Databases used in the analysis is freely available (prior registration) in the Demographic and Health Survey Program website: https://www.dhsprogram.com/data/ For this analysis, we used the latest version available (28.01.2018) for Angola, Chad, Ethiopia, Ghana, Kenya, Lesotho, Malawi, Rwanda, Senegal, Tanzania, Bangladesh, Cambodia, Myanmar, Nepal, Guatemala and Armenia. The supplemental .zip archive for this publication contains a generic SPSS syntax file which was created using Version 25. This syntax applies to all databases, since the variables have the same name in the databases of all countries. The name, definition and other detail of the variables is available in the section “Using datasets analysis” at the DHS Program website: https://www.dhsprogram.com/data/Using-Datasets-for-Analysis.cfm In the zip folder is: 1.- SPSS syntax for all the analyses: Syntax_DHS paper ****************************************************************************************************************************************************************************************************************************** ****************************************************************************************************************************************************************************************************************************** To work with the databases you can folow these steps, which are described here: https://dhsprogram.com/data/Using-DataSets-for-Analysis.cfm#CP_JUMP_14037: 1.-Select surveys for analysis. There are different surveys available by country, type of survey, year, search by survey characteristics (for example, surveys that included HIV testing, or the Domestic Violence module), or use the full survey search. 2.- Review questionnaires. Familiarize yourself with the questionnaires used to collect the data that you want to analyze. Model questionnaires are used for each survey phase , but each country modifies the core questionnaire slightly to meet their needs. The questionnaires used to collect data for a specific survey are always included at the back of each survey's final report. All final reports are free to download, and in some cases, can be ordered in hard copy, also for free. Use the questionnaires to determine whether the information you want to analyze was collected in your survey of interest, and who you want to analyze (your unit of analysis). In our paper, we wanted to analyze information collected for everyone listed in the household questionnaire. 3.- Register for dataset access. All DHS datasets are free to download and use. To download datasets, you must complete a short registration form. Remember your username and password; you can use it later to login quickly and register for access to additional datasets. Requests to access datasets are usually approved within 24 hours. You will receive an email from archive@dhsprogram.com once your request has been approved with instructions for download. 4.- Download datasets. Follow instructions from the email you received after registering. Once you log in to dhsprogram.com, you will see the country, survey, and list of datasets that you are approved to download. View the full tutorial on how to download DHS datasets in the video available in:https://youtu.be/Kzv075WRVZA Once you log in to dhsprogram.com, you will see the country, survey, and list of datasets that you are approved to download. The list of Zip files containing datasets are labeled with brief but meaningful names, such as KEIR41DT. The full description of file naming conventions is here, but briefly: -The first two letters ("KE") refer to the country – in this case, Kenya. The country code list is available at: https://dhsprogram.com/data/File-Types-and-Names.cfm#CP_JUMP_10136 In our case we used datasets of: Angola(AO), Chad(TD), Ethiopia(ET), Ghana(GH), Kenya(KE), Lesotho(LS), Malawi(MW), Rwanda(RW), Senegal(SN), Tanzania(TZ), Bangladesh(BD), Cambodia(KH), Myanmar(MM), Nepal(NP), Guatemala(GU) and Armenia(AM). -The second two letters ("IR") refer to the data file type. IR is the individual (women's) recode file, MR is the men's recode, HR is the household recode, etc. In our analysis we used HR files (household) -The next two characters ("41") refer to the phase and number of the survey. If you are only analyzing one survey, all datasets from that survey will have the same numbering. -The last two letters refer to the software program you want to use. The DT file contains the Stata (.DTA) data file and associated documentation; The SV file contains the SPSS (.SAV) file; the SD file contains the SAS (.SAS7BDAT) file; and the FL file contains an ASCII file and dictionaries. The syntaxis code available for this paper was performed in SPSS, so we use the datasets with .sav extension. 5.- Open your dataset in the software you are using for analysis. 6.-Get to know your variables. When your dataset is open, you will see thousands of variables with confusing names and very short variable labels that briefly describe the contents of each variable. To understand each variable and its contents, get to know the DHS recode manual: https://dhsprogram.com/pubs/pdf/DHSG4/Recode7_DHS_10Sep2018_DHSG4.pdf In our analysis we used the following variables: VARIABLE B8 = Current age of the child in single years for all living children. In the DHS VII recode, B8 is based on the CDC of day of interview and date of birth of child and now calculated as ((V008A – B18) / 30.4375) / 12, where 30.4375 = 3625.25 divided by 12 months. Then take the integer part to get completed years. In previous recodes that was calculated as the integer of V008 – B3) / 12. BASE: Living children (B5 = 1). This variable was recategorized in: B8_under5 (where (0=0) (1=1) (2=2) (SYSMIS=SYSMIS) (3 thru 4=3) (5 thru Highest=4) VARIABLE B4 = Sex