Nonfood Probiotic, Prebiotic, and Synbiotic Use    Reduces All-Cause And Cardiovascular Mortality Risk In Older Adults: A Population-Based Cohort Study

doi:10.21203/rs.3.rs-2630152/v1

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Nonfood Probiotic, Prebiotic, and Synbiotic Use Reduces All-Cause And Cardiovascular Mortality Risk In Older Adults: A Population-Based Cohort Study

https://doi.org/10.21203/rs.3.rs-2630152/v1

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Objectives

Pro-, pre-, and synbiotic supplements improve cardiovascular risk factors. However, the association between nonfood pro-, pre-, and synbiotics and long-term all-cause and cardiovascular mortality have not been studied. Thus, our objective was to determine the impact of nonfood pro-, pre-, and synbiotics to all-cause and cardiovascular mortality.

Design, setting, and participants:

A retrospective, cohort study of 4837 nationally representative American participants aged 65 years or older with a median follow-up duration of 77 months.

Measurements:

all-cause and cardiovascular mortality.

Results

A total of 1556 participants died during the median 77 months follow-up, and 517 died from cardiovascular disease. Compared with participants without nonfood pro-, pre-, and synbiotics use, nonfood pro-, pre-, and synbiotics use reduces nearly 41% risk of all-cause mortality (hazard ratio 0.59, 95%CI 0.43 to 0.79) and 52% risk of cardiovascular mortality (HR 0.48, 95%CI 0.30 to 0.76). Such an effect persists in most subgroup analysis and complete-case analysis.

Conclusion and relevance:

In this study, we found a protective effect of NPPS for all-cause and cardiovascular mortality in Americans aged 65 years or older. Nonfood pro-, pre-, and synbiotics can be a novel, inexpensive, low-risk treatment addition for all-cause and cardiovascular mortality for older individuals.

all-cause mortality

cardiovascular mortality

probiotic

prebiotic

synbiotic

From 1999 to 2019, the prevalence of cardiovascular disease (CVD) steadily increased from 271 million to 523 million, and the cases of CVD-specific death increased from 12.1 million to 18.6 million, even though substantial efforts had been made to prevent and treat CVD and CVD-specific death. (1, 2)

Comprising viruses, fungi, bacteria, archaea, and protozoa, the intestinal microbiota interacts with the host immune system at the beginning of birth, playing a vital role in the lifelong health of hosts.(3, 4) The intestinal microbiota undergoes structural and functional changes during aging, contributing to systemic inflammation and inflammatory pathologies. (5) Therefore, the imbalanced intestinal microbiota is increasingly recognized as contributing to various diseases, such as CVD. (6)

Gut microbiomes are a forgeable microbial community that various factors (such as diet, probiotics, prebiotics, and synbiotics) can alter. (7) Probiotics refer to live microorganisms that confer health benefits on the host when consumed in sufficient amounts. (8) Prebiotics are edible substrates that cannot be digested by humans but can selectively stimulate the growth of beneficial live microorganisms in the gut.(9) Synbiotics are a mixture of live microorganisms (for example, probiotics) and substrates (for example, prebiotics) that are selectively utilized by host microorganisms and confer a health benefit on the host. (10) Numerous human and animal studies revealed that pro-, pre-, and synbiotics improve cardiovascular risk factors such as systemic inflammation, body mass index (BMI), blood pressure, total cholesterol, low-density lipoprotein, heart lipid content, and insulin resistance, favorably modifying both functional and biochemical markers of vascular dysfunction, having a direct cardiac protection effect. (11–18) Therefore, pro-, pre-, and synbiotics may be a potential cost-efficient therapeutic approach to all-cause and cardiovascular mortality. In a nationwide population-based study, Lin found that all-cause mortality, but not cardiovascular mortality and cancer mortality, is inversely associated with yogurt (a natural probiotic source) consumption. (19) However, the association of nonfood pro-, pre-, and synbiotics (NPPS) with all-cause and cardiovascular mortality has not been studied. Consequently, the study aims to elucidate the relation of NPPS with unspecific and CVD-specific death for the older people in a nationwide population-based older American cohort.

Population

The National Health and Nutrition Examination Survey (NHANES) is designed to assess Americans’ health and nutritional status. The NHANES began in the early 1960s, and in 1999, the survey became a continuous program. A nationally representative sample of 5000 people is surveyed annually, and two-year surveys constitute each cycle. The National Center for Health Statistics (NCHS) Ethics Review Board approved the program, informed consent was obtained from all participants, and survey data are publicly available on the internet.

