Abstract
BACKGROUND:
The associations of N-terminal pro-B-type natriuretic peptide (NT-pro-BNP) with dual energy x-ray absorptiometry (DEXA)-derived measures of body mass and composition are largely unknown.
METHODS:
We included participants aged ≥20 years from the 1999–2004 National Health and Nutrition Examination Survey with NT-pro-BNP and DEXA-derived body composition (fat and lean mass) measures. We used linear and logistic regression to characterize the associations of measures of body mass and composition (body mass index [BMI], waist circumference [WC], fat mass, and lean mass) with NT-pro-BNP, adjusting for cardiovascular risk factors.
RESULTS:
We conducted sex-specific analyses among 9134 adults without cardiovascular disease (mean age 44.4 years, 50.8% women, and 72% White adults). The adjusted mean NT-proBNP values were lowest in the highest quartiles of BMI, WC, fat mass, and lean mass. There were large adjusted absolute differences in NT-pro-BNP between the highest and lowest quartiles of DEXA-derived lean mass, −6.26 pg/mL (95% confidence interval [CI], −8.99 to −3.52) among men and −22.96 pg/mL (95% CI, −26.83 to −19.09) among women. Lean mass exhibited a strong inverse association with elevated NT-pro-BNP ≥ 81.4 pg/mL (highest quartile) - odds ratio (OR) 0.58 (95% CI, 0.39–0.86) in men and OR 0.59 (95% CI, 0.47–0.73) in women for highest lean mass quartile vs. lowest quartile. Further adjustment for fat mass, BMI, or WC did not appreciably alter the inverse association of lean mass with NT-pro-BNP.
CONCLUSIONS:
In a national sample of US adults, lean mass was inversely associated with NT-pro-BNP.
Introduction
N-terminal pro-B-type natriuretic peptide (NT-pro-BNP) is a member of the natriuretic peptides family, which are cardiac-derived hormones secreted in response to myocardial strain (1, 2). The effects of natriuretic peptides are ubiquitous, extending beyond the cardiovascular system, and include among other functions natriuresis, diuresis, vasodilation, lusitropy, lipolysis, weight loss, and improved insulin sensitivity (1). Mechanistic studies have shown an intricate relation between natriuretic peptides and obesity and insulin resistance, with natriuretic peptides receptors present in the adipose tissue, where their binding has a lipolytic effect (1, 3, 4). A number of population-based studies have described an inverse relation between obesity and natriuretic peptides levels (5–7), but these studies have typically focused on body mass index (BMI) or waist circumference (WC). Fat and lean mass measures (e.g., fat mass index [FMI, fat mass/height2] and lean mass index [LMI, lean mass/height2]) are more specific body composition measures than BMI or WC (8–10). These measures provide more precise information on the relative contributions of various body compartments to the metabolism and to disease risk. Indeed, knowing how NT-pro-BNP relates to lean mass can help us better understand and characterize the link between NT-pro-BNP and adiposity, as well as its physiological, clinical, and prognostic implications. There is a paucity of community-based studies of NT-pro-BNP that have evaluated dual energy x-ray absorptiometry (DEXA)-derived measures of fat and lean mass (11).
Using data from participants of the 1999–2004 National Health and Nutrition Examination (NHANES), we assessed the associations between measures of body composition (non-imaging based anthropometric [BMI and WC] and DEXA-derived measures [fat mass and lean mass]) and NT-pro-BNP in a nationally representative sample of US adults aged 20 years and older.
Methods
STUDY POPULATION
The NHANES is a nationally representative sample of the noninstitutionalized, civilian population in the US. We measured NT-pro-BNP in individuals with available stored blood samples in NHANES 1999–2004. A total of 12 374 nonpregnant participants aged ≥20 years in the NHANES 1999–2004 survey with a BMI ≥ 18.5 kg/m2 and who had body composition assessed by DEXA were eligible for this study. We excluded individuals with a history of cardiovascular disease (including coronary heart disease, stroke, and heart failure n = 1422) and those with missing data for NT-pro-BNP (n = 954) and for relevant covariates (n = 864). Our final sample for analysis included 9134 participants.
Informed consent was obtained from all participants. The NHANES protocols and the measurement of NT-pro-BNP in stored specimens was approved by the National Center for Health Statistics ethics review board.
BODY COMPOSITION ASSESSMENT
Height and weight, measured at the mobile examination center, were used to calculate BMI (kg/m2). WC was measured at the uppermost lateral border of the ilium using a tape measure. DEXA is a well-established and validated technique of measuring body composition, with total body mass divided into 3 compartments: bone, fat mass, and lean mass. DEXA scans were acquired using the QDR 4500A fan beam densitometer (Hologic, Inc.) and analyzed centrally (12). NHANES calibration from Schoeller et al. (13) was applied before results were publicly released. The DEXA-based measures include, among others, fat mass (kg), lean mass (kg), and percent fat, calculated as fat mass divided by total mass. FMI was calculated as fat mass/height2, and LMI was calculated as lean mass/height2.
N-TERMINAL PRO-B-TYPE NATRIURETIC PEPTIDE (NT-PRO-BNP) MEASUREMENT
We measured NT-pro-BNP in stored serum samples at the University of Maryland School of Medicine between 2018 and 2020. NT-pro-BNP was measured by electro-chemiluminescence immunoassay (Roche Diagnostics Corp.) on a Cobas e601 analyzer (Elecsys, Roche Diagnostics). The NT-pro-BNP assay had a coefficient of variation between 2.7% and 3.1%, and an upper and lower limit of detection of 35 000 and 5 pg/mL, respectively. Although the serum samples underwent long-term storage, prior studies have shown excellent stability of NT-pro-BNP when measured in long-term stored samples (14–16).
COVARIATES
Demographic and lifestyle information, including information on smoking, alcohol, and physical activity, was self-reported and collected using a computer-assisted personal interview system.
Hypertension was defined using a mean systolic blood pressure ≥140 mmHg, mean diastolic blood pressure ≥90 mmHg, or self-reported history of diagnosis by a healthcare provider. Hemoglobin A1C was measured by HPLC on the Primus CLC330 and Primus CLC385 instruments (Primus). We defined diabetes as a hemoglobin A1C ≥ 6.5% (48 mmol/mol) or self-reported history of diagnosis by a healthcare provider. Total cholesterol was measured using an enzymatic method. Hypercholesterolemia was defined as total cholesterol ≥240 mg/dL (6.2 mmol/L) or self-reported lipid-lowering medication use. Estimated glomerular filtration rate (eGFR) was estimated in mL/min/1.73m2 using the 2021 CKD-EPI equation based on creatinine and cystatin C (17).
