Utafiti: Kunywa Maji Mengi kunapunguza hatari ya kupata Magonjwa na kufa mapema

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Middle-age high normal serum sodium as a risk factor for accelerated biological aging, chronic diseases, and premature mortality​

Summary​

Background​

It is known that some people age faster than others, some people live into old age disease-free, while others develop age-related chronic diseases. With a rapidly aging population and an emerging chronic diseases epidemic, finding mechanisms and implementing preventive measures that could slow down the aging process has become a new challenge for biomedical research and public health. In mice, lifelong water restriction shortens the lifespan and promotes degenerative changes. Here, we test the hypothesis that optimal hydration may slow down the aging process in humans.​

Methods​

We performed a cohort analysis of data from the Atherosclerosis Risk in Communities study with middle-age enrollment (45–66 years, n = 15,752) and 25 years follow-up. We used serum sodium, as a proxy for hydration habits. To estimate the relative speed of aging, we calculated the biological age (BA) from age-dependent biomarkers and assessed risks of chronic diseases and premature mortality.​

Findings​

The analysis showed that middle age serum sodium >142 mmol/l is associated with a 39% increased risk to develop chronic diseases (hazard ratio​

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= 1.39, 95% confidence interval [CI]:1.18–1.63) and >144 mmol/l with 21% elevated risk of premature mortality (HR = 1.21, 95% CI:1.02–1.45). People with serum sodium >142 mmol/l had up to 50% higher odds to be older than their chronological age (OR = 1.50, 95% CI:1.14–1.96). A higher BA was associated with an increased risk of chronic diseases (HR = 1.70, 95% CI:1.50–1.93) and premature mortality (HR = 1.59, 95% CI 1.39–1.83).​

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Interpretation​

People whose middle-age serum sodium exceeds 142 mmol/l have increased risk to be biologically older, develop chronic diseases and die at younger age. Intervention studies are needed to confirm the link between hydration and aging.​

Funding​

This work was funded by Intramural Research program of the National Heart, Lung, and Blood Institute (NHLBI). The ARIC study has been funded in whole or in part with federal funds from the NHLBI; the National Institutes of Health (NIH); and the Department of Health and Human Services.​

Keywords​

Evidence before this study​

In this study, we aimed to evaluate pro-aging effects of mild subclinical hypohydration that activates water conservation mechanisms leading to the excretion of lower volume of more concentrated urine but does not elevate plasma sodium and osmolality beyond normal ranges. We searched PubMed, and Web of Science, without any language restriction using combinations of the terms “serum sodium,” “hydration,” “aging,” “biological aging,” “chronic diseases,” “mortality.” We focused on finding studies assessing associations between the hydration status of healthy people at middle age or younger with a long-term aging-related outcomes such as future development of chronic diseases or premature mortality. We also were looking for studies estimating biological age in relation to the markers of habitual low hydration such as serum sodium. We did not find studies relating markers of subclinical hypohydration at middle age with the speed of biological aging. Several observational epidemiological studies identified associations of the hydration markers with future development of heart failure, metabolic disease and mortality. Increased risk of mortality after 3–6 years of follow-up was demonstrated among people with serum sodium in the upper end of normal range.​

Added value of this study​

Current study presents a comprehensive analysis of a large population-based observational study with a long 25-years follow-up. The analysis demonstrated that middle-age serum sodium in the upper part of normal range (135–146 mmol/l) is able to predict faster rate of the biological aging, and an increased burden of chronic diseases later in life, including heart failure, dementia, chronic lung disease, stroke, diabetes, peripheral vascular disease and atrial fibrillation. The analysis identified serum sodium threshold of 142 mmol/l that can be used in clinical practice to identify people at risk.​

Implications of all the available evidence​

Findings from this and previous studies are consistent with the hypothesis that decreased hydration may accelerate aging. The findings suggest that people whose serum sodium exceeds 142 mmol/l may benefit from a more thorough clinical evaluation of their hydration status, including fluid intake habits and pathological conditions that may predispose to an increased water losses. The results warrant testing possible anti-aging effects of improved hydration in interventional trials, and support addition of recommendations for optimal fluid intake in the prevention guidelines.
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Introduction​

Finding and implementing preventive measures that can slow down the aging process is currently recognized as a major challenge of preventive medicine to combat the epidemic of age-dependent chronic diseases that is emerging as a result of a rapidly aging world population.

