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BACKGROUND To compare prevalence of hypertension and stage II hypertension assessed by 2 blood pressure (BP) observation protocols. METHODS Participants aged 18 years and older (n = 4,689) in the National Health and Nutrition Examination Survey (NHANES 2017–2018) had their BP measured following 2 protocols: the legacy auscultation protocol (AP) and oscillometric protocol (OP). The order of protocols was randomly assigned. Prevalence estimates for hypertension (BP ≥130/80 mm Hg or use of medication for hypertension) and stage II hypertension (BP ≥140/90 mm Hg) were determined overall, by demographics, and by risk factors for each protocol. Ratios (OP% ÷ AP%) and kappa statistics were calculated. RESULTS Age-adjusted hypertension prevalence was 44.5% (95% confidence interval [CI]: 41.1%–48.0%) using OP and 45.1% (95% CI: 41.5%–48.7%) using AP, prevalence ratio = 0.99 (95% CI = 0.94–1.04). Age-adjusted stage II hypertension prevalence was 15.8% (95% CI: 13.6%–18.2%) using AP and 17.1% (95% CI: 14.7%–19.7%) using OP, prevalence ratio = 0.92 (95% CI = 0.81–1.04). For both hypertension and stage II hypertension, the prevalence ratios by demographics and by risk factors all included unity in their 95% CI, except for stage II hypertension in adults 60+ years (ratio: 0.88 [95% CI: 0.78–0.98]). Kappa for agreement between protocols for hypertension and stage II hypertension was 0.75 (95% CI = 0.71–0.79) and 0.67 (95% CI = 0.61–0.72), respectively. CONCLUSIONS In adults and for nearly all subcategories there were no significant differences in prevalence of hypertension and stage II hypertension between protocols, indicating that protocol change may not affect the national prevalence estimates of hypertension and stage II hypertension.

Objectives This report describes the creation of the NHANES 2017-March 2020 prepandemic data files, including the selection of the appropriate NHANES sample design (2015-2018) to create sample weights and variance units for public-use data files. Additionally, the development of a factor applied to the primary sampling units to adjust the 2017-March 2020 data to fit the NHANES 2015-2018 sample design is described. Analyses to assess representativeness of the target population were performed, and a simulation to replicate the impact of interrupted data collection using earlier NHANES cycles was undertaken. Analytic guidance specific to use for prepandemic data files is also included. .

This report describes the creation of the NHANES 2017–March 2020 prepandemic data files.

Background and objectives-In March 2020, the coronavirus disease 2019 (COVID-19) pandemic halted National Health and Nutrition Examination Survey (NHANES) field operations. As data collected in the partial 2019–2020 cycle (herein referred to as 2019–March 2020) are not nationally representative, they were combined with previously released 2017–2018 data to produce nationally representative estimates. This report explains the creation of the 2017–March 2020 prepandemic data files, provides recommendations for and limitations of the files’ use, and presents prevalence estimates for selected health outcomes based on the files. Methods-The 2019–2020 primary sampling units (PSUs) were reassigned to the 2015–2018 sample design strata and combined with the 2017–2018 data to create a data set that could be used to calculate nationally representative estimates. A PSUlevel adjustment factor was created to equalize the contribution of each stratum to the total survey sample and applied to participant base weights. Interview and examination weights were calculated from the adjusted base weights. The performance of final interview weights was assessed by comparing the demographic characteristics of the weighted NHANES 2017–March 2020 prepandemic sample with nationally representative estimates from the 2018 5-year American Community Survey. Prevalence estimates and 95% confidence intervals were calculated for selected health outcomes. Results-Among children and adolescents aged 2–19 years, the prevalence of obesity was 19.7% and the prevalence of untreated or restored dental caries in one or more primary or permanent teeth was 46.0%. Among adults aged 20 and over, the age-adjusted prevalence of obesity was 41.9%, severe obesity was 9.2%, and diabetes was 14.8%. Among adults aged 18 and over, the age-adjusted prevalence of hypertension was 45.1%. Among adults aged 65 and over, the age-adjusted prevalence of complete tooth loss was 13.8%. Conclusion-A PSU-level adjustment factor and additional weighting adjustments made nationally representative estimates from the 2017–March 2020 prepandemic data files possible;this was the last NHANES data collected before widespread transmission of COVID-19. © 2021, National Center for Health Statistics. All rights reserved.