of child (1= male; 2=female) VARIABLE V025= De facto type of place of residence is a copy of V102, added to this section to allow for analysis of completion rates by urban/rural residence. (1=Urban; 2=Rural) VARIABLE V106= Highest education level attended. This is a standardized variable providing level of education in the following categories: 0=No education, 1=Primary, 2=Secondary, and 3=Higher. We recode this variable V106_dico, considering 0= No education and 1= Primary, Secondary or Higher VARIABLE M4= The duration of breastfeeding of the child in months considering 93= Ever breastfed, not currently breastfeeding; 94=Never breastfed; 95=Still breastfeeding;96=Breastfed until died; 97=Inconsistent;98=Don't know *Note:ever include code 93-95-96. We recode this variable in M4_dico, considering 0=Ever breastfed (codes 93,95 and 96); 1= Never (codes 94,97 and 98) VARIABLES M18= Size of child as reported subjectively by the respondent (1=Very large; 2= Larger than average; 3=Average; 4=Smaller than average; 5=Very small; 6=Don't know We recategorized in variable M18_dico including codes in 1 thru 3=0 (average or larger) and 4 thru 5=1 (smaller than average) VARIABLES V190= Wealth index (1= poorest; 2= poorer; 3=middle; 4=richer; 5= richest) We recategorized this variable in V190_3cat, considering codes 1-2= 1(poor); 3= 2 (Middle) and 4-5=3 (Rich) VARIABLES H34= Whether the respondent received or not a vitamin A dose in form of an ampoule, a capsule or syrup in last 6 months BASE: All living children born in the last five years (B19 < 60 and B5 = 1) Codes 0=no; 1=Yes; 8=don´t know We recategorized this variable in H34_dico, considering codes 0= 0 (no); 1=1 (yes) and 8= missing VARIABLES H43= Drugs for intestinal parasites in last 6 months BASE: All living children born in the last five years (B19 < 60 and B5 = 1) We recategorized this variable in H43_dico, considering codes 0= 0 (no); 1=1 (yes) and 8= missing VARIABLES H2= Whether a date of vaccination was recorded on the health card for BCG. Code 1 means the child has a date recorded for the vaccination. Code 2 is used to indicate that the respondent reported that the child had received the vaccination although the health card was not seen or did not exist, or the vaccination was not recorded on the health card, but was reported by the mother. Code 3 is used to indicate situations where the health card is clearly marked to indicate that the vaccination was given, but no date was recorded on the health card for the vaccination. We recategorized this variable in H2_dico, considering codes 1,2,3= 1(yes);0=0 (no); and 8= missing VARIABLES H9= Measles 1 vaccination. Code 1 means the child has a date recorded for the vaccination. Code 2 is used to indicate that the respondent reported that the child had received the vaccination although the health card was not seen or did not exist, or the vaccination was not recorded on the health card, but was reported by the mother. Code 3 is used to indicate situations where the health card is clearly marked to indicate that the vaccination was given, but no date was recorded on the health card for the vaccination. We recategorized this variable in H9_dico, considering codes 1,2,3= 1(yes);0=0 (no); and 8= missing VARIABLES H7= DPT 3 vaccination. Code 1 means the child has a date recorded for the vaccination. Code 2 is used to indicate that the respondent reported that the child had received the vaccination although the health card was not seen or did not exist, or the vaccination was not recorded on the health card, but was reported by the mother. Code 3 is used to indicate situations where the health card is clearly marked to indicate that the vaccination was given, but no date was recorded on the health card for the vaccination. We recategorized this variable in H7_dico, considering codes 1,2,3= 1(yes);0=0 (no); and 8= missing VARIABLES H8= Polio 3 vaccination. Code 1 means the child has a date recorded for the vaccination. Code 2 is used to indicate that the respondent reported that the child had received the vaccination although the health card was not seen or did not exist, or the vaccination was not recorded on the health card, but was reported by the mother. Code 3 is used to indicate situations where the health card is clearly marked to indicate that the vaccination was given, but no date was recorded on the health card for the vaccination. We recategorized this variable in H8_dico, considering codes 1,2,3= 1(yes);0=0 (no); and 8= missing VARIABLE Full inmunization include children with BCG, DPT3,Polio3 and Measles completed (code 1 in all variables). VARIABLE HW71= Weight for age standard deviation (according to WHO). This variables was recategorized in variable HW71_underweight2D. Codes 9996, 9997 and 9998 were considered missing and Values lowest thru -201 were considered underweight. VARIABLE HW72= Weight for height standard deviations (according to WHO) This variables was recategorized in variable HW72_stunting2D. Codes 9996, 9997 and 9998 were considered missing and Values lowest thru -201 were considered stunting. VARIABLE HW73= BMI standard deviations (according to WHO) This variables was recategorized in variable HW72_waisting2D. Codes 9996, 9997 and 9998 were considered missing and Values lowest thru -201 were considered waisting. 7.- Use sample weights. DHS sample weights were used in all tabulation in our paper. As recommended by DHS program we used variable V005 to generate weight conidering: In SPSS: COMPUTE WGT = V005/1000000. WEIGHT by WGT. All frequencias and logistic regression models considered complex samples weighting analysis by WGT. ********************************************************************************************************************************************************************************