Study cohort

The Whitehall Study II consists of non-industrial civil servants, who were recruited in London at age 35 to 55 years during 1985–1988 (phase 1). The initial sample size was 10,308 individuals (33.1% female and 66.9% male). The participants were followed up via questionnaire in 1989–1990 (phase 2), 1991–1993 (phase 3), 1995–1996 (phase 4), 1997–1999 (phase 5), 2001 (phase 6), 2003–2004 (phase 7), 2006 (phase 8), 2008–2009 (phase 9) and 2012–2013 (phase 11). In phases 1, 3, 5, 7, 9 and 11 they were additionally invited for screening in a research clinic29. Phase 10 (2011) consisted of a smaller sample of participants used for a pilot study. The study was approved by the Joint UCL/UCLH Committee on the Ethics of Human Research and carried out in accordance with the ethical principles set out in the Declaration of Helsinki. Further all participants have been asked for informed consent at every follow-up.

Ascertainment of sugar intake from sweet food/beverages

Diet was assessed at phases 3, 5, 7 and 9 using a 127-item machine-readable semi-quantitative food frequency questionnaire (FFQ) which originates from the tool used in the US Nurses’ Health Study, a self-administered questionnaire on habitual diet over the past 12 months30, 31. In order to reflect most diets in the UK it has been modified and anglicized32. This FFQ has been validated against a 7 day diet diary in a stratified random sample of 865 participants in the Whitehall Study II at collection phase 330. Sweet food and beverage intake was measured with 15 items such as cakes, biscuits, added sugar to coffee or tea, and fizzy soft drinks (see Supplementary Table S1). Sugar intake was calculated by multiplying sweet food/beverage consumption frequencies per day by their sugar content and portion size based on McCance and Widdowson’s The Composition of Foods, 5th edition 33.

Depressive symptom assessment

The 30-item General Health Questionnaire (GHQ) measures depressive and somatic symptoms over the past two weeks34. Caseness was defined as reporting ≥5 symptoms and is referred to as common mental disorder (CMD). This measure was included in follow-up questionnaires at all phases apart from phase 4. In addition, the 20-item Center of Epidemiologic Studies Depression Scale (CES-D), a self-report measure of depressive symptoms in the general population over the past week35, was administered at phases 7, 9 and 11. Individuals scoring ≥16 were considered cases of depression36. Lastly, a clinical interview using the Revised Clinical Interview Schedule (CIS-R) was administered at phase 11 with participants assessed according to International Classification of Diseases (ICD-10) F32 criteria. The computerized self-completion version of the CIS-R included questions on depressive symptoms that were present for at least 2 weeks37,38,39. The GHQ and CES-D have been validated against the CIS-R in this cohort and showed high sensitivity and specificity in measuring depressive episodes39.

Covariates

Potential confounders were chosen based on review of the literature and restricted to variables available at all phases used in the analyses. All estimates were initially adjusted for age, ethnicity (White/ South Asian/ Black) and sex, with an interaction of sex and age where both sexes included. Socio-demographic variables consisted of marital status (married/cohabiting, single or divorced/widowed) and last employment grade level within the civil service, (high, intermediate, low). Health behaviours included smoking (never, former, current), alcohol intake (none: ≤1 unit/weeks, moderate, heavy: ≥14 units/week) self-reported physical activity (vigorous, moderate and non/mild)40 and duration of sleep (5 categories from ≤5 hours to ≥9 hours/day). Diet-related factors comprised energy intake, diet quality, fish, coffee and tea intake based on FFQ data. Energy intake was used to ascertain dietary misreporting. Misreporting was considered where the log ratio of energy intake to estimated energy expenditure was outside of 3 SD of the log mean. This definition was adopted by Mosdol et al. 2007 and based on basal metabolic rate equations of the Department of Health41,42,43. Since sugar intake from sweet food/beverages was strongly correlated with energy intake (r = 0.61, P < 0.001), energy intake was adjusted for with the partition method by using energy intake from other foods44. Diet quality was assessed using the Dietary Approaches to Stop Hypertension (DASH) diet score modified by excluding a measure for sweet drinks45. DASH diet score, coffee and tea intake were analysed as continuous variables, fish intake per day as quintiles and all dichotomized for descriptive analyses. Body mass index (BMI) (kg/m2) and central obesity (in women waist circumference ≥88 cm and in men ≥102 cm) were both measured by trained staff46. Physical health was defined as diabetes and cardiovascular disease (coronary heart disease and stroke, CVD) based on self-reports which were validated using the study clinical examination, Hospital Episode Statistics data, and by contacting general practitioners for confirmation when no other external source existed. Cancer was based on cancer registration data29. Finally, doctor diagnosis of depression was based on self-report at phases 1 to 4 and on self-reported antidepressant intake at all phases after phase 4.

