Health related behaviours across the life course, including dietary habits, play an important role in health and ageing (1-3). However, the measurement and analysis of diet in longitudinal epidemiological studies is extremely challenging. An individual’s diet is the result of the current zeitgeist, their social, economic and cultural circumstances and, it varies in relation to age (2, 4, 5). A person’s dietary intake will also vary according to season, day of week and has considerable random variation (6). The aim in epidemiological studies is to capture an individual’s consistent long-term diet in the context of this variation. Objective measures of dietary intake, such as direct observation, are costly and carry significant participant and researcher burden (7). Therefore self-reported measures of dietary intake have been developed. A number of these are used in the CLOSER cohorts e.g. food frequency questionnaires (FFQs) in ALSPAC, National Child & Development Study (NCDS), 1970 British birth cohort (BCS70), Southampton Women's Survey (SWS), Hertfordshire cohort study (HCS) and diet diaries in National Survey of Health and Development (NSHD), ALSPAC and SWS. However, it remains difficult to accurately capture habitual dietary intake, and there is always the possibility of over- or under-reporting (7). Validation studies of these instruments in EPIC-Norfolk demonstrated that correlation between dietary biomarkers and a 7-day food diary was better than correlation with an FFQ (8, 9). However, each of these methods also have specific pros and cons. For example, FFQs can capture foods consumed irregularly but reporting is limited to the items contained in the food list designed for the study (7). In food diaries, all food consumed at the time of consumption is recorded, but it may miss foods not eaten regularly (7). Within-method differences e.g. a 3-day food diary versus a 7-day food diary adds to heterogeneity in dietary measurement. Results from each method can therefore be slightly different. For example, one study found that macronutrient estimates from FFQs are higher compared with estimates from a 7-day or 16-day food diary using data from EPIC-Norfolk (8). In ALSPAC, slightly different dietary patterns in childhood were produced depending on the dietary assessment used (10).

Nutritional epidemiology has advanced during the time span of the CLOSER cohorts. An individual’s diet contains many foods/nutrients that interact or can act in synergy to influence health. Nutritional epidemiology is moving away from analysing associations of health outcomes with individual foods and nutrients towards dietary pattern analysis (11). Analyses of data in the CLOSER cohorts reflect this trend (10, 12-14). Comparing dietary intake across CLOSER cohorts would provide powerful information about longitudinal and secular trends. For example, a previous comparison of data from a 24-hour recall in NSHD and a 4 day food diary in the National Diet and Nutrition Survey, found that children in 1950 consumed a diet that was higher in fat, but was considered healthier than children in the 1990s (15). Clarifying and documenting the methodological differences in dietary assessment between the CLOSER cohorts is an essential step for any cross-cohort dietary pattern comparisons.

Comparing relationships between diet and health outcomes across cohorts will provide insight into potential cohort specific or consistent associations. Allostatic load (AL) is one health outcome that has been harmonised across the CLOSER cohorts. AL is a measure of cumulative biological dysregulation across body systems (16) which has been associated with mortality and frailty (16-18). Environmental stressors, including diet, have been proposed as contributors to AL however evidence is limited (19-24). Supporting evidence from large, longitudinal studies will help to confirm the link between diet and AL. Therefore, examining the association between diet and AL across the CLOSER cohorts would be a significant contribution to this effort.

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