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Type 2 diabetes (T2D) can be prevented or delayed through a healthy lifestyle. Digital behavior change interventions (DBCIs) may offer cost-effective and scalable means to support lifestyle changes. This study investigated associations between user engagement with a habit-formation-based DBCI, the BitHabit app, and changes in T2D risk factors over 12 months in 963 participants at risk of T2D. User engagement was characterized by calculating use metrics from the BitHabit log data. User ratings were used as a subjective measure of engagement. The use metrics and user ratings were the strongest associated with improvements in diet quality. Weak positive associations were observed between the use metrics and changes in waist circumference and body mass index. No associations were found with changes in physical activity, fasting plasma glucose, or plasma glucose two hours after an oral glucose tolerance test. To conclude, increased use of the BitHabit app can have beneficial impacts on T2D risk factors, especially on diet quality.

BackgroundPrenatal urban environmental exposures have been associated with blood pressure in children. The dynamic of these associations across childhood and later ages is unknown. ObjectivesTo assess associations of prenatal urban environmental exposures with blood pressure trajectories from childhood to early adulthood.MethodsRepeated measures of systolic (SBP) and diastolic blood pressure (DBP) were collected in up to 7,454 participants from a UK birth cohort. Prenatal urban exposures (n=42) covered measures of noise, air pollution, built environment, natural spaces, traffic, meteorology, and food environment. An exposome-wide association study approach was used. Linear spline mixed-effects models were used to model associations of each exposure with trajectories of blood pressure. Replication was sought in four independent European cohorts (N up to 9,261). ResultsIn discovery analyses, higher humidity was associated with a faster increase (mean yearly change in SBP for an interquartile range [IQR] increase in humidity: 0.29 mmHg/year, 95%CI 0.20; 0.39) and higher temperature with a slower increase (mean yearly change in SBP per IQR increase in temperature: -0.17 mmHg/year, 95%CI -0.28; -0.07) in SBP in childhood. Higher levels of humidity and air pollution were associated with faster increase in DBP in childhood and slower increase in adolescence. There was little evidence of an association of other exposures with change in SBP or DBP. Results for humidity and temperature, but not for air pollution, were replicated in other cohorts. ConclusionsReplicated findings suggest that higher prenatal humidity and temperature could modulate blood pressure changes across childhood.

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Funder: The NIHR Biomedical Research Centre in Cambridge, Funder: Finnish Innovation Fund Sitra, Funder: Foundation for Paediatric Research, Funder: Ministry of Social Affairs and Health of Finland, Funder: Yrjö Jahnsson Foundation, Funder: Research Committee of the Kuopio University Hospital Catchment Area (State Research Funding), Funder: The city of Kuopio, Funder: The UK Medical Research Council, Funder: Finnish Cultural Foundation, Funder: Ministry of Education and Culture of Finland, Funder: Juho Vainio Foundation, Funder: Paavo Nurmi Foundation, Funder: Diabetes Research Foundation in Finland, Funder: Finnish Foundation for Cardiovascular Research, Funder: Social Insurance Institution of Finland, Aims/hypothesis: We studied for the first time the long-term effects of a combined physical activity and dietary intervention on insulin resistance and fasting plasma glucose in a general population of predominantly normal-weight children. Methods: We carried out a 2 year non-randomised controlled trial in a population sample of 504 children aged 6–9 years at baseline. The children were allocated to a combined physical activity and dietary intervention group (306 children at baseline, 261 children at 2-year follow-up) or a control group (198 children, 177 children) without blinding. We measured fasting insulin and fasting glucose, calculated HOMA-IR, assessed physical activity and sedentary time by combined heart rate and body movement monitoring, assessed dietary factors by a 4 day food record, used the Finnish Children Healthy Eating Index (FCHEI) as a measure of overall diet quality, and measured body fat percentage (BF%) and lean body mass by dual-energy x-ray absorptiometry. The intervention effects on insulin, glucose and HOMA-IR were analysed using the intention-to-treat principle and linear mixed-effects models after adjustment for sex, age at baseline, and pubertal status at baseline and 2 year follow-up. The measures of physical activity, sedentary time, diet and body composition at baseline and 2 year follow-up were entered one-by-one as covariates into the models to study whether changes in these variables might partly explain the observed intervention effects. Results: Compared with the control group, fasting insulin increased 4.65 pmol/l less (absolute change +8.96 vs +13.61 pmol/l) and HOMA-IR increased 0.18 units less (+0.31 vs +0.49 units) over 2 years in the combined physical activity and dietary intervention group. The intervention effects on fasting insulin (regression coefficient β for intervention effect −0.33 [95% CI −0.62, −0.04], p = 0.026) and HOMA-IR (β for intervention effect −0.084 [95% CI −0.156, −0.012], p = 0.023) were statistically significant after adjustment for sex, age at baseline, and pubertal status at baseline and 2 year follow-up. The intervention had no effect on fasting glucose, BF% or lean body mass. Changes in total physical activity energy expenditure, light physical activity, moderate-to-vigorous physical activity, total sedentary time, the reported consumption of high-fat (≥60%) vegetable oil-based spreads, and FCHEI, but not a change in BF% or lean body mass, partly explained the intervention effects on fasting insulin and HOMA-IR. Conclusions/interpretation: The combined physical activity and dietary intervention attenuated the increase in insulin resistance over 2 years in a general population of predominantly normal-weight children. This beneficial effect was partly mediated by changes in physical activity, sedentary time and diet but not changes in body composition. Trial registration: ClinicalTrials.gov NCT01803776 Graphical abstract

