Proposal summaries
B814 - Children born prematurely compared to children born full term in terms of contrast sensitivity contour interaction and circle deformation visual acuity stereoscopic vision and accommodation at age seven data from the ALSP - 23/04/2009
(No outline received).
B812 - The Geography of Fast Food and Childhood Obesity - 23/04/2009
Background
Obesity in children, and adults, is a rapidly growing problem in the UK and worldwide and has been increasing at accelerating rates in more recent years. It is associated with a number of co-morbidities in childhood and with increased risk of adult disease, particularly cardiovascular disease, hypertension and type 2 diabetes. Obesity related diseases account for a substantial proportion of costs of health care resources worldwide (WHO, 2004). The Select Committee Report on Obesity (2004) estimated that the total cost of treating obesity in the UK was £3.3-3.7 billion in 2002, increasing to £7 billion by 2020, and the latest estimates (Foresight report, 2007) put it at £45.5 billion by 2050.
A dietary risk factor for obesity is a high consumption of high fat, salt and sugar (HFSS) foods, and in particular "fast foods" (energy dense, nutrient poor, foods) (Reidpath et al, 2002; Mendoza et al, 2007; Procter, 2007a). The popularity of fast foods has increased over recent years and consumption by children has risen 300% over the last twenty years (St-Onge et al, 2003). It has been shown that on days when children eat fast food, then their energy and fat intake is likely to be higher, and fruit and vegetable intake lower, than normal (Bowman et al, 2004). Also children who eat fast food frequently consume more total energy, more energy per gram of food, more total fat, more total carbohydrate, more added sugars, and less fibre, less milk, fewer fruit and vegetables than children who eat fast food infrequently (Bowman et al, 2004; Speiser et al, 2005). Accordingly, it may not be the consumption of fast food, per se, that leads to obesity (as both lean and obese people consume fast food), but the fact that overweight consumers of fast food are less likely to adjust their daily energy intake to take account of an energy dense fast food meal than their lean counterparts (Ebbeling et al, 2004). This "passive over-consumption" is due to the weak innate ability of humans to identify energy dense foods and thus do not correspondingly reduce the amount of food eaten to achieve energy balance (Prentice & Jebb, 2003).
Household income has been shown to be a significant predictor of obesity (inverse relationship) (Strauss & Knight, 1999; Stamatakis et al, 2005), as has deprivation (Kinra et al, 2000; Kinra et al, 2005) and low socio-economic status (SES) (Parsons et al, 1999; Hardy et al, 2000; Okasha et al, 2003; Monden et al, 2006). The increased prevalence of obesity from more deprived backgrounds could be due to a multitude of factors: dietary differences are often apparent; lack of opportunity / funds for activities, so TV viewing is the primary leisure activity by default; constraints on calories per pound, which focuses purchases on energy dense foods. Also the association between SES and obesity may be due to SES acting as a proxy for the effect of multiple adverse circumstances, which are then manifesting as obesity in the long term (Power & Parsons, 2000). For example, it has been shown that there is a higher density of fast food outlets in poorer areas, which may (partially) explain the phenomenon (Reidpath et al, 2002). Obesity and deprivation may be connected due to the routine consumption of a high energy dense, low cost diet (Drewnoski, 2003). Energy dense diets are associated with lower diet quality and lower costs, and vice versa (Cade et al, 1999; Darmon et al 2004; Andrieu et al, 2006; Drewnoski et al, 2007). Research shows that low income households are associated with a high energy dense diet (Mendoza et al, 2006).
There is a large literature contending that the environment, particularly that of our place of residence or school/work, impacts on health related behaviour and therefore health outcomes (Macintyre et al, 2002; Mohan et al, 2005). This increased interest in the effect of place on health seems to stem from the publication of the Black Report some twenty-five years ago (Black et al, 1980). Since then many authors have shown that deprivation is related to mortality as well as to specific health outcomes. An important debate within health geography is that of whether the environment has compositional or contextual effects on health. That is, the issue of whether individual or area effects on health predominate. Accordingly, the compositional school of thought is that individuals have risks of ill health, therefore an area's ill health is reflective of that of the individuals who live (or work, as appropriate) there. For example, do obese people congregate in similar locations? Conversely, the contextual theory is that living (or working) in an area imposes ill health on that area's residents. For example, do certain attributes of places cause its inhabitants to become obese? This study seeks to address the question of fast food and obesity from both contextual (the physical environment of fast food outlets) and compositional (individual consumption) perspectives
Objectives and hypothesis of project
To describe, measure and map obesity, fast food outlet density and fast food consumption in Bristol, UK(and Leeds,UK)
To investigate the relationship between density of outlets and area measures of deprivation, and to examine whether there is a dose-response relationship between deprivation and outlet density (e.g. as deprivation rises, outlet density rises).
To assess the relationship between obesity and energy dense, low nutrient ("fast") foods: availability and consumption.
To consider the policy implications of the results.
Hypothesis: Fast food outlet density and consumption will be related to the patterns of obesity. Families with the lowest incomes will be more influenced by or susceptible to these factors than higher income households.
Methods
Stage 1 - Describing and mapping obesity
The first stage in the study of spatial variations in obesity will be to build a geographic information system (GIS). The GIS will contain all the census data for Bristol/Avon Region at 'output area' (the new small area census unit), as well as the Index of Deprivation (Communities and Local Government, 2004) at 'super output area' level. This will allow us to identify areas of both low and high social deprivation. The GIS will also contain obesity data from the ALSPAC dataset.
Spatial microsimulation modelling will then be used for estimating or predicting small area levels of obesity. Specifically, we will build on the SimObesity model (a deterministic, re-weighting, spatial microsimulation model developed in the School of Geography, University of Leeds), which combines individual micro-data from national level surveys, such as the Health Survey for England (HSE), which only have location data at the scale of large areas, with census statistics for lower Super Output Areas (SOAs) to create synthetic micro-data estimates for SOAs in Leeds. The new, synthesised, micro dataset includes all the attributes from both the survey and the census datasets. The key benefits of using spatial microsimulation are: to add more attributes to the population under analysis by adding census data to the survey data thereby creating a richer dataset; to get data to a smaller geographical scale in order to identify 'hot spots' of problem areas; and it is cheaper and quicker than commissioning a survey of the local area. There is significant experience of spatial microsimulation modelling in the University of Leeds (Clarke, 1996; Ballas et al, 2005; Procter, 2007b).
Significant clusters of obesity (from both children and adults) will be identified using Spatial Scan Statistics (such as SaTScan, Kulldorff, 1997). Temporal (serial cross sectional) as well as geographic analysis will be undertaken.
Stage 2 - Relationship between fast food and obesity
Once the patterns and spatial/temporal variations of obesity have been understood, the next exercise is to consider the relationship with fast food consumption. There are two components to this analysis.
Firstly we wish to examine the relationship between fast food outlet density and obesity. This stage of the project will involve sourcing (e.g. from the council or yellow pages) the location of fast food restaurants in the study area and transposing this data into a GIS. Ground truthing of the data will also be required (i.e. physically checking the locations exist). Then fast food outlet density for output areas can be calculated and the relationship with obesity considered. The association with an area measure of deprivation will also be considered.
The next stage is to take this further, and to consider the relationship between actual fast food consumption and obesity. This Fast Food consumption data regarding diet is available from the ALSPAC cohort and will be added to the previously described GIS model. This data may be used to simulate fastfood consumption in children in other geographical areas using spatial microsimulation modelling.
Analysis of these data will involve the use of multi-level modelling and geographically weighted regression, in order that the special properties of spatial data (e.g. spatial autocorrelation) can be accounted for.
Stage 3 - Policy implications
The final stage in the project will be to consider how the results from the previous two stages can be utilised to influence policy and to help slow down the rising rates of obesity. The spatial microsimulation model will be used to undertake "what if" scenario analysis to theoretically evaluate the potential impact of policy/intervention suggestions on the prevalence of obesity in say 5, 10 or 20 years time, which is cheaper and much quicker than running a pilot study. Further, we will work with key local stakeholders (from both public and private sector, as both have a responsibility to endorse public health (Stafford et al, 2007)) to enable suggestions to be rated for validity, relevance and potential for change. This is important, as small individual programmes are unlikely to make a difference to the obesity epidemic. For maximum benefit an obesity prevention policy needs to take a coordinated, multi-component, multi-sectoral public health approach and overall policy unity and coherence is required, with buy-in of all stakeholders.
How will the research be useful and to whom
This research will be useful to the PCTs for health planning as it will identify any hot spots of problem areas of obesity. It will also elucidate further on the impact of aspects of the environment and diet on obesity and whether these issues can be addressed using public health policies, and if so, the likely future impact of such changes.
Interdisciplinary nature of the research
This project is clearly interdisciplinary. It combines the quantitative geographic techniques (such as spatial microsimulation, GIS) with those from medical research, using data from local studies as well as national cross sectional surveys. Training will be given for use of the spatial techniques (e.g. SimObesity, ArcGIS, geographically weighted regression). There is extensive experience of using these techniques within the University of Leeds, plus some external courses are available.
Timetable
Year 1/2: Develop literature review; gather information for mapping; learn techniques; carry out stage 1
Year 3/4: Carry out stage 2
Year 5/6: Carry out stage 3 and write up thesis
References
Andrieu, E., N. Darmon, et al. (2006). "Low-cost diets: more energy, fewer nutrients." European Journal of Clinical Nutrition 60(3): 434-6.
Black D, Morris J, Smith C, Townsend P (1980). Inequalities in health: report of a Research Working Group. London: Department of Health and Social Security
Bowman SA, Gortmaker SL, Ebbeling CB, Pereira MA, Ludwig DS (2004). Effects of fast-food consumption on energy intake and diet quality among children in a national household survey. Pediatrics, 113: 112-118
Communities and Local Government. The English Indices of Deprivation 2004. http://www.communities.gov.uk/index.asp?id=1128449 Accessed September 2007
Darmon, N., A. Briend, et al. (2004). "Energy-dense diets are associated with lower diet costs: a community study of French adults." Public Health Nutrition 7(1): 21-7.
Drewnowski, A. (2003). "The role of energy density." Lipids 38(2): 109-15.
Drewnowski, A., P. Monsivais, et al. (2007). "Low-energy-density diets are associated with higher diet quality and higher diet costs in French adults." Journal of the American Dietetic Association 107(6): 1028-32.
Ebbeling CB, Sinclair KB, Pereira MA, Garcia-Lago E, Feldman HA, Ludwig DS (2004). Compensation for energy intake from fast food among overweight and lean adolescents. The Journal of the American Medical Association, 291 (23): 2828-2833
Foresight Report (2007). Tackling Obesities: future choices http://www.foresight.gov.uk/Obesity/obesity_final/20.pdf Accessed October 2007
Hardy R, Wadsworth M, Kuh D (2000). The influence of childhood weight and socioeconomic status on change in adult body mass index in a British national birth cohort. International Journal of Obesity, 24 (6): 725-34
Kinra S, Nelder RP, Lewendon GJ (2000). Deprivation and childhood obesity: a cross sectional study of 20,973 children in Plymouth, United Kingdom. Journal of Epidemiology & Community Health, 54 (6): 456-460
Kinra S, Baumer JH, Davey Smith G (2005). Early growth and childhood obesity: a historical cohort study. Archives of Disease in Childhood, 90 (11): 1122-1127
Kulldorff M (1997). A spatial scan statistic. Communications in Statistics: Theory and Methods, 26: 1481-1496
Macintyre S, Ellaway A, Cummins S (2002). Place effects on health: how can we conceptualise, operationalise and measure them? Social Science and Medicine, 55: 125-39
Mendoza, J. A., A. Drewnowski, et al. (2006). "Dietary energy density is associated with selected predictors of obesity in U.S. Children." Journal of Nutrition 136(5): 1318-22.
Mendoza, J. A., A. Drewnowski, et al. (2007). "Dietary energy density is associated with obesity and the metabolic syndrome in U.S. adults." Diabetes Care 30(4): 974-9.