Background The purpose of the National Health and Nutrition Examination Survey (NHANES) is to produce national estimates representative of the total noninstitutionalized civilian U.S. population. The sample for NHANES is selected using a complex, four-stage sample design. NHANES sample weights are used by analysts to produce estimates of the health-related statistics that would have been obtained if the entire sampling frame (i.e., the noninstitutionalized civilian U.S. population) had been surveyed. Sampling errors should be calculated for all survey estimates to aid in determining their statistical reliability. For complex sample surveys, exact mathematical formulas for variance estimates that fully incorporate the sample design are usually not available. Variance approximation procedures are required to provide reasonable, approximately unbiased, and design-consistent estimates of variance. Objective This report describes the NHANES 2015-2018 sample design and the methods used to create sample weights and variance units for the public-use data files, including sample weights for selected subsamples, such as the fasting subsample. The impacts of sample design changes on estimation for NHANES 2015-2018 are described. Approaches that data users can use to modify sample weights when combining survey cycles or when combining subsamples are also included.

Over the past two decades, a steady decline in response rates on national face-to-face surveys has been documented, with steeper declines observed in recent years. The impact of nonresponse on survey estimates is inconsistent and depends on the correlation between response propensity and the survey estimates. To better understand the impact of declining response rates on the 2017-2018 National Health and Nutrition Examination Survey (NHANES), potential nonresponse bias (NRB) was investigated. NRB was assessed using three approaches: (a) studying variation within the respondent set; (b) benchmarking and comparisons to external data; and (c) comparing alternative weighting adjustments. Because NHANES only samples 30 counties in every 2-year cycle, the sample of counties in any given cycle may be an outlier on some characteristics. Such sampling variability may compound the effects of NRB. For this reason, the representativeness of the 2017-2018 NHANES counties was examined by comparing: (a) the characteristics of the 2017-2018 sampled counties with those from prior cycles; (b) each sampled county with the average of all the counties in the sampling stratum from which that county was selected; and (c) the 2017-2018 counties with 5,000 other samples that could have been drawn under the same sample design using a simulation study. The NRB analyses showed that the 2017-2018 NHANES sample had a lower proportion of college graduates and higher-income individuals compared with prior cycles. Additionally, the 2017-2018 NHANES counties had lower proportions of college graduates and lower mean incomes compared with counties from prior cycles and counties not selected in 2017-2018, which exacerbated the effects of NRB. Weighting adjustments used in prior cycles were not sufficient to address the bias in the 2017-2018 NHANES. Instead, enhanced weighting adjustments for education and income reduced the bias resulting from nonresponse and location sampling variability.

BACKGROUND: Automated blood pressure (BP) devices have been used in the home for self-management purposes and are increasingly being used in population-based research. Although these devices are convenient and affordable and may be used by inexperienced lay personnel, the potential impact of an examiner’s skill level on the results needs to be evaluated quantitatively. The aim of this study was to compare BP measurements obtained in a home setting by personnel with healthcare experience with those obtained by personnel without healthcare experience. In addition, the percent agreement in high blood pressure (HBP) classification between the home BP measurement by the field interviewer (FI) and measurements obtained in a standardized environment was examined. METHODS: The Health Measures at Home Study was a pilot study carried out among 128 adult participants recruited from the National Health and Nutrition Examination Survey. The Health Measures at Home Study provided the opportunity to compare the BP values obtained with an automated device in a home setting by both experienced health technicians (HTs) with those obtained by FIs who had no healthcare experience. Differences between measurements obtained by the HT and measurements obtained by the FI were assessed using paired t-tests, Pearson’s correlations, and Bland–Altman plots. Percent agreement and κ-statistics were used to assess agreement in HBP classification between examiners in the home. Measurements obtained by the FI were also compared with those obtained in the National Health and Nutrition Examination Survey mobile exam center (MEC) by a physician using percent agreement and κ-statistics. RESULTS: There was a high correlation in both systolic blood pressure (SBP; r = 0.903) and diastolic blood pressure (DBP; r = 0.894) between measurements obtained by HTs and those obtained by FIs. The mean SBP and DBP obtained by the FIs (SBP, 119.0 ± 14.4 mmHg; DBP,71.9 ± 9.8 mmHg) were significantly higher than the HT measurements (SBP, 117.0 ± 12.7 mmHg; DBP,69.9.9 ± 9.2 mmHg). In the home, the FI classified 11.7% as having HBP, whereas the HT classified 7.0%. The percent of individuals classified as having HBP by the physician in the MEC was 10.2% of the participants. CONCLUSION: Operationally, FIs could take BP measurements in the home; however, there were some differences between measurements obtained by the FI and HT. The absolute difference between measurements obtained by the FI and those obtained by the HT in the home showed that measurements obtained by the FI tended to be higher than the HT, but the magnitude of these differences was less than 5 mmHg. The HT classified 7.0% of HBP whereas the FI classified 11.7% of HBP. Similarly, the FI and the MEC physician classified a different percent of individuals with HBP. Further investigation is warranted to determine the cause of these small but significant absolute differences between measurements obtained by the FI and HT.

