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Background/objectiveChildren BMI is a longitudinal phenotype, developing through interplays between genetic and environmental factors. Whilst childhood obesity is escalating, we require a better understanding of its early origins and variation across generations to prevent it.Subjects/methodsWe designed a cross-cohort study including 12,040 Finnish children from the Northern Finland Birth Cohorts 1966 and 1986 (NFBC1966 and NFBC1986) born before or at the start of the obesity epidemic. We used group-based trajectory modelling to identify BMI trajectories from 2 to 20 years. We subsequently tested their associations with early determinants (mother and child) and the possible difference between generations, adjusted for relevant biological and socioeconomic confounders.ResultsWe identified four BMI trajectories, ‘stable-low’ (34.8%), ‘normal’ (44.0%), ‘stable-high’ (17.5%) and ‘early-increase’ (3.7%). The ‘early-increase’ trajectory represented the highest risk for obesity. We analysed a dose-response association of maternal pre-pregnancy BMI and smoking with BMI trajectories. The directions of effect were consistent across generations and the effect sizes tended to increase from earlier generation to later. Respectively for NFBC1966 and NFBC1986, the adjusted risk ratios of being in the early-increase group were 1.08 (1.06–1.10) and 1.12 (1.09–1.15) per unit of pre-pregnancy BMI and 1.44 (1.05–1.96) and 1.48 (1.17–1.87) in offspring of smoking mothers compared to non-smokers. We observed similar relations with infant factors including birthweight for gestational age and peak weight velocity. In contrast, the age at adiposity peak in infancy was associated with the BMI trajectories in NFBC1966 but did not replicate in NFBC1986.ConclusionsExposures to adverse maternal predictors were associated with a higher risk obesity trajectory and were consistent across generations. However, we found a discordant association for the timing of adiposity peak over a 20-year period. This suggests the role of residual environmental factors, such as nutrition, and warrants additional research to understand the underlying gene–environment interplay.

Background/Objectives Children’s biological age does not always correspond to their chronological age. In the case of BMI trajectories, this can appear as phase variation, which can be seen as shift, stretch, or shrinking between trajectories. With maturation thought of as a process moving towards the final state - adult BMI, we assessed whether children can be divided into latent groups reflecting similar maturational age of BMI. The groups were characterised by early factors and time-related features of the trajectories. Subjects/Methods We used data from two general population birth cohort studies, Northern Finland Birth Cohorts 1966 and 1986 (NFBC1966 and NFBC1986). Height ( n  = 6329) and weight ( n  = 6568) measurements were interpolated in 34 shared time points using B-splines, and BMI values were calculated between 3 months to 16 years. Pairwise phase distances of 2999 females and 3163 males were used as a similarity measure in k-medoids clustering. Results We identified three clusters of trajectories in females and males ( Type 1 : females, n = 1566, males, n  = 1669; Type 2 : females, n  = 1028, males, n  = 973; Type 3 : females, n  = 405, males, n  = 521). Similar distinct timing patterns were identified in males and females. The clusters did not differ by sex, or early growth determinants studied. Conclusions: Trajectory cluster Type 1 reflected to the shape of what is typically illustrated as the childhood BMI trajectory in literature. However, the other two have not been identified previously. Type 2 pattern was more common in the NFBC1966 suggesting a generational shift in BMI maturational patterns.

ObjectivesType 2 diabetes (T2D) and comorbid depression challenges clinical management particularly in individuals with overweight. We aim to explore the shared etiology, via lifecourse adiposity, between T2D and depression.MethodsWe used data from birth until 46years from Northern Finland Birth Cohort 1966 (n = 6,372; 53.8% females). We conducted multivariate analyses on three outcomes: T2D (4.2%), depression (19.2%) and as comorbidity (1.8%). We conducted (i) Path analysis to clarify time-dependent body mass index (BMI) related pathways, including BMI polygenic risk scores (PRS); and (ii) Cox regression models to assess whether reduction of overweight between 7years and 31years influence T2D, depression and/or comorbidity. The models were tested for covariation with sex, education, smoking, physical activity, and diet score.ResultsThe odd ratios (OR) of T2D in individuals with depression was 1.68 [95% confidence interval (CI): 1.34–2.11], and no change in estimate was observed when adjusted for covariates. T2D and comorbidity showed similar patterns of relationships in the path analyses (P < 0.001). The genetic risk for obesity (PRS BMI) did not show direct effect on T2D or comorbidity in adulthood but indirectly through measures of adiposity in early childhood and mid-adulthood in the path analysis (P < 0.001). Having early-onset of overweight at 7years and 31years showed highest risk of T2D (OR 3.8, 95%CI 2.4–6.1) and comorbidity (OR 5.0, 95%CI 2.7–9.5), with mild-to-moderate attenuation with adjustments. Depression showed no significant associations.ConclusionsWe found evidence for overweight since childhood as a risk factor for T2D and co-morbidity between T2D and depression, influenced moderately by lifestyle factors in later life. However, no shared early life adiposity related risk factors were observed between T2D and depression when assessed independently in this Finnish setting.