Mohan J, Twigg L, Barnard S, Jones K (2005). Social capital, geography and health: a small-area analysis for England. Social Science and Medicine, 60: 1267-1283
Monden CWS, van Lenthe FJ, Mackenbach JP (2006). A simultaneous analysis of neighbourhood and childhood socio-economic environment with self-assessed health and health-related behaviours. Health and Place, 12(4): 394-403
Okasha M, McCarron P, McEwen J, Durnin J, Davey Smith G (2003). Childhood social class and adulthood obesity: findings from the Glasgow Alumni Cohort. Journal of Epidemiology and Community Health, 57: 508-9
Parsons TJ, Power C, Logan S, Summerbell CD (1999). Childhood predictors of adult obesity: a systematic review. International Journal of Obesity, 23 (Suppl. 8): S1-107
Prentice AM & Jebb SA (2003). Fast foods, energy density and obesity: a possible mechanistic link. Obesity Reviews, 4 (4): 187-194
Reidpath DD, Burns C, Garrard J, Mahoney M, Townsend M (2002). An ecological study of the relationship between social and environmental determinants of obesity. Health and Place, 8: 141-145
Rudolf MCJ, Cole TJ, Krom AJ, Sahota, P, Walker J (1999). Growth of primary school children: a validation of the 1990 standards and their use in growth monitoring. Archives Disease in Childhood 83: 298-301
Rudolf MCJ, Levine R, Feltbower RG, Connor A, Robinson M (2006). The Trends project: development of a methodology to reliably monitor the obesity epidemic in childhood. Archives of Disease in Childhood; 91: 309-311
Select Committee on Health - Third Report (Obesity) (2004). Health Committee Publications, http://www.parliament.thestationeryoffice.co.uk/pa/cm200304/cmselect/cmh... Accessed December 2005
Speiser PW, Rudolf MC, Anhalt H, Camacho-Hubner C, Chiarelli F, Eliakim A, Freemark M, Gruters A, Hershkovitz E, Iughetti L, Krude H, Latzer Y, Lustig RH, Pescovitz OH, Pinhas-Hamiel O, Rogol AD, Shalitin S, Sultan C, Stein D, Vardi P, Werther GA, Zadik Z, Zuckerman-Levin N, Hochberg Z; Obesity Consensus Working Group (2005). Childhood Obesity, The Journal of Clinical Endocrinology and Metabolism, 90 (3):1871-87
Stamatakis E, Primatesta P, Chinn S, Rona R, Falascheti E (2005). Overweight and obesity trends from 1974 to 2003 in English children: what is the role of socioeconomic factors? Archives of Disease in Childhood, 90: 999-1004
St-Onge MP, Keller KL, Heymsfield SB (2003). Changes in childhood food consumption patterns: a cause for concern in light of increasing body weights. The American Journal of Clinical Nutrition, 78 (6): 1068-1073
Strauss RS & Knight J (1999). Influence of the home environment on the development of obesity in children. Pediatrics, 103 (6): e85
World Health Organisation (2004). Report of a WHO Consultation on Obesity: preventing and managing the global epidemic. WHO Technical Report Series; 894. Geneva. http://www.who.int/nutrition/publications/obesity/en/index.html (accessed Oct 2007).
B816 - Foetal and maternal genetic modifiers of the effects of prenatal tobacco exposure - 20/04/2009
1. SUMMARY
Maternal smoking during pregnancy is a well-established and preventable risk factor for low birthweight and its sequelae of poor physical, cognitive and behavioural development, excess morbidity, and increased rates of both perinatal and adult mortality. Preliminary findings from genetic epidemiology studies suggest that the degree to which prenatal tobacco exposure depresses birthweight may be moderated by foetal and maternal genotype. The advent of affordable genomewide genotyping presents an opportunity for systematic investigation of this phenomenon. We propose to prioritize candidate polymorphisms using genomewide genotype data from three studies for which data is available on prenatal tobacco exposure and perinatal outcomes. We will use this information to prioritize approximately 50 single nucleotide polymorphisms (SNPs) to be genotyped in 3,500 mother-child dyads participating in ALSPAC. We will use these data to test hypotheses about the moderating effects of maternal and foetal genotype on the effects of prenatal tobacco exposure to reduce birthweight, shorten gestation, and alter postnatal physical, cognitive, and behavioural development.
2. BACKGROUND
Maternal smoking during pregnancy is a well-established and preventable risk factor for low birthweight (less than 2,500g) and its sequelae of poor physical, cognitive and behavioral development, excess morbidity, and increased rates of both perinatal and adult mortality (Kramer, 2003). The primary causes of low birthweight are preterm birth and intrauterine growth restriction (IUGR). The consequences of IUGR include both short-term and long-term morbidity and permanent deficits in growth and neurocognitive development (Kramer, 2003). Epidemiological studies have shown that maternal smoking is associated with both short gestation and IUGR (Kramer, 2003). Mothers who quit smoking while pregnant have longer gestations and heavier newborns than those who continue to smoke (Lumley, Oliver, Chamberlain, & Oakley, 1998). This fact is recognized in public policy: in the UK, formal smoking cessation programs are recommended as part of antenatal care to prevent low birthweight (Health Development Agency, 2004).
Preliminary findings from studies in genetic epidemiology, including my own research, suggest that the degree to which prenatal tobacco exposure depresses birthweight may be moderated by foetal and maternal genotype (e.g. Infante-Rivard, Weinberg, & Guiguet, 2006, T. S. Price, Grosser, Plomin, & Jaffee, 2008). The combination of affordable experimental methods for high-throughput genotyping and the availability of richly phenotyped birth cohorts for whom information is available on prenatal environmental exposures and perinatal outcomes provides an opportunity for systematic investigation of this phenomenon. I propose to study the issue using a two-phase experimental design. Phase 1 will address the issue broadly, in three large cohorts, by studying the impact on intrauterine growth of all common genetic variation. Phase 2 will address the issue deeply, in an independent sample, by looking at the downstream effects of selected polymorphisms on long-term features of postnatal development.
3. METHODS
3.1 Overview
Phase 1. Genomewide association studies to detect interactions between maternal and child genotype and maternal smoking during pregnancy on intrauterine growth. I have negotiated access to three studies with genomewide genotype data and information on prenatal environmental exposures and perinatal outcomes. Two of these studies are birth cohorts with genomewide genotype information on the children: the Twins Early Development Study (TEDS, PI R. Plomin; Trouton, Spinath, & Plomin, 2002) and the 1966 North Finnish Birth Cohort (NFBC, PI: M.-R. Jarvelin; Rantakallio, 1969). The third has genotype data from parent-child trios and siblings (IMAGE, PI: P. Asherson; Kuntsi, Neale, Chen, Faraone, & Asherson, 2006). In total, these samples comprise more than 9,000 families for whom information will be available on genomewide genotype, environmental risk exposure and perinatal outcomes. Hypotheses of genotype*environment interaction and haplotype*environment interaction will be tested genomewide in each study population. Untyped polymorphisms will be imputed using standard techniques (Marchini, Howie, Myers, McVean, & Donnelly, 2007) to ensure that the genotype set is consistent across studies and facilitate meta-analysis.
Phase 2. Replication and extension. Approximately 50 single nucleotide polymorphisms (SNPs) prioritized in the initial stage - located in the 5 genomic regions providing the best evidence of genotype-environment interaction - will be typed in an independent sample of approximately 3,500 mother-child dyads participating in the Avon Longitudinal Study of Parents and Children (ALSPAC, PI: G. Davey-Smith; Golding, Pembrey, & Jones, 2001). These data will be used to test hypotheses of genotype-environment interaction and haplotype-environment interaction on intrauterine growth and on postnatal phenotypes associated with maternal smoking during pregnancy including Attention-Deficit Hyperactivity Disorder (ADHD), cognitive ability, and height. The availability of prospective information on environmental exposure in this sample will allow hypotheses to be tested about dose-related effects and the impact of timing for mothers who quit smoking during pregnancy.
3.2 Data collection.
We propose to genotype approximately 3,500 mothers and their children participating in the ALSPAC study for approximately 50 single nucleotide polymorphisms prioritized in the first phase of the study. We will choose the 1,500 or so families in which the mother reported smoking throughout the pregnancy, an equal number of families in which the mother reported not smoking at any time during the pregnancy, plus the 500 or so families in which the mother reported smoking early in the pregnancy and subsequently quitting. The intention is to select the five regions providing the best evidence of genotype-environment interaction in phase 1, and fine map the immediate regions of linkage disequilibrium (as defined using resequencing data for Caucasian populations) in ALSPAC so as to be able to test hypotheses of haplotype-environment interaction in phase 2. Although haplotype block length is enormously variable, we anticipate an average of 10 non-redundant SNPs per region will suffice based on estimates of haplotype block length in Caucasian populations (Li & Chen, 2008).
3.3 Existing data required
Concept
Specific Measure
Person
Source
Time Point(s)
Demographic variables (age, sex, ethnicity, marital status, family structure, SES, education, employment, income etc.)
Family
Questionnaire
Antenatal
Pregnancy health variables (nulliparity, pre-eclampsia, IUGR, gestational diabetes etc.)
Mother
Questionnaire, medical records
Antenatal
Parental anthropometrics (height weight)
Mother, Father
Questionnaire
Antenatal
Pregnancy exposure variables (tobacco, alcohol and drug use; chemical exposure; diet; nutrient supplementation; stress; life events; partner cruelty; lack of social support)
Mother
Questionnaire
Antenatal
Birth/delivery variables (weight/length, placental weight, gestational age, Caesarian), perinatal health
Child
Questionnaire, medical records
Birth/perinatal period
Childhood head injury
Child
Questionnaire
Birth - 4 years
Childhood temperament
Carey
Child
Questionnaire
6-24 months
Childhood behaviour
SDQ
Child
Questionnaire
42 - 157 months
ADHD
Child
Questionnaire
166 months
Antisocial behaviour
Child
Questionnaire
169 months - 198 months
Psychotic symptoms
Child
Questionnaire
140 months - 198 months
Adolescent substance use (tobacco, alcohol, drugs)
Child
Questionnaire
157 months - 198 months
Language development
McCarthy
Child
Questionnaire
24 months
Cognitive ability
WISC
Child
Clinic test
8-10 years
Scholastic achievement
Child
Questionnaire
166 months
Anthropometrics (Height, weight)
Child
Questionnaire
Birth - 157 months
Parental antisocial behaviour (antisocial behaviour as children or adults; contact with police; criminal convictions)
Mother, father
Questionnaire
Antenatal - 145 months
Childhood postnatal experiences (maternal depression and anxiety, parental discipline)
Mother
Questionnaire
Birth - 145 months
Parental postnatal substance use (tobacco, alcohol, drugs)
Mother, father
Questionnaire
Birth - 145 months
3.4 Data Analysis.
Phase 1. Missing genotype data (including polymorphisms genotyped in at least one but less than three of the datasets) will be imputed using published methods (Marchini et al., 2007). Hypotheses about effects on birthweight (corrected for gestational age) will be tested using linear models incorporating terms for prenatal tobacco exposure, foetal genotype, interaction between foetal genotype and prenatal tobacco exposure plus relevant covariates (including significant principal components of the genetic data to guard against spurious associations due to population admixture (A. L. Price et al., 2006), demographics, pregnancy and antenatal health variables, and parental physical and behavioural characteristics). Meta-analysis will be performed to synthesize the results from the three studies. SNPs to be genotyped in phase 2 will be chosen based on the regions that show the greatest evidence of association in phase 1. Where significant results are found for foetal genotype, post hoc analyses of the influence of maternal genotype and parent-of-origin effects will be tested in the IMAGE sample.
