NHANES

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Type declaration dctypes:Dataset
Title National Health and Nutrition Examination Survey
Description The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The survey is unique in that it combines interviews and physical examinations.
Publisher https://wwwn.cdc.gov
HTML page https://www.cdc.gov/nchs/nhanes/index.htm
Update frequency Annual
Alternative titles NHANES
License https://www.cdc.gov/nchs/data/nhanes/nhanes_release_policy.pdf
Rights https://www.cdc.gov/nchs/data/nhanes/nhanes_release_policy.pdf
References https://www.cdc.gov/nchs/nhanes/about_nhanes.htm
Citations https://www.ncbi.nlm.nih.gov/pubmed/25093338, https://www.ncbi.nlm.nih.gov/pubmed/25090039, https://www.ncbi.nlm.nih.gov/pubmed/25569458
Preferred prefix NHANES
Version linking NHANES 2017-2018
Publications using this dataset https://www.ncbi.nlm.nih.gov/pubmed/?term=(%22National+Health%22%5Btiab%5D+AND+%22Nutrition+Examination+Survey%22%5Btiab%5D)+OR+%22NHANES%22%5Btiab%5D+NOT+(%22KOREA%22%5Btiab%5D+OR+%22KOREAN%22%5Btiab%5D)
Publication number 9421
Patient type General public
Geographic area All the counties in the United States are divided into 15 groups based on their characteristics. One county is selected from each large group, and together they form the 15 counties in the NHANES surveys for each year. Within each county, smaller groups (with a large number of households in each group) are formed, and between 20 and 24 of these small groups are selected. All of the houses or apartments within those selected small groups are identified, and a sample of about 30 households are selected within each group. NHANES interviewers go to each selected household and ask for information (age, race, and gender) on all persons in the household. A computer algorithm randomly selects some, all, or none of the household members.
Method entities in publications Survival Analysis, Logistic Regression, Chi-squared Test, Mann-Whitney U Test, Paired T Test, T Test, ANOVA, Stepwise Logistic Regression, Logistic Regression Model, Linear Regression, Regression Model, Chi Square, Analysis Of Variance, Principal Component Analysis, K-means, Poisson Regression, Kruskal-Wallis Test, Chi-squared, F Test, Kruskal-Wallis, Cox Proportional Hazards, Cox Regression, Cox Model, Hazard Model, Proportional Hazards, Wilcoxon, Chi-square, Wald Test, Chisquare, Pearson's R, Kolmogorov-Smirnov, Kruskal Wallis Test, T-test, Linear Regression Model, F-test, Fisher's Exact Test, Mc Nemar's Test, Chi-square Test, Bagging, Pearsons R, Pearson Correlation Coefficient, Mann-Whitney, Mann-Whitney U-test, KolmogorovSmirnov, Wilcoxon Rank Sum Test, Wilcoxon Rank-sum Test, Mann Whitney, Shapiro-Wilk Test, Chi Squared, Simple Linear Regression, MannWhitney, Pearson R, Wilcoxon Signed-rank Test, Wilcoxon Signed Rank Test, Paired T-test, Bootstrap, Cochran-Armitage Test, CochranArmitage Trend Test, Cochran-Armitage Trend Test, Wilcoxon Sign Rank Test, KaplanMeier Survival, Proportional Hazards Regression, Linear And Logistic Regression, Apriori, Fisher Exact Test, McNemar's Test, Log-rank Test, Logrank Test, Chisquare Test, KruskalWallis Test, Kaplan-Meier Survival, Boosting, Chisquared, Expectation Maximization, Schoenfeld Test, Ttest, KruskalWallis, Fishers Exact Test, Filter Method, MannWhitney U Test, EM Algorithm, Whitening, Log Rank Test, Cochrane-Armitage Test, Cochran Armitage Test, Leave One Out, CN2, Multivariable Cox Proportional Hazards, McNemar Test, Levenes