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Dietary assessment of British police force employees: a description of diet record coding procedures and cross-sectional evaluation of dietary energy intake reporting (The Airwave Health Monitoring Study)

04 Apr 2017

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 affect disease risk, a collection of prospective multiday dietary records is required. The aims of this paper are to: (1) collect multiday dietary data in the Airwave Health Monitoring Study, (2) describe the dietary coding procedures applied and (3) 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 4412) who completed 7-day food records were included for cross-sectional analyses. Energy intake (EI) misreporting was estimated using the Goldberg method. Multivariate logistic regression models were applied to determine participant characteristics associated with EI misreporting.

Setting

British police force employees enrolled (2007–2012) 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 EI under-reporting were body mass index (BMI) and physical activity. Compared with participants with BMI<25 kg/m2, those with BMI>30 kg/m2 had increased odds of being classified as under-reporting EI (men OR 5.20 95% CI 3.92 to 6.89; women OR 2.66 95% CI 1.85 to 3.83). Men and women in the highest physical activity category compared with the lowest were also more likely to be classified as under-reporting (men OR 3.33 95% CI 2.46 to 4.50; women OR 4.34 95% CI 2.91 to 6.55).

Conclusions

A reproducible dietary record coding procedure has been developed to minimise coding error in complex 7-day diet diaries. The prevalence of EI under-reporting is comparable with existing national UK cohorts and, in agreement with previous studies, classification of under-reporting was biased towards specific subgroups of participants.

Click here to view the full article which appeared in BMJ Open