The Families, Children and Child Care (FCCC) study in relation to area characteristics: Recruitment and sample description

Similar documents
Population Trends 139 Spring 2010

This is a repository copy of Poverty and Participation in Twenty-First Century Multicultural Britain.

*p <.05. **p <.01. ***p <.001.

Multiple Imputation for Missing Data in KLoSA

Power and Priorities: Gender, Caste, and Household Bargaining in India

COMPARISON OF EMPLOYMENT PROBLEMS OF URBANIZATION IN DISTRICT HEADQUARTERS OF HYDERABAD KARNATAKA REGION A CROSS SECTIONAL STUDY

Occupational Structure and Social Stratification in East Asia: A Comparative Study of Japan, Korea and Taiwan

Wine-Tasting by Numbers: Using Binary Logistic Regression to Reveal the Preferences of Experts

Comparative Analysis of Fresh and Dried Fish Consumption in Ondo State, Nigeria

PARENTAL SCHOOL CHOICE AND ECONOMIC GROWTH IN NORTH CAROLINA

Emerging Local Food Systems in the Caribbean and Southern USA July 6, 2014

Flexible Working Arrangements, Collaboration, ICT and Innovation

1) What proportion of the districts has written policies regarding vending or a la carte foods?

Online Appendix to Voluntary Disclosure and Information Asymmetry: Evidence from the 2005 Securities Offering Reform

Northern Region Central Region Southern Region No. % of total No. % of total No. % of total Schools Da bomb

Senior poverty in Canada, : A decomposition analysis of income and poverty rates

Dietary Diversity in Urban and Rural China: An Endogenous Variety Approach

Credit Supply and Monetary Policy: Identifying the Bank Balance-Sheet Channel with Loan Applications. Web Appendix

Zeitschrift für Soziologie, Jg., Heft 5, 2015, Online- Anhang

Risk Assessment Project II Interim Report 2 Validation of a Risk Assessment Instrument by Offense Gravity Score for All Offenders

Gail E. Potter, Timo Smieszek, and Kerstin Sailer. April 24, 2015

Labor Supply of Married Couples in the Formal and Informal Sectors in Thailand

An application of cumulative prospect theory to travel time variability

Pitfalls for the Construction of a Welfare Indicator: An Experimental Analysis of the Better Life Index

A Web Survey Analysis of the Subjective Well-being of Spanish Workers

Relationships Among Wine Prices, Ratings, Advertising, and Production: Examining a Giffen Good

FACTORS DETERMINING UNITED STATES IMPORTS OF COFFEE

BNI of kinds of corn chips (descriptive statistics)

Online Appendix to The Effect of Liquidity on Governance

BORDEAUX WINE VINTAGE QUALITY AND THE WEATHER ECONOMETRIC ANALYSIS

Volume 30, Issue 1. Gender and firm-size: Evidence from Africa

Demographic, Seasonal, and Housing Characteristics Associated with Residential Energy Consumption in Texas, 2010

Online Appendix for. To Buy or Not to Buy: Consumer Constraints in the Housing Market

ICT Use and Exports. Patricia Kotnik, Eva Hagsten. This is a working draft. Please do not cite or quote without permission of the authors.

Missing value imputation in SAS: an intro to Proc MI and MIANALYZE

IT 403 Project Beer Advocate Analysis

Method for the imputation of the earnings variable in the Belgian LFS

Housing Quality in Europe A Comparative Analysis Based on EU-SILC Data

MARKET ANALYSIS REPORT NO 1 OF 2015: TABLE GRAPES

Candidate Agreement. The American Wine School (AWS) WSET Level 4 Diploma in Wines & Spirits Program PURPOSE

Transportation demand management in a deprived territory: A case study in the North of France

COMPARISON OF CORE AND PEEL SAMPLING METHODS FOR DRY MATTER MEASUREMENT IN HASS AVOCADO FRUIT

Missing Data Treatments

THE ECONOMIC IMPACT OF BEER TOURISM IN KENT COUNTY, MICHIGAN

Food and beverage services statistics - NACE Rev. 2

Table A.1: Use of funds by frequency of ROSCA meetings in 9 research sites (Note multiple answers are allowed per respondent)

Structural Reforms and Agricultural Export Performance An Empirical Analysis

Growth in early yyears: statistical and clinical insights

This appendix tabulates results summarized in Section IV of our paper, and also reports the results of additional tests.

