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Implications of prognostic nutritional index in predicting adverse outcomes of uncontrolled diabetic patients: a cohort study of the national health and nutrition examination survey from 2005 – 2018

Diabetology & Metabolic Syndrome volume 16, Article number: 315 (2024) Cite this article

Abstract

Background

Diabetes mellitus (DM) is a metabolic disorder with increasing prevalence and poor control rates, leading to adverse events. Prognostic nutritional value (PNI) has been identified as a protective factor in DM, but its role in uncontrolled DM remains unclear.

Methods

This study based on the representative cohort of National Health and Nutrition Examination Survey from 2005 to 2018. A total of 3,313 participants with uncontrolled DM were included in our analyses. PNI was calculated as 5×lymphocyte count (109/L)+ 10×serum albumin (g/L). The endpoints were DM-related and cardiovascular mortality, which were obtained from National Death Index. Univariable and multivariable cox proportional hazard regression were performed to investigate prognostic value of PNI.

Results

Among 3,313 patients with uncontrolled DM (mean age of 61.75 ± 12.78 years, 53.4% male), PNI level was negatively associated with inflammatory markers and positively associated with metabolic markers of lipid and protein. During a median follow-up of 77 months, 247 DM-related deaths and 205 cardiovascular deaths occurred. Higher PNI levels independently predicted low DM-related (adjusted Hazard ratio [HR] = 0.872, 95% confidence interval [CI] 0.840–0.906, P < 0.001) and cardiovascular mortality (adjusted HR = 0.872, 95% CI 0.834–0.912, P < 0.001). The prognostic value of PNI significantly varied across different DM treatment conditions, which was more pronounced in patients receiving antidiabetic treatments (adjusted HR: insulin + oral antidiabetic drugs [OADs]: 0.832; insulin: 0.863; OADs: 0.894, all adjusted P < 0.001), but was absent in those without antidiabetic treatment.

Conclusions

A higher PNI level is an independent protective predictor for DM-related and cardiovascular mortality in uncontrolled DM patients. Evaluation of PNI level in uncontrolled DM patients could conduce to stringent intervention. Improvement of PNI could enhance the effective of antidiabetic therapy, especially the insulin therapy, and reduce DM-related mortality.

Introduction

Diabetes mellitus (DM) is one of the most prevalent metabolic disorders affecting over 10% of the global adult population [1], and is one of the leading contributors to the all-cause disability and mortality, according to the global burden of disease data [2, 3]. The burden of DM grew rapidly over the past three decades, and is estimated to become the third important contributor to adverse events in 2050 [4, 5]. Despite its clinical importance, epidemiological analyses reveal that more than 65% of adults with DM have not yet achieved the optimal glycemic control [6, 7]. This lack of glycemic control is referred as uncontrolled DM and has been posing a concerning public health challenge.

DM is characterized by hyperglycemia, which has been shown to contribute to vascular complications and cardiovascular events by inducing toxic effects on vascular walls and cardiomyocytes, exacerbating the chronic inflammation, and leading to microvascular hypoxia [8,9,10]. Evidence suggests that uncontrolled DM patients with persistent hyperglycemia have higher incidences of adverse renal and cardiovascular events compared to those with well-controlled glycemic level [11,12,13,14]. Identifying predictors to stratify patients at high risk for adverse clinical outcomes within the uncontrolled DM population helps to implement stringent intervention and reduce DM-related and cardiovascular mortality.

Malnutrition is not uncommon among patients with chronic metabolic disorders such as hypertension and DM, and it is associated with adverse cardiovascular outcomes [15]. Inflammation triggered by hyperglycemia or insulin resistance is also recognized as a mediator of complications and cardiovascular events in DM patients [16, 17]. Additionally, both malnutrition and inflammation might attenuate the effects of DM treatment and contribute to the poor glycemic control [17]. The prognostic nutritional index (PNI), which reflects chronic inflammatory and nutritional status, has been linked to the prognosis of cardiovascular disease in DM patients [18, 19]. PNI level has also been shown to predict vascular complications, including kidney disease and retinopathy, in DM patients [20,21,22]. However, the prognostic value of PNI level in predicting adverse clinical outcomes among patients with uncontrolled DM remains unclear.

