Breastfeeding and Infant Health
Last registered on March 12, 2020

Pre-Trial

Trial Information
General Information
Title
Breastfeeding and Infant Health
RCT ID
AEARCTR-0005549
Initial registration date
March 12, 2020
Last updated
March 12, 2020 6:58 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
University of Zurich
Other Primary Investigator(s)
PI Affiliation
PLA NAVY NO.905 Hospital
PI Affiliation
Fudan University
PI Affiliation
University of Zurich
Additional Trial Information
Status
In development
Start date
2020-03-13
End date
2021-06-30
Secondary IDs
Abstract
This study examines the impact of an information treatment on breastfeeding and infant illness as the primary outcomes as well as maternal and child well-being more broadly as secondary outcomes. The aim is to study the causal effect of breastfeeding promotion on infant illness in a developed context with low rates of infection. For this purpose, we plan to recruit around 6,000 new or expectant mothers in WeChat groups in China. To a random subsample, we will show a video that encourages breastfeeding, especially leveraging the fact that incorrect information about breastfeeding during the Corona pandemic is arguably present in China.
External Link(s)
Registration Citation
Citation
Brenøe, Anne et al. 2020. "Breastfeeding and Infant Health." AEA RCT Registry. March 12. https://doi.org/10.1257/rct.5549-1.0.
Experimental Details
Interventions
Intervention(s)
We have three study groups:

1) Intervention: mothers in the intervention group will see a video explaining the beneficial effects of breastfeeding on the infant’s immune system and that health authorities recommend healthy mothers to continue breastfeeding during the current situation with the Corona virus.

2) Active control: The active control group will watch a video that explains how virus spreads and how to prevent contamination.

3) Pure control: The pure control group will not see any video.
Intervention Start Date
2020-03-13
Intervention End Date
2020-04-30
Primary Outcomes
Primary Outcomes (end points)
We have two primary outcomes:
1) A breastfeeding index and

2) An infant illness index
Primary Outcomes (explanation)
We will construct the indexes in the following ways:

1) The breastfeeding index: we construct this index as the average number of times the infant received breast milk during the last 24 hours over four months after the intervention (or during the infant’s first four months of life, in case the mother was still pregnant at baseline), as reported by the mother every three weeks.

2) The infant illness index: we construct this index as a weighted summary index of ten variables (following the approach by Anderson 2008). These 12 variables are constructed based on the weekly answers to the follow up surveys through four months after the intervention (or during the infant’s first four months of life, in case the mother was still pregnant at baseline). They include indicators for any as well as at least two episodes of fever, caught, breathing difficulty chest only, breathing difficulty nose only, breathing difficulty chest and nose, rash, and diarrhea. In case of a symptom being recorded in two consecutive weeks, we will treat this as one episode.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary outcomes will include the two primary outcomes split by 1, 2, 3, and 4 months after the intervention (or by infant age, in case of answers from women who were pregnant at baseline), the individual components of the illness index, measures of infant feeding (frequency of formula and solid food feedings as well as any and exclusive breastfeeding), and maternal mental health.
Secondary Outcomes (explanation)
If we find a statistically significant effect at the 5 percent level of the intervention on our primary breastfeeding outcome, we will further conduct longer follow-up surveys when infants are 6 and 12 months. If we only find a statistically significant effect for certain subgroups, as defined in the secondary heterogeneity analysis, we will conduct these longer follow-up surveys with serious effort to keep attrition rates low in these subgroups, while we will only invite other groups to participate in the survey online with minimal attempt to keep attrition rates low.

In these longer follow-up surveys, we will collect information on child health and development, maternal mental and general health, attachment/bonding between mother and child, labor market outcomes of the mother, support obtained by the mother, parental investment in the child, beliefs about breastfeeding and mental health, and further measures of infant feeding.

If we do not find a statistically significant effect at the 5 percent level of the intervention on our primary breastfeeding outcome for any reasonable subgroup, we will instead of these longer follow-up surveys conduct an extended weekly follow-up survey within six months after the intervention (or before the infant turns 6 months, in case of the pregnant women at baseline). This survey will take 10-15 minutes and ask more detailed into infant feeding, infant health, and maternal physical and mental health.
Experimental Design
Experimental Design
We will run a Randomized Control Trial (RCT) where expectant and new mothers will be randomly assigned to an intervention group or one of two control groups (active control and pure control). Infants who are not currently breastfed will only be assigned to the pure control group. During the baseline survey, we randomize respondents into one of the three study groups and conduct the intervention.

We recruit women through social media and conduct the baseline and weekly follow-up surveys online. When children are 6 and 12 months, we will conduct longer phone interviews.
Experimental Design Details
Starting from mid-March 2020, we will cooperate with approximately 50 internet health organizations to distribute our online survey through their WeChat groups, public WeChat accounts, and public Webo/Blog accounts. Additionally, we will cooperate with around 20 local hospitals to help us distribute the survey. They will print our survey QR code and post in the waiting room and invite people to scan it. If we do not recruit enough participants through the above-mentioned methods, we will pay some consulting company to help us recruit the subjects online.