Test, ShapiroWilk Test, Chi Square Test, McNemars Test, SD Model, F Ratio, Nearest Neighbor, Chisquared Test, F -test, Part Model, Wilcoxon-Mann-Whitney Test, Cochrane Armitage Test, Wilcoxon Ranksum Test, Kaplan-Meier Survival Analysis, KaplanMeier Survival Analysis, CochranArmitage Test, Cochran-Armitage Test For Trend, Kruskal Wallis, Gini Index, K-means Method, Kaplan Meier Survival, Group Average, Chi -square, KaplanMeier Survival Curve, K-nearest Neighbor, ART3, GSP, Propensity Score Matching, Mann Whitney U Test, Wilcoxon Sign-rank Test, Chi Squared Test, Propensity Score Analysis, T -test, Support Vector Machine, Multi-dimensional Scaling, Multidimensional Scaling, Ftest, K-means Algorithm, Classification Model, Chi2, Random Forests, Reclassification Analysis, IBL, Expectation Maximization Method, Shapiro Wilk Test, Kaplan-Meier Survival Curve, Kaplan Meier Survival Curve, Inverse Probability Weighting, Kmeans, Backward Stepwise Logistic Regression, Cobweb, Bayesian Method, Wilcoxon Signed- Rank Test, Association Rule Mining, Nearest Neighbour, CHAID, Adaptive Resonance Theory, K-NN, Linear Discriminant Analysis, Perceptron, Naive Bayes, Neural Network Algorithm, Expectation Maximization Algorithm, Ensemble Learning, Complete Linkage, Minimum Variance, Kmeans Method, Decision Tree Model, Classification And Regression Tree, Bayesian Algorithm, T- Test, Neural Network Model, Genetic Algorithm, Kaplan Meier Survival Analysis, Average Linkage, Pearson Product Moment Correlation Coefficient, Mann-Whitney-Wilcoxon, F-ratio, ID3, Dimensionality Reduction Method, Levene's Test, Chi - Square, Quadratic Discriminant Analysis, Embedded Algorithm, Average Link, Chi- Square, Levene Test, KS Test, Information Gain, Filter Algorithm, Modeling Algorithm, T - Test, Kolmogorov Smirnov, Complete Linkage Clustering, Paired Ttest, Feature Selection Method, Hierarchical Clustering Algorithm, WilcoxonMannWhitney Test, Fisher S Exact Test, Generative Model, Mann - Whitney U Test, K Means, K-S Test, Kolmogorov- Smirnov, Pearson Product-moment Correlation Coefficient, Chi-squared Automatic Interaction Detection, CHAID Model, Chi -Square Test, PRISM Model, Wilcoxon Signedrank Test, Cochran Armitage Trend Test, CART Algorithm, Feature Extraction Algorithm, K Nearest Neighbour, Minimum-variance, MannWhitneyWilcoxon, Mann- Whitney U Test, Clustering Model, Kruskal- Wallis, Regression Modeling Method, Fratio, CochraneArmitage Test, Input Method, Pearson Productmoment Correlation Coefficient, K Nearest Neighbor, KNN, Ensemble Method, Bootstrap Aggregating, Chi- Square Test, Kruskal- Wallis Test, Descriptive Model, Unsupervised Discretization Method, Subgroup Discovery, Induction Method, CochranArmitage Test For Trend, Hierarchical Clustering Method, Entropy-based Method, Mc Nemar Test, Average Linkage Clustering, Correlation-based Algorithm, Pearsons Rho, CART Method, Schoenfeld Residuals Test, Deep Learning, Generative Method, Association Rule Discovery Algorithm, Symmetrical Uncertainty, Feature Selection Algorithm, Chi- Squared, KNN Model, Correlation-based Method
Top methods in publications EM Algorithm (29.55%), Neural Network Model (19.63%), Wilcoxon Signed-Rank Test (16.69%), Poisson Regression (15.02%), Chi-Squared Test (14.85%), Kruskal-Wallis Test (14.32%), Logistic Regression (12.56%), Log-Rank Test (12.17%), Linear Regression (10.04%), T-Test (8.51%)
Availability Public for research purpose. Need to submit a research proposal to the NCHS Research Data Center (RDC).
