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The Millennium Cohort Study: the making of a multi-purpose resource for social science and policy

October 2016
Longitudinal and Life Course Studies 7(4)

October 2016
7(4)

DOI:10.14301/llcs.v7i4.410

Authors:

Heather Joshi

University College London

Emla Fitzsimons

University College London

This paper gives an account of the origins, objectives and structure of the Millennium Cohort Study (MCS) – some 19,000 individuals born in the UK in 2000-2001 – and its use in a wide range of research on many aspects of their lives in childhood years. We highlight some of the mass of output on the first five surveys to age 11 in 2012. Topics discussed are social inequalities in child development; comparisons with other cohorts; areas not well covered by previous national cohorts: season of birth, fathers, ethnicity and childcare; parental behaviour; intergenerational links; social ecology and differences between and within UK countries. We also discuss the challenges faced by the National Evaluation of Sure Start (NESS) in drawing controls from the MCS. As the cohort marches to its seventh survey in 2018, and beyond, the potential for research across life course domains will only continue to grow.

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Longitudinal+and+Life+Course+Studies+2016+Volume+7+Issue+4+Pp+409+–+430+++++++++ISSN+1757-9597+

409$

The$UK$Millennium$Cohort$Study:$the$making$of$a$multi-

purpose$resource$for$social$science$and$policy$$

Heather$Joshi$University*College*London*Institute*of*Education,*UK*

h.joshi@ucl.ac.uk

Emla$Fitzsimons$ University*College*London*Institute*of*Education,*UK$

Received*February*2016*****Revised*May*2016)*

*http://dx.doi.org/10.14301/llcs.v7i4.410*

Abstract

This%paper% gives%an% account%of% the%origins,% objectives%and% structure%of%the% Millennium%Cohort%Study%

(MCS)%–%some%19,000% individuals% born%in% the% UK%in%2000-2001% –% and% its% use% in% a% wide% range% of%

research%on%many%aspects%of%their%lives%in%childhood%years.%We%highlight%some%of%the%mass%of%output%

on% the% first% five% surveys% to% age% 11% in% 2012.% Topics% discussed% are% social% inequalities% in% child%

development;%comparisons%with%other%cohorts;%areas%not%well%covered%by%previous%national%cohorts:%

season% of% birth,% fathers,% ethnicity% and% childcare;% parental%behaviour;%intergenerational%links;%social%

ecology%and%differences% between%and%within% UK%countries.%We% also%discuss%the% challenges% faced%by%

the% National% Evaluation% of% Sure% Start%(NESS)%in% drawing% controls% from% the%MCS.% As% the% cohort%

marches% to% its% seventh%survey% in% 2018,% and% beyond,% the% potential% for% research% across% life% course%

domains%will%only%continue%to%grow.%%

Keywords$

Millennium*Cohort*Survey,*life*course*inequalities,*Sure*Start,*neighbourhood*effects,*UK*regions*

Introduction$

*****The*UK* inaugurated*a* new*national*cohort*study*

to*greet*the*new*millennium*with*an*investment*in*

a*multi-purpose*data* resource.**The*study*has* now*

run* for* six* sweeps – at ages nine*months,* three,*

five,*seven,*11*and*14*years*–**and*is*preparing*for*a*

seventh*follow-up* at* age* 17.* * The* scale* of* the*

resource* and* its* variety* means* that* a* complete*

story* would* extend* well* beyond* the* scope* of* a*

single* article.* Indeed* a* profile* of* the* Millennium*

Cohort* (MCS)* up* to* its* fifth* sweep*at* age* 11*has*

already* been* published,* focussing* on* its* potential*

use* for* epidemiological* research*(Connelly* &* Platt,*

2014).* *The* aim* of* this* article* is*to* explain* to*

potential* users* how*the*objectives,* structure* and*

content*of*the* study*were*shaped*by*the*history*of*

its* forerunners* in* previous* British* cohorts* and*by*

the* context* of*its*funding.**Its* primary*goal*was*to*

create* a* rich* and* easily* accessible* scientific*

resource,* shaped* by* expert* input.* It* aimed* to*

provide* continuity* with* the*past* and* to* reflect* the*

present.* The* purpose* of* this* paper* is* to* provide*

information* on* its* background* for*users* of* the*

resource.* This* should* also* be* useful* for*anyone*

contemplating* founding* a* cohort* study* in* the*

future.* In*reviewing*how* objectives* have* so* far*

been*met,*we*hope*to*indicate*the*scope*for*further*

analysis.*

*****Cohort* studies* have* come* to* be* regarded* as* an*

important* way* for* research* and* policy* to* take*

account*of*the* life*course*–*the*sequence*of*events*

and* experiences* in* individual* lives*through* a*

number* or* domains,* in* the* context* of* historical*

developments* at* the* level* of* society*(Elder,* 1985).*

A* framework* recognising* the* family* and*social*

contexts* that* surround* individual* development*

(Bronfenbrenner,* 1979)* also* contributed*

intellectual* underpinning* for* the* multi-dimensional*

approach*taken*by* MCS.** It*was*always*intended* to*

Heather+Joshi,+Emla+Fitzsimons+++++++The+Millennium+Cohort+Study:+the+making+of+a+multi+purpose+resource…+