Harvesting Charges for Florida Citrus, 2016/17

MBA 503 Final Project Guidelines and Rubric

November 9, Myde Boles, Ph.D. Program Design and Evaluation Services Multnomah County Health Department and Oregon Public Health Division

Activity 10. Coffee Break. Introduction. Equipment Required. Collecting the Data

Perspective of the Labor Market for security guards in Israel in time of terror attacks

COMPETITION ENTRY FORMS GENERAL REGULATION

II. The National School Lunch Program

Characteristics of U.S. Veal Consumers

Fair Trade and Free Entry: Can a Disequilibrium Market Serve as a Development Tool? Online Appendix September 2014

West Melbourne Small Area Demographic Profile.

OF THE VARIOUS DECIDUOUS and

Level 2 Mathematics and Statistics, 2016

Internet Appendix. For. Birds of a feather: Value implications of political alignment between top management and directors

PEEL RIVER HEALTH ASSESSMENT

The Grocer : Soft Drinks Research on behalf of The Grocer April 2018

Gender and Firm-size: Evidence from Africa

What are the Driving Forces for Arts and Culture Related Activities in Japan?

AJAE Appendix: Testing Household-Specific Explanations for the Inverse Productivity Relationship

Valuation in the Life Settlements Market


2. Relative difference in ASCFR1 between Russia and the USA:

Is Fair Trade Fair? ARKANSAS C3 TEACHERS HUB. 9-12th Grade Economics Inquiry. Supporting Questions

Community differences in availability of prepared, readyto-eat foods in U.S. food stores

Table 1.1 Number of ConAgra products by country in Euromonitor International categories

Mobility tools and use: Accessibility s role in Switzerland

Bt Corn IRM Compliance in Canada

The Common Agricultural Policy

Evaluating Population Forecast Accuracy: A Regression Approach Using County Data

Gender Gaps in Higher Education Participation

Regression Models for Saffron Yields in Iran

Decision making with incomplete information Some new developments. Rudolf Vetschera University of Vienna. Tamkang University May 15, 2017

Specialty Coffee Market Research 2013

Problem. Background & Significance 6/29/ _3_88B 1 CHD KNOWLEDGE & RISK FACTORS AMONG FILIPINO-AMERICANS CONNECTED TO PRIMARY CARE SERVICES

Buying Filberts On a Sample Basis

HOME ROASTER COMPETITION ENTRY FORMS GENERAL REGULATION

Panel A: Treated firm matched to one control firm. t + 1 t + 2 t + 3 Total CFO Compensation 5.03% 0.84% 10.27% [0.384] [0.892] [0.

Internet Appendix to. The Price of Street Friends: Social Networks, Informed Trading, and Shareholder Costs. Jie Cai Ralph A.

Technical Memorandum: Economic Impact of the Tutankhamun and the Golden Age of the Pharoahs Exhibition

ASSESSING THE HEALTHFULNESS OF FOOD PURCHASES AMONG LOW-INCOME AREA SHOPPERS IN THE NORTHEAST

Notes on the Philadelphia Fed s Real-Time Data Set for Macroeconomists (RTDSM) Capacity Utilization. Last Updated: December 21, 2016

Guideline to Food Safety Supervisor Requirements

Report Brochure P O R T R A I T S U K REPORT PRICE: GBP 2,500 or 5 Report Credits* UK Portraits 2014

Relation between Grape Wine Quality and Related Physicochemical Indexes

INTERNATIONAL UNDERGRADUATE PROGRAM BINA NUSANTARA UNIVERSITY. Major Marketing Sarjana Ekonomi Thesis Odd semester year 2007

To make wine, to sell the grapes or to deliver them to a cooperative: determinants of the allocation of the grapes

The age of reproduction The effect of university tuition fees on enrolment in Quebec and Ontario,

Final Exam Financial Data Analysis (6 Credit points/imp Students) March 2, 2006

Gasoline Empirical Analysis: Competition Bureau March 2005

2010 Winter Canola Variety Trial

The Economic Impact of the Craft Brewing Industry in Maine. School of Economics Staff Paper SOE 630- February Andrew Crawley*^ and Sarah Welsh

How Rest Area Commercialization Will Devastate the Economic Contributions of Interstate Businesses. Acknowledgements

Transcription:

