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Abstract
Aims This study aimed to evaluate the relationship between both low and high osmolarity and the risk of all-cause and cause-specific mortality in diabetic population.
Methods All participants were included from the National Health and Nutrition Examination Survey 1999–2014. Baseline serum osmolality was determined from laboratory tests and cause of death from national death records. HRs and 95% CIs for all-cause mortality and cardiovascular mortality in diabetes were estimated using Cox proportional regression analysis. The non-linear relationship was explored using restricted cubic splines regression.
Results Among 7622 individuals with diabetes, 1983 (12.4%) died during a total of 3.26 thousand person-years of follow-up. Compared with the reference category (281–284 mmol/kg), the multivariable-adjusted HRs and 95% CIs for all-cause mortality were 1.27 (1.16–1.40; p<0.001) in the lowest osmolality category (<201 mmol/kg) and 1.18 (1.09–1.28; p<0.001) in the highest osmolality category (>312 mmol/kg). Restricted cubic splines results showed that serum levels of osmolality had a U-shaped association with the risk of all-cause mortality, and L-shaped relationship with the risk of cardiovascular death.
Conclusions Both low osmolality and high osmolality were predictive of increased all-cause mortality in patients with diabetes, supporting a U-shaped relationship. Also, a lower serum osmolality increased the risk of cardiovascular mortality.
- Diabetes Mellitus, Type 2
Data availability statement
Data are available upon reasonable request.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
Previous studies have confirmed the association between serum osmolarity and health outcomes in different population.
WHAT THIS STUDY ADDS
Both low osmolality and high osmolality were predictive of increased all-cause mortality in diabetes.
A lower serum osmolality increased the risk of cardiovascular mortality.
The inflection points of osmolality on all-cause and cardiovascular mortality were 281 mmol/kg.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
The serum osmolality should be controlled at a reasonable range in patients with diabetes.
Introduction
Osmolality serves as an indicator of dehydration, reflecting the volume of extracellular fluid.1 Serum osmolality in humans is regulated in the range of 275–295 mOsmol/kg H2O.2 A previous study showed that being close to the upper limit of normal range (292–293 mOsm/kg) seems to be the optimal plasma osmolality level in terms of cardiovascular prognosis in patients with heart failure (HF).3 However, hyperosmolarity has also been reported as a risk for developing hypertension regardless of salt intake.4 Decreased serum osmolality might be associated with poor prognosis after Fontan procedure.5 An acute decrease in serum osmolality was also a risk factor for potentially severe postoperative neurologic complications following kidney transplantation.6 It has been proven that the components of the formula, namely sodium,7 blood urea nitrogen,8 serum glucose,9 and other parameters interacting with osmolality such as serum albumin10 and renal function,11 affect all-cause and cause-specific mortality in general population, while few studies have elucidated about the prognostic meaning of osmolality itself in all-cause and cause-specific mortality in diabetic population.
In our study, we investigated the association between levels of osmolality and the risk of all-cause mortality and cause-specific mortality in diabetic population.
Method
Study population
The participants were selected from the National Health and Nutrition Examination Survey cycle of 1999–2014, a nationwide survey conducted by the National Center for Health Statistics. The survey was designed to assess the health and nutritional status of the non-institutionalized US population by a stratified and multistage sampling design. Participants with missing records on osmolality and mortality were excluded from our analysis. After excluding participants with missing records on osmolality (n=279) and mortality (n=48), a total of 7622 participants with diabetes were eligible for our study.
Exposure and endpoints
The sodium, glucose and blood urea nitrogen concentrations were determined from standard biochemistry laboratory tests. Serum osmolality was calculated from the Dorwart-Chalmers formula, that is, serum osmolality=1.86×[sodium (mmol/L)]+glucose (mg/dL)/18+blood urea nitrogen (mg/dL)/2.8+9.12 Participants were stratified by osmolality quintiles (Q1–Q5), with Q1 representing patients with lowest osmolality values and Q4 representing patients with highest osmolality values. The primary endpoint was all-cause mortality while the secondary endpoints included death from cardiovascular disease (CVD) or malignant neoplasms, which were obtained by linkage to the National Death Index followed by December 31, 2015. CVD was defined as International Classification of Diseases 10th Revision (ICD-10) codes I00–I09, I11, I13, or I20–I51. Malignant neoplasm was defined as ICD-10 codes C00–C97.
Covariates collection
Data on sex, age, race, education level, poverty income ratio (PIR), smoking, drinking, activity, and comorbid illness were collected by using standardized questionnaires. The levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), and estimated glomerular filtration rate (eGFR) were measured by standard biochemistry assays. The body mass index (BMI) of each participant was obtained from the physical examinations. The PIR is a ratio of family income to poverty threshold to create three categories of income status, low (PIR<1), mid (1–3) and high (>3), as an indication of socioeconomic status based on eligibility for receiving benefits. A history of hypertension and CVD were determined from self-reports. Multiple imputation was performed for missing values.
Statistical analysis
Numeric parameters were expressed as the mean±SD and categorical variables were presented as numbers (percentages). Comparisons between the osmolality quintiles were examined using the χ2 (categorical variables) and analysis of variance (continuous variables) tests. Survival probability was assessed using the Kaplan-Meier method. Multivariable Cox proportional regression models were constructed to explore the relationship between osmolality, as a continuous variable or a categorical variable, and all-cause and cause-specific mortality. Model 1 was adjusted for age and male sex. Model 2 was additionally adjusted for education level, race, PIR, BMI, smoking, drinking, and activity. Model 3 was additionally adjusted for hypertension, CVD, total cholesterol, LDL, and eGFR. Restricted cubic splines were used to describe the non-linear relationship between osmolality and all-cause mortality and cardiovascular mortality. If non-linearity was detected, we constructed a two-piecewise Cox regression model to calculate the threshold effect of osmolality on mortality. All statistical analysis was performed using IBM SPSS V.25.0. A p value <0.05 was considered as statistically significant.
