(2024) 22:317
Yu et al. BMC Medicine
https://doi.org/10.1186/s12916-024-03536-3

BMC Medicine

RESEARCH

Open Access

The non-high-density lipoproteincholesterol to high-density lipoproteincholesterol ratio (NHHR) as a predictor of allcause and cardiovascular mortality in US adults
with diabetes or prediabetes: NHANES 1999–
2018
Binyang Yu1,4†, Min Li2†, Zongliang Yu1, Tao Zheng1, Xue Feng3, Anran Gao3, Haoling Zhang4 and Rui Gao4*

Abstract
Background The non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR)
serves as a novel composite lipid indicator for atherosclerosis. However, the association between NHHR and mortality in patients with diabetes or prediabetes remains unclear. Consequently, the objective of this study was to investigate the relationship between NHHR and both all-cause and cardiovascular mortality in US adults with diabetes
or prediabetes.
Methods This study included 12,578 adult participants with diabetes or prediabetes from the US National Healthand Nutrition Examination Survey (1999–2018). Mortality outcomes were ascertained by linking to the National Death
Index (NDI) record up to December 31, 2019. We employed a weighted multivariate Cox proportional hazards modeland restricted cubic splines to assess the associations between NHHR and all-cause and cardiovascular mortality.
A segmented Cox proportional hazards model was used for evaluating threshold effects. Furthermore, a competingrisks analysis was performed to explore the relationship between NHHR and cardiovascular mortality.
Results During a median follow-up period of 8.08 years, 2403 participants encountered all-cause mortality, with 662
of them specifically succumbing to cardiovascular mortality. The restricted cubic splines revealed a U-shaped association between NHHR and all-cause mortality, while an L-shaped association was observed for cardiovascular mortality.
The analysis of threshold effects revealed that the inflection points for NHHR and all-cause and cardiovascular mortality were 2.72 and 2.83, respectively. Specifically, when the baseline NHHR was below the inflection points, a negative
correlation was observed between NHHR and both all-cause mortality (HR: 0.76, 95% CI: 0.68–0.85) and cardiovascularmortality (HR: 0.70, 95% CI: 0.57–0.85). Conversely, when the baseline NHHR exceeded the inflection points, a positive†

Binyang Yu and Min Li contributed equally to this study.

*Correspondence:
Rui Gaoruigao@126.com
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0
International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as longas you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if
you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article orparts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicatedotherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not
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Yu et al. BMC Medicine(2024) 22:317

Page 2 of 13

correlation was observed between NHHR and both all-cause mortality (HR: 1.11, 95% CI: 1.06–1.16) and cardiovascularmortality (HR: 1.08, 95% CI: 1.00–1.16).
Conclusions Among US adults with diabetes or prediabetes, a U-shaped association was observed between NHHR
and all-cause mortality, whereas an L-shaped association was identified with cardiovascular mortality. The inflection
points for all-cause and cardiovascular mortality were 2.72 and 2.83, respectively.
Keywords NHHR, Diabetes, Prediabetes, Mortality, Cardiovascular disease, NHANES

Background
Diabetes and its complications are among the leading
causes of death and disability worldwide, posing a significant challenge to global public health. The global incidence of diabetes is increasing annually due to factors
such as population aging and unhealthy dietary habits[1, 2]. Epidemiological studies have shown that in 2021,
there were approximately 529 million individuals worldwide with diabetes, and by 2050, the number of affectedindividuals is projected to reach 1.31 billion [3]. Moreover, diabetes ranks as the eighth leading cause of deathglobally, with associated healthcare expenditures reaching a staggering $966 billion, imposing a significant economic burden on healthcare systems [3–5]. Importantly,
diabetes is closely associated with several major causesof death worldwide and is a primary risk factor for cardiovascular disease (CVD) [3]. Although cancer is also
emerging as a primary cause of death in individuals withdiabetes in certain regions, CVD remains the leading
cause of mortality among individuals with diabetes [6, 7].
CVD among individuals with diabetes is multifactorial, and controlling cardiovascular risk factors can significantly reduce the incidence of cardiovascular events.
Research has demonstrated that atherosclerotic cardiovascular diseases (ASCVDs) caused by factors such as
hypertension, high blood glucose, dyslipidemia, obesity,and insulin resistance are the primary causes of mortality
in diabetes patients [7–9]. Notably, dyslipidemia plays apivotal role in the development of ASCVD in individuals with diabetes. Dyslipidemia in diabetes patients ischaracterized by increased levels of the non-high-density
lipoprotein cholesterol (non-HDL-C), including lowdensity lipoprotein cholesterol (LDL-C), intermediatedensity lipoprotein, and very low-density lipoprotein
remnants, all of which are contributors to the progression of atherosclerosis [10, 11]. In recent years, the clinical value of non-HDL-C has gained widespread attention
and recognition. In 2021, the UK-based National Institutefor Health and Care Excellence (NICE) recommended
that non-HDL-C be used as the primary target for reducing CVD risk in patients with diabetes, replacing LDLC. This recommendation emphasizes the significance of
non-HDL-C in assessing CVD risk and treatment efficacy [12, 13]. However, a novel composite lipid indicator,

the non-HDL-C to high-density lipoprotein cholesterol(HDL-C) ratio (NHHR), has demonstrated promisingpredictive value in assessing the risk of various diseases,
including coronary artery disease, diabetes, abdominal
aortic aneurysm, and carotid atherosclerosis [14–17].
Compared to non-HDL-C, the NHHR is a superior andcomprehensive indicator that takes into account both
the risk factor (non-HDL-C) and the protective factor(HDL-C) in atherosclerosis [18, 19]. However, the prognostic value of NHHR in patients with diabetes remains
unclear. To address this gap, we conducted a study utilizing the National Health and Nutrition Examination Survey (NHANES) database. The aim of this research was
to investigate the association between NHHR and allcause and cardiovascular mortality in participants withdiabetes or prediabetes, as well as its association withvarious population characteristics, aiming to provide valuable insights into disease management and prevention
strategies.

