Mapping exclusive breastfeeding in Africa between 2000 and 2017

Exclusive breastfeeding (EBF)—giving infants only breast-milk (and medications, oral rehydration salts and vitamins as needed) with no additional food or drink for their first six months of life—is one of the most effective strategies for preventing child mortality1–4. Despite these advantages, only 37% of infants under 6 months of age in Africa were exclusively breastfed in 20175, and the practice of EBF varies by population. Here, we present a fine-scale geospatial analysis of EBF prevalence and trends in 49 African countries from 2000–2017, providing policy-relevant administrative- and national-level estimates. Previous national-level analyses found that most countries will not meet the World Health Organization’s Global Nutrition Target of 50% EBF prevalence by 20256. Our analyses show that even fewer will achieve this ambition in all subnational areas. Our estimates provide the ability to visualize subnational EBF variability and identify populations in need of additional breastfeeding support.


Supplementary
For all data inputs from multiple sources that are synthesized as part of the study: 3 Describe how the data were identified and how the data were accessed.
Methods: Data extraction and processing section 4 Specify the inclusion and exclusion criteria. Identify all ad-hoc exclusions.
Methods: Data extraction and processing section; Supplementary Tables  4-6  5 Provide information on all included data sources and their main characteristics. For each data source used, report reference information or contact name/institution, population represented, data collection method, year(s) of data collection, sex and age range, diagnostic criteria or measurement method, and sample size, as relevant.
Extended Data Figure 5; Supplementary Tables 2  and 3 6 Identify and describe any categories of input data that have potentially important biases (e.g., based on characteristics listed in item 5).
Methods: Data extraction and processing and Data Accuracy sections For data inputs that contribute to the analysis but were not synthesized as part of the study: 7 Describe and give sources for any other data inputs. Supplementary Table 6 For all data inputs: 8 Provide all data inputs in a file format from which data can be efficiently extracted (e.g., a spreadsheet rather than a PDF), including all relevant meta-data listed in item 5. For any data inputs that cannot be shared because of ethical or legal reasons, such as third-party ownership, provide a contact name or the name of the institution that retains the right to the data.
Methods: Data extraction and processing section 10 Provide a detailed description of all steps of the analysis, including mathematical formulae. This description should cover, as relevant, data cleaning, data pre-processing, data adjustments and weighting of data sources, and mathematical or statistical model(s).
Methods: Data extraction and processing and Statistical analysis sections 11 Describe how candidate models were evaluated and how the final model(s) were selected.
Methods: Statistical analysis section 12 Provide the results of an evaluation of model performance, if done, as well as the results of any relevant sensitivity analysis.
Methods: Statistical analysis section

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Describe methods for calculating uncertainty of the estimates. State which sources of uncertainty were, and were not, accounted for in the uncertainty analysis.

Methods: Statistical analysis and Limitations sections 14
State how analytic or statistical source code used to generate estimates can be accessed.

Results and Discussion 15
Provide published estimates in a file format from which data can be efficiently extracted.
Main text; Methods: Statistical analysis section; Figure 1f  17 Interpret results in light of existing evidence. If updating a previous set of estimates, describe the reasons for changes in estimates.

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Discuss limitations of the estimates. Include a discussion of any modelling assumptions or data limitations that affect interpretation of the estimates.

Methods: Limitations section
Supplementary For each modeling region, the following parameters are reported: intercept ( 0 ), regression coefficients ( 1 ) corresponding to the three submodels (generalised additive model (GAM), boosted-regression trees (BRT), and Lasso), nominal range, nominal variance, precision for countrylevel random effects ( ), precision for independent and identically distributed nugget (uncorrelated error term) effect ( ), and hyperparameter ( ) for the temporal first-order autoregressive (AR1) covariance function at 2.5 th , 50 th and 97.5 th quantiles. For each model configuration, the following metrics are reported: mean error (ME (percentage points)), root-mean-square error (RMSE (percentage points)), and 95% prediction interval coverage ("coverage" (%)). *These models were chosen as our final models based on results from sensitivity analyses. 20 25