Well, among many other considerations, you will need to look at the care practices of the different communities you are working with. For example, when I was in Niger in 2007 doing SMART surveys, I found that one area had significantly higher AM rates among boys than girls compared to another one. It took a few community meetings to find out that the Tuareg community had a tradition of sending boys to live with their grandparents if the mother became pregnant again, but not girls, who would remain with their mothers. Those boys were not fed equally at the grandparent's place as girls would be at their own home, and therefore the AM rates where higher among males. The Haousa people would instead give priority to boys at the HH as they were bound to become the ones working harder in the fields, the income generators for the HH, and so most of them were better off than their sisters, who were last in the queue for the family meal. The range of reasons will vary a lot depending on these cultural practices, socio-economic status and even the period of the year, so one of the actions you need to take to determine the reasons for such results is investigate local practices and attitudes towards infant and young child feeding, with a properly tailored KAP survey for instance. There are many other considerations which I am sure other colleagues will be able to share here.

Well,I think we need to look to the currently running nutritional programs to evaluate SAM M:F ration differences.The coverage of the program must be taken into consideration.If we are sure that our program is reaching population and everyone has access to it,then we should see the number of screened children(M:F) and evaluate the representativeness. Some possible reason is that the girls may not attend the centers for screening in comparison to the boys,this issue should be investigated through CHVs at their respective communities.Social/Cultural factors also play a role. You can scam through morbidity indicators among under 5 ,recent SMART and SQUEAC,to see sex differences,this could help to understand.

Also it could partly related to the use of the WHO reference table. This table is based on how children in different populations grow when being in favorable circumstaces. This meas often middle class and higher. In many populations middle class like boys to look wealthy and girls to look active. This could be the source of the discrepancy between boys and girls in the reference table, and thus in your analysis, specifically when the situation is borderline.

I think these are all good suggestions. You may need to investigate as suggested probably aiming do inform the design of a case-control study. The suggestion of a problem with the criteria for inclusion for WGS reference (leading, as stated) to a reference dominated by children middle and upper classes and from developed countries is an intriguing. You can see if this is an issue by seeing if the difference persists when you define "wasting" using MUAC (a far better indicator than WHZ for many reasons). You might also look to see if there are many borderline WHZ cases. Also, does the difference persist if you look at WHZ < -3 (i.e. SAM by WHZ) cases and is the difference due to differences in oedema prevalence. I have seen this in adults in famines (males suffering more often and more severely from oedema. I'd also look to difference in age between boys and girls. You may find (e.g.) that you have a deficit of older boys who may play further from home and be missing from the sample - probably not the case given the sex-ratio but worth a look. I'd do these sorts of re-analysis before embarking on further investigation. I hope this is of some use.

Whenever we have looked at undernutrition prevalence in household survey data we have found higher prevalences in boys vs. girls, even if not statistically significant. Most of the survey data we have collected and looked at is from emergency affected populations in Africa, so those more used to looking at Asian data may see different patterns. But as a general observation, the nutritional status of boys is usually worse than girls or the same as girls, when assessed using either the WHO 2006 Growth Standards, or the previously used NCHS/WHO international growth reference. One slightly intriguing aspect of this is that people are often surprised by this when they look at actual data. The available evidence just does not support much of the gender and nutrition narrative, expounded by international agencies and policy makers; yet this narrative persists and is rarely challenged. Of course, there may be issues with the construction of the growth curves leading to a gender bias, and/or girls may often be better protected then boys due to poorly described or understood social factors, or physiological vulnerabilities. Lots more to understand. But the current data is what it is. An interesting WHO publication on gender and stunting in Africa (boys being more stunted than girls) can be found here: [url]http://www.who.int/gho/health_equity/outcomes/stunting_children_text/en/[/url] Would be great if someone has a reference on a large scale analysis of wasting by gender to add to the discussion (or get published)?

Very interesting stuff. Just to address your last paragraph. This is something that could be done with the data collected for the oedema mapping project (after getting permissions from the data providers). This is currently about 1700 smart-type surveys with data on well over a million children from about 50 countries collected over 20+ years. The database creation phase is not yet complete and we expect a 25% growth over the next few months. A simple and well specified analysis could be part of a student (MSc) research project (dealing with huge datasets and with "found" data both have some interesting challenges). I cannot promise access but I am sure that ICH could negotiate access.

Thanks for that idea Mark. To give it a bit of spin I guess we could call that Big Data.

We should probably, I think pursue this idea outside of this forum. A reasonable "spin" is big data. It is not "data mining" (a technique associated with big data) but the issues are similar. We'd want (e.g.) to use effect size estimates rather than statistical hypothesis testing (at n = 1,t00,000 any difference we see will likely be "statistically significant" no matter how small they are) to avoid "false discovery". We also have the problem of "self-selection" (not quite the right term) in that much of the data is from surveys in settings and at times when humanitarian actors are present. It is (to coin a phrase) "données trouvé" (found data). This is also an issue with data-mining. I think this will make quite an interesting student project. If this goes ahead, I'd be happy to provide support on a pro bon publico basis.

The issue raised around this difference between boys and girls will really need further investigations as suggested earlier, in many comminities like in South Sudan, this observation is valid but in some communities the culture norms are in favour of boys than girls when it comes to care and food parrerns yet the surveys show a complete different figure. Furthermore, the admission trends in current programming for treating AM has highlighted that many girls are being admitted in the program than boys but this does not says that girls are more malnourished than girls... We know the sex ration is slightly different for these two gender/age group but it could be the fact that girls are more available in their home that boys or any other reasons....

FSNAU data for Somalia shows that the prevalence of GAM was higher in boys of both 6-23 months and 24-59 months compared to girls in different livelihood zones of Somalia . The gender difference in GAM prevalence were statistically significant among agro pastoral, pastoral and IDPs. In the Riverine livelihoods, gender differences were statistically significant only among older children ( 24-59 months) . The likelihood of boys to continue showing high GAM compared to girls is almost twice (this is per the risk reduction ratio percentage) Just like GAM, among children aged (6-23 and 24- 59 months) boys exhibited higher SAM prevalence compared to girls among pastoral, agro pastoral, riverine, and IDPs Similar observations are made by FSNAU in all the nutrition assessments conducted over last 5 yrs

Currently we are implementing a BCC project in Nutrition in Somalia in Sanaag Region and before embarking on the project we did a nutrition survey in Dec 2014 to understand the nutrition situation we had a total of 432 children between 6-59 months, of which 209 were boys and 223 were girls. the GAM rate in the boys was slightly higher 12.9% and girls 12.6%,for MAM the boys were also sightly higher 11% while girls were 10.3% but in SAM the girls were slightly higher 2.2% and boys 1.9%. In my conclusion i would say in cases of severe acute malnutrition girls are more likely to suffer more than boys but these needs further studies to find out and document the probable reasons.