Methods
Study population and design

The NHANES is a nationwide survey study designed toassess the nutritional and health status of adults and children in the USA. The survey employed a stratified, complex multistage sampling methodology and incorporates
interviews, physical examinations, and laboratory tests[20]. The study protocol was formally approved by the
National Center for Health Statistics (NCHS) Research
Ethics Review Board, and all participants involved in
the study provided informed consent by signing consent
forms [21]. This study utilized data from the NHANES
database spanning from 1999 to 2018, encompassing a total of 101,316 participants. Initially, participants
under the age of 20 were excluded (n = 46,235). Subsequently, participants who did not meet the diagnostic
criteria for diabetes or prediabetes according to the 2021
American Diabetes Association guidelines [22] were
excluded (n = 31,214). Diabetes was defined as (1) selfreported diabetes, (2) insulin injection or hypoglycemic
medication usage, (3) hemoglobin A1c (HbA1c) ≥ 6.5%,(4) fasting blood glucose (FBG) ≥ 7.0 mmol/L, and(5) 2-h postprandial glucose (2hPG) ≥ 11.1 mmol/L.

Yu et al. BMC Medicine(2024) 22:317

Prediabetes was defined as (1) HbA1c 5.7–6.4%, (2) FBG
5.6–6.9 mmol/L, and (3) 2hPG 7.8–11.0 mmol/L. Subsequently, participants lacking NHHR data were excluded(n = 11,250). Finally, after excluding participants withmissing mortality data (n = 39), a total of 12,578 participants were included in this study (Fig. 1).
Assessment of NHHR

Blood lipid parameters are critical components of cardiovascular disease (CVD) laboratory assessments in
the NHANES and are essential for assessing CVD risk.
These parameters encompass a spectrum of measurements, including total cholesterol (TC), HDL-C, LDL-C,
and triglycerides. The associated testing procedures were
performed at the mobile examination centers (MECs).
After collection, serum samples were processed and thenstored. These samples were then dispatched to the University of Minnesota for comprehensive analysis. In ourstudy, we employed the NHHR to evaluate participants’lipid levels and CVD risk. The NHHR was calculated
based on serum TC and HDL-C levels from the NHANES
database for the years 1999–2018. Non-HDL-C is definedas TC minus HDL-C, and the NHHR is calculated as theFig. 1 Flow chart of the study participants

Page 3 of 13

ratio of non-HDL-C to HDL-C [23]. Participants weredivided into four groups (Q1, Q2, Q3, and Q4) based on
the NHHR quartiles, with the Q1 group serving as thereference group.
Ascertainment of mortality

To ascertain the all-cause and cardiovascular mortality
status of the participants in this study, we utilized the
public-use linked mortality files provided by the NCHS.
These files integrate survey participants’ data with deathcertificate records from the National Death Index (NDI)
using a probabilistic matching algorithm. The follow-up
mortality data were updated until December 31, 2019.
The specific cause of death was established based on theInternational Classification of Diseases, Tenth Revision(ICD-10), with cardiovascular deaths including codes
I00-I09, I11, I13, and I20-I51 [24]. All-cause mortality
refers to the total of all specific cause deaths.
Assessment of covariates

The selection of covariates in this study took into
account a range of demographic characteristics andhealth-related information, including age, sex (male orYu et al. BMC Medicine(2024) 22:317

female), race (Mexican American, non-Hispanic White,
non-Hispanic Black, or other), education (less thanhigh school, high school or equivalent, or some college or above), and marital status (married/living withpartner, widowed/divorced/separated, or never married). The poverty income ratio (PIR) was divided into
the following categories: low income (< 1.3), moderate
income (1.3–3.5), and high income (> 3.5). Body massindex (BMI) was classified as normal/underweight (< 25),
overweight (25–30), or obese (> 30). Smoking status
was categorized as never smoking (smoking fewer than
100 cigarettes in a lifetime), former smoking (smoking more than 100 cigarettes in a lifetime but currently
not smoking), or current smoking (smoking more than
100 cigarettes in a lifetime and currently smoking everyday). Drinking status was dichotomized as yes or no(defined as whether the individual consumed more than
12 drinks per year). Physical activity was classified as vigorous, moderate, or other. Hypertension was defined as
self-reported hypertension, the use of antihypertensive
medication, or an average blood pressure of > 130 mmHg
or a diastolic pressure of > 80 mmHg. Hyperlipidemia
was defined as self-reported high cholesterol level, use ofcholesterol-lowering medications, or laboratory examination indicating TC ≥ 200 mg/dl, triglycerides ≥ 150 mg/
dl, LDL-C ≥ 130 mg/dl, and HDL < 40 mg/dl (male)or < 50 mg/dl (female). The participants’ medication status is defined as follows: antihypertensive treatment (yesor no), lipid-lowering treatment (yes or no), and antihyperglycemic treatment (only oral medication, only insulin, insulin and oral medication, or untreated).
Statistical analyses

