There is a simple reason why national health surveys matter for children, and it has nothing to do with statistics.
A hospital record only contains children who made it to the hospital. A vaccination register only counts the children who showed up. Every administrative dataset in a health system shares this quiet bias: it sees the people the system already touched. The child who was never brought in, whose asthma was never diagnosed, whose emotional difficulties were never named, does not exist in these records.
National health surveys work the other way around. They knock on doors. Their sampling frame is the household, not the clinic, which means they reach the child who never entered the system at all. That single design feature is what makes them the only reliable way to measure unmet need, hidden illness, and the real distance between a population and the services meant to serve it.
This matters more than it sounds. When researchers used Pakistan’s national health survey to measure childhood injuries, they found that hospital-based records had been systematically undercounting the burden (Fatmi et al., 2009). When Australian researchers used survey data to map breastfeeding rates by state and socioeconomic status, they revealed a social gradient that routine birth records had never shown (Donath & Amir, 2000). In both cases the survey did not just add precision. It changed the picture.
What thirty-six years of research looks like
To understand how this body of work has developed, I assembled a corpus of 183 peer-reviewed articles from the Web of Science Core Collection, spanning 1990 to 2026, all using national health survey data to study child and adolescent health. Together they have accumulated 3,431 citations.
The growth pattern is uneven in an interesting way. The 1990s produced eleven articles. The 2000s produced thirty-nine. The 2010s produced sixty-five, and the years since 2020 have already produced sixty-eight. More than two-thirds of everything ever published in this space appeared after 2010.
That surge has less to do with intellectual breakthroughs than with plumbing. Statistical agencies loosened their microdata policies. Open-access publishing expanded, and a hundred of the 183 articles are now openly available. Software capable of handling complex survey designs became routine rather than specialist. When the barriers dropped, the research followed.
The map has a very large blank space
The geography of this literature is startlingly concentrated. Spain accounts for 140 institutional records in the corpus, far ahead of Indonesia (34), Australia (31), Brazil (31), Serbia (31), Iran (30) and Mexico (25). Spain’s dominance has a clear explanation: its national health survey has run on a regular cycle since 1987, it carries a dedicated child questionnaire, and its microdata is genuinely accessible to researchers. Spanish teams have used that single infrastructure to study adolescent physical activity (Lasheras et al., 2001), childhood obesity (Pizarro & Royo-Bordonada, 2012), mental health difficulties (Ortuño-Sierra et al., 2018) and the relationship between screen time and sleep (Cartanyà-Hueso, Lidón-Moyano et al., 2021). One well-maintained dataset, three decades of questions.
Now the uncomfortable part. I searched the titles, abstracts, author addresses and keywords of all 183 articles for any trace of Türkiye. There is none. Not one study.
This is not a data problem. Türkiye runs the Turkey Health Survey on a two-year cycle, with two separate child questionnaires split by age (Turkish Statistical Institute, 2023). It runs the Turkey Demographic and Health Survey roughly every five years, with anthropometric measurement, immunisation, breastfeeding and child nutrition modules (Hacettepe University Institute of Population Studies, 2019). The infrastructure exists, it is maintained, and it collects most of what the international literature asks about. It is simply not being used to produce internationally visible child health research.
The same holds across the wider Middle East and North Africa region, which appears in the corpus mainly through a handful of Iranian growth-reference studies.
Four things this literature keeps not doing
Reading 183 papers with an eye for what is absent rather than present, four gaps stand out.
The first is about survey design. National surveys are stratified and clustered, and every respondent carries a sampling weight. Ignoring that structure does not just make estimates slightly imprecise; it makes confidence intervals artificially narrow, which makes findings look more certain than they are. Only twenty-one of the 183 articles explicitly report handling this. That is roughly one in nine.
The second is about time. Most of these surveys repeat the same questions across multiple waves, which means the raw material for trend analysis is sitting there. Only twelve articles used it. Those that did produced some of the most useful work in the corpus, such as the tracking of severe obesity in Australian children from 1985 to 2012 (Garnett et al., 2016) and the analysis of how socioeconomic inequality in children’s dental access changed in Spain between 1987 and 2011 (Pinilla et al., 2015).
The third is about inequality. Fifty-seven articles talk about inequality, socioeconomic difference or social determinants. Three of them actually measure it with a formal tool such as a concentration index or a decomposition analysis (Gonzalo-Almorox & Urbanos-Garrido, 2016; Quintal & Oliveira, 2017; Wariri et al., 2019). The distinction matters practically, not just technically. Knowing that inequality exists justifies acting. Knowing which component it comes from tells you where to act.
The fourth is about cost. Exactly one study in the entire corpus performs an economic evaluation (Guo et al., 2021). National surveys routinely collect data on service use, out-of-pocket spending and insurance coverage. The absence here is not a limit of the data. It is a limit of the questions being asked.
Behind all four sits a fifth pattern. Sorting the corpus by Web of Science category gives ninety-four records under public health, twenty-six under paediatrics, twelve under health services research, eight under health policy and three under economics. Evidence is being produced in abundance. It is not being translated into the language of decisions.
What Türkiye could ask tomorrow
The point of mapping a literature is not to complain about it. It is to work out what to do next.
