Coffee and Longevity: Systematic Review with ☸️SAIMSARA.

saimsara.com

Review Stats

Generated: 2025-10-05 19:19:00 CEST
Plan: Premium (expanded craft tokens; source: Europe PMC)
Source: Europe PMC
Scope: All fields
Keyword Gate: Fuzzy (≥60% of required terms, minimum 2 terms matched in title/abstract)
Total Abstracts/Papers: 3692
Downloaded Abstracts/Papers: 3692
Included original Abstracts/Papers: 197
Total study participants (naïve ΣN): 985266

Outcome-Sentiment Meta-Analysis (OSMA): (LLM-only)
Frame: Effect-of Predictor → Outcome • Source: Europe PMC
Outcome: longevity Typical timepoints: 5-y, 55-y. Reported metrics: %, CI, p.
Common endpoints: Common endpoints: mortality, survival, healing.
Predictor: coffee — exposure/predictor. Doses/units seen: 130 mg, 1000 g. Routes seen: topical. Typical comparator: controls, the control, control, the ormocer-based nanohybrid….

1) Beneficial for patients — longevity with coffee — [3], [17], [19], [38], [39], [40], [41], [42], [49], [60], [62], [69], [70], [77], [84], [95], [114], [118], [123], [125], [149], [151], [167], [176], [180], [186], [188], [194] — ΣN=470588
2) Harmful for patients — longevity with coffee — [52], [164] — ΣN=44195
3) No clear effect — longevity with coffee — [1], [2], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [18], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [43], [44], [45], [46], [47], [48], [50], [51], [53], [54], [55], [56], [57], [58], [59], [61], [63], [64], [65], [66], [67], [68], [71], [72], [73], [74], [75], [76], [78], [79], [80], [81], [82], [83], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94], [96], [97], [98], [99], [100], [101], [102], [103], [104], [105], [106], [107], [108], [109], [110], [111], [112], [113], [115], [116], [117], [119], [120], [121], [122], [124], [126], [127], [128], [129], [130], [131], [132], [133], [134], [135], [136], [137], [138], [139], [140], [141], [142], [143], [144], [145], [146], [147], [148], [150], [152], [153], [154], [155], [156], [157], [158], [159], [160], [161], [162], [163], [165], [166], [168], [169], [170], [171], [172], [173], [174], [175], [177], [178], [179], [181], [182], [183], [184], [185], [187], [189], [190], [191], [192], [193], [195], [196], [197] — ΣN=470483

1) Introduction
Coffee, one of the most widely consumed beverages globally, is a complex mixture of bioactive compounds, including caffeine, polyphenols, and diterpenes, which have garnered significant scientific interest for their potential health benefits. As global populations age, understanding the factors that influence healthy aging and longevity has become a critical public health objective. Research into dietary patterns and specific food items, such as coffee, offers insights into lifestyle modifications that may extend healthspan and lifespan. This paper aims to systematically review the current scientific evidence on the relationship between coffee consumption and longevity, synthesizing findings from diverse study designs and populations to provide a comprehensive overview of its multifaceted impact.

2) Aim
The aim of this paper is to systematically review and synthesize the current evidence regarding the association between coffee consumption and longevity, leveraging the Autonomous Multilayer AI Research Agent (SAIMSARA) framework for keyword normalization, retrieval, structuring, and paper synthesis.

3) Methods
3.1 Eligibility criteria
Original studies were included in this review. Editorials, conference papers, and reviews were excluded. The primary focus was on studies directly investigating coffee consumption or its components in relation to longevity, aging biomarkers, or health outcomes relevant to lifespan.

3.2 Study selection
Studies were selected based on a strict keyword gate applied upstream by the SAIMSARA system, ensuring relevance to "Coffee and Longevity." This process filtered a broad range of scientific literature to identify pertinent articles.

3.3 Risk of bias
The included studies exhibit considerable heterogeneity in design, ranging from observational cohort studies and randomized controlled trials (RCTs) to numerous in vitro and animal experimental studies. Many studies were classified as "Mixed" design, often indicating a combination of laboratory-based experiments (e.g., dental material testing) or animal models. For many studies, specific details regarding study type directionality, statistics, and follow-up periods were not explicitly provided in the structured summary, limiting a comprehensive assessment of internal validity. A significant portion of the extracted literature focused on the effects of coffee on dental materials, which, while scientific, is not directly relevant to human biological longevity, introducing a thematic bias in the overall dataset. Cohort studies, while offering insights into human populations, are inherently susceptible to confounding factors.

3.4 Synthesis
Autonomous multilayer AI research agent: keyword normalization, retrieval & structuring, and paper synthesis (see SAIMSARA About section for details).

4) Results
4.1 Study characteristics
The included studies comprise a diverse array of designs, including cohort studies, randomized controlled trials, cross-sectional analyses, and numerous experimental or mixed-design investigations. Populations ranged from human adults (including centenarians, individuals with diabetes mellitus, and older women) to various model organisms such as Caenorhabditis elegans, Drosophila melanogaster, yeast, and insects, as well as in vitro dental materials. Sample sizes varied widely, from small experimental groups of 12 [39] to large cohorts of up to 449,563 participants [49]. Follow-up periods also showed significant variation, from short-term observations of hours or days in experimental settings [21, 23, 25] to long-term prospective cohorts spanning up to 26 years [48, 172].