Diabetes is a major cause of morbidity and mortality in the United States (1-3). Diabetes can be present but undiagnosed, meaning that a person can have diabetes but not report having ever been told by a doctor or health professional that they have the condition. Type 2 diabetes can progress over an extended time period with gradual, often unnoticed, changes occurring before diagnosis. If left unmanaged, diabetes may contribute to serious health outcomes including neuropathy, nephropathy, retinopathy, coronary artery disease, stroke, and peripheral vascular disease (4). This report presents the prevalence of total, diagnosed, and undiagnosed diabetes in U.S. adults in 2013-2016.

Background Both excessive sodium intake and obesity are risk factors for hypertension and cardiovascular disease. The association between sodium intake and obesity is unclear, with few studies assessing sodium intake using 24-h urine collection. Objectives Our objective was to assess the association between usual 24-h sodium excretion and measures of adiposity among US adults. Methods Cross-sectional data were analyzed from a sample of 730 nonpregnant participants aged 20-69 y who provided up to 2 complete 24-h urine specimens in the NHANES 2014 and had data on overweight or obesity [body mass index (kg/m2) ≥25] and central adiposity [waist circumference (WC): >88 cm for women, >102 cm for men]. Measurement error models were used to estimate usual sodium excretion, and multiple linear and logistic regression models were used to assess its associations with measures of adiposity, adjusting for sociodemographic, health, and dietary variables [i.e., energy intake or sugar-sweetened beverage (SSB) intake]. All analyses accounted for the complex survey sample design. Results Unadjusted mean ± SE usual sodium excretion was 3727 ± 43.5 mg/d and 3145 ± 55.0 mg/d among participants with and without overweight/obesity and 3653 ± 58.1 mg/d and 3443 ± 35.3 mg/d among participants with or without central adiposity, respectively. A 1000-mg/d higher sodium excretion was significantly associated with 3.8-units higher BMI (95% CI: 2.8, 4.8) and a 9.2-cm greater WC (95% CI: 6.9, 11.5 cm) adjusted for covariates. Compared with participants in the lowest quartile of sodium excretion, the adjusted prevalence ratios in the highest quartile were 1.93 (95% CI: 1.69, 2.20) for overweight/obesity and 2.07 (95% CI: 1.74, 2.46) for central adiposity. The associations also were significant when adjusting for SSBs, instead of energy, in models. Conclusions Higher usual sodium excretion is associated with overweight/obesity and central adiposity among US adults.

Background: Higher levels of sodium and lower levels of potassium intake are associated with higher blood pressure. However, the shape and magnitude of these associations can vary by study participant characteristics or intake assessment method. Twenty-four–hour urinary excretion of sodium and potassium are unaffected by recall errors and represent all sources of intake, and were collected for the first time in a nationally representative US survey. Our objective was to assess the associations of blood pressure and hypertension with 24-hour urinary excretion of sodium and potassium among US adults. Methods: Cross-sectional data were obtained from 766 participants age 20 to 69 years with complete blood pressure and 24-hour urine collections in the 2014 National Health and Nutrition Examination Survey, a nationally representative survey of the US noninstitutionalized population. Usual 24-hour urinary electrolyte excretion (sodium, potassium, and their ratio) was estimated from ≤2 collections on nonconsecutive days, adjusting for day-to-day variability in excretion. Outcomes included systolic and diastolic blood pressure from the average of 3 measures and hypertension status, based on average blood pressure ≥140/90 and antihypertensive medication use. Results: After multivariable adjustment, each 1000-mg difference in usual 24-hour sodium excretion was directly associated with systolic (4.58 mm Hg; 95% confidence interval [CI], 2.64–6.51) and diastolic (2.25 mm Hg; 95% CI, 0.83–3.67) blood pressures. Each 1000-mg difference in potassium excretion was inversely associated with systolic blood pressure (–3.72 mm Hg; 95% CI, –6.01 to –1.42). Each 0.5 U difference in sodium-to-potassium ratio was directly associated with systolic blood pressure (1.72 mm Hg; 95% CI, 0.76–2.68). Hypertension was linearly associated with progressively higher sodium and lower potassium excretion; in comparison with the lowest quartile of excretion, the adjusted odds of hypertension for the highest quartile was 4.22 (95% CI, 1.36–13.15) for sodium, and 0.38 (95% CI, 0.17–0.87) for potassium ( P Conclusions: These cross-sectional results show a strong dose-response association between urinary sodium excretion and blood pressure, and an inverse association between urinary potassium excretion and blood pressure, in a nationally representative sample of US adults.

