NSCH Crosswalk provides a view of all survey changes since 2016.
2021
- Household Screener (PDF - 1.2 MB) | Spanish (PDF - 1.2 MB)
- Topical Questionnaire (Children, 0-5 years) (PDF - 1.2 MB) | Spanish (PDF - 1.3 MB)
- Topical Questionnaire (Children, 6-11 years) (PDF - 771 KB) | Spanish (PDF - 873 KB)
- Topical Questionnaire (Children, 12-17 years) (PDF - 742 KB) | Spanish (PDF - 858 KB)
2020
- Household Screener (PDF - 1.3 MB) | Spanish (PDF - 1.6 MB)
- Topical Questionnaire (Children, 0-5 years) (PDF - 1.2 MB) | Spanish (PDF - 2.7 MB)
- Topical Questionnaire (Children, 6-11 years) (PDF - 800 KB) | Spanish (PDF - 998 KB)
- Topical Questionnaire (Children, 12-17 years) (PDF - 761 KB) | Spanish (PDF - 1.7 MB)
Methodology and Data User FAQs
- FAQs (PDF - 474 KB)
- Source and Accuracy Statement (PDF - 639 KB)
- Survey and Sampling Administration Map
(PDF - 601 KB) - Methodology Report (PDF - 2.1 MB)
- Multiple Imputation Data Guide (PDF - 223 KB)
- Non-Response Bias Analysis (PDF - 662 KB)
- Multi-Year Analysis Guide (PDF - 234 KB)
Variable Lists and Frequencies
- Screener Variable List (PDF - 870 KB)
- Topical Variable List (PDF - 1.3 MB)
- Screener PUF Frequencies (PDF - 1.2 MB)
- Topical PUF Frequencies (PDF - 1.8 MB)
Data Guide
- Guide to Topics and Questions Asked (PDF - 496 KB)
2019
2018
2017
2016
A Note on Sample Size
In both individual year and multi-year analyses, the NSCH sample size may be limited for smaller populations (e.g., American Indian (AI) /Alaska Native (AN)) and state-level subgroups or rare outcomes (e.g., adolescent children with special health care needs (CSHCN) or autism in a particular state).
Small sample sizes may produce unstable estimates.
To minimize misinterpretation, we recommend only presenting statistics with a sample size or unweighted denominator of 30 or more.
Additionally, if the 95% confidence interval width exceeds 20 percentage points or 1.2 times the estimate (≈ relative standard error>30%), we recommend flagging for poor reliability and/or presenting a measure of statistical reliability (e.g., confidence intervals or statistical significance testing) to promote appropriate interpretation.