The NHANES survey was conducted using a complex,
multistage, probability sampling design to ensure therepresentativeness of the research results for the US civilian non-institutionalized population. In our study, we
incorporated sample weights, stratification, and clustering for analysis purposes. The participants were divided
into four groups based on the quartiles (Q1–Q4) of the
NHHR. Continuous variables were reported as the means
and standard deviations (SDs), while categorical variables
were reported as frequencies and percentages. The baseline characteristics of the four participant groups werecompared using analysis of the variance (ANOVA) for
continuous variables and the chi-square (χ2) test for categorical variables. We established three models to control
for confounding factors and used weighted multivariate
Cox proportional hazards models to estimate the associations between NHHRs and all-cause and cardiovascularmortality. Model 1 did not include any covariate adjustments. Model 2 was adjusted for age, sex, race, education,
marital status, and PIR. Model 3 was further adjusted forPage 4 of 13

BMI, smoking status, drinking status, physical activity,
hypertension, hyperlipidemia, antihypertensive treatment, lipid-lowering treatment, and antihyperglycemictreatment. We also conducted a test for multicollinearity among all variables included in the analysis. The variance inflation factor (VIF) for each variable was below
5 (Additional file 1: Table S1), indicating no evidence ofsignificant multicollinearity. Moreover, the linear trend
test was performed to assess the trend by designating themedian NHHR for each quartile as a continuous variablein the regression model. We employed multiple imputation by chained equations (MICE) to address missing
values, thereby minimizing the reduction in sample size
caused by the absence of covariate data. The proportionsof missing covariates and the methods of imputation aredetailed in the Additional File 1: Tables S2.
To investigate the dose–response relationship between
NHHR and mortality, we employed Cox proportional
hazards regression models incorporating restricted cubic
splines (RCSs) for smooth curve fitting. If the RCS indicated a nonlinear association, we identified the inflection
point using the “segmented” package based on the likelihood-ratio test and the bootstrap resampling method.
Subsequently, we assessed the association between
NHHR and mortality using a segmented Cox proportional hazards model across both sides of the inflection
point. We performed subgroup analyses stratified by age(< 60 or ≥ 60 years), sex (male or female), race (Mexican
American, non-Hispanic White, non-Hispanic Black, orother), smoking status (former, current, or never), drinking status (yes or no), physical activity (vigorous, moderate, or other), BMI (normal/underweight, overweight,
or obese), and classification of diabetes (diabetes or prediabetes). Likelihood ratio tests were used to assess theinteractions among the subgroups. To evaluate the stability of the models, we performed several sensitivity analyses. Firstly, we excluded participants with missing values
for variable to eliminate the potential impact of missing
data on the primary outcomes. Secondly, given that cancer is one of the major causes of mortality among diabetic patients and is intimately associated with all-cause
mortality, we excluded participants who self-reported adiagnosis of cancer at baseline to mitigate the potential
confounding effects. Thirdly, to minimize the potential
for reverse causality, we excluded all participants fromthe first 2 years of follow-up by delaying their entry time.
Fourthly, we utilized the Fine and Gray subdistribution
hazards model [25] to examine the association between
the NHHR quantiles and the risk of cardiovascular mortality, treating non-cardiovascular death as a competing risk. Finally, to mitigate the influence of extreme
values, we excluded participants with a NHHR exceeding the mean ± 3 SD. All analyses were performed usingYu et al. BMC Medicine(2024) 22:317

R software, version 4.2.1, and a two-sided P-value < 0.05
was considered to indicate statistical significance. The
Bonferroni correction threshold to address multiple comparisons and establish statistical significance(α = 0.05/8 = 0.006 for subgroup interaction tests).

Results
Characteristics of the study participants

A total of 12,578 participants were included in this study,
with an average age of 53.06 years and a male proportion of 53.9%. The mean NHHR of the participants wascalculated to be 3.14 ± 1.47. Table 1 presents the baselinecharacteristics of the participants according to NHHR
quartiles. Compared to participants in the lowest quartile, those with higher NHHRs are often younger, male,and exhibit higher levels of HbA1c and TC. Furthermore,in the higher NHHR quartiles, an increase in the number of participants with obesity, current smoking, alcohol
consumption, and physical inactivity has been observed,
which suggests potential association between unhealthy
lifestyle habits and an elevated NHHR.
Associations between NHHR and mortality

During a mean follow-up period of 8.08 years, a totalof 2403 participant deaths were recorded, of which 662
were attributed to cardiovascular causes. The relationship between NHHR and mortality is presented inTable 2. We employed the weighted multivariate Cox
proportional hazards regression model to estimate theindependent association between NHHR and the risk ofmortality. After adjusting for multiple variables (model3), the hazard ratios (HRs) and 95% confidence intervals(CIs) for all-cause mortality across the lowest to highest quartiles of the NHHR (Q1–Q4) were 1.00 (reference), 0.86 (0.75, 0.99), 0.81 (0.70, 0.93), and 1.05 (0.89,
1.23), respectively. For cardiovascular mortality, the HRs
and 95% CIs were 1.00 (reference), 0.76 (0.58, 0.99), 0.78
(0.60, 1.01), and 0.86 (0.65, 1.15), respectively. According
to the trend analysis, no significant linear relationships
were detected between NHHR and all-cause mortality(P for trend = 0.678) or cardiovascular mortality (P for
trend = 0.366).
Detection of nonlinear relationships