Results
The demographic characteristics of 7622 participants were presented in table 1. Compared with participants with lower levels of osmolality, population with higher osmolality levels had more percentage of men, non-Hispanic white, and comorbid illness (hypertension and CVD) and higher levels of BMI, total cholesterol, and LDL.
Characteristics of the study population according to osmolality quintiles
Kaplan-Meier survival curves confirmed that the osmolality category was associated with all-cause mortality risk and cardiovascular mortality (all log rank p<0.05; figure 1). Compared with the reference category (281–284 mmol/kg), the multivariable-adjusted HR and 95% CI for all-cause mortality was 1.27 (1.16–1.40; p<0.001) in the lowest osmolality category (<201 mmol/kg) and 1.18 (1.09–1.28; p<0.001) in the highest osmolality category (>312 mmol/kg). Compared with the reference category, the multivariable-adjusted HR and 95% CI for cardiovascular death was 1.50 (1.19–1.90; p<0.01) in the lowest osmolality category (table 2).
The Kaplan-Meier analysis between the osmolality quintiles and all-cause mortality (A) and cardiovascular mortality (B). All log rank p<0.05.
Association of osmolality with all-cause and cause-specific mortality
Furthermore, restricted cubic splines suggested that serum osmolality was non-linearly associated with all-cause (p for non-linearity <0.001) and cardiovascular mortality (p for non-linearity=0.005) (figure 2).
The restricted cubic regression between the osmolality quintiles with all-cause mortality (A) and cardiovascular mortality (B).
Threshold effect analysis revealed that the inflection points of osmolality on all-cause and cardiovascular mortality were 281 mmol/kg. On the left side of the inflection point, all-cause mortality decreased with increasing osmolality (β=0.97, 95% CI 0.96–0.98). On the right side of the inflection point, all-cause mortality increased with increasing osmolality (β=1.06, 95% CI 1.05–1.07) (table 3).
Threshold effect analysis of osmolality on all-cause and cardiovascular mortality using piecewise binary Cox regression models
Discussion
In this study involving a total of 7622 adults, we investigated the correlation between osmolality and risk of mortality. We showed that both low osmolality and high osmolality were predictive of increased all-cause mortality. Also, serum osmolality had L-shaped relationship with the risk of cardiovascular death. Due to the nature of simplicity, convenience and low cost, serum osmolality was helpful in identifying high-risk individuals and predicting their long-term health.
Osmolality is a crucial parameter in dilute solutions, including extracellular and intracellular fluids in the body.13 According to the differences between the solute amounts of the medium, osmolality can be classified into three: isotonic, hypertonic, and hypotonic.14 It is known that the extracellular medium contains various proteins, polysaccharides, and macromolecules and micromolecules. Therefore, the osmolality of the extracellular medium changes with the transport between the inside and outside of the cell.15 Previous studies have investigated the association between serum osmolarity and health outcomes in different population. Lower discharge serum osmolality was reported to predict worse postdischarge mortality,16 while a higher serum osmolarity also predicted a worse outcome in patients with HF.17 Besides, osmolarity was proved to have a U-shaped relationship with the risk of mortality in acutely ill patients,18 in pulmonary patients in intensive care unit19 or other critical admission diagnoses.20 Our results further demonstrated that osmolality levels had U-shaped association with cardiovascular mortality in diabetes.
The underlying mechanisms that influence the relationship between osmolality and all-cause mortality are not clear. First, osmolality is indicative of blood glucose levels, which contributes to the overall solute concentration. Increased osmolality leads to symptoms such as osmotic diuresis, exacerbating dehydration and electrolyte imbalances. In addition, the cells and tissues are adaptive to hypertonic stress in diabetes. A low osmolality shock can increase the cell swelling and enhance the cytocidal effects, leading to the cell shrinkage21 22 and rupture.23 Besides, low-serum osmolality was associated with many features of advanced HF, which may reflect high in-hospital and postdischarge neurohormonal activity, increasing cardiovascular mortality. Further research is needed to elucidate the more detailed mechanisms.
There were several limitations to this study. First, the cross-sectional design of the study precluded us from establishing a causal association. Second, the mechanism underlying the relationship between osmolality and mortality was not very clear, which needs to be further validated in prospective cohort studies.
Conclusion
Our study found that both low osmolality and high osmolality were associated with increased all-cause mortality in diabetic population, supporting a U-shaped relationship. Also, a lower serum osmolality increased the risk of cardiovascular mortality. Our findings provide further evidence for the predictive role of serum osmolality on long-term health outcomes of patients with diabetes.
Data availability statement
Data are available upon reasonable request.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants and was approved by the Institutional Review Board of National Center for Health Statistics (Protocol No 98-12). Participants gave informed consent to participate in the study before taking part.
Footnotes
TH and CL contributed equally.
Contributors AG and JG designed the study. TH and CL performed the statistical analysis. TW and HL wrote the manuscript. All authors approved the final manuscript. AG was responsible for the overall content as the guarantor.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.