Harmonized US National Health and Nutrition Examination Survey 1988-2018 for high throughput exposome-health discovery
Nguyen, V. K.; Middleton, L. Y. M.; Huang, L.; Zhao, N.; Verly, E.; Kvasnicka, J.; Sagers, L.; Patel, C. J.; Colacino, J.; Jolliet, O.
Show abstract
The National Health and Nutrition Examination Survey (NHANES) provides data on the health and environmental exposure of the non-institutionalized US population. Such data have considerable potential to understand how the environment and behaviors impact human health. These data are also currently leveraged to answer public health questions such as prevalence of disease. However, these data need to first be processed before new insights can be derived through large-scale analyses. NHANES data are stored across hundreds of files with multiple inconsistencies. Correcting such inconsistencies takes systematic cross examination and considerable efforts but is required for accurately and reproducibly characterizing the associations between the exposome and diseases. Thus, we developed a set of curated and unified datasets and accompanied code by merging 614 separate files and harmonizing unrestricted data across NHANES III (1988-1994) and Continuous (1999-2018), totaling 134,310 participants and 4,740 variables. The variables convey 1) demographic information, 2) dietary consumption, 3) physical examination results, 4) occupation, 5) questionnaire items (e.g., physical activity, general health status, medical conditions), 6) medications, 7) mortality status linked from the National Death Index, 8) survey weights, 9) environmental exposure biomarker measurements, and 10) chemical comments that indicate which measurements are below or above the lower limit of detection. We also provide a data dictionary listing the variables and their descriptions to help researchers browse the data. We also provide R markdown files to show example codes on calculating summary statistics and running regression models to help accelerate high-throughput analysis and secular trends of the exposome. O_TBL View this table: org.highwire.dtl.DTLVardef@9f5eb0org.highwire.dtl.DTLVardef@1019e2aorg.highwire.dtl.DTLVardef@136df18org.highwire.dtl.DTLVardef@170baecorg.highwire.dtl.DTLVardef@8cd_HPS_FORMAT_FIGEXP M_TBL C_TBL Background & SummaryThe Centers for Disease Control and Prevention (CDC) designed the National Health and Nutrition Examination Survey (NHANES) to monitor the health and nutritional status of adults and children in the US1. Beginning in 1960s, the NHANES program has included a series of surveys to ascertain health, nutritional, and environmental measurements in nationally representative samples. NHANES III was conducted in 1988-1994, consisting of a total of 39,695 persons aged 2 months and older, and was separated into two phases, Phase 1 (1988-1991) and Phase 2 (1991-1994). Continuous NHANES is a series of surveys conducted every two years since 1999, consisting of approximately 10,000 participants for every two-year study period to culminate to a total of 134,310 participants2. The data were ascertained through home interviews and health examinations. The interviews included self-reported questionnaires on demographics, socioeconomic status, health history, dietary intake, and occupation2. The health examination was conducted in mobile exam centers (MEC) staffed by a highly trained medical team2. The examination consists of clinical and physiological measurements of health metrics. In addition, the physical examination includes laboratory tests to quantify biomarkers of environmental chemical exposures in serum or urine. Overall, NHANES houses a wealth of data to be used to understand the health of the nation, but the potential to study secular changes in associations, such as in cancer mortality, over a wide range of time have not been evaluated.
Matching journals
The top 1 journal accounts for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Characterization and Racial Stratification of Social Determinants of Health for Individuals with Type 2 Diabetes as Recorded in Electronic Health Records: Implications for Artificial Intelligence Development 91%
- Automatic Gender Detection in Twitter Profiles for Health-related Cohort Studies 90%
- Using indication embeddings to represent patient health for drug safety studies 88%
Similar papers in this journal
- Cohort Profile: Genetic data in the German Socio-Economic Panel Innovation Sample (Gene-SOEP) 92%
- Rural Roads to Cognitive Resilience (RRR): A prospective cohort study protocol 92%
- Rationale and study protocol of the MAMELI Cohort study (MApping the Methylation of repetitive elements to track the Exposome effects on health: the city of Legnano as a LIving lab) 92%
Similar papers in this journal
- Windows of Susceptibility to Air Pollution During and Surrounding Pregnancy in Relation to Longitudinal Maternal Measures of Adiposity and Lipid Profiles 92%
- Using low-cost sensors and GPS to assess spatiotemporal variations in personal exposure to PM2.5 in the Washington State Twin Registry 92%
- Brick kiln pollution and its impact on health: A systematic review and meta-analysis 92%
Similar papers in this journal
- Exposure to landscape fire smoke extremely reduced birthweight in low- and middle-income countries 92%
- Estimating salt consumption in 49 low- and middle-income countries: Development, validation and application of a machine learning model 91%
- Sparse Dimensionality Reduction Approaches in Mendelian Randomization with highly correlated exposures 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.