STATISTICAL ANALYSIS
We summarized the baseline characteristics of the study population across quartiles of NT-pro-BNP using means and percentages. We accounted for the complex survey design and used survey weights in all analyses to obtain estimates that would be generalizable to the US adult population. Weights are used in NHANES to account for the complex survey design (including oversampling), survey nonresponse, and post-stratification adjustment to match total US population counts from the Census Bureau. Standard errors were obtained using Taylor series linearization.
Given known sex differences in body composition (18), all analyses were sex stratified. We used linear regression to estimate the adjusted mean of NT-pro-BNP (natural log-transformed) across categories of each of the body mass/composition measures (BMI, WC, lean mass, or fat mass). In addition to the adjusted mean differences (absolute differences) in NT-pro-BNP, we estimated the percent difference in NT-pro-BNP with 95% confidence intervals (CI) as: (eß-1) ×100, where ß was the coefficient from linear regression models. We also modeled the associations between measures of body mass/composition (BMI, WC, lean mass, or fat mass) and NT-pro-BNP using restricted cubic linear spline (4 knots, at sex-specific 5th, 35th, 65th and 95 percentiles) to allow for deviations from linearity. We further used multivariable logistic regression to evaluate the associations of measures of body mass and composition with elevated NT-pro-BNP, defined as levels ≥81.4 pg/mL, which correspond to values in the highest quartile of the distribution. We modeled measures of body mass and composition categorically, using restricted cubic splines. In addition to categorizing BMI according to sex-specific quartiles, we also categorized it as 18.5 to < 25 kg/m2 (reference group), 25 to < 30 kg/m2, 30 to < 35 kg/m2, and ≥35 kg/m2. We categorized WC, fat mass, and lean mass according to sex-specific quartiles with the lowest quartile serving as the reference group.
All models included age, race/ethnicity, education, alcohol use, smoking status, physical activity, hypertension, diabetes, hypercholesterolemia, and eGFR.
A two-sided P-value < 0.05 was considered statistically significant for all tests (including interaction tests). Stata version 17 was used for all analyses.
Results
CHARACTERISTICS OF STUDY PARTICIPANTS
Among the 9134 study participants weighted to the general US adult population, the mean age was 44.4 years, 50.8% were female, and 72% were White adults. Participants in the highest quartile of NT-pro-BNP were older; had a lower BMI; and were more likely to be physically active, female, White, and to have hypertension, hyperlipidemia, diabetes, or low eGFR (Table 1).
Table 1.
Characteristics of US adults aged 20 and older according to quartiles of NT-pro-BNP, NHANES 1999–2004.
| NT-pro-BNP category | Quartile 1 (<20.6 pg/mL) |
Quartile 2 (20.6-<42.0 pg/mL) |
Quartile (42.0-<81.4 pg/mL) |
Q4 (≥81.4 pg/mL) |
P value |
|---|---|---|---|---|---|
| Unweighted n | 2189 | 2119 | 2098 | 2728 | |
| Female, % (SE) | 22.1 (1.0) | 43.5 (1.2) | 64.0 (1.2) | 73.4 (0.8) | <0.001 |
| Age, mean (SE) | 36.8 (0.4) | 40.3 (0.3) | 44.7 (0.4) | 55.6 (0.4) | <0.001 |
| Race, % (SE) | <0.001 | ||||
| Non-Hispanic White | 59.3 (2.0) | 70.7 (1.8) | 77.1 (1.6) | 80.8 (1.8) | |
| Non-Hispanic Black | 15.9 (1.5) | 11.1 (1.0) | 7.5 (0.9) | 7.4 (1.0) | |
| Mexican American | 10.6 (1.2) | 8.2 (1.1) | 6.1 (0.8) | 4.0 (0.7) | |
| Other race/ethnicity | 14.2 (1.9) | 9.9 (1.5) | 9.2 (1.2) | 7.7 (1.3) | |
| Education, % (SE) | <0.001 | ||||
| Less than high school | 19.4 (1.0) | 17.7 (1.0) | 15.2 (0.9) | 20.4 (1.1) | |
| High school | 24.9 (1.5) | 23.6 (1.1) | 28.1 (1.2) | 28.3 (1.1) | |
| AA degree | 30.7 (1.2) | 33.1 (1.4) | 29.9 (1.2) | 27.9 (1.1) | |
| College graduate and above | 25.0 (1.6) | 25.6 (1.6) | 26.8 (1.4) | 23.4 (1.6) | |
| Smoking, % (SE) | <0.001 | ||||
| Never | 53.3 (1.6) | 51.4 (1.6) | 50.9 (1.4) | 47.4 (1.1) | |
| Former | 19.8 (1.0) | 21.4 (1.3) | 25.4 (1.2) | 29.3 (1.2) | |
| Current | 26.9 (1.4) | 27.1 (1.4) | 23.7 (1.1) | 23.4 (1.0) | |
| Drinking, % (SE) | <0.001 | ||||
| Never | 9.9 (1.4) | 10.1 (1.2) | 12.3 (1.3) | 15.6 (1.4) | |
| Former | 12.9 (1.2) | 12.6 (1.0) | 15.2 (1.2) | 20.1 (1.1) | |
| Moderate | 34.7 (1.6) | 35.9 (1.8) | 34.4 (1.6) | 34.1 (1.6) | |
| Heavy | 42.5 (1.6) | 41.4 (1.6) | 38.0 (1.4) | 30.3 (1.5) | |
| Physically activea, % (SE) | 66.7 (1.6) | 67.2 (1.6) | 67.0 (1.4) | 60.7 (1.4) | <0.001 |
| Diabetes, % (SE) | 4.6 (0.6) | 4.8 (0.6) | 4.9 (0.5) | 7.6 (0.6) | <0.001 |
| Hypertension, % (SE) | 25.3 (1.1) | 23.4 (1.3) | 30.5 (1.1) | 48.0 (1.2) | <0.001 |
| Hyperlipidemia, % (SE) | 30.2 (1.1) | 29.3 (1.4) | 32.7 (1.1) | 39.2 (1.4) | <0.001 |
| eGFR (mL/min/1.73 m2), median (Q1-Q3) | 114.4 (104.5–122.9) | 112.6 (103.3–121.1) | 108.1 (97.7–118.4) | 97.9 (80.8–110.3) | <0.001 |
| Waist circumference (cm), Male, mean (SE) | 98.1 (0.4) | 98.9 (0.5) | 100.7 (0.7) | 103.0 (0.7) | 0.065 |
| Waist circumference (cm), Female, mean (SE) | 96.6 (0.8) | 92.9 (0.6) | 92.1 (0.6) | 93.3 (0.6) | <0.001 |
| BMI (kg/m2), male, mean (SE) | 28.0 (0.1) | 28.0 (0.2) | 28.1 (0.3) | 28.0 (0.3) | <0.001 |
| BMI (kg/m2), female, mean (SE) | 30.2 (0.4) | 28.5 (0.2) | 27.9 (0.3) | 28.0 (0.2) | 0.888 |
| FMI (kg/m2), male, mean (SE) | 7.9 (0.1) | 8.0 (0.1) | 8.3 (0.2) | 8.6 (0.2) | 0.003 |
| FMI (kg/m2), female, mean (SE) | 12.7 (0.2) | 11.8 (0.2) | 11.5 (0.2) | 11.8 (0.2) | <0.001 |
| LMI (kg/m2), male, mean (SE) | 20.3 (0.1) | 20.2 (0.1) | 20.0 (0.1) | 19.5 (0.2) | <0.001 |
| LMI (kg/m2), female, mean (SE) | 17.8 (0.2) | 17.0 (0.1) | 16.7 (0.1) | 16.5 (0.1) | <0.001 |
IQR, interquartile range.
