Our paper examined common approaches to adjusting for energy intake using a causal framework. Willet et al raised 4 points of disagreement with our conclusions.
I'll try to summarise with our responses. Beware, it jumps straight into technical details!
Willet et al: 'the energy partition model is not appropriate because it does not ultimately control for total energy intake" & this "is not consistent with the isocaloric diet/disease relation of greatest interest'
@GeorgiaTomova et al: 'Nutritional data are compositional, with the total being mathematically determined by its components. A model containing all components of energy intake therefore... controls for the total, making it necessarily isocaloric'
4/12
Q2: Standard energy-adjusted models
Willet et al: '(The claimed issues with the 'standard model' are) not a limitation or bias of the standard energy-adjusted model as the authors conclude. Rather, this reflects a poorly specified exposure'
@GeorgiaTomova et al: this is a 'genuine statistical bias' because '1) fewer components... leads to greater residual confounding; & 2) more components summarized by the total energy variable (may yield) composite variable bias'
6/12
Q3 Nutrient densities.
Willet et al: 'energy density... represents an interaction, but such an interaction is often biologically likely... it is (therefore) fully appropriate to hypothesize and model diet composition expressed as a percentage of calories'
@GeorgiaTomova et al: 'We profoundly disagree' & quote Willet & Stamfer: 'Since a nutrient density variable contains the inverse of caloric intake... nutrient densities will tend to be associated with disease in the opposite direction to total'
8/12
Q4 Measurement error
Willet et al: 'correlated errors in the numerator & denominator tend to cancel out when calculating nutrient densities or energy-adjusted intakes... (in) partition model, measurement errors are accumulated...'
@GeorgiaTomova et al: 'adjustment for all components should... offer the maximum information about the... error structure and, therefore, return the most accurate coefficients... adjusting for total energy intake does not provide as much information'
10/12
We are thrilled at the interest that our paper has attracted & hope it will increase awareness of the issues with different approaches to modelling energy intake.
If this is your area, please consider a reading our paper & letter exchange!
PS the notes to Willet et al include a curious/amusing claim that we 'chose' not to reply to Willet et al's letter! This is untrue, & hopefully is something @AJCNutrition can correct.
I'm glad both the letter & our response can now be read!
Excited to have @mpiccininni3 speaking at the @turinginst causal inference interest group about whether cognitive screening tests should be corrected for age and education
Marco explains it is fairly standard, when performing cognitive screening tests, to 'correct' (or standardise) the result for demographic characteristics (e.g. age and level of education). The resulting score tells you someone's result for people of similar age & education
'Correcting' the cognitive score for age and education is therefore equivalent to ignoring the part of the cognitive test score that is due to age and education.
So an older (or less educated) person needs to score lower on the raw test to achieve the same 'corrected' result.
Many nutrition studies are interested in substitution effects.
Substitution effects are the effect of SWAPPING a particular nutrient or food with one or more other nutrients or foods while keeping the total energy (or mass) the same.
Our new study confirms the tragic consequences of delaying the UK's first lockdown.
If it started 1 week earlier, there would have been 20k-35k fewer deaths. The required duration, for the same exit incidence, would also have halved from 69 to 35 days 1/6 journals.plos.org/plosone/articl…
The UK experienced one of the highest per-capita death tolls during the first #Covid19 wave.
It has been fiercely debated whether this was partly due to the UK government's relatively slow initiation of lockdown measures.
Our study used novel simulations to estimate the number of #Covid19 cases & deaths that would have happened in England during the first wave if lockdown measures had been started 1 week earlier, & the impact on the required duration of lockdown. 3/6 journals.plos.org/plosone/articl…
Most people don't realise that academic science is a very long way from healthy.
In fact, all good academic scientists must, at some point, go through a reckoning. When they awaken from the 'dream of science' to realise just how broken things are.
My own crisis happened during my PhD. It was gradual, but at some point I realised academic science wasn't driven by truth, quality, or collectivism, but ego, opportunism, and exploitation. I couldn't believe it. It seemed so wrong and unfair.
It hit me like grief. Anger, depression, bargaining. Years later & I'm still struggling. It hurts when I see bad science or a bad scientist getting celebrated.
I've been been told my 'problem' is I 'care about doing good science'. But I refuse to give in.
A thread on our study in @BJOGTweets, which uses a regression discontinuity approach to estimate the separate effects of fasting plasma glucose and diagnosis of gestational diabetes in women screened during pregnancy
/1 #EpiTwitter
In England, women are diagnosed with gestational diabetes if they have a fasting glucose above 5.6mmol/L. This is a higher than other countries, including Scotland, where the threshold is 5.1mmol/L. It's thought women with 'mild' hyperglycaemia have low risk.
If 'evidence based medicine' is working there should be REGULAR occasions when the 'evidence' not only disagrees with 'clinical experience' but actively contradicts it.
Wherever 'clinical experience' is allowed to overrule 'scientific evidence', we return to quackery.
'Clinical experience' can be extremely misleading, and history is littered with examples. That's why we take a wider dispassionate view and aim to update practice based on science. This principle is the main distinction between contemporary medicine and 'medicine' of old.