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A new research field of geroscience aims to develop safe, practical, and widely available interventions targeting aging: a common driver of chronic diseases. Accumulating findings suggest that slowing the aging processes and extending healthy life span has a potential to improve quality of life and decrease health care cost to a substantially greater degree than a cure of any single disease.

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Disparities in the pace of biological aging are already detectable at midlife

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indicating that preventive measures that can be applied early in life would be most effective to slow down the aging processes and decrease the burden of chronic diseases.

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In the current study, we test the hypothesis that optimal hydration may slow down the aging process. Here, we define hypohydration as a state in which water conservation mechanisms, including the secretion of antidiuretic hormone and renal urine concertation, are activated when low water intake or high water loss result in decreased body water content and elevated plasma tonicity.

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This hypothesis was inspired by previous mouse studies in which lifelong water restriction, increasing serum sodium by 5 mmol/l, shortened the mouse lifespan by 6 months which corresponds to about 15 years of human life.

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The shortened life span was accompanied by accelerated degenerative changes within multiple organ systems of the chronically hypohydrated mice. In humans, there is a large variation in daily amounts of fluids consumed and worldwide surveys find that a large proportion of people do not consume the recommended amounts and are hypohydrated

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In order to test the hypothesis that hydration can affect speed of aging, we analyzed data from Atherosclerosis Risk in Communities (ARIC) study: an ongoing population-based prospective cohort study in which 15,792 45-66 year-old black (African American) and white men and women were enrolled from four US communities in 1987–1989 and followed up for more than 25 years.

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We used serum sodium, that increases when we drink less fluids,

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as a proxy for the hydration habits of study participants

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In our previous preliminary assessment of ARIC study participants who lived until old age (70–90 years), we noticed increased prevalence of many chronic diseases among people with middle-age serum sodium in the upper part of the normal reference range.

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Further detailed time-to-event analysis adjusted for major cardiovascular risk factors to exclude possible confounding identified high normal serum sodium, as well as other hydration measures, such as body water deficit and blood tonicity, as independent risk factors for heart failure.

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In healthy people, hypohydration is reflected in increased serum sodium concentration and tonicity.

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Normal serum sodium range, defined as the interval that 95% of reference healthy population fall into, lies between 135 and 146 mmol/l. In a healthy person, free of diseases affecting water and electrolytes balance regulation, there are two major mechanisms that are activated in response to hypohydration: thirst and ADH release.

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Both these mechanisms are controlled by plasma tonicity that depends on the concentration of osmotically active plasma solutes with sodium and glucose being the main contributors. When plasma tonicity increases due to decreased water intake, water conservation mechanisms are activated including release of antidiuretic hormone (ADH) from the posterior pituitary gland,

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that then acts on the kidney resulting in the excretion of a lower volume of more concentrated urine. In the absence of hyperglycemia or renal failure, the sodium concentration is the chief determinant of plasma tonicity representing 96%–98% of its value of 275–295 mosmol/kg. The tonicity threshold that stimulates ADH secretion varies in a narrow range around 285 mosmol/kg that would correspond to approximately 140–142 mmol/l of serum sodium.

Here, to test the hypothesis that hydration has a systemic effect on the aging processes, we assessed association of middle-age serum sodium with risk of premature mortality, rate of biological aging and burden of chronic diseases. The analysis showed that people whose serum sodium exceeded 142 mmol/l had increased risk to be biologically older, develop chronic diseases and die at younger age.​

Methods​

Dataset​

We used data from the ARIC study. The data were obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). The datasets were redacted to remove personal identifiers to conform to the individual informed consent restrictions. Transfer of datasets was approved by the NIH Office of Human Subjects Research and was excluded from Institutional Review Board review as Not Human Subjects Research, based on the interpretation of 45 CRF 46 under “Research Involving Coded Private Information or Biological Specimens” and Guidance on Engagement of Institutions in Human Subjects Research (October 16, 2008). For current analyses, we used outcome variables, exposure variables and covariates from the data collected and curated by the ARIC study investigators and obtained by us from the BioLINCC data repository.​

Study population: overview of recruitment and follow-up​

ARIC is an ongoing population-based prospective cohort study in which 15,792 black and white men and women aged 45–66 years were enrolled from four U.S. communities in 1987–1989. A detailed study design description has been published.

