High exposure to unemployment may predispose to type 2 diabetes in middle-aged men. For clinicians, awareness of the patient's unemployment status may be helpful in recognizing undiagnosed cases.

Objectives Type 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. Methods We 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. Results The 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. Conclusions We 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.

Background/objective: Children 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/Methods: We designed a cross-cohort study including 12,040 Finnish children from the Northern Finland Birth Cohorts 1966 and 1986 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. Results:We 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 earlyincrease group were 1.

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STUDY QUESTION What is the association between childhood and adolescent BMI and reproductive capacity in women? SUMMARY ANSWER Adolescent girls with obesity had an increased risk of infertility and childlessness in adulthood independently of their marital status or the presence of polycystic ovary syndrome (PCOS). WHAT IS KNOWN ALREADY Girls with obesity (BMI (kg/m2)&gt;95th percentile) more often exhibit menstrual irregularities and infertility problems as compared to those with normal weight, and premenarcheal girls with obesity have an increased risk of childlessness and infertility in adulthood. Follow-up studies on the relation between childhood and adolescence growth patterns and fertility or parity throughout the reproductive life span are limited. STUDY DESIGN, SIZE, DURATION A prospective, population-based cohort study (the Northern Finland birth cohort 1966) was performed with 5889 women born in 1966 and followed from birth to age 50 years. Postal questionnaires at ages 31 and 46 years addressed questions on reproductive capacity evaluated by decreased fecundability, need for infertility assessment and treatment by 46 years of age. Childlessness and number of children by age 50 years were recovered from registers. Women who did not report ever having attempted to achieve pregnancy (n = 1507) were excluded. The final study population included 4382 women who attempted to achieve pregnancy before age 46 years. PARTICIPANTS/MATERIALS, SETTING, METHODS Data on BMI were collected by trained personnel at all stages. We assessed association with both prospectively measured BMI at various time points and with early adiposity phenotypes derived from linear mixed models including the timing and the BMI at adiposity peak (AP) and adiposity rebound (AR). Self-reported infertility assessments and treatments were assessed at ages 31 and 46 years. Data on deliveries were collected from the national birth register. Decreased fecundability was defined at age 31 years as time to achieve pregnancy over 12 months. Logistic regression analyses were conducted with adjustments for marital status, education level and smoking at age 31 years. Women with PCOS were excluded from stratification-based sensitivity analyses. Obesity at a specific age group was defined by having at least one BMI value above the 95th percentile during the related period. MAIN RESULTS AND THE ROLE OF CHANCE BMI at the age of AR (5–7 years) was not associated with fertility outcomes after adjustments, but girls with AR &lt;5.1 years had a higher risk of remaining childless compared to girls with AR over 5.1 years (adjusted odds ratio (OR): 1.45 (1.10–1.92)). At ages 7–10 and 11–15 years, obesity was associated with decreased fecundability (adjusted OR 2.05 (1.26–3.35) and 2.04 (1.21–3.44), respectively) and a lower number of children. At age 11–15 years, both overweight and obesity were associated with a higher risk of childlessness (adjusted OR 1.56 (1.06–2.27), 1.77 (1.02–3.07), respectively), even after excluding women with PCOS. Underweight at age 11–15 years was associated with an increased risk for infertility treatment (adjusted OR 1.55 (1.02–2.36)) and a tendency for an increased risk for infertility assessment (adjusted OR 1.43 (0.97–2.10)) after excluding women with PCOS. LIMITATIONS, REASON FOR CAUTION Despite a high participation rate throughout the follow-up, some growth data for children over the different age groups were missing. Infertility outcomes were self-reported. A potential over-diagnosis of obesity may have reduced the significance of the association between childhood obesity and fertility outcomes, and the diagnosis of PCOS was self-reported. WIDER IMPLICATIONS OF THE FINDINGS This study supports previous results showing that girls with obesity in late childhood and in adolescence displayed reduced fertility and an increased risk of remaining childless in adulthood, independently of marital history and PCOS in adulthood. These findings corroborate the body of evidence for a causal relation between early adiposity and the reproductive functions in women. We recommend reinforcing the prevention of obesity in school-age girls to reduce the risk of impaired reproductive functions. STUDY FUNDING/COMPETING INTEREST(S) NFBC1966 received financial support from University of Oulu Grant no. 65354, Oulu University Hospital Grant no. 2/97, 8/97, Ministry of Health and Social Affairs Grant no. 23/251/97, 160/97, 190/97, National Institute for Health and Welfare, Helsinki Grant no. 54121, Regional Institute of Occupational Health, Oulu, Finland Grant no. 50621, 54231. The Finnish Medical Foundation, the North Ostrobothnia Regional Fund, the Academy of Finland (project grants 315921, 104781, 120315, 129269, 1114194, 24300796), Center of Excellence in Complex Disease Genetics and SALVE, the Sigrid Juselius Foundation, Biocenter Oulu, University Hospital Oulu and University of Oulu (75617), Jalmari ja Rauha Ahokkaan säätiö, The Finnish Medical Foundation, Medical Research Center Oulu, National Institute for Health Research (UK). M. R. J., S. S. and R. N. received funding by the Academy of Finland (#268336) and the European Union’s Horizon 2020 research and innovation program (under Grant agreement no. 633595 for the DynaHEALTH action and GA 733206 for LifeCycle). The funders had no role in study design, in the collection, analysis and interpretation of the data, in the writing of the article and in the decision to submit it for publication. The authors have no conflict of interest to disclose. TRIAL REGISTRATION NUMBER N/A.

Background: Cardiovascular diseases may originate in childhood. Biomarkers identifying individuals with increased risk for disease are needed to support early detection and to optimise prevention strategies. Methods: In this prospective study, by applying a machine learning to high throughput NMR-based metabolomics data, we identified circulating childhood metabolic predictors of adult cardiovascular disease risk (MetS score) in a cohort of 396 females, followed from childhood (mean age 11¢2 years) to early adulthood (mean age 18¢1 years). The results obtained from the discovery cohort were validated in a large longitudinal birth cohort of females and males followed from puberty to adulthood (n = 2664) and in four cross-sectional data sets (n = 6341). Findings: The identified childhood metabolic signature included three circulating biomarkers, glycoprotein acetyls (GlycA), large high-density lipoprotein phospholipids (L-HDL-PL), and the ratio of apolipoprotein B to apolipoprotein A-1 (ApoB/ApoA) that were associated with increased cardio-metabolic risk in early adulthood (AUC = 0¢641-0¢802, all p<0¢01). These associations were confirmed in all validation cohorts with similar effect estimates both in females (AUC = 0¢667-0¢905, all p<0¢01) and males (AUC = 0¢734-0¢889, all p<0¢01) as well as in elderly patients with and without type 2 diabetes (AUC = 0¢517-0¢700, all p<0¢01). We subsequently applied random intercept cross-lagged panel model analysis, which suggested bidirectional causal relationship between metabolic biomarkers and cardio-metabolic risk score from childhood to early adulthood. Interpretation: These results provide evidence for the utility of a circulating metabolomics panel to identify children and adolescents at risk for future cardiovascular disease, to whom preventive measures and followup could be indicated.

At 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.

Objective: We investigated the association between changes in weight status from childhood through adulthood and subsequent type 2 diabetes risks and whether educational attainment, smoking and leisure time physical activity (LTPA) modify this association. Research design and methods: Using data from 10 Danish and Finnish cohorts including 25,283 individuals, childhood body mass index (BMI) at 7 and 12 years was categorised as normal or high using age-and sex-specific cutoffs (