A total of 48484 participants in NHANES 2007–2016 were recruited initially. Among them, 7013 subjects aged 65 years or older were included in our study. Then 2168 and 8 participants were excluded for unclear NPPS usage and follow-up results, respectively. Finally, a total of 4837 subjects were used for data analysis (Fig. 1).

Nonfood probiotics, prebiotics, and synbiotics

Currently, probiotics are not regulated by The Food and Drug Administration (FDA), so they are available as dietary supplements only, while the FDA regulates part of prebiotics as medications. Therefore, according to the search terms in O'Connor’s study, (20) a keyword phrase mining process was conducted on all dietary supplement names, dietary supplement ingredients, medication names, and medication ingredients from the database to identify NPPS use. The NPPS was a dichotomized variable in which participants had one or more pro-, pre-, and synbiotics assigned “yes”.

Covariables

Age, gender, ethnicity, ratio of family income to poverty, and educational level information were acquired from the demographics file. Ethnicity was classified as Mexican American, Non-Hispanic Black, Non-Hispanic White, and other. The ratio of family income to poverty is an index of household financial status. Participants with a ratio of family income to poverty ≤ 1.3 was defined as low income, 1.3 ~ 3.5 was defined as median income, and >3.5 was defined as high income. (21) Education levels were categorized as less than high school and equal to or above high school.

The dietary inflammation index (DII) is an assessment tool developed to estimate the inflammatory potential of an individual’s diet. (22) In a word, a dietary parameter with proof of anti-inflammation effect would obtain a score of “-1”. In contrast, a food parameter would be scored “+1” if it was reported to increase inflammatory biomarkers level and scored”0” for no effect on inflammation biomarkers. Less than 30 food parameters can keep its predictive ability. (23) Twenty-eight food parameters from NHANES 24-h dietary recall interviews were used in our study to calculate the DII, including carbohydrates, protein, total fat, alcohol, fiber, cholesterol, saturated fat, monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs), niacin, vitamin A, thiamin, riboflavin, vitamin B6, vitamin B12, vitamin C, vitamin D, vitamin E, Fe, Mg, Zinc, Selenium, folic acid, β -carotene, caffeine, energy, n-3 fatty acids, and n-6 fatty acids. (24) The healthy eating index (HEI) was devised to measure the quality of American diets, and a higher HEI reflects a better diet quality. In our study, HEI 2015 edition was calculated based on the first-day total nutrient intakes obtained from the NHANES 24-h recall interview, Food and Nutrient Database for Dietary Studies (FNDDS), and Food Pattern Equivalence Database (FPED). (25) Subjects who smoked less than 100 cigarettes in life were classified as non-smokers, otherwise the smoker. (26)

Hypertension can be diagnosed if participants had been informed of hypertension previously, measured at least three times in four blood pressure measurements ≥ 140/90 mmHg, or were on anti-hypertensive agents. Diabetes was diagnosed based on the following criteria: ever been diagnosed diabetes, glycohemoglobin >6.5%, fasting glucose ≥ 7.0 mmol/L, random blood glucose ≥ 11.1mmol/L, tow-hour OGTT blood glucose ≥ 11,1mmol/L, or using diabetes medications or insulin currently. Hyperlipidemia was defined as having total triglyceride ≥ 150mg/dL, total cholesterol ≥ 200mg/dL, low-density lipoprotein ≥ 130mg/dL, high-density lipoprotein (HDL)< 40mg/dL for males, HDL<50mg/dL for females, or using lipid-lowering medications. Body mass index (BMI, kg/m2) is a continuous variable. Chronic kidney disease (CKD) was diagnosed for participants with Chronic Kidney Disease Epidemiology Collaboration(CKD-EPI) equation calculated estimated glomerular filtration rate(eGFR)<60ml/min/1.73m2, or previously diagnosed weak/failing kidneys. (27) Cardiovascular disease (CVD) was defined as coronary heart disease (CHD), congestive heart failure (HF), heart attack, stroke, or angina. The responses to the Medical Conditions questionnaires defined CHD, HF, heart attack, stroke, angina, and cancer. Trained interviewers collected medication information in household interviews. Having angiotensin-converting enzyme inhibitors (ACEI), angiotensin-II receptor blockers (ARB), or β blockers at baseline was defined as taking medication.