Publication-based Popularity Index 1880.9
  • Note: Annual survey. Consists of separate datasets: demographics, dietary, examination, laboratory, questionnaire and limited access
Facts about "NHANES"
AvailabilityPublic for research purpose. Need to submit a research proposal to the NCHS Research Data Center (RDC). +
Cito:citesAsAuthorityhttps://www.ncbi.nlm.nih.gov/pubmed/25093338 +, https://www.ncbi.nlm.nih.gov/pubmed/25090039 + and https://www.ncbi.nlm.nih.gov/pubmed/25569458 +
Cito:citesAsDataSourcehttps://www.ncbi.nlm.nih.gov/pubmed/?term=("National+Health"[tiab+AND+"Nutrition+Examination+Survey"[tiab])+OR+"NHANES"[tiab]+NOT+("KOREA"[tiab]+OR+"KOREAN"[tiab])] +
Dct:accrualPeriodicityAnnual +
Dct:alternativeNHANES +
Dct:descriptionThe National Health and Nutrition Examinat
The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The survey is unique in that it combines interviews and physical examinations.
ines interviews and physical examinations. +
Dct:licensehttps://www.cdc.gov/nchs/data/nhanes/nhanes_release_policy.pdf +
Dct:publisherhttps://wwwn.cdc.gov +
Dct:referenceshttps://www.cdc.gov/nchs/nhanes/about_nhanes.htm +
Dct:rightshttps://www.cdc.gov/nchs/data/nhanes/nhanes_release_policy.pdf +
Dct:titleNational Health and Nutrition Examination Survey +
Foaf:pagehttps://www.cdc.gov/nchs/nhanes/index.htm +
Geographic areaAll the counties in the United States are
All the counties in the United States are divided into 15 groups based on their characteristics. One county is selected from each large group, and together they form the 15 counties in the NHANES surveys for each year. Within each county, smaller groups (with a large number of households in each group) are formed, and between 20 and 24 of these small groups are selected. All of the houses or apartments within those selected small groups are identified, and a sample of about 30 households are selected within each group. NHANES interviewers go to each selected household and ask for information (age, race, and gender) on all persons in the household. A computer algorithm randomly selects some, all, or none of the household members.
me, all, or none of the household members. +
Idot:preferredPrefixNHANES +
Methods in publicationsSurvival Analysis +, Logistic Regression +, Chi-squared Test +, Mann-Whitney U Test +, Paired T Test +, T Test +, ANOVA +, Stepwise Logistic Regression +, Logistic Regression Model +, Linear Regression +, Regression Model +, Chi Square +, Analysis Of Variance +, Principal Component Analysis +, K-means +, Poisson Regression +, Kruskal-Wallis Test +, Chi-squared +, F Test +, Kruskal-Wallis +, Cox Proportional Hazards +, Cox Regression +, Cox Model +, Hazard Model +, Proportional Hazards +, Wilcoxon +, Chi-square +, Wald Test +, Chisquare +, Pearson's R +, Kolmogorov-Smirnov +, Kruskal Wallis Test +, T-test +, Linear Regression Model +, F-test +, Fisher's Exact Test +, Mc Nemar's Test +, Chi-square Test +, Bagging +, Pearsons R +, Pearson Correlation Coefficient +, Mann-Whitney +, Mann-Whitney U-test +, KolmogorovSmirnov +, Wilcoxon Rank Sum Test +, Wilcoxon Rank-sum Test +, Mann Whitney +, Shapiro-Wilk Test +, Chi Squared +, Simple Linear Regression +, MannWhitney +, Pearson R +, Wilcoxon Signed-rank Test +, Wilcoxon Signed Rank Test +, Paired T-test +, Bootstrap +, Cochran-Armitage Test +, CochranArmitage Trend Test +, Cochran-Armitage Trend Test +, Wilcoxon Sign Rank Test +, KaplanMeier Survival +, Proportional Hazards Regression +, Linear And Logistic Regression +, Apriori +, Fisher Exact Test +, McNemar's Test +, Log-rank Test +, Logrank Test +, Chisquare Test +, KruskalWallis Test +, Kaplan-Meier Survival +, Boosting +, Chisquared +, Expectation Maximization +, Schoenfeld Test +, Ttest +, KruskalWallis +, Fishers Exact Test +, Filter Method +, MannWhitney U Test +, EM Algorithm +, Whitening +, Log Rank Test +, Cochrane-Armitage Test +, Cochran Armitage Test +, Leave One Out +, CN2 +, Multivariable Cox Proportional