Phase 2. Hypotheses about effects on birthweight, head circumference, and crownheel length (all corrected for gestational age) will be tested using linear models incorporating terms for prenatal tobacco exposure, maternal genotype, foetal genotype, interaction between maternal genotype and prenatal tobacco exposure, interaction between foetal genotype and prenatal tobacco exposure, and the three-way interaction between foetal and maternal genotype and prenatal tobacco exposure, plus relevant covariates (including demographics, pregnancy and antenatal health variables, and parental physical and behavioural characteristics). Analyses will be stratified by ethnicity to guard against spurious associations due to population admixture. Should statistically significant results be found, post hoc hypotheses about trajectories of postnatal physical, behavioural, and cognitive development will be tested using growth curve models and growth mixture models; in addition, mediation analyses will be conducted to test whether postnatal development is conditionally independent of genotype and prenatal tobacco exposure after controlling for any effects on birthweight and gestational age. Hypotheses about the effects of prenatal tobacco exposure will test for heterogeneity of the effects with respect to mode of exposure (maternal smoking/maternal exposure to second hand smoke), dose, and timing of smoking cessation. A parallel set of analyses will be conducted using paternal tobacco exposure as the environment of interest in order to validate the inference of intrauterine effects. Analyses will be conducted to assess the possible influence of attrition in the sample on the outcomes of interest. If necessary, informative missingness will be explicitly modelled.
3.5 Statistical Power
Phase 1. Based on the most accurate information available, we anticipate that information on genomewide genotype, prenatal environmental exposures, and perinatal outcomes will be available for children from 4,000 families enrolled in TEDS, 4,763 families participating in NFBC, and 304 families from IMAGE. We expect that the numbers of children born to mothers who reported smoking during pregnancy in these three samples will be, respectively, 568, 700, and 63. For the purposes of the power analysis let us assume a total population of N = 9,067, exposure prevalence of 14.7%, population SD of birthweight = 400g, marginal effect of maternal smoking -200g, and no marginal effect of genotype. We will use alpha = 10-6 so that if we test 2-sided hypotheses of GxE in relation to 10-6 SNPs we expect on average 1 false positive by chance. Under these assumptions we will have 80% power to detect GxE accounting for 0.356% of the variance in birthweight and 50% power to detect GxE accounting for 0.261% of the variance.
Under an additive model of inheritance, 0.261%-0.356% of the variance corresponds to GxE accounting for a difference of 102-119 g between groups differing by an allele count of 1 and with different smoking status, assuming a minor allele frequency of 20%, or 136-159 g assuming a minor allele frequency of 10%. Under a dominant model of inheritance, 0.380%-0.521% of the variance corresponds to GxE accounting for a difference of 120-141 g between groups differing in whether or not they carry a risk allele and with different smoking status, assuming a minor allele frequency of 20%, or 147-172 g assuming a minor allele frequency of 10%.In other words, for common SNPs there is good power to detect a GxE whose coefficient is similar in magnitude to the marginal environmental effect. Effect sizes of this magnitude are by no means implausible, as recent candidate gene studies have demonstrated (e.g. Sasaki et al., 2008, T. S. Price et al., 2008), but there are likely to be relatively few variants in the genome that could account for interactive effects of this size. It is for this reason that we intend to follow up only a handful of the best hits.
Phase 2. Assuming that genotype data is available for 3,000 individuals, with 50% exposure to prenatal smoking throughout pregnancy, a population SD for birthweight of 400g, a marginal effect of maternal smoking of -200g, and using 2-tailed hypotheses for each of the three phenotypes of birthweight, head circumference, and crownheel length and a conservative significance threshold of alpha = 3.3e-4 (0.05 after Bonferroni correction for 50 x3 = 150 hypothesis tests), we estimate that for the effect sizes giving 50% power in the phase 1 we expect 69% power to replicate in phase 2, and for the kinds of effect size giving 80% power in phase 1 we expect at least 88% power to replicate in phase 2.
3.6 Work already completed
We recently investigated the relations between maternal smoking, foetal genotype, and foetal growth in a dizygotic twin pairs participating in TEDS (T. S. Price et al., 2008). Maternal smoking retarded growth by 118g in twins born to mothers who reported smoking less than 10 cigarettes per day and by 185g in twins born to heavier smokers, allowing for the effects of twin sex, birth order, gestational age, and maternal and familial characteristics. We selected 497 twin pairs, whose mothers smoked, for a molecular genetic study. In this subsample, a functional SNP in the NQO1 gene (Pro187Ser; rs1800566) was significantly associated with foetal growth within families assuming a dose-related model of effects (p=0.0028). These results provide the first demonstration that foetal genotype for a xenobiotic metabolizing enzyme influences intrauterine growth under conditions of smoke exposure independently of maternal genotype.
4. REFERENCES
Golding, J., Pembrey, M., & Jones, R. (2001). ALSPAC--the Avon Longitudinal Study of Parents and Children. I. Study methodology. Paediatr Perinat Epidemiol, 15(1), 74-87.
Health Development Agency. (2004). The evidence of effectiveness of public health interventions - and the implications.
Infante-Rivard, C., Weinberg, C. R., & Guiguet, M. (2006). Xenobiotic-metabolizing genes and small-for-gestational-age births - Interaction with maternal smoking. Epidemiology, 17(1), 38-46.
Kramer, M. S. (2003). The epidemiology of adverse pregnancy outcomes: An overview. Journal of Nutrition, 133(5), 1592S-1596S.
Kuntsi, J., Neale, B. M., Chen, W., Faraone, S. V., & Asherson, P. (2006). The IMAGE project: methodological issues for the molecular genetic analysis of ADHD. Behav Brain Funct, 2, 27-27.
Li, J., & Chen, Y. (2008). Generating samples for association studies based on HapMap data. BMC Bioinformatics, 9, 44-44.
Lumley, J., Oliver, S., Chamberlain, C., & Oakley, L. (1998). Interventions for promoting smoking cessation during pregnancy. Cochrane Database of Systematic Reviews(3), Art. No.: CD001055. DOI: 001010.001002/14651858.CD14001055.pub14651852.
Marchini, J., Howie, B., Myers, S., McVean, G., & Donnelly, P. (2007). A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet, 39(7), 906-913.
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006). Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet, 38(8), 904-909.
Price, T. S., Grosser, T., Plomin, R., & Jaffee, S. R. (2008, Nov 11-15). Fetal genotype for the xenobiotic metabolizing enzyme NQO1 influences intrauterine growth among infants whose mothers smoked during pregnancy. Paper presented at the American Society for Human Genetics, Philadelphia, PA.
Rantakallio, P. (1969). Groups at risk in low birth weight infants and perinatal mortality. Acta Paediatr Scand, 193.
Sasaki, S., Sata, F., Katoh, S., Saijo, Y., Nakajima, S., Washino, N., et al. (2008). Adverse birth outcomes associated with maternal smoking and polymorphisms in the N-nitrosamine-metabolizing enzyme genes NQO1 and CYP2E1. American Journal of Epidemiology, 167(6), 6.
Trouton, A., Spinath, F. M., & Plomin, R. (2002). Twins Early Development Study (TEDS): A multivariate, longitudinal genetic investigation of language, cognition and behavior problems in childhood. Twin Research, 5(5), 444-448.
B813 - The assessment of loci associated with varying levels of IL6 through the use of Genome Wide Association Studies - 20/04/2009
Interleukin-6 (IL6) is a key pro-inflammatory cytokine involved in the acute-phase response and is associated with a number of diseases, including Type 2 Diabetes.
We plan to do an IL6 genome-wide association study meta-analysis of 1410 ALSPAC individuals with 1210 individuals from the InCHIANTI study. We will require IL6 levels, age and gender adjusted results and combine using an inverse variance approach. We will perform genome-wide analyses and also cis-effect analyses for variants in or near (+/- 300kb) the genes coding for IL6 or IL6R - encoding for the IL6 receptor. IL6R SNPs have been previously associated with IL6 levels and can act as positive controls (Melzer et. al 2008).
Having meta-analysed this data, we then plan to replicate our initial findings using ~5000 additional children with IL6 measured from the ALSPAC study in order to determine loci that are robustly associated with varying levels of IL6. Potentially, this may involve ~10 top hits (or candidate hits) from the meta-analysis, although the exact number of SNPs we will follow up will depend on the false discovery rate/QQ plot statistics.
Note also that the InCHIANTI study has been approached by another GWAS consortium looking at IL6 levels (based around the Sardinia study) with a view to replicating their results. In the event that the GWAS meta-analysis of ALSPAC and InCHIANTI does not produce any stand out results, we would suggest that the best next step will be to join ALSPAC and InCHIANTI into an expanded IL6 GWAS consortium. Although making the relative contribution of ALSPAC and INCHIANTI smaller, it will increase power substantially and help identify variants that influence IL6 levels, something that could be useful for Mendelian Randomisation studies.
B810 - Interactions between birth weight and BDNF on IQ - 16/04/2009
The aim of this study is to understand how fetal growth influences neurocognitive function. We hypothesize that the outcome on IQ is mediated by birth weight in interaction with polymorphisms of certain SNPs of the BDNF gene.
Methods: In the large Asian cohort study of SCORM we have analysed six hundred fifty three children aged 7-9 years old, recruited from 3 schools in Singapore, who were followed yearly from 1999 onwards. Birth parameters were recorded by health personnel. Childhood IQ was measured with the Raven's Standard Progressive Matrices at ages 8 to 12. Buccal DNA was collected and single nucleotide polymorphisms for BDNF were obtained from the Illumina 550K beadchip.
Results: In SCORM we found that the BDNF gene show significant interactions between rs6265 (p=0.000) and rs11030104 (p=0.000) and birth weight (corrected for gestational age) on IQ. In children with TC (p=0.033) and TT (0.045) alleles of BNDF rs6265 and CC (0.054) and TC (0.029) alleles of the BNDF 11030104 a lower birth weight is associated with a lower IQ, while a higher birth weight is associated with a higher IQ.
These findings could implicate that improved fetal growth reduces the risk for lower IQ and improved developmental outcomes in children with certain alleles of BDNF genotypes. We would like to replicate these findings in the large Western cohort of ALSPAC.
Satistical Analysis:
Categorical data will be analyzed using the chi-square test. Differences between gender in age, birth weight and IQ are measured with t-tests. Genotype differences for continuous variables are evaluated using one-way analysis of variance. Birth weight will be corrected for gestational age. The interaction effects of SNP * Birth weight (corrected for gestational age) on IQ are examined with lineair regression. Posthoc analyses are performed if the relationship was found to be significant by subgroup analyses. All p values are two-tailed and considered statistically significant when the values were below 0.05. All statistical procedures used SPSS version 16.0 (SPSS Inc, Chicago, USA).
B809 - Follow-up and meta-analysis of signals associated with intelligence maths scores and memory in ALSPAC - 16/04/2009
(No outline received).
B811 - In-utero lead exposure and timing of puberty in the United Kingdom - 13/04/2009
Specific Aim - To conduct analyses of existing data to assess the effects of in-utero lead exposure on timing of puberty in children enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC).
Background and Significance - Recent literature suggests that lead appears to have endocrine disrupting potential in humans. Cross-sectional analyses of the United States Third National Health Examination and Nutrition Survey showed associations of blood lead levels with delayed breast and pubic hair development and menarche in girls 1 2 A cross-sectional study from Russia reported a delayed onset of genital development among boys with blood lead levels >= 5 micro-g/dL 3. Overall, the literature of the impact of lead on pubertal timing is sparse and the mechanisms leading to these associations are not known.
The Centers for Disease Control and Prevention (CDC) is currently conducting a study in ALSPAC participants to assess effects of exposure to substances with endocrine-disrupting potential in pubertal onset and progression. Analytes being tested in maternal serum and urine and children urine samples originate mainly from pesticides or plasticizers. The analytes are: organochlorine pesticides, polychlorinated biphenyls (PCBs), brominated flame retardants (PBB and PBDE), polyfluoroalkyl chemicals (PFCs), triazine herbicides (atrazine), environmental phenols, phthalates, and phytoestrogens.Data on pubertal development have been collected via self-administered questionnaires beginning at age 8 up to age 14.
In our study we are not testing samples for lead levels. However, ALSPAC have tested maternal blood samples for lead levels to study the effect of this exposure on other health outcomes. Because of the evidence that lead may impact the pace of pubertal development we want to obtain from ALSPAC the data on maternal blood lead levels to assess the effects of in-utero lead exposure on timing of puberty onset.