To examine potential nonlinear trends, we employed
RCS fitted for Cox proportional hazards models to further investigate the relationship between NHHR andmortality. Notably, we discovered a significant U-shaped
association between NHHR and all-cause mortality(Fig. 2A) as well as a significant L-shaped association
between NHHR and cardiovascular mortality (Fig. 2B).
Utilizing the “segmented” package, we identified thatthe inflection points for NHHR in relation to the risks

Page 5 of 13

of all-cause and cardiovascular mortality were 2.72 and
2.83, respectively. To further investigate these relationships, we employed a segmented Cox proportional hazards model and found that the results of the likelihood
ratio tests were statistically significant (Table 3). In particular, below the inflection points, NHHR showed aninverse association with all-cause and cardiovascularmortality. For each unit increase in NHHR, the risk of
all-cause mortality decreased by 24% (HR: 0.76, 95% CI:
0.68–0.85, P = 0.001), and the risk of cardiovascular mortality decreased by 30% (HR: 0.70, 95% CI: 0.57–0.85,
P = 0.001). Above the inflection points, NHHR showed
a positive association with all-cause and cardiovascular mortality. For each unit increase in the NHHR, therisk of all-cause mortality increased by 11% (HR: 1.11,
95% CI: 1.06–1.16, P = 0.001), and the risk of cardiovascular mortality increased by 8% (HR: 1.08, 95% CI:
1.00–1.16, P = 0.027). We also examined the associations between the NHHR and mortality in diabetic andprediabetic populations, respectively (Fig. 3). The results
revealed that in participants with diabetes, the NHHR
exhibited a U-shaped association with all-cause mortality (P for nonlinear < 0.001) and an L-shaped association
with cardiovascular mortality (P for nonlinear = 0.009).
For participants with prediabetes, NHHR also demonstrated a U-shaped association with all-cause mortality(P for nonlinear = 0.003) but showed no significant nonlinear correlation with cardiovascular mortality (P for
nonlinear = 0.436).
Subgroup analyses

To further elucidate the relationship between NHHR andthe risks of all-cause and cardiovascular mortality, we
conducted a series of subgroup analyses. In the subgroup
analysis (Fig. 4), stratified by sex, age, race, smoking status, drinking status, physical activity, BMI, and diabetes
classification, the relationship between NHHR and allcause and cardiovascular mortality was consistent acrossall subgroups (P for interaction > 0.006). Notably, no significant interaction was observed between the baseline
NHHR and the stratified variables.
Sensitivity analysis

In the sensitivity analysis, after excluding participants
with missing covariate values at baseline, a total of
10,438 participants were included in the study. The
results showed that the associations between NHHR
and all-cause and cardiovascular mortality remained
relatively stable (Additional file 1: Table S3). Excluding
participants who self-reported cancer at baseline, thefinal study population comprised 11,109 individuals.
After adjusting for all confounding factors, the association between NHHR and mortality was found to be

Yu et al. BMC Medicine(2024) 22:317

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Table 1 Baseline characteristics according to NHHR quartiles
Characteristics

Quartiles of NHHR
OverallQ1 (< 2.12)

Q2 (2.12–2.91)

Q3 (2.91–3.88)

Q4 (> 3.88)

N(%)

12,578

3267

3186

3068

3057

Age, years, mean (SD)53.05 (16.10)

55.93 (17.52)

54.51 (16.17)

51.97 (15.55)

49.80 (14.33)

Male6732 (53.9)

1406 (42.3)

1532 (48.1)

1766 (57.9)2028 (67.3)

Female5846 (46.1)

1861 (57.7)

1654 (51.9)1302 (42.1)

1029 (32.7)

Mexican American

2337 (8.8)

428 (6.7)

556 (8.7)

646 (9.5)

707 (10.3)

Non-Hispanic White

5355 (66.7)

1336 (65.2)

1363 (66.3)

1281 (67.1)

1375 (68.4)

Non-Hispanic Black2523 (11.5)

905 (16.1)

669 (12.1)

552 (10.3)

397 (7.6)

Other2363 (12.9)

598 (12.1)

598 (12.8)

589 (13.1)

578 (13.6)

Less than high school

3828 (20.4)

902 (18.0)

932 (19.2)

941 (20.7)

1053 (23.7)

High school grad or equivalent

2976 (25.7)

722 (23.4)

763 (25.6)

755 (26.7)

736 (27.0)

Some college or above

5774 (53.9)

1643 (58.6)

1491 (55.2)

1372 (52.6)

1268 (49.3)

Married/living with partner

7875 (66.2)

1845 (60.9)

2002 (67.6)

2000 (67.1)

2028 (69.3)

Widowed/divorced/separated

3214 (21.5)

968 (25.1)

842 (22.4)

721 (19.9)

683 (18.7)

Never married

1489 (12.2)

454 (14.0)

342 (9.9)347 (13.0)

346 (12.0)

Low4009 (22.6)

886 (19.1)

1011 (22.3)

991 (22.8)

1121 (26.2)

Moderate

4994 (38.3)

1373 (39.6)

1254 (38.0)

1215 (37.8)

1152 (37.9)

High3575 (39.1)

1008 (41.3)

921 (39.7)

862 (39.4)

784 (35.9)

Normal/underweight2720 (20.9)1125 (35.2)

706 (22.1)

513 (15.2)

376 (10.9)

Overweight

4314 (33.9)

1018 (32.2)

1087 (33.4)

1077 (35.1)

1132 (35.1)

Obese5544 (45.2)

