(1) Random sequence generation (checking for possible selection bias)

For each included study, we will describe the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups.

We will assess the method as:

• low risk of bias (any truly random process, e.g. random number table, computer random number generator);

• high risk of bias (any non‐random process, e.g. odd or even date of birth, hospital or clinic record number);

• unclear risk of bias.

(2) Allocation concealment (checking for possible selection bias)

For each included study, we will describe the method used to conceal allocation to interventions prior to assignment, and will assess whether intervention allocation could have been foreseen in advance of, during recruitment, or changed after assignment.

We will assess the methods as:

• low risk of bias (e.g. telephone or central randomisation, consecutively numbered sealed opaque envelopes);

• high risk of bias (open random allocation, unsealed or non‐opaque envelopes, alternation, date of birth);

• unclear risk of bias.

(3.1) Blinding of participants and personnel (checking for possible performance bias)

For each included study, we will describe the methods used, if any, to blind study participants and personnel from knowledge of which intervention a participant received. We will consider that studies are at low risk of bias if they were blinded, or if we judge that the lack of blinding would be unlikely to affect results. We will assess blinding separately for different outcomes or classes of outcomes.

We will assess the methods as:

• low, high, or unclear risk of bias for participants;

• low, high, or unclear risk of bias for personnel.

(3.2) Blinding of outcome assessment (checking for possible detection bias)

For each included study, we will describe the methods used, if any, to blind outcome assessors from knowledge of which intervention a participant received. We will assess blinding separately for different outcomes or classes of outcomes.

We will assess methods used to blind outcome assessment as:

• low, high, or unclear risk of bias.

(4) Incomplete outcome data (checking for possible attrition bias due to the amount, nature, and handling of incomplete outcome data)

For each included study, and for each outcome or class of outcomes, we will describe the completeness of data, including attrition and exclusions from the analysis. We will state whether attrition and exclusions were reported, and the numbers included in the analysis at each stage (compared with the total randomised participants), reasons for attrition or exclusion where reported, and whether missing data were balanced across groups or were related to outcomes. Where sufficient information is reported, or can be supplied by the trial authors, we will re‐include missing data in the analyses that we undertake.

We will assess methods as:

• low risk of bias (e.g. no missing outcome data, missing outcome data balanced across groups);

• high risk of bias (e.g. numbers or reasons for missing data imbalanced across groups, ‘as treated’ analysis done with substantial departure of intervention received from that assigned at randomisation);

• unclear risk of bias.

(5) Selective reporting (checking for reporting bias)

For each included study, we will describe how we investigated the possibility of selective outcome reporting bias and what we found.

We will assess the methods as:

• low risk of bias (where it is clear that all of the study’s pre‐specified outcomes and all expected outcomes of interest to the review have been reported);

• high risk of bias (where not all the study’s pre‐specified outcomes have been reported, one or more reported primary outcomes were not pre‐specified, outcomes of interest are reported incompletely and so cannot be used, study fails to include results of a key outcome that would have been expected to have been reported);

• unclear risk of bias.

(6) Other bias (checking for bias due to problems not covered by (1) to (5) above)

For each included study, we will describe any important concerns we have about other possible sources of bias.

We will assess whether each study was free of other problems that could put it at risk of bias:

• low risk of other bias;

• high risk of other bias;

• unclear whether there is risk of other bias.

(7) Overall risk of bias

We will make explicit judgements about whether studies are at high risk of bias, according to the criteria given in the Cochrane Handbook of Systematic Reviews of Interventions (Higgins 2011). With reference to (1) to (6) above, we will assess the likely magnitude and direction of the bias and whether we consider it is likely to impact on the findings. We will explore the impact of the level of bias through undertaking sensitivity analyses ‐ see Sensitivity analysis.

Maternal

1. hypertensive disorders of pregnancy (as reported by trialists, including pre‐eclampsia, pregnancy‐induced hypertension, eclampsia);

2. caesarean section;

3. perineal trauma;

4. postnatal weight retention or return to pre‐pregnancy weight;

5. postnatal depression (as defined by trialists);

6. induction of labour.

Child (as a fetus, neonate, child, adult)

1. large‐for‐gestational age (more than 4 kg);

2. perinatal mortality (stillbirth and neonatal mortality);

3. mortality and morbidity composite (variously defined by trials, e.g. perinatal or infant death, shoulder dystocia, bone fracture or nerve palsy);

4. hypoglycaemia requiring treatment (as defined by trialists);

5. adiposity (including skin fold thickness, neonatal fat mass)*;

6. diabetes (type 1, type 2)*;

7. neurosensory disability (defined as any of the following: legal blindness, sensorineural deafness requiring hearing aids, moderate or severe cerebral palsy, developmental delay or impairment (defined as developmental quotient less than two standard deviations (SDs) below the mean).

We will use GRADEpro GDT software to import data from Review Manager 5.3 and create ’Summary of findings’ tables (GRADEpro GDT; RevMan 2014). We will produce a summary of the intervention effect and a measure of quality for each of the above outcomes, using the GRADE approach. The GRADE approach uses five considerations (study limitations, consistency of effect, imprecision, indirectness, and publication bias) to assess the quality of the body of evidence for each outcome. The evidence can be downgraded from 'high quality' by one level for serious, or by two levels for very serious limitations, depending on assessments for risk of bias, indirectness of evidence, serious inconsistency, imprecision of effect estimates, or potential publication bias.

*These outcomes will be reported for each stage of life where data are reported.

Dichotomous data

For dichotomous data, we will present results as a summary risk ratio (RR) with 95% confidence intervals (CI).

Continuous data

For continuous data, we will use the mean difference (MD) with 95% CI if outcomes are measured in the same way between trials. We will use the standardised mean difference (SMD) with 95% CI to combine trials that measure the same outcome, but use different methods.

Cluster‐randomised trials

We will include cluster‐randomised trials in the analyses along with individually‐randomised trials. If any included studies are cluster‐randomised trials, we will make adjustments, using the methods described in the Cochrane Handbook of Systematic Reviews for Interventions (Section 16.3.4 or 16.3.6), using an estimate of the intra‐cluster correlation co‐efficient (ICC) derived from the trial (if possible), from a similar trial, or from a study of a similar population (Higgins 2011). If we use ICCs from other sources, we will report this, and conduct sensitivity analyses to investigate the effect of variation in the ICC. We will consider it reasonable to combine the results from both cluster‐randomised trials and individually‐randomised trials if there is little heterogeneity between the study designs, and is unlikely there will be an interaction between the effect of intervention and the choice of randomisation unit. If cluster‐randomised trials are included, we will seek statistical advice on the appropriate analysis to enable us to include the data in the meta‐analyses.

Other unit of analysis issues