In a new technical report, I turned each thematic cluster in the corpus into a research question that could be tested with Turkish data, then assessed each one for feasibility. Four questions can be answered with existing data as it stands today.
How large is income-related inequality in childhood overweight and obesity in Türkiye, and how much of it is attributable to household income, parental education, region and dietary behaviour? How common is unmet health care need among children, how does it split between financial, geographic and waiting-time causes, and how has that changed across survey waves? What is the dropout rate between the first and final doses in the childhood immunisation schedule, and which household characteristics predict it? How does the double burden of stunting and overweight among under-fives distribute across socioeconomic and regional gradients?
Three further questions are partially feasible and would benefit from small additions to future survey modules, covering adolescent mental health service contact, adherence to twenty-four-hour movement guidelines, and the combined burden of preventable outcomes such as oral health problems, unintentional injury and secondhand smoke exposure.
None of these requires new fieldwork. None requires a grant to collect data. They require someone to open the microdata files, apply the survey design correctly, and ask a question that a health manager could actually act on.
That is a low barrier. The fact that it has not yet been crossed is the most interesting finding in the whole exercise.
The full technical report, including the comparative anatomy of national survey infrastructures and the complete prioritised research agenda, is available on ResearchGate.
References
Cartanyà-Hueso, A., Lidón-Moyano, C., Martín-Sánchez, J. C., González-Marrón, A., Matilla-Santander, N., Miró, Q., & Martínez-Sánchez, J. M. (2021). Association of screen time and sleep duration among Spanish 1-14 years old children. Paediatric and Perinatal Epidemiology, 35(1), 120-129. https://doi.org/10.1111/ppe.12695
Donath, S., & Amir, L. H. (2000). Rates of breastfeeding in Australia by state and socio-economic status: Evidence from the 1995 National Health Survey. Journal of Paediatrics and Child Health, 36(2), 164-168. https://doi.org/10.1046/j.1440-1754.2000.00486.x
Fatmi, Z., Kazi, A., Hadden, W. C., Bhutta, Z. A., Razzak, J. A., & Pappas, G. (2009). Incidence and pattern of unintentional injuries and resulting disability among children under 5 years of age: Results of the National Health Survey of Pakistan. Paediatric and Perinatal Epidemiology, 23(3), 229-238. https://doi.org/10.1111/j.1365-3016.2009.01024.x
Garnett, S. P., Baur, L. A., Jones, A. M. D., & Hardy, L. L. (2016). Trends in the prevalence of morbid and severe obesity in Australian children aged 7-15 years, 1985-2012. PLOS ONE, 11(5), Article e0154879. https://doi.org/10.1371/journal.pone.0154879
Gonzalo-Almorox, E., & Urbanos-Garrido, R. M. (2016). Decomposing socio-economic inequalities in leisure-time physical inactivity: The case of Spanish children. International Journal for Equity in Health, 15, Article 106. https://doi.org/10.1186/s12939-016-0394-9
Guo, Y., Yang, Y., Bai, Q., Huang, Z., Wang, Z., Cai, D., Li, S., Man, X., & Shi, X. (2021). Cost-utility analysis of newborn hepatitis B immunization in Beijing. Human Vaccines & Immunotherapeutics, 17(4), 1196-1204. https://doi.org/10.1080/21645515.2020.1807812
Hacettepe University Institute of Population Studies. (2019). 2018 Turkey Demographic and Health Survey. Hacettepe University Institute of Population Studies.
Lasheras, L., Aznar, S., Merino, B., & López, E. G. (2001). Factors associated with physical activity among Spanish youth through the National Health Survey. Preventive Medicine, 32(6), 455-464. https://doi.org/10.1006/pmed.2001.0843
Ortuño-Sierra, J., Aritio-Solana, R., & Fonseca-Pedrero, E. (2018). Mental health difficulties in children and adolescents: The study of the SDQ in the Spanish National Health Survey 2011-2012. Psychiatry Research, 259, 236-242. https://doi.org/10.1016/j.psychres.2017.10.025
Pinilla, J., Negrín-Hernández, M. A., & Abásolo, I. (2015). Time trends in socio-economic inequalities in the lack of access to dental services among children in Spain 1987-2011. International Journal for Equity in Health, 14, Article 9. https://doi.org/10.1186/s12939-015-0132-8
Pizarro, J. V., & Royo-Bordonada, M. A. (2012). Prevalence of childhood obesity in Spain: National Health Survey 2006-2007. Nutrición Hospitalaria, 27(1), 154-160. https://doi.org/10.3305/nh.2012.27.1.5414
Quintal, C., & Oliveira, J. (2017). Socioeconomic inequalities in child obesity and overweight in Portugal. International Journal of Social Economics, 44(10), 1377-1389. https://doi.org/10.1108/IJSE-11-2015-0291
Turkish Statistical Institute. (2023). Turkey Health Survey, 2022. Turkish Statistical Institute.
Wariri, O., Edem, B., Nkereuwem, E., Nkereuwem, O. O., Umeh, G., Clark, E., Idoko, O. T., Nomhwange, T., & Kampmann, B. (2019). Tracking coverage, dropout and multidimensional equity gaps in immunisation systems in West Africa, 2000-2017. BMJ Global Health, 4(5), Article e001713. https://doi.org/10.1136/bmjgh-2019-001713