Endpoints and follow-up period

According to the National Death Index (NDI), we defined all-cause and cardiovascular mortality endpoints. The follow-up period was from the household interview to either death endpoints or the end of follow-up (December 31, 2019).

Statistics

All analyses were performed in R 4.2.1. Missing values (Supplementary Fig. S1) were mainly in DII (n = 542, 11.21%), HEI (n = 542, 11.21%), and the ratio of family income to poverty (n = 535, 11.06%). To retain the samples as many as possible, we adopted multiple imputations by “mice” R package to impute the missing values. All cases of all variables were included, and the repetition counts were 20.

According to the rule of “the least common denominator”, appropriate interviewer weights from the home interview (WTINT2YR) were used to obtain US nationally representative estimates. (20, 21) Continuous variables were presented as weighted medians with 95% confidence intervals (CI), and categorical variables were weighted proportions. Comparisons for baseline characteristics were made based on the usage of NPPS. Weighted Wilcoxon rank-sum test and Rao& Scott’s second-order correction test were used to analyzing group differences for continuous and categorical data, respectively. Two side P value<0.05 was considered statistically significant.

Weighted Cox proportional hazards regression models estimated the association between NPPS and all-cause and cardiovascular mortality. Model 1 was unadjusted, and the covariables in 3 additional models were as follows: age, gender, ethnicity, the ratio of family income to poverty, and education level (Model 2); Model 2 plus DII, HEI, and smoking (Model 3); Model 3 plus hypertension, diabetes, hyperlipidemia, CVD, cancer, CKD, BMI, and medication (Model 4). Then, subgroup analyses were made according to gender, the ratio of family income to poverty, education levels, DII, HEI, smoking, hypertension, diabetes, hyperlipidemia, BMI, CVD, cancer, CKD, and medication. Among them, DII and HEI were dichotomized based on weighted mean values (1.45, 95%CI 1.36 to 1.54 and 55.66, 95%CI 55.01 to 56.31, respectively) while BMI was classified as ≥ 25kg/m² and<25kg/m². The covariables in subgroup analyses were Model 4 minus the corresponding subgroup variables. Finally, the complete-case analysis was used to avoid imputation bias for missing data (n = 3619).

Baseline characteristics

The baseline characteristics are presented in Table 1. In the 4837 participants aged 65 years and older, the mean age was 73.23years (95%CI, 72.98 to 73.48 years), 58.77% were women, and 82.15% were Non-Hispanic White. Compared with participants without NPPS use, participants with NPPS use are much younger (p = 0.001), more intend to be non-Hispanic White (p = 0.003), higher educated (p<0.001), have a higher income (p<0.001), lower DII score (p = 0.008), higher HEI score (p<0.001), and taking medications (p = 0.003). However, there is no significant difference in gender (p = 0.400), smoking (p = 0.800), and chronic diseases.

Table 1

Baseline characteristics.
		Nonfood Pro-, Pre-, and Synbiotic Use
Characteristics	Overall^*	No^*	Yes^*	P-Value^†
Age (year)	73.23 (72.98,73.48)	73.34 (73.78, 73.61)	72.04 (71.34,72.73)	0.001
Gender				0.400
Female	58.77%	58.52%	61.27%
Male	41.23%	41.48%	38.73%
Ethics				0.003
Mexican American	2.89%	3.02%	1.66%
Non-Hispanic Black	6.79%	7.11%	3.63%
Non-Hispanic White	82.15%	81.53%	88.34%
Other	8.17%	8.35%	6.36%
Income levels				<0.001
Low	16.95%	17.74%	9.05%
Median	43.82%	44.13%	40.73%
High	39.23%	38.14%	50.22%
Educational levels				<0.001
Lower than high school	18.68%	19.76%	7.87%
Higher or equal to high school	81.32%	80.24%	92.13%
Dietary Inflammation Index	1.45 (1.36, 1.54)	1.49 (1.41, 1.57)	1.03 (0.72, 1.35)	0.008
Smoking				0.800
Non-smoker	50.62%	50.73%	49.58%
Smoker	49.38%	49.27%	50.42%
Health Eating Index	55.66 (55.01, 56.31)	55.37 (54.72, 56.02)	58.63 (56.96, 60.30)	<0.001
Hypertension				0.300
No	23.88%	23.59%	26.83%
Yes	76.12%	76.41%	73.17%
Diabetes				0.068
No	72.15%	71.65%	77.20%
Yes	27.85%	28.35%	22.80%
Hyperlipidemia				0.300
No	16.13%	15.91%	18.34%
Yes	83.87%	84.09%	81.66%
Body Mass Index (kg/m²)	28.59 (28.31, 28.87)	28.60 (28.32, 28.88)	28.52 (27.64, 29.41)	0.800
Cardiovascular Disease				0.200
No	73.58%	73.16%	77.83%
Yes	26.42%	26.84%	22.17%
Chronic Kidney Disease				0.110
No	69.46%	68.94%	74.71%
Yes	30.54%	31.06%	25.29%
Cancer				0.200
No	70.08%	69.74%	73.44%
Yes	29.92%	30.26%	26.56%
Medication				0.003
No	27.17%	26.33%	35.67%
Yes	72.83%	73.67%	64.33%
^*Mean (95%CI), %; ^†Wilcoxon rank-sum test for complex survey samples; chi-squared test with Rao & Scott's second-order correction; Medication, having angiotensin converting enzyme inhibitors (ACEI), angiotensin-II receptor blocker (ARB), or β blocker at baseline; Continuous variables present as weighted medians with 95% confidence intervals (CI), categorical variables present as weighted proportions.