Due to the sparse, yet suggestive, reports on the association of lead with delayed pubertal development in boys and girls the proposed analysis of existing data would be an important contribution to the literature on the effects of environmental contaminants on endocrine function.
Research Design and Methods - As indicated previously outcome and exposure data has already been collected for other purposes. Among 8-14 year old singletons who responded to the puberty questionnaire, there were 3945 girls with valid data on breast and pubic hair Tanner stage and menarche; 3938 boys with valid data on pubic hair Tanner stage; and 2877 boys with valid data on genital Tanner stage.
We will construct survival models to assess the effect of lead on puberty. For girls, we will estimate the difference in timing of menarche attainment and of transition into stage 2 of breast and pubic hair development in exposure groups after adjustment for confounders. For boys, we will estimate the same for transition into stage 2 of genital and pubic hair development. We found inconsistencies in genital stage reporting in a large proportion of boys. Because of the reported association between delayed genital development and lead exposure we believe that it is important to assess this association in our study group. We have included the analyses of this association in the proposal as a possibility whose validity would be explored further.
Lead levels were tested on samples taken at time of enrollment in approximately 4000 mothers whohad whole blood stored in an acid washed vaccutainers. Data collection on parents and children enrolled in the ALSPAC cohort was conducted by the University of Bristol. The University of Bristol assigned a unique identification number to the puberty data they sent to CDC. We will provide the identification numbers of children with valid puberty data to ALSPAC staff to obtain their mother's lead levels and the gestational age when the blood sample was obtained. They will not be sending blood samples to CDC for lead testing. They will use the CDC assigned IDs to know for which children we want to obtain results of the blood lead testing they conducted. What we expect from them is an updated de-identified dataset of children with valid puberty data that will include results of their blood lead testing and the age the child was tested. Only the University of Bristol has access to information on personal identifiers. Data transfer will be conducted according to the confidentiality assurances and procedures that the University of Bristol have implemented as part of their study to prevent any breach in confidentiality.
The final number of children with both exposure and outcome values is not yet known. The number of maternal samples tested is large and may yield sufficient children to detect statistically significant differences among exposure groups. As a comparison, of the 1127 children from the Children in Focus Cohort seen at 25 months, 368 girls responded to at least one puberty questionnaire. If we apply this ratio (368/1127) to the number of mothers with lead data (~4000) we may have about 1300 girls with both lead and puberty data for analyses.
We conducted power calculations for different sample size scenarios of the study outcomes. For menarche attainment we obtained power estimates for sample sizes ranging from 250 to 1500 in increments of 250 at a level of significance of 0.05, a proportion of lost to follow-up of 13%, and a prevalence of delayed menarche of 3.2 2 for unequal sample sizes in comparison groups. Estimates were obtained using the PASS software.
Power calculations
Sample
size
Difference in proportion of girls with
menarche in comparisons groups
3.0
5.0
7.0
9.0
250
0.29
0.52
0.71
0.84
500
0.50
0.81
0.95
0.99
750
0.67
0.94
0.99
1.00
1000
0.80
0.98
1.00
1.00
1250
0.88
0.99
1.00
1.00
1500
0.93
0.99
1.00
1.00
With a sample size of 500 we will be able to attain a power of 80% to find a difference in the proportion of menarche attainment >= 5.0. It is likely that effects of lead in puberty are of a smaller magnitude; however, it seems reasonable to expect that the number of girls with lead and puberty data will be larger. We will address the potential for selection bias by exploring differences between those children with and without lead data. The proposed analyses of existing data seem feasible and will make an important contribution to current knowledge on effects of lead on endocrine function.
References
1. Selevan SG, Rice DC, Hogan KA, Euling SY, Pfahles-Hutchens A, Bethel J. Blood lead concentration and delayed puberty in girls. N Engl J Med 2003;348(16):1527-36.
2. Wu T, Buck GM, Mendola P. Blood lead levels and sexual maturation in U.S. girls: the Third National Health and Nutrition Examination Survey, 1988-1994. Environ Health Perspect 2003;111(5):737-41.
3. Hauser R, Sergeyev O, Korrick S, Lee MM, Revich B, Gitin E, et al. Association of blood lead levels with onset of puberty in Russian boys. Environ Health Perspect 2008;116(7):976-80.
B807 - The measurement of polybrominated diphenylether flame retardants in samples of umbilical cord - 01/04/2009
The hypothesis we would like to test is that children with autism, and perhaps those with other forms of developmental delay (DD), may have elevated body polybrominatd diphenylether (PBDE) concentrations, compared to typically developing (TD) controls. Using samples of umbilical cord tissue to measure PBDE leadings is highly relevant to what the foetus would have received from the mother via the placenta. In the first instance we would like to obtain 3 samples of cord tissue of varying mass, between 0.3 and 1.5g, so that we can find out what PBDEs we can measure in samples of this size. Hopefully we will be able to meaure most of the important PBDEs in these samples so that we could proceed with a funding application to measure samples from the different study groups described above.
PBDEs have been used as flame retardants in textiles, including carpets, curtains and household furnishings, as well as in plastics and computer components, since the mid-1980s, around the time that autism prevalence began to increase globally. While the causative factors involved in an individual becoming autistic are likely to be multi-factorial, the timing of PBDE introduction in homes and workplaces, their rapid rise in the environment since the 1980s and a parallel rise of PBDE concentrations in human tissues and fluids along with their known affects on metabolism makes them environmental factors that are very worthy of further investigation. Unlike many of the other neuroendocrine and elemental toxins such as dioxins, PCBs, Hg and Pb, that are all decreasing in the environment, PBDEs have risen rapidly over the same time frame as the recorded increased prevalence of autism. While around 43 PBDE congeners have been identified the contribution to overall tissue concentrations in humans is largely represented by 10 congeners namely PBDEs 28, 47, 49, 66, 99, 100, 153, 154,183 and 209. The measurement of tissue PBDE concentrations will be conducted using state-of-the-art analytical equipment including automated solvent extraction (ASE(tm)) and gas-chromatography/mass spectrometry (GC/MS). PBDEs have known endocrine disrupting activity including alteration of thyroid hormone concentrations [they deplete T4 levels and function, as well as reducing vitamin A (retinol)]. In addition, PBDEs stimulate pro-oxidant activity resulting in an increase in the oxidised/reduced glutathione ratio (GSSG/GSH). Increased GSSG/GSH ratio and antioxidant dysfunction have been reported in patients with autism. PBDEs induce hepatic cytochrome P450 IIB1 and 1A1 hepatic detoxifying systems. Possible impairments in this metabolic detoxification in individuals with autism and/or developmental delay might make these individuals more susceptible to elevated tissue levels of PBDEs. Perhaps the greatest concern of damaging effects of PBDEs relate to developmental neurotoxicity in mice and rats. These effects include disruption of spontaneous behaviour, impaired learning and memory, hearing and memory impairments and behavioural changes. The mechanisms for these affects on behaviour and cognition are unknown but may be associated with alterations to cholinergic receptors (Viberg et al., 2002).
B805 - Exploring and understanding the food practices of working families with younger children - 30/03/2009
N.B. This research proposal is a response to a specific call from the ESRC/Food Standards Agency relating to the NDNS
Recent research suggests that the nation's diet will be more likely to improve if healthy eating policies take into account changing patterns of family life (Jackson & Pickering, 2009). This study aims to map and understand the effects of a major social change that research indicates affects the quality of children's diets, namely the rise of maternal/dual parental employment in the UK. The study will take as its starting point that children's nutrition and food practices take place not only in their homes but in a range of contexts. The study will interrogate the 2009 National Diet and Nutrition Survey (NDNS), the Health Survey for England (HSE) and the Avon Longitudinal Study of Parents and Children (ALSPAC) to examine in relation to diet the associations found in other studies between childhood overweight and parental employment. This secondary analysis will be followed by an intensive study of 48 working families sampled from the NDNS and selected according to (high and low) income level and the quality of children's diets. This part of the study will seek to provide explanations for statistical associations found (or not found) in the NDNS survey data. It will employ ethnographic methods, including interviews and photo elicitation, in order to understand the social processes which influence healthy and unhealthy diets of children both within and outside the home. The quantitative analysis of secondary data will hypothesise and examine associations between diet and parental employment status while the qualitative part of the study will inductively explore the contextual meanings of 'food use' in working families, the embodiment of food practices, and their embeddedness in different social contexts (inside and outside the home). The implications of the research for policy and practice include informing the design and evaluation of health interventions so that they may be tailored more effectively to the needs of employed families. Through its use of a variety of research tools the study will inform the methodology of future studies.
Background
Between 1995 and 2003, the prevalence of obesity among children aged 2 to 10 rose from 9.9% to 13.7% (Health Survey for England, 2006). As UK studies suggest, early childhood overweight is associated with the propensity for overweight and obesity in adulthood (Gardner et al., 2009). Given the lack of robust evidence concerning the effectiveness of interventions later in the life course (Summerbell et al., 2003), public policy is concerned with children's health (DH/DCFS, 2008a). Research has shown that some groups of children are at greater risk of being overweight and obese than others (Waldman, 2008): those from lower social economic groups (e.g. Kinra et al., 2000; Armstrong et al., 2003; Power et al., 2003; Stamatakis et al., 2005); and some ethnic minority groups (Health Survey for England, 2004; Rennie & Jebb, 2005; Law et al., 2007).
In addition, research evidence suggests an association between maternal employment and children's overweight status (Scholder, 2007; Hawkins et al., 2008). Analysing the Millennium Cohort Study, Hawkins et al. (2008) found associations between maternal employment and overweight among preschool children, a finding supported by some US research (e.g. Anderson et al. 2003; Crepinsek & Burstein, 2004). Specifically, Hawkins et al. found that children's likelihood of being overweight increased with the number of hours their mother worked per week. However, this finding was only significant among higher income families (annual income in excess of £33,000) (Hawkins et al., 2008). These results mirror US studies showing links between childhood overweight and maternal employment in highly educated, well off, white families (Fertig et al., 2003). These findings thus serve to complicate the general picture of a positive association between household income and children's weight (see e.g. Health Survey for England, 2006). Hawkins et al. (2008) hypothesise a link with diet, suggesting that longer maternal working hours may impede young children's access to physical activity and healthy foods. Analyses of ALSPAC suggest that the dietary patterns of children aged three (North & Emmet 2000) and seven (Northstone & Emmet, 2005) whose mothers were in paid employment were significantly associated with a 'junk' dietary component, although these studies do not explore diets in relation to working hours. In apparent contradiction, a survey by Sweeting & West (2005) of older children and their working parents (N=2,146) suggests a link between non-working mothers and poor diets : 63% of 11 year old children whose mothers were at home full-time were classed as eating "less healthily", compared to 52% of those whose mothers worked full-time. However, this latter analysis did not control for income and maternal education which are known to affect children's diets (Gregory et al., 1995; Northstone & Emmett, 2005).
Early nutritional experiences have both immediate and long term consequences not only for younger children's weight but also for their educational attainment and mental, social and economic wellbeing (NHS/HDA 2004; DfES, 2006; FHF, 2007; Feinstein et al., 2008; Golley et al., 2008). A possible link between parental employment and children's diet is important since the rise of maternal employment is one of the key recent social changes which has impacted upon children's lives in the UK (Layard & Dunn, 2009); the economic activity rate for women aged 16-59 rose from 59% in 1971 to 74% in 2007 (ONS, 2007; Walling, 2005). The most striking change in employment rates has occurred among mothers of young children (Berthoud 2007). In 2004, 57 per cent of women with a child of pre-school age were economically active compared with 55 per cent in 1997 (Aston et al., 2005); more than two thirds of working-age women with dependent children (68%) were in employment in the second quarter of 2008 (ONS, 2008).
