Introduction

The potential positive contributions to human health from ingested microorganisms are being increasingly acknowledged [1]. The “old friends’ hypothesis” states that exposure to commensal or non-harmful microbes in food serves as a pivotal and advantageous means of providing microbial stimuli for the immune system [2]. Notably, such immune regulatory activities may have an impact on current chronic immune, metabolic, and other “lifestyle” diseases associated with Western diets [3].

Previous studies have documented associations of live microorganisms and fermented foods with health outcomes [4, 5]. However, live microorganisms have been discovered to exist not only within fermented food, but also in a wide range of other foods, including raw, unpeeled fruits and vegetables [6, 7]. Recently, Sander et al. [8] developed a classification system that assigns each food recorded by National Health and Nutrition Examination Survey (NHANES) to one of three microbial categories (low, medium, and high), and estimated the number of live microbes in the diet of US population, finding that adults in US steadily increased their consumption of foods with live microbes between the earliest (2001–2002) and latest (2017–2018) survey cycles. Interestingly, based on this microbial classification method, previous studies have found that increased consumption of foods with medium to high amounts of live microbes is associated with a lower blood pressure, BMI, waist circumference, plasma glucose, C-reactive protein, insulin, triglyceride levels, and CVD risk [9, 10]. However, these studied failed to separate the contribution of foods with live microbes from the effects of those foods as a whole [11]. Moreover, the association between consumption of foods with live microbes and health benefits was based on cross-sectional study, findings based on prospective cohort study remain limited. From a public health perspective, investigation of the contributions of foods with live microbes to human survival promotes awareness to consumption of foods containing high levels of live microorganisms and provides new insights for healthy diet recommendations, thereby reducing the burden of mortality.

In present study, we investigated the association of consumption of foods with medium to high amounts of live microbes with all-cause, cancer-specific, and cardiovascular disease (CVD)-specific mortality among US adults. Moreover, we estimated population-attributable fractions (PAFs) of consumption of foods with medium to high amounts of live microbes in relation to mortality.

Methods

Study population

NHANES is a national survey program designed to assess health and nutritional status of people in the United States, obtained using a complex, stratified, clustered multi-staged probability sampling design [12]. The survey was approved by the Centers for Disease Control and Prevention Research Ethics Review Board. All participants have signed informed consent. This study was exempt from review because data used in this study was de-identified.

A total of 48,751 adults aged ≥ 20 years with a day 1 dietary recall participated in the 1999 to 2018 NHANES. After excluding participants with missing data on death or follow-up years (n = 83) or potential covariates (n = 12,083), and those who were pregnant or breastfeeding (n = 1286), a total of 35,299 adults aged ≥ 20 years were included in this study, of which 2861, 3748, 3448, 3365, 3951, 4142, 3618, 3889, 3525, and 2752 were in the survey cycles of 1999–2000, 2001–2002, 2003–2004, 2005–2006, 2007–2008, 2009–2010, 2011–2012, 2013–2014, 2015–2016, and 2017–2018, respectively (Fig. 1).

Fig. 1
figure 1

Flow chart of inclusion/exclusion of participants

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Determinations of the intakes of foods with microbes

According to Sanders’ researches [8, 13], experts in the field relied on primary literature, manuscript reviews, professional knowledge, and microbial viability in relation to food processing to estimate the live microbial content for 9388 individual food codes within 48 NHANES subgroups, and then designated foods into three categories (low, medium [Med], and high [Hi]) based on the estimated live microbial content. These levels of low, Med, and hi were chosen to reflect the approximate numbers of viable microbes expected to be present in pasteurized foods (< 104 CFU/g), fresh fruits and vegetables eaten unpeeled (104–107 CFU/g), and unpasteurized fermented foods (> 107 CFU/g), respectively [14]. The differences were resolve through discussion and external consulting with Fred Breidt, USDA Agricultural research service microbiologist.