Association between NPPS and death endpoints

During the median follow-up duration of 77 months, 1556 participants died, including 517 deaths from cardiovascular diseases. The Kaplan–Meier curves (Fig. 2) showed a significant difference in all-cause and cardiovascular mortality between the NPPS and non-NPPS groups (HR with all-cause mortality 0.47, 95%CI 0.35 to 0.62 ; HR with cardiovascular mortality 0.36, 95%CI 0.22 to 0.57). Supplementary Fig. S2 shows the effect of NPPS on all-cause and cardiovascular mortality in different models. In fully adjusted model, NPPS reduced 41% risk of all-cause mortality (HR 0.59, 95%CI 0.43 to 0.79) and 52% risk of cardiovascular mortality (HR 0.48, 95%CI 0.30 to 0.76).

The results of gender, income level, education level, DII score, HEI score, smoking, hypertension, diabetes, hyperlipidemia, BMI, CVD, cancer, CKD, and medication use based subgroup analysis were presented in Fig. 3–4. The protective effects of NPPS on unspecific death persists in women, smokers, hypertensive, and hyperlipidemic participants, and the HRs are 0.54 (95%CI 0.36 to 0.80), 0.39 (95%CI 0.24 to 0.64), 0.56 (95%CI 0.43 to 0.75), and 0.54 (95%CI 0.38 to 0.78), respectively. As to the outcome of CVD-specific death, the HRs for subjects with higher income, higher DII, smoking, hypertension, hyperlipidemia, and CKD are 0.28 (95%CI 0.10 to 0.84), 0.48 (95%CI 0.28 to 0.84), 0.39 (95%CI 0.17 to 0.88), 0.44 (95%CI 0.28 to 0.71), 0.45 (95%CI 0.25 to 0.80), and 0.45 (95%CI 0.24 to 0.83), respectively. The benefit of NPPS on cardiovascular mortality appeared to be more pronounced among smokers. (P = 0.040 for the interaction).

The complete-case analysis shows a similar result (Supplementary Fig. S3 and Table S1).

In this study, we found a protective effect of NPPS for all-cause and cardiovascular mortality in Americans aged 65 years or older after adjusting for demographic characteristics (age, gender, ethnicity, family income levels, and education levels), lifestyle (DII, HEI, and smoking), comorbidities (hypertension, diabetes, hyperlipidemia, BMI, CVD, CKD, and cancer), and prescription medication information. To our knowledge, this is the first study to describe the association of NPPS with long-term all-cause and cardiovascular mortality in the resident civilian U.S. population aged 65 years or older.