However, these rises in parental employment have not been accompanied by any significant increase in public policy or workplace support for employed parents. Within the household, although recent studies have highlighted increases in men's care contribution to family life (e.g. Gershuny, 2001; O'Brien & Shemilt, 2003), including food provisioning (e.g. Drydon et al., 2009), gendered sociocultural expectations around carework have not kept pace with changes in parental employment patterns. Women remain disproportionately responsible for food work (Murcott, 2000; DeVault, 1997): the UK Time Use Survey suggests that in 2000 females spent roughly twice as much time as males on the activities of shopping, preparing food and washing up (ONS, 2000). Some US literature suggests that 'time poor' working families may face significant challenges in meeting the demands of feeding their families (e.g. Jabs et al., 2007). Parents' feeding decisions may represent attempts to reconcile competing symbolic and practical tasks. For example, whilst they recognise that some 'convenience' food is not 'healthy', mothers may find it helps them 'meet their priority of feeding their families in a time-scarce environment' (Jabs et al., 2007:24; Warde, 1999).
Theoretical approaches and methodologies
Research suggests that because parents play such a critical role in determining the diets of their children, as meal providers and role models (e.g.Wardle and Cooke, 2008), 'pressures on parents' food choices have great importance for the nutrition and health status of their children' (Devine et al., 2006: 2592). However, children exert their own pressures on parents (Norgaard et al., 2007), form their own preferences and practices and use food to forge (and reject) connection with others. Food is an important way in which people construct identities through consumption (Valentine, 1999), especially for children (e.g. James, 1998; Wills et al., 2008; James, 2008; James et al., forthcoming). In short, food practices are negotiated (DeVault, 1997; Jackson & Pickering, 2009:4). This study will be guided by such ideas and by a practice-based theory of family life (Morgan, 1996) in which children's agency is given due weight (Christensen, 2004). While home and family are of central importance in terms of feeding younger children and establishing eating patterns (Birch, 1998), they also interact with other environments (Bronfenbrenner, 1979) which provide food and influence food practices (NICE, 2006:149). School is a key eating environment for older children and when mothers or both parents work, for younger children nurseries, childminders, after school clubs, and the homes of friends and relatives are environments where a large proportion of the daily diet is consumed. Much of the limited supply of childcare in the UK is provided in the private sector by large companies or small businesses (private nurseries and childminding) where regulations around food consumption are limited (More, 2008), in contrast with the tighter regulations in schools (cf. Belot & James, 2009). A holistic view of children's nutrition and food practices is needed to understand the range of intersecting contexts in which children are nourished and their food practices nurtured.
A focus in some public health policy on individual consumer 'choice' has tended to confound food selection with preference, obscure the socio structural conditions in which food practices evolve and neglect the cultural and emotional factors that influence nutrition (Attree, 2006:67). Food plays important roles beyond providing sustenance, fulfilling non material cultural goals (de Garine, 2004:19) for adults and children (Alcock, 2007). It is an expression of care and identity (Kaplan, 2000). It is also political (Lien, 2004); food mediates power relations, including those based on age and gender (Murcott,1982,1983a; Charles & Kerr 1988). Understanding food practices requires approaches that go beyond rational-choice paradigms to confront 'habitus' (Bourdieu, 1977) - the situatedness of practices in everyday routines and social relations. Providing empirical data concerning the relationship between parental employment and children's diets and the embedded practices and processes which shape them, the proposed study will fill a clear gap in knowledge.
The main aims of the study are to address these key research questions:
* How does parental employment influence and shape family food practices in particular the diets of children (aged 1.5 to 10 years)?
* How do parents' experiences of negotiating the demands of 'work' and 'home' affect domestic food provisioning in families?
* What foods do children of working parents eat in different contexts - home, childcare and school - and how do children negotiate food practices?
The specific objectives of the study are:
1. To examine the relationship between parental employment status and the diets of younger children via secondary analysis of the 2009 NDNS Survey, the Health Survey for England (HSE) and the Avon Longitudinal Study of Parents and Children (ALSPAC)
2. To seek understandings of the food practices of children in working families, including families with high and low incomes and those whose children are classified on the NDNS as having 'healthy' and 'unhealthy' diets, by applying a range of in-depth qualitative methods
3. To develop the methodology in this area through the use of a multi-method research approach
4. To inform healthy eating advice for employed families, by presenting to policymakers and practitioners issues to consider for bringing about improvements in children's diets
Research design: A mixed methods approach
Hawkins et al., (2008:37) have suggested that '[f]urther research is needed to examine factors along the causal pathway between maternal employment patterns and childhood overweight, which can help inform policy and interventions. For example, little is known about differences in children's diet or physical activity levels by maternal employment status. Focussing on diet, this study will employ the different logics which underpin different methods (cf. Murcott, 1995:734; Brannen, 1992, 2005; Bryman, 1988; Greene et al., 1989). Through secondary analysis of survey data it will hypothesise and examine associations between diet and parental employment status. Through an anthropological and sociological approach it will inductively explore the contextual meanings of food use in working families, the embodiment of food practices, and their situatedness in different social contexts and practices. Together these approaches will help to provide a fuller picture (Brannen 2004; Mason, 2006).
Exploiting the knowledge and capacities of the multidisciplinary research team, the study will draw on a mix of disciplines (anthropology, sociology and social statistics) and research fields including the 'new social studies of childhood', family studies, childcare research and the study of food practices to achieve these objectives and complement the FSA's existing work in nutrition, dietetics and physiology. Its sample will aim to focus on families with at least one young child aged 1.5-10 years. The study will have four main phases. The timetable below is proposed based upon NDNS data becoming available in December 2009:
Phase 1: October - December 2009 Access to large scale data sets (NDNS, HSE, ALSPAC), identification of relevant variables, preparation of data set for analysis in Phase 2, design and piloting of qualitative research instruments for use in Phase 3.
Phase 2: November 2009 - Feb 2010 Secondary analysis of large scale surveys. To examine how parent employment relates to children's diets, secondary analysis will be carried out on the 2009 NDNS, the Health Survey for England (HSE) and the Avon Longitudinal Study of Parents and Children (ALSPAC), as all of these collect data on children's diet and mothers' employment. The NDNS is the only rolling UK survey to collect nationally representative and detailed dietary information on children and adults. So far, different waves have concentrated on specific age groups. A key advantage is that NDNS contains linked data on food, nutrient intake, nutritional status and contextual information on individuals. The first NDNS (1992/93) collected data on the diets of 1,340 children aged 1.5 to 4.5 and collected detailed data on the mother's hours of work. The third survey (1997) collected data for children aged 4 to18, with a full dietary record for 1,701 children; the survey asked about mother's employment, but only classified hours of work as full or part time. Some data have been analysed by social class (Gregory & Hinds, 1995), but not by mother's employment. Unfortunately, the sample sizes are quite small, especially for analysing sub-groups (Scientific Advisory Committee on Nutrition, 2008:21), such as employed mothers. Parental employment appears to have been asked in NDNS 2009.
HSE is an annual survey carried out on behalf of the NHS. The survey includes data on diet and nutrition for children and hours of work for mothers (although only full or part time). In 2007 there was a boost sample of children, so that a total of 7,504 children were included (Craig & Shelton, 2008b). The relation between diet and maternal employment has not been analysed. However, even a sample this size has limitations: as the survey report noted, while 'exploratory analysis indicated that there may be associations between a child's perception of how healthy they perceive their diet to be and how healthy their parents perceive their own diet to be... numbers of parent and child pairs ... are too small to produce reliable conclusions' (Craig & Shelton, 2008a: 292).
From the early 1990s ALSPAC followed approximately 14,000 children from birth into their teenage years. It collected detailed data at different age points on children and their families, including data on parental employment and on diet and nutrition (Emmett, 2009). This unique dataset provides opportunities to explore associations between employment and children's diets in a large sample across the childhood years. The level of detail on mothers' hours of employment varies at different points in time: at 47 months mothers were asked about employment, but not about hours of work; at 61 and 85 months mothers were asked about hours of work. However at 73 months mothers were not asked any questions about their employment. This study would look in detail at the effect of hours of work at different ages. Other studies have related diet and nutritional information for children and socio-economic data for adults: diet in 3-year olds (North & Emmett, 2000) and 4-year olds and 7-year olds (Northstone & Emmett, 2005) was analysed in relation to socio-economic factors, including mother's employment, although diets in relation to working hours was not examined.
These three datasets each has some information to contribute, but each has its limitations - in terms of sample size or in terms of details on hours of work. By analysing the data in combination, it should be possible to explore the relation between mother's hours of work and children's diet in more detail than has been done before. To identify a composite measure of diet quality using variables from the NDNS, HSE and ALSPAC datasets the advice of a public health nutritionist will be sought. The nutrition literature contains a wide variety of diet quality indices (Emmett, 2009; Kant, 1996) which have different advantages and disadvantages. The aim is to derive and interpret children's dietary patterns and assess their association with parental employment status using appropriate multivariate analysis techniques. The viability of the NDNS 2009 sample we wish to select will also be tested - single and dual parent earner households with children aged 1.5-10 years. Given the possible small sample size of the latter age group in the NDNS 2009 it may be necessary to carry out the analysis on all children in the survey who are under 18 years.
Phase 3: January - December 2010 Selection of participants, fieldwork and preliminary analysis of the qualitative study of employed parents and children's diet. The 2009 NDNS offers the most up to date analysis of children's diets and will provide the sampling frame for working families. This part of the project will seek to understand the relationship between parental employment and the food practices in which parents and their children aged 1.5-10 engage both in the home and in contexts outside the home. Forty eight dual and lone parent households and high and low income groups will be selected from the NDNS 2009 survey. The sample of households will be drawn from a number of urban and suburban areas in which these data are clustered in several different parts of England. To assist recruitment and thank participants for their time commitment, vouchers will be given to each household. Whilst we would hope to secure all 48 households in this way, we may need to be pragmatic if this is not possible. Further families will be found through snowballing from the selected NDNS participants. These participants will be screened for household employment and age of children, income and broad dietary indicators through completion of a short telephone interview (Casey et al., 1999). The diet data will be collected in the same format as in the NDNS to make the additional sample comparable. Four groups of working families divided by income level and by the quality of children's diets as assessed by the NDNS data will be selected:
(a) 12 households (one child aged 1.5-10) in which the child scores high on a composite measure of diet quality and where the parent /s they live with are employed and in low status jobs;
(b) 12 households (one child aged 1.5-10) in which the child scores low on a composite measure of diet quality where the parent/s they live with are employed and in low status jobs;
(c)12 households (one child aged 1.5-10) in which the child scores high on a composite measure of diet quality where the parent/s they live with are employed and in high status jobs;
(d) 12 households (one child aged 1.5-10) in which the child scores low on a composite measure of diet quality where the parent/s they live with are employed and in high status jobs.
Since the home is at the centre of family food practices the study will necessarily focus on food in the domestic domain. However, because other environments (workplaces, preschools, schools, after school clubs) interact with the home (e.g. Brannen & Storey, 1998; Burgess & Morrison, 1998), supplementing and influencing food practices within it (and vice versa), data will be collected from parents and children about food consumption in these contexts. Further, because food practices are embedded in social relations and social processes, they are not necessarily easily accessible to reflection (Eisner, 2008). The use of creative and visual methods facilitates investigating layers of experience that cannot easily be put into words (Gauntlett, 2007; Bagnoli, 2009). A flexible range of research tools (e.g. Mooney & Blackburn, 2003; Edwards et al., 2005) will be employed as appropriate to bring practices to the level of discourse and to address the contexts in which food is consumed. These will include 4 approaches: (a) in-depth semi-structured interviews with parents and children aged 1.5-10 that includes story telling with children; (b) drawing methods with children (e.g. Backett & Alexander, 1991; Backett-Milburn & McKie, 1999; Hill et al., 1996; Morrow, 2001); (c) a task based exercise in which family members will be asked to suggest working-family-friendly meal ideas for inclusion in a cookbook; (d) photo elicitation interview methods (PEI's) (Collier, 1967; Radley & Taylor, 2005) carried out by parents and children (Punch, 2002) in which they will photograph foods and meals (consumed in and outside the home) for discussion in the interview. Adopting this range of qualitative tools will enable choices to be made about the most appropriate methods for eliciting children's perspectives based on their maturity, competencies and preferences (Hill, 2006; Christensen & James 2000). Rather than only serving as 'records' of food eaten (as in a realist approach), photographs, drawings and storytelling will be employed to aid reflection (Harper, 1998, 2002; Pink, 2001) upon the meaning of food events to participants and the relevance and importance of different social, environmental and temporal contexts. Photography is a particularly appropriate method for achieving our objectives, not only because it may bring the public into the private (and vice versa; cf. Moss, 2001) but also because food is a material substance which appeals to several senses and is amenable to visual representation. Households will be visited twice. At the first visit, the PEI and other exercises will be explained to parent(s) and children; at the second visit, parent(s) and children will be interviewed, employing photographs, drawing, storytelling and the cookbook task as appropriate. Analysis of photographs is a collaborative process between participants and the researcher. As in qualitative research more generally, analysis is an iterative process in which emergent questions guide the collection of future data (Pink, 2004; Jenkings et al., 2008). Qualitative data analysis software (e.g. NVivo/NUD*IST/Atlas.ti) will be employed to assist in the inductive development of key themes, patterns and categories (Hammersley & Atkinson, 2007) specifically relating to the negotiation of domestic food provisioning and the experiences of participants relating to food practices across different sites.