Considering that analysis of both Med and Hi foods included in the same model as separate terms showed that their coefficients were similar, and Hi category comprised primarily fermented dairy foods, we developed a fourth category (MedHi) as in previous study [8, 13], referring to foods that were categorized as either having medium or high microbial content. We then calculated the grams of four categories of food consumed for each participant, and used consumption of MedHi foods as a variable of interest. Consistent with previous study [13], participants were further classified into three groups (G1: Participants without MedHi foods intakes; G2: those with MedHi foods intakes greater than zero but less than the median intake for participants; and G3: those with MedHi foods intakes greater than the median intake for participants). Given the low consumption (2%), probiotic dietary supplements were not included in the current analyses.

Determination of mortality

The National Center for Health Statistics provides mortality data related to the National Death Index as of December 31, 2019. The International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) is used to document the underlying causes of death. CVD-specific mortality was defined as ICD-10 codes I00-I09, I11, I13, I20-I51, or I60-I69; cancer-specific mortality was defined as ICD-10 codes C00-C97. The duration of follow-up was defined as the interval in months from the date of interview to the date of death or to December 31, 2019.

Assessment of covariates

Sociodemographic characteristics included age, sex (male or female), race and ethnicity (non-Hispanic Black, Hispanic [Mexican Americans/other Hispanic], non-Hispanic White, or others [American Indian/Native Alaskan/Pacific Islander, Asian, multiracial]), educational level (less than high school graduate, high school graduate or GED, and some college or above), and household poverty-to-income ratio (< 1.30, 1.30–3.49, or ≥ 3.50) [15]. The body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Alcohol use was classified as “never”, “former” (a history of daily binge drinking), “current heavy” (≥ 3 drinks per day for females, ≥ 4 drinks per day for males, or binge drinking [≥ 4 drinks on same occasion for females, ≥ 5 drinks on same occasion for males] on 5 or more days per month), “current moderate” (≥ 2 drinks per day for females, ≥ 3 drinks per day for males, or binge drinking ≥ 2 days per month), or “current mild” (current drinking but not meeting the standard of moderate and heavy drinking) [16]. Smoking status was classified as “never” (smoked less than 100 cigarettes in life), “former” (smoked more than 100 cigarettes in life, but they were not currently smoking cigarettes.), or “current smokers” (smoked more than 100 cigarettes in life and smoke some days or every day) [17]. Healthy Eating Index-2015 (HEI-2015), consisting of thirteen dietary components scores, was calculated for each participant on the basis of data of 24 h dietary recalls, and a higher HEI-2015 score indicates a better dietary quality and a closer compliance with the intake level recommended by the 2015–2020 Dietary Guidelines for Americans [18]. Food calorie intake and total dietary fiber intake were considered continuous variables. Physical activity (PA) was assessed on the basis of data of self-reported Global Physical activity Questionnaire [19], which consists of work-related activity, transportation-related activity, and leisure time-related activity. Total PA was estimated as minutes of moderate-intensity activity plus twice the number of minutes of vigorous activity in work-related activity and leisure time-related activity, then plus the number of minutes of transportation-related activity. According to the 2018 Physical Activity Guidelines for Americans, participants with total PA less than 150 min/wk and those with PA of 150 min/wk or more were classified as inactive and active, respectively [20].

Hypertension was defined as self-reported physician’s diagnosis, use of hypertensive drugs, or blood pressure of ≥ 140/90 mmHg. Diabetes mellitus (DM) was defined as self-reported physician’s diagnosis, a glycosylated hemoglobin A1c level of ≥ 6.5%, a fasting plasma glucose level of ≥ 7.0 mmol/l, random blood glucose level of ≥ 11.1 mmol/l, two-hour glucose tolerance test blood glucose level of ≥ 11.1 mmol/l, or use of diabetes medication or insulin [21]. Hyperlipidemia was defined as total triglyceride ≥ 200 mg/dL, total cholesterol (TC) ≥ 240 mg/dL, high density lipoprotein cholesterol (HDL-C) < 40 mg/dL, low density lipoprotein cholesterol ≥ 160 mg/dL, or TC /HDL-C ratio ≥ 5 [22]. CVD was defined as a composite of self-reported doctor diagnoses of coronary heart disease, myocardial infarction, angina pectoris, congestive heart failure, or stroke [23].