Because of the logistic complexity, excessive respondent burden, and high cost of conducting 24-h urine collections in a national survey, alternative strategies to monitor sodium intake at the population level need to be evaluated. We conducted a calibration study to assess the ability to characterize sodium intake from timed-spot urine samples calibrated to a 24-h urine collection. In this report, we described the overall design and basic results of the study. Adults aged 18–39 y were recruited to collect urine for a 24-h period, placing each void in a separate container. Four timed-spot specimens (morning, afternoon, evening, and overnight) and the 24-h collection were analyzed for sodium, potassium, chloride, creatinine, and iodine. Of 481 eligible persons, 407 (54% female, 48% black) completed a 24-h urine collection. A subsample (n = 133) collected a second 24-h urine 4–11 d later. Mean sodium excretion was 3.54 6 1.51 g/d for males and 3.09 6 1.26 g/d for females. Sensitivity analysis excluding those who did not meet the expected creatinine excretion criterion showed the same results. Day-to-day variability for sodium, potassium, chloride, and iodine was observed among those collecting two 24-h urine samples (CV = 16–29% for 24-h urine samples and 21–41% for timed-spot specimens). Among all race-gender groups, overnight specimens had larger volumes (P < 0.01) and lower sodium (P < 0.01 to P 5 0.26), potassium (P < 0.01), and chloride (P < 0.01) concentrations compared with other timed-spot urine samples, although the differences were not always significant. Urine creatinine and iodine concentrations did not differ by the timing of collection. The observed day-to-day and diurnal variations in sodium excretion illustrate the importance of accounting for these factors when developing calibration equations from this study. J. Nutr. 143: 1276–1282, 2013.

Compared to venipuncture, dried blood spots (DBS) can be collected by non-phlebotomists in non-clinical settings, is relatively inexpensive, more easily transported and stored conveniently. Disadvantages of DBS include difficult assay development and validation. This study compared DBS to venous methods for hemoglobin A1c, glucose, total cholesterol, high-density lipoprotein cholesterol, and C-reactive protein (CRP).DBS collection and venipuncture were performed on 401 participants. The DBS were collected on Whatman 903 protein saver card. For analysis, 3.2mm blood punches were placed into a 96-well microtiter plate for elution and then analyzed.The Pearson squared correlation coefficients were high for hemoglobin A1c (0.92), CRP (0.84) and glucose (0.81) and low for total cholesterol (0.34) and high-density lipoprotein (HDL) cholesterol (0.30). Sensitivity (82%) and specificity (90%) were high for CRP, glucose and hemoglobin A1c at selected clinical cut-points. Low sensitivity (41%) and high specificity (87%) were seen for total and HDL cholesterol.The hemoglobin A1c, glucose and CRP correlated well between DBS and venous methods (r(2)0.80), but there was a poor correlation for total and HDL cholesterol (r(2)0.34). This resulted in low sensitivity of DBS methods for total and HDL cholesterol.

BACKGROUND: Currently, no national prevalence is available on home blood pressure monitoring (HBPM). METHODS: This report is based on national-level, cross-sectional data for noninstitutionalized US adults aged ≥18 years (n = 6,001 participants) from the National Health and Nutrition Examination Survey (NHANES), 2009-2010. RESULTS: Overall, 21.7% of the population reported HBPM in the past year. Using 2010 Census data as a reference, approximately 33 million (14.5%) individuals engaged in monthly or more frequent HBPM. The frequency of HBPM increased with higher age, higher body mass index, higher family income-to-poverty ratio, and a higher number of health-care visits (all, P < 0.05). Adults with health-care coverage engaged in monthly or more frequent HBPM than adults without coverage (16.1% vs. 8.4%; P < 0.05). Among people with hypertension (blood pressure ≥140/90mm Hg or currently taking medication), 36.6% engaged in monthly or more frequent HBPM. Of those with hypertension whom were aware, treated, and controlled, 41.9%, 43.5%, and 42.1%, respectively, engaged in monthly or more frequent HBPM. Adjusting for covariables, those who were aware of, treated for, and controlled their hypertension were more likely to have a higher frequency of HBPM than the reference: unaware, untreated, and uncontrolled (odds ratio (OR) = 3.59; OR = 3.96; and OR = 1.50, respectively). CONCLUSIONS: Approximately 14.5% of adults engaged in monthly or more frequent HBPM. Being aware of hypertension, being pharmacologically treated, and being controlled were associated with an increased frequency of HBPM. Even among these categories of people with hypertension