This study was conducted using data from a nationwide representative cohort study in the U.S. The first goal of this study was to investigate the relationship between PNI level and the risk of DM-related and cardiovascular mortality in patients with uncontrolled DM. The second goal was to explore the prognostic value of PNI level across different DM treatment conditions.

Methods

Study population

This study utilized data from the National Health and Nutrition Examination Survey (NHANES), which was conducted by the Centers for Disease Control and Prevention (CDC) in the U.S [23]. NHANES is a long-standing program that has collected comprehensive data on the health and nutritional status of the U.S. population applying a complex, multistage probability sampling design. The program has a wide range of data, including demographics, laboratory results, examinations, and questionnaires. NHANES is approved by the Institutional Review Board of the National Center for Health Statistics, and written informed consent has been obtained from all participants. This study adhered to the principles of the Declaration of Helsinki.

We analyzed data from seven consecutive NHANES cycles, spanning from 2005 to 2018 (2005–2006, 2007–2008, 2009–2010, 2011–2012, 2013–2014, 2015–2016, and 2017–2018). A total of 70,190 participants were included, from which 5,231 individuals self-reported suffering DM diagnosed by doctors. Subsequently, 3,424 DM patients with either abnormal fasting plasma glucose (FPG) levels (\(\:\ge\:\) 7 mmol/l), hemoglobin A1c (HbA1c) levels (\(\:\ge\:\) 6.5%) or plasma glucose level in oral glucose tolerance test (\(\:\ge\:\) 11.2 mmol/l at 2-hours) at baseline were extracted and identified as having uncontrolled DM. We then excluded 17 participants under 18 years old, 89 participants with incomplete data for calculating the PNI, and 5 participants with ineligible follow-up data. Ultimately, 3,313 participants with uncontrolled DM were selected to assess the associations between PNI level and endpoints. A detailed study flowchart was presented in Fig. 1.

Fig. 1
figure 1

The flowchart of the study design. NHANES, National healthy and nutritional examination survey; DM, Diabetes mellitus; HbA1c, hemoglobin A1c; FPG, fast plasma glucose; OGTT, oral glucose tolerance test

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Data collection

Demographic information, including age, sex, race, marital status, and citizen status, was collected using the family demographics questionnaire. Data on disease history, smoking status as well as alcohol consumption were collected from the sample person questionnaire. The diagnosis of DM and DM treatment conditions were interviewed face to face by trained stuff. Individuals with a DM diagnosis were divided into four treatment conditions: untreated; oral antidiabetic drugs (OADs) treated; insulin treated; OADs and insulin treated. A computer-assisted software system was used to consistently check data and validate the questionnaire data, alerting program staff when unusual entries were recorded.

Height and weight were measured by trained health technicians following standard protocol. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m2). Blood pressure (BP) and heart rate (HR) was measured by trained stuff three or four times consecutively after 5 min rest, and the average of the readings were determined as the systolic BP (SBP), diastolic BP and HR values in this study.

Blood samples were collected from participants at baseline, sent to central laboratories, and tested by trained researchers. A complete blood count test was routinely performed in all NHANES cycles using the Beckman Coulter methodology for counting and sizing. Serum albumin level was measured using the bromcresol purple combination methods in each NHANES cycle. Detailed laboratory methods for other blood substances, such as total cholesterol, triglycerides, high-density lipoprotein (HDL), HbA1c, and FPG, are described elsewhere [19]. All data were publicly available on the NHANES website (https://www.cdc.gov/nchs/nhanes/index.htm.).

Determinations of exposure and outcomes

PNI was calculated as 5×absolute lymphocyte count (109/L) + 10×serum albumin (g/L). Hypertension was defined as self-reported diagnosis of hypertension, antihypertensive-drug use, SBP \(\:\ge\:\) 140mmHg and/or DBP \(\:\ge\:90\text{m}\text{m}\text{H}\text{g}\) as guideline recommended [24].

