Objectives: Dietary intake is a key aspect of occupational health.
To capture the characteristics of
dietary behaviour that is affected by occupational environment that may impact on disease risk,
collection of prospective multi
-
day dietary records are required. The aims of this paper are to: i) the
collection of multi da
y dietary data in the
Airwaves health monitoring study, ii) describe the dietary
coding procedures applied and ii
i
) investigate the
plausibility
of dietary reporting
in this
occupational cohort.
Design: A dietary coding protocol for this large
-
scale study
was developed to minimise coding error
rate. Participants (
n
4,412) who completed 7
-
day food records were included for cross
-
sectional
analyses. Energy intake misreporting was
estimated using the Goldberg method. Multivariate
logistic regression models
we
re applied to
determine participant characteristics associated with
energy intake misreporting.
Setting: British police force employees enrolled (2007 to 2012) into the Airwave Health Monitoring
Study.
Results: The mean code error rate per food diary was
3.7% (SD 3.2%). The strongest predictors of
energy intake under
-
reporting were body mass index (BMI) and physical activity. Compared to
participants with
BMI <25kg/m2,
those
with BMI >30kg/m2 had increased odds of being classified
as under
-
reporting energ
y intake (men OR 5.20 95%CI 3.92, 6.89; women OR 2.66 95%CI 1.85,
3.83). Men and women in the highest physical activity category compared to the lowest were also
more likely to be classified as under
-
reporting (men OR 3.33 95%CI 2.46, 4.50; women OR 4.34
9
5%CI 2.91, 6.55).
Conclusions: A reproducible dietary record coding procedure
h
as been developed to minimise
coding error in complex 7
-
day diet diaries. The prevalence of energy intake under
-
reporting is
comparable to
existing
national UK cohort
s
and, in agreement with previous studies classification
of under
-
reporting was biased towards specific sub groups of participants.