FCCC-recruitment (April, 21st, 2005) 1 The Families, Children and Child Care (FCCC) study in relation to area characteristics: Recruitment and sample description Lars-Erik Malmberg, Beverley Davies, Jo Walker, Jacqueline Barnes, Kathy Sylva, Alan Stein and Penelope Leach (2005) 1 Abstract The aims of the paper are to (1) provide an overview of the recruitment procedures for the Families, Children and Child Care study (FCCC) (2) investigate whether nonparticipation was related to ward poverty level, and (3) examine the relationship between ward and individual level indicators of poverty in the recruited sample. In total 1862 mothers gave contact details for a later approach of which 217 were found not to meet eligibility criteria and 444 subsequently decided not to participate. The rate of participation was lower for mothers recruited in more deprived wards (as measured by the Child Poverty Index, CPI; Noble et al., 2000). Although the two recruitment sites, North London and Oxfordshire, differed with regard to levels of deprivation; the North London participants were in relatively deprived areas (below the national average) and the Oxfordshire participants were in less deprived areas (above the national average), the combined sample reflected the national distribution of deprivation. Mothers self-reported socio-economic information was related to area level of poverty. Acknowledgements George Smith, at the Department of Social Work and Social Policy, University of Oxford, kindly linked the mothers postcode information with ward-level indicators of deprivation. Fiona Roberts compiled census information. 1 This document was partly based on administrative data and minutes of the Families, Children and Child Care (FCCC) project. The Principal investigators are Kathy Sylva, Alan Stein and Penelope Leach. Jacqueline Barnes and Lars-Erik Malmberg are senior investigators. Fieldworkers are Gemma Ellis, Jenny Gotlieb, Lindsay Hague, Denise Jennings, Michelle Nichols, and Bina Ram. Correspondence can be addressed to Lars-Erik Malmberg, Department of Educational Studies, University of Oxford, 15, Norham Gardens, OX2 6PY, UK. E-mail: lars-erik.malmberg@edstud.ox.ac.uk

FCCC-recruitment (April, 21st, 2005) 2 The aims of the paper are to (1) provide an overview of the recruitment procedures for the Families, Children and Child Care study (see research protocol on this website: Sylva, Stein & Leach, 2000) (2) investigate whether non-participation was related to ward poverty level, and (3) examine the relationship between ward and individual level indicators of poverty in the recruited sample. 1. Recruitment procedure The data for the FCCC were collected on two fieldwork sites, in North London and Oxfordshire. The recruitment centred on ante-natal clinics held in two large hospitals, one in North London and one in Oxfordshire, both catering to demographically diverse populations. In addition, a number of community post-natal clinics were used for recruitment to reach more disadvantaged families, so that the distribution of socioeconomic class would reflect that of England as closely as possible. During the final phase, selective over-recruitment of disadvantaged mothers was carried out, whereby high socioeconomic class mothers were excluded in order to achieve a balanced overall sample. When mothers in clinics were asked whether they were interested in the study, a total of 1862 mothers gave their contact details to be approached for participating in the study, 991 in London and 871 in Oxford (see Table 1 and Figure 1). Table 1. Study participation in North London and Oxfordshire Site Total North London Oxfordshire in 3m sample did not participate 391 270 661 (35.5%) participated 600 601 1201 (64.5%) Total 991 871 1862 (100.0%) Out of the total 1862 mothers who gave their contact details, 1201 (64.5%) mothers joined the study, 217 (11.7%) were found not to be eligible for the study and 444 (23.8%) opted not to take part. The initial non-participation rate was thus 27.0% (444 of 1645 eligible subjects). There were more North London mothers who did not participate in the study than Oxfordshire mothers (χ 2 [1] = 10.12; p<.01). Eligibility The following eligibility criteria applied to the child: birth weight 2500 grams or more, gestation of 37 weeks or more, no significant congenital abnormalities, being cared for in Special Baby Care Unit (SBCU) for no more than 48 hours, and being a singleton. The following eligibility criteria applied to the mother: aged 16 or more at child s birth, adequately fluent in English for interview, no intention to move away over the next 1-2 years, and no plans to have their child adopted or placed in the care of social services. Table 2 gives the reasons for non-participation.