1124 (32.6)

1393 (44.5)

1478 (49.7)

1549 (54.0)

HbA1c, %, mean (SD)5.94 (1.13)

5.84 (0.95)

5.92 (1.06)

5.92 (1.08)

6.07 (1.37)< 0.001

HDL-C, mmol/L, mean (SD)1.33 (0.40)

1.73 (0.44)

1.39 (0.27)

1.20 (0.22)

0.99 (0.19)< 0.001

TC, mmol/L, mean (SD)5.11 (1.10)

4.49 (0.93)

4.86 (0.92)

5.19 (0.90)

5.89 (1.12)< 0.001

Never

6463 (50.4)

1794 (54.1)

1719 (53.1)

1566 (50.2)

1384 (44.2)

Former3695 (29.7)

971 (31.6)

918 (28.8)

917 (29.4)

889 (29.0)

Current

2420 (19.9)

502 (14.3)

549 (18.2)

585 (20.4)

784 (26.7)

Yes8231 (69.9)

2084 (69.5)

2005 (67.4)

1998 (69.5)

2144 (73.2)

No4347 (30.1)

1183 (30.5)1181 (32.6)

1070 (30.5)

913 (26.8)

Vigorous

2205 (20.7)

602 (23.1)

538 (19.7)

524 (19.3)

541 (20.6)

Moderate

3455 (29.9)

942 (30.5)875 (29.7)

843 (31.0)795 (28.4)

Other6918 (49.4)

1723 (46.4)

1773 (50.5)

1701 (49.7)

1721 (51.0)

Yes8185 (61.1)

2149 (59.3)

2090 (62.3)

1967 (61.2)

1979 (61.7)

No4393 (38.9)

1118 (40.7)

1096 (37.7)

1101 (38.8)

1078 (38.3)

Yes9813 (77.9)

1631 (48.2)

2310 (71.6)

2816 (91.6)

3056 (100.0)

No2765 (22.1)

1636 (51.8)

876 (28.4)

252 (8.4)

1 (0.0)1702 (11.3)

511 (12.3)

461 (12.7)

376 (10.1)

354 (9.9)

Sex, n(%)< 0.001< 0.001

Race, n (%)< 0.001

Education, n (%)< 0.001

Marital, n (%)< 0.001

PIR, n (%)< 0.001

BMI (kg/m2), n (%)< 0.001

Smoking status, n (%)< 0.001

Drinking status, n (%)

0.002

Physical activity, n (%)

0.034

Hypertension, n (%)

0.323

Hyperlipidemia, n (%)< 0.001

Antihyperglycemic treatment,n (%)
Only oral medication

P value

0.004

Yu et al. BMC Medicine(2024) 22:317

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Table 1 (continued)
Characteristics

Quartiles of NHHR
OverallQ1 (< 2.12)

Q2 (2.12–2.91)

Q3 (2.91–3.88)

Q4 (> 3.88)

Only insulin

283 (1.8)

84 (2.3)

81 (2.0)67 (1.6)

51 (1.2)

Insulin and oral medication

340 (2.1)

113 (2.5)

84 (1.9)76 (2.2)

67 (1.9)

Untreated

10,253 (84.8)

2559 (82.9)2560 (83.4)

2549 (86.0)2585 (87.0)

Yes3190 (24.3)

1077 (32.2)

890 (27.1)

691 (21.3)

532 (16.7)

No9388 (75.7)

2190 (67.8)

2296 (72.9)

2377 (78.7)

2525 (83.3)

Yes4710 (33.9)

1419 (37.4)

1293 (37.7)

1066 (32.5)

932 (27.9)

No

P value

Lipid-lowering treatment, n (%)< 0.001

Antihypertensive treatment, n (%)< 0.001
7868 (66.1)

1848 (62.6)

1893 (62.3)

2002 (67.5)

2125 (72.1)

Diabetes, n (%)

4089 (27.1)

1095 (27.1)

1024 (27.8)

965 (26.3)

1005(27.3)

0.748

Prediabetes, n(%)

8489 (72.9)2172 (72.9)

2162 (72.2)

2103 (73.7)

2052 (72.7)

0.748

The data are presented as the mean (SD) or n (%). All estimates were obtained from complex survey designs, analysis of variance or χ2 tests where appropriate
BMI Body mass index, HDL-C High density lipoprotein cholesterol, HbA1c Hemoglobin A1c, PIR Poverty income ratio, SD Standard deviation, TC Total cholesterol

Table 2 HRs (95% CIs) for mortality according to NHHR quartiles
Quartiles of NHHR

P for trend

Q1 (< 2.12)

Q2 (2.12–2.91)

Q3 (2.91–3.88)

Q4 (> 3.88)

