Analysis of complex findings to consider saturated fats and health
PHE ePoster Library. Kijauskaite G. Apr 9, 2019; 258521; 15373
Goda Kijauskaite
Goda Kijauskaite
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Abstract
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Abstract Background:
The Scientific Advisory of Nutrition Committee (SACN) advises the UK Government on nutrition and related health matters. SACN undertakes risk assessments in line with its framework for evaluation of evidence. This can be challenging where systematic reviews (SR), meta-analysis (MA) and pooled analyses (PA) under consideration take different analytical approaches or present multiple and potentially contradictory analyses. A key example is the use of fixed-effect or random-effects models within MA. There is a lack of consensus on the most appropriate model, the choice of which can impact on results.

Methods:
A systematic search was undertaken for SR, MA and PA on saturated fats and health. Reference was made to the approach to statistical models in the Cochrane Handbook and advice sought from statisticians. Detailed data from studies that met the inclusion criteria were extracted to evidence tables.

Results:
Thirty MA were identified: 6 used both fixed-effect and random-effects, 2 used fixed-effect; 12 used random-effects; and 10 were unclear. The most comprehensive SR with MA presented the results of both models. The results for a key outcome (CHD events) differed depending on the model used. The following were considered for all: the appropriateness of the model assumptions, the direction and magnitude of the effect, statistical significance and the level of agreement between the models where the results of both models were reported. Any disagreement between the results of fixed-effect and random-effects models (for example, differing p-values) was reflected in the grading of the evidence which was used to inform recommendations.

Conclusion:
Complex evidence on saturated fats and health required consideration of the totality of the available data - without favouring one statistical approach or disregarding any results - in order to reach robust public health recommendations.
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