Percentage of physically active; defined as physical activity levels ≥ 500 metabolic equivalent/min/week
DIFFERENCES IN NT-PRO-BNP ACROSS LEVELS OF BODY COMPOSITION MEASURES
Restricted cubic splines of the association of measures of body mass/composition and NT-pro-BNP showed an inverse association for BMI, WC, and lean mass in women, whereas the corresponding associations were roughly U-shaped in men and for fat mass in women (Fig. 1).
Fig. 1.
Associations of measures of body composition measures with NT-pro-BNP levels (log transformed). (A), WC; (B), BMI; (C), FMI; and (D), LMI. All the body composition measures were modeled as sex-specific restricted cubic splines with knots at the 5th, 35th, 65th, and 95th percentiles. The regression models were adjusted by age, race, education, drinking, smoking, physical activity, diabetes, high-cholesterol, hypertension, eGFR (linear spline with knot at 60 mL/min/1.73 m2). Models for FMI were additionally adjusted by LMI (continuously), and vice versa. Predictions were made with average of all covariates.
The adjusted absolute values of NT-pro-BNP were lower at higher categories of BMI, WC, fat mass, and lean mass compared to lower categories among women and men (Table 2). These patterns were not always obvious for all measures of body composition when examining un-adjusted values only, an example being that of crude values of WC across quartiles (Table 2). The lower values of NT-pro-BNP in higher categories of lean mass or fat mass persisted after accounting for the other body composition measures, e.g., adjustment for fat mass when assessing lean mass and adjustment for lean mass adjustment when assessing fat mass (Table 2). The association of lean mass and fat mass with NT-pro-BNP also persisted after accounting for BMI or WC (Table 2). In men, the adjusted absolute difference in NT-pro-BNP between those in the highest and lowest quartiles of BMI was −6.17 pg/mL (95% CI, −9.02 to −3.31); the corresponding difference between highest and lowest quartiles were −4.75 pg/mL (95%CI, −7.83 to −1.67) for WC, −6.02 pg/mL (95% CI, −9.04 to −3.00) for fat mass, and −6.26 pg/mL (95% CI, −8.99 to −3.52) for lean mass, respectively (Table 2). In women, the equivalent values of for the absolute differences between the highest and lowest quartiles of BMI, WC, fat mass, and lean mass were as follows: −20.36 pg/mL (95% CI, −25.59 to −15.13), −20.53 pg/mL (95% CI, −26.12 to −14.93), −17.42 pg/mL (95% CI, −22.99 to −11.85), and −22.96 pg/mL (95% CI, −26.83 to −19.09), respectively (Table 2).
Table 2.
Adjusted absolute difference (95% CI) in NT-pro-BNP according to measures of body composition among US adults aged 20 or older, NHANES 1999–2004.
| Men | Women | |||||||
|---|---|---|---|---|---|---|---|---|
| NT-pro-BNP | Waist circumference (cm)—Quartiles | Waist Circumference (cm)—Quartiles | ||||||
| Q1 (62.4–89.3) | Q2 (89.4–97.9) | Q3 (98.0–107.9) | Q4 (108.0–173.4) | Q1 (62.0–81.3) | Q2 (81.4–90.8) | Q3 (90.9–102.4) | Q4 (102.5–155.9) | |
| Mean (95% CI), pg/mL | 23.4 (21.6–25.3) | 26.8 (24.7–29.1) | 28.8 (26.9–30.8) | 32.4 (30.2–34.8) | 63.09 (59.00–67.46) | 62.88 (58.72–67.33) | 61.83 (57.91–66.01) | 59.11 (55.68–62.75) |
| Adjusted absolute Difference, pg/mL | 0 | −3.39 (−6.08, −0.71) | −6.21 (−8.71, −3.71) | −4.75 (−7.83, −1.67) | 0 | −9.62 (−15.39, −3.84) | −17.87 [−23.35, −12.38] | −20.53 [−26.12, −14.93] |
| Body Mass Index (kg/m2)—Clinical Categories | Body Mass Index (kg/m2)—Clinical Categories | |||||||
| 18.5–<25 kg/m2 | 25–<30 kg/m2 | 30–<35 kg/m2 | BMI ≥ 35 kg/m2 | 18.5–<25 kg/m2 | 25–<30 kg/m2 | 30–<35 kg/m2 | BMI ≥ 35 kg/m2 | |
| Mean (95% CI), pg/mL | 28.71 (26.49–31.12) | 26.69 (25.12–28.36) | 27.56 (24.89–30.51) | 28.99 (25.75–32.63) | 67.11 (63.97–70.40) | 62.64 (58.88–66.64) | 56.30 (52.01–60.94) | 54.18 (49.93–58.78) |
| Adjusted absolute Difference, pg/mL | 0 | −6.19 (−8.83, −3.56) | −5.98 (−8.96, −3.00) | −3.78 (−7.23, −0.34) | 0 | −10.68 (−14.72, −6.64) | −15.82 (−20.35, −11.30) | −17.34 (−21.73, −12.95) |