Numerous studies suggest that pro-, pre-, and synbiotics reduce the risk of many cardiovascular risk factors. A mate analysis including twenty-six RCTs shows that probiotics significantly reduce BMI, total cholesterol, low-density lipoprotein, and inflammatory markers. (28) In another parallel, randomized, double-blind, placebo-controlled clinical trial, Soleimani found probiotic supplements can significantly improve insulin resistance and β-cell function for patients with type 2 diabetes mellitus. (12) Recently, improved blood pressure, reduced heart lipid content, and regulated expression of natriuretic peptide and lipid metabolism-related genes by prebiotics were observed in rat models. (13) A randomized, triple-blinded research found that daily synbiotics consumption for eight weeks improved oxidative, metabolic, blood pressure, and inflammation in females with the polycystic ovarian syndrome. (15) In another randomized, double-blind, placebo-controlled, parallel clinical study, synbiotic supplements reduced the prevalence of metabolic syndrome and insulin resistance. (16) In our study, NPPS reduces the risk of cardiovascular mortality for subjects with higher DII, smoking history, hypertension, hyperlipidemia, and CKD but participants without those risk factors. It is speculated that NPPS reduces all-cause and cardiovascular mortality risk partially by attenuating the worsening effects of the abovementioned risk factors. Similar speculation has already been raised.(29)

We additionally found that the protective effect of NPPS on CVD-specific death may be more pronounced in smokers. Long-term, low-grade inflammation plays a pivotal role in the development of cardiovascular diseases. (30) Balanced gut microbiota maintain the epithelium barrier’s integrity by regulating the formation of short-chain fatty acids (SCFA), leading to a reduced leakage on bacterial lipopolysaccharide (LPS) into bloodstream, and finally inhabit long-term, low-grade system inflammation. (31–33) Smoking is related to a wide range alteration of inflammation marker and unbalanced gut microbiota. (34, 35) Therefore, we speculate that the more significant protective effect may contribute to the modulation of NPPS on unbalanced intestinal flora and more severe inflammation burden of smokers.

Strength and limitation

Our study has several strengths. First, chronic inflammation, regulated mainly by diet, plays an essential role in the development of CVD. (36) DII is a dietary inflammatory potential assessment tool, and a higher DII score relates to a higher cardiovascular mortality risk. (37) Diet quality is also crucial for all-cause and cardiovascular mortality. (38) Therefore, DII and HEI are included in our study as covariables, which is rarely considered in other studies. Second, the study is based on the NHANES provided nationally representative cohort. The interviews, healthy measurements, and laboratory data are collected by professional staff and recorded using an advanced computer system in a high-quality and standardized procedure with rigorous and extensive quality control procedures.

Several unignorable limitations should also be considered. First, it has been proposed that probiotic supplements may need to be taken in specific amounts for a particular time to integrate and interact with the intestinal microbiota temporarily or permanently. (28, 39)The analyzed NPPS in our study was the NPPS used during the previous 30 days from dietary supplements and prescription medications. Therefore, the taken amounts and time were not considered, and our study could not explore the dose-response relationship of NPPS with death endpoints. Second, the effects of probiotic supplements on death endpoints may be strain-dependent. (40) However, our study did not differentiate the strain of probiotics and synbiotics. Finally, due to the severe missing data about inflammatory markers, we could not explore the role that inflammation plays in the protective effect of NPPS on unspecific and CVD-specific death.

We found that NPPS reduces the all-cause and cardiovascular mortality risk of Americans aged 65 years or older. Thus, NPPS may be a novel, inexpensive, low-risk treatment addition for all-cause and cardiovascular mortality.

Ethical Statement

The National Center for Health Statistics (NCHS) Ethics Review Board approved NHANES program. Written informed consent was obtained for participation in this study.

Conflict of interest disclosure form

The authors declare that they have no known competing fiscal interests or personal relationships, perceived to have influenced the work reported in this article.

Funding Sources

This study is funded by the Zhejiang Traditional Chinese Medicine Research Fund Project (2022ZB405) for covering publication fees.

Acknowledgement

The authors thank the participants and staff of the National Health and Nutrition Examination Survey 2007-2016 for their valuable contributions.

Author Contributions

R.S. contributed to the study design, data analysis, and manuscript drafting. S.C. (co-first author) contributed to study design and data analysis. W.L. contributed to manuscript drafting. J.S. contributed to the interpretation of the data. T.W. and L.L. contributed to study design and the critical revision. All authors have read and approved the final manuscript.

Data Availability Statement

Publicly available datasets were used in this study. These can be found in NHANES at https://www.cdc.gov/nchs/nhanes/index.htm.

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Nonfood Probiotic, Prebiotic, and Synbiotic Use Reduces All-Cause And Cardiovascular Mortality Risk In Older Adults: A Population-Based Cohort Study

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Nonfood probiotics, prebiotics, and synbiotics

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Association between NPPS and death endpoints

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