410$

serve*multiple*purposes,*which*themselves* grew*as*

the* sources* of* funding* increased.* The* study’s*

objectives,*listed*in*box*1,*emerged*over*its*first*few*

years.*The* first*six* were*incorporated*in*the* project*

as* initially* funded* by* the* Economic* and* Social*

Research* Council* (ESRC).* * Co-funding* by*

Government* departments* enhanced* the* resources*

available*to*achieve*these*six*aims.*It*also*extended*

the* scope* of* the* study* to* three*further* objectives,*

seven*to*nine**in*box*1.*

Box$1:$MCS$Objectives$(from$MCS$report$to$funders,$2001)$

1. To*chart*the*initial*conditions*facing*new*children*in*the*new*century*in*terms*of*

social,*economic*and*health*advantages*and*disadvantages,*building*evidence*for*

future*research*on*individual*development.*

2. To*provide*a*basis*for*comparing*processes*of*development*with*the*preceding*

British*cohorts.**

3. To*collect*information*on*previously*neglected*topics,*such*as*the*role*of*fathers,*

non-parental*childcare*and*ethnicity.*

4. To*focus*on*the*experience*and*aspiration*of*the*children’s*parents*as*the*immediate*

‘background’,*of*the*child’s*early*years*

5. To*emphasise*intergenerational*links*including*those*back*to*the*parents’*own*

childhood.*

6. To*investigate*the*wider*social*ecology*of*the*family:*social*networks,*civic*

engagement,*community*facilities*and*services,*splicing*in*geo-coded*data*as*

available.**

7. To*cover*the*whole*of*the*United*Kingdom,*providing*big*enough*samples*for*

analysis*within*Wales,*Scotland*and*Northern*Ireland.*

8. To*provide*evidence*for*use*in*the*National*Evaluations*of*Sure*Start*and*of*the*

Children’s*Fund.*

9. To*enhance*the*content*of*the*survey*by*collecting*data*from*sources*beyond*survey*

interviews,*drawing*on*supplementary*sources*of*funding*if*necessary.*

*****Our* first* section*gives* an* account* of* the* early*

history*of*the*study*around* 2000-2001.*The*second*

describes*the*building*up*of*the*data*resource*since*

then,* summarised* in* table* 1.* * The* third*section*

reviews*some*results*that*have*emerged*in* relation*

to*the*first*seven*objectives,*and*also*addresses*the*

eighth* objective* –* the* study’s* novel* use* in* impact*

evaluations.**

*****We*leave*a*detailed*treatment*of*objective*nine,*

enhancements,* beyond* the* scope* of* this* paper.*

There* have* been* a* number* of* ways* in* which*

supplementary* information* has* been* drawn* into*

the* database,* indicated* in* table* 1.* Its* funding* has*

tended* to* be* ‘added-on’,* mainly* from* government*

funders.* * These*include* an* important* and* growing*

set*of*consented*linkages*to*administrative*records,*

which*will*continue*to*be*an*important*part*of*the**

study.**In* due* course* these* linkages* of*

administrative* records* to* the* study* should* yield*

enough* material* for* a* separate* account,* including*

the* challenges* that* have* been* faced* in* their*

implementation.**Likewise,* the* collection* of*

biomedical*samples* and* measurements* (such* as*

height,* weight* and* physical* activity)* are* not*

discussed* here.**Some* of* them* are* described* by*

Connelly* and* Platt*(2014)*and* others* are* ongoing.**

Though* their* story* is* not* told* here,* both* types* of*

enhancement* add* greatly* to* the* wealth* and*

complexity*of*this*multi-faceted*asset.*

*****Box* 2* points* towards* further* information* about*

the* MCS*datasets*and* research* using* them.* An*

appendix* provides* further* detail* of* the* innovative*

use*of*MCS*in*the*National*Evaluation*of*Sure*Start.*

Heather'Joshi,'Emla'Fitzsimons''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''The'Millennium'Cohort'Study:'the'making'of'a'multi'purpose'resource…'

411#

Table#1.#UK#Millennium#Cohort#Study#(MCS):#main#sources#of#information#

Born#2000/01#a#

Fieldwork*

2001/2*

2003/4'

2006'

2008'

