Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 3 complete abstracts (546 words), 9 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
The relating of causes to the effects they produce. Causes are termed necessary when they must always precede an effect and sufficient when they initiate or produce an effect. Any of several factors may be associated with the potential disease causation or outcome, including predisposing factors, enabling factors, precipitating factors, reinforcing factors, and risk factors.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Causalities; Enabling Factors; Enabling Factor; Factor, Enabling; Factors, Enabling; Multifactorial Causality; Causalities, Multifactorial; Causality, Multifactorial.
Where it fits in the MeSH classification
- Broader topics
- Epidemiologic Factors
- Narrower topics
- Precipitating Factors; Protective Factors; Risk Factors
- See also
- Mediation Analysis
Research landscape
PubMed indexes 1,132,431 records tagged with the MeSH heading “Causality” (counts retrieved 2026-10-31). 293,246 of them (25.9%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 436,663 records.
Reviews account for 197,793 records (17.5%) and meta-analyses for 31,085. Randomized controlled trials number 26,656 (2.4%) as a share of all records on the topic.
Show the data
| Period | Records |
|---|---|
| through 1999 | 141,521 |
| 2000-2009 | 261,001 |
| 2010-2019 | 436,663 |
| 2020 onward | 293,246 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 197,793 | 17.5% |
| Meta-analyses | 31,085 | 2.7% |
| Randomized controlled trials | 26,656 | 2.4% |
Method: PubMed query "Causality"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-31.
Reading the evidence in public health and nutrition
Population and nutrition studies mostly observe what people eat, breathe or are exposed to and then look for links with health, which shows association and not proof of cause. Self-reported diet is imprecise, people who eat or live differently also differ in other ways, and effects measured across a population may not apply to one person. Check the study design, how exposure was measured, what else was accounted for and the size of the effect, not only whether it was statistically significant.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Cardiometabolic risk assessment by anthropometric and biochemical indices in mexican population | 2025 | Research article Design not recorded in structured metadata | 12 | cc by PMID 40727914 · DOI · PMC12301211 |
| Nicotine pouches and youth: emerging patterns and potential cardiovascular risks | 2025 | Review article Design not recorded in structured metadata | 7 | cc by PMID 41358246 · DOI · PMC12675456 |
| Polygenic scores capture genetic modification of the adiposity-cardiometabolic risk factor relationship | 2026 | Research article Design not recorded in structured metadata | 5 | cc by PMID 41297543 · DOI · PMC12985365 |
Cardiometabolic risk assessment by anthropometric and biochemical indices in mexican population [1]
Abstract reading summary — source excerpts
- Opening excerpt
- BackgroundCardiometabolic risk (CMR) factors, including obesity, hypertension, hyperglycemia, and dyslipidemia, are major contributors to global morbidity and mortality.
- Closing excerpt
- Future studies are required to validate these findings and establish population-specific reference values.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (286 words)
BackgroundCardiometabolic risk (CMR) factors, including obesity, hypertension, hyperglycemia, and dyslipidemia, are major contributors to global morbidity and mortality. Although gold-standard diagnostic methods for obesity and insulin resistance exist, they are costly and inaccessible in resource-limited settings. Conventional anthropometric measures underestimate parameters that enhance risk prediction and fail explaining the complex relationship between adipose tissue distribution and metabolic dysfunction. This study evaluated and compared the diagnostic accuracy of 15 conventional and non-conventional anthropometric and biochemical indices for identifying CMR factors in Mexican adults. We hypothesized that non-conventional indices would demonstrate superior diagnostic performance compared with traditional measures.MethodsWe analyzed data from 1,876 participants aged 20-80 years from the 2022 National Health and Nutrition Survey (ENSANUT). Anthropometric indices, including body mass index (BMI), waist-to-height ratio (WHtR), body roundness index (BRI), deep abdominal adipose tissue index (DAAT), and weight-adjusted waist index (WWI), were calculated alongside biochemical indices such as HOMA-IR, triglyceride-glucose index (TG), and combined indices like TG*BMI and TG*WC. Receiver operating characteristic (ROC) curve analysis evaluates diagnostic performance, with sex-stratified analyses conducted to determine optimal cut-off values.ResultsNon-conventional indices demonstrated superior diagnostic performance across all outcomes. For obesity detection, TG*BMI achieved the highest area under the curve (AUC=0.972), followed by WHtR and BRI (AUC=0.934). For CMR assessment, BRI showed perfect discrimination (AUC=1.000), whereas TG*WC (AUC=0.976) and LAP (AUC=0.963) demonstrated exceptional performance. Sex-based analyses revealed that optimal cut-off values varied, with most indices maintaining a consistent discriminatory capacity across sexes.ConclusionsNon-conventional anthropometric indices, particularly those incorporating metabolic and anthropometric parameters, outperform traditional BMI-based assessments for CMR stratification in Mexican adults. These accessible, cost-effective tools offer superior diagnostic accuracy and enhance early identification of high-risk individuals in resource-limited healthcare settings. Future studies are required to validate these findings and establish population-specific reference values.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40727914 · DOI · PMC12301211
Nicotine pouches and youth: emerging patterns and potential cardiovascular risks [2]
Abstract reading summary — source excerpts
- Opening excerpt
- The rapid rise in nicotine pouch use among teens and young adults signals a shift in nicotine consumption with significant public health implications.