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Each community cohort was selected in the ARIC study by probability sampling from lists of persons with driver's licenses or state identification cards, or persons eligible for jury duty. To ensure that all individuals in eligible age group had equal chances of being selected, households were identified after a random selection process was performed. Home interview was administered to each potential cohort member that included items on cardiovascular risk factors, socioeconomic factors, and family medical history. This was followed by an invitation to the clinic examination. Participants were asked to fast for 12 h and bring all medications they used within the last two weeks to the examination.

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Detailed analysis of response rates and characteristics of responders and non-responders was performed for this study that allows to estimate the degree of selection bias.

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In summary, among age-eligible individuals, 77% of white people and 72% of black people completed the home interview. 68% of white and only 46% of black eligible individuals also completed the clinical examination and became the study participants.

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There were three subsequent visits at approximately 3-year intervals (Visit 2 in 1990–1992; Visit 3 in 1993–1995; Visit 4 in 1996–1998) followed by visit 5 in 2011–2013 (Fig. 1a). Participants have been contacted semi-annually since baseline, to obtain information about hospitalizations and for additional data collection.

Fig. 1Middle-age serum sodium and risk of all-cause mortality in Atherosclerosis Risk in Communities (ARIC) study. a) Overview of ARIC study and exclusion criteria. b, c, d) Splitting study participants into four groups using classification and regression trees (CART) algorithm based on average serum sodium measured at visits 1 and 2 and cumulative mortality by the end of 25 years follow-up. b) Overview of CART algorithm outcome for the group splitting. c) Histograms showing distributions of the study participants according to serum sodium. Groups identified by CART algorithm are shown in different colors. Mortality rate by the end of 25 years follow-up and number of people in each group are shown above histogram. d) Average age does not differ between sodium groups. e, f) Assessment of relative risk for all-cause mortality in four sodium groups. e) Kaplan–Meier Survival Analysis: P < 0.001 (Log–Rank test). All Pairwise Multiple Comparison Procedures): ∗P = 0.04, ∗∗P = 0.001 (Holm-Sidak method). See Table S2 for N at risk at each time point. f) Time-to-event analysis: COX proportional hazard model. People whose middle-age serum sodium exceeds 144 mmol/l or is lower than 137 mmol/l have increased risk of dying at earlier age. See also Table S2 for descriptive statistics and demographic data for these four sodium groups.​

Ethics​

The ARIC study protocol was approved by the Institutional Review Board of each participating center.

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Written informed consent was obtained from participants at each study visit. Detailed information about participating institutions can be found on the study website: sites.cscc.unc.edu/aric.

Study objectives and overview of the analytical approach​

The main goal of the analysis performed in the current study is to find out whether higher serum sodium at middle age is associated with accelerated aging and to identify serum sodium thresholds that can be used in clinical practice to identify people at risk who can potentially benefit from improved hydration. The overview of the study analyses is shown on Fig. S1. To access speed of aging, we used three indicators of faster aging process. Two main age-related outcomes/endpoints were analyzed: 1) age-related chronic diseases and 2) all-cause mortality. We used these aging indicators as outcome variables in the time-to-event analyses with middle age serum sodium as exposure variable (Fig. S1, Analysis 1). Third measure of the aging process that we used in this study was biological age (BA) that was calculated from age-dependent biomarkers. BA have been shown to characterize aging process and predicts mortality better than chronological age

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We first used BA at baseline as exposure variable in the time-to-event analysis to assess its ability to predict age-dependent outcomes, namely chronic diseases and mortality, in the ARIC cohort (Fig. S1, Analysis 2). To assess a link between serum sodium and BA, we then performed cross-sectional logistic regression analysis using serum sodium as exposure variable and BA as dependent variable (Fig. S1, Analysis 3).

Exclusions​

Since the purpose of this analysis was to examine effects of hydration, we aimed to exclude people whose serum sodium could be affected by other factors in addition to the amount of liquids they consume. Therefore, to avoid including people with possible abnormalities of water/salt balance regulation, we excluded people who had an average sodium concentration from Visits 1 and 2 outside normal reference range of 135–146 mmol/l. We also excluded participants with plasma glucose level higher than 140 mg/dL at visits 1 and 2, since hyperglycemia, in spite of causing dehydration, results in decrease of serum sodium concentration.