**************2012*

2015'

Age##

(Sweep)#

Collection#

#Mode#

(see#note)#

9*months**

(MCS1)*

3*years**

(MCS2)*

5*years**

(MCS3)*

7*years**

(MCS4)*

11*years**

(MCS5)*

14*years**

(MCS6)*

Source#

Mother*

Mother**

Mother*

Resident*partner*

Resident*partner**

Resident*partner*

c**

Assessments**

Assessments*

Height/weight*

+waist*circumference*

+waist*

circumference/body*fat*

+body*fat*

Cohort*member*

Biological*samples*

Accelerometry*

Accelerometry**

Time*use*diary*

********Older*siblings*

Older*siblings*

Teacher*

Birth*registration*

School*recordsl*

School*records*m*

School*recordsm*

Hospital*recordsn*

Size*

18,818*

15,808*

15,460*

14,043*

13,469*

11,938*

Response*rate*%*p*

96.4*

81.0*

79.2*

72.0*

69.0*

61.2*

Heather'Joshi,'Emla'Fitzsimons''''''''The'Millennium'Cohort'Study:'the'making'of'a'multi'purpose'resource…'

412$

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Acknowledgements$

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)

References$

O($;JI=)e"=)H($AK%;A=)#"=)O!,-(;=)e"=)[(I$!-5=)S"=)T+C!-%KJ=)E")9).A()@#>>)T(;(!,?A)b(!C")8344N<")#**(?.;)+*)

>K,(;.!,.)[+?!$)V,+&,!CC(;)+-)MA%$5,(-)!-5)]!C%$%(;P)#!,$I)]%-5%-&;")@%2"2'#&A$/20-*&B1(%,-*=)CC<=)

0Y^NG0Y^7")A..DP115`"5+%"+,&104"006N1'CU"677Z6"YZ0^Y7"3])))))

O($;JI=)e"=)[(I$!-5=)S"E"=)O!,-(;=)e"=)9)H($AK%;A=)#")83442<")>K,()>.!,.)%-)#-&$!-5")D-,0$"6&CECG)670")

A..DP115`"5+%"+,&104"040N1;40Y4GN^6N842<N4063G`)

Oo?!,(;=)["=)@!f,++=)e")9)X($$I=)j")8340Z<"))S)$+-&%.K5%-!$)(`!C%-!.%+-)+*)C!.(,-!$=)*!C%$I=)!-5)!,(!G$(F($)

(`D(,%(-?(;)+*),!?%;C)+-)?A%$5,(-\;);+?%+(C+.%+-!$)5(F($+DC(-.P)V!..(,-;)!-5)D+;;%'$()

(`D$!-!.%+-;"))F102-*&F02$,0$&G&A$/202,$=)=H6)037a06Z")

A..DP115`"5+%"+,&104"040N1U";+?;?%C(5"340Z"47"43Z)

O$!-5(-=)e")9)H!?A%-=)>")83447<")WD)!-5)5+/-).A()&(-(,!.%+-!$)%-?+C()$!55(,)%-)O,%.!%-P)D!;.)?A!-&(;)!-5)

*K.K,()D,+;D(?.;")I-"21,-*&J,'"2"("$&K01,1+20&L$52$M=)<N>O=<=)040G00N")

A..DP115`"5+%"+,&104"00^^1443^2Z404742NZ2Y)

O,!5'K,I=)O"=)M+,!J=)H"=):!$5*+&($=)e")9):!;A',++J=)#")8340Z<)P11&A-,.&;#2*/%$,&D$8"&@$#2,/:&P#$&Q:F:&

R0#2$5$+$,"&S-)&2,&;1+)-%-"25$&T$%')$0"25$:&@(/)j+,JP)TK;;($$)>!&()]+K-5!.%+-"))))

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82,/2,U'&8%1+&"#$&RU$&==&'(%5$.:)[+-5+-P)M(-.,()*+,)[+-&%.K5%-!$)>.K5%(;")

M!$5(,/++5=)[")83406<")bA(),+$()+*),(;D+-5(-.)?A!,!?.(,%;.%?;)%-).,!?J%-&)+-)$+-&%.K5%-!$);K,F(I;P)(F%5(-?()

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M,!/*+,5=) M"=) [") R(!,5(-) 9) h,(!F(;) #") 8340Y<")bA() 5,%F(,;) +*) C+-.AG+*G'%,.A) 5%**(,(-?(;) %-) ?A%$5,(-\;)

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Heather'Joshi,'Emla'Fitzsimons''''''''The'Millennium'Cohort'Study:'the'making'of'a'multi'purpose'resource…'

428$

Appendix$$

The$role$of$MCS$in$the$national$evaluation$of$Sure$Start$$

)))))>K,()>.!,.)/!;)!);(.)+*)!,(!G'!;(5)D,+&,!CC(;)+*);(,F%?(;)*+,)?A%$5,(-)K-5(,)*+K,)%-).A()C+;.)5(D,%F(5)

$+?!$)!,(!;)%-)#-&$!-5=),+$$(5)+K.)'(./((-)0222)!-5)3446")B.);.!,.(5)%-)N4)>K,()>.!,.)$+?!$%.%(;)%-)0222=)

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.A()'(;.)(**+,.;)+-).A()D!,.)+*).A()(F!$K!.%+-).(!C).+)+F(,?+C().A(C=).A(;()?A!$$(-&(;)/(,()+*.(-)

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Choice$of$control$groups$

)))))bA()?,%.%?!$)'(5,+?J)+*)!-)%CD!?.)(F!$K!.%+-)%;).A()?A+%?()+*)!);K%.!'$()?+-.,+$)&,+KD")bA(),!D%5)(`D!-;%+-)

+*).A()>>[V;)$%C%.(5).A()!F!%$!'%$%.I)+*)D+;;%'$()?+-.,+$)!,(!;")B-)3443=)'(*+,()!-I),(;K$.;)/(,()!F!%$!'$(=).A()

.!,&(.)-KC'(,)+*)>>[V;)*+,)344Y)/!;)5+K'$(5"))d-()?A!$$(-&()/!;).A!.)>K,()>.!,.)!,(!;)/(,()C+,()

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+K.).A!.).A()_%CD!?.\)+*).A()D,+&,!CC(),(*$(?.;).A()%-*$K(-?()+*)+.A(,)5%**(,(-?(;)'(./((-).A()!,(!;)

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-+.)D+;;%'$().+)*%-5);K%.!'$()?+-.,+$)!,(!;)*+,).A()Z^)C+;.)5(D,%F(5)+*).A()>K,()>.!,.)!,(!;)8+*)!).+.!$)+*)0Z4)

!F!%$!'$()*+,)(F!$K!.%+-)*,+C),+K-5;)+-().+)*+K,)+*)>K,()>.!,.<=);+)+F(,)+-().A%,5)+*).A(C)A!5).+)'()(`?$K5(5)

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+*).A()0Z4<)!-5)0=7^2)?A%$5,(-)%-)^3)-+-G>>[V)!,(!;")

Data$collection$

)))))]+,)./+);(D!,!.();.K5%(;)/%.A)5%;.%-?.)+'U(?.%F(;).+).,!?J)(!?A)+.A(,)%;)(`.,(C($I)?A!$$(-&%-&=)(F(-)%-).A()

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?++,5%-!.%+-)%;)5%**%?K$.).+);K;.!%-)!-5)$%J($I).+)*!5()+K.)%-)C(5%KC).+)$+-&).(,C=),(-5(,%-&).A()(;.%C!.%+-)+*)

$+-&),K-)(**(?.;)%CD+;;%'$(")bA()@#>>)!-5)HM>),(;(!,?A).(!C;)?++,5%-!.(5)?$+;($I)*,+C).A()+K.;(.=).A+K&A)

;+C()D,+'$(C;=);+C()K-*+,(;((-=)?+K$5)-+.)'()+F(,?+C("))

&&&&&B-)'+.A);.K5%(;=)*!C%$%(;)/(,()F%;%.(5)/A(-).A()?A%$5)/!;)-%-()C+-.A;)+$5=).A,((=)*%F()!-5);(F(-)I(!,;)+*)

Heather'Joshi,'Emla'Fitzsimons''''''''The'Millennium'Cohort'Study:'the'making'of'a'multi'purpose'resource…'

429$

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.A!.).A()@#>>);!CD$()/!;)'+,-)./+)I(!,;)!*.(,).A()HM>=)!-5).A().%C%-&)+*)5!.!)?+$$(?.%+-;)/!;)-+.)!$%&-(5")

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Other$considerations$

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How to mitigate selection bias in COVID-19 surveys: evidence from five national cohorts

