Bradford Hill criteria explained

The Bradford Hill criteria, otherwise known as Hill's criteria for causation, are a group of nine principles that can be useful in establishing epidemiologic evidence of a causal relationship between a presumed cause and an observed effect and have been widely used in public health research. They were established in 1965 by the English epidemiologist Sir Austin Bradford Hill.

In 1996, David Fredricks and David Relman remarked on Hill's criteria in their seminal paper on microbial pathogenesis.[1]

Definition

In 1965, the English statistician Sir Austin Bradford Hill proposed a set of nine criteria to provide epidemiologic evidence of a causal relationship between a presumed cause and an observed effect. (For example, he demonstrated the connection between cigarette smoking and lung cancer.) The list of the criteria is as follows:[2]

  1. Strength (effect size): A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal.
  2. Consistency (reproducibility): Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect.
  3. Specificity: Causation is likely if there is a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.
  4. Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay).
  5. Biological gradient (dose–response relationship): Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.
  6. Plausibility: A plausible mechanism between cause and effect is helpful (but Hill noted that knowledge of the mechanism is limited by current knowledge).
  7. Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of an effect. However, Hill noted that "lack of such [laboratory] evidence cannot nullify the epidemiological effect on associations".
  8. Experiment: "Occasionally it is possible to appeal to experimental evidence".
  9. Analogy: The use of analogies or similarities between the observed association and any other associations.

Some authors[3] consider, also, Reversibility: If the cause is deleted then the effect should disappear as well.

Debate in epidemiology

Bradford Hill's criteria had been widely accepted as useful guidelines for investigating causality in epidemiological studies but their value has been questioned because they have become somewhat outdated.[4]

In addition, their method of application is debated. Some proposed options how to apply them include:

  1. Using a counterfactual consideration as the basis for applying each criterion.[5]
  2. Subdividing them into three categories: direct, mechanistic and parallel evidence, expected to complement each other. This operational reformulation of the criteria has been recently proposed in the context of evidence-based medicine.[6]
  3. Considering confounding factors and bias.[7]
  4. Using Hill’s criteria as a guide, but not considering them to give definitive conclusions.[8]
  5. Separating causal association and interventions, because interventions in public health are more complex than can be evaluated by use of Hill’s criteria[9]

An argument against the use of Bradford Hill criteria as exclusive considerations in proving causality is that the basic mechanism of proving causality is not in applying specific criteria—whether those of Bradford Hill or counterfactual argument—but in scientific common sense deduction.[10] Others argue that the specific study from which data has been produced is important, and while the Bradford Hill criteria may be applied to test causality in these scenarios, the study type may rule out deducing or inducing causality, and the criteria are only of use in inferring the best explanation of this data.[11]

Debate over the scope of application of the criteria includes, whether they can be applied to social sciences.[12] The argument proposes that there are different motives behind defining causality; the Bradford Hill criteria applied to complex systems such as health sciences are useful in prediction models where a consequence is sought; explanation models as to why causation occurred are deduced less easily from Bradford Hill criteria because the instigation of causation, rather than the consequence, is needed for these models.

Examples of application

Researchers have applied Hill’s criteria for causality in examining the evidence in several areas of epidemiology, including connections between exposures to molds and infant pulmonary hemorrhage,[13] ultraviolet B radiation, vitamin D and cancer,[14] [15] vitamin D and pregnancy and neonatal outcomes,[16] alcohol and cardiovascular disease outcomes,[17] infections and risk of stroke,[18] nutrition and biomarkers related to disease outcomes,[19] foods and nutrients related to cardiovascular disease and diabetes[20] and sugar-sweetened beverage consumption and the prevalence of obesity and obesity-related diseases.[21] They have also been used in non-human epidemiological studies, such as on the effects of neonicotinoid pesticides on honey bees.[22] Their use in quality improvement of health care services has been proposed, highlighting how quality improvement methods can be used to provide evidence for the criteria.[23]

Since the description of the criteria, many methods to systematically evaluate the evidence supporting a causal relationship have been published, for example the five evidence-grading criteria of the World Cancer Research Fund (Convincing; Probable; Limited evidence – suggestive; Limited evidence – no conclusion; Substantial effect on risk unlikely).[24]

