Similar to the NCDS, the BCS is a birth cohort study that started life as a study focussing on perinatal mortality, in this case the British Births Survey (BBS) (Elliott and Shepherd 2006). The aim was to compare the results with those from the 1958 PMS. The BBS collected data from a cohort of 16571 children (this time from Northern Ireland as well as England, Scotland and Wales) born during a one week period in 1970, with the data collected by midwifes and linked with data from clinical medical records. This perinatal study was extended to a longitudinal study (through the combined efforts of the University of Bristol and the University of London), and the cohort children were further interviewed at the ages of 5, 10 and 16 to explore their physical, educational and social development. As with the NCDS, the BCS has continued to collect data throughout the life course, with data collected when the cohort children were 26, 30, 34, 38 and 42, with further surveys planned at ages 46 and 50. 9841 cohort members took part at age 42.
Similar to the NCDS, the BCS has several strengths, such as its large sample size and fact that it can be seen as being a true snapshot of the British population born in 19701. Additionally,
1 The birth survey extended to Northern Ireland (and therefore initially covered the whole of the UK), however
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compared to the NCDS, the BCS can be considered more ambitious in terms of data
coverage. Although there are several associated weaknesses, such as poor response rate at age 16, it is argued that overall the biases present in the observed sample should be
relatively minimal (Bynner and Joshi 2007). 2.3 Millennium Cohort Study
The MCS is a birth cohort study made up of a stratified sample of children born between 1st September 2000 and 31st August 2001 in England and Wales, and children born between 24th November 2000 and 11 January 2002 in Scotland and Northern Ireland. The only inclusion criteria was that the children needed to be living in the UK at age 9 months and eligible to receive child benefit (Plewis et al., 2007). In response to the renewed interest in evidence based policy by the Labour government, the MCS was developed as a multidisciplinary study to capture the influence of several markers of early family life on child health and
development throughout childhood (Hansen 2014).The MCS cohort children were first surveyed when they were around 9 months of age, and have been further interviewed at ages 3, 5, 7 and 11. The age 14 survey is expected to be released at some point in 2017, with further data collection planned at the age of 17. Although the main unit of observation is the cohort member, information is also collected at the household level. 20646 families were originally contacted, with just under 90% responding. The baseline sample in the first wave was 188272.
Given the problems with the older British cohort studies, such as the NCDS and BCS, the MCS was designed to have a number of significant new features while maintaining continuity with the older studies. For instance, the representation of the cohort was broadened to cover a sample of a whole year of births, and where possible, both the mother and the father were interviewed. Furthermore, the sample was stratified in order to make sure that ethnic groups and individuals born in deprived circumstances were sufficiently represented in the initial sample.
As argued by Connelly et al., (2014), the MCS has several other desirable properties. Firstly, the current sample is large (N=13287 at age 11), with levels of attrition relatively low as compared to other UK longitudinal studies. Secondly, the dataset is the first British birth
2 For a comprehensive description of the survey design, recruitment process and fieldwork please see Dex and
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cohort study to include all four countries of the UK, meaning that cross country comparisons can be conducted. Thirdly, the dataset has deliberately oversampled children from deprived backgrounds and ethnic minorities, in order to assess the outcomes from these often
underrepresented groups. Fourthly, the range of health and cognitive measures present in the MCS allows for the cohort child’s health and development to be studied in detail from an ecological perspective. Fifthly, the collection of standardised measures of pregnancy and early childhood outcomes means the MCS is an excellent resource with which to compare to other cohort studies both internationally and nationally, including the three previous UK based cohort studies (1946 Birth Cohort, NCDS and BCS). Finally, the MCS has collected extensive information regarding the cohort member’s family, allowing for studies examining the intergenerational transmission of parental factors on child outcomes.