Preprint

Full-text available

Mar 2024

Background: Non-response is a common problem, and even more so during the COVID-19 pandemic where social distancing measures challenged data collections. As non-response is often systematic, meaning that respondents are usually healthier and from a better socioeconomic background, this potentially introduces serious bias in research findings based on COVID-19 survey data. The goal of the current study was to see if we can reduce bias and restore sample representativeness despite systematic non-response in the COVID-19 surveys embedded within five UK cohort studies using the rich data available from previous time points. Methods: A series of three surveys was conducted during the pandemic across five UK cohorts: National Survey of Health and Development (NSHD, born 1946), 1958 National Child Development Study (NCDS), 1970 British Cohort Study (BCS70), Next Steps (born 1989-90) and Millennium Cohort Study (MCS, born 2000-02). We applied non-response weights and utilised multiple imputation, making use of covariates from previous waves which have been commonly identified as predictors of non-response, to attempt to reduce bias and restore sample representativeness. Results: Response rates in the COVID-19 surveys were lower compared to previous cohort waves, especially in the younger cohorts. We identified bias due to systematic non-response in the distributions of variables including parental social class and childhood cognitive ability. In each cohort, respondents of the COVID-19 survey had a higher percentage of parents in the most advantaged social class, and a higher mean of childhood cognitive ability, compared to the original (full) cohort sample. The application of non-response weights and multiple imputation was successful in reducing bias in parental social class and childhood cognitive ability, nearly eliminating it for the former. Conclusions: The current paper demonstrates that it is possible to reduce bias from non-response and to a large degree restore sample representativeness in multiple waves of a COVID-19 survey embedded within long running longitudinal cohort studies through application of non-response weights or multiple imputation. Such embedded COVID-19 surveys therefore have an advantage over cross-sectional COVID-19 surveys, where non-response bias cannot be handled by leveraging previously observed information on non-respondents. Our findings suggest that, if non-response is appropriately handled, analyses based on the COVID-19 surveys within these five cohorts can contribute significantly to COVID-19 research, including studying the medium and long-term effects of the pandemic.

Chronotype and depression in adolescence: Results from a UK birth cohort study

Article

Full-text available

May 2024

Background Research has established a bidirectional association between sleep disturbances and depression in both adults and youth, as well as links between depression and circadian rhythms and chronotype, predominantly in adult populations. However, the link between chronotype and depression in the general adolescent population, independently of poor sleep and prior mental health problems, remains unclear. Methods This study investigated the association between time‐to‐sleep (TTS) and depressive symptoms in middle adolescence (age 14 years) using data from a large, nationally representative birth cohort from the UK. The relationship between TTS and self‐reported number of depressive symptoms was adjusted for individual, family, and neighborhood characteristics, including sleep quality, earlier mental health, diet and family meal routines, body‐mass index, screen time, physical activity, chronic illness, special educational needs, peer victimization, socioeconomic status, maternal mental health, area safety and the built environment (air pollution). Results An “evening” chronotype was positively associated with depressive symptoms, and biological sex moderated this association—with eveningness being more strongly related to depressive symptoms in females. TTS inconsistency between non‐school and school nights was associated with depressive symptoms and sleeping later on non‐school nights predicted fewer depressive symptoms. The results were robust to further sensitivity analyses that used the sleep midpoint on non‐school nights and controlled for sleep duration. Limitations This was a correlational study. The independent and dependent variables were self‐reported, and there was no clinical screening for sleep disorders. The TTS variables were provided in crude hour slots. Conclusions A robust association was found between evening chronotype and depressive symptoms in middle adolescence, even after adjustment for a wide range of confounders. Eveningess and depressive symptoms were more strongly associated in females.

Causal Relationships in Longitudinal Observational Data: An Integrative Modeling Approach

Article

Full-text available

Apr 2024

Much research in psychology relies on data from observational studies that traditionally do not allow for causal interpretation. However, a range of approaches in statistics and computational sciences have been developed to infer causality from correlational data. Based on conceptual and theoretical considerations on the integration of interventional and time-restrainment notions of causality, we set out to design and empirically test a new approach to identify potential causal factors in longitudinal correlational data. A principled and representative set of simulations and an illustrative application to identify early-life determinants of cognitive development in a large cohort study are presented. The simulation results illustrate the potential but also the limitations for discovering causal factors in observational data. In the illustrative application, plausible candidates for early-life determinants of cognitive abilities in 5-year-old children were identified. Based on these results, we discuss the possibilities of using exploratory causal discovery in psychological research but also highlight its limits and potential misuses and misinterpretations.

Dissecting the contribution of common variants to risk of rare neurodevelopmental conditions