We recruit participants in groups for expectant and new mothers. Eligible women have a due date by June 30, 2020 or have an infant born on or after October 1st, 2019. If they click on the link that we or our partners post in these groups, they are first directed to the study information and a consent form. If they accept, they are directed to fill in the baseline survey. During the baseline survey, they will randomly be assigned to one of the three study groups. In the following four months, we follow up with weekly short surveys (taking 1-2 minutes). The links to these follow-up surveys are sent through WeChat. In case of non-response three weeks in a row, we will send them a slightly extended survey to ask about the previous month and week instead of only the previous week. For the main sample, we will follow up with a phone interview if they do not answer the extended online survey.

Note, we will follow all infants with the weekly follow-ups for four months. Therefore, we will keep pregnant women in the short follow-up surveys for longer than four months, as we will start counting infant age from their date of birth.

We will run a Randomized Control Trial (RCT) where mothers will be randomly assigned to the intervention group or one of two control groups, stratifying by infant age [1) pregnant, 2) infant <3 months, and 3) infant >=3 months]. Infants who are not currently breastfed will only be assigned to the pure control group. We have one treatment group, one active control group, and one pure control group.

During the baseline survey, mothers in the intervention group will see a cartoon-video explaining the beneficial effects of breastfeeding on the infant’s immune system and that WHO and UNICEF recommend to continue breastfeeding even during the current situation with the Corona virus. The content of the video is designed in collaboration with breastfeeding experts and consultants with the purpose of providing scientifically correct but easy-to-understand information. In the active control group, the video will not mention breastfeeding. Instead, it explains how virus spreads and how to prevent contamination. In the pure control group, no video will be shown.

The main target population consists of women that are about to give birth and women that have just given birth. Since it is difficult to predict both the number of women we are able to recruit and the distribution of their relative closeness to their (predicted) date of birth, we will follow an adaptive design. We will recruit women that are either pregnant in their last trimester or mother of a child that is younger than 6 months old.

If we are able to recruit at least 4,100 women that are either pregnant and within one month of their due date or have given birth within the last two months and are still breastfeeding within the first three weeks after launching the baseline survey, we will use these women as our main sample. We will make an extra effort to keep these women in the follow-up surveys and conduct phone interviews with these women for the longer follow-up surveys, while keeping the longer follow-up surveys as online surveys for the remaining participants. We will refer to this as “1 pregnant & 2 born”.

Otherwise, we loosen the restrictions in the following steps: 1 pregnant & 3 born, 2 pregnant & 3 born, 2 pregnant & 4 born, 2 pregnant & 5 born, 3 pregnant & 5 born, 3 pregnant & 6 born. After each step, we stop if the restrictions allow for at least 4,100 women in the main sample.

Women who are recruited but are not part of the main sample are still useful for our study. However, for financial reasons we will not be able to spend much effort to keep them in the study in case they do not answer the weekly follow-up surveys. Women who have stopped breastfeeding at baseline (and are therefore not part of the main sample) are still useful to keep in the overall study, as they will provide information on the health status of infants who are not breastfed. Moreover, women who are still breastfeeding at baseline but outside our main sample will still help us with power for analysis of heterogeneous effects.

As secondary analysis, we will test whether the effects of the intervention are heterogeneous with respect to the following baseline characteristics:
a) Age of infant: Pregnant, infant less than 3 months, infant at least three months
b) Exclusive vs partial breastfeeding for the sample of women who had given birth and who were still breastfeeding
c) Main breast milk feeding method: at breast vs through other method (e.g. bottle) for the sample of women who had given birth and who were still breastfeeding
d) Parity: first vs second (or higher) born
e) High vs low maternal education (defined by median split)
f) High vs low affected area in terms of the Corona virus based on the their current location (defined by median split)
g) Maternal mental health

Because these are seven dimensions of (potential) heterogeneity, we will account for multiple hypothesis testing.

For further heterogeneity analysis, we will split the sample in two in the following way. We will sort the data by date/time of the reply of the participants. We will then set the seed “123” in Stata and generate a random, uniformly distributed number between 0 and 1 as additional variable. We will use those observation with the additional variable being smaller than 0.4 as the “mining sample”. In the mining sample, we will use Lasso to select a model of heterogeneity. In the rest of the sample, we will then test the selected model. Finally, we will use the causal forest approach and report the best tree of treatment heterogeneity (see Athey & Wager, 2019).
Randomization Method
Randomization done in the survey program online
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
4,100 expectant and new mothers
Sample size: planned number of observations
4,100 expectant and new mothers
Sample size (or number of clusters) by treatment arms
We plan to randomize 44% into treatment, 28% into the active control, and 28% into the pure control.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The target number of 4,100 observations in the main sample comes from power calculations, in which we assume 50% attrition and a minimum detectable effect of 0.15 standard deviations (at the standard 5% type-1-error and 80% power). The total number of observations in the study will naturally be much higher, as we will not include mothers who are not still breastfeeding in the main sample and we will exclude those outside the target age group of their pregnancy/infant. Thus, we report the planned number of observations as 4,100, although we will most likely end up with a much higher number.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Department of Public Economics, Fudan University
IRB Approval Date
2020-02-21
IRB Approval Number
N/A
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS