NCHS has linked data from various surveys with death certificate records from the National Death Index (NDI). Linkage of the NCHS survey participant data with the NDI mortality data provides the opportunity to conduct a vast array of outcome studies designed to investigate the association of a wide variety of health factors with mortality. The Linked Mortality Files (LMF) have been updated with mortality follow-up data through December 31, 2019.

Public-use Linked Mortality Files (LMF) are available for 1986-2018 NHIS, 1999-2018 NHANES, and NHANES III. The files include a limited set of mortality variables for adult participants only. The public-use versions of the NCHS Linked Mortality Files were subjected to data perturbation techniques to reduce the risk of participant re-identification. For select records, synthetic data were substituted for follow-up time or underlying cause of death. Information regarding vital status was not perturbed.

Measurements of discrimination by sex and race/ethnicity, NHANES III linked mortality file 1988–2006.

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 (e.g., cancer mortality outcomes). 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 of the exposome and secular trends on cancer mortality. csv Data Record: The curated NHANES datasets and the data dictionaries includes 13 .csv files and 1 excel file. The curated NHANES datasets involves 10 .csv formatted files, one for each module and labeled as the following: 1) mortality, 2) dietary, 3) demographics, 4) response, 5) medications, 6) questionnaire, 7) chemicals, 8) occupation, 9) weights, and 10) comments. The eleventh file is a dictionary that lists the variable name, description, module, category, units, CAS Number, comment use, chemical family, chemical family shortened, number of measurements, and cycles available for all 4,740 variables in NHANES ("dictionary_nhanes.csv"). The 12th csv file contains the harmonized categories for the categorical variables ("dictionary_harmonized_categories.csv"). The 13th file contains the dictionary for descriptors on the drugs codes (“dictionary_drug_codes.csv”). The 14th file is an excel file that contains the cleaning documentation, which records all the inconsistencies for all affected variables to help curate each of the NHANES datasets (“nhanes_inconsistencies_documentation.xlsx”). R Data Record: For researchers who want to conduct their analysis in the R programming language, the curated NHANES datasets and the data dictionaries can be downloaded as a .zip file which include an .RData file and an .R file. We provided an .RData file that contains all the aforementioned datasets as R data objects (“w - nhanes_1988_2018.RData”). Also in this .RData file, we make available all R scripts on customized functions that were written to curate the data. We also provide an .R file that shows how we used the customized functions (i.e. our pipeline) to curate the data (“m - nhanes_1988_2018.R”).

Sex and race/ethnicity-specific equation parameters for estimation of 10-year risk of ASCVD mortality, NHANES III linked mortality file 1988–2006.

Characteristics of adults aged 40–79 years with no prior atherosclerotic cardiovascular disease, NHANES III linked mortality file 1988–2006.

The National Health and Nutrition Examination Survey (NHANES) provides data and have considerable potential to study the health and environmental exposure of the non-institutionalized US population. However, as NHANES data are plagued with multiple inconsistencies, processing these data is required before deriving new insights through large-scale analyses. Thus, we developed a set of curated and unified datasets by merging 614 separate files and harmonizing unrestricted data across NHANES III (1988-1994) and Continuous (1999-2018), totaling 135,310 participants and 5,078 variables. The variables conveydemographics (281 variables),dietary consumption (324 variables),physiological functions (1,040 variables),occupation (61 variables),questionnaires (1444 variables, e.g., physical activity, medical conditions, diabetes, reproductive health, blood pressure and cholesterol, early childhood),medications (29 variables),mortality information linked from the National Death Index (15 variables),survey weights (857 variables),environmental exposure biomarker measurements (598 variables), andchemical comments indicating which measurements are below or above the lower limit of detection (505 variables).csv Data Record: The curated NHANES datasets and the data dictionaries includes 23 .csv files and 1 excel file.The curated NHANES datasets involves 20 .csv formatted files, two for each module with one as the uncleaned version and the other as the cleaned version. The modules are labeled as the following: 1) mortality, 2) dietary, 3) demographics, 4) response, 5) medications, 6) questionnaire, 7) chemicals, 8) occupation, 9) weights, and 10) comments."dictionary_nhanes.csv" is a dictionary that lists the variable name, description, module, category, units, CAS Number, comment use, chemical family, chemical family shortened, number of measurements, and cycles available for all 5,078 variables in NHANES."dictionary_harmonized_categories.csv" contains the harmonized categories for the categorical variables.“dictionary_drug_codes.csv” contains the dictionary for descriptors on the drugs codes.“nhanes_inconsistencies_documentation.xlsx” is an excel file that contains the cleaning documentation, which records all the inconsistencies for all affected variables to help curate each of the NHANES modules.R Data Record: For researchers who want to conduct their analysis in the R programming language, only cleaned NHANES modules and the data dictionaries can be downloaded as a .zip file which include an .RData file and an .R file.“w - nhanes_1988_2018.RData” contains all the aforementioned datasets as R data objects. We make available all R scripts on customized functions that were written to curate the data.“m - nhanes_1988_2018.R” shows how we used the customized functions (i.e. our pipeline) to curate the original NHANES data.Example starter codes: The set of starter code to help users conduct exposome analysis consists of four R markdown files (.Rmd). We recommend going through the tutorials in order.“example_0 - merge_datasets_together.Rmd” demonstrates how to merge the curated NHANES datasets together.“example_1 - account_for_nhanes_design.Rmd” demonstrates how to conduct a linear regression model, a survey-weighted regression model, a Cox proportional hazard model, and a survey-weighted Cox proportional hazard model.“example_2 - calculate_summary_statistics.Rmd” demonstrates how to calculate summary statistics for one variable and multiple variables with and without accounting for the NHANES sampling design.“example_3 - run_multiple_regressions.Rmd” demonstrates how run multiple regression models with and without adjusting for the sampling design.

Adjusted hazard ratios of all-cause mortality risk for allostatic load score categories for racial/ethnic groups according to age and education: NHANES III-Linked Mortality File, 2015.

Descriptive statistics for biomarkers and allostatic load score for adults 25 years of age or older: NHANES III-Linked Mortality File, 2015.

BackgroundFew studies have explored the association between water intake and mortality risk, and the findings were inconsistent.ObjectiveThis study aimed to explore the water intake–mortality association, utilizing the data from the National Health and Nutrition Examination Survey (NHANES) and the 2015 public-linked mortality files released by the National Center for Health Statistics.MethodsWe used the diet- and mortality-linked data of a total of 35,463 adults (17,234 men) aged ≥20 years in the NHANESs 1999–2014 to perform a prospective study. The multivariate-adjusted Cox proportional hazards model was used to explore the associations of the amount of water intake (expressed by total water, plain water, beverage, and food water) and water intake proportion (expressed by the percentage of each kind of water) with mortality risks due to all causes, malignant neoplasms/cancer, and heart disease. The restricted cubic spline plots were adopted to clarify the dose–response relationships among them.ResultsWith a median of 88 months (interquartile range: 49–136 months) follow-up, a total of 4,915 all-cause deaths occurred, including 1,073 and 861 deaths from malignant neoplasms/cancer and heart disease, respectively. The amount of water intake in either type was negatively associated with all-cause mortality risk. Additionally, the negative linear dose–response relationships of water intake and all-cause mortality risk were found for all types of water except for food water, which followed a non-linear pattern. Similarly, compared to the lowest quartile (beverage water intake: <676 g/day; food water intake: <532 g/day), beverage and food water intakes in the range of 1,033–1,524 and 1,612–3,802 g/day were associated with decreased malignant neoplasms/cancer mortality risk. A U-shaped dose–response relationship was found for beverage water intake and malignant neoplasms/cancer mortality risk and a negative linear dose–response relationship was found for food water intake and malignant neoplasms/cancer mortality risk. Coffee and/or tea consumption was/were negatively associated with mortality risks due to all causes and malignant neoplasms/cancer. No significant associations of water intake proportion and mortality risks were found.ConclusionOur findings demonstrated that higher water intake is associated with lower mortality risks among the United States population.

ImportanceReligiosity has been associated with positive health outcomes. Hypothesized pathways for this association include religious practices, such as church attendance, that result in reduced stress.ObjectiveThe objective of this study was to examine the relationship between religiosity (church attendance), allostatic load (AL) (a physiologic measure of stress) and all-cause mortality in middle-aged adults.Design, setting and participantsData for this study are from NHANES III (1988–1994). The analytic sample (n = 5449) was restricted to adult participants, who were between 40–65 years of age at the time of interview, had values for at least 9 out of 10 clinical/biologic markers used to derive AL, and had complete information on church attendance.Main outcomes and measuresThe primary outcomes were AL and mortality. AL was derived from values for metabolic, cardiovascular, and nutritional/inflammatory clinical/biologic markers. Mortality was derived from a probabilistic algorithm matching the NHANES III Linked Mortality File to the National Death Index through December 31, 2006, providing up to 18 years follow-up. The primary predictor variable was baseline report of church attendance over the past 12 months. Cox proportional hazard logistic regression models contained key covariates including socioeconomic status, self-rated health, co-morbid medical conditions, social support, healthy eating, physical activity, and alcohol intake.ResultsChurchgoers (at least once a year) comprised 64.0% of the study cohort (n = 3782). Non-churchgoers had significantly higher overall mean AL scores and higher prevalence of high-risk values for 3 of the 10 markers of AL than did churchgoers. In bivariate analyses non-churchgoers, compared to churchgoers, had higher odds of an AL score 2–3 (OR 1.24; 95% CI 1.01, 1.50) or ≥4 (OR 1.38; 95% CI 1.11, 1.71) compared to AL score of 0–1. More frequent churchgoers (more than once a week) had a 55% reduction of all-cause mortality risk compared with non-churchgoers. (HR 0.45, CI 0.24–0.85) in the fully adjusted model that included AL.Conclusions and relevanceWe found a significant association between church attendance and mortality among middle-aged adults after full adjustments. AL, a measure of stress, only partially explained differences in mortality between church and non-church attendees. These findings suggest a potential independent effect of church attendance on mortality.

Background Current evidence on the relationship between carotenoids and chronic kidney disease (CKD) patients are limited and controversial. Methods Data were obtained from the Nutrition and Health Examination Survey (NHANES) database and the NHANES Linked Mortality File, both from a nationally representative sample. Dietary intake was assessed through 24-h dietary recall, and information was available both on dietary and serum α-carotene, β-carotene, β-cryptoxanthin, lycopene, and lutein/zeaxanthin (combined) through the NHANES cycles used. We used multivariable Cox proportional hazards regression models to estimate the risk for all-cause mortality associated with carotene intakes and serum levels, adjusting for potential confounding factors. Results Of the 6,095 CKD participants, 1,924 subjects died (mean follow-up time, 8.1 years). After eliminating all the confounding factors, we found that high levels of total carotene (HR = 0.85, 95% CI, 0.75-0.97, P = 0.011) intakes at baseline were significantly associated with a lower risk of death. And the serum concentrations of carotenoid were also showing that a-carotene (HR = 0.77, 95%CI, 0.65-0.92, P = 0.002), beta-cryptoxanthin (HR = 0.83, 95%CI, 0.70-0.98, P = 0.019), lycopene (HR = 0.77, 95% CI, 0.65-0.91, P = 0.002), and lutein + zeaxanthin (HR = 0.82, 95% CI, 0.70-0.96, P = 0.002) was significantly associated with decreased all-cause mortality of CKD patients. The associations remained similar in the sensitivity analyses. Conclusion Findings suggest that high-level carotene dietary intake and the serum concentration were associated with a lower risk of mortality in the CKD population.

Crude and adjusted hazard ratiosa of all-cause and CVD-specific mortality risk for allostatic load score categories: NHANES III-Linked Mortality File, 2015.

BackgroundPrevious research has linked systemic inflammatory markers and the Dietary Inflammatory Index (DII) with depression. However, the relationship between DII and these markers, and their impact on mortality risk among depressed adults, remains underexplored. This study aims to explore the association between DII and systemic inflammatory markers and their mediating effect on mortality risk in adults with depression.MethodsThis study analyzed data from 4,981 adults with depression in the National Health and Nutrition Examination Survey (NHANES). This study quantified dietary inflammatory potential with the DII and systemic inflammation with the Systemic Immune-Inflammation Index (SII) and Systemic Inflammation Response Index (SIRI). Cox proportional hazards regression and inverse probability weighting evaluated the impact of DII, SII, and SIRI on mortality risk in depressed adults, as well as their mediating effects. Multiple linear regression analyzed the associations between DII and SII/SIRI. Restricted cubic spline analysis explored the non-linear relationship between DII and mortality risk.ResultsIn adjusted regression models, DII, SII, and SIRI were significantly associated with all-cause mortality risk in depressed adults, with hazard ratios (HRs) (95% CIs) from 1.333 to 1.497 (1.051–1.233, 1.689–1.832). DII was linearly related to SII, with βs (95% CIs) from 0.001 to 0.121 (0.001–0.017, 0.001–0.224). SII significantly mediated the DII-mortality risk link, especially in males (8.07%). The DII-mortality relationship was linear (Pnon-linear = 0.174), with a beneficial threshold at 1.62.ConclusionDII and SII are associated with increased all-cause mortality risk in depressed adults. The DII-related mortality risk in depression can be partially mediated by SII, with a more pronounced effect in males.

BackgroundMorbidity and mortality of arteriosclerotic cardiovascular disease (ASCVD) varied according to socioeconomic status (SES), and evidence on the association between SES and ASCVD risk, and cause-specific and all-cause mortality was nevertheless lacking in large-scale or population-based studies.MethodsA multicycle cross-sectional design and mortality linkage study was conducted using data from Continuous National Health and Nutrition Examination Survey (NHANES) in the United States, including public use linked mortality follow-up files through December 31, 2019. Poverty income ratio (PIR) served as a SES index. A series of weighted Logistic regressions and Cox proportional hazards regressions were used to investigate the association between the SES and the risk of ASCVD and mortality, respectively.ResultsThe study sample was comprised of 30,040 participants aged 20–85 years old during the 2005–2018 period. Weighted Logistic regression models consistently indicated significant relationship between people experiencing poverty and increased risk of ASCVD, and linear trend tests were all statistically significant (all P for trend < 0.001). Additionally, weighted Cox regression analysis consistently demonstrated that the hazards of cause-specific and all-cause mortality increased, with the decrease of each additional income level, and trend analyses indicated similar results (all P for trend < 0.001).ConclusionsOur study confirmed that the SES was strongly linked to living with ASCVD, and cause-specific and all-cause mortality, even after adjusting for other factors that could impact risk, such as the American Heart Association (AHA)'s Life's Simple 7 cardiovascular health score and variables of age, sex, marital status, education, and depression severity.

IntroductionCompared with sleep disorders, no consensus has been reached on whether a subjective complaint of having trouble sleeping is associated with increased all-cause and heart disease mortality risk. Previous studies displayed considerable heterogeneity in population disease characteristics and duration of follow-up. Therefore, the aims of this study were to examine the relationship between sleep complaints and all-cause and heart disease mortality and whether the associations were influenced by follow-up time and population disease characteristics. In addition, we aimed to figure out the influence of the joint effects of sleep duration and sleep complaints on mortality risk.MethodsThe present study utilized data from five cycles of the National Health and Nutrition Examination Survey (NHANES) (2005~2014) linked with the most updated 2019 National Death Index (NDI). Sleep complaints were determined by answers to “Have you ever told a doctor or other health professional that you have trouble sleeping?” and “Have you ever been told by a doctor or other health professional that you have a sleep disorder?”. Those who answered ‘Yes' to either of the aforementioned two questions were considered as having sleep complaints.ResultsA total of 27,952 adult participants were included. During a median follow-up of 9.25 years (interquartile range, 6.75–11.75 years), 3,948 deaths occurred and 984 were attributable to heart disease. A multivariable-adjusted Cox model revealed that sleep complaints were significantly associated with all-cause mortality risk (HR, 1.17; 95% CI, 1.07–1.28). Subgroup analysis revealed that sleep complaints were associated with all-cause (HR, 1.17; 95% CI, 1.05–1.32) and heart disease (HR, 1.24; 95% CI, 1.01–1.53) mortality among the subgroup with cardiovascular disease (CVD) or cancer. In addition, sleep complaints were more strongly associated with short-term mortality than long-term mortality. The joint analysis of sleep duration and sleep complaints showed that sleep complaints mainly increased the mortality risk in those with short (< 6 h/day, sleep complaints HR, 1.40; 95% CI, 1.15–1.69) or recommended (6–8 h/day, sleep complaints HR, 1.15; 95% CI, 1.01–1.31) sleep duration group.DiscussionIn conclusion, sleep complaints were associated with increased mortality risk, indicating a potential public benefit of monitoring and managing sleep complaints in addition to sleep disorders. Of note, persons with a history of CVD or cancer may represent a potentially high-risk group that should be targeted with a more aggressive intervention of sleep problems to prevent premature all-cause and heart disease death.

BackgroundSarcopenia is prevalent in metabolic dysfunction-associated fatty liver diseases (MAFLD), and the primary treatment for both diseases is lifestyle modification. We studied how dietary components and physical activity affect individuals with sarcopenia and MAFLD.Materials and methodsWe conducted a study utilizing National Health and Nutrition Examination Survey (NHANES) III (1988–1994) data with Linked Mortality file (through 2019). The diagnosis of fatty liver disease (FLD) was based on ultrasound images revealing moderate and severe steatosis. Using bioelectrical measures, sarcopenia was assessed. Using self-report data, dietary intake and physical activity levels were evaluated.ResultsAmong 12,259 participants, 2,473 presented with MAFLD, and 290 of whom had sarcopenia. Higher levels of physical activity (odds ratio [OR] = 0.51 [0.36–0.95]) and calorie (OR = 0.58 [0.41–0.83]) intake reduced the likelihood of sarcopenia in MAFLD patients. During a median follow-up period of 15.3 years, 1,164 MAFLD and 181 MAFLD patients with sarcopenia perished. Increased activity levels improved the prognosis of patients with sarcopenia (Insufficiently active, HR = 0.75 [0.58–0.97]; Active, HR = 0.64 [0.48–0.86]), which was particularly pronounced in older patients.ConclusionIn the general population, hyperglycemia was highly related to MAFLD prognosis. Physical inactivity and a protein-restricted diet corresponded to sarcopenia, with physical inactivity being connected to poor outcomes. Adding protein supplements would be beneficial for older people with sarcopenia who are unable to exercise due to frailty, while the survival benefits were negligible.

