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Background Poor diet and lack of physical activity are strongly linked to non-communicable disease risk, but modifying them is challenging. There is increasing recognition that adolescence is an important time to intervene; habits formed during this period tend to last, and physical and psychological changes during adolescence make it an important time to help individuals form healthier habits. Improving adolescents’ health behaviours is important not only for their own health now and in adulthood, but also for the health of any future children. Building on LifeLab—an existing, purpose-built educational facility at the University of Southampton—we have developed a multi-component intervention for secondary school students called Engaging Adolescents in Changing Behaviour (EACH-B) that aims to motivate and support adolescents to eat better and be more physically active. Methods A cluster randomised controlled trial is being conducted to evaluate the effectiveness of the EACH-B intervention. The primary outcomes of the intervention are self-reported dietary quality and objectively measured physical activity (PA) levels, both assessed at baseline and at 12-month follow-up. The EACH-B intervention consists of three linked elements: professional development for teachers including training in communication skills to support health behaviour change; the LifeLab educational module comprising in-school teaching of nine science lessons linked to the English National Curriculum and a practical day visit to the LifeLab facility; and a personalised digital intervention that involves social support and game features that promote eating better and being more active. Both the taught module and the LifeLab day are designed with a focus on the science behind the messages about positive health behaviours, such as diet and PA, for the adolescents now, in adulthood and their future offspring, with the aim of promoting personal plans for change. The EACH-B research trial aims to recruit approximately 2300 secondary school students aged 12–13 years from 50 schools (the clusters) from Hampshire and neighbouring counties. Participating schools will be randomised to either the control or intervention arm. The intervention will be run during two academic years, with continual recruitment of schools throughout the school year until the sample size is reached. The schools allocated to the control arm will receive normal schooling but will be offered the intervention after data collection for the trial is complete. An economic model will be developed to assess the cost-effectiveness of the EACH-B intervention compared with usual schooling. Discussion Adolescents’ health needs are often ignored and they can be difficult to engage in behaviour change. Building a cheap, sustainable way of engaging them in making healthier choices will benefit their long-term health and that of their future children. Trial registration ISRCTN 74109264. Registered on 30 August 2019. EACH-B is a cluster randomised controlled trial, funded by the National Institute for Health Research (RP-PG-0216-20004).

Objectives To (1) describe micronutrient intakes among women of reproductive age living in Mumbai slums; (2) assess the adequacy of these intakes compared with reference values; (3) identify important dietary sources of micronutrients. Subjects/methods Participants were 6426 non-pregnant women aged 16–39 years, registered in a randomised controlled trial of a food-based intervention set in the Bandra, Khar and Andheri areas of Mumbai, India. Cross-sectional quantified food frequency questionnaire (FFQ) data were collected. Vitamin (n = 9) and mineral (n = 6) intakes were calculated and analysed in relation to dietary reference values (DRVs). Important dietary sources were identified for each micronutrient. Results Median intakes of all micronutrients, except vitamin E, were below the FAO/WHO reference nutrient intake (RNI). Intakes of calcium, iron, vitamin A and folate were furthest from the RNI. For seven of the micronutrients, over half of the women had intakes below the lower reference nutrient intake (LRNI); this figure was over 75% for calcium and riboflavin. The majority of women (93%) had intakes below the EAR for 5 or more micronutrients, and 64% for 10 or more. Adolescents had lower intakes than women aged >19 years. Less than 1% of adult women and no adolescents met the EAR for all micronutrients. Animal source foods and micronutrient-rich fruit and vegetables were consumed infrequently. Conclusions These women had low intakes of multiple micronutrients, increasing their risk of insufficiency. There is a need to determine the factors causing poor intakes, to direct interventions that improve diet quality and nutritional sufficiency.

Background: studies since the early 1990s have shown that birth size can be a predictor of the development of Type 2 diabetes mellitus (T2DM). In the present study, we evaluated changes in the strength of associations between T2DM and birth size and maternal weight with age. Methods: in 1993–1994 (t0), 509 men and women (mean age 46 years) who had been born in Holdsworth Memorial Hospital were screened for diabetes, with increased diabetes risk identified in those who were shorter at birth and those born to heavier mothers. Ten years later (t10), the screening was repeated in 266 subjects who were non-diabetic at t0 (70% of survivors). Results: at t10, 56 new cases of diabetes were found. The incidence of diabetes decreased with increasing birth length (odds ratio (OR) = 0.90, 95% confidence interval (CI) 0.84–0.97/cm birth length; P = 0.006) after adjustment for sex, age, socioeconomic status, family history, and current body mass index. Overall, there were no significant differences in OR for the association between birth length and diabetes at t0 compared with t10, but limiting analysis to subjects with normal glucose tolerance at t0 resulted in a stronger association at t10 (OR = 0.71, 95% CI 0.58–0.87) than at t0 (OR = 0.95, 95% CI 0.86–1.05; P = 0.015 for the difference). There was a positive correlation between maternal weight and incident disease at t0 (OR = 1.08, 95% CI 1.03–1.14; P = 0.001), but not at t10 (OR = 0.98/kg, 95% CI 0.92–1.05; P = 0.6; P = 0.02 for the difference). Conclusions: short birth length remains a risk factor for diabetes. Changes in the effects of birth length and maternal weight on diabetes risk with age may indicate different causal pathways. These findings require replication in studies with more accurate dating of the onset of diabetes

The association between lower birthweight and metabolic syndrome may result from fetal undernutrition (fetal programming hypothesis) and/or genes causing both low birthweight and insulin resistance (fetal insulin hypothesis). We studied associations between the birthweight of parents and metabolic syndrome in the offspring.We identified men and women (aged 35-68 years), who had been born in Holdsworth Memorial Hospital, Mysore, India. We also identified the offspring (20-46 years) of these men and women. In total, 283 offspring of 193 mothers and 223 offspring of 144 fathers were studied. Investigations included anthropometry, oral glucose tolerance, plasma insulin and lipid concentrations and blood pressure. The metabolic syndrome was defined using WHO criteria.Among the offspring, lower birthweight was associated with an increased risk of glucose intolerance (impaired glucose tolerance, impaired fasting glucose or type 2 diabetes) and higher cholesterol and triacylglycerol concentrations (p0.05 for all adjusted for sex and age). Most outcomes in the offspring, including most individual components of the metabolic syndrome, were unrelated to parental birthweight. However, both maternal and paternal birthweight were inversely related to offspring metabolic syndrome (odds ratio [OR] 0.36 [95% CI: 0.13-1.01] per kg, p = 0.053 for mother-offspring pairs; OR 0.26 [0.07-0.93], p = 0.04 for father-offspring pairs, adjusted for offspring age, sex, BMI and socioeconomic status). Maternal birthweight was inversely related to offspring systolic blood pressure (beta = -2.5 mmHg [-5.00 to 0.03] per kg maternal birthweight; p = 0.052).Factors in both parents may influence the risk of metabolic syndrome in their offspring. There are several possible explanations, but the findings are consistent with the fetal insulin (genetic) hypothesis.