Notes and References

  1. Fredricks . David . Relman . David . Sequence-Based Identification of Microbial Pathogens: a Reconsideration of Koch's Postulates . Clinical Microbiology Reviews . January 1996 . 9 . 1 . 18–33 . 10.1128/CMR.9.1.18 . 8665474 . 172879.
  2. Hill . Austin Bradford . 1965 . The Environment and Disease: Association or Causation? . . 58 . 295–300 . 14283879 . 1898525 . 5 . 10.1177/003591576505800503.
  3. Howick J, Kelly P, Kelly M. Establishing a causal link between social relationships and health using the Bradford Hill Guidelines. . SSM Popul Health . 2019 . 8 . 100402 . 31193417 . 10.1016/j.ssmph.2019.100402 . 6527915 .
  4. Schünemann H, Hill S, Guyatt G . etal . 2011 . The GRADE approach and Bradford Hill's criteria for causation . Journal of Epidemiology & Community Health . 65 . 5. 392–95 . 10.1136/jech.2010.119933. 20947872 . 206990828 .
  5. Höfler M . 2005. The Bradford Hill considerations on causality: a counterfactual perspective? . . 2 . 11 . 16269083 . 1291382 . 1 . 10.1186/1742-7622-2-11 . free .
  6. Howick J, Glasziou P, Aronson JK . 2009. The evolution of evidence hierarchies: what can Bradford Hill's 'guidelines for causation' contribute? . . 102 . 186–94 . 19417051 . 10.1258/jrsm.2009.090020 . 5 . 2677430.
  7. Glass TA, Goodman SN, Hernán MA, Samet JM . 2013 . Causal inference in public health . . 34 . 61–75 . 23297653 . 10.1146/annurev-publhealth-031811-124606 . 4079266.
  8. Potischman N, Weed DL . 1999 . Causal criteria in nutritional epidemiology . . 69 . 6 . 1309S–14S . 10359231. 10.1093/ajcn/69.6.1309S . free .
  9. Rothman KJ, Greenland S . 2005 . Causation and causal inference in epidemiology . . 95 . Suppl 1 . S144–50 . 16030331 . 10.2105/AJPH.2004.059204. 10.2105/AJPH.2004.059204 . free .
  10. Phillips, CV . Goodman KJ . 2006. Causal criteria and counterfactuals; nothing more (or less) than scientific common sense?. Emerging Themes in Epidemiology. 3 . 5 . 16725053 . 1488839 . 1 . 10.1186/1742-7622-3-5 . free .
  11. Ward, AC . 2009 . The role of causal criteria in causal inferences: Bradford Hill's "aspects of association . Epidemiologic Perspectives & Innovations . 6 . 2 . 19534788 . 1 . 10.1186/1742-5573-6-2 . 2706236 . free .
  12. Ward, AC . 2009. The Environment and Disease: Association or Causation? . Medicine, Health Care and Philosophy . 12 . 333–43 . 19219564 . 10.1007/s11019-009-9182-2 . 3. 7284783 .
  13. Etzel . Ruth A. . 2003 . Stachybotrys . Current Opinion in Pediatrics . en . 15 . 1 . 103–106 . 10.1097/00008480-200302000-00017 . 12544280 . 1040-8703.
  14. Grant WB . 2009 . How strong is the evidence that solar ultraviolet B and vitamin D reduce the risk of cancer? An examination using Hill's criteria for causality . Dermatoendocrinology . 1 . 1 . 17–24 . 20046584 . 2715209 . 10.4161/derm.1.1.7388.
  15. Mohr SB, Gorham ED, Alcaraz JE, Kane CI, Macera CA, Parsons JE, Wingard DL, Garland CF . 2012 . Does the evidence for an inverse relationship between serum vitamin D status and breast cancer risk satisfy the Hill criteria? . Dermatoendocrinology . 4 . 2 . 152–57 . 22928071 . 10.4161/derm.20449 . 3427194.
  16. Aghajafari F, Nagulesapillai T, Ronksley PE, Tough SC, O'Beirne M, Rabi DM . 2013 . Association between maternal serum 25-hydroxyvitamin D level and pregnancy and neonatal outcomes: systematic review and meta-analysis of observational studies . . 346 . Mar 26 . f1169 . 23533188 . 10.1136/bmj.f1169. free .
  17. Ronksley PE, Brien SE, Turner BJ, Mukamal KJ, Ghali WA . 2011 . Association of alcohol consumption with selected cardiovascular disease outcomes: a systematic review and meta-analysis . . 342 . Feb 22 . d671 . 21343207 . 3043109 . 10.1136/bmj.d671.
  18. Grau AJ, Urbanek C, Palm F . 2010 . Common infections and the risk of stroke . Nat Rev Neurol . 6 . 12 . 681–94 . 21060340 . 10.1038/nrneurol.2010.163. 29975502 .
  19. de Vries J, Antoine JM, Burzykowski T, Chiodini A, Gibney M, Kuhnle G, Méheust A, Pijls L, Rowland I . 2013 . Markers for nutrition studies: review of criteria for the evaluation of markers . . 52 . 7 . 1685–99 . 23955424 . 10.1007/s00394-013-0553-3. 9356545 .
  20. Miller . Victoria . Micha . Renata . Choi . Erin . Karageorgou . Dimitra . Webb . Patrick . Mozaffarian . Dariush . 2022-02-01 . Evaluation of the Quality of Evidence of the Association of Foods and Nutrients With Cardiovascular Disease and Diabetes: A Systematic Review . JAMA Network Open . 5 . 2 . e2146705 . 10.1001/jamanetworkopen.2021.46705 . 2574-3805 . 8814912 . 35113165.
  21. Hu FB . 2013 . Resolved: there is sufficient scientific evidence that decreasing sugar-sweetened beverage consumption will reduce the prevalence of obesity and obesity-related diseases . . 14 . 8. 606–19 . 23763695 . 10.1111/obr.12040. 5325726.
  22. Cresswel . James E. Desneux. Nicolas. VanEngelsdorp. Dennis. Dietary traces of neonicotinoid pesticides as a cause of population declines in honey bees: an evaluation by Hill's epidemiological criteria. Pest Management Science. 68. 6. 819–827. 24 January 2012. 10.1002/ps.3290. 22488890.
  23. Poots. Alan J. Reed. Julie E. Woodcock. Thomas. Bell. Derek. Goldmann. Don. How to attribute causality in quality improvement: lessons from epidemiology. BMJ Quality & Safety. 26. 11. 933–937. 2 August 2017. 10.1136/bmjqs-2017-006756. 28768711. 10044/1/49089. 2782038 . free.
  24. http://www.aicr.org/continuous-update-project/ What the Continuous Update Conclusions Mean

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