Trials with several study arms can be included more than once for different comparisons. Cross-over trials From cross-over trials, we will consider the first period of measurement only and will analyze the results together with parallel-group studies. Multiple outcome events In several outcomes, a participant might experience more than one outcome event during the trial period. For all outcomes, we will extract the number of participants with at least one event. Dealing with missing data We will contact the trial authors if the available data are unclear, missing, or reported in a format that is different from the format needed. We aim to perform a 'per protocol' or 'as observed' analysis; otherwise, we will perform a complete case analysis. This means that for treatment failure, we will base the analyses on the participants who received treatment and the number of participants for which there was an inability to clear malarial parasitaemia or prevent recrudescence after administration of an antimalarial medicine reported in the studies. Assessment of heterogeneity Heterogeneity in the results of the trials will be assessed by visually examining the forest plot to detect non-overlapping CIs, using the Chi2 test of heterogeneity (where a P value of less than 0.1 indicates statistical significance) and the I2 statistic of inconsistency (with a value of greater than 50% denoting moderate levels of heterogeneity). When statistical heterogeneity is present, we will investigate the reasons for it, using subgroup analysis. Assessment of reporting biases We will construct a funnel plot to assess the effect of small studies for the main outcome (when including more than 10 trials). Data synthesis The primary analysis will include all eligible studies that provide data regardless of the overall risk of bias as assessed by the RoB2 tool. Analyses will be conducted using Review Manager 5.4 (Review Manager 2020). Cluster-RCTs will be included in the main analysis after adjustment for clustering (see the previous section on cluster-RCTs). The meta-analysis will be performed using the Mantel-Haenszel random-effects model or the generic inverse variance method (when adjustment for clustering is performed by adjusting SEs), as appropriate. Subgroup analysis and investigation of heterogeneity The overall risk of bias will not be used as the basis in conducting our subgroup analyses. However, where data are available, we plan to conduct the following subgroup analyses, independent of heterogeneity. Dose of folic acid supplementation: higher doses (4 mg or more, daily) versus lower doses (less than 4 mg, daily). Moderate-severe anaemia at baseline (mean haemoglobin of participants in a trial at baseline below 100 g/L for pregnant women and children aged six to 59 months, and below 110 g/L for other populations) versus normal at baseline (mean haemoglobin above 100 g/L for pregnant women and children aged six to 59 months, and above 110 g/L for other populations). Antimalarial drug resistance to parasite: known resistance versus no resistance versus unknown/mixed/unreported parasite resistance. Folate status at baseline: Deficient (e.g. RBC folate concentration of less than 305 nmol/L, or serum folate concentration of less than 7nmol/L) and Insufficient (e.g. RBC folate concentration from 305 to less than 906 nmol/L, or serum folate concentration from 7 to less than 25 nmol/L) versus Sufficient (e.g. RBC folate concentration above 906 nmol/L, or serum folate concentration above 25 nmol/L). Presence of anaemia at baseline: yes versus no. Mandatory fortification status: yes, versus no (voluntary or none). We will only use the primary outcomes in any subgroup analyses, and we will limit subgroup analyses to those outcomes for which three or more trials contributed data. Comparisons between subgroups will be performed using Review Manager 5.4 (Review Manager 2020). Sensitivity analysis We will perform a sensitivity analysis, using the risk of bias as a variable to explore the robustness of the findings in our primary outcomes. We will verify the behaviour of our estimators by adding and removing studies with a high risk of bias overall from the analysis. That is, studies with a low risk of bias versus studies with a high risk of bias. Summary of findings and assessment of the certainty of the evidence For the assessment across studies, we will use the GRADE approach, as outlined in (Schünemann 2021). We will use the five GRADE considerations (study limitations based on RoB2 judgements, consistency of effect, imprecision, indirectness, and publication bias) to assess the certainty of the body of evidence as it relates to the studies which contribute data to the meta-analyses for the primary outcomes. The GRADEpro Guideline Development Tool (GRADEpro) will be used to import data from Review Manager 5.4 (Review Manager 2020) to create 'Summary of Findings' tables. The primary outcomes for the main comparison will be listed with estimates of relative effects, along with the number of participants and studies contributing data for those outcomes. These tables will provide outcome-specific information concerning the overall certainty of evidence from studies included in the comparison, the magnitude of the effect of the interventions examined, and the sum of available data on the outcomes we considered. We will include only primary outcomes in the summary of findings tables. For each individual outcome, two review authors (KSC, LFY) will independently assess the certainty of the evidence using the GRADE approach (Balshem 2011). For assessments of the overall certainty of evidence for each outcome that includes pooled data from included trials, we will downgrade the evidence from 'high certainty' by one level for serious (or by two for very serious) study limitations (risk of bias, indirectness of evidence, serious inconsistency, imprecision of effect estimates, or potential publication bias).

Crider K ，Williams J ，Qi YP ，Gutman J ，Yeung L ，Mai C ，Finkelstain J ，Mehta S ，Pons-Duran C ，Menéndez C ，Moraleda C ，Rogers L ，Daniels K ，Green P ... -  《Cochrane Database of Systematic Reviews》

Effectiveness and safety of vitamin D in relation to bone health.

Cranney A ，Horsley T ，O'Donnell S ，Weiler H ，Puil L ，Ooi D ，Atkinson S ，Ward L ，Moher D ，Hanley D ，Fang M ，Yazdi F ，Garritty C ，Sampson M ，Barrowman N ，Tsertsvadze A ，Mamaladze V ... -  《-》

Vitamin D supplementation for women during pregnancy.