Preprint

Full-text available

Mar 2024

Although rare neurodevelopmental conditions have a large Mendelian component, common genetic variants also contribute to risk. However, little is known about how this polygenic risk is distributed among patients with these conditions and their parents, its interplay with rare variants, and whether parents' polygenic background contributes to their children's risk beyond the direct effect of variants transmitted to the child (i.e. via indirect genetic effects potentially mediated through the prenatal environment or 'genetic nurture'). Here, we addressed these questions using genetic data from 11,573 patients with rare neurodevelopmental conditions, 9,128 of their parents and 26,869 controls. Common variants explained ~10% of variance in overall risk. Patients with a monogenic diagnosis had significantly less polygenic risk than those without, supporting a liability threshold model, while both genetically undiagnosed patients and diagnosed patients with affected parents had significantly more risk than controls. In a trio-based model, using a polygenic score for neurodevelopmental conditions, the transmitted but not the non-transmitted parental alleles were associated with risk, indicating a direct genetic effect. In contrast, we observed no direct genetic effect of polygenic scores for educational attainment and cognitive performance, but saw a significant correlation between the child's risk and non-transmitted alleles in the parents, potentially due to indirect genetic effects and/or parental assortment for these traits. Indeed, as expected under parental assortment, we show that common variant predisposition for neurodevelopmental conditions is correlated with the rare variant component of risk. Our findings thus suggest that future studies should investigate the possible role and nature of indirect genetic effects on rare neurodevelopmental conditions, and consider the contribution of common and rare variants simultaneously when studying cognition-related phenotypes.

A data-driven approach to understanding non-response and restoring sample representativeness in the UK Next Steps cohort

Article

Full-text available

Feb 2024

Non-response is common in longitudinal surveys, reducing efficiency and introducing the potential for bias. Principled methods, such as multiple imputation, are generally required to obtain unbiased estimates in surveys subject to missingness which is not completely at random. The inclusion of predictors of non-response in such methods, for example as auxiliary variables in multiple imputation, can help improve the plausibility of the missing at random assumption underlying these methods and hence reduce bias. We present a systematic data-driven approach used to identify predictors of non-response at Wave 8 (age 25–26) of Next Steps, a UK national cohort study that follows a sample of 15,770 young people from age 13–14 years. The identified predictors of non-response were across a number of broad categories, including personal characteristics, schooling and behaviour in school, activities and behaviour outside of school, mental health and well-being, socio-economic status, and practicalities around contact and survey completion. We found that including these predictors of non-response as auxiliary variables in multiple imputation analyses allowed us to restore sample representativeness in several different settings, though we acknowledge that this is unlikely to universally be the case. We propose that these variables are considered for inclusion in future analyses using principled methods to explore and attempt to reduce bias due to non-response in Next Steps. Our data-driven approach to this issue could also be used as a model for investigations in other longitudinal studies.

Marriage and GCSE results

Article

Full-text available

May 2023

The importance of family economics (e.g. incomes) is well known and well represented in research and government policy on education. What is frequently overlooked in both research and policy discussions is the importance of marriage and family relationships.  Using new GCSE data from the Millennium Cohort Study, we analysed the probability that 17-year-old children did not achieve Maths and English GCSE to nationally accepted pass levels.  In our sample of 6,346 children born between 2000 and 2002, we found that 30% of boys and 24% of girls did not achieve that level in both Maths and English GCSEs.  Among the 5,145 children born to couples, the probability of passing both Maths and English GCSE at grade C/4 or above was influenced uniquely for boys by his mother's education level and his closeness to his mother at age 14; and for girls by whether her mother was married when she was born, her mother's housing tenure soon after she was born, and whether her parents were still together when she was aged 17.  In summary, family economics has a unique influence on exam results for both boys and girls. For boys only, family relationships also matter. For girls only, family structure matters. What had no effect were factors related to family 'culture' (ethnicity, religion, grandparent status), mother's relationship choices (ante-natal classes, planned pregnancy, other partners), and parent relationship timing (age, time co-resident, birth order).  In a separate analysis that included children born to single mothers, we found their weaker results were related to family economics and not to being a single mother per se.  This robust analysis shows the importance of both family economics and family relationships on subsequent GCSE results. In particular, these findings emphasise the central role of marriage on educational outcomes for girls. After taking into account factors that included mother's ethnicity, age, income and happiness, girls whose parents never married were significantly less likely to pass both Maths and English GCSEs. On the other hand, boys were significantly less likely to pass both Maths and English GCSEs if his mother had not passed her own GCSEs/O-levels and more likely if she had a university degree.

Estimating the impact of transmitted and non-transmitted psychiatric and neurodevelopmental polygenic scores on youth emotional problems

