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…continued from page 112
In countries (or individuals) with high carbohydrate
intakes, limiting intake could be beneficial. In a recent issue
of
The Lancet Public Health
, Sara Seidelmann and colleagues
examine the 25-year follow-up data from the Atherosclerosis
Risk in Communities (ARIC) study and place their findings
in the context of a meta-analysis of published studies about
carbohydrate intake.
The authors concluded that the epidemiological association
between carbohydrate intake and death is U-shaped, with the
lowest risk occurring with a carbohydrate intake of 50–55%
of energy, and with both lower and higher intakes being
associated with higher risk of death (hazard ratio 1.20, 95%
CI: 1.09–1.32 for low carbohydrate consumption; 1.23, 1.11–
1.36 for high carbohydrate consumption). Such differences
in risk associated with extreme differences in intake of a
nutrient are plausible, but observational studies cannot
completely exclude residual confounders when the apparent
differences are so modest.
Based on first principles, a U-shaped association is logical
between most essential nutrients versus health outcomes.
Essential nutrients should be consumed above a minimal
level to avoid deficiency and below a maximal level to avoid
toxicity. This approach maintains physiological processes and
health (i.e. a so-called sweet spot). Although carbohydrates
are technically not an essential nutrient (unlike protein
and fats); a certain amount is probably required to meet
short-term energy demands during physical activity and to
maintain fat and protein intakes within their respective sweet
spots.
On the basis of these principles, moderate intake of
carbohydrate (e.g. roughly 50% of energy) is likely to be more
appropriate for the general population than are very low or
very high intakes. This would translate to a generally balanced
diet that includes fruit, vegetables, legumes, whole grains,
nuts, fish, dairy and unprocessed meats, all in moderation.
The findings of the meta-analysis should be interpreted
with caution, given that so-called group thinking can lead to
biases in what is published from observational studies, and
the use of analytical approaches to produce findings that
fit in with current thinking. The ideal approach to meta-
analysis would be a collaboration involving investigators of
all the large studies ever done (including those that remain
unpublished) that have collected data about carbohydrate
intake and clinical events, and pool the individual data using
transparent methods. This approach is likely to provide
the best and most unbiased summary of the effects of
carbohydrates on health, rather than reliance on the results
of any single study.
Future observational studies should also consider new
methods, which include triangulation, to assess whether
there is a coherent pattern of information about the links
between consumption of a nutrient, such as carbohydrates,
with a panel of physiological or nutritional biomarkers
and clinical outcomes. When appropriate, this approach
should be complemented by large and long-term clinical
trials investigating the effects of different dietary patterns
(constructed from information about the effects of individual
nutrients and foods), because the effect of individual nutrients
is likely to be modest. When coherent information emerges
from different approaches and is replicated, this will form a
sound basis for robust public health recommendations.
Source:
The Lancet Public Health
2018;
3
(9): e408–409.