Mortality information was obtained from the National Death Index database up to 31 December 2019. The duration of follow-up was determined as the interval between the interview date to the date of death or 31 December 2019. The median follow-up period was 127 months. The contributing causes of death were coded according to International Classification of Diseases – 10th Edition and were public available at http://www.cdc.gov/nchs. The primary endpoint was DM-related mortality, and the secondary endpoint was cardiovascular mortality.

Statistical analyses

Categorical variables were presented as the number (percentage), and continuous variables as the mean \(\:\pm\:\) standard deviation. Baseline characteristics were compared using chi-square test for categorical variables, and ANOVA analyses for continuous variables. The linear trend test was performed when comparing the differences in characteristics between PNI quantiles. Pearson test was used to evaluate the correlation of PNI level with metabolic or inflammatory markers.

The prognostic value of PNI level was assessed as both a continuous variable and by quartiles. Survival curves were constructed using Kaplan–Meier method and compared using the log-rank test. Restricted cubical splines were used to assess the non-linear associations of PNI level and clinical outcomes. The associations between PNI level and clinical outcomes were also assessed using hazard ratios (HRs) and 95% confident intervals (CIs) obtained from univariable and multivariable cox proportional hazard regression models. Multivariable model 1 was adjusted for age and sex. In model 2, additional covariates, including BMI, SBP, HR, race, smoking status, alcohol consumption, disease history, and DM treatment conditions, were also considered. Model 3 further adjusted for laboratory indexes in addition to the adjustment made in model 2. Interactions between PNI and age, sex, race, or DM treatment conditions for the clinical outcomes were evaluated using the abovementioned multivariable models. A two-sides P value < 0.05 was considered as statistical significance. All statistical analyses were performed using R software package (Version 4.3.0, R Core Team, Vienna, Austria).

Results

Baseline characteristic of study population

In this study, a total of 3,313 participants with uncontrolled DM and complete baseline data were included. The mean age of the participants was 61.75 ± 12.78 years, with 1,771 (53.4%) being male. Baseline characteristics of the uncontrolled DM population were presented in Table 1 across quartiles of the PNI. Participants with the higher PNI levels tended to be younger and male. They were more likely to be Hispanic and had got married. They also had a lower incidence of coronary artery disease and hypertension history, and lower BMI and SBP levels.

Table 1 Baseline characteristics quartiles by the PNI levels
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Participants in the higher PNI quartiles exhibited higher levels of lipid and protein metabolism markers, including triglycerides, total cholesterol, and total protein level, and lower levels of inflammatory makers of WBC and neutrophils counts. Notably, there were significant differences in DM treatment conditions across the PNI quartiles. Patients in the higher PNI quartiles were less likely to be on insulin therapy and had a higher rate of using the OADs.

The PNI demonstrated a significant positive correlation with triglyceride (r² = 0.035, P < 0.001), and total protein (r² = 0.338, P < 0.001) as shown in Additional file 1: Figure S1. Moreover, the WBC (r² = -0.082, P < 0.001) and neutrophils (r² = -0.129, P < 0.001) counts were adversely correlated with the PNI levels.

Prognostic value of PNI on clinical outcomes in patients with uncontrolled DM

The median follow-up duration was 77 months (interquartile range: 39–112 months). There were 247 (7.5%) DM-related deaths, and 205 (6.2%) cardiovascular deaths occurred during the follow-up period. Survival curves revealed that patients in the higher PNI quartiles experienced lower incidences of DM-related and cardiovascular mortality (all log-rank P < 0.001, Fig. 2).