Statistical analysis

All analyses in this study were conducted in accordance with NHANES analysis guidelines and accounted for unequal selection probabilities, oversampling of certain subgroups, and nonresponse adjustment to ensure nationally representative estimates.

Continuous variables were expressed as weighted mean with standard error (SE), and categorical variables as weighted frequency distribution. Baseline characteristics were compared using the survey-weighted linear regression for continuous variables and the survey-weighted Chi-square test for categorical variables.

Differences of cumulative mortality between three consumption categories of MedHi foods (G1, G2, G3) were shown using survey-weighted Kaplan–Meier survival curves and were compared using the log-rank test. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for examining the associations of consumption of MedHi foods (low level as the reference) with all-cause, cancer-specific, and CVD-specific mortality. Model 1 was adjusted for age, sex, race and ethnicity; model 2 was additionally adjusted for educational level, family poverty income ratio, BMI, smoking status, alcohol use, total PA, CVD, hypertension, DM, and hyperlipidemia. To separate the contribution of MedHi foods from the effects of high-quality diet, model 3 was additionally adjusted for HEI-2015 score, food calorie intake, and total dietary fiber intake. We also applied the multivariable Cox regression based on restricted cubic splines to explore dose-response association. The adjusted PAFs of MedHi foods consumers (G2 + G3) vs. nonconsumers (G1) were estimated for the proportion of mortality that could be avoided if nonconsumers ingest MedHi foods. Furthermore, the adjusted PAFs of high (G3) vs. intermediate or low consumption of MedHi foods (G1 + G2) were also estimated, indicating that the proportion of mortality that could be avoided if each participant achieves a high consumption of MedHi foods (G3).

We conducted subgroup analyses by age (20–29 years, 40–59 years, and > = 60 years), sex, BMI (< 25, 25-29.9, and ≥ 30), race/ethnicity, educational level, ratio of family income to poverty, and PA level. We further examined the potential effect of interaction by adding an interaction term of each stratifying variable and consumption of MedHi foods in each model and assessing it via a likelihood ratio test. Sensitivity analysis was conducted by excluding participants with a history of CVD or death within the first 2 years of follow-up to lessen the probability of reverse causation.

A two-tailed P value < 0.05 was considered statistically significant. Statistical analyses were performed using R software version 4.2.1 and STATA version 16.0 (Stata Corporation, College Station, TX, USA).

Results

Characteristics of participants

The characteristics of participants across the three levels of consumption of MedHi foods (G1, G2, and G3) are shown in Table 1. The relative frequency of adults in G1 (nonconsumers), G2 (below median of consumers), and G3 (above median of consumers) was 35.22%, 32.43%, and 32.34%, respectively. Adults in G3 were prone to female, elderly people, non-Hispanic White, having a high education level and a high ratio of family income to poverty, mild drinking, having a low BMI, having an active PA, having a high HEI-2015 score, having high energy and dietary fiber intakes, and being without a history of CVD (All P < 0.001).

Table 1 Characteristics of US adults by three levels of MedHi foods consumption
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Association of microbes with mortality

During a median follow-up of 9.67 years (interquartile range: 5.42–14.25 years), participants who consumed more MedHi foods had a significantly lower cumulative incidence rate of all-cause and CVD-specific mortality (P < 0.001 for all log-rank tests, Fig. 2).