All-cause mortality
Number of deaths

658

613

534

598

Model 1
HR (95% CI) P value

10.83 (0.72,0.95)0.007

0.66 (0.57,0.75)0.001

0.70 (0.62,0.79)0.001

0.001

Model 2
HR (95% CI) P value

10.88 (0.77,1.01)0.074

0.79 (0.69,0.89)0.001

1.00 (0.87,1.15)0.992

0.579

Model 3
HR (95% CI) P value

10.86 (0.75,0.99)0.041

0.81 (0.70,0.93)0.004

1.05 (0.89,1.23)0.550

0.678

CVD mortality
Number of deaths

157

181

171

153

Model 1
HR (95% CI) P value

1

0.76 (0.59,0.98)0.038

0.70 (0.54,0.91)0.006

0.63 (0.48,0.82)0.001

0.001

Model 2
HR (95% CI) P value

10.82 (0.63,1.07)0.149

0.87 (0.69,1.11)0.266

0.95 (0.72,1.25)0.697

0.671

Model 3
HR (95% CI) P value

1

0.76 (0.58,0.99)0.042

0.78 (0.60,1.01)0.065

0.86 (0.65,1.15)0.319

0.366

Model 1 was unadjusted
Model 2 was adjusted for sex, age, race, education, marital status, and poverty income ratio
Model 3 was further adjusted for BMI, smoking status, drinking status, physical activity, hypertension, hyperlipidemia, antihyperglycemic treatment, lipid-lowering
treatment, and antihypertensive treatment, based on model 2
The results are presented as HRs and 95% CIs
BMI Body mass index, CI Confidence interval, CVD Cardiovascular disease, HR Hazard ratio

largely consistent with the primary analysis (Additional
file 1: Table S4). After excluding participants during thefirst 2 years of follow-up, the study sample consistedof 11,510 participants. Similar associations between
NHHR and all-cause and cardiovascular mortality wereobserved (Additional file 1: Table S5). In the Fine andGray competing risks models, the relationship between

NHHR and cardiovascular mortality was found to berobust (Additional file 1: Table S6). After excluding
extreme values (mean ± 3 SD) of the NHHR, a total of
12,447 participants were included in the study. After
adjusting for a range of potential confounding factors,
the associations between NHHR and both all-cause andcardiovascular mortality persisted (Additional file 1:
Table S7).

Yu et al. BMC Medicine(2024) 22:317

Page 8 of 13

Fig. 2 Restricted cubic splines were utilized to evaluate the hypothesis of potential nonlinear relationships between NHHR and all-cause (A)and cardiovascular (B) mortality in participants with diabetes or prediabetes. The NHHRs of 2.72 for A and 2.83 for B were chosen as reference
estimates for each hazard ratio (HR). The analysis was adjusted for sex, age, race, education, marital status, poverty income ratio, BMI, smoking
status, drinking status, physical activity, hypertension, hyperlipidemia, antihyperglycemic treatment, lipid-lowering treatment, and antihypertensive
treatment. The Cox proportional hazards models were fitted, with solid lines representing estimated values and shaded areas representing
the corresponding 95% confidence intervals (CIs). The black dashed line represents the location of the inflection point in the curve. BMI, body massindex; CVD, cardiovascular disease

Discussion
To the best of our knowledge, our study is the first prospective cohort study to reveal the association between
NHHR and the risk of all-cause and cardiovascularmortality in participants with diabetes or prediabetes.
Our findings indicate a U-shaped association between

NHHR and all-cause mortality as well as an L-shaped
association with cardiovascular mortality among participants with diabetes or prediabetes. The threshold
effect analysis results reveal that the NHHR has inflection points at 2.72 and 2.83 for the risks of all-cause
and cardiovascular mortality, respectively. Our study

Yu et al. BMC Medicine(2024) 22:317

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Table 3 Threshold effect analysis of NHHR on all-cause and CVD
mortality in participants with diabetes or prediabetes
Adjusted HR (95%CI), P value
All-cause mortality
Total

1.03 (0.99, 1.08) 0.104

Segmented cox proportional hazards model
Inflection point

2.72

NHHR < 2.72

0.76 (0.68, 0.85) 0.001

NHHR ≥ 2.72

1.11 (1.06, 1.16) 0.001

P for Log-likelihood ratio< 0.001

CVD mortality
Total

0.98 (0.90, 1.06) 0.568

Segmented cox proportional hazards model
Inflection point

2.83

NHHR < 2.83

0.70 (0.57, 0.85) 0.001

NHHR ≥ 2.83

1.08 (1.00, 1.16) 0.027

P for Log-likelihood ratio

0.001

The model was adjusted for sex, age, race, education, marital status,
poverty income ratio, BMI, smoking status, drinking status, physical activity,
hypertension, hyperlipidemia, antihyperglycemic treatment, lipid-lowering
treatment, and antihypertensive treatment
BMI Body mass index, CI Confidence interval, CVD Cardiovascular disease, HR
Hazard ratio

underscores the significance of the NHHR as a valuable
clinical prognostic indicator for both all-cause and cardiovascular mortality in patients with diabetes or prediabetes. Furthermore, it holds immense importance indisease risk stratification and prognosis.
The NHHR is a novel lipid ratio indicator that is costeffective and easily obtainable, and previous studies
have revealed its clinical predictive value in various diseases. A longitudinal cohort study by Sheng et al. [14]involving 15,464 participants demonstrated that the
NHHR is a superior indicator for predicting diabetes
risk compared to conventional lipid markers, with an
inflection point at approximately 2.74. This finding isessentially in agreement with the results of our study.
You et al. [26] reported a positive correlation between
NHHR and coronary artery disease, noting that anelevated NHHR is associated with an increased riskof acute coronary syndrome. Similarly, Mao et al. [17]demonstrated that the NHHR serves as an independent
predictor for severe coronary artery disease and major
adverse cardiovascular events and is associated withthe prognosis of patients with non-ST-segment elevation myocardial infarction. These studies indirectly
support the conclusions of our research. Additionally,other studies have revealed a relationship between
NHHR and depression as well as suicidal ideation in
adults, shedding light on the connection between lipid
metabolism and mental health [23, 27].