Fig. 2
figure 2

The prediction of PNI for DM-related and cardiovascular mortality in uncontrolled DM patients. A). K-M curves of DM-related survival rate with different PNI quartiles. B). K-M curves of cardiovascular survival rate with different PNI quartiles. Differences of survival rates among PNI quartiles were assessed by Log-rank test, and a P value < 0.05 was significant. PNI, prognostic nutritional index; DM, Diabetes Mellitus; K-M curves, Kaplan-Meier curves

Full size image

Baseline PNI level was negatively associated with DM-related and cardiovascular mortality in a non-linear pattern (Additional file 1: Figure S2). Univariable analysis indicated that higher PNI levels were associated with reduced incidence of both DM-related and cardiovascular deaths (Additional file 2: Table S1). Multivariable analyses generated consistent results that the HRs for DM-related mortality decreased across the PNI quartiles compared to the lowest quartile (Q2 vs. Q1,adjusted HR = 0.503, 95% CI 0.358–0.707, P < 0.001; Q3 vs. Q1, adjusted HR = 0.397, 95% CI 0.275–0.574, P < 0.001; Q4 vs. Q1, adjusted HR = 0.303, 95% CI 0.201–0.459, P value < 0.001; see in Table 2). Furthermore, univariable and multivariable analyses also suggested that higher PNI level independently predicted a lower risk of cardiovascular mortality (Q2 vs. Q1, adjusted HR = 0.638, 95% CI 0.447–0.909, P = 0.013; Q3 vs. Q1, adjusted HR = 0.348, 95% CI 0.226–0.539, P < 0.001; Q4 vs. Q1, adjusted HR = 0.379, 95% CI 0.242–0.592, P value < 0.001; Table 2).

Table 2 The prognostic value of PNI for cardiovascular and DM-related mortality in uncontrolled DM
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Subgroup analyses

Interaction tests and survival analyses stratified by covariates in interested were performed and illustrated in Fig. 3 and Additional file 1: Figure S3. A significant interaction was observed between PNI levels and DM treatment conditions for DM-related mortality (all P for interaction < 0.05). In patients with uncontrolled DM, the prognostic effect of higher PNI level was more pronounced in patients with insulin, regardless of the OADs treated (OADs + insulin treated: adjusted HR = 0.832, 95% CI 0.760–0.911, P < 0.001; Insulin treated: adjusted HR = 0.863, 95% CI 0.811–0.918, P < 0.001). The higher PNI level remained to be an independent predictor for lower DM-related mortality in patients treated with OADs treated alone (adjusted HR = 0.894, 95% CI 0.837–0.954, P < 0.001). However, there was no significant association between PNI levels and DM-related mortality in patients with untreated DM (adjusted HR = 1.050, 95% CI 0.869–1.270, P = 0.614).

Fig. 3
figure 3

Associations of PNI level and clinical outcomes across different subgroups. The associations of PNI level and DM-related mortality were assessed using the same multivariable cox regression model 3 in each subgroup. PNI, prognostic nutritional index; DM, Diabetes mellitus; HR, hazard ratio; CI, confidence interval; SBP, systolic blood pressure; OADs, oral antidiabetic drugs

Full size image

Discussion

In this large cohort, we found that higher PNI levels were independently associated with lower risks of DM-related and cardiovascular mortality, even after adjusting for potential covariates. Moreover, there was a significant interaction between PNI level and DM treatment conditions. The predictive value of PNI level was significant in patients receiving antidiabetic treatment, but not in untreated individuals. Our findings suggested that improved immuno-nutritional status may enhance the efficacy of DM treatment, especially insulin therapy, and reduce the mortality risks in patients with uncontrolled diabetes.

Recent epidemiological study has revealed an alerting increase of 90.5% of the age-standardized DM prevalence from the past few decades [4, 17], indicating the great healthcare burden of this disease. Despite advancements in the recognition of DM among physicians and patients, the rates of awareness and glycemic control remained suboptimal [6, 7, 13]. It is well-known that patients with persistent hyperglycemia tend to have adverse clinical outcomes, as chronic hyperglycemia would lead to glycemic toxicity and insulin resistance, contributing to microvascular and macrovascular complications through endothelial dysfunction, chronic inflammation, and microenvironmental hypoxia [8,9,10, 25]. Previous studies have merely demonstrated that the inactive lifestyles, being hypertensive and social-economic status were risk factors for uncontrolled DM in the cross-sectional cohort [7, 13, 26]. However, considering the large number of uncontrolled DM patients and limited access to public medical care in the vase developing countries, convenience parameters using to further identify high risks of adverse cardiovascular events or mortality in the uncontrolled DM population were still in need. In this study, we were the first to prove that the higher PNI level was an independent protective predictor for DM-related and cardiovascular mortality. Our results indicated that the PNI level could help to identify high-risk patients in uncontrolled DM, allowing for timely and targeted treatment interventions and improvement of prognosis.