Statistical analysis

At each phase, participants were included if they had answered at least 8 of the FFQ sweet food and beverage items47 (less than 5% of eligible sample had one missing item and about 1% two or more), their ethnicity was known to be either White, Black or South Asian, and participants were not energy misreporters (see above). In addition, participants were also excluded from analyses if they had incomplete data on GHQ-, CES-D- or CIS-R caseness for outcome-specific analyses, respectively. Supplementary Fig. S1 shows how the included sample was reached (see Online).

Three binary outcomes were analysed, GHQ caseness, CES-D caseness and CIS-R caseness. Daily sweet food and beverage intake was modelled as sex-specific tertiles of sugar intake from sweet food/beverages based on the distribution at phase 3 (in men <39.5, ≥39.5 to <67.0 and ≥67.0 g/day; in women <30.0, ≥30.0 to <51.0 and ≥51.0 g/day). To describe the sample at phase 3, GHQ cases, non-cases and tertiles of sugar intake by covariate were compared. To examine the prospective association of sugar intake from sweet food and beverages, a random effects logistic regression model (REM) was performed using the STATA command xtlogit 48, with exposures at phases 3, 5, 7 and 9 for GHQ caseness, and at phases 7 and 9 for CES-D caseness. The applicability of the REM was tested by introducing study phase-interactions and likelihood ratio tests (LRT). The prospective effect of sugar intake from sweet food/beverages on incident and recurrent CMD and depression was examined using REMs in 2, 5 and 10-year cycles49. Figure 1 shows the included phases for analyses using GHQ caseness as the outcome. For example, the association between sugar intake and GHQ status 2 years later was conducted by combining the associations between sugar intake at Phase 5 and incident GHQ caseness at Phase 6, and between sugar intake at Phase 7 and incident GHQ caseness at Phase 8. For all depression outcomes, incidence was assumed if no CMD was apparent at each baseline, and recurrence if CMD was apparent at each baseline. For the analyses of depression, two 5-year cycles (to Phase 9 and 11) and three 10 year cycles (to Phases 7, 9 and 11) were used. For clinical depression, one 5-year cycle and one 10-year cycle were used.

Figure 1 Modes of analysis using cycle approach for common mental disordera. Numbers indicate study phases. Phases with food frequency data in bold; no data on common mental disorder available at Phase 4. aCommon mental disorder measured using the 30-item General Health Questionnaire. Full size image

To check for reverse causation, that depressive symptoms may affect subsequent sugar intake from sweet food/beverages, linear regression models of 5-year change and multinomial logistic regression for change groups were fitted for each cycle, from phases 3 to 5, 5 to 7 and 7 to 9, with CMD at phases 3, 5, 7 respectively, and for change from phase 7 to 9 with depression at phase 7. Normal distribution of change in sugar intake from sweet food/beverages was verified using a histogram. Change groups were created by subtracting tertiles of sugar intake at baseline (t) from sugar intake from sweet food/beverages at follow-up (t + 5 y) and coding −2/−1 as decrease, 0 as no change and +1/+2 as increase in sugar intake from sweet food/beverages.

All analyses were performed using Stata 1450. Interactions of CMD and depression with sex in the initial model (Model 0 per sex-specific tertile trend: adjusted for age and ethnicity) were tested using LRT since sex-differences have been reported in a prior study on the association of diet and depression in the Whitehall II cohort51. Further adjustments were grouped into four hierarchical models: baseline socio-demographic factors and health behaviours (Model 1), diet-related factors (Model 2), BMI and central obesity (Model 3), and physical health (Model 4). In sensitivity analyses, main analyses were repeated by: (a) excluding participants with unknown or reported doctor diagnosis of depression at each baseline (at phases 3/5/7/9: 166/156/193/209 individuals) and: (b) excluding participants with extreme values of sugar intake (>7 SD) at phases 3/5/7/9: 5/3/4/4 individuals.