Children's biological age does not always correspond to their chronological age. In the case of BMI trajectories, this can appear as phase variation, which can be seen as shift, stretch, or shrinking between trajectories. With maturation thought of as a process moving towards the final state - adult BMI, we assessed whether children can be divided into latent groups reflecting similar maturational age of BMI. The groups were characterised by early factors and time-related features of the trajectories. We used data from two general population birth cohort studies, Northern Finland Birth Cohorts 1966 and 1986 (NFBC1966 and NFBC1986). Height (n = 6329) and weight (n = 6568) measurements were interpolated in 34 shared time points using B-splines, and BMI values were calculated between 3 months to 16 years. Pairwise phase distances of 2999 females and 3163 males were used as a similarity measure in k-medoids clustering. We identified three clusters of trajectories in females and males (Type 1: females, n = 1566, males, n = 1669; Type 2: females, n = 1028, males, n = 973; Type 3: females, n = 405, males, n = 521). Similar distinct timing patterns were identified in males and females. The clusters did not differ by sex, or early growth determinants studied. Trajectory cluster Type 1 reflected to the shape of what is typically illustrated as the childhood BMI trajectory in literature. However, the other two have not been identified previously. Type 2 pattern was more common in the NFBC1966 suggesting a generational shift in BMI maturational patterns.

Rising public concern about comprehensive child and adolescent well-being has led to the development of school-based interventions with the potential for high-reaching and effective support. While some interventions have shown effectiveness, limited understanding exists regarding how social inequalities are considered and evidenced in such interventions. This study examines how social inequalities are considered in universal school-based interventions and their potential to affect inequalities through differential effects. A systematic review following the PRISMA protocol was conducted using the following databases: PubMed, Web of Science, CINAHL, Scopus, ProQuest and APA PsycArticles. Studies published between 2014 and 2023 were included. Screening and data extraction were conducted independently by two researchers. Of 10 028 initial articles, 44 were included in the final analysis. These studies primarily involved physical activity and mindfulness interventions in schools. Despite many studies including information regarding students' social backgrounds, such as socioeconomic position and immigrant background, the analysis of differential intervention effects among demographic groups was limited and mostly based on sex. Most differential effect analyses showed no significant differences based on social background, and no clear differences were found based on intervention type. While some universal school-based interventions show promise in reducing social inequalities in students' well-being, more empirical research is needed to explicitly target these questions. This review highlights the critical need for comprehensive intervention studies to consider and report relevant dimensions of social background and their interactions with intervention effects. PROSPERO; registration no. CRD42023423448.

BackgroundA body of literature suggests a metabolically healthy phenotype in individuals with obesity. Despite important clinical implications, the early origins of metabolically healthy obesity (MHO) have received little attention.ObjectiveTo assess the prevalence of MHO among the Northern Finland Birth Cohort 1966 (NFBC1966) at 31 years of age, examine its determinants in early life taking into account the sex specificity.MethodsWe studied 3205 term-born cohort participants with data available for cardio-metabolic health outcomes at 31 years, and longitudinal height and weight data. After stratifying the population by sex, adult BMI and a strict definition of metabolic health (i.e., no risk factors meaning metabolic health), we obtained six groups. Repeated childhood height and weight measures were used to model early growth and early adiposity phenotypes. We employed marginal means adjusted for mother and child covariates including socio-economic status, birth weight and gestational-age, to compare differences between the groups.ResultsThe prevalence of adult MHO was 6% in men and 13.5% in women. Differences in adult metabolic status were linked to alterations in BMI and age at adiposity peak in infancy (p < 0.0003 in men and p = 0.027 in women), and BMI and age at adiposity rebound (AR) (p < 0.0001 irrespective of sex). Compared to MHO, metabolically unhealthy obese (MUO) women were five and a half months younger at AR (p = 0.007) with a higher BMI while MUO men were four months older (p = 0.036) with no difference in BMI at AR.ConclusionAt the time of AR, MHO women appeared to be older than their MUO counterparts while MHO men were younger. These original results support potential risk factors at the time of adiposity rebound linked to metabolic health in adulthood. These variations by sex warrant independent replication.

The steady rise in overweight and obesity in Europe disproportionately affects people and communities with a lower socio-economic position (SEP). Many obesity prevention approaches exist, but these have had limited reach and unsatisfactory effects thus far, especially in low-SEP populations. In this context, there is a need for implementation of effective individual-level and population-based preventive strategies that also tackle health inequalities. Effective strategies require consideration of the complex and cross-domain obesity risk factors across the life course. Feasible and acceptable strategies require multisectoral collaborations and innovative approaches, including a whole-of community and systems perspective. With the Horizon Europe-funded OBCT project, we aim to quantify the relative contribution of biological, socio-cultural and built environment factors to obesity and the interactions of these risks within and across various life course stages; and translate the resulting knowledge into practical, equitable, and effective tools for action. These tools will include: a comprehensive obesity risk screener; a map of the obesogenicity of neighbourhood environments as well as trends in obesity prevalence of each European country; recommendations for lifestyle behaviours (diet, physical activity, sedentary behaviours) to prevent obesity during key life transition stages; a decision support dashboard for policy makers; and co-developed toolboxes to support implementation of policy recommendations in low-SEP communities. OBCT's outputs will highlight the areas and domains in which obesity should be targeted and will empower the research community, policymakers, health professionals and residents in Europe to adapt and implement strategies to effectively reduce obesity risk, particularly in low-SEP communities.