Hazards +, McNemar Test +, Levenes Test +, ShapiroWilk Test +, Chi Square Test +, McNemars Test +, SD Model +, F Ratio +, Nearest Neighbor +, Chisquared Test +, F -test +, Part Model +, Wilcoxon-Mann-Whitney Test +, Cochrane Armitage Test +, Wilcoxon Ranksum Test +, Kaplan-Meier Survival Analysis +, KaplanMeier Survival Analysis +, CochranArmitage Test +, Cochran-Armitage Test For Trend +, Kruskal Wallis +, Gini Index +, K-means Method +, Kaplan Meier Survival +, Group Average +, Chi -square +, KaplanMeier Survival Curve +, K-nearest Neighbor +, ART3 +, GSP +, Propensity Score Matching +, Mann Whitney U Test +, Wilcoxon Sign-rank Test +, Chi Squared Test +, Propensity Score Analysis +, T -test +, Support Vector Machine +, Multi-dimensional Scaling +, Multidimensional Scaling +, Ftest +, K-means Algorithm +, Classification Model +, Chi2 +, Random Forests +, Reclassification Analysis +, IBL +, Expectation Maximization Method +, Shapiro Wilk Test +, Kaplan-Meier Survival Curve +, Kaplan Meier Survival Curve +, Inverse Probability Weighting +, Kmeans +, Backward Stepwise Logistic Regression +, Cobweb +, Bayesian Method +, Wilcoxon Signed- Rank Test +, Association Rule Mining +, Nearest Neighbour +, CHAID +, Adaptive Resonance Theory +, K-NN +, Linear Discriminant Analysis +, Perceptron +, Naive Bayes +, Neural Network Algorithm +, Expectation Maximization Algorithm +, Ensemble Learning +, Complete Linkage +, Minimum Variance +, Kmeans Method +, Decision Tree Model +, Classification And Regression Tree +, Bayesian Algorithm +, T- Test +, Neural Network Model +, Genetic Algorithm +, Kaplan Meier Survival Analysis +, Average Linkage +, Pearson Product Moment Correlation Coefficient +, Mann-Whitney-Wilcoxon +, F-ratio +, ID3 +, Dimensionality Reduction Method +, Levene's Test +, Chi - Square +, Quadratic Discriminant Analysis +, Embedded Algorithm +, Average Link +, Chi- Square +, Levene Test +, KS Test +, Information Gain +, Filter Algorithm +, Modeling Algorithm +, T - Test +, Kolmogorov Smirnov +, Complete Linkage Clustering +, Paired Ttest +, Feature Selection Method +, Hierarchical Clustering Algorithm +, WilcoxonMannWhitney Test +, Fisher S Exact Test +, Generative Model +, Mann - Whitney U Test +, K Means +, K-S Test +, Kolmogorov- Smirnov +, Pearson Product-moment Correlation Coefficient +, Chi-squared Automatic Interaction Detection +, CHAID Model +, Chi -Square Test +, PRISM Model +, Wilcoxon Signedrank Test +, Cochran Armitage Trend Test +, CART Algorithm +, Feature Extraction Algorithm +, K Nearest Neighbour +, Minimum-variance +, MannWhitneyWilcoxon +, Mann- Whitney U Test +, Clustering Model +, Kruskal- Wallis +, Regression Modeling Method +, Fratio +, CochraneArmitage Test +, Input Method +, Pearson Productmoment Correlation Coefficient +, K Nearest Neighbor +, KNN +, Ensemble Method +, Bootstrap Aggregating +, Chi- Square Test +, Kruskal- Wallis Test +, Descriptive Model +, Unsupervised Discretization Method +, Subgroup Discovery +, Induction Method +, CochranArmitage Test For Trend +, Hierarchical Clustering Method +, Entropy-based Method +, Mc Nemar Test +, Average Linkage Clustering +, Correlation-based Algorithm +, Pearsons Rho +, CART Method +, Schoenfeld Residuals Test +, Deep Learning +, Generative Method +, Association Rule Discovery Algorithm +, Symmetrical Uncertainty +, Feature Selection Algorithm +, Chi- Squared +, KNN Model + and Correlation-based Method +
PPI1,880.9 +
Patient typeGeneral public +
Pav:hasCurrentVersionNHANES 2017-2018 +
Publication number9421 +
Rdf:typedctypes:Dataset +
Top methods in publicationsEM Algorithm (29.55%), Neural Network Mode
EM Algorithm (29.55%), Neural Network Model (19.63%), Wilcoxon Signed-Rank Test (16.69%), Poisson Regression (15.02%), Chi-Squared Test (14.85%), Kruskal-Wallis Test (14.32%), Logistic Regression (12.56%), Log-Rank Test (12.17%), Linear Regression (10.04%), T-Test (8.51%)
Linear Regression (10.04%), T-Test (8.51%) +