Fyysinen, sosiaalinen, taloudellinen ja poliittinen ruokaympäristö muovaavat lasten ja nuorten ruokatottumuksia ja vaikuttavat terveyteen läpi elämän. Terveyttä edistävien ruokavalintojen tulisi olla edullisia, vaivattomia ja miellyttäviä jokaiselle. Hankkeen tavoitteina oli selvittää suomalaisten lasten ja nuorten ruokaympäristön nykytilaa sekä keinoja, joilla sitä on edistetty hallinnon eri aloilla, kehittää menetelmät lasten ja nuorten ravitsemuksen seuraamiseen ja ruokaympäristöön kohdistuvien toimenpiteiden kustannusvaikutusten arviointiin sekä laatia toimenpide-ehdotuksia ruokaympäristön kehittämiseksi. Selvitys osoitti, että ruokaympäristön edistämiseen on saatavilla suosituksia ja työvälineitä, mutta niiden jalkautumisessa on haasteita. Vahvempia ohjauskeinoja tarvitaan esimerkiksi hintojen, markkinoinnin ja hankintojen ohjaamiseen. Kattava tieto lasten ja nuorten ravitsemuksesta puuttuu. Lasten ja nuorten ravitsemuksen seuraamiseen kehitettiin digitaalinen työkalu mahdollistamaan tiedon tehokkaampaa keräämistä ja hyödyntämistä terveydenhuollossa sekä tiedolla johtamisessa. Terveystaloudellisten mallinnusten perusteella ruokaympäristöön kohdistuvilla lasten ja nuorten terveeseen painonkehitykseen tähtäävillä politiikkatoimilla voidaan saavuttaa terveyshyötyjen lisäksi merkittäviä säästöjä terveydenhuollon pitkänaikavälin kustannuksissa. Ruokaympäristön kehittämiseen esitetään 11 toimenpidekokonaisuutta: ravitsemusprofiili, lasten ja nuorten ravitsemusseuranta, hintaohjaus, markkinoinnin ohjaus, valikoiman ja esillepanon ohjaus, ravitsemuslaatu varhaiskasvatuksen ja koulujen ruokailuissa, muu ruokatarjonta kouluissa, ruokatarjonta harrastusympäristöissä ja koulujen lähiympäristöissä, ravitsemusmerkinnät, ruokakasvatus sekä poikkihallinnollisuus ja ravitsemusohjaus kunnissa.

Objective: To investigate the cross-sectional associations of dietary carbohydrate and fatty acid intakes with cognition in mid-childhood. Design: Dietary carbohydrate and fatty acid intakes were assessed using 4-d food records, and cognition was evaluated using the Raven’s Coloured Progressive Matrices (RCPM) score. The cross-sectional associations of dietary carbohydrate and fatty acid intakes with cognition were investigated using linear regression analyses adjusted for age, sex, body fat percentage, household income, parental education and daily energy intake. Setting: The baseline examinations of the Physical Activity and Nutrition in Children study. Participants: A population-based sample of 487 children (250 boys, 237 girls) aged 6–8 years living in the city of Kuopio, Finland. Results: A higher dietary intake of fructose (standardised regression coefficient, β = 0·24, P < 0·001), total fibre (β = 0·16, P = 0·02) and soluble fibre (β = 0·15, P = 0·02) was associated with a higher RCPM score in boys. Other dietary carbohydrates and fatty acids, including total carbohydrates, glucose, sucrose, starch, insoluble fibre, total fat, SFAs, MUFAs, PUFAs, palmitic acid (C16), stearic acid (C18), linoleic acid (C18:2), α-linoleic acid (C18:3), arachidonic acid (C20:4), EPA (C20:5n-3) and DHA (C22:6n-6), were not associated with the RCPM score in boys. Dietary carbohydrates or fatty acids were not associated with the RCPM score in girls. Conclusions: Higher dietary fructose and fibre intakes were associated with better cognition in boys, but not in girls. Dietary fatty acids were not related to cognition in boys or in girls. peerReviewed