ObjectiveThis study aimed to elucidate the relationship between retinopathy status or severity and the all-cause and specific-cause mortality risk based on the updated National Health and Nutrition Examination Survey (NHANES) database and 2019 Public Access Link mortality file.MethodsIn this prospective cohort study, a total of 6,797 participants aged over 40 years based on NHANES 2005–2008 were analyzed. The severity of retinopathy was classified into 4 grades-no retinopathy, mild non-proliferative retinopathy (NPR), moderate to severe NPR, and proliferative retinopathy (PR). Multiple covariate-adjusted Cox proportional hazards regression models and Fine and Gray competing risk regression models were used to assess the all-cause and cause-specific mortality risks, respectively. The propensity score matching (PSM) approach was also applied additionally to adequately balance between-group covariates to validate our findings.ResultsA final total of 4,808 participants representing 18,282,772 United States (US) non-hospitalized participants were included for analysis, 50.27% were male (n = 2,417), 55.32% were non-hispanic white (n = 2,660), and mean [SE] age, 56.10 [0.40] years. After a median follow-up of 12.24 years (interquartile range, 11.16–13.49 years), 1,164 participants died of all-cause mortality, of which 941 (80.84%) died without retinopathy and 223 (19.16%) died with retinopathy at baseline. The presence of retinopathy was associated with increased all-cause mortality, cardiovascular disease (CVD), and diabetes mellitus (DM)-specific mortality, and the results remain consistent after PSM. Severity analysis showed that only mild NPR was associated with an increased all-cause mortality risk (hazard ratio (HR) = 2.01; 95% confidence interval (CI), 1.00–4.03), while increased CVD and DM-specific mortality risk were associated with all grades of retinopathy and were exponentially greater with increasing retinopathy severity, and the trend test was also significant (P for trend 0.004 and 0.04, respectively).DiscussionOur findings suggest that the diagnosis of retinopathy is an independent risk factor for all-cause mortality in people over 40 years old. Retinopathy grading is significantly associated with the survival risk of patients with CVD or DM, it can be a valuable predictor in the stratified management and risk warning of CVD or DM patients, as well as in the monitoring of systemic vasculopathy status.

BackgroundNumerous studies have shown that low levels of vitamin D are linked to a higher risk of inflammatory diseases and their progression. However, how vitamin D levels affect mortality in chronic obstructive pulmonary disease (COPD) patients is still unclear. Thus, this study aimed to explore the relationship between serum 25-hydroxyvitamin D [25(OH)D] levels and the risk of death from all causes in U.S. adults with COPD.MethodsThis study analyzed 1,876 adults with COPD from the National Health and Nutrition Examination Survey (2005–2018). Mortality data up to December 31, 2019, were obtained from the National Death Index (NDI) records. Participants were categorized into three groups according to their 25(OH)D levels: Q1 (

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease. Body mass index (BMI) is the most used obesity index but has important limitations. The weight-adjusted waist index (WWI) is a novel obesity metric and accurately reflects body composition. We explored the association of WWI with all-cause and cardiovascular disease (CVD) mortality in MASLD.MethodsAdult participants with MASLD were included from NHANES 1999-2018. WWI was calculated by dividing the waist circumference (WC) by the square root of body weight. MASLD was diagnosed by the presence of hepatic steatosis and at least one cardiometabolic risk factor in the absence of other causes of steatosis. A fatty liver index ≥60 suggested the presence of hepatic steatosis. Mortality data was obtained by prospectively linking to the National Death Index. Multivariate Cox proportional hazards regression analyses were used to explore these associations and multiple adjustment models were constructed including crude, partial, and fully adjusted models.ResultsAfter adjusting for all covariates including BMI, WWI remained positively and linearly associated with all-cause and CVD mortality in MASLD (hazard ratios [HR] 1.247 and 1.218, respectively). Higher WWI was associated with a significantly increased risk of mortality (both p for trend <0.05). There was an “obesity paradox” between BMI and all-cause mortality in MASLD, with significantly lower all-cause mortality in those with overweight/obesity compared to normal BMI (HR 0.625 and 0.596, respectively, p for trend = 0.024), and no association between BMI and CVD mortality. Interaction analyses indicated that these associations were influenced by several demographic variables and disease status. Time-dependent receiver operating characteristic curves indicated that the predictive value of WWI for mortality in MASLD was higher than that of BMI, WC, and waist-to-height ratio across all follow-up durations.ConclusionsWWI was positively and linearly associated with all-cause and CVD mortality in MASLD, whereas BMI did not accurately reflect mortality risk. WWI provided the optimal predictive value for mortality compared to traditional obesity indicators. These findings emphasize the potential use of WWI as a novel obesity indicator for mortality risk assessment, stratification, and prevention in MASLD.

Crude Death Rates of the participants from the US.