| Body Mass Index (kg/m2)—Quartiles | Body Mass Index (kg/m2)—Quartiles | |||||||
| Q1 (18.5–24.4) | Q2 (24.4–27.3) | Q3 (27.3–30.5) | Q4 (30.5–64.2) | Q1 (18.5–23.2) | Q2 (23.2–26.8) | Q3 (26.9–32.0) | Q4 (32.0–66.4) | |
| Mean (95% CI), pg/mL | 29.32 (26.94–31.90) | 27.43 (25.19–29.85) | 25.67 (23.81–27.67) | 28.38 (26.33–30.59) | 67.45 (62.61–72.67) | 65.12 (61.27–69.23) | 60.80 (56.06–65.94) | 54.27 (50.67–58.13) |
| Adjusted absolute Difference, pg/mL | 0 | −5.28 (−8.47, −2.08) | −8.39 (−11.53, −5.26) | −6.17 (−9.02, −3.31) | 0 | −9.37 (−15.15, −3.60) | −15.14 (−20.50, −9.77) | −20.36 (−25.59, −15.13) |
| Fat Mass Index (kg/m2)—Quartiles | Fat Mass Index (kg/m2)—Quartiles | |||||||
| Q1 (2.2–6.0) | Q2 (6.0–7.7) | Q3 (7.7–9.6) | Q4 (9.6–27.7) | Q1 (3.7–8.4) | Q2 (8.4–11.0) | Q3 (11.0–14.2) | Q4 (14.2–36.4) | |
| Mean (95% CI), pg/mL | 25.99 (23.93–28.23) | 24.86 (22.74–27.18) | 27.12 (25.15–29.24) | 30.10 (27.63–32.78) | 63.05 (58.69–67.73) | 62.62 (58.17–67.42) | 57.32 (53.02–61.97) | 58.00 (53.65–62.70) |
| Adjusted absolute Difference (95% CI), pg/mL | 0 | −7.38 (−10.41, −4.35) | −7.31 (−10.36, −4.25) | −6.02 (−9.04, −3.00) | 0 | −11.34 (−16.94, −5.75] | −17.61 (−22.61, −12.60) | −17.42 (−22.99, −11.85) |
| Adjusted absolute Difference (95% CI), pg/mL—LMI adjustmenta | 0 | −5.88 (8.88 to −2.88) | −4.93 (−7.95 to −1.91) | −2.49 (−5.91–0.92) | 0 | −7.28 (−13.06 to −1.50) | −8.26 (−14.52 to −2.00) | 0.17 (−9.68–10.01) |
| Adjusted absolute Difference (95% CI), pg/mL—BMI adjustmenta | 0 | −5.88 (−8.88 to −2.88) | −4.93 (−7.95 to −1.91) | −2.49 (−5.91–0.92) | 0 | −7.28 (−13.06 to −1.50) | −8.26 (−14.52 to −2.00) | 0.17 (−9.68–10.01) |
| Adjusted absolute Difference (95% CI), pg/mL—WC adjustmenta | 0 | −5.00 (−8.12 to −1.88) | −3.51 (−7.09–0.07) | 0.23 (−4.70–5.15) | 0 | −4.04 (−10.77–2.69) | −3.28 (−11.84–5.28) | 9.00 (−6.49–24.48) |
| Lean Mass Index (kg/m2)—Quartiles | Lean Mass Index (kg/m2)—Quartiles | |||||||
| Q1 (13.5–18.3) | Q2 (18.3–19.9) | Q3 (19.9–21.5) | Q4 (21.5–38.0) | Q1 (11.4–14.9) | Q2 (14.9–16.3) | Q3 (16.3–18.2) | Q4 (18.2–31.6) | |
| Mean (95% CI), pg/mL | 32.18 (29.28–35.36) | 27.66 (25.37–30.17) | 24.66 (22.71–26.79) | 22.29 (20.63–24.08) | 74.12 (69.34–79.23) | 63.40 (59.49–67.56) | 58.08 (53.47–63.08) | 45.49 (42.09–49.17) |
| Adjusted absolute Difference (95% CI), pg/mL | 0 | −2.97 (−5.55 to −0.39) | −6.02 (−8.90 to −3.14) | −6.26 (−8.99 to −3.52) | 0 | −6.48 (−11.59 to −1.36) | −12.33 [−18.46 to −6.20] | −22.96 (−26.83 to −19.09] |
| Adjusted absolute Difference (95% CI), pg/mL—FMI adjustmenta | 0 | −2.66 (−5.19 to −0.13) | −5.50 (−8.59 to −2.42) | −5.41 (−8.82 to −1.99) | 0 | −6.53 (−11.88 to −1.19) | −12.47 [−19.13 to −5.81] | −23.18 (−29.47 to −16.90) |
| Adjusted absolute Difference (95% CI), pg/mL—BMI adjustmenta | 0 | −2.33 (−5.02–0.35) | −4.97 (−8.81 to −1.12) | −4.58 (−9.49–0.33) | 0 | −6.25 (−11.86 to −0.63) | −11.84 (−19.13 to −4.56) | −22.16 (−30.55 to −13.77) |
| Adjusted absolute Difference (95% CI), pg/mL—WC adjustmenta | 0 | −2.45 (−4.93–0.04) | −5.13 (−8.29 to −1.96) | −4.84 (−8.31 to −1.38) | 0 | −4.40 (−9.48–0.67) | −7.61 (−14.55 to −0.67) | −15.52 (−22.76 to −8.28) |
Differences in means were adjusted for age, race, education, drinking, smoking, physical activity, diabetes, high cholesterol, hypertension, and estimated glomerular filtration rate (linear spline at 60).
indicates additional adjustment for the mentioned variable.
A similar pattern of results was observed when examining the percent differences in NT-pro-BNP across levels of BMI, WC, FMI, and LMI (Table 3). After adjusting for age, race, education, drinking, smoking, physical activity, diabetes, high cholesterol, hypertension, and eGFR, the levels of NT-pro-BNP in the highest quartile of LMI vs. the lowest quartile of LMI was −20.53 % (95% CI, −28.10, −12.16) lower in men and 32.43% (95% CI, −36.94 to −27.60) lower in women (Table 3). Although the magnitude of the percent difference was attenuated with further adjustment for BMI, WC, or FMI, it remained statistically significant (Table 3).
Table 3.
