Consumption of sugar-sweetened beverages (SSB) by infants and young children are less explored in Asian populations. The Growing Up in Singapore Towards healthy Outcomes cohort study examined associations between SSB intake at 18 months and 5 years of age, with adiposity measures at 6 years of age. We studied Singaporean infants/children with SSB intake assessed by FFQ at 18 months of age (n 555) and 5 years of age (n 767). The median for SSB intakes is 28 (interquartile range 5·5–98) ml at 18 months of age and 111 (interquartile range 57–198) ml at 5 years of age. Association between SSB intake (100 ml/d increments and tertile categories) and adiposity measures (BMI standard deviation scores (sd units), sum of skinfolds (SSF)) and overweight/obesity status were examined using multivariable linear and Poisson regression models, respectively. After adjusting for confounders and additionally for energy intake, SSB intake at age 18 months were not significantly associated with later adiposity measures and overweight/obesity outcomes. In contrast, at age 5 years, SSB intake when modelled as 100 ml/d increments were associated with higher BMI by 0·09 (95 % CI 0·02, 0·16) sd units, higher SSF thickness by 0·68 (95 % CI 0·06, 1·44) mm and increased risk of overweight/obesity by 1·2 (95 % CI 1·07, 1·23) times at age 6 years. Trends were consistent with SSB intake modelled as categorical tertiles. In summary, SSB intake in young childhood is associated with higher risks of adiposity and overweight/obesity. Public health policies working to reduce SSB consumption need to focus on prevention programmes targeted at young children.

The importance of overall diet in modifying circulating lipoprotein particles and fatty acids during pregnancy is unclear. We examined the relationships of diet quality as assessed by the validated Healthy Food Intake Index (HFII) with serum HDL, LDL and VLDL particle concentrations and sizes and proportions of serum fatty acids in pregnant women at high risk for gestational diabetes mellitus (GDM). Overall, 161 women with a BMI of ≥30 kg/m2 and/or a history of GDM were drawn from the Finnish Gestational Diabetes Prevention Study, which is a dietary and exercise intervention trial to prevent GDM. At baseline, the HFII score was inversely related to concentrations of HDL particles (P=0·010) and MUFA (P=0·010) and positively related to concentrations of n-3 (P<0·001) and n-6 (P=0·003) PUFA. The significance for MUFA disappeared after adjustments. An increase in the HFII score from the first to second trimester of pregnancy correlated with reduced VLDL particle size (r −0·16, 95 % CI −0·31, −0·01), decreased MUFA concentrations (r −0·17, 95 % CI −0·31, −0·01) and elevated n-6 PUFA concentrations (r 0·16, 95 % CI 0·01, 0·31). In the maximum-adjusted model, the results remained significant except for VLDL particle size. These findings suggest that higher diet quality as defined by the HFII is related to a more favourable serum fatty acid profile, whereas the relationship with serum lipoprotein profile is limited in pregnant women at increased GDM risk.

Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84–88) presented a critique of our recently published paper in Cell Reports entitled ‘Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets’ (Lam et al., Cell Reports, Vol. 21, 2017, 2597–2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229–237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from ‘inflation in the FDR [false discovery rate]’, as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84–88), and are not ‘more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence’.

The aim was to analyse whether changes in the Healthy Food Intake Index (HFII) during pregnancy are related to gestational diabetes (GDM) risk. The 251 pregnant women participating had a pre-pregnancy BMI≥30 kg/m2 and/or a history of GDM. A 75 g oral glucose tolerance test (OGTT) was performed during the first and second trimesters of pregnancy for assessment of GDM. A normal OGTT result at first trimester was an inclusion criterion for the study. FFQ collected at first and second trimesters served for calculating the HFII. A higher HFII score reflects higher adherence to the Nordic Nutrition Recommendations (NNR) (score range 0–17). Statistical methods included Student’s t test, Mann–Whitney U test, Fisher’s exact test and linear and logistic regression analyses. The mean HFII at first trimester was 10·1 (95 % CI 9·7, 10·4) points, and the mean change from the first to the second trimester was 0·35 (95 % CI 0·09, 0·62) points. The range of the HFII changes varied from –7 to 7. The odds for GDM decreased with higher HFII change (adjusted OR 0·83 per one unit increase in HFII; 95 % CI 0·69, 0·99; P=0·043). In the analysis of the association between HFII-sub-indices and GDM, odds for GDM decreased with higher HFII-Fat change (fat percentage of milk and cheese, type of spread and cooking fats) but it was not significant in a fully adjusted model (P=0·058). Dietary changes towards the NNR during pregnancy seem to be related to a lower risk for GDM.