Phase 4: Jan 2011-September 2011. Analysis, writing up and raising methodological questions for future research including the NDNS survey. The fourth phase will involve integrating the data and results generated from the secondary analysis of NDNS, HSE and ALSPAC and from the qualitative study. The ways in which the different data sets will be integrated will be considered from the outset of the study (Greene et al 1989; Brannen 1992, 2005; Bryman, 2006). Mixed methods can provide for an articulation between different layers and types of explanation - macro and micro - each of which cannot be fully explained without reference to the other (Kelle, 2001). However, it is recognised that translation of research questions across different methods of data collection changes their significance and is likely to affect responses and create problems of interpretation. The two layers do not map on to each other readily; they are different forms of explanation albeit they may complement one another (Bryman, 2007; Murcott 1995). We may expect to find some dissonance (Perlesz & Lindsay, 2003) between findings generated by different methods, e.g. reports of the nature of diets in the survey and what is said in the interviews. On the other hand, we may expect the two analyses to complement each other, e.g. explanations for dietary habits may not be viewed in relation to health or quality issues. The analysis of the NDNS and the qualitative study will provide guidance for future research about the value of a mixed method approach for this area of research, which methods and which survey/interview questions are useful and for which purposes.
B801 - Determination of the affect of a complex CNV region on Chr 12 on various psychological variables of the ALSPAC cohort - 30/03/2009
Copy number variation (CNV) represents a significant proportion of human genomic variation and it is increasingly becoming clear that CNV is involved in phenotypic variation and disease (Itsara et al, 2009). We are interested in understanding the relationship between copy number variation at loci critical to development, growth and disease. Our current region of interest focuses on a genomic domain spanning genes important for pluripotency, energy utilisation and the immune response. Our analysis of the current genome build reveals part of this region to exist mainly as an ancient (pre-simian) tandem duplication, with corresponding gene duplications. SNP genotyping across this interval in a case control study demonstrated association with rheumatoid arthritis and also revealed hints for CNV (Lorentzen et al, 2007). Due to its complexity and limited LD with surrounding DNA the region is not detected using current genome wide SNP technologies, and therefore targetted CNV analysis is required. Assays for CNV within the tandem duplication were developed based on an adaption to the paralogous ratio test (PRT)(Armour et al, 2007). In these assays the relative number of copies between the tandem repeats is assessed using oligonucleotide primers that amplify simultaneously from both repeats. During this analysis we discovered that either repeat can be duplicated or deleted, thereby representing a complex CNV. From these investigations we have developed an accurate copy number counting assay and demonstrated a significant association between rheumatoid arthritis and copy number of this tandem duplication. This region is of substantial interest as, in addition to the association with RA, it has been implicated in a number of disorders through the data from the rat genome database including QTLs related to insulin resistance and heart disease. Mouse models determine that homozygous nulls for this gene are lethal whereas heterozygous null are related to insulin resistance and increased body mass. Furthermore, changes in protein levels of one of the genes within the CNV in humans has been linked to cancer, insulin resistance and Alzheimer's disease. Given the wide range of disease associations and the role pluripotency, energy transfer and immune response plays in growth and development it is likely that changes in copy number at this region will have an impact on various underlying biochemical measures. Therefore it would be prudent, in addition to traditional case control studies that we are planning, to examine the role of copy number in relation to various endophenotypes. For this the highly characterised ALSPAC cohort is ideal.
For this purpose we have designed and assessed a number of assays based on the paralog ratio test (PRT). These assays allow the assessment of copy number between the repeats, and thereby can indicate which of the two repeats are changing in copy number. The PRT is relatively unique among copy number counting methods in that it requires very little DNA to produce accurate counting. It would therefore be feasible to rapidly genotype the entire ALSPAC cohort with multiple assays using 100 ng DNA, including repeats.
The results of these assays would then be analysed in relation to various biochemical and physiological measures listed below.
B804 - Contribution of ALSPAC lung function data to international consortium on lung function reference values - 24/03/2009
An international concortium led by Janet Stocks, UCL and funded initiallly by Asthma UK, has produced reference equations for spirmoetry from childhood through to adult life (www.growing lungs.org). This project is an extension of this work utilising large collections of lung function data from cohort and cross-sectional studies to refine the current reference equations. ALSPAC has greater than 7000 measurements fo spirmoetry in 8 year olds and a further 4000 from 15 year olds that will be a valuable addition to the resource and wil be appropriately credited in publicatiosn arising from this work.
Data required are spirometry measurements form Focus@8: FEV1, FVC and mid expiratory flows (FEF 25-75) and child's sex, height and weight on day of measurement. No other identifying information will be sent.
B803 - Evaluation of a novel atopic dermatitis susceptibility variant in the ALSPAC cohort - 24/03/2009
Atopic dermatitis (AD or eczema) is a chronic inflammatory skin disorder and a major manifestation of allergic disease. In the industrialized countries, the prevalence of AD is approximately 15 % with a steady increase over the past decades1. Genetic and environmental factors interact to determine disease susceptibility2, and family and twin studies indicate that the genetic contribution is substantial3. The molecular mechanisms underlying eczema are not fully understood. Skin barrier defect as well as systemic and cutaneous immune dysfunction in response to allergens or bacterial products are thought to play an important role4.
We conducted a genome-wide association study in 939 individuals with AD and 975 controls as well as 270 complete nuclear families with 2 affected siblings. SNPs consistently associated with AD in both discovery sets were then investigated in two additional independent replication sets totalling 2637 cases and 3957 controls. Highly significant association was found with rs7927894 on chromosome 11q13.5 (Pcombined = 3.1 x 10-10). Approximately 13% of individuals of European origin are homozygous for the risk allele, and their risk of developing AD is 1.47 times that of noncarriers5.
The objective of this study is to evaluate this novel eczema susceptibility variant at the at the general population level in the ALSPAC cohort in order to
1) replicate the initially reported association with eczema.
The ALSPAC cohort (n=7000) carries sufficient power to replicate the original finding:
Under the assumption of a moderate odds ratio of 1.3 and a disease prevalence of 10%, the power to detect an association is 94%.
2) assess the population-attibutable risk of this variant for eczema.
in contrast to the affected families and cases/controls used in the GWAS, the ALSPAC cohort will enable us to estimate the population attributable risk fraction (PARF) which indicates the proportion of cases in the population attributable to the rs7927894 risk allele.
3) evaluate this variant for association with other atopic disorders.
Interestingly, this variant has also been reported to be a risk factor for Crohn's Disease6, extending the number of overlapping risk variants for different chronic inflammatory diseases and highlighting the importance of shared molecular pathogenic pathways. The ALSPAC cohort will allow us to test this variant for association with other atopic disorders including asthma, and hayfever. An association analysis with Crohn's Disease may be attempted. However, due to the expected low prevalence of Crohn's disease, the ALSPAC cohort may not carry sufficient power to yield conclusive results.
4) evaluate epistatic effects between this variant and Filaggrin loss-of-function mutations.
Loss-of-function mutations in the filaggrin gene are strongly associated with eczema7,8. We have detected an epistatic effect between rs7927894 and the filaggrin loss-of-function mutations in the German Multicenter Allergy Study (MAS 90). However, only 871 of the original 1300 MAS children were available for genetic studies. The ALSPAC cohort is significantly larger than the MAS cohort and will allow us to replicate this finding and to estimate the effect size more accurately.
Reference List
1. Taylor, B., Wadsworth, J., Wadsworth, M., & Peckham, C. Changes in the reported prevalence of childhood eczema since the 1939-45 war. Lancet 2, 1255-1257 (1984).
2. Cookson, W. The alliance of genes and environment in asthma and allergy. Nature 402, B5-11 (1999).
3. Schultz, L. F. Atopic dermatitis: a genetic-epidemiologic study in a population-based twin sample. J.Am.Acad.Dermatol. 28, 719-723 (1993).
4. Bieber, T. Atopic dermatitis. N.Engl.J.Med. 358, 1483-1494 (2008).
5. Esparza-Gordillo, J. et al.A common variant on chromosome 11q13 is associated with atopic dermatitis. Nature Genetics in press (2009).
6. Barrett, J. C. et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease. Nat.Genet. 40, 955-962 (2008).
7. Palmer, C. N. et al. Common loss-of-function variants of the epidermal barrier protein filaggrin are a major predisposing factor for atopic dermatitis. Nat.Genet. 38, 441-446 (2006).
8. Brown, S. J. & McLean, W. H. Eczema genetics: current state of knowledge and future goals. J Invest Dermatol 129, 543-552 (2009).
Concept Specific measure Person Source Time point(s)
eczema Doctor's diagnosis of eczema child questionnaire Age 0-5 years
Age 6-10 years
Age greater than 10 years
eczema eczema child Physical exam Age 0-5 years
Age 6-10 years
Age greater than 10 years
asthma Doctor's diagnosis of asthma child questionnaire Age 0-5 years
Age 6-10 years
Age greater than 10 years
asthma asthma child Physical exam Age 0-5 years
Age 6-10 years
Age greater than 10 years
hayfever Doctor's diagnosis of hayfever child questionnaire Age 0-5 years
Age 6-10 years
Age greater than 10 years
hayfever hayfever child Physical exam Age 0-5 years
Age 6-10 years
Age greater than 10 years
atopy Elevated spec. IgE or Skin Prick test child evaluation Age 0-5 years
Age 6-10 years
Age greater than 10 years
Chronic inflamm. bowel disease (IBD) Doctor's diagnosis of IBD child questionnaire ever
B802 - Investigating the relationship between IL-6 and bone mass accrual in childhood - 24/03/2009
(No proposal received).
B799 - Parallel longitudinal model of childhood depression and BMI LINKED TO B0659 - 23/03/2009
(No outline received).
B800 - The Impact of Prolonged Infertility on Parenting - 20/03/2009
Previous studies have small samples with small or no control groups. ALSPAC's vast data will allow for a larger sample of women who have experienced prolonged infertility. The data also provides for control groups. Due to the large numbers of variables present in the data, it will be possible to screen out for a variety of variables that might skew the data. For example, age of mother, ethnicity, socioeconomic status, and other variables. To date I have not found other studies that use the length of time of being infertile as a variable. Using the ALSPAC data, this will be possible. Instead of focusing on the type of technology used to become pregnant, I will focus on how the length of time trying to conceive influences subsequent parenting.
B798 - Understanding the lifestyle molecular and genetic pathways that link womens reproductive function to healthy ageing LINKED TO B1193 - 15/03/2009
Aims and objectives of the programme
Broad aims of programme
The aims of the programme are to (i) understand the mechanisms that underlie the associations of women's reproductive characteristics (age at menarche, menstrual patterns, follicular activity, fertility, pregnancy and age of menopause and menopausal changes) with later risk for chronic complex diseases and their risk factors (obesity, hypertension, dyslipidaemia, hyperglyaceamia, insulin resistance, type 2 diabetes, coronary heart disease, stroke, osteoporosis, depression, breast density and breast cancer); (ii) to understand the role of women's reproductive health in healthy ageing and (iii) to determine the mechanisms for the intergenerational transmission of patterns of women's reproductive, cardiovascular, metabolic, skeletal and mental health.