Adjusted percent difference (95% CI) in NT-pro-BNP according to measures of body composition among US adults aged 20 or older, NHANES 1999–2004.
| Men | Women | |||||||
|---|---|---|---|---|---|---|---|---|
| NT-pro-BNP | Waist Circumference—Quartiles | Waist Circumference—Quartiles | ||||||
| Q1 (62.4–89.3) | Q2 (89.4–97.9) | Q3 (98.0–107.9) | Q4 (108.0–173.4) | Q1 (62.0–81.3) | Q2 (81.4–90.8) | Q3 (90.9–102.4) | Q4 (102.5–155.9) | |
| Mean (95% CI), pg/mL | 23.4 (21.6–25.3) | 26.8 (24.7–29.1) | 28.8 (26.9–30.8) | 32.4 (30.2–34.8) | 63.09 (59.00–67.46) | 62.88 (58.72–67.33) | 61.83 (57.91–66.01) | 59.11 (55.68–62.75) |
| % difference (95%CI) | 0 | −10.83 (−18.67 to −2.24) | −19.80 (−26.57 to −12.41) | −15.20 (−23.81 to −5.62) | −12.97 (−20.02 to −5.29) | −24.00 (−30.19 to −17.26) | −27.45 (−33.59 to −20.74) | |
| Body Mass Index (kg/m2)—Clinical Categories | Body Mass Index (kg/m2)—Clinical Categories | |||||||
| 18.5–<25 kg/m2 | 25–<30 kg/m2 | 30–<35 kg/m2 | BMI ≥ 35 kg/m2 | 18.5–<25 kg/m2 | 25–<30 kg/m2 | 30–<35 kg/m2 | BMI ≥ 35 kg/m2 | |
| Mean (95% CI), pg/mL | 28.71 (26.49–31.12) | 26.69 (25.12–28.36) | 27.56 (24.89–30.51) | 28.99 (25.75–32.63) | 67.11 (63.97–70.40) | 62.64 (58.88–66.64) | 56.30 (52.01–60.94) | 54.18 (49.93–58.78) |
| % difference (95% CI) | 0 | −19.43 (−26.50 to −11.68) | −18.77 (−26.94 to −9.70) | −12.06 (−21.84 to −1.05) | −15.04 (−20.37 to −9.35) | −22.34 (−28.17 to −16.04) | −24.30 (−29.92 to −18.22) | |
| Body Mass Index (kg/m2)—Quartiles | Body Mass Index (kg/m2)—Quartiles | |||||||
| Q1 (18.5–24.4) | Q2 (24.4–27.3) | Q3 (27.3–30.5) | Q4 (30.5–64.2) | Q1 (18.5–23.2) | Q2 (23.2–26.8) | Q3 (26.9–32.0) | Q4 (32.0–66.4) | |
| Mean (95% CI), pg/mL | 29.32 (26.94–31.90) | 27.43 (25.19–29.85) | 25.67 (23.81–27.67) | 28.38 (26.33–30.59) | 67.45 (62.61–72.67) | 65.12 (61.27–69.23) | 60.80 (56.06–65.94) | 54.27 (50.67–58.13) |
| % difference (95% CI) | 0 | −16.12 (−24.79 to −6.46) | −25.58 (−33.33 to −16.93) | −18.91 (−26.16 to −10.95) | 0 | −12.74 (−19.95 to −4.89) | −20.55 (−27.02 to −13.50) | −27.61 (−33.54 to −21.16) |
| Fat Mass Index (kg/m2)—Quartiles | Fat Mass Index (kg/m2)—Quartiles | |||||||
| Q1 (2.2–6.0) | Q2 (6.0–7.7) | Q3 (7.7–9.6) | Q4 (9.6–27.7) | Q1 (3.7–8.4) | Q2 (8.4–11.0) | Q3 (11.0–14.2) | Q4 (14.2–36.4) | |
| Mean (95% CI), pg/mL | 25.99 (23.93–28.23) | 24.86 (22.74–27.18) | 27.12 (25.15–29.24) | 30.10 (27.63–32.78) | 63.05 (58.69–67.73) | 62.62 (58.17–67.42) | 57.32 (53.02–61.97) | 58.00 (53.65–62.70) |
| % difference (95% CI) | 0 | −23.06 (−30.93 to −14.30) | −22.81 (−30.63 to −14.10) | −18.73 (−26.67 to −9.93) | 0 | −15.74 (−22.84 to −7.97) | −24.46 (−30.40 to −18.01) | −24.23 (−30.93 to −16.87) |
| % difference (95% CI)—LMI adjustmenta | 0 | −19.45 (−27.96 to −9.93) | −16.30 (−25.00 to −6.59) | −8.19 (−18.57–3.52) | 0 | −11.28 (−19.44 to −2.30) | −12.85 (−21.55 to −3.19) | 0.08 (−14.44–17.07) |
| % difference (95% CI)—BMI adjustmenta | 0 | −17.22 (−26.41 to −6.87) | −12.08 (−23.01–0.41) | 0.83 (−15.24–19.95) | 0 | −6.69 (−16.85–4.72) | −5.54 (−18.52–9.52) | 14.46 (−10.24–45.96) |
| % difference (95% CI)—WC adjustmenta | 0 | −19.32 (−28.03 to −9.56) | −16.22 (−27.17 to −3.61) | −7.29 (−23.05–11.71) | 0 | −7.90 (−16.47–1.55) | −8.09 (−18.83–4.06) | 5.22 (−9.12–21.84) |
| Lean Mass Index (kg/m2)—Quartiles | Lean Mass Index (kg/m2)—Quartiles | |||||||
| Q1 (13.5–18.3) | Q2 (18.3–19.9) | Q3 (19.9–21.5) | Q4 (21.5–38.0) | Q1 (11.4–14.9) | Q2 (14.9–16.3) | Q3 (16.3–18.2) | Q4 (18.2–31.6) | |
| Mean (95% CI), pg/mL | 32.18 (29.28–35.36) | 27.66 (25.37–30.17) | 24.66 (22.71–26.79) | 22.29 (20.63–24.08) | 74.12 (69.34–79.23) | 63.40 (59.49–67.56) | 58.08 (53.47–63.08) | 45.49 (42.09–49.17) |
| % difference (95% CI) | 0 | −9.78 (−17.69 to −1.11) | −19.73 (−27.80 to −0.77) | −20.53 (−28.10 to −12.16) | 0 | −9.07 (−15.91 to −1.68) | −17.36 (−25.32 to −8.55) | −32.43 (−36.94 to −27.60) |
| % difference (95% CI)—FMI adjustmenta | 0 | −8.88 (−16.76 to −0.26) | −18.32 (−27.11 to −8.46) | −18.02 (−27.89 to −6.81) | 0 | −9.13 (−16.18 to −1.47) | −17.49 (−25.97 to −8.04) | −32.64 (−39.97 to −24.43) |
| % difference (95% CI)—BMI adjustmenta | 0 | −7.92 (−16.30–1.31) | −16.76 (−27.79–4.05) | −15.49 (−29.79–1.71) | 0 | −8.24 (−16.09–0.33) | −17.19 (−26.39 to −6.85) | −16.26 (−26.48 to −4.62) |
| % difference (95% CI)—WC adjustmenta | 0 | −8.77 (−16.18 to −0.71) | −16.71 (−25.92 to −6.35) | −31.40 (−41.13 to −20.07) | −6.51 (−13.69 to 1.27) | −11.32 (−20.86 to −0.63) | −23.19 (−32.43 to −12.67) | |
Differences were adjusted for age, race, education, drinking, smoking, physical activity, diabetes, high cholesterol, hypertension, and estimated glomerular filtration rate (Iinear spline at 60).
indicates additional adjustment for the mentioned variable.