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Since obesity is known to alter distribution of body fluids and elevates serum sodium, we excluded participants with averaged body mass index (BMI) greater than 35 kg/m2 at visits 1 and 2.

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After these exclusions, 11,255 participants remained in the dataset. For BA calculations, we additionally excluded participants who were taking blood pressure (BP) and cholesterol lowering medications, since systolic BP and total cholesterol were included as biomarkers for these calculations and the medications would change real values for these biomarkers (N = 6956). In each analysis, people with missing data were also excluded.

Calculation of biological age​

We calculated BA of the ARIC study participants at Visit 2, that was used as the study baseline, using the Klemera and Doubal method. BA estimated by this method have been shown to be a reliable predictor of mortality performing superior to chronological age

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and also a good predictor of aging rates in young adults.

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We selected biomarkers for BA calculation based on knowledge about their age dependency, role in aging process, good performance in previous BA calculations

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and availability in ARIC study. We selected 15 biomarkers characterizing performance of multiple organ systems and processes: cardiovascular (systolic blood pressure), renal (eGFR, cystatin-C, urea nitrogen, creatinine, uric acid), respiratory (FEV), metabolic (glucose, cholesterol, HbA1c, glycated albumin, fructosamine), immune/inflammatory (CRP, albumin, beta 2-microglobulin). We assessed age-dependence of the biomarkers by Pearson correlation analysis with age and selected 9 biomarkers with strongest correlation for the BA calculations. For sensitivity analysis, we also calculated BA using all 15 biomarkers. The results are presented on Fig. 3.

Middle-age serum sodium and risk to develop age-related chronic diseases. a) Age dependence of chronic diseases. Cumulative incidence curves (CIFs) accounting for competing mortality for eight age-dependent chronic diseases in ARIC study participants (N = 11,255). Right panel shows how diseases are combined into two sets containing four and seven diseases for following analysis of chronic diseases burden. b-d) Analysis of chronic diseases burden in 5168 ARIC study participants aged 70–90 years who attended visit 5 at the end of 25 years follow-up. b) Distribution of the study participants based on number of diseases from Set 1 (blue) and Set 2 (orange) that they are diagnosed with. c, d) Analysis of association between middle-age serum sodium and risk to develop chronic diseases from Set 1. c) Splitting study participants into four groups using classification and regression trees (CART) algorithm based on average serum sodium measured at visits 1 and 2. Percent of people diagnosed with at least one out of four diseases from Set 1 by the end of follow-up was used as outcome variable for the splitting algorithm. d) Assessment of relative risk to develop at least one disease from Set 1 in four sodium groups. Participants are divided into 2 groups: 0 – disease-free at the end of follow-up; 1 – have at least one disease. Left panel: Time-to-event analysis: Cox proportional hazards model. Right panel: Retrospective case–control analysis: multivariable logistic regression. Participants with serum sodium 138-140 mmol/l have lowest risk to develop chronic diseases. Both lower and higher sodium concentrations are associated with increased risk. See also Fig. S3 for analysis of Set 2 diseases.​

Calculation of biological age (BA) based on age-dependent biomarkers. Fifteen biomarkers were selected based on prior knowledge of their age-dependence and availability in ARIC study. a, b) Verification of age-dependence for 15 biomarkers measured in ARIC study participants at visit 2 (n = 6,956, see methods and Fig. S1 for exclusions criteria). a) Linear regression lines for nine biomarkers that showed significant correlation with age and were used for BA calculations. 95% CI for the regression lines are shown in blue. rage denotes Pearson Coefficient for correlation of each biomarker with age (∗∗∗P < 0.0001). Pslope denotes P-value for the slope deviation from zero. The panel inserts show distribution of the study participants based on the corresponding biomarkers. b) rage and Pslope for six additional biomarkers with lower correlation coefficients that were included for BA calculation based on 15 biomarkers. c) Distributions of the study participants based on their chronological age (Age) and BA calculated from 9 to 15 biomarkers using Klemera and Doubal's method (see methods section for details). Distributions of BA from nine and 15 biomarkers are almost identical with Pearson correlation r = 0.99 (†P < 0.0001) indicating that they gave similar results.


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