- Closing excerpt
- This review explores the potential cardiovascular consequences of nicotine pouch use in youth, emphasizing the urgency of evidence-based research to inform clinical guidance, regulatory action, and prevention strategies.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (111 words)
The rapid rise in nicotine pouch use among teens and young adults signals a shift in nicotine consumption with significant public health implications. Marketed as discreet and "tobacco free," these products are often perceived as safer alternatives to smoking, yet their cardiovascular risks remain largely unexamined. Emerging concerns center on the high nicotine content, efficient bloodstream delivery, and growing rates of dual or poly-use with other nicotine products. Adolescents, in particular, face heightened vulnerability due to ongoing physiological development and increased addiction susceptibility. This review explores the potential cardiovascular consequences of nicotine pouch use in youth, emphasizing the urgency of evidence-based research to inform clinical guidance, regulatory action, and prevention strategies.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41358246 · DOI · PMC12675456
Polygenic scores capture genetic modification of the adiposity-cardiometabolic risk factor relationship [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Polygenic scores (PGSs) that can predict response to interventions can facilitate precision medicine and are detectable in observational datasets as PGS-by-exposure (PGS×E) interactions.
- Closing excerpt
- Our study provides a framework for the comparison of PGS×E strategies and informs efforts toward clinically useful response-focused PGSs.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (149 words)
Polygenic scores (PGSs) that can predict response to interventions can facilitate precision medicine and are detectable in observational datasets as PGS-by-exposure (PGS×E) interactions. PGSs based on interactions (iPGSs) or variance effects (vPGSs) may be more powerful than standard PGSs for detecting PGS×E, but these have yet to be systematically compared. We describe a generalized pipeline for developing and comparing these PGS types and apply it to detect genetic modification of the relationship between adiposity (measured by BMI) and a broad set of cardiometabolic risk factors. Our applied analysis in the UK Biobank identified significant PGS×BMI for 16/20 risk factors, most consistently for the iPGS approach. Many interactions replicated in All of Us (AoU); for example, we observed a 72% larger BMI-alanine aminotransferase association in the top iPGS decile in AoU. Our study provides a framework for the comparison of PGS×E strategies and informs efforts toward clinically useful response-focused PGSs.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41297543 · DOI · PMC12985365
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Global Effect of Modifiable Risk Factors on Cardiovascular Disease and Mortality [4]
- Research article The Epidemiology of Alzheimer's Disease Modifiable Risk Factors and Prevention [5]
- Research article Carotid Intima-Media Thickness Progression as Surrogate Marker for Cardiovascular Risk: Meta-Analysis of 119 Clinical Trials Involving 100 667 Patients [6]
- Research article Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps [7]
- Research article Long-term cardiometabolic disease risk in women with PCOS: a systematic review and meta-analysis [8]
- Research article Obesity and Cardiometabolic Risk Factors: From Childhood to Adulthood [9]
References
- Quirino-Vela L, Mayoral-Chavez M, Pérez-Cervera Y, Ildefonso-García O, Cruz-Altamirano E, Ruiz-García M, et al.. Cardiometabolic risk assessment by anthropometric and biochemical indices in mexican population. . 2025. PMID 40727914 · DOI · PMC12301211
- Abid S, Aggarwal A, Duarte F, Sethi S, Iyengar S, Zarich S. Nicotine pouches and youth: emerging patterns and potential cardiovascular risks. . 2025. PMID 41358246 · DOI · PMC12675456
- Westerman KE, Gervis JE, O'Connor LJ, Udler MS, Manning AK. Polygenic scores capture genetic modification of the adiposity-cardiometabolic risk factor relationship. . 2026. PMID 41297543 · DOI · PMC12985365
- Global Cardiovascular Risk Consortium, Magnussen C, Ojeda FM, Leong DP, Alegre-Diaz J, Amouyel P, et al.. Global Effect of Modifiable Risk Factors on Cardiovascular Disease and Mortality. N Engl J Med. 2023. PMID 37632466 · DOI · PMC10589462
- Zhang XX, Tian Y, Wang ZT, Ma YH, Tan L, Yu JT. The Epidemiology of Alzheimer's Disease Modifiable Risk Factors and Prevention. J Prev Alzheimers Dis. 2021. PMID 34101789 · DOI · PMC12280729
- Willeit P, Tschiderer L, Allara E, Reuber K, Seekircher L, Gao L, et al.. Carotid Intima-Media Thickness Progression as Surrogate Marker for Cardiovascular Risk: Meta-Analysis of 119 Clinical Trials Involving 100 667 Patients. Circulation. 2020. PMID 32546049 · DOI · PMC7115957
- Polygenic Risk Score Task Force of the International Common Disease Alliance. Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps. Nat Med. 2021. PMID 34782789 · DOI
- Wekker V, van Dammen L, Koning A, Heida KY, Painter RC, Limpens J, et al.. Long-term cardiometabolic disease risk in women with PCOS: a systematic review and meta-analysis. Hum Reprod Update. 2020. PMID 32995872 · DOI · PMC7600286
- Drozdz D, Alvarez-Pitti J, Wójcik M, Borghi C, Gabbianelli R, Mazur A, et al.. Obesity and Cardiometabolic Risk Factors: From Childhood to Adulthood. Nutrients. 2021. PMID 34836431 · DOI · PMC8624977
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-11-04; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-11-04.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.