Article

Full-text available

Nov 2023

Anxiety and depression (emotional disorders) are familial and heritable, especially when onset is early. However, other cross-generational studies suggest transmission of youth emotional problems is explained by mainly environmental risks. We set out to test the contribution of parental non-transmitted genetic liability, as indexed by psychiatric/neurodevelopmental common polygenic liability, to youth emotional problems using a UK population-based cohort: the Millennium Cohort Study. European (N = 6328) and South Asian (N = 814) ancestries were included, as well as a subset with genomic data from both parents (European: N = 2809; South Asian: N = 254). We examined the association of transmitted (PGST) and non-transmitted polygenic scores (PGSNT) for anxiety, depression, bipolar disorder and neurodevelopmental disorders (attention-deficit/hyperactivity disorder [ADHD], autism spectrum disorder [ASD], schizophrenia) with youth emotional disorder and symptom scores, measured using the parent- and self-reported Strengths and Difficulties Questionnaire emotional subscale at 6 timepoints between ages 3–17 years. In the European sample, PGST for anxiety and depression, but not bipolar disorder, were associated with emotional disorder and symptom scores across all ages, except age 3, with strongest association in adolescence. ADHD and ASD PGST also showed association across ages 11–17 years. In the South Asian sample, evidence for associations between all PGST and outcome measures were weaker. There was weak evidence of association between PGSNT for anxiety and depression and age 17 symptom scores in the South Asian sample, but not in the European sample for any outcome. Overall, PGST for depression, anxiety, ADHD and ASD contributed to youth emotional problems, with stronger associations in adolescence. There was limited support for non-transmitted genetic effects: these findings do not support the hypothesis that parental polygenic psychiatric/neurodevelopmental liability confer risk to offspring emotional problems through non-transmitted rearing/nurture effects.

MULT: An allometric body mass index (ABMI) reference to assess nutritional status of multi-ethnic children and adolescents

Preprint

Full-text available

Jun 2024

Objectives: To develop an allometric body mass index (ABMI) reference that adjusts the weight in relation to height, taking into account the changes during development (MULT ABMI reference), and to compare it with international BMI references. Methods: The MULT ABMI reference was constructed through the LMS method, calculated with 65 644 ABMI observations of 17 447 subjects aged 5-22 years, from the United Kingdom, Ethiopia, India, Peru, Vietnam, Portugal, and Brazil. The M, S, and L curves of the MULT ABMI reference were compared with the curves of the MULT, World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), International Obesity Task Force (IOTF), and Dutch Growth Study (DUTCH). Results: The greater differences in the M curve between MULT ABMI and WHO, CDC, IOTF, DUTCH, and MULT BMI references were around puberty (138 to 150 months for boys; 114 to 132 for girls). MULT ABMI presented S values similar to IOTF and DUTCH BMI references for boys 60 to 114 months and then became higher, approaching the MULT BMI S values from 198 to 240 months. For girls the MULT ABMI S values were close to the IOTF, CDC, and DUTCH from 60 to 110 months, and then became higher, approaching the MULT BMI S values until 240 months. Conclusion: MULT ABMI presented an advantage in comparison to the existing BMI references because it takes into account the growth changes during puberty and is a new option to assess the nutritional status of multi-ethnic populations.

Bullying fosters interpersonal distrust and degrades adolescent mental health as predicted by Social Safety Theory

Article

Feb 2024

Pubertal development at age 14 is associated with male adolescents' combustible cigarette smoking and dual use, but not with e-cigarette use - Findings from the UK Millennium Cohort Study

Article

Nov 2023

Millennium Cohort Study First Survey: A User’s Guide to Initial Findings

Book

Full-text available

Jan 2004

Children of the new century: mental health findings from the Millennium Cohort Study

Book

Full-text available

Nov 2015

Moving home in the early years: What happens to children in the UK?

Article

Full-text available

Jul 2016

Children’s early years are a time when many families move home. Does residential mobility affect children’s wellbeing at age five in terms of cognitive and behavioural development? The question arises as moving home is sometimes portrayed as a stressful life event adversely affecting child development, particularly if frequent. Other studies suggest a more mixed role for home moves, which may reflect good or bad changes in family circumstances. This paper first presents evidence from the first five years of the UK Millennium Cohort Study about who moved, how often and why. We find that many British families at this point in the life cycle move to improve the housing of a growing family. We then investigate the relationship between the number of moves and child outcomes. Generally, moving displays an adverse association with our three indicators of child development at age five. However the adverse association is statistically explained by changes in family structure, employment status, insecure housing tenure, and other controls for family vulnerabilities. Moving is better seen as sometimes a response to other family stressors. Differentiating moves in terms of their destination we find that moving into the 30% poorest areas, as well as ‘failing’ to move out of them, shows some adverse outcomes for children. After allowing for other associations with family disadvantage, also apparent in other studies of the Millennium Cohort, we find a small but significant disadvantage to living in low-income areas as well as moving within them. © 2016, Society for Longitudinal and Life Course Studies. All rights reserved.