Introduction: National efforts toward reducing population sodium intake necessitate developing a feasible and valid monitoring method, especially for the distribution tails given about 90% of the US population consumes more sodium than recommended. Objective: We developed and tested the validity of a statistical approach using one or two timed-spot urines to estimate population distribution of usual 24-hour sodium excretion. Methods: A convenience sample of 407 adults, 18-39 years of age, (54% female, 48% black) collected urine for a 24-hour period, placing each void in a separate container. Of these, 133 repeated the procedure 4-11 days later. Four timed-spot specimens (morning, afternoon, evening, and overnight) were selected from each 24-hour collection. We developed gender-specific equations using Fuller’s error-in-the-equation measurement error model to calibrate total sodium excreted in each of the one-spot (e.g., morning) and combined two-spot (e.g., morning + afternoon) urines to 24-hour sodium excretion. The calibrated sodium excretions were used to estimate the population distribution of usual 24-hour sodium excretion. Participants were then randomly assigned to modeling (n=160) or validation (n=247) groups to examine the bias in estimated population percentiles. Results: Median bias in predicting the 5 th , 25 th , 50 th , 75 th , and 95 th population percentiles of usual 24-hour sodium excretion with one-spot urine ranged from -367 to 284 mg (-7.7 to 12.2% of the observed usual excretions) for men and -604 to 486 mg (-14.6 to 23.7%) for women, and with two-spot urines from -338 to 263 mg (-6.9 to 10.4%) and -166 to 153 mg (-4.1 to 8.1%), respectively. Four of the six two-spot urine combinations produced no significant bias in predicting selected percentiles. Conclusions: Our approach to estimate the population distribution of usual 24-hour sodium excretion using calibrated spot urine sodium accounted for day-to-day variation and covariance between measurement errors, and produced percentile estimates with relatively low biases across low to high sodium levels. This may provide a low-burden, low-cost alternative to 24-hour collections in monitoring population sodium intake among healthy young adults and merits further investigation in other population subgroups.

Background: High US sodium intake and national reduction efforts necessitate developing a feasible and valid monitoring method across the distribution of low-to-high sodium intake. Objective: We examined a statistical approach using timed urine voids to estimate the population distribution of usual 24-h sodium excretion. Methods: A sample of 407 adults, aged 18–39 y (54% female, 48% black), collected each void in a separate container for 24 h; 133 repeated the procedure 4–11 d later. Four timed voids (morning, afternoon, evening, overnight) were selected from each 24-h collection. We developed gender-specific equations to calibrate total sodium excreted in each of the one-void (e.g., morning) and combined two-void (e.g., morning + afternoon) urines to 24-h sodium excretion. The calibrated sodium excretionswere used toestimate the populationdistribution ofusual 24-h sodium excretion.Participantswere thenrandomly assigned to modeling (n =1 60) or validation (n = 247) groups to examine the bias in estimated population percentiles. Results: Median bias in predicting selected percentiles (5th, 25th, 50th, 75th, 95th) of usual 24-h sodium excretion with onevoid urines ranged from 2367 to 284 mg (27.7 to 12.2% of the observed usual excretions) for men and 2604 to 486 mg (214.6 to 23.7%) for women, and with two-void urines from 2338 to 263 mg (26.9 to 10.4%) and 2166 to 153 mg (24.1 to 8.1%), respectively. Four ofthe 6 two-void urine combinations produced no significant bias in predicting selected percentiles. Conclusions: Our approach to estimate the population usual 24-h sodium excretion, which uses calibrated timed-void sodium to account for day-to-day variation and covariance between measurement errors, produced percentile estimates with relatively low biases across low-to-high sodium excretions. This may provide a low-burden, low-cost alternative to 24-h collections in monitoring population sodium intake among healthy young adults and merits further investigation in other population subgroups. This study was registered at clinicaltrials.gov as NCT01631240. JN utrdoi: 10.3945/jn.114.206250.