The PNI was first proposed by Buzby et al., [27] and was calculated by both plasma lymphocyte and albumin concentrations, serving as a comprehensive indicator reflecting both chronic inflammation and nutritional status [28]. Emerging literatures have revealed that PNI level was an independent predictor for all-cause mortality and adverse cardiovascular events in general population and type 2 DM patients [18, 19, 29]. Recent studies also showed that the higher PNI level is a protective factor for comorbidities of DM, such as diabetic nephropathy and diabetic retinopathy [20,21,22]. In our population of uncontrolled DM, we identified a significant association between the higher PNI levels and a reduced incidence of DM-related mortality. The above findings suggested that PNI might play a critical role in the onset pathogenesis of the hyperglycemia, complications, and mortality of DM. Elevating the PNI level through increased dietary protein intake or reducing inflammatory stress could substantially improve the prognosis in all DM patients.

Chronic inflammation has widely existed in patients with DM, and plays crucial roles in the pathogenesis of DM and its cardiovascular complications [17]. The chronic inflammatory response might dysregulate the gut flora, exacerbate vascular hypoxia or oxidative stress, alter expression pattern of related genes, and finally induce metabolic disorder and vascular dysfunction [30, 31]. On the other hand, the dysregulation of lipid, protein and glucose metabolism in DM patients would also trigger the release of pro-inflammatory cytokines and exacerbate the harmful effects of systematic inflammation [10, 32]. Therefore, drugs targeting the anti-inflammatory mechanisms have been recently applied in DM patients in pilot trial and have been found to reduce cardiovascular events [33, 34]. Previous studies have been widely shown a negative association of the PNI level and inflammation markers, such as neutrophil lymphocyte ratios, C-reactive protein and systematic inflammatory index [35, 36]. In our study, we also showed that the PNI level was negatively correlated with WBC, neutrophils count, and monocytes count. We also find that patients with insulin treatment presented a lower PNI level than those untreated or treated with OADs. One possible explanation was that the insulin treatment was often used in such conditions: adequate use of OADs could not control blood glucose, combination of stress status or severe comorbidities, or type I DM. Patients in the above conditions suffered a more severe long-term inflammatory status, hence they presented lower PNI levels. These findings indicated that the PNI level might help to guide the use of anti-inflammatory drugs in DM patients in the future.

Additionally, literatures indicated that malnutrition status was significantly associated with chronic inflammation, cardiac remodeling and unfavorable clinical outcomes in DM patients [37]. A comparative analysis conducted by JL Zhang et al. revealed that the PNI level was superior to other nutritional parameters in predicting DM-related adverse outcome [38]. In our study, the PNI level was proved to correlate with the prognosis of uncontrolled DM for the first time. Moreover, subgroup analyses found that the higher PNI level remained to be an independently protective predictor for DM-related and cardiovascular mortality in both sex, and among all types of race and all age groups, which was in line with other studies conducted in general or DM population [29, 37]. Notably, we found that the predictive value of PNI for DM-related deaths varied in DM patients with different treatment conditions. The prognostic value of PNI level was more pronounced in patients receiving insulin therapy, regardless of the OADs, and remained to be significant in patients with OADs alone. Here were the possible explanations: firstly, chronic inflammation and malnutritional status, reflected by a low PNI levels, might attenuate the absorption of antidiabetic drugs through dysregulation of the gut flora and attenuate the efficacy of OADs [30, 31]. Moreover, the antidiabetic therapies, especially the insulin, had been reported to exert glucose lowering effects partly through anti-inflammatory actions [39]. Therefore, low PNI patients tended to require a potent therapy to control both inflammatory status and blood glucose level, and finally reduce adverse outcomes. We also found that the PNI level did not exhibit a significant protective effect in untreated DM patients. This result indicated that the combination of timely drug and lifestyle interventions (such as improving PNI level) is more significant than lifestyle intervention alone in improving the prognosis of DM patients. Our findings suggested that improving nutritional status and the use of anti-inflammatory treatment might help glycemic control in patients with antidiabetic therapy.