Lipid profiles provide crucial information about lipid
metabolism and an individual’s health status and can beused to predict the risk of certain diseases [28]. Although
the biological mechanisms linking NHHR to mortality
remain unclear, several studies have suggested a potential association between NHHR and atherosclerosis [14,29]. Atherosclerosis in patients with diabetes is associated with several pathological mechanisms, including
diabetes dyslipidemia, hyperglycemia, and insulin resistance, all of which play important roles in the development of atherosclerosis and are associated with adverse
CVD outcomes [30, 31]. Specifically, insulin resistance indiabetic patients leads to an increase in the productionof very LDL (VLDL) particles by the liver. The combined
effect of these VLDL particles with intestinal chylomicron remnants results in hypertriglyceridemia, which inturn induces an increase in the number of small dense
LDL (sd-LDL) particles. As sd-LDL particles undergo
glycosylation and oxidation by free radicals, this processenhances vascular endothelial permeability and promotes
macrophage aggregation, thus contributing to the gradual formation of atherosclerotic plaques [11, 32]. Whenatherosclerotic plaques are eroded or rupture, triggering
thrombotic events that can ultimately precipitate acutecardiovascular events, resulting in patient mortality.
Consequently, dyslipidemia is a critical link in both thedevelopment of atherosclerosis and the adverse prognosis in diabetic patients [30]. Diabetic dyslipidemia ischaracterized by elevated levels of non-HDL-C, including
LDL-C and other components, which contribute to thedevelopment of atherosclerosis and thus render it a superior predictor of ASCVD [33–35]. Conversely, HDL-C isknown to exert anti-inflammatory, antioxidant, and antiatherogenic effects, displaying a negative correlation with
the incidence of ASCVD [36, 37]. The NHHR incorporates all lipid-related information relevant to both atherogenic and anti-atherogenic processes, offering a morecomprehensive depiction of their balance. It serves as amore reflective indicator of a patient’s lipid health status.
Our study uncovered a negative correlation between
NHHR and age, as well as HDL-C at baseline, whereas apositive correlation was noted between NHHR, HbA1c,
and TC. This finding consistent with the research of Honget al. [38], which suggests that NHHR may serve as a cardiovascular risk factor and is associated with adverse outcomes in individuals. Our research revealed a U-shaped
association between NHHR and all-cause mortality andan L-shaped association with cardiovascular mortality.
The inflection points for these association were identified at NHHR values of 2.72 and 2.83, respectively. Below
the inflection points, for every unit increase in NHHR,
the all-cause and cardiovascular mortality was foundto decrease by 24% and 30%, respectively. Conversely,Yu et al. BMC Medicine(2024) 22:317

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Fig. 3 Restricted cubic splines were utilized to evaluate the hypothesis of potential nonlinear relationships between NHHR and all-cause (A)and cardiovascular (B) mortality in participants with diabetes. The NHHRs of 2.55 for A and 2.50 for B were chosen as reference estimates for eachhazard ratio (HR). Similarly, restricted cubic splines were utilized to evaluate the hypothesis of potential nonlinear relationships between NHHR
and all-cause (C) and cardiovascular (D) mortality in participants with prediabetes. Using NHHR of 3.13 for C and 2.83 for D as reference estimatesfor each HR, the analysis was adjusted for sex, age, race, education, marital status, poverty income ratio, BMI, smoking status, drinking status,
physical activity, hypertension, hyperlipidemia, antihyperglycemic treatment, lipid-lowering treatment, and antihypertensive treatment. The
Cox proportional hazards model was used to fit the data, with solid lines representing the estimated values and shaded areas representing
the corresponding 95% CIs. The black dashed line represents the location of the inflection point in the curve. BMI, body mass index; CVD,
cardiovascular disease

above the inflection points, a unit increase in NHHR was
associated with an increase in all-cause and cardiovascular mortality by 11% and 8%, respectively. Therefore,
for patients with diabetes or prediabetes, maintaining
the NHHR within the range of approximately 2.7 to 2.8
may significantly minimize the risk of adverse outcomes.
Multiple studies have partially supported this conclusion. Several studies [39–41] have shown a U-shaped
relationship between non-HDL-C and all-cause andcardiovascular mortality, observed across populationsof hypertensive participants, those with chronic kidney disease, and males not receiving statin therapy. Furthermore, two prospective cohort studies have shown a
U-shaped relationship between HDL-C levels and allcause mortality [42]. The findings of these studies suggestthat both HDL and non-HDL-C levels should be maintained within a reasonable range. Notably, our study also

demonstrates that both excessively high and excessively
low NHHRs are associated with an increased risk of mortality. When the NHHR levels are excessively high, therisk of patient mortality increases, which is attributed tothe accelerated development of atherosclerosis associatedwith extremely high non-HDL-C levels, leading to anelevated risk of mortality [43]. We also found that excessively low NHHRs can lead to a significant increase in therisk of mortality. Possible mechanisms for this observation are as follows: (1) an excessively low NHHR is often
associated with low levels of TC. Lower levels of TC havebeen associated with poorer health conditions [44] or areduction in cholesterol levels due to frailty and illness,
which may potentially increase the risk of mortality [45,46]. (2) An excessively low NHHR may also be attributed
to extreme high levels of HDL-C, which are typicallycaused by genetic variations and can exacerbate the risk