We developed and tested calibration equations from spot urine specimens to estimate the distribution of usual 24h sodium excretion (24UNa). A convenience sample of 407 adults, 18-39 y, (54% female,...

Because of the logistic complexity, excessive respondent burden, and high cost of conducting 24-h urine collections in a national survey, alternative strategies to monitor sodium intake at the population level need to be evaluated. We conducted a calibration study to assess the ability to characterize sodium intake from timed-spot urine samples calibrated to a 24-h urine collection. In this report, we described the overall design and basic results of the study. Adults aged 18–39 y were recruited to collect urine for a 24-h period, placing each void in a separate container. Four timed-spot specimens (morning, afternoon, evening, and overnight) and the 24-h collection were analyzed for sodium, potassium, chloride, creatinine, and iodine. Of 481 eligible persons, 407 (54% female, 48% black) completed a 24-h urine collection. A subsample (n = 133) collected a second 24-h urine 4–11 d later. Mean sodium excretion was 3.54 ± 1.51 g/d for males and 3.09 ± 1.26 g/d for females. Sensitivity analysis excluding those who did not meet the expected creatinine excretion criterion showed the same results. Day-to-day variability for sodium, potassium, chloride, and iodine was observed among those collecting two 24-h urine samples (CV = 16–29% for 24-h urine samples and 21–41% for timed-spot specimens). Among all race-gender groups, overnight specimens had larger volumes (P < 0.01) and lower sodium (P < 0.01 to P = 0.26), potassium (P < 0.01), and chloride (P < 0.01) concentrations compared with other timed-spot urine samples, although the differences were not always significant. Urine creatinine and iodine concentrations did not differ by the timing of collection. The observed day-to-day and diurnal variations in sodium excretion illustrate the importance of accounting for these factors when developing calibration equations from this study. J. Nutr. 143: 1276–1282, 2013.

Introduction: Reducing mean population sodium intake by ~1200 mg is projected to reduce thousands of deaths from heart disease and stroke and save billions of health care dollars annually. Twenty-four hour urine collection is recommended for assessing changes in mean population sodium intake, but can be difficult to implement. Predicting 24-hour urine sodium excretion using spot urines is not recommended due to diurnal variations in excretion. Further, sodium excretion patterns differ between black and white persons. We assessed the validity of previously published prediction equations for 24-hour sodium excretion in black and other young adults by timing of spot urine collection. Design: Of 481 adult volunteers aged 18-39 years (50% Blacks) asked to participate in a 2011 study in the Metropolitan DC area, 407 collected each urine void in a separate container for 24 hours. Four timed voids from the 24-h urine collection were selected (morning, afternoon, evening, and overnight) to use with previously published predictive equations. Predictive equations were based on one of two approaches; 1) an indirect approach using spot urine sodium-to-creatinine concentrations and predicted 24-hour creatinine excretion ( Tanaka, Kawasaki, Mage ), and 2) a direct approach using spot urine sodium, potassium, and creatinine concentrations, and age, and body mass index with separate equations by sex ( Brown ). We assessed mean differences between predicted and measured 24-hour sodium excretion (bias) and individual differences across levels of sodium excretion using Bland-Altman plots. Results: Among participants, mean measured 24-hour sodium excretion was ~3300 mg (SD ~1400 mg). Of the equations evaluated, mean bias in predicted 24-hour sodium excretion was least from Brown equations when using morning (-165 mg, 95% confidence interval [CI], -295, -36 mg), afternoon (-90 mg, 95% CI, -208, 28 mg) or evening ( -120 mg, 95% CI -230, -11 mg) spot urines. When using overnight spot urines, mean bias from Brown equations was greatest and statistically significant (-247 mg, 95% CI, -348, -151 mg). When using overnight spot urines, mean bias from Tanaka (-23 mg) or Mage (-145 mg) equations was not significant, however, when stratified by sex, mean biases were significant and in opposite directions. Among Blacks, mean biases from Brown were not significant (-167 to 122 mg) except using overnight specimens among Black females (-267 mg, 95% CI, -525, -47 mg). Across equations and time periods, Bland-Altman plots indicated significant bias at the individual level. Conclusions: Of the evaluated equations, predicted 24-hour urine sodium excretion using the Brown equations with morning, afternoon, or evening specimens may provide the least biased estimates of group mean sodium intake among young US adults. None of the equations adequately predicted individual 24-hour sodium excretion measured on the same day.