NGA_2018-2019_CMAM_v01_M
Incidence of Severe Acute Malnutrition After Treatment: A Prospective Matched Cohort Study in Sokoto, Nigeria 2018-2019
Name | Country code |
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Nigeria | NGA |
Other Household Health Survey [hh/hea]
Sample survey data [ssd]
V1.1: Edited, anonymous dataset for public distribution
2021-07-22
Version 1.1 consists of five edited and anonymised datasets with the responses to a small number of questions removed; these were removed for confidentiality purposes or because they were not needed for the analysis. Some of the datasets also contain selected constructed indicators prefixed by n_. These constructed indicators are included to save data users time as they require complex reshaping and extraction of data from multiple sources (but they could be generated by data users if preferred).
Topic | Vocabulary |
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Nutrition |
This study took place in five rural local government areas (LGAs) in Sokoto State in Northern Nigeria.
Name |
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Oxford Policy Management Ltd. |
Name | Role |
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Valid International | Support in research design and analysis |
Name |
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Children’s Investment Fund Foundation |
Name | Affiliation | Role |
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United Nations Children's Fund Nigeria | UNICEF | Support in research implementation |
This prospective matched cohort study was conducted in five rural local government areas (LGAs) in Sokoto State, northern Nigeria. Nine out of the 23 LGAs in Sokoto State hosted the CMAM program. Of these, four were excluded because they were either hosting another study looking at improving CMAM delivery, were peri-urban, or not easily accessible. In the selected five LGAs, the CMAM program had been running since 2010 and was being implemented throughout the study period. Within each LGA, five health facilities were hosting the CMAM program, and the study covered this exhaustive list of 25 health facilities (i.e. there was no sampling of health facilities within LGAs, all health facilities that were hosting the CMAM program in each LGA were included in the study).
The study followed two cohorts of subjects:
Exclusion criteria for both cohorts of children for enrolment into the study included:
· Presence of disability or any congenital disease (after clinical examination) that affects growth or prevents accurate anthropometric measurement and/or prevents the child from eating normally;
· A sibling already enrolled into the study;
· The biological mother of the child having passed away; or
· Having a mother <15 years old.
Note that children were not sampled. Rather:
The sample size determination was based on the relapse rate as the principal outcome variable.
The minimum sample size required for this study was calculated to be 500 OTP-cured and 500 community control children across the 25 facilities. This sample size would allow us to detect a 4% point difference in SAM incidence between both cohorts of children with 95% confidence. Calculation parameters were chosen conservatively and assumed an incidence of SAM among community controls of 1%, a total number of 25 clusters (health facilities), a coefficient of variation of cluster sizes of 0.9, and an intra-cluster correlation of 0.02. Sample size calculations were implemented using the clustersampsi tool in Stata.
With an anticipated loss to follow-up of 20%, the study therefore aimed to recruit 600 children per cohort.
It is important to emphasise that the two cohorts of children included in this study are not necessarily representative of the overall population of children in Northern Nigeria or even Sokoto State. On the one hand, children from the OTP-cured cohort were recruited from health facilities in a purposefully selected set of LGAs within that state. Given the way that they were recruited, they do represent a census of OTP-cured children from those health facilities that were discharged as cured during the recruitment phase of this study and that were eligible for the study. However, the level of representativeness beyond that group is unclear. Community control children, on the other hand, were selected using snowball sampling, which essentially implies purposeful sampling within visited communities. Hence, generalising findings beyond the two groups covered in the study should only be done with care.
Therefore, the sample size of the study (and consequently the number of observations of the published data) consists of 553 OTP-cured children and 526 community control children.
In terms of the outcomes of children at the end of the study:
The collected data does not have any sampling weights. This is due to the nature of child selection, whereby all children that were discharged as cured during the study's recruitment period and were eligible were invited to participate in the study.
This cohort study was implemented in several phases that took place sequentially, and that included recruitment of OTP-cured children, recruitment of community control children, first home visit (to collect baseline characteristics), and subsequent follow-up home visits. At each phase, different questionnaires were administered.
At each health facility, a CMAM day is held once a week, rotating through all facilities per LGA so that no two facilities within an LGA have a CMAM day on the same day per week. Children who are enrolled in the CMAM programme and their caregivers attend CMAM days for check-ups and treatment. This study recruited OTP-cured children at these CMAM days, identifying children who were discharged as cured.
The data collection timeline was as follows:
OTP-cured children were recruited at health facilities on a rolling basis between September and November 2018. There, the study team screened all children who had been discharged as cured on that day for eligibility and consent to participate in the study. This meant enrolling children as they were successfully discharged from the CMAM programme in the 25 health facilities that formed part of this study. At each CMAM day and health facility, teams of two interviewers were present throughout the day to ensure that all children discharged from the programme on that day were screened for possible enrolment into the study and recruited if eligible up until the minimum sample size is reached.
Following recruitment into the study, each OTP-cured child was tracked to their community and visited at their home within 2 to 3 weeks of their initial recruitment. Field teams used the information collected at recruitment to locate children in their community. Most communities were accessed either on foot or by motorcycle. This constituted the first home visit where a long baseline questionnaire was administered.