The programme will bring together existing funded work of the PI and co-applicants that is concerned with pregnancy related changes and future cardiovascular, metabolic and bone health in offspring and mothers (project grants from US NIH, MRC, Wellcome Trust & BHF). In the first phase we will focus primarily on consolidating the work from these different projects (objective 1 of the first 5 years) in order to obtain a comprehensive picture of how pregnancy related changes affect a wide range of future health related outcomes in mother and offspring. In addition in the first 5 years we will obtain detailed repeatedly assessed phenotypic data (hormonal, vascular, metabolic, bone and DNA methylation changes) on a cohort of women (the mothers) as they go through the menopausal transition (from age 47-52 years). These new data will be used to address objectives 2-7 below and will provide the evidence based for understanding how oestrogen deficiency and menopausal changes influence ageing in general and specifically vascular, metabolic and muscular-skeletal ageing. With subsequent renewal of the programme , after the first 5 years, we would focus on the daughter's menstrual pattern, follicular activity and emerging fertility, as well as linking data on the mother's breast density from routine mammography and mental health outcomes to the main dataset.
Specific objectives of the first 5 years
We will:
1. Determine the extent to which pregnancy related weight gain, vascular and metabolic changes are related to the mother's and her offspring's future reproductive, vascular, metabolic and muscular-skeletal health.
2. Determine the pattern of changes in glucose, insulin, lipids, blood pressure, total and truncal fat and bone mineral density as women go through the menopausal transition and distinguish whether there is a specific menopausal effect over and above age related changes in these phenotypes.
3. Determine the hormonal, genetic, molecular and lifestyle pathways that underlie variation in age at menopause and variation in changes in vascular, metabolic and bone phenotypes over the menopausal transition.
4. Determine the association of different patterns of change in glucose, insulin, lipids, blood pressure and total and truncal fat over the menopausal transition with variation in postmenopausal carotid intima media thickness.
5. Establish the role of DNA methylation in determining the timing and magnitude of menopausal changes.
6. Determine the pattern of global and gene-specific (e.g. ESR1) DNA methylation patterns as women go through the menopausal transition.
7. Determine the consequences of menopause- related DNA methylation changes with respect to subsequent changes in vascular, metabolic and muscular-skeletal health.
Data requirements and new data collection
Objective 1 above will use existing data or data currently being collected (e.g. mums clinic and 17+ clinic fasting blood samples and assays) and brings together agreed work of the PIs in ALSPAC as funded by existing grants (NIH; MRC; BHF).
The remaining objectives will be addressed by collection of new data from a subgroup (~3000) of the ALSPAC mothers who fulfil the following criteria:
Age 47-49 years at start of new clinics (September 2010)
No previous history of hysterectomy or bilateral oophorectomy
Not known to have undergone natural menopause
Mothers fulfilling these criteria will be invited to attend annual clinics over a 4 year period (4 clinics in total) at which the following will be completed:
1. Completion of menstrual cycle & hormonal use questionnaire
2. Taking of a fasting blood sample
3. Measurement of weight, height, waist circumference and blood pressure
4. DXA scan - total & hip
The grant will request funds to complete the following on the blood samples:
1. Repeat assessment (at each clinic) of sex hormones, glucose, insulin and lipids
2. Global and gene specific DNA methylation patterns.
B796 - Metabolic syndrome in adolescents Associations with dietary intakes circulating 25-hyrdroxyvitamin D and IGF-1 - 05/03/2009
The prevalence of metabolic syndrome (MetS) has been estimated anywhere from 2% to 9.4% for US
adolescents and varies depending on the definition used (1-3). A more recent report based on the National
Health and Nutrition Examination Survey (NHANES 1999-2002) estimated the prevalence of MetS as
high as 23% for overweight/obese children aged 12-18 years (4). MetS components in childhood are
carried into adulthood (5, 6). With the growing obesity epidemic and the positive relationship between
obesity and MetS (7), research aimed at understanding the risk factors for MetS in children is needed and
is likely to have important public health implications.
Diet is a known risk factor for MetS, although contributions of individual dietary components to MetS
remain relatively ambiguous for children and adolescents. In particular, associations between dairy intake
and MetS remain unclear, although several studies, mainly in adults, suggest a protective effect crosssectionally
(8-10) and prospectively (11, 12). The Coronary Artery Risk Development in Young Adults
(CARDIA) study, a 10-year prospective study, reported a lower incidence of MetS (OR: 0.28; 0.14-0.58)
among overweight individuals consuming the highest compared with the lowest dairy category (12).
Little information exists regarding this relationship in children and adolescents. A recent cross-sectional
study observed a decreased likelihood of MetS with higher frequency of dairy, fruit, and vegetable
consumption in children aged 6-18 years living in Iran (13).
Calcium and vitamin D are two major nutrients found in dairy products that may play a protective role
against MetS (10, 14-16). Serum 25-hydroxyvitamin D is used to assess overall vitamin D status. A few
population-based studies have found inverse associations between 25(OH) D and MetS (17, 18). Data
regarding the relationship between calcium, vitamin D, and MetS are limited for children. However, a
cross-sectional study of 217 obese children aged 7-18 years found that vitamin D insufficiency was
associated with several MetS risk factors including higher BMI and systolic blood pressure and lower
HDL-cholesterol concentrations (19). Therefore, examining the potential relationship between dietary
calcium, serum vitamin D and MetS may be important in understanding the associations.
Higher circulating levels of IGF-1 have been associated with risk of certain types of cancer such as
prostate cancer (20, 21), whereas lower levels have been related to other chronic conditions such as
obesity and MetS (22, 23). In several studies, IGF-1 has been positively associated with dairy and milk
intake (24-26). Rich-Edwards et al (27) reported results from two pilot studies examining associations
between milk intake and IGF-1 as follows: 1) Mongolian children showed significant increases in IGF-1
and other factors with whole milk intake over 1 month, and 2) girls living in Boston showed small
increases in IGF-1 when consuming lowfat milk compared with a vegetable-based milk substitute over a
1 week period; these findings were not statistically significant. Rogers et al (26) found that milk and
dairy intakes were associated with IGF-1 and its binding protein (IGFBP-3) concentrations for all
children and for boys after adjustment. These associations were no longer statistically significant after
additional adjustment for protein intake, suggesting that protein may be an important mediator in this
relationship. In that study, dairy intake was positively associated with leg length in boys but not in girls,
and it appeared that IGF-1 played a role in this relationship as the association was attenuated after
adjustment. The mechanism by which IGF-1 is related to milk consumption is not fully understood.
Possible explanations include the high protein content of milk and dairy (26, 28) and/or constituents in
milk that may not be degraded/deactivated during digestion, such as growth hormones used in milk
production (27). More research is needed to identify the exact mechanism by which milk intake increases
IGF-1 and other growth factors. A recent population-based study of 6,810 British subjects found that
serum 25(OH)D and IGF-1 concentrations were inversely associated with MetS. However, associations
with IGF-1 were not statistically significant for participants with the lowest vitamin D concentrations,
indicating that both need to be considered in future research studies (22). Research projects that consider
all of the nutrients and factors discussed above are needed, especially in child and adolescent populations.
B791 - Investigation of population prevalence and health consequences of structural genetic variants using genome-wide SNP data - 03/03/2009
We propose an analysis of the prevalence and health consequences of genetic variants that are not single nucleotide polymorphisms (SNPs). These include deletions, duplications, variations in copy number and translocations of parts of the genome, up to and including the duplication or deletion of whole chromosomes (monosomy, trisomy etc). Specific examples are: duplications/deletions of parts of genes such as the Haptoglobin duplicon (HP gene) and growth hormone receptor exon 3 insertion/deletion (GHR gene), large chromosomal alterations such as Prader-Willi syndrome (deletion of part of chromosome 15) and changes in chromosome number such as Klinefelter's syndrome (XXY, an additional sex chromsome), triple X syndrome (XXX, an additional sex chromosome) and Down's syndrome (three copies of chromsome 21). These types of genetic variation are not directly measured by current genome-wide SNP arrays, but can be inferred from the raw data, and present the opportunity to gain added value from existing data.
Experimental plan:
* Existing raw genotyping data from Illumina SNP genotyping performed at the Wellcome Trust Sanger Institute will be used
* Raw fluorescence data will be analysed for reductions or increases in total fluorscence across a number of genomically adjacent SNP tests (representing loss or gain of the DNA sequence containing those SNPs
* "Extended homozygosity" (regions where many SNPs appear to have two copies of one allele, rather than two different alleles) will also be identified - some of these will represent deletions
* Pairwise Hardy-Weinberg equilibrium will be used to identify distortions in genotype frequencies that might represent a "null allele" in the sample
* All identified variants will be "phenome-scanned" (i.e. tested against a range of phenotypes representative of all data available), and/or specifically analysed (if they affect a single gene for which the function is known). Whilst numbers may be small, the aim is to identify whether a genetic variant causes individuals to be in the "tail" of the population distribution for particular phenotypes
* Population frequencies of variants, and potentially differences in break-points, will be estimated. Further testing of DNA for breakpoint location and fine mapping is beyond the scope of the current application, but may be requested in the future
For phenotypic analyses a representative range of phenotypic data will be needed. We ask the committee to approve "all" phenotypes, as genomic analyses will inform the phenotypes to analyse on a case-by-case basis, and as such phenotype choice will be iterative. In each case we would wish to compare relevant phenotypes for those individuals with a genetic variant to the phenotype distribution or frequency in the rest of the ALSPAC cohort.
B793 - Association of childhood socioeconomic position at birth with adiposity and metabolic markers at age 9 and 15 - 25/02/2009
Adverse childhood socioeconomic position is associated with increased coronary heart disease (CHD) risk in later life,(1,2,3) and it has been suggested that this may, at least in part, be mediated by adiposity and its associated adverse metabolic and vascular changes. As well as being associated with future risk of CHD, individuals from poorer socioeconomic backgrounds in childhood have also been found to be more obese, more dyslipidaemic and more insulin resistant in adulthood than those from higher socioeconomic groups.( 4,5) Greater BMI and obesity in childhood and early adulthood have been shown in two very large studies to predict CHD risk in adulthood,( 6,7) but it is unknown whether this association is because of the tracking of BMI from childhood to adulthood (in which case interventions to prevent/treat obesity in adulthood might be an appropriate option) or whether permanent changes in metabolic and vascular function occur in childhood as a result of greater adiposity (in which case interventions in childhood would be paramount). A major problem with life course studies that identify associations of risk factors in childhood / early adulthood (socioeconomic position or BMI in the examples above) with future risk of adult diseases such as CHD, is that by definition the populations being studied experienced their childhood at least 5-6 decades ago and the relevance of these findings to contemporary populations of children, who live in very different circumstances, is unclear.
If the association of childhood adverse socioeconomic position with adult CHD risk from older birth cohorts is at least in part because those from poorer backgrounds in childhood were more obese and therefore experienced adverse metabolic consequences which resulted in long-term damage and increased susceptibility to future CHD risk, and if socioeconomic differentials in contemporary children were likely to have similar long term effects on future CHD risk, then one would expect to find socioeconomic differentials in adiposity and its associated adverse metabolic outcomes in contemporary cohorts of children.