FCCC-recruitment (April, 21st, 2005) 3 Fieldworkers approached mothers in clinics Total number of mothers who gave contact details to be approached for first interview: Feb.-Sept. 1998 October 1998 up to April 2001 Hospital A (n=542) Six clinics (n=449) Total n = 991 Hospital B (n=218) 19 Clinics (n=653) Total n = 871 Contact details n = 1862 Not eligible n = 217 Withdrew n = 444 Ward-level information Not available: 10 23 31 Available: 207 421 1170 3 month interview n = 1201 Figure 1: Flowchart of recruitment procedure and availability of ward-level information (based on post-codes) Table 2. Reason for initial non-participation or exclusion from the study Reason for exclusion recorded Total Did not join Not eligible REASON Refusal 251 0 251 Uncontactable 156 0 156 Cancelled, unavailable 13 0 13 Moved, intention to move 0 48 48 Insufficient English 0 20 20 Partner refusal 24 0 24 Baby underweight 0 28 28 Baby too old 0 26 26 Socioeconcomic class a 0 69 69 Other reason b 0 26 26 Total 444 217 661 a During the final phase of the recruitment selective over-recruitment of disadvantaged mothers was carried out, whereby high socioeconomic class mothers were excluded in order to achieve a balanced overall sample. b The other reason category consists of babies who were seriously ill, had been cared in special care units more than 48h, who were still-born or the mother was too young at child s birth.

FCCC-recruitment (April, 21st, 2005) 4 Table 3. Mothers and fathers socioeconomic class distribution in the FCCC study compared to English mothers (2001 census) North London Oxfordshire All FCCC England d FCCC Census b FCCC Census c N % % N % % N % % Socio-Economic Class a of Mothers Working 232 38.7 34.7 249 41.4 34.3 481 40.0 42.2 Intermediate 116 19.3 20.6 105 17.5 24.8 221 18.4 24.5 Managerial and professional 252 42.0 44.7 247 41.1 40.9 499 41.5 33.3 Total 600 601 1,201 Socio-Economic Class a of Fathers Working 162 30.9 32.9 165 29.5 34.4 327 30.1 41.5 Intermediate 90 17.1 18.3 76 13.6 17.9 166 15.3 19.3 Managerial and professional 273 52.0 48.8 319 57.0 47.7 592 54.6 39.2 Total 525 560 1,085 Note: a = The Socio-Economic Classes (SEC; Elias, Halstead & Prandy, 1993; Rose & O Reilly, 1998), was used: Working Class includes unskilled labour, semi-routine and routine occupations and long-term unemployed; Intermediate Class including clerical, service, small scale employers and own account workers; and Managerial and Professional Class including large employers and managers, professionals, associate professionals (ancillaries to professionals), small managers and higher supervisors. b = Census information was derived for four Northern London recruitment areas (Census information for 2001 in National Statistics, 2005). c = Census information is for Oxfordshire county. d = Census information for England (i.e., excluding information for Wales, Scotland and North Ireland).

FCCC-recruitment (April, 21st, 2005) 5 Socioeconomic class in FCCC and in the population Overall the recruitment procedure resulted in a sample which was relatively balanced with regard to mother s socioeconomic class when compared with National Census figures for the respective areas (see Table 3). In both North London and Oxfordshire the proportion of working class mothers was larger than the proportions at the area level. The proportion of intermediate class mothers was slightly below the area figure in North London and 7.3% off in Oxfordshire. The proportion of managerial class mothers was slightly below the area figures in both North London and Oxfordshire. Having included the 69 managerial class mothers would have skewed the distribution more. The distribution of the partners (1085 mothers reported living with a partner at the time of the interview) was more skewed toward the managerial class. However, this skew was probably due to the 116 single mothers, for whom no partner record, naturally, was available. 2. Area- and family-level predictors of participation Deprivation Measures at the Ward level Six separate indices of deprivation were available at the ward level (Noble et al., 2000): Housing, Income, Child Poverty, Employment, Health, and Education; and one Multiple Deprivation, an aggregate of the aforementioned. A higher score on each Index (either a z-score type of scale or one ranging between 0-100) indicates a higher level of deprivation. The indices are also expressed as ranks, in relation to all 8414 wards in the UK, and a decile, placing each ward into deciles according to their rank order. A lower rank or decile indicates more deprivation. Using their postcode, each participant and nonparticipant could be linked to the relevant deprivation values for their ward, those living in the same ward having the same scores. For the present study, focusing on the lives of infants the Child Poverty Index (CPI) was deemed the most relevant index. The CPI is an aggregate measure of the proportion of families with 0-16 year old children within each electoral ward, who claim means-tested financial benefits (i.e. income support, job seekers allowance, family credit and disability working allowance; Noble et al., 2000). Demographic variables at the family level The ward-level deprivation indicators for each individual were correlated with individual level indices of adversity. These were collected during mother interviews when the child was 3, 10 and 18 months old: mother s educational qualifications (1 = vocational qualifications at age 16 or below, to 6 = higher degree or above), mother s and partner s occupational status as measured by the Socioeconomic Class index (Elias, Halstead & Prandy; Rose & O Reilly, 1998) by three ordinal categories (1 = working class occupations (e.g. factory work or low level job in service industries), 2 = intermediate occupations (e.g. secretary, data entry), 3 = managerial and professional (e.g. the professions, senior management jobs), adverse living conditions between 3-18 months, and average family income between 3-18 months. Adverse living condition was calculated as the average adversity score when the child was 3, 10 and 18 months. The six-point adversity scale was based on five dichotomous indicators (0=no, 1=yes): living in rented accommodation, having shared bathroom or kitchen, having a garden, more than four stair to flat, having car or access to car, and crowdedness (1.5 or more persons