Epidemiological studies have shown that a number of nutrients are associated with better physical performance. However, little is still known about the role of the whole diet, particularly a healthy Nordic diet, in relation to physical performance. Therefore, we examined whether a healthy Nordic diet was associated with measures of physical performance 10 years later. We studied 1072 participants from the Helsinki Birth Cohort Study. Participants’ diet was assessed using a validated 128-item FFQ at the mean age of 61 years, and a priori-defined Nordic diet score (NDS) was calculated. The score included Nordic fruits and berries, vegetables, cereals, PUFA:SFA and trans-fatty acids ratio, low-fat milk, fish, red and processed meat, total fat and alcohol. At the mean age of 71 years, participants’ physical performance was measured using the Senior Fitness Test (SFT), and an overall SFT score was calculated. Women in the highest fourth of the NDS had on average 5 points higher SFT score compared with those in the lowest fourth (Pfor trend 0·005). No such association was observed in men. Women with the highest score had 17 % better result in the 6-min walk test, 16 % better arm curl and 20 % better chair stand results compared with those with the lowest score (all P values<0·01). In conclusion, a healthy Nordic diet was associated with better overall physical performance among women and might help decrease the risk of disability in old age.

Dyslipidaemia, hypertension and low-grade inflammation increase the risk of CVD. In the present meta-analysis, we examined whether adherence to a healthy Nordic diet, also called the Baltic Sea diet, may associate with a lower risk of these cardiometabolic risk factors. In 2001–2007, three cross-sectional Finnish studies were conducted: the Dietary, Lifestyle and Genetic Determinants of Obesity and Metabolic Syndrome study (n 4776); Health 2000 Survey (n 5180); Helsinki Birth Cohort Study (n 1972). The following parameters were assessed in these three studies: blood pressure, total, HDL- and LDL-cholesterol, TAG and high-sensitivity C-reactive protein (hs-CRP); a validated FFQ was used to assess the participants' dietary intakes. The Baltic Sea Diet Score (BSDS) was developed based on the healthy Nordic diet. All studies assessed confounding variables, such as physical activity and BMI, based on standardised questionnaires and measurements. The random-effects meta-analysis provided summary estimates for OR and 95 % CI by the BSDS quintiles. In the meta-analysis, the risk of elevated hs-CRP concentration was lower among men (OR 0·58, 95 % CI 0·43, 0·78) and women (OR 0·73, 95 % CI 0·58, 0·91) in the highest BSDS quintile than among those in the lowest BSDS quintile. In contrast, the risk of lowered HDL-cholesterol concentration was higher among women (OR 1·67, 95 % CI 1·12, 2·48) in the highest BSDS quintile than among those in the lowest BSDS quintile. However, no other associations were found. In conclusion, the associations between the adherence to the healthy Nordic diet and cardiometabolic risk factors are equivocal. Longitudinal studies are needed to further examine this hypothesis.