Fig. 2
figure 2

Survey-weighted Kaplan–Meier survival curves shows differences of cumulative all-cause, CVD-specific, and cancer-specific mortality between three levels of MedHi foods consumption (G1, G2, G3)

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Multivariable Cox regression models showed that compared with adults in G1, those in G3 had 16% (HR, 0.84; 95% CI, 0.77–0.90) (P for trend = 0.03) reduced risk of all-cause mortality, and 23% (HR, 0.77; 95% CI, 0.67–0.89) (P for trend = 0.06) reduced risk of CVD-specific mortality after adjustment for all potential covariates (Table 2). However, no significant association between consumption of MedHi foods and cancer-specific mortality was observed. The adjusted PAFs of MedHi foods consumers (G2 + G3) vs. nonconsumers (G1) with all-cause and CVD-specific mortality were 3.6% and 3.6%, respectively. The adjusted PAFs of high (G3) vs. intermediate or low consumption of MedHi foods (G1 + G2) with all-cause and CVD-specific mortality were 3.4% and 4.3%, respectively (Table 2).

Table 2 Adjusted hazard ratios of microbes with risk of all-cause mortality and CVD mortality, NHANES 2005–2018
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There were approximately linear dose–response associations of consumption of MedHi foods with all-cause (P for non-linear association = 0.59) and CVD-specific (P for non-linear association = 0.75) mortality, and the risk of all-cause and CVD-specific mortality decreased linearly as consumption of MedHi foods (per 100 g) increased (Fig. 3).

Fig. 3
figure 3

Dose–response relationships of consumption of MedHi foods (per 100 g) with all-cause, and CVD-specific mortality. The reference is set at 5 points for consumption of MedHi foods. Models were adjusted by age, sex, race and race/ethnicity, educational level, family poverty income ratio, BMI, smoking status, alcohol use, total PA, CVD, hypertension, DM, hyperlipidemia, HEI-2015 score, food calorie intake and total dietary fiber intake

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Subgroup analysis

Subgroup analyses showed that the patterns of high consumption of MedHi foods in relation to reduced risk of all-cause and CVD-specific mortality remained consistent across subgroups of age, sex, BMI, race/ethnicity, educational level, family income-to-poverty ratio, and PA level (Fig. 4) (Supplementary Table 1). Interestingly, we observed a significant interaction between age and consumption of MedHi foods both on all-cause and CVD-specific mortality.

Fig. 4
figure 4

Association between consumption of foods with medium to high amounts of live microbes and all-cause and CVD-specific mortality in subgroups. Models were adjusted for age, sex, race and race/ethnicity, educational level, family poverty income ratio, BMI, smoking status, alcohol use, total PA, CVD, hypertension, DM, hyperlipidemia, HEI-2015 score, food calorie intake and total dietary fiber intake

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Sensitivity analysis

Similar patterns of high consumption of MedHi foods in relation to reduced risk of all-cause and CVD-specific mortality were observed after excluding adults with CVD history or death occurred during the first 2-year follow-up (Supplementary Tables 2 and 3).

Discussion

To our knowledge, this study is the first to directly provide evidence of an association between dietary intake of live microbes and risk of all-cause and CVD-specific mortality. Based on a large nationally representative sample of US adults, we found that adults with a high level of MedHi food intake had a reduced risk of all-cause and CVD-specific mortality. These association remained consistent in sensitivity analyses and in most subgroups. There was an approximately linear dose–response association of increased MedHi food intake with reduced risk of all-cause and CVD-specific mortality. Interestingly, we observed that the increase at any level of the MedHi food intake has a benefit based on the spline plots, and adults with the lower MedHi food intake seem to benefit more from a small change. In addition, we documented that 3.4–3.6% of all-cause mortality and 3.6–4.3% of CVD-specific mortality could be avoided if all of adults were able to obtain a high level of MedHi food intake.