In supplementary analyses, there was no interaction between the age and measures of body composition with NT-pro-BNP (Supplemental Fig. 1). In sensitivity analyses, associations of body composition measures with NT-pro-BNP in women not taking oral contraceptives were similar to those in all women (Supplemental Fig. 2; Supplemental Table 1).
ASSOCIATION OF BODY COMPOSITION MEASURES WITH ELEVATED NT-PRO-BNP
In multivariable adjusted logistic regression models, the odds of having an elevated NT-pro-BNP (≥81.4 pg/mL) were significantly lower among individuals with the higher quartiles of BMI, WC, fat mass, and lean mass, as compared to those in the lowest quartiles (Table 4). A lower odds of having an elevated NT-pro-BNP was observed when comparing the highest vs. lowest quartile of lean mass among men (odds ratio [OR]: 0.58, 95% CI, 0.39–0.86) and among women (OR: 0.59, 95% CI, 0.47–0.73). The results for lean mass were not appreciably different after further adjustment for measures of adiposity (Table 4), including fat mass (0.51 [95% CI, 0.29–0.91] in men and 0.51 [95% CI, 0.37–0.70] in women), BMI (0.48 [95% CI, 0.24–0.94] in men and 0.47 [95% CI, 0.32–0.69] in women), or WC (0.49 [95% CI, 0.28–0.87] in men and 0.69 [95% CI, 0.53–0.91] in women).
Table 4.
Association of measures of body composition and elevated NT-pro-BNP(≥ 125 pg/mL) among US adults aged 20 or older, NHANES 1999–2004.
| Men | Women | |||||||
|---|---|---|---|---|---|---|---|---|
| Waist Circumference (cm)—Quartiles | Waist Circumference (cm)—Quartiles | |||||||
| Q1 (62.4–89.3) | Q2 (89.4–97.9)) | Q3 (98.0–107.9) | Q4 (108.0–173.4) | Q1 (62.0–81.3) | Q2 (81.4–90.8) | Q3 (90.9–102.4) | Q4 (102.5–155.9) | |
| % with elevated NT-pro-BNP (95% CI) | 9.06 (0.99) | 11.76 (0.95) | 16.33 (1.08) | 16.81 (1.10) | 33.77 (1.88) | 37.77 (2.00) | 39.11 (1.40) | 33.99 (1.61) |
| Odds ratio (95% CI) | 1.00 (Reference) | 0.68 (0.49–0.94) | 0.70 (0.47–1.04) | 0.61 (0.43–0.87) | 1.00 (Reference) | 0.91 (0.70–1.20) | 0.75 (0.59–0.96) | 0.55 (0.42–0.74) |
| Body Mass Index—Clinical Categories | Body Mass Index—Clinical Categories | |||||||
| 18.5–<25 kg/m2 | 25–<30 kg/m2 | 30–<35 kg/m2 | BMI ≥ 35 kg/m2 | 18.5–<25 kg/m2 | 25–<30 kg/m2 | 30–<35 kg/m2 | BMI ≥ 35 kg/m2 | |
| % with elevated NT-pro-BNP (95% CI) | 13.61 (1.18) | 13.37 (0.72) | 14.07 (1.42) | 12.62 (1.88) | 37.61 (1.47) | 37.15 (1.49) | 34.35 (1.77) | 32.82 (2.23) |
| Odds ratio (95% CI) | 1.00 (Reference) | 0.68 (0.50–0.91) | 0.71 (0.49–1.04) | 0.67 (0.44–1.02) | 1.00 (Reference) | 0.79 (0.65–0.97) | 0.70 (0.55–0.89) | 0.67 (0.51–0.89) |
| Body Mass Index—Quartiles | Body Mass Index—Quartiles | |||||||
| Q1 (18.5–24.4) | Q2 (24.4–27.3) | Q3 (27.3–30.5) | Q4 (30.5–64.2) | Q1 (18.5–23.2) | Q2 (23.2–26.8) | Q3 (26.9–32.0) | Q4 (32.0–66.4) | |
| % with elevated NT-pro-BNP (95% CI) | 14.06 (1.27) | 13.38 (0.99) | 12.93 (1.01) | 13.68 (1.11) | 36.38 (1.97) | 39.11 (1.62) | 36.57 (1.79) | 32.59 (1.69) |
| Odd ratio (95% CI) | 1.00 (Reference) | 0.68 (0.49–0.94) | 0.61 (0.42–0.87) | 0.64 (0.47–0.89) | 1.00 (Reference) | 0.91 (0.73–1.15) | 0.76 (0.60–0.96) | 0.65 (0.51–0.83) |
| Fat Mass Index (kg/m2)—Quartiles | Fat Mass Index (kg/m2)—Quartiles | |||||||
| Q1 (2.2–6.0) | Q2 (6.0–7.7) | Q3 (7.7–9.6) | Q4 (9.6–27.7) | Q1 (3.7–8.4) | Q2 (8.4–11.0) | Q3 (11.0–14.2) | Q4 (14.2–36.4) | |
| % with elevated NT-pro-BNP (95% CI) | 11.13 (1.14) | 12.12 (1.04) | 13.79 (1.09) | 17.01 (1.25) | 35.22 (2.05) | 37.76 (1.70) | 36.42 (1.63) | 35.24 (1.69) |
| Odds ratio (95% CI) | 1.00 (Reference) | 0.54 (0.36–0.81) | 0.51 (0.33–0.80) | 0.61 (0.43–0.87) | 1.00 (Reference) | 0.78 (0.61–1.01) | 0.68 (0.56–0.82) | 0.65 (0.50–0.85) |
| Odds ratio (95% CI)—LMI adjustmenta | 1.00 (Reference) | 0.58 (0.37–0.89) | 0.58 (0.35–0.95) | 0.77 (0.46–1.28) | 1.00 (Reference) | 0.82 (0.63–1.06) | 0.76 (0.61–0.95) | 0.84 (0.56–1.27) |
| Odds ratio (95% CI)—BMI adjustmenta | 1.00 (Reference) | 0.57 (0.37–0.88) | 0.56 (0.33–0.96) | 0.73 (0.39–1.38) | 1.00 (Reference) | 0.80 (0.61–1.05) | 0.71 (0.52–0.96) | 0.72 (0.40–1.29) |
| Odds ratio (95% CI)—WC adjustmenta | 1.00 (Reference) | 0.52 (0.34–0.82) | 0.49 (0.29–0.83) | 0.56 (0.29–1.09) | 1.00 (Reference) | 0.87 (0.67–1.15) | 0.86 (0.64–1.15) | 1.01 (0.62–1.67) |
| Lean Mass Index (kg/m2)—Quartiles | Lean Mass Index (kg/m2)—Quartiles | |||||||
| Q1 (13.5–18.3) | Q2 (18.3–19.9) | Q3 (19.9–21.5) | Q4 (21.5–38.0) | Q1 (11.4–14.9) | Q2 (14.9–16.3) | Q3 (16.3–18.2) | Q4 (18.2–31.6) | |
| % with elevated NT-pro-BNP (95% CI) | 19.11 (1.43) | 13.27 (1.03) | 12.00 (1.05) | 9.67 (1.04) | 42.72 (1.94) | 38.43 (1.70) | 34.47 (1.64) | 29.10 (1.63) |