Studies in contemporary populations of children from high income countries have shown socioeconomic differentials in adiposity, with those from more deprived socioeconomic backgrounds being more adipose.( 8,9) For example, in the European Heart Health Study children aged 9 and 15 from Denmark (high income country) whose parents were least well educated and who came from houses with the lowest income had larger waist circumferences and skinfold thicknesses and greater BMI than those from more educated parents and higher income families, though in two lower income countries (Estonia & Portugal) associations were in the opposite direction.(8) In that study socioeconomic differentials in lipids (HDLc, LDLc and triglycerides) and circulating insulin were in the directions that one would anticipate from the associations with adiposity, but few other studies have been able to examine socioeconomic differentials in a wide range of metabolic markers in a contemporary population of children. Of particular relevance to this application, it has also been show in ALSPAC that there is a clear social gradient (based on head of household social class at birth) of fat mass (with children of higher social class having a lower fat mass), but no gradient in lean mass.(9) Comparing these results to published studies using BMI the authors concluded that social inequalities in childhood obesity may have been underestimated in previous studies.(9) Our aims here are to extend that work by looking at other adiposity markers within ALSPAC and also metabolic and vascular risk factors. The lead author of that published paper (Andy Ness) is a co-applicant on this application and we would be happy to involve others who worked on those data on the papers that result from this application.
The aim of this proposal is to examine the association of socioeconomic position at birth with adiposity and metabolic markers in childhood at age 9.
Our specific objectives are:
1. Determine the magnitude of the association of head of household occupational social class, maternal educational attainment and parental educational attainment (as determined at birth) with BMI, waist circumference and DXA assessed fat mass at age 9.
2. Determine the magnitude of the association of head of household occupational social class, maternal education and paternal education (at birth) with blood pressure and circulating levels of insulin, HDLc, LDLc, triglycerides, apolipoprotein, adiponectin, leptin, CRP and IL6 at age 9.
3. To determine whether any associations in objective 2 are mediated by adiposity measurements.
In a second paper we would like to build on this first paper (whatever the findings) by completing the following objectives:
1. Determine the magnitude of the association of head of household occupational social class, maternal educational attainment and parental educational attainment (as determine at birth) with BMI, waist circumference and DXA assessed fat mass at age 15.
2. Determine the magnitude of the association of head of household occupational social class, maternal education and paternal education (at birth) with blood pressure and circulating fasting levels of insulin, HDLc, LDLc, triglycerides, apolipoprotein at age 15.
3. To determine whether any associations in objective 2 are mediated by adiposity measurements.
The rationale for this second paper is that the association of childhood BMI/obesity with future CHD risk (as shown in two very large study populations (6,7)) strengthens with older age at BMI assessment, suggesting that later childhood/early adulthood may be a more important risk period and/or that tracking of obesity into adulthood might be an important mechanism for the association of childhood adiposity with future CHD risk. There is also some evidence that the associations of childhood socioeconomic position with adiposity and metabolic and vascular risk factors increase with age. In the European Heart Health Study point estimates are larger at age 15 than 9 but the sample size it too small to determine whether these differences are statistically robust.
Our rationale for treating these as two separate papers is that (a) we believe there is sufficient data for two papers each with distinct and clear messages, with the second clearly building on the first; (b) the measurements at age 15 were on fasting samples, whereas those at 9 were not, and at age 9 a wider range of measurements (including leptin, adiponecting and markers of inflammation) have been completed than at 15 and we do not wish to distract from the messages of the paper by having in one paper to discuss these differences in detail (they will be discussed in the second paper).
Plan for completing work
1. DAL will put dataset together
2. DAL, LH & BG will agree analysis plan
3. LH will complete initial analyses with input from DAL & BG
4. LH will draft initial paper with input from DAL & BG
5. Other applicants on this proposal (and others they suggest as appropriate) will comment on draft and further revisions
References:
1. Galobardes B, Lynch JW, Davey Smith G. Childhood socioeconomic circumstances and cause-specific mortality in adulthood: systematic review and interpretation. Epidemiol Rev. 2004;26:7-21.
2. Galobardes B, Lynch JW, Davey Smith G. Is the association between childhood socioeconomic circumstances and cause-specific mortality established? Update of a systematic review. J Epidemiol Community Health. 2008 May;62:387-90
3. Galobardes B, Davey Smith G, Lynch JW. Systematic review of the influence of childhood socioeconomic circumstances on risk for cardiovascular disease in adulthood. Ann Epidemiol. 2006 Feb;16:91-104.
4. Davey Smith G, Hart C. Insulin resistance syndrome and childhood social
conditions. Lancet 1997;349:2845.
5. Lawlor DA, Ebrahim S, Davey Smith G. Socioeconomic position in childhood and adulthood and insulin resistance: cross sectional survey using data from the British women's heart and health study. BMJ 2002; 325:805-807
6. Baker JL, Olsen LW, Sorensen TI. Childhood body-mass index and the risk of coronary heart disease in adulthood. N Engl J Med 2007;357:2329-2337
7. Bjorge T, Engeland A, Tverdal A, Smith GD. Body Mass Index in Adolescence in Relation to Cause-specific Mortality: A Follow-up of 230,000 Norwegian Adolescents. Am J Epidemiol 2008;168:30-37
8. Lawlor DA, Harro M, Wedderkopp N, Andersen LB, Sardinha LB, Riddoch CJ, Page AS, Anderssen SA, Froberg K, Stansbie D, Davey Smith G. The association of socioeconomic position with insulin resistance among children from northern (Denmark), eastern (Estonia) and southern (Portugal) Europe: findings from the European Youth Heart Study. BMJ 2005;331:183-86.
9. Ness AR, Leary S, Reilly J, Wells J, Tobias J, Clark E, Davey Smith G, the ALSPAC Study Team. The social patterning of fat and lean mass in a contemporary cohort of children. International Journal of Pediatric Obesity 2006; 1:1, 59-61
Data required
1. SEP at birth (exposure) - occupational social class mother & father; education mother; education father
2. Adiposity measurements at age 9 (outcome 1): month and year of clinic; age of child at clinic; weight; height; waist circumference; DXA fat mass & lean mass from 9 year clinic
3. Metabolic and vascular measurements at age 9 (outcome 2): BP, lipids, insulin, adiponectin, leptin, CRP, IL6 from samples taken at 9 year clinic
4. Adiposity measurements at age 15 (outcome 1, second paper): month and year of clinic; age of child at clinic; weight; height; waist circumference; DXA fat mass & lean mass from 15 year clinic
5. Metabolic and vascular measurements at age 15 (outcome 2, second paper): BP, fasting lipids, insulin and glucose from samples taken at 15 year clinic
6. Potential confounding factors: Maternal and Paternal age at birth, ethnicity, maternal parity, maternal smoking in pregnancy, paternal smoking around time of birth/pregnancy, maternal pre-pregnancy BMI, paternal BMI around time of birth/pregnancy; child's sex.
B794 - Psychosocial aspects of maturation family functioning and substance use in adolescence - 24/02/2009
Aim: To identify whether pubertal timing moderates longitudinal associations between parent substance use, parent-child relationship quality and adolescent substance use.
Background: Early initiation of substance use has been associated with a more rapid progression to heavier use and abuse (Spear, 2000), has short- and long-term health implications (van den Bree, 2005) and can impact on individual and others' welfare through associations with increased risky behaviour (Patton et al., 2004). Understanding the psychosocial risk mechanisms that lead some adolescents to earlier initiation and heavier use of substances is arguably central to reducing the existing public health burden presented by frequent and/or excessive drinking and smoking. The quality of family relationships, parents' own substance use and the timing of pubertal maturation relative to one's peers are risk factors for substance use in adolescence. The potential interplay between these risk factors in influencing the use of cigarettes and alcohol in early to mid-adolescence is not well understood.
Children from homes characterised by poor family functioning and by parents own heavy substance use are at increased risk of substance use (Hawkins, Catalano & Miller, 1992; Engels et al., 2004). Family relationships that are non-supportive or characterised by conflict can undermine adolescents' ability to regulate their behaviour in a goal-oriented way, with self-regulation linked in turn to substance use (e.g. Brody & Ge, 2001). On the other hand, adolescents who smoke or drink regularly may incur parents' disapproval that in turn is linked to decreased expressions of warmth and affection by parents and increased conflict (Shelton et al., 2008).
The timing of the pubertal transition (compared to same-sex, same-age peers) is theorised to be an important determinant of the relationship between pubertal maturation and psychopathology (Graber et al., 1997). Early maturing adolescents may be more prone to experiencing difficulties because they are less well prepared for pubertal change (Peskin, 1973). Early pubertal timing is associated with the increased use as well as abuse of substances (e.g. Graber et al., 1997; Lanza & Collins, 2002; Orr & Ingersoll, 1995). Other studies, however, have also shown that late-maturing males begin to drink earlier and to smoke more than on-time maturing males (Graber et al., 1997; (Bratberg et al., 2007).
Early maturation is theorised to sensitise children to variations in parent mood and behaviour, which heightens risk for psychological adjustment problems (e.g. Ge et al., 2002). In addition, while pubertal maturation has been associated with negative emotions among adolescents, this emotionality may be partly attributed to parents who are not perceived to be sensitive to the adolescent's needs (Paikoff & Brooks-Gunn, 1991). Findings suggest a potential disparity between parent and adolescent expectations about the timing of developmental tasks in the families of off-time maturing boys and girls.
While previous research has independently identified early maturation, parent substance use and parent-child relationship quality as risk factors for adolescent substance use, it is not clear how domains of family functioning might interact with the timing of pubertal development to influence use of cigarettes and alcohol. In our analyses based on Addhealth data we found that the longitudinal association between parent-child relationship quality (assessed in 1995) and alcohol use (assessed one year later in 1996) was stronger for early than late maturing girls, in addition, we also found gender differences in the moderating influences of pubertal development on the associations between relations with the parents and adolescent substance use (Shelton and van den Bree, submitted).
The aim of the proposed research is to investigate in ALSPAC the transactional nature of longitudinal associations between the quality of parent-child relations, parent substance use and adolescent cigarette and alcohol use and to assess whether any such relationships are moderated by the timing of pubertal maturation as well as to further explore potential gender differences.
Analyses will involve structural equation models using maximum likelihood estimation in LISREL (Joreskog & Sorbom, 1996).
Data which we would like to use for this project are:
103 months of life (frequency of use of different alcoholic beverages)
115 months of life (parental awareness of child alcohol use)
140 months of life (parental awareness of child alcohol use)
157 months of life (frequency of use of different alcoholic beverages)
8 Years old Ever drunk without permission (antisocial behaviour questionnaire)- personal interview
10 Years old Ever drunk without permission (Antisocial behaviour questionnaire)- personal interview
11 Years old Got very drunk (sensation seeking questionnaire) - personal interview based
13 Years old Several question related to alcohol use, frequency of use, pattern of use, binge drinking, getting drunk, age started, usage by friends.
14 Years old Several question related to alcohol use, frequency of use, pattern of use, binge drinking, getting drunk, age started, usage by friends .
15 Years old Several question related to alcohol use, frequency of use, pattern of use, binge drinking, getting drunk, age started, usage by friends.
115 months of life (parental awareness of child cigarettes use)
140 months of life (parental awareness of child cigarettes use)
167 months (cigarettes use attitude) - questionnaire based
8 Years old Ever smoked - personal interview based
10 Years old Ever smoked - personal interview based
13 Years old Several question related to cigarettes smoking, frequency of use, pattern of use, age started, usage by friends.
14 Years old Several question related to cigarettes smoking, frequency of use, pattern of use, age started, usage by friends.
15 Years old Several question related to cigarettes smoking, frequency of use, pattern of use, age started, usage by friends.
Parental reports
97 months of life Cigarettes use/ Partner smoking/ Alcohol use
110 months of life Drug use/ Partner smoking/ Partner drinking
134 months of life Cigarettes use/ Partner smoking
145 months of life Cigarettes use/ Partner smoking/ Partner drinking
97 months of life Parent to child interaction (Enjoyment)
Partner's parent to child interaction (Parental enjoyment)
Parent to parent interaction (aggression, affection)
110 months of life Partner's parent to child interaction (Parental enjoyment)
Parent to parent interaction (activities together, satisfaction, rows, warmth, authority)
145 months of life Partner's parent to child interaction (Parental enjoyment)
Parent to parent interaction (activities together, satisfaction, rows, warmth, authority)
169 months of life Parent to child interaction (Parental involvement in child social life and parental awareness)
Timing of variables of pubertal development SPECIFIC CHILD BASED QUESTIONNAIRE "Growing and Changing" (including Tanner assessments).