Immediately after the first home visit of each OTP-cured child, a search for a suitable community control for that child was conducted. For each OTP-cured child, potential community controls were identified using a snowball approach. In essence, this approach meant that interviewers were referred to potential community control children by the mother of the OTP-cured child. Potential community controls were assessed with respect to their eligibility to enter the study and to whether they matched the corresponding OTP-cured child on a set of criteria (mentioned in the sampling section). The first community control to meet both sets of criteria was recruited into the study and the search for a community control for a given OTP-cured child ended at that stage. Once a control child was identified, the same first home (baseline) questionnaire was administered to the household and mother of that child.
Afterwards, both cohorts were followed-up fortnightly for a total of 12 home visits (the 12 visits includes the first baseline home visit).
Participation in the study for both cohorts ended at the 12th home visit, unless a child developed SAM earlier or dropped out of the study (e.g. family no longer consented to participate in the study or moved out of the community, or child had died), whichever came first. In total, children were followed up for a duration of up to six months after discharge from OTP. Within the six months of follow-up, if children were identified as being SAM by the field team, they proceeded to exit the study and interviewers referred those children to CMAM services.
There were a number of questionnaires that were used for this study.
A recruitment questionnaire for OTP-cured children was administered to the mother of the child on the day children were discharged and recruited into the study. This questionnaire assessed eligibility of the child and collected some information to help with locating the home of the child.
Additionally, data on children's health status at admission and discharge from the OTP were also collected from registration and treatment tracking cards kept at the facility by staff (OTP cards and Ration cards). This data was scanned on enumerator's tablets and later on entered into a database by data entry staff. Information that was entered from these records included anthropometric measurements and morbidity at admission, duration of treatment and anthropometric measurements at each visit to the OTP. Note that data from the scanned OTP and Ration cards has not been uploaded for public use due to data quality concerns. The data suffers from many missing observations, given that this data was not directly collected by the enumerators but relied on health facility staff filling in the OTP and Ration cards for the treated children.
During this phase, a health facility questionnaire was also administered in each health facility to assess adherence of the health facility to the Nigeria CMAM national guidelines and availability of OTP-related drugs and equipment and the general quality of infrastructure and resources. The survey also collected data on shocks that affected the catchment area of facilities in the year prior to the survey, such as drought, floods, sandstorms, and security-related events. In each health facility, this survey was administered once, on the first day the interview team visited the health facility. The survey used direct observation as well as interviews with the head of the health facility and the CMAM focal person in charge. If either of these individuals were not available on the day, other knowledgeable health facility member was asked to respond to the questions.
A recruitment questionnaire for community control children was administered to the mothers of the children to assess eligibility and matching criteria and decide if they can be recruited.
At the first home visit, a long baseline questionnaire was administered to the mother of the recruited child and the household head to collect baseline information across several domains related to the child, mother, and household. Children's MUAC was measured using the WHO/UNICEF-recommended MUAC tape and measurement protocol, whereas height and length were measured with a precision of 0.1 cm, using boards manufactured by SECA: standing boards for children who were able to stand and lying-down boards for children unable to. The domains included in the baseline questionnaire include:
At each follow-up home visit, a short follow-up questionnaire was administered to the mother of the child to collect child-level co-morbidity data in the 2 weeks preceding the visit (a subset of the questions asked in the baseline questionnaire) and to measure the child's MUAC.
In the final follow-up visit (i.e. the visit when the child exited the study either because they developed SAM or if they reached the final 12th visit), additional questions were asked of the household including on mother's employment status, changes in the breastfeeding and pregnancy status of mothers, deaths in the household, household food security, child feeding, household and child dietary diversity, and mother's feeding knowledge and practices. These questions were a subset of those asked in the baseline questionnaire and they were added in order to understand if household, mother, or child conditions assessed at the first home visit might have changed at the point of exit. Note that these additional questions were not asked of children who dropped out of the study (because the interviewers would not have known that the previous visit was going to be the final exit visit).
All questionnaires were administered using the Computer-Assisted Personal Interviewing software CSPro (Version 7.1.3), and OTP and Ration cards were scanned and data entered digitally using the SurveyCTO software. Questionnaires were translated into Hausa and administered to all respondents in Hausa.
SAM was determined using the WHO and national MUAC criteria of MUAC <115 mm. Given that this study's objective was to identify definite relapses and cases of SAM that would require treatment, we classify a child as having SAM if his/her MUAC =112 mm at any home visit or if his/her MUAC is between 112 and 115mm for two consecutive visits. The reason we do this is to account for the possibility of measurement error, i.e. it is difficult to identify whether children around the 115mm MUAC cut-off temporarily dip into SAM or whether they are a certain SAM case that requires treatment.
Survival analysis techniques can be used to analyse the data.