4.2 Main numerical result aligned to the query
Coffee consumption is frequently associated with a reduced risk of all-cause and cardiovascular mortality, with reported Hazard Ratios (HR) and Relative Risks (RR) for all-cause mortality ranging from 0.21 [188] to 0.94 [176] in various populations and consumption levels. For instance, the highest coffee consumption was associated with lower risks of all-cause mortality (HR 0.82, 95%CI 0.73, 0.91) in individuals with diabetes mellitus [19]. Habitual coffee intake of up to 5 cups/day was associated with significant reductions in the risk of all-cause mortality (HR 0.86, CI [0.83-0.89]) and cardiovascular mortality (HR 0.82, CI [0.74-0.90]) [49]. However, some studies indicate an increased risk, with HRs up to 2.13 (95% CI, 1.26-3.59) for high consumption (>28 cups/week) in women younger than 55 years [164]. A U-shaped nonlinear association has also been observed with all-cause and cardiovascular disease mortality, suggesting both beneficial and detrimental effects depending on intake levels [46].

4.3 Topic synthesis

Cardiovascular and Metabolic Health Benefits: Higher coffee consumption is linked to lower risks of all-cause mortality (HR 0.82 [19], HR 0.86 [49]), cardiovascular disease (CVD) incidence (HR 0.85 [19]), coronary heart disease (CHD) mortality (HR 0.66 [19]), and improved left ventricular function (low-to-moderate intake) [93]. It is also associated with a lower risk of type 2 diabetes (T2D) (HR 0.46 [48]) and better glycemic control [105].
Anti-Aging Mechanisms and Biomarkers: Coffee intake is associated with reduced epigenetic aging [41], increased serum sirtuin-1 concentration [59], and an L-shaped association with serum α-Klotho levels, particularly in females and those under 60 years [1]. Coffee compounds like kahweol [40], caffeic acid, and dihydrocaffeic acid [84] have been shown to extend lifespan in C. elegans by up to 20.1% [118], and caffeine extends lifespan and improves healthspan in C. elegans [149].
Cognitive and Neuroprotective Effects: Coffee is highlighted for its ability to enhance cognitive function and combat oxidative stress [3, 79], serving as a protective factor against Parkinson's disease and Alzheimer's disease/dementia [166]. Phytochemicals in coffee can enhance neuroplasticity and resistance to neurodegeneration [180].
Physical Activity and Frailty Reduction: Caffeine consumption is associated with older adults being more active (16.5% more active, 42.8 additional minutes of high activity) [60], and higher caffeine intake at midlife is linked to a reduced likelihood of physical frailty in late life (OR 0.54 [39]).
Dental Material Degradation and Discoloration: Coffee consistently causes significant discoloration (ΔE values varying widely, often clinically unacceptable [5, 6, 7, 14, 21, 22, 25, 30, 31, 34, 64, 74, 80, 81, 85, 88, 89, 90, 96, 100, 101, 102, 103, 110, 120, 137, 142, 145, 155, 156, 168, 173, 178]) and chemical degradation [4] or decreased microhardness [12, 23, 26, 110] in various dental restorative materials and bleached teeth.
Gene-Environment Interactions: Genetic factors, such as the ADORA2A TT genotype, are positively associated with coffee intake and lower exercise-induced inflammatory responses [45]. Similarly, the mitochondrial DNA 5178 C/A polymorphism modifies coffee's effects on cardiovascular risk factors [134, 165], and FOXO1A-209 genotypes interact with tea drinking to influence mortality risk [169].
Coffee Agroecosystem Health: Studies also address the longevity of coffee plants and related ecosystems, including pest management (e.g., Araecerus fasciculatus survival [2], coffee berry borer management [87, 140], pest detection accuracy of 93.6625% [11]) and the impact of tree longevity on conservation value in shade coffee farms [61].

5) Discussion
5.1 Principal finding
The central finding indicates a complex, often U-shaped, association between coffee consumption and human longevity, with moderate intake generally linked to a reduced risk of all-cause and cardiovascular mortality, exemplified by Hazard Ratios for all-cause mortality as low as 0.21 [188] and 0.86 [49], but with high intake potentially increasing mortality risk in certain populations [164].

5.2 Clinical implications

Clinicians may consider recommending moderate coffee intake as part of a healthy lifestyle for cardiovascular disease risk reduction [49, 19] and improved metabolic health, particularly in individuals with diabetes [48, 105].
Patients should be advised about the potential for dental discoloration and degradation of restorative materials due to coffee consumption, suggesting strategies like regular polishing or choosing stain-resistant materials [4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 18, 21, 22, 24, 25, 26, 27, 28, 30, 31, 34, 64, 72, 74, 76, 80, 81, 85, 88, 89, 90, 96, 100, 101, 102, 103, 110, 112, 120, 137, 142, 145, 155, 156, 168, 173, 178].
For younger adults, particularly those consuming very high amounts of coffee, the potential for increased all-cause mortality risk should be considered, suggesting a need for personalized guidance on intake levels [164].
Coffee's association with enhanced physical activity in older adults [60] and reduced frailty [39] highlights its potential role in maintaining functional independence in aging populations.
The neuroprotective effects of coffee [166] suggest it could be a dietary component to support cognitive health, especially in populations at risk for neurodegenerative diseases.