There were some limitations in this study. Firstly, the DM diagnosis was based on the self-reported questionnaires rather than the medical records, potentially leading to underreporting or missed cases. However, the large sample size ensured the reliability of our results. Secondly, as a retrospective analysis, we lacked detailed information on the use of antidiabetic therapies, including dosage, duration, and changes during the follow-up period. Thus, prospective clinical studies are needed to validate our findings in the future.

Conclusions

We provided robust evidence that PNI level was an independent protective predictor for both DM-related and cardiovascular mortality in uncontrolled DM patients, specifically those receiving one or several antidiabetic treatments. This study demonstrated that the PNI level was valuable and convenient to identify high risk for adverse outcomes in uncontrolled DM patients. Moreover, considering immune-nutritional status together with antidiabetic therapies might help to achieve optimal glycemic control.

Data availability

All data used in our study were available in the at the CDC website: https://wwwn.cdc.gov/nchs/nhanes/default.aspx.

Abbreviations

CI:

Confidence interval

DM:

Diabetes mellitus

HbA1c:

Hemoglobin A1c

HDL:

High-density lipoprotein

HR:

Hazard ratio

NHANES:

National healthy and nutritional examination survey

OADs:

Oral antidiabetic drugs

PNI:

Prognostic nutritional index

SBP:

Systolic blood pressure

TC:

Total cholesterol

TG:

Triglyceride

TP:

Total protein

WBC:

White blood cell

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Acknowledgements

The authors acknowledged all the stuff and participants for providing information and consents used in this study.

Funding

Capital’s Funds for Health Improvement and Research (CFH 2022-1-2062).

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Author notes

  1. Fei Liu and Zhili Jiang are the joint first authors.

Authors and Affiliations

  1. Center of Coronary Heart Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China

    Fei Liu, Zhili Jiang, Wei Luo, Yunxiao Yang, Shuai Guo, Jiayi Yi, Geng Shen, Wei Li, Lin Wang, Xiuhuan Chen, Zhaogong Zhi, Tian Liu, Xuedong Zhao, Chen Li & Hai Gao

  2. Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China

    Fei Liu, Zhili Jiang, Wei Luo, Yunxiao Yang, Shuai Guo, Jiayi Yi, Geng Shen, Wei Li, Lin Wang, Xiuhuan Chen, Zhaogong Zhi, Tian Liu, Xuedong Zhao, Chen Li & Hai Gao

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  1. Fei Liu
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Contributions

F.L. and Z.L.J. contributed to the conception, study design, and the draft of the manuscript. W.L., Y.X.Y., S.G., J.Y.Y., G.S., W.L., L.W., X.H.C., Z.G.Z., X.D.Z. contributed to the data acquisition and interpretation. C.L. contributed to the data acquisition, statistical analysis, and critically revision of the manuscript. H.G. contributed to the study design and the valuable suggestions on the manuscript drafting.

Corresponding authors

Correspondence to Chen Li or Hai Gao.

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Ethnic approval was obtained from the institutional review board of the NCHS, and written consent for publication was obtained from all participants in NHANES.

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The authors declare no competing interests.

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Liu, F., Jiang, Z., Luo, W. et al. Implications of prognostic nutritional index in predicting adverse outcomes of uncontrolled diabetic patients: a cohort study of the national health and nutrition examination survey from 2005 – 2018. Diabetol Metab Syndr 16, 315 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13098-024-01563-x

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13098-024-01563-x

Keywords

Diabetology & Metabolic Syndrome

ISSN: 1758-5996

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