We investigated the associations of cardiometabolic risk factors with academic achievement and whether motor performance, cardiorespiratory fitness, physical activity, or sedentary behaviour mediated these associations. Altogether 175 children 6–8 years-of-age participated in the study. We assessed body fat percentage (BF%), waist circumference, insulin, glucose, triglycerides, HDL cholesterol, and systolic and diastolic blood pressure, leptin, alanine aminotransferase, and gamma-glutamyltransferase (GGT). Reading fluency, reading comprehension, and arithmetic skills were assessed using standardized tests. Speed/agility, balance, and manual dexterity test results were used to calculate motor performance score and physical activity was assessed by combined heart rate and movement sensor and cardiorespiratory fitness by maximal cycle ergometer test. In boys, BF% was inversely associated with reading fluency (β = −0.262, P = 0.007) and reading comprehension (β = −0.216, P = 0.025). Motor performance mediated these associations. Leptin was inversely related to reading fluency (β = −0.272, P = 0.006) and reading comprehension (β = −0.287, P = 0.003). The inverse association of leptin with reading fluency was mediated by motor performance. In girls, GGT was inversely associated with reading fluency independent of confounders (β = −0.325, P = 0.007). The inverse association of BF% with academic achievement among boys was largely explained by motor performance. Leptin in boys and GGT in girls were inversely associated with academic achievement independent of confounding factors. peerReviewed

Purpose Poor diet quality may impair academic achievement in children, but such evidence is limited. Therefore, we investigated the associations of healthy diet in Grade 1 assessed by Mediterranean Diet Score (MDS), Baltic Sea Diet Score (BSDS), and Finnish Children Healthy Eating Index (FCHEI) with academic achievement in Grades 1–3 in children. Methods The participants were 161 Finnish children who were 6–8 years old in Grade 1 and attended in a large ongoing physical activity and dietary intervention study. Dietary factors were assessed using 4-day food records, and MDS, BSDS, and FCHEI were calculated. Academic achievement was assessed by reading fluency, reading comprehension, and arithmetic skill tests. The data were analyzed using linear regression analysis and analysis of covariance adjusted for age, sex, parental education, household income, body fat percentage, physical activity, the PANIC Study group, and total energy intake. Results MDS was positively associated with reading comprehension in Grade 3 (standardized regression coefficient β = 0.167, P = 0.032). BSDS was positively associated with reading fluency in Grades 2–3 and reading comprehension in Grades 1–3 (β = 0.161–0.274, P < 0.05). FCHEI was positively related to reading fluency in Grades 1–2 and reading comprehension in Grades 1–3 (β = 0.190–0.344, P < 0.05). Children in the highest third of BSDS and FCHEI had better reading fluency and reading comprehension in Grades 1–3 than children in the lowest third (P < 0.05). None of the diet scores was associated with arithmetic skills. Conclusions Healthier diet assessed by BSDS or FCHEI in Grade 1 was associated with better reading skills, but not with arithmetic skills, among children in Grades 1–3. Long-term intervention studies are needed to investigate the effects of improvements in diet quality on academic achievement among children. peerReviewed

Lähtökohdat: Lasten pienempään ylipainon ja lihavuuden riskiin yhteydessä olevasta fyysisen aktiivisuuden määrästä ja kuormittavuudesta tiedetään verrattain vähän. Tavoitteenamme oli selvittää objektiivisesti mitatun fyysisen aktiivisuuden eri kuormittavuustasojen ja fyysisen passiivisuuden määrän yhteyksiä ikä- ja sukupuolivakioidun painoindeksin keskihajontapistemäärään (BMI-SDS) ja ylipainoisuuteen 6–8-vuotiailla suomalaisilla lapsilla. Menetelmät: Tutkimukseen osallistui 386 lasta. Fyysinen aktiivisuus ja fyysinen passiivisuus mitattiin liike- ja sykemittaukset yhdistävällä aktiivisuusmittarilla (Actiheart®, CamNtech Ltd., Papworth, Iso-Britannia). Fyysinen passiivisuus ja fyysisen aktiivisuuden kuormittavuus määriteltiin fyysisen aktiivisuuden aiheuttaman energiankulutuksen perusteella hyödyntäen lepoaineenvaihdunnan kerrannaisia (Metabolic equivalent of task, MET). Fyysinen passiivisuus vastasi alle 1,5 MET:n kuormittavuutta, kevyt fyysinen aktiivisuus 1,5–4 MET:n kuormittavuutta ja vähintään kohtuukuormitteinen fyysinen aktiivisuus yli 4 MET:n kuormittavuutta. BMI-SDS määritettiin suomalaisten viitearvojen perusteella ja ylipaino määriteltiin kansainvälisen lihavuusasiantuntijaryhmän esittämien raja-arvojen mukaan. Aineisto analysoitiin lineaarisella regressioanalyysilla ja Receiver Operating Characteristics (ROC) -käyrien avulla. Tulokset: Runsaampi fyysisen passiivisuuden määrä (standardoitu regressiokerroin β=0,235, P