Vitamin D supplementation during pregnancy may help improve maternal and neonatal health outcomes (such as fewer preterm birth and low birthweight babies) and reduce the risk of adverse pregnancy outcomes (such as severe postpartum haemorrhage). To examine whether vitamin D supplementation alone or in combination with calcium or other vitamins and minerals given to women during pregnancy can safely improve certain maternal and neonatal outcomes. We searched the Cochrane Pregnancy and Childbirth Trials Register (which includes results of comprehensive searches of CENTRAL, MEDLINE, Embase, CINAHL, ClinicalTrials.gov, the WHO International Clinical Trials Registry Platform, and relevant conference proceedings) (3 December 2022). We also searched the reference lists of retrieved studies. Randomised and quasi-randomised trials evaluating the effect of supplementation with vitamin D alone or in combination with other micronutrients for women during pregnancy in comparison to placebo or no intervention. Two review authors independently i) assessed the eligibility of studies against the inclusion criteria, ii) assessed trustworthiness based on pre-defined criteria of scientific integrity, iii) extracted data from included studies, and iv) assessed the risk of bias of the included studies. We assessed the certainty of the evidence using the GRADE approach. The previous version of this review included 30 studies; in this update, we have removed 20 of these studies to 'awaiting classification' following assessments of trustworthiness, one study has been excluded, and one new study included. This current review has a total of 10 included studies, 117 excluded studies, 34 studies in awaiting assessment, and seven ongoing studies. We used the GRADE approach to assess the certainty of the evidence. This removal of the studies resulted in evidence that was downgraded to low-certainty or very low-certainty due to study design limitations, inconsistency between studies, and imprecision. Supplementation with vitamin D compared to no intervention or a placebo A total of eight studies involving 2313 pregnant women were included in this comparison. We assessed four studies as having a low risk of bias for most domains and four studies as having high risk or unclear risk of bias for most domains. The evidence is very uncertain about the effect of supplementation with vitamin D during pregnancy compared to placebo or no intervention on pre-eclampsia (risk ratio (RR) 0.53, 95% confidence interval (CI) 0.21 to 1.33; 1 study, 165 women), gestational diabetes (RR 0.53, 95% CI 0.03 to 8.28; 1 study, 165 women), preterm birth (< 37 weeks) (RR 0.76, 95% CI 0.25 to 2.33; 3 studies, 1368 women), nephritic syndrome (RR 0.17, 95% CI 0.01 to 4.06; 1 study, 135 women), or hypercalcaemia (1 study; no cases reported). Supplementation with vitamin D during pregnancy may reduce the risk of severe postpartum haemorrhage; however, only one study reported this outcome (RR 0.68, 95% CI 0.51 to 0.91; 1 study, 1134 women; low-certainty evidence) and may reduce the risk of low birthweight; however, the upper CI suggests that an increase in risk cannot be ruled out (RR 0.69, 95% CI 0.44 to 1.08; 3 studies, 371 infants; low-certainty evidence). Supplementation with vitamin D + calcium compared to no intervention or a placebo One study involving 84 pregnant women was included in this comparison. Overall, this study was at moderate to high risk of bias. Pre-eclampsia, gestational diabetes, and maternal adverse events were not reported. The evidence is very uncertain about the effect of supplementation with vitamin D and calcium on preterm birth (RR not estimable; very low-certainty evidence) or for low birthweight (RR 1.45, 95% CI 0.14 to 14.94; very low-certainty evidence) compared to women who received placebo or no intervention. Supplementation with vitamin D + calcium + other vitamins and minerals versus calcium + other vitamins and minerals (but no vitamin D) One study involving 1298 pregnant women was included in this comparison. We assessed this study as having a low risk of bias in all domains. Pre-eclampsia was not reported. The evidence is very uncertain about the effect of supplementation with vitamin D, calcium, and other vitamins and minerals during pregnancy compared to no vitamin D on gestational diabetes (RR 0.42, 95% CI 0.10 to 1.73; very low-certainty evidence), maternal adverse events (hypercalcaemia no events and hypercalciuria RR 0.25, 95% CI 0.02 to 3.97; very low-certainty evidence), preterm birth (RR 1.04, 95% CI 0.68 to 1.59; low-certainty evidence), or low birthweight (RR 1.12, 95% CI 0.82 to 1.51; low-certainty evidence). This updated review using the trustworthy assessment tool removed 21 studies from the previous update and added one new study for a total of 10 included studies. In this setting, supplementation with vitamin D alone compared to no intervention or a placebo resulted in very uncertain evidence on pre-eclampsia, gestational diabetes, preterm birth, or nephritic syndrome. It may reduce the risk of severe postpartum haemorrhage; however, only one study reported this outcome. It may also reduce the risk of low birthweight; however, the upper CI suggests that an increase in risk cannot be ruled out. Supplementation with vitamin D and calcium versus placebo or no intervention resulted in very uncertain evidence on preterm birth and low birthweight. Pre-eclampsia, gestational diabetes, and maternal adverse events were not reported in the only study included in this comparison. Supplementation with vitamin D + calcium + other vitamins and minerals versus calcium + other vitamins and minerals (but no vitamin D) resulted in very uncertain evidence on gestational diabetes and maternal adverse events (hypercalciuria) and uncertain evidence on preterm birth and low birthweight. Pre-eclampsia was not reported in the only study included in this comparison. All findings warrant further research. Additional rigorous, high-quality, and larger randomised trials are required to evaluate the effects of vitamin D supplementation in pregnancy, particularly in relation to the risk of maternal adverse events.

Palacios C ，Kostiuk LL ，Cuthbert A ，Weeks J ... -  《Cochrane Database of Systematic Reviews》