| Odds ratio (95% CI) | 1.00 (Reference | 0.69 (0.50–0.95) | 0.66 (0.47–0.94) | 0.58 (0.39–0.86) | 1.00 (Reference) | 0.93 (0.72–1.19) | 0.75 (0.58–0.98) | 0.59 (0.47–0.73) |
| Odds ratio (95% CI)—FMI adjustmenta | 1.00 (Reference) | 0.67 (0.49–0.92) | 0.63 (0.43–0.92) | 0.51 (0.29–0.91) | 1.00 (Reference) | 0.91 (0.71–1.16) | 0.70 (0.53–0.93) | 0.51 (0.37–0.70) |
| Odds ratio (95% CI)—BMI adjustmenta | 1.00 (Reference) | 0.65 (0.47–0.90) | 0.60 (0.39–0.92) | 0.48 (0.24–0.94) | 1.00 (Reference) | 0.89 (0.69–1.15) | 0.68 (0.50–0.92) | 0.47 (0.32–0.69) |
| Odds ratio (95% CI)—WC adjustmenta | 1.00 (Reference) | 0.66 (0.48–0.90) | 0.61 (0.41–0.91) | 0.49 (0.28–0.87) | 1.00 (Reference)0 | 0.96 (0.75–1.22) | 0.81 (0.61–1.08) | 0.69 (0.53–0.91) |
Odds ratios were adjusted for age, race, education, drinking, smoking, physical activity, diabetes, high cholesterol, hypertension, estimated glomerular fraction (linear spline at 60).
Elevated NT-pro-BNP corresponds to NT-pro-BNP ≥ 125 pg/mL.
indicates additional adjustment for the mentioned variable.
Discussion
In a nationally representative population of US adults, we made a number of observations related to the link between measures of body composition and NT-pro-BNP levels among adults free of cardiovascular disease. First, we confirmed the previously described inverse relation between BMI or WC and NT-pro-BNP levels among women. We further clarified the relation of BMI or WC with NT-pro-BNP in men, in whom it may be more U-shaped. Second, the DEXA-derived measures of body mass/composition, especially the lean mass, exhibited an inverse association with NT-pro-BNP, and this association persisted even after accounting for fat mass, BMI, or WC. Third, our results also highlight the sex differences in the association between the measures of body composition/mass and NT-pro-BNP, with stronger associations in women than in men. Our findings provide additional insight into the relation between natriuretic peptide levels in subjects and measures of body composition by showing the extent of the independent association of lean mass with the levels of NT-pro-BNP above and beyond adiposity (irrespective of the approach used to evaluate adiposity). The association of lean mass and NT-proBNP and its potential implications is underrecognized.
Our results extend previous studies of natriuretic peptides, which have primarily used BMI as a measure of body mass or composition (5, 6, 19, 20). Our investigation specifically points out the importance of lean mass as a correlate of the circulating levels of NT-pro-BNP irrespective of adiposity. These findings suggest possible metabolic influences above and beyond the adipose tissue, especially given the role of muscle in metabolic regulation. It is also possible that lean mass, which mainly captures skeletal muscle mass, reflects the overall exercise capacity and thus myocardial health. While a number of studies have examined the relation of body fat distribution and natriuretic peptides (7, 21), the vast majority have not included measures of lean mass. In the present study, we examined a wide spectrum of body composition measures including fat mass and lean mass. Our results are consistent with those of a prior community-based study, the Dallas Heart Study (11), which showed that lean mass, but not fat mass, was inversely related to both brain natriuretic peptide (BNP) and NT-pro-BNP levels. The Japanese J-SHIPP study also showed an inverse association between muscle mass and BNP levels (22). Among athletes, who tend to have higher lean mass, lower levels of NT-pro-BNP levels were present after several weeks of endurance training as compared to controls (23). We also demonstrated that lean mass is an important determinant of NT-pro-BNP levels above and beyond adiposity (as assessed by either fat mass, BMI, or WC) in the general US adult population. Prior studies have typically focused on older and less healthy individuals (5, 6, 19, 20). Our study, in a healthier and numerically larger population that included a wider age range, further enhances our understanding of the numerous factors that affect NT-pro-BNP.
Our findings have potential clinical and public health implications and inform current controversies regarding cut-points for NT-pro-BNP. Our data support the use of different cut-points in subpopulations with high levels of adiposity. The refinement of current cut-points using measures of fat mass or lean mass may improve the reliability of NT-pro-BNP in routine clinical use to rule out heart failure or monitor cardiovascular risk in the general population. However, such a refinement requires further explorations that would leverage datasets similar to ours but include cardiovascular events in addition to the mortality outcomes.
