The validity of grocery purchase data as an indicator of food consumption is uncertain. This paper investigated (1) the associations between food consumption and grocery purchases using automatically accumulated purchase data and (2) whether the strength of the associations differed in certain sub-populations. The participants filled in a FFQ, and a major Finnish retailer issued us with their loyalty-card holders’ grocery purchase data covering the 1- and 12-month periods preceding the FFQ. We used gamma statistics to study the association between thirds/quarters of FFQ and grocery purchase data (frequency/amount) separately for eighteen food groups among the 11 983 participants. Stratified analyses were conducted for subgroups based on sex, family structure, educational level, household income and self-estimated share of purchases from the retailer. We also examined the proportion of participants classified into the same, adjacent, subsequent and opposite categories using the FFQ and purchase data. The gammas ranged from 0·12 (cooked vegetables) to 0·75 (margarines). Single households had stronger gammas than two-adult families, and participants with > 60 % of purchases from the retailer had stronger gammas. For most food groups, the proportion of participants classified into the same or adjacent category was > 70 %. Most discrepancies were observed for fresh/cooked vegetables, berries and vegetable oils. Even though the two methods did not categorise all food groups similarly, we conclude that grocery purchase data are able to describe food consumption in an adult population, and future studies should consider purchase data as a resource-saving and moderately valid measure in large samples.

Several prospective studies have shown an association between cows’ milk consumption and the risk of islet autoimmunity and/or type 1 diabetes. We wanted to study whether processing of milk plays a role. A population-based birth cohort of 6081 children with HLA-DQB1-conferred risk to type 1 diabetes was followed until the age of 15 years. We included 5545 children in the analyses. Food records were completed at the ages of 3 and 6 months and 1, 2, 3, 4 and 6 years, and diabetes-associated autoantibodies were measured at 3–12-month intervals. For milk products in the food composition database, we used conventional and processing-based classifications. We analysed the data using a joint model for longitudinal and time-to-event data. By the age of 6 years, islet autoimmunity developed in 246 children. Consumption of all cows’ milk products together (energy-adjusted hazard ratio 1·06; 95 % CI 1·02, 1·11; P = 0·003), non-fermented milk products (1·06; 95 % CI 1·01, 1·10; P = 0·011) and fermented milk products (1·35; 95 % CI 1·10, 1·67; P = 0·005) was associated with an increased risk of islet autoimmunity. The early milk consumption was not associated with the risk beyond 6 years. We observed no clear differences based on milk homogenisation and heat treatment. Our results are consistent with the previous studies, which indicate that high milk consumption may cause islet autoimmunity in children at increased genetic risk. The study did not identify any specific type of milk processing that would clearly stand out as a sole risk factor apart from other milk products.

The aim of the present study was to examine the associations between the maternal intake of fatty acids during pregnancy and the risk of preclinical and clinical type 1 diabetes in the offspring. The study included 4887 children with human leucocyte antigen (HLA)-conferred type 1 diabetes susceptibility born during the years 1997–2004 from the Finnish Type 1 Diabetes Prediction and Prevention Study. Maternal diet was assessed with a validated FFQ. The offspring were observed at 3- to 12-month intervals for the appearance of type 1 diabetes-associated autoantibodies and development of clinical type 1 diabetes (average follow-up period: 4·6 years (range 0·5–11·5 years)). Altogether, 240 children developed preclinical type 1 diabetes and 112 children developed clinical type 1 diabetes. Piecewise linear log-hazard survival model and Cox proportional-hazards regression were used for statistical analyses. The maternal intake of palmitic acid (hazard ratio (HR) 0·82, 95 % CI 0·67, 0·99) and high consumption of cheese during pregnancy (highest quarter v. intermediate half HR 0·52, 95 % CI 0·31, 0·87) were associated with a decreased risk of clinical type 1 diabetes. The consumption of sour milk products (HR 1·14, 95 % CI 1·02, 1·28), intake of protein from sour milk (HR 1·15, 95 % CI 1·02, 1·29) and intake of fat from fresh milk (HR 1·43, 95 % CI 1·04, 1·96) were associated with an increased risk of preclinical type 1 diabetes, and the intake of low-fat margarines (HR 0·67, 95 % CI 0·49, 0·92) was associated with a decreased risk. No conclusive associations between maternal fatty acid intake or food consumption during pregnancy and the development of type 1 diabetes in the offspring were detected.

The duration of the period of time during which diet should be recorded for sufficiently accurate results on the usual intake of an individual is an especially challenging issue in prospective studies among children. We set out to describe nutrient intake variability in preschoolers and to determine the number of record days required (D) to estimate intake of energy and thirty-two nutrients. The diet and the use of dietary supplements were assessed with three consecutive daily food records including one weekend day in 1639 children participating in the population-based birth cohort of the Type 1 Diabetes Prediction and Prevention Project (DIPP) in Finland. Variance ratios and D stratified by sex and age groups were calculated for 455 (1-year-old), 471 (3-year-old) and 713 (6-year-old) children (born between 1998 and 2003). Within:between variance ratios and D increase with increasing age, and are slightly higher for girls. Vitamin A, cholesterol, n-3 and n-6 fatty acids, β-carotene and folate intakes require the most replicates. Including supplemental intake has an impact on the variance estimates according to the proportion of supplement users. In the DIPP Nutrition Study with 3 d food records, the correlation coefficients between observed and true intakes of energy and thirty-two nutrients averaged 0·91 in 1-year-old children, 0·79 in 3-year-old children and 0·74 in 6-year-old children. For providing accurate nutrient intake estimates, three replicates of food records are reasonable in 1-year-old children but must be questioned for several nutrients in 3- and 6-year-old children. The accuracy of ranking boys is greater than that for girls.

The diet of pre-school children is determined by the parents and carers. The aim of the present study was to describe dietary clusters of pre-school children and their mothers in Finland, and analyse the similarity of dietary clusters within child–mother pairs. The present study comprised the mothers (n 4862) whose child was recruited in the Type 1 Diabetes Prediction and Prevention Nutrition Study and the children belonging to selected, cross-sectional age groups of 1 year (n 719), 3 years (n 708) and 6 years (n 841). The dietary data were collected from children by 3-d food records and from mothers by a FFQ validated for pregnant women. The food consumption data were analysed for patterns by hierarchical cluster analysis. Three main dietary clusters were identified in children: ‘healthy’ and ‘traditional’ in all three age groups, and ‘ready-to-eat baby foods’ in 1-year-olds and ‘fast foods, sweet’ in the older children. Six main clusters were identified among the mothers who completed a FFQ for their diet during pregnancy. Some familial dependence between dietary clusters of mother–child pairs was observed in 6-year-old children but not in younger children. Younger age and lower educational level of the mother were associated with the cluster ‘fast food, sweet’ only at the age of 3 years. The diets of pre-school children vary by age and only a slight similarity within dietary clusters of mother–child pairs was observed.