Developmental Origins ofHEALTH AND DISEASE9th WORLD CONGRESS CAPE TOWN, SOUTH AFRICA 9 NOVEMBER 2015

Sunday saw an enthusiastic crowd convene here at the CTICC to attend a number of satellite workshops to kick-start the 9th DOHaD World Congress. The topics presented promised to explore various aspects of the DOHaD hypothesis and did not disappoint. Each of the sessions was well represented by experts in the field ensuring top-notch presentations and discussions. The day culminated in the welcoming session where Shane Norris extended a hearty welcome to all delegates, members, and guests and welcomed a number of distinguished speakers to the stage for opening remarks. Among those to grace stage were Mark Hanson, Caroline Fall, Matthew Gilman, Matthew Kemp and Francisco Mardones. Formalities were followed by cheese, wine, and a marimba band, which truly set the festivities in full swing.

Please browse through the pages of this copy for a summary of the various topics and speakers that formed part of the highlights of day 1. Keep an eye out for the DOHaD news every morning to keep you up to date about any changes, announcements and of course highlights from the previous days proceedings.Please take special note of the Notice section in the right -hand banner of this page for important information.

Welcome to DOHaD 2015!

9th WORLD CONGRESS CAPE TOWN, SOUTH AFRICA 9 NOVEMBER 2015

NOTICES- Please note that there are afew changes to theprogramme. The most up todate version of theprogramme is the Wall Banner,situatenear main registraition.

- For those partaking in theoral-poster presentationsplease ensure your posters areset-up in the tea breakpreceding your presentation.

- For the oral-posterpresentations please also notethat you should be present forthe entire duration of thesession in which you arepresenting.

- There are 3 SpecialEvents Sessions between 18:00and 19:00 this evening.

- Don't forget the CocktailFunction this evening at 19:00

Proudly brought to you by DOHaD rapporteurs:

Asanda Mtintsilana Ntabozuko Dwane Martha Ngobeni Rihlat Said MohamedAlessandra Prioreschi Lukhanyo Nyati Refiloe Cele Stephaine WrottesleyRichard Manthuli Juliana Kagura Mercy Manyema Cynthia lamperSara Nieuwoudt Lynnsay Dickson Moji Musa Doug Momberg

DOHaD, Environment and Sexual DimorphismChaired by Karin Michels, this session sought to explore an emerging hypothesis of the DOHaD concept. The likelihood that the effects of environmental stressors result in sex-related differences in target organs, particularly in the placenta, sculpting its epigenomes, and hence the epigenomes of the developing fetus. The placenta plays a critical role in fetal growth and development and therefore affects the fetal programming underlying subsequent sex-specific adult health and disease. Prenatal insults, such as poor diet, alcohol consumption or stress in the mother is translated to the fetus via the placenta. In studies using animal models, it was concluded that both male and female offspring exposed to glucocorticoids in utero exhibited a 25% reduction in kidney nephron numbers, a 10mmHg rise in blood pressure. Sexual differences were seen in kidney function with male offspring having a faster progression towards high glomerular filtration rate and an altered kidney function. In utero alcohol exposure also mediated sex-related differences in glucose metabolism with males showing a worse insulin and glucose profile than the female offspring.Another common environmental endocrine disruptor, bisphenol A (BPA), which is an organic compound used in the making of plastic kitchenware, was also suggested to alter glucose metabolism during pregnancy. BPA-exposed mice were characterized by increased body weight, adiposity, and decreased pancreatic beta cell mass and function several months postpartum. In light of this finding questions were raised as to whether BPA could be considered as a novel risk factor for the increased occurrence of diabetes during and after pregnancy in humans.Phthalates were portrayed in a similar light to BPA in an epidemiological study which suggested that maternal exposure to this compound results in the altered gene expression at the placental level which may result in altered genital as well as neurocognitive development and behaviour. In terms of health, the beneficial effect of sex specific developmental programming of physical activity was reported and it was suggested that increased physical activity around conception and during pregnancy was associated with an increased physical activity in female, but not male offspring.Details of underlying mechanisms governing sexual dimorphism within the DOHAD concept still remains unclear. More work is still required to decipher the exact steps in which the prenatal exposures result in divergent consequences between sexes.

