Engaging adolescents in changing behaviour (EACH-B): a study protocol for a cluster randomised controlled trial to improve dietary quality and physical activity.

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).

Predicting the risk of childhood overweight and obesity at 4-5 years using population-level pregnancy and early-life healthcare data.

BACKGROUND: Nearly a third of children in the UK are overweight, with the prevalence in the most deprived areas more than twice that in the least deprived. The aim was to develop a risk identification model for childhood overweight/obesity applied during pregnancy and early life using routinely collected population-level healthcare data. METHODS: A population-based anonymised linked cohort of maternal antenatal records (January 2003 to September 2013) and birth/early-life data for their children with linked body mass index (BMI) measurements at 4-5 years (n = 29,060 children) in Hampshire, UK was used. Childhood age- and sex-adjusted BMI at 4-5 years, measured between September 2007 and November 2018, using a clinical cut-off of ≥ 91st centile for overweight/obesity. Logistic regression models together with multivariable fractional polynomials were used to select model predictors and to identify transformations of continuous predictors that best predict the outcome. RESULTS: Fifteen percent of children had a BMI ≥ 91st centile. Models were developed in stages, incorporating data collected at first antenatal booking appointment, later pregnancy/birth, and early-life predictors (1 and 2 years). The area under the curve (AUC) was lowest (0.64) for the model only incorporating maternal predictors from early pregnancy and highest for the model incorporating all factors up to weight at 2 years for predicting outcome at 4-5 years (0.83). The models were well calibrated. The prediction models identify 21% (at booking) to 24% (at ~ 2 years) of children as being at high risk of overweight or obese by the age of 4-5 years (as defined by a ≥ 20% risk score). Early pregnancy predictors included maternal BMI, smoking status, maternal age, and ethnicity. Early-life predictors included birthweight, baby's sex, and weight at 1 or 2 years of age. CONCLUSIONS: Although predictive ability was lower for the early pregnancy models, maternal predictors remained consistent across the models; thus, high-risk groups could be identified at an early stage with more precise estimation as the child grows. A tool based on these models can be used to quantify clustering of risk for childhood obesity as early as the first trimester of pregnancy, and can strengthen the long-term preventive element of antenatal and early years care.

Are environmental area characteristics at birth associated with overweight and obesity in school-aged children? Findings from the SLOPE (Studying Lifecourse Obesity PrEdictors) population-based cohort in the south of England.

BACKGROUND: Geographical inequalities in overweight and obesity prevalence among children are well established in cross-sectional research. We aimed to examine how environmental area characteristics at birth are related to these outcomes in childhood. METHODS: Anonymised antenatal and birth data recorded by University Hospital Southampton linked to school-measured weight and height data for children within Southampton, UK, were utilised (14,084 children at ages 4-5 and 5637 at ages 10-11). Children's home address at birth was analysed at the Lower and Middle layer Super Output Area (LSOA/MSOA) levels (areas with average populations of 1500 and 7000, respectively). Area-level indices (walkability, relative density of unhealthy food outlets, spaces for social interaction), natural greenspace coverage, supermarket density and measures of air pollution (PM2.5, PM10 and NOx) were constructed using ArcGIS Network Analyst. Overweight/obesity was defined as a body mass index (BMI; kg/m2) greater than the 85th centile for sex and age. Population-average generalised estimating equations estimated the risk of being overweight/obese for children at both time points. Confounders included maternal BMI and smoking in early pregnancy, education, ethnicity and parity. We also examined associations for a subgroup of children who moved residence between birth and outcome measurement. RESULTS: There were mixed results between area characteristics at birth and overweight/obesity at later ages. MSOA relative density of unhealthy food outlets and PM10 were positively associated with overweight/obesity, but not among children who moved. LSOA greenspace coverage was negatively associated with the risk of being overweight/obese at ages 10-11 in all children (relative risk ratio 0.997, 95% confidence interval 0.995-0.999, p = 0.02) and among children who moved. CONCLUSIONS: Local access to natural greenspaces at the time of birth was inversely associated with becoming overweight or obese by age 10-11, regardless of migration. Increased access/protection of greenspace may have a role in the early prevention of childhood obesity.

Are socioeconomic inequalities in the incidence of small-for-gestational-age birth narrowing? Findings from a population-based cohort in the South of England.

OBJECTIVES: To investigate socioeconomic inequalities, using maternal educational attainment, maternal and partner employment status, and lone motherhood indicators, in the risk of small-for-gestational-age (SGA) births, their time trend, potential mediation by maternal smoking and body mass index, and effect modification by parity. DESIGN: Population-based birth cohort using routine antenatal healthcare data. SETTING: Babies born at University Hospital Southampton, UK, between 2004 and 2016. PARTICIPANTS: 65 909 singleton live births born to mothers aged ≥18 years between 24-week and 42-week gestation. MAIN OUTCOME MEASURES: SGA (birth weight <10th percentile for others born at the same number of completed weeks compared with 2013/2014 within England and Wales). RESULTS: Babies born to mothers educated up to secondary school level (adjusted OR (aOR) 1.32, 99% CI 1.19 to 1.47), who were unemployed (aOR 1.27, 99% CI 1.16 to 1.38) or with unemployed partners (aOR 1.27, 99% CI 1.13 to 1.43), were at greater risk of being SGA. There was no statistically significant change in the magnitude of this risk difference by these indicators over time between 2004 and 2016, as estimated by linear interactions with year of birth. Babies born to lone mothers were not at higher risk compared with partnered mothers after adjusting for maternal smoking (aOR 1.05, 99% CI 0.93 to 1.20). The inverse association between maternal educational attainment and SGA risk appeared greater in multiparous (aOR 1.40, 99% CI 1.10 to 1.77) compared with primiparous women (aOR 1.28, 99% CI 1.12 to 1.47), and the reverse was true for maternal and partner's unemployment where the association was stronger in primiparous women. CONCLUSIONS: Socioeconomic inequalities in SGA risk by educational attainment and employment status are not narrowing over time, with differences in association strength by parity. The greater SGA risk in lone mothers was potentially explained by maternal smoking. Preventive interventions should target socially disadvantaged women, including preconception and postpartum smoking cessation to reduce SGA risk.