An important point to emphasise is that for OTP-cured children there was a lag of up to three weeks between their recruitment at the health facility and the first visit at home (where we collected baseline data). Some children had already relapsed into SAM at the first home visit before additional data on these children could be collected. For those children who relapsed between recruitment and the first home visit, it would therefore not be possible to assess whether certain time-varying characteristics collected at the first home visit - e.g. child-level health indicators - materialised as a consequence of relapse or prior to relapse. This is a limitation and could present implications for data analysis, depending on the type of analysis the users of the data wish to conduct. Specifically, it is important for the analysis not to suffer from endogeneity if for instance users are interested in assessing the effect of certain factors on relapse rates. There are options to deal with this limitation, for instance, i) limiting the analysis to the factors/covariates that could reasonably be assumed to be time-invariant between recruitment and the first home visit, or ii) defining the time origin for OTP-cured children as the first home visit (as opposed to their recruitment from the health facility) and restricting the analysis to the subsample of children that had not relapsed into SAM at the first home visit (though this option would entail a significant reduction in sample size).
Start | End |
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2018-09-03 | 2019-05-31 |
Name |
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Oxford Policy Management |
Several data quality assurance mechanisms were implemented to ensure data quality throughout the survey:
A number of pre-tests were conducted in Sokoto state during 2018 to test the instruments and protocols. A team of core nutrition and survey specialists and experienced survey supervisors visited facilities and households. The objectives of the pre-tests were to:
This study met the ethics criteria of the Sokoto State Health Research Ethical Committee and approval was received on 12 March 2018.
Verbal informed consent was sought and recorded in the questionnaire from mothers during recruitment of children into the study and from household heads at the first home visit. Consent was sought again from households at each follow-up visit. All children who experienced SAM during the study were referred to the nearest OTP services.
Before data collection was conducted, training was organised for the interviewing teams and included a mix of in-class training and piloting. Two trainings were organised: one for the recruitment phase and one for the home visits phase. The main objective of the training was to ensure that the data collection teams mastered the questionnaires, could measure MUAC accurately and implement the survey protocol, and were comfortable using CAPI.
Classroom training for the recruitment phase was structured following the recruitment and health facility questionnaire: for each module a brief introduction was delivered, then each module question explained, and finally a mock interview between trainees took place. The training ended with a two-day piloting exercise to practice using the instruments and protocols.
Similarly, classroom training for the home visits phase was structured to follow the long household questionnaire: for each module a brief introduction was delivered, then each module question explained, and finally a mock interview between trainees took place. A full day of training was dedicated to MUAC measurement and young children from Sokoto were invited for in-class practice. The training ended with a two-day piloting exercise to further familiarise trainees with overall survey instruments and protocols.
A central component of quality assurance was the supervision and feedback that each enumerator received during the training, piloting, and roll-out of the study. At the beginning of every training day, the trainees had to complete a test on the modules covered the previous day and individual feedback was provided daily to identify and resolve any challenges faced by the interviewing team.
Team supervisors were selected from among the most experienced and best-performing participants, and these individuals completed an additional training module for the extra tasks of coordination and quality assurance.
Given the data was electronically collected, it was continually checked, edited and processed throughout the survey cycle.
A first stage of data checking was done by the survey team which involved
(i) checking of all IDs;
(ii) checking for missing observations;
(iii) checking for missing item responses where none should be missing; and
(iv) first round of checks for inadmissible/out of range and inconsistent values.
Additional data processing activities were performed at the end of data collection in order to transform the collected cleaned data into a format that is ready for analysis. The aim of these activities was to produce reliable, consistent and fully-documented datasets that can be analysed throughout the survey and archived at the end in such a way that they can be used by other data users well into the future. Data processing activities involved:
The datasets were then sent to the analysis team where they were subjected to a second set of checking and cleaning activities. This included checking for out of range responses and inadmissible values not captured by the filters built into the CAPI software or the initial data checking process by the survey team.
A comprehensive data checking and analysis system was created including a logical folder structure, the development of a detailed data analysis guide and template syntax files (in Stata), to ensure data checking and cleaning activities were recorded and that all analysts used the same file and variable naming conventions appropriately.
Name | URL | |
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Oxford Policy Management | http://www.opml.co.uk/ | admin@opml.co.uk |
The datasets have been anonymised and are available as a Public Use Dataset. They are accessible to all for statistical and research purposes only, under the following terms and conditions:
The original collector of the data, Oxford Policy Management Ltd, and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Oxford Policy Management. Incidence of Severe Acute Malnutrition After Treatment: A Prospective Matched Cohort Study in Sokoto, Nigeria, Version 1.1 of the public use dataset (November 2021). Ref: NGA_2018-2019_CMAM_v01_M. Downloaded from [url] on [date].
The user of the data acknowledges that the original collector of the data, the authorised distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
(c) 2021, Oxford Policy Management Ltd.
Name | URL | |
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Oxford Policy Management | admin@opml.co.uk | http://www.opml.co.uk/ |
DDI_NGA_2018-2019_CMAM_v01_M
Name | Affiliation | Role |
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Ngowi, Abraham | Oxford Policy Management Ltd. | Documentation of the study |
Harb, Jana | Oxford Policy Management Ltd. | Data analyst |
2021-11-17
Version 1.1 (November 2021)
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