Several concepts formed the basis for the hypothesis that the ingestion of live microbes could have positive effects on human health [24]. First, improved hygiene and sanitation, coupled with modern food production and processing, have led to a decrease in the amounts of live microbes ingested by modern humans compared to our ancestors [25]. Although improved food and environmental hygiene can bring about significant public health benefits, reductions in microbial exposures could also lead to unexpected negative health outcomes. Previous studies have documented the contribution of diet to the rise over the past century of many modern chronic immune, metabolic, and other “lifestyle” diseases such as asthma, eczema, lupus, type 1 diabetes, and CVD [10, 26, 27]. Second, studies have shown that fruits, vegetables and fermented dairy products are the top three food groups that provide live microorganisms, and that in addition to providing live microbes, these foods also provide a significant amount of key nutrients that are lacking in the diets of children and adults, including calcium, fiber, and potassium [8]. Third, immune regulatory activities of live microorganisms can potentially improve health by reducing excessive inflammation caused by Western diets lacking in live microbes [28]. For example, eating fermented foods can reduce levels of inflammatory markers [13]. Fourth, it has been demonstrated that the ingestion of live microbes in the form of probiotics can lead to enhanced health outcomes such as prevention of necrotizing enterocolitis, functional bowel disorders, and antibiotic-associated diarrhea, treatment of ulcerative colitis, and the reduction of both the incidence and duration of common upper respiratory and gastrointestinal infections [29].

Interestingly, a cross-sectional study demonstrated that dietary intakes of live microbes are associated with lower blood pressure, BMI, and a range of other indicators related to population health [9]. Although cause and effect relationships cannot be determined, these findings do provide additional evidence supporting a link between dietary intakes of live microbes and decreased mortality. Indeed, we observed that participants with high dietary intakes of live microbes were prone to having high HEI-2015 score and dietary fiber intakes, which suggested that MedHi foods are more likely to contain higher levels of dietary fiber and better meet human needs. To separate the contribution of MedHi foods from the effects of high-quality diet, we additionally adjusted HEI-2015 score, food calorie intake and total dietary fiber intake in model 3. Interestingly, there were attenuations of associations of MedHi foods with all-cause and CVD-specific mortality, while the associations remain significant, indicating that consumption of MedHi foods is independently associated with decreased mortality.

It is noteworthy that there existed interaction effects of age and consumption of MedHi foods on all-cause and CVD-specific mortality. With advancing age, an individual’s dietary habits will undergo changes due to decreased tooth and saliva function, modifications in their lifestyle, and reduced digestion and absorption capabilities [30]. Middle-aged and elderly individuals can benefit greatly from consumption of foods with medium to high amounts of live microbes, especially in light of the reduced variety in their diets and the rise in inflammatory cytokines [31].

We broke through the limitations of previous studies. First, this is the first large-scale, nationally representative cohort study to examine the association of consumption of foods with live microbes with mortality. Second, to separate the contribution of foods with live microbes from the effects of dietary patterns, we adjusted for various possible confounding dietary factors, including HEI-2015, food calorie intake, and total dietary fiber intake in models. We acknowledge the potential limitations of this study. First, there may be recall bias in self-reported dietary intake and PA. Second, additional confounding by measured or unmeasured covariates may affect the observed associations. Third, our analysis utilized a classification system that did not have precise measurements of microbial types as well as may not have captured more subtle differences. Further studies are needed to measure more accurately the species and content of consumed microorganisms and to get the risk model for estimation of all-type-death of CVD development based on analyzing the missing diversity of microbial food components.

Conclusion

Consumption of foods with higher microbial concentrations is associated with a reduced risk of all-cause and CVD-specific mortality in US adults. Middle-aged and elderly individuals can benefit greatly from consumption of foods with medium to high amounts of live microbes. Given the potential for small dietary adjustments to yield substantial health advantages, it is crucial to enhance public understanding regarding the consumption of foods with high microbial concentrations. This includes incorporating the intake of live microbes into dietary evaluations and establishing suggested values for live microbes within healthy dietary regimens, similar to the current recommended values for fiber.