Recent genome-wide association studies have identified multiple loci associated with BMI or the waist:hip ratio (WHR). However, evidence on gene–lifestyle interactions is still scarce, and investigation of the effects of well-documented dietary and other lifestyle data is warranted to assess whether genetic risk can be modified by lifestyle. We assessed whether previously established BMI and WHR genetic variants associate with obesity and weight change in the Finnish Diabetes Prevention Study, and whether the associations are modified by dietary factors or physical activity. Individuals (n 459) completed a 3 d food record and were genotyped for twenty-six BMI- and fourteen WHR-related variants. The effects of the variants individually and in combination were investigated in relation to obesity and to 1- and 3-year weight change by calculating genetic risk scores (GRS). The GRS were separately calculated for BMI and the WHR by summing the increasing alleles weighted by their published effect sizes. At baseline, the GRS were not associated with total intakes of energy, macronutrients or fibre. The mean 1- and 3-year weight changes were not affected by the BMI or WHR GRS. During the 3-year follow-up, a trend for higher BMI by the GRS was detected especially in those who reported a diet low in fibre (P for interaction = 0·065). Based on the present findings, it appears unlikely that obesity-predisposing variants substantially modify the effect of lifestyle modification on the success of weight reduction in the long term. In addition, these findings suggest that the association between the BMI-related genetic variants and obesity could be modulated by the diet.

Strong epidemiological evidence suggests that slow prenatal or postnatal growth is associated with an increased risk of CVD and other metabolic diseases. However, little is known whether early growth affects postprandial metabolism and, especially, the appetite regulatory hormone system. Therefore, we investigated the impact of early growth on postprandial appetite regulatory hormone responses to two high-protein and two high-fat content meals. Healthy, 65–75-year-old volunteers from the Helsinki Birth Cohort Study were recruited; twelve with a slow increase in BMI during the first year of life (SGI group) and twelve controls. Subjects ate a test meal (whey meal, casein meal, SFA meal and PUFA meal) once in a random order. Plasma glucose, insulin, TAG, NEFA, ghrelin, peptide tyrosine-tyrosine (PYY), glucose-dependent insulinotropic peptide, glucagon-like peptide-1 and a satiety profile were measured in the fasting state and for 4 h after each test meal. Compared with the controls, the SGI group had about 1·5-fold higher insulin responses after the whey meal (P= 0·037), casein meal (P= 0·023) and PUFA meal (P= 0·002). TAG responses were 34–69 % higher for the SGI group, but only the PUFA-meal responses differed significantly between the groups. The PYY response of the SGI group was 44 % higher after the whey meal (P= 0·046) and 115 % higher after the casein meal (P= 0·025) compared with the controls. No other statistically significant differences were seen between the groups. In conclusion, early growth may have a role in programming appetite regulatory hormone secretion in later life. Slow early growth is also associated with higher postprandial insulin and TAG responses but not with incretin levels.

A cluster of variants in the fat mass and obesity-associated (FTO) gene are associated with the common form of obesity. Well-documented dietary data are required for identifying how the genetic risk can be modified by dietary factors. The objective of the present study was to investigate the associations between the FTO risk allele (rs9939609) and dietary intake, and to evaluate how dietary intake affects the association between FTO and BMI in the Finnish Diabetes Prevention Study during a mean follow-up of 3·2 years. A total of 479 (BMI >25 kg/m2) men and women were genotyped for rs9939609. The participants completed a 3 d food record at baseline and before every annual study visit. The average intakes at baseline and during the years 1, 2 and 3 were calculated. At baseline, the FTO variant rs9939609 was not associated with the mean values of total energy intake, macronutrients or fibre. At baseline, a higher BMI by the FTO risk genotype was detected especially in those who reported a diet high in fat with mean BMI of 30·6 (sd 4·1), 31·3 (sd 4·6) and 34·5 (sd 6·2) kg/m2 for TT, TA and AA carriers, respectively (P =0·005). Higher BMI was also observed in those who had a diet low in carbohydrates (P =0·028) and fibre (P =0·015). However, in the analyses adjusted for total energy intake, age and sex, significant interactions between FTO and dietary intakes were not found. These findings suggest that the association between the FTO genotype and obesity is influenced by the components of dietary intake, and the current dietary recommendations are particularly beneficial for those who are genetically susceptible for obesity.