The Preterm Infant

Leading this session was the dynamic duo of Shane Norris and Stephen Kennedy. The group from Oxford, led by Stephen Kennedy, drew delegates' attention to the plight of preterm birth. Preterm birth is one of the main causes of morbidity and mortality in maternal and child health, with approximately 15 million preterm births per year globally. Of the ten countries with the highest preterm birth rates, eight of these are n the African continent.WHO growth standards are a globally utilised tool for assessing sub-optimal growth within and between populations. However, they do not cover growth in-utero, which may have a significant impact on growth trajectories in the post-natal period. Although many growth reference charts exist, these are usually based on local data and are not prescriptive. These gaps in currently available growth standards and prenatal reference data were the motivation behind the INTERGROWTH-21st study, which aimed to: provide international prescriptive standards to measure: gestational age, fetal growth, new born size for gestational age and postnatal growth for preterm infants across 8 sites (USA, UK, Brazil, Kenya, Oman, Italy, China and India). Of the 53 871 healthy, well-nourished pregnant women with accurate gestational age determined in the study, approximately 10.8% had preterm births (births >16 weeks and <37 weeks gestation). These were included in a secondary study aimed at identifying new phenotypic classing of preterm birth and fetal growth restriction syndromes. The main findings were that:- Preterm infants are a heterogeneous group characterised by multiple phenotypes with varied underlying causes and neonataloutcomes- The most prevalent phenotype contributing to preterm birth was: no obvious maternal, fetal or placental conditions detected (i.e. the causewas unknown)- Although this phenotype was the most common, it was associated with the best neonatal outcomes (highest birth weight and birth length, aswell as the lowest neonatal mortality rate)- Deeper neonatal phenotyping and therefore functional characterisation of the new born (beyond low birth weight/preterm birth)provides usefulclinically relevant information for targeting interventions- Use of standardised methods across study sites, provides comparable data for fetal and newborn growth and therefore a nationally relevantstandard for characterisation and diagnosis of sub-optimal growth globally.This was further buttressed by Chrystelle Wedi who pointed out that ART naive maternal HIV infection is associated with increased risk ofpreterm birth, as well as low birth weight, small-for-gestational age infants, still birth, term low birth weight and preterm low birth weight.There are no differences in the risk of adverse perinatal outcomes, including preterm birth, between HIV positive women on highlyactive antiretroviral treatment (HAART) and HIV-negative women living in Soweto, Johannesburg. However, women who are initiated onHAART prior to conception have an increased risk of adverse outcomes than those who are initiated antenatally.

9th WORLD CONGRESS CAPE TOWN SOUTH AFRICA 9 NOVEMBER 2015

Dr Esnat Chirwa, a senior statistician from the MRC, discussed effects and procedures for dealing with missing data in longitudinal cohort studies. There are various reasons why data may be missing in longitudinal studies, and it is important to understand the underlying mechanisms for these missing data, as this will effect the assumptions that can be made. Missing data can be classified as MCAR (missing completely at random), MAR (missing at random) or MNAR (missing not at random), depending on whether the fact that data is missing is related the outcome being measured, or other variables being studied. The effect of missing data will depend on the reason for this missing data, how much information is missing, as well as the distribution of the missing data. Often, missing data will lead to reduced sample sizes, and therefore large standard errors. There are various methods for dealing with missing data, and again these will depend on the assumptions made about the data, proportion and distribution of missing data, the types of variables that are being measures, as well as the research question being examined. Based on this information, researchers can choose to use only complete cases (which may reduce sample size), single or multiple imputation (which preserves sample size but requires good estimates or models for missing data), or available case analysis (which uses previous measurements to estimate values).

Chaired by Linda Adair from the University of North Carolina, this session addressed critical methodological issues facing epidemiological studies. Given the line-up of distinguished speakers, with expertise in statistical modelling, this promised to be an informative session for both the advanced data analyst and novice alike Prof Adair started off with a short presentation, introducing the speakers, methodologists as she called them, and giving context to some of the significant challenges with using statistics to address epidemiological questions. Among several challenges, the chair highlighted the limitation of birthweight as a proxy for intrauterine growth and the use growth in height, which is a “sum total of metabolic pathways”, in association studies. Many studies trying to answer DOHAD questions are limited by available data, which are mostly birth weight and a height at a single time point or several points in longitudinal studies. She advocated for the initiation of data at the preconception period followed by data collection at key development periods taking into account time-varying exposures. The complexity of biological phenomena and the limitation of statistical models to account for the often intertwined pathways were highlighted. Notwithstanding, strides and significant developments have been made in this area. Statistical modelling has advanced our understanding of biological phenomena and the relationship between exposures and outcome. In the words of Cohen “mathematics is biology’s next microscope, only better; biology is mathematics’ next physics, only better” . From latent trajectory and growth mixture models to sitar, conditional regression models and mediation analysis these widely varied statistical techniques all seeking to model biological phenomena were discussed.