GUEST EDITORIAL - Residential mobility and wellbeing: exploring children’s living situations and their implications for housing policy

Article

Full-text available

Jul 2016

Breastfeeding and Child Development

Article

Dec 2021

We show that children who are born at or just before the weekend are less likely to be breastfed, owing to poorer breastfeeding support services in hospitals at weekends. We use this variation to estimate the effect of breastfeeding on children's development in the first seven years of life, for a sample of births of low-educated mothers. We find large effects of breastfeeding on children's cognitive development but no effects on health or noncognitive development during the period of childhood we consider. Regarding mechanisms, we study how breastfeeding affects parental investments and the quality of the mother-child relationship. (JEL I12, I14, I18, J13, J16, J24)

Providing a Sure Start: How government discovered early childhood

Book

Sep 2011

Naomi Eisenstadt

This book tells the story of Sure Start, one of the flagship programmes of the last government. It tells how Sure Start was set up, the numerous changes it went through, and how it has changed the landscape of services for all young children in England. Offering insight into the key debates on services for young children, as well as how decisions are made in a highly political context, it will be of keen interest to policy academics, senior managers of public services and all those with a keen interest in developing services for young children.

Children of the 21st century: The first five years

Book

Jan 2010

This book documents the first five years of life of the children of the influential Millennium Cohort Study, which is tracking almost 19,000 babies born in 2000 and 2001 in England, Scotland, Wales and Northern Ireland. This book is the second in a series of books which will report on the findings from the data and follows on from Children of the 21st century: From birth to nine months (The Policy Press, 2005). It takes an extended look at the children’s lives and development as they grow and begin formal education, and the implications for family policy, and service planning in health and social services. The chapters in this book are written by experts across a wide range of social science and health fields and form a unique look at the early lives of children that cuts across disciplinary boundaries. It is essential reading for academics, students and researchers in these fields. It will also be of relevance to policy makers and practitioners with an interest in children’s early years, family life, child development, child poverty, childcare and education and health care.

Persistent poverty and children's cognitive development: Evidence from the UK Millennium Cohort Study

Article

Feb 2016

We use data from the four sweeps of the UK Millennium Cohort Study of children born at the turn of the 21st century to document the effect that poverty, and in particular persistent poverty, has on their cognitive development in their early years. Using structural equation modelling, we show that children born into poverty have significantly lower test scores at age 3, age 5 and age 7 years, and that continually living in poverty in their early years has a cumulative negative effect on their cognitive development. For children who are persistently in poverty throughout their early years, their cognitive development test scores at age 7 years are almost 20 percentile ranks lower than children who have never experienced poverty, even after controlling for a wide range of background characteristics and parental investment.

Too Many Children Left Behind: The US Achievement Gap in Comparative Perspective

Book

Jan 2015

The belief that with hard work and determination, all children have the opportunity to succeed in life is a cherished part of the American Dream. Yet, increased inequality in America has made that dream more difficult for many to obtain. In Too Many Children Left Behind, an international team of social scientists assesses how social mobility varies in the United States compared with Australia, Canada, and the United Kingdom. Bruce Bradbury, Miles Corak, Jane Waldfogel, and Elizabeth Washbrook show that the academic achievement gap between disadvantaged American children and their more advantaged peers is far greater than in other wealthy countries, with serious consequences for their future life outcomes. With education the key to expanding opportunities for those born into low socioeconomic status families, Too Many Children Left Behind helps us better understand educational disparities and how to reduce them. Analyzing data on 8,000 school children in the United States, the authors demonstrate that disadvantages that begin early in life have long-lasting effects on academic performance. The social inequalities that children experience before they start school contribute to a large gap in test scores between low- and high-SES students later in life. Many children from low-SES backgrounds lack critical resources, including books, high-quality child care, and other goods and services that foster the stimulating environment necessary for cognitive development. The authors find that not only is a child's academic success deeply tied to his or her family background, but that this class-based achievement gap does not narrow as the child proceeds through school. The authors compare test score gaps from the United States with those from three other countries and find smaller achievement gaps and greater social mobility in all three, particularly in Canada. The wider availability of public resources for disadvantaged children in those countries facilitates the early child development that is fundamental for academic success. All three countries provide stronger social services than the United States, including universal health insurance, universal preschool, paid parental leave, and other supports. The authors conclude that the United States could narrow its achievement gap by adopting public policies that expand support for children in the form of tax credits, parenting programs, and pre-K. With economic inequalities limiting the futures of millions of children, Too Many Children Left Behind is a timely study that uses global evidence to show how the United States can do more to level the playing field.

The Scourge of Asian Flu

Article

Jan 2011

Elaine Kelly

This paper examines the impact of in utero exposure to the Asian influenza pandemic of 1957 upon childhood development. Outcome data are provided by the National Child Development Study (NCDS), a panel study where all members were potentially exposed in the womb. Epidemic effects are identified using geographic variation in a surrogate measure of the epidemic. Results point to multiple channels linking fetal health shocks to childhood outcomes: physical development is impeded, but only when mothers had certain health characteristics; by contrast, the negative effects on cognitive development appear general across the cohort.

The Millennium Cohort Study: the making of a multi-purpose resource for social science and policy

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