FCCC-recruitment (April, 21st, 2005) 6 per room), a higher value indicating more adverse living conditions at the individual level. Family income was the average of the sum of the mother s and their partner s income across the three time points at 3, 10 and 18 months. In order to link study participants and non-participants to ward-level deprivation (Indices of Multiple Deprivation, IMD; Noble, Penhale, Smith, Wright, Dibben, Owen, Lloyd, 2000), postcode information for 1591 mothers who provided contact details was used (54 or 3.4% had missing information, or a non-valid postcode). Of the 1201 mothers who participated in the study when their child was 3 months old, no postcode was available for 31 of them. Hence, the analysis of area level deprivation was conducted for 1170 families. In order to investigate the extent to which ward-level poverty predicted nonparticipation, a logistic hierarchical regression model was specified in MLWin (Rasbash, Steele, Browne & Prosser, 2004). Non-participation was used as dependent variable (0 = participated, 1 = did not participate). Two models were specified. In the first model two fixed effects at the ward-level were included: number of approached mothers per Ward and the Child Poverty Index (Table 4, left). In the second model the Index of Multiple Deprivation was included (Table 4, right). In order to investigate between-ward variance, a random effect was estimated for the intercept. Table 4. Ward-level predictors of participation b s.e. e b p b s.e. e b p Constant 1.169 0.062 Constant 1.145 0.061 Fixed effects Fixed effects N mothers in ward -0.010 0.004 0.99 ** N mothers in ward -0.009 0.004 0.99 * CPI (deciles) 0.111 0.024 1.12 *** IMD (deciles) 0.103 0.023 1.11 *** Random effect Ward 0.000 0.000 Random effect Ward 0.000 0.000 Note: CPI = Child Poverty Index, IMD = Index of Multiple Deprivation, a higher decile indicates less poverty. e b is the exponential of the beta-weight, interpreted as an Odds-Ratio. As we can see in Table 4, mothers who lived in wards where more mothers had been approached, were less likely to participate in the study (p<.01 and p<.05). Mothers who lived in more advantaged wards as indicated by the CPI were more likely to participate in the study (p<.001) 2. The effect of the IMD was very similar to that of the CPI. There was no reliable between-ward variance. 2 A number of other models were specified, including more predictors: ward-average maternal educational level, ward-average maternal socioeconomic class, ward-average family income and ward-average adverse living conditions. On their own each of these variables predicted study-participation in the expected direction. Due to collinearity between these variables, and between these variables and the ward-level indices of disadvantage, the separate effects of each demographic variable were not visible when all were entered into a regression model. However, the ward-level demographic predictors were based on information from the participating mothers, and hence biased towards participants.