Growth Mixture Models – Darren Dahly Most growth modeling techniques look at the mean growth curve of a particular variable but the Latent Growth Class Modeling (LGCM) predicts and group individuals with similar growth pattern in the same curve. It identifies unobserved subpopulations with similar trajectories over time. Latent variables are not directly observed but are rather inferred from other observed variables. It should be noted that: each individual belongs to one class only, each class is described by a different model and class membership of each individual can be estimated, not observed. Mplus version 7.4 software is specifically used to do such analysis. It deals with missing data using missing at random (MAR) assumption. You only need one data point for an individual to be assigned a class.The best way to do such an analysis is to use exploratory approach and check different model fitting criteria to find the optimal number of classes. You need to check posterior probabilities of class membership, close to 1 is the best fit, proportion per class, the AIC, BIC and aBIC values (smaller values means good fit) and other factors.We model latent intercept and latent slopes (linear, quadratic or cubic). These growth parameters can vary within and between latent classes. You can use exact age (time scores) or rounded age when data was collected.Once we have trajectories, the more interesting issue becomes explaining individual differences in trajectories. You can further analysis within Mplus or you can export the classes other statistical software. We can explore factors that drive the class membership and also how these latent classes affect the distal outcome. For instance you can explore how early life factors affect body mass index trajectories, then after how these trajectories associate with blood pressure later in life.One of the major problems is convergence. Sometimes the model does not converge; you can solve this by fixing some growth parameters.

Socio ecological model Katherine MurphyTo kick off the Satellite session, Kathy Murphy provided the group with an overview of socio-ecological models of health behaviour, emphasizing that the effectiveness of health education interventions are often limited if the social, policy and built environments are not supportive. At the formative stage of intervention planning an ecological approach calls for multi-level analysis to identify mechanisms of change at the individual, interpersonal, organizational, community and societal levels. This analysis should guide intervention strategies or mixes, from policy advocacy or social marketing to individual health education. Socio-ecological models can also be applied over the life course. During the session small groups brainstormed successful interventions that have led to large-scale behaviour shifts, e.g. tobacco taxation, which reinforced the value of thinking about change in a way that reflects the complexity within which individuals live and act.

Theories and Styles of Behaviour Change

Longitudinal Data Analysis

Krisela Steyn presented the 'Development of the the Salt Reduction Policy in South Africa'. This started with the vision of PhD student Karen Charlton to reduce the salt intake in foods commonly consumed by poor South Africans. 10 years later, with the efforts of multiple stakeholders, the South African Government declared Regulation R214 (20 March 2013). The salt content of food, including breads and cereals, will be reduced gradually before the year 2020.The success of this campaign was a result of a comprehensive strategy.It started with establishing the basal salt intake in the South African population which was found to be blacks 7.8; Coloured 8.5, Whites 9.5 g/day. This exceeded the WHO recommendation of <5 g/day. A reduction in salt intake would reduce blood pressure by approximately 6 mmHg.The food groups which contributed most to the high salt intake was found to be bread, processed foods (sausages, pies, processed foods), soup powder/stock cubes and margarine. With the assistance of food producers like Sasko Bakery, it was found that consumers did not taste the difference in bread with a lower salt content.The economic impact of reducing salt in bread, margarine, soup mix and seasoning was estimated to result in 7400 fewer deaths due to cardiovascular disease and 4300 fewer non-fatal strokes per annum. This equated to cost savings of R300 million (33 million U.S. Dollars)While 55% of salt intake is from the manufacturing process, 40% is from salt added in cooking and at the table. The dream for salt reduction in SA will also require behavior change in the individual. Many challenges await including mass communication campaigns as well as the implementation, regulation and evaluation of regulation R214.

Clive Osmond emphasizes the need to take into account correlation of variables in longitudinal data analyses by employing conditional variables. He illustrated how conditional variables are created and can be used in statistical analyses testing the mismatch hypotheses. He also highlighted that data cleaning is very crucial before any conditionals are created to ensure attrition is accounted for and to test goodness of fit of the conditional regression analyses. Conditionals are generated by regression of current measure on the prior measurement. Conditional variables can be useful in the forward or backward perceptive.

Tim Cole highlighted the importance of SITAR in growth curve modelling and how time is a biological construct that needs to be accurately captured in longitudinal analyses. He described growth as an increase in size or shape over time. SITAR summarises the growth curve using the mean curve or individual growth patterns with the size (big/small), tempo (early/late) and velocity (fast/slow). Sitar can be used to describe the influence of an intervention or a certain period of growth for example puberty on growth. SITAR is not useful in capturing growth curves over a short period of time, it requires a time span long enough to capture non-linearity of the growth curve.