There are a number of mechanisms by which body composition might affect NT-pro-BNP levels. Experimental studies suggest a role for the natriuretic peptides as metabolic regulators. These have been shown to stimulate lipolysis with mice that overexpress B-type natriuretic peptide being protected from weight gain and glucose intolerance when fed a high-fat diet.(3, 24) Adipocytes highly express natriuretic peptide clearance receptors-C (NPR-C). Thus, the inverse relation between adiposity measures and natriuretic peptides has been attributed to an increased NPR-C expression in the adipose tissue, with the consequential increased clearance of brain natriuretic peptide (BNP) in obese subjects. However, NT-pro-BNP and BNP are structurally different, and NT-pro-BNP is not cleared by NPR-C (11). Thus, it is possible that the adipose tissue expresses a protease that cleaves the N terminal fragment of NT-pro-BNP, thus allowing a clearance of BNP by NPR-C. Regarding the lean mass and NT-pro-BNP link, 3 hypotheses have been postulated (11). First, lean mass could have an endocrine function that suppresses the synthesis or release of natriuretic peptides from cardiomyocytes. Second, the lean mass effect can be mediated by sex steroids, which influence natriuretic peptide synthesis and body composition. Androgens, which promote lean mass development, may suppress natriuretic peptide release, whereas estrogens, associated with lower lean mass, increase natriuretic peptide levels. For example, it has been shown that suppression of testosterone in men increases NT-pro-BNP levels (25). Among women, high free circulating testosterone has been associated with lower levels of NT-pro-BNP and hormone replacement therapy is associated with higher levels of NT-pro-BNP (26–30). Furthermore, in animal studies, estrogen replacement increases atrial natriuretic gene expression and type A receptor messenger RNA in the myocardium and reduces the expression of type C receptor messenger RNA in the mesenteric adipose tissue. These actions lead to increased atrial natriuretic peptide levels in the plasma after estrogen treatment (31). In humans, a similar effect was obtained by hormone replacement in postmenopausal women (31). Third, lean mass could produce a substance that degrades NT-pro-BNP, or lean mass may contribute directly to NT-pro-BNP clearance. Fourth, obesity is also associated with decreased concentrations of pro-BNP not glycosylated at threonine residue 71. Hence, a decreased pro-BNP substrate amenable to processing could partially explain the lower NT-pro-BNP observed in obese individuals (32).
Our study had limitations. First, information on history of cardiovascular disease was limited to self-report, which may be subject to misclassification with some individuals having subclinical heart failure. However, self-reported cardiovascular disease is known to be highly specific, although lacking sensitivity (33, 34). Second, we lacked data on left ventricular mass, which would be a marker of subclinical disease and an important determinant of the levels of NT-pro-BNP. Third, our ability to explore pathways explaining the observed association was limited, as for example, we lacked data on sex steroids to possibly explore the lean mass and NT-pro-BNP mechanism of association. Fourth, we did not distinguish between the superficial and deep fat compartments, and thus we did not assess the relative importance of these compartments in relation to NT-pro-BNP. Finally, our study was cross-sectional, thus unable to establish whether low NT-pro-BNP levels preceded or followed abnormalities in body composition measures.
The strengths of this study include the large, diverse, and nationally representative sample, which enhances the generalizability of our findings. Second, our examination of the association of body mass/composition measures with NT-pro-BNP levels accounted for factors known to affect NT-pro-BNP in healthy populations such as age, sex, race/ethnicity, renal function, behavioral factors, and other cardiovascular risk factors (18). Third, we used multiple body mass/composition measures including anthropometry and imaging-based estimates.
Conclusion
In the general adult population of US adults, NT-pro-BNP was inversely associated with lean mass, with stronger associations in women than in men. These results suggest that a better understanding of the intrinsic mechanisms that link body mass and composition to NT-pro-BNP is needed, as this will inform the pathobiology of natriuretic peptides, as well as the resulting clinical and public health implications for disease prognosis.
Supplementary Material
Authors’ Disclosures or Potential Conflicts of Interest:
Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest:
Employment or Leadership: R.H. Christenson, Editor-in-Chief of The Journal of Applied Laboratory Medicine, AACC; J.B. Echouffo Tcheugui, Associate Editor for Diabetes Care; E. Selvin, Deputy Editor of Diabetes Care and a member of the Editorial Board of Diabetologia.
Consultant or Advisory Role: R.H. Christenson, Siemens Healthineers, Roche Diagnostics, Beckman Coulter, Sphingotech, Quidel Medical, scientific advisory boards for Roche Diagnostics, Quidel, Pixcell Medical.
Stock Ownership: None declared.
Honoraria: R.H. Christenson, Siemens Healthineers, Roche Diagnostics, Beckman Coulter, Sphingotech GHB, Quidel Medical.
Research Funding: This work was funded by a grant from the Foundation for the National Institutes of Health Biomarkers Consortium to the Johns Hopkins Bloomberg School of Public Health (PI: E. Selvin). The Foundation for the National Institutes of Health received support for this project from Abbott Laboratories, AstraZeneca, Johnson & Johnson, the National Dairy Council, Ortho Clinical Diagnostics, Roche Diagnostics, and Siemens Healthcare Diagnostics. E. Selvin was also supported by NIH/NHLBI grant K24 HL152440 and the American Heart Association. J.B. Echouffo Tcheugui was supported by NIH/NHLBI grant K23 HL153774 and the American Heart Association. Reagents for NT-proBNP assays were donated by the Roche Diagnostics Corporation. S.P. Juraschek, National Institutes of Health, American Heart Association; C. Ndumele, National Institutes of Health, American Heart Association; R.H. Christenson, NHANES through Johns Hopkins University, Siemens Healthineers, Roche Diagnostics, Abbott Diagnostics, Beckman Coulter, Sphingotech, Quidel Medical.
Expert Testimony: None declared.
Patents: None declared.
Other Remuneration: E. Selvin receives royalties for authorship of sections of UpToDate related to screening and diagnosis of diabetes and laboratory tests for diabetes.
Role of Sponsor:
The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, preparation of manuscript, or final approval of manuscript.
Nonstandard Abbreviations:
- NT-pro-BNP
N-terminal pro-B-type natriuretic peptide
- BMI
body mass index
- WC
waist circumference
- FMI
fat mass index
- LMI
lean mass index
- DEXA
dual energy x-ray absorptiometry
- NHANES
National Health and Nutrition Examination Survey
- eGFR
estimated glomerular filtration rate
- CI
confidence interval
- OR
odds ratio
- BNP
brain natriuretic peptide
- NPR-C
natriuretic peptide clearance receptor-C
Footnotes
Supplemental Material
Supplemental material is available at Clinical Chemistry online.
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