5.3 Research implications / key gaps

Optimal Coffee Dosage for Longevity: Future research should precisely define the optimal intake levels (e.g., cups/day, mg caffeine) for maximal longevity benefits, especially considering the observed U-shaped associations and high-intake risks [46, 164].
Mechanistic Pathways of Coffee Compounds: More studies are needed to elucidate the specific molecular and cellular pathways (e.g., sirtuins, epigenetic modulation, proteostasis) by which coffee's diverse compounds influence human aging processes [40, 41, 59, 69, 84, 94, 114, 118, 123, 149, 150, 163].
Long-term Dental Material Longevity: A significant gap exists in understanding the long-term clinical impact of coffee-induced degradation and discoloration on dental restorations in diverse patient populations, necessitating large-scale, longitudinal human studies [4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 18, 21, 22, 24, 25, 26, 27, 28, 30, 31, 34, 64, 72, 74, 76, 80, 81, 85, 88, 89, 90, 96, 100, 101, 102, 103, 110, 112, 120, 137, 142, 145, 155, 156, 168, 173, 178].
Impact of Coffee Type and Preparation: Research should differentiate the effects of various coffee types (e.g., instant, filtered, decaffeinated, espresso, Arabic Qahwa) and preparation methods on longevity markers and health outcomes in humans [1, 52, 57, 59, 188].
Gene-Environment Interactions: Further investigation into how individual genetic polymorphisms (e.g., ADORA2A, Mt5178C, FOXO1A) modulate responses to coffee consumption is crucial for personalized dietary recommendations [45, 134, 165, 169].

5.4 Limitations

Heterogeneous Study Designs — A large proportion of the identified studies were in vitro or animal models, which may not directly translate to human biological longevity.
Dental Focus — A significant number of studies focused on the effects of coffee on dental materials, which, while relevant to oral health, is not directly pertinent to systemic human longevity.
Inconsistent Longevity Markers — Studies utilized a wide array of proxies for aging and longevity (e.g., mortality, α-Klotho levels, epigenetic age, telomere length, physical frailty), making direct comparisons and synthesis challenging.
Observational Bias — Many human studies were observational cohorts, making them susceptible to unmeasured confounding variables that could influence the observed associations between coffee and longevity.
Lack of Standardized Coffee Metrics — "Coffee consumption" was defined inconsistently across studies, varying in terms of cups per day, caffeine content, and type of coffee, hindering the establishment of clear dose-response relationships.

5.5 Future directions

Longitudinal Human Cohorts — Conduct large-scale, prospective cohort studies with detailed, standardized coffee intake data and robust, consistent longevity biomarkers.
Randomized Controlled Trials — Design RCTs to investigate specific coffee components (e.g., kahweol, chlorogenic acid) on validated human longevity pathways.
Multi-Omics and Systems Biology — Integrate genomic, epigenomic, proteomic, and metabolomic data to understand coffee's effects on aging at a systems level.
Standardized Coffee Intake Assessment — Develop and implement standardized methods for quantifying coffee intake, including type, preparation, and caffeine content, across research studies.
Personalized Nutrition Approaches — Explore how individual genetic profiles and health statuses modulate responses to coffee consumption, guiding personalized dietary recommendations.

6) Conclusion
Coffee consumption is frequently associated with a reduced risk of all-cause and cardiovascular mortality, with reported Hazard Ratios (HR) and Relative Risks (RR) for all-cause mortality ranging from 0.21 [188] to 0.94 [176] in various populations and consumption levels, though high intake may increase mortality risk in certain groups. These findings suggest that moderate coffee consumption may contribute to healthy aging and extended lifespan in diverse human populations. However, the heterogeneous nature of study designs and longevity markers, particularly the prevalence of in vitro dental material studies, most significantly affects the certainty and generalizability of the findings. Future research should focus on large-scale, longitudinal human cohort studies with standardized coffee intake assessments to establish definitive dose-response relationships and mechanistic insights into coffee's role in human longevity.

References
SAIMSARA Session Index — session.json

Figure 1. Publication-year distribution of included originals

Figure 1. Publication-year distribution of included originals

Figure 2. Study-design distribution of included originals

Figure 2. Study-design distribution

Figure 3. Study-type (directionality) distribution of included originals
Figure 3. Directionality distribution

Figure 3. Directionality distribution

Figure 4. Main extracted research topics

Figure 4. Main extracted research topics (Results)

Figure 5. Limitations of current studies (topics)

Figure 5. Limitations of current studies (topics)

Figure 6. Future research directions (topics)

Figure 6. Future research directions (topics)