FFQ require validation as part of epidemiological research of diet–disease relationships. Studies exploring associations between carbohydrate type and chronic diseases are rapidly increasing, but information on the validity of carbohydrate fractions, dietary glycaemic index (GI) and the glycaemic load (GL) estimated by FFQ is scarce. Likewise, the effects of subject characteristics on FFQ validity have been poorly documented. The present study evaluates the relative validity of an 131-item FFQ in relation to two 3 d food records (FR) performed 6 months apart focusing on the intake of carbohydrate fractions, dietary GI and the GL. Furthermore, we assessed the extent to which subjects' age, education and BMI explain differences between these methods. The study sample comprised 218 men and 292 women aged 25–74 years participating in a large population-based survey in Finland. Energy-adjusted Spearman's rank correlations ranged from 0·27 (sugars) to 0·70 (lactose) for men and from 0·37 (sugars) to 0·69 (lactose) for women. On average, 73 % of the subjects were categorised into the same or adjacent distribution quintile based on the two methods. In general, the FFQ overestimated the intakes compared with FR. Especially in women, FFQ validity for some nutrients was associated with the level of intake, subjects' age and, to a lesser extent, education but not BMI. In conclusion, the FFQ appears to be reasonably valid in the assessment of carbohydrate exposure variables, but the findings show a need for adjustment of diet–disease relationships for subjects' age and education.

Potatoes, especially mashed potatoes, are known to result in high glycaemic and insulinaemic responses. However, in most meals, potatoes are accompanied by other foods. The objective of the present study was to investigate how glycaemic and insulinaemic responses to a mashed potato meal changed when a high-fat food (rapeseed oil), a high-protein food (chicken breast) and/or salad were added to the meal. Healthy subjects (n 11) ingested the test meals once and the reference food (glucose solution) twice in a random order at 1-week intervals. Capillary blood samples were then drawn for 2 h, and glucose and insulin were analysed. The 2 h glycaemic responses to six mashed potato-containing meals varied more than twofold. The glycaemic index (GI) of pure mashed potato was 108, whereas combined with chicken breast, rapeseed oil and salad, it was only 54. The latter GI also differed considerably from its predicted value of 103, which was based on the individual GI of the components of the meal. The insulinaemic indices of the mashed potato-based meals varied between 94 and 148. Chicken breast in the meal increased the insulinaemic response, and rapeseed oil diminished it. However, the insulinaemic response to mashed potato with chicken breast and rapeseed oil was lower than that to mashed potato alone. In conclusion, the protein, fat and salad contents of a meal exert considerable influence on the glycaemic and insulinaemic responses to mashed potatoes. Furthermore, the estimation of the GI of a mixed meal by calculation is imprecise.

The beneficial effects of a low-glycaemic index (GI) meal on postprandial glucose and insulin levels have been demonstrated. However, limited data are available on the impact of overweight and glucose tolerance on postprandial responses to different GI meals. Our aim was to study the effects of physiological characteristics on postprandial glucose, insulin and lipid responses and the relative glycaemic response (RGR) of a low-GI (LGI) and a high-GI (HGI) meal. We recruited twenty-four normal-weight and twenty-four overweight subjects, twelve with normal glucose tolerance (NGT) and twelve with impaired glucose tolerance (IGT) in each group. Both test meals were consumed once and the glucose reference twice. Blood glucose and insulin were measured in the fasting state and over a 2 h period after each study meal, and TAG and NEFA were measured in the fasting state and over a 5 h period. The glucose responses of subjects with IGT differed significantly from those of subjects with NGT. The highest insulin responses to both meals were observed in overweight subjects with IGT. Physiological characteristics did not influence TAG or NEFA responses or the RGR of the meals. The LGI meal resulted in lower glucose (P < 0·001) and insulin (P < 0·001) responses, but higher TAG responses (P < 0·001), compared with the HGI meal. The GI of the meals did not affect the NEFA responses. In conclusion, the LGI meal causes lower glucose and insulin responses, but higher TAG responses, than the HGI meal. The RGR of the meals does not differ between normal-weight and overweight subjects with NGT or IGT.