Early Childhood Development

Bernadette Daelmans, WHO, addressed among other things the action plans for implementing ECD policies, the framework for action and the platforms for delivery. Early child development (ECD) has gained new momentum from the Sustainable Development Goals which recognize the universal importance of ECD in transformation. A global Strategy for Women, Children and Adolescent Health encompassing 17 of the 169 targets in the SDGs was put in place by the WHO in 2010, with the aim of implementing it simultaneously with the SDGs. A multi-sectoral life course approach is needed in implementation. It is also necessary to start the interventions in the first 3 years of childhood and address the inequities found in many countries. To date about 45% of LMICs have national multi sectoral ECD policies though coverage varies widely. Policies that create an enabling environment are important such as paid maternity leave, breastfeeding at work and free preschool education. Platforms for delivery include population-wide interventions, local communities, the health services sector and education. Further research is necessary to asses effective interventions and core indicators for evaluation need to be identified.

Cesar Victora from the Federal University of Pelotas in Brazil presented results from a systematic review and meta-analysis on the impact of breastfeeding on IQ and schooling in children. Overall, breastfed children were more intelligent than non-breastfed children regardless of the duration of breastfeeding. Some studies reviewed reported increases in IQ of over 7 points. Questions arising from this review were whether these gains in IQ would persist into adulthood and if they had any real benefit. A study done using the Pelotas cohort in Brazil helped to answer these questions by investigating the impact of breastfeeding on human capital at 30 years of age. The study showed a 2.5 point increase in IQ with longer breastfeeding. The potential economic impact of gains in IQ is substantial with a 15 point increase in IQ estimated to increase income by 16% in LMICs. If all children were breastfed for at least 6 months there would potentially be a 0.49% increase in global gross national income or US$302 billion per year. It is therefore important to invest in maternal nutrition and support breastfeeding for human capital development.

Dr Stephen Lye of the Fraser Mustard Institute for Human Development, University of Toronto, CanadaEnvironmental factors such as nutrition, socio-economic status and nurturing can alter the genomes that determine the child’s health, body composition and learning ability. The mechanism through which the environment alters genes was illustrated with the following research evidence:• In a trial using mice, it was shown that micethat were restricted in food consumption bore infants thathad high body fat mass and increased levels of glucose(indicating susceptibility to diabetes).• Children born to mothers who hadhypertension during pregnancy had shortened telomereby the age of 17. Telomere shortening is associated withearly ageing.• The father’s genome can affect the child’sgenome based on his body composition and nutrition, ifthe father is obese it contributes the baby’s adiposity,insulin resistance, beta cell dysfunctions in femaleoffspring.• Breast feeding was found to support thedevelopment of good microbiomes in infants which isappropriate for immune function.In conclusion, changes in the epigenetic marking aretransferable up to two generations. Therefore the earlierthe intervention on the environment the better theimprovement in trajectories.

No session concerning ECD would be complete without the presence of Linda Richter, who chaired the session. Pia Rebello Britto: Fascinating science, what does it mean in terms of Early Childhood Development (EDC). The importance and advancement of ECD forms part of a global agenda. It’s a historical moment for ECD because for the first time it is part of the 2030 Sustainable Development Agenda. ECD is the foundation of all 17 Sustainable Development goals, such as no poverty, good health, quality education, reduced inequality, peace and justice. Delivery platforms such as the community, schools, clinics and the media are critical for these interventions. Synergetic impact of these interventions effect can be greater. In conclusion, she quoted UNICEF executive director Mr Anthony Lake, “What we are learning should ignite a revolution in how we think about and act on early childhood development”. What we are learning should start moving us forward.

According to Wendy Lawrence healthy conversational skills are essential in finding solutions to health problems or challenges faced by the patients. During the satellite workshop various activities were conducted to highlight the importance of healthy conversation skills in implementing behavioural changes. Health practitioners or workers are encouraged to be more interactive with the patients by asking open discovery questions (i.e. what and how?), to listen to the patients and show empathy in order to “explore” the patient’s world. This approach is believed to be more effective than using closed questions (i.e. why?) that provide little information (or no solutions) to the challenges experienced by the patients. Furthermore, health practitioners or workers are advised to be less judgmental or interrogative, to stop making assumptions and stop telling patients what to do!!! Therefore, your approach determines if the patient opens up or not and this in turn determines if you can implement change or not.