Unlike the NCDS and BCS (which are self-weighting, given that they are snapshots of the British population born in specific weeks in 1958 and 1970), the MCS is a heavily stratified sample. In England, the population were stratified into three strata: an ‘ethnic minority’ stratum (where the proportion of ethnic minorities in the ward was at least 30% in the 1991 census), a ‘disadvantaged’ stratum (which contained the poorest 25% wards as predicted by the Child Poverty Index) and an ‘advantaged’ stratum, which contained children located in the remaining wards. For the rest of UK, the children were only split into the ‘disadvantaged’ and ‘advantaged’ strata, as there was not the requisite numbers of children from ethnic minorities to form an ‘ethnic minority’ stratum.
Given the splitting of the electoral wards into the three strata, the MCS sample was clustered by the characteristics of the particular electoral wards in order to keep fieldwork costs down and to take into account neighbourhood-level effects. The initial MCS sample was randomly selected only within the specific strata and clustering areas, resulting in a disproportionally stratified cluster sample (Plewis et al., 2007). Due to the stratified nature of the sample, it is argued that it is important, where possible, to adjust the data in order to provide accurate estimates and robust standard errors (Connelly 2014). The MCS provides a range of sample design and probability weights in order to correct for MCS cases having unequal probabilities of selection that result from the stratified cluster sample design, which are relatively straightforward to implement.
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The UKHLS is a longitudinal study of national representative private households, designed to capture life in the UK and how it changes over time. The survey (which began collecting data in 2008) replaced the British Household Panel Survey (BHPS), and is part of an international network of studies including the German Socioeconomic Panel, the Swiss Household Panel, and various other household studies from Australia, Canada, South Africa, USA, Korea and China (Buck and McFall 2011). The design of the UKHLS means the survey provides
information regarding a wide range of policy relevant factors, for example labour market outcomes such as unemployment, household factors such as marriage, and individual outcomes such as health and well-being.
The total sample in the first wave of the UKHLS was 39802 households, marginally below the target sample of 40000 households. The number of individuals in the total sample of the first wave was 101086, including children. The survey has continued to collect information on an annual basis regarding each household’s social and economic circumstance, employment, family life and health, amongst other factors.
In order to achieve such a large sample, various sampling strategies were used. The general population sample was a stratified, clustered sample of the entire residential population of the UK, drawn from the national postcode address file. The Northern Ireland sample was unclustered, with addresses drawn systematically from the Land and Property Agency List. The primary sampling units (PSUs) used in the dataset were stratified by geographical region, population density and ethnic minority density respectively. In the initial sample, 18
addresses were systematically selected from each of the 2640 postal sectors, resulting in an initial sample of 47520 households, rising to 49920 households once the addresses from Northern Ireland were also incorporated. Several other smaller sampling strategies have also been used, including an ethnic minority boost, an innovation panel (used mainly to test novel methods of data collection) and the incorporation of previous BHPS sample members. There are several distinctive features of the household panel design which give it an
advantage as compared to cohort studies. Firstly, while a birth cohort study such as the NCDS or the BCS is representative of one particular cohort, a household panel such as the UKHLS is representative of the whole population, and therefore eliminates the impact of cohort effects. Secondly, following households rather than individuals allows for the
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investigation of factors that occur at the household level, such as economic welfare, the inter relationships between individuals within the household and changes in household composition.
There are also several key important features specific to UKHLS. For example, it is clearly a very large sample size, allowing researchers to explore issues other longitudinal surveys would be unable to do, such as analysis of small subgroups and regional variation. Secondly, the study specifically focuses on several factors related to ethnicity, diversity and
commonality, and boosts the ethnic minority population of the survey. Finally, it is possible to link the UKHLS to several other data sources, including education data (specifically Key Stage 1 and Key Stage 2 results), localised spatial data and various biomedical measures for a sub-sample of the panel.
Like its predecessor, the BHPS, the UKHLS has a very complex sampling design, and subsequently the associated weighting strategy is also complex (Buck and McFall 2011). A variety of household and individual weights are provided by the UKHLS for use in empirical analysis, in order to account for factors such as the probability of selection and non-
response, as well as to make the sample distribution a closer match to the UK population distribution.
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