Yu et al. BMC Medicine(2024) 22:317

Page 11 of 13

Fig. 4 Subgroup analysis of the associations between NHHR and all-cause and cardiovascular mortality. The reference NHHRs for all-cause mortality
were NHHRs < 2.72, while for cardiovascular mortality, the reference was NHHRs < 2.83. The model was adjusted for sex, age, race, education, marital
status, poverty income ratio, BMI, smoking status, drinking status, physical activity, hypertension, hyperlipidemia, antihyperglycemic treatment,
lipid-lowering treatment, and antihypertensive treatment. BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; HR, hazard
ratio

of coronary heart disease and mortality[39, 42]. However, the specific mechanisms underlying the association
between NHHR and the risk of diabetes-related mortality
remain to be further investigated.
We further examined the populations with diabetes and prediabetes separately. The results revealed a
U-shaped association between NHHR and all-cause mortality in participants with diabetes, while an L-shaped
association was observed with cardiovascular mortality.
In participants with prediabetes, the NHHR was also
associated with all-cause mortality in a U-shaped manner but showed a linear correlation with cardiovascular mortality. The aforementioned discrepancies may be
attributed to the relatively small number of participants
experiencing cardiovascular mortality in the study. The
sensitivity analysis results indicated that the relationships
between the NHHR and both all-cause and cardiovascular mortality remained relatively stable.
There are several limitations in this study. Firstly, as
an observational study, we cannot establish a causal

relationship between NHHR and mortality. Secondly, thisstudy only assessed the prognostic value of the baseline
NHHR and did not investigate the association betweenchanges in NHHR over time and mortality. Thirdly, we
did not adjust for diabetes classification or disease duration, which may introduce potential biases. Fourthly, thestudy population consisted primarily of the general population in the US, so caution should be exercised when
extrapolating the findings to other ethnicities. Finally, theproportion of patients with CVD outcomes in the study
population was small, potentially limiting the statisticalpower to detect differences between groups.

Conclusions
The findings of this study demonstrate that the NHHR
serves as a valuable predictive indicator for all-cause
and cardiovascular mortality in participants with diabetes or prediabetes. In our nationally representative
sample of adults with diabetes or prediabetes in the US,
we observed a U-shaped association between NHHR

Yu et al. BMC Medicine(2024) 22:317

Page 12 of 13

and all-cause mortality as well as an L-shaped association with cardiovascular mortality. Routine monitoring of NHHR may contribute to the evaluation ofmortality risk and prognosis in participants with diabetes
or prediabetes.

Declarations

Abbreviations
ASCVD	Atherosclerotic cardiovascular disease
BMI	Body mass index
CI	Confidence intervals
CVD	Cardiovascular diseaseDM	Diabetes mellitus
FBG	Fasting blood glucose
HbA1c	Hemoglobin A1c
HDL-C	High-density lipoprotein cholesterolHR	Hazard ratios
LDL-C	Low-density lipoprotein cholesterol
MECs	Mobile examination centers
MICE	Multiple imputation by chained equations
NCHS	National Center for Health Statistics
NDI	National death index
NHHR	Non-high density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio
Non-HDL-C	Non-high density lipoprotein cholesterol
PG	Postprandial glucose
RCS	Restricted cubic spline
Sd-LDL	Small dense low-density lipoprotein
TC	Total cholesterol
VIF	Variance inflation factor
VLDL	Very low-density lipoprotein

Consent for publication
All authors have agreed to the submission and publication of this research.

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12916-​024-​03536-3.
Additional file 1: Table S1. Assessment of multicollinearity among
independent variables. Table S2. The proportion of missing covariates
and imputation methods. Table S3. HRsfor mortality according to NHHR
quartiles after excluding participants with any missing covariate values
at baseline. Table S4. HRsfor mortality according to NHHR quartiles after
excluding participants with self-reported cancer at baseline. Table S5.
HRsfor mortality according to NHHR quartiles after excluding participantsfrom the first 2 years of follow-up. Table S6. Association between NHHR
and cardiovascular mortality using Fine & Gray competing risks models.
Table S7. HRsfor mortality according to NHHR quartiles after excluding
extreme valuesof NHHR.
Acknowledgements
We sincerely express our gratitude to the participants and investigators of
the NHANES study for their invaluable contributions, which have provided
significant support and assistance to our research endeavors.
Authors’ contributions
The study was conceived by BY, ML, and RG, who were responsible for
performing the data analysis and manuscript writing. TZ and ZY extracted thedata from the official NHANES website. HZ contributed to the revision andreview of the manuscript. AG and XF conducted a repeat analysis of the data
and verified the results. All authors read and approved the final manuscript.
Funding
This study was supported by the Innovation Fund of the China Academy ofChinese Medical Sciences (CI2021A04701) and the National Key Research andDevelopment Program of China (2021YFF 0901404).
Availability of data and materials
No datasets were generated or analysed during the current study.

Ethics approval and consent to participate
The NHANES protocol was approved by the Institutional Review Board of
the National Center for Health Statistics (https://​www.​cdc.​gov/​nchs/​nhanes/​
irba98.​htm). All participants provided written informed consent.

Competing interests
The authors declare no competing interests.
Author details
1
Graduate School, Beijing University of Chinese Medicine, Beijing 100029,
China. 2 School of Nursing, Xi’an Jiaotong University Health Science Center,
Xi’an 710061, China. 3 Graduate School, China Academy of Chinese Medical
Sciences, Beijing 100700, China. 4 Xiyuan Hospital, Chinese Academy of Chinese Medical Sciences, Beijing 100091, China.
Received: 2 April 2024 Accepted: 19 July 2024

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