FCCC-recruitment (April, 21st, 2005) 7 3. In what kinds of area do the study-participants live? In order to investigate the kinds of areas in which the study participants lived, a series of descriptive and correlational analyses was conducted. Table 5 gives descriptive information on the average ward-level indices of deprivation for the 1170 families for whom complete postcodes were available. Table 5. Average scores for the Indices of Deprivation for FCCC participants (N=1170) N Min Max Mean S.D. Housing deprivation 1170-2.20 2.41.89.84 Income deprivation 1170 3.74 55.97 20.94 12.17 Child Poverty 1170 1.57 74.06 29.50 17.34 Employment deprivation 1170 1.51 30.72 9.94 6.18 Health deprivation 1170-2.29 1.68 -.28.82 Education deprivation 1170-2.46 2.18.18.93 Index of multiple deprivation 1170 1.88 71.11 23.58 15.86 Note: A higher value indicates a higher level of deprivation. In Table 6 the average deprivation indices for the 259 wards in which the participants lived are presented. The ward-level information is not weighted by the number of participants per ward. Table 6. Average scores for the Indices of deprivation for the wards from which FCCC participants were recruited (N=259) N Minimum Maximum Mean Std Housing deprivation 259-2.20 2.41.64 1.00 Income deprivation 259 3.74 55.97 17.84 12.23 Child poverty index 259 1.57 74.06 24.69 18.02 Employment deprivation 259 1.51 30.72 9.07 6.85 Health deprivation 259-2.29 1.68 -.46.90 Education deprivation 259-2.46 2.18 -.17.84 Index of Multiple deprivation 259 1.88 71.11 19.91 16.02 Note: A higher value indicates a higher level of deprivation. Next, the levels of deprivation at each site were compared for each participant (Table 7) and for each relevant ward (Table 8). The North London mothers lived in more deprived wards than the Oxfordshire mothers, with regard to the income index, child poverty index, employment index, and the multiple deprivation index. All variances and meanlevels were significant at the p<.001 level, except those for the education index (variances were tested with the Levene s F-test and mean-level differences with independent groups t-tests). Comparing the wards in which the participants lived, all mean-level differences were significantly different at the p<.001 level.

FCCC-recruitment (April, 21st, 2005) 8 Table 7. Average deprivation scores for FCCC participants (N=1170) by site Site N Min Max Mean Std North London Housing deprivation 570-1.29 2.41 1.48.47 Income deprivation 570 6.22 55.97 27.89 11.51 Child Poverty 570 3.83 74.06 38.56 16.43 Employment deprivation 570 2.37 30.72 14.35 5.51 Health deprivation 570-1.97 1.68.20.63 Education deprivation 570-1.53 2.18.26.96 Index of multiple deprivation 570 1.88 71.11 32.39 15.06 Oxfordshire Housing deprivation 600-2.20 2.02.32.71 Income deprivation 600 3.74 36.28 14.34 8.58 Child Poverty 600 1.57 49.82 20.90 13.34 Employment deprivation 600 1.51 12.89 5.75 3.09 Health deprivation 600-2.29.73 -.72.72 Education deprivation 600-2.46 2.04.11.90 Index of multiple deprivation 600 3.25 46.05 15.22 11.45 Table 8. Average deprivation scores for the wards from which FCCC participants were recruited, by site (N=259) Site N Min Max Mean Std North London Housing deprivation 120-1.29 2.41 1.43.67 Income deprivation 120 6.22 55.97 26.64 12.07 Child poverty 120 3.83 74.06 37.22 17.60 employment deprivation 120 2.37 30.72 14.45 6.48 Health deprivation 120-1.97 1.68.20.70 Education deprivation 120-1.53 2.18.09.88 Multiple deprivation index 120 1.88 71.11 31.23 16.26 Oxfordshire Housing deprivation 139-2.20 2.02 -.04.68 Income deprivation 139 3.74 36.28 10.24 5.34 Child poverty 139 1.57 49.82 13.88 9.28 Employment deprivation 139 1.51 12.89 4.43 2.15 Health deprivation 139-2.29.73-1.04.59 Education deprivation 139-2.46 2.04 -.40.74 Multiple deprivation index 139 3.25 46.05 10.15 6.68 Next, the relationship between numbers recruited was examined in relation to the deprivation scores of their ward. There were between 1 and 42 mothers recruited per ward (M = 4.52; SD = 5.42).The overall number recruited was higher when deprivation was higher according to all the indices except Employment (see Table 9)(significant correlations ranged from.17 to.35). However, when the two sites were considered separately it was found that there were no such relationships between number of recruited persons per ward and each deprivation index for the North London sample, while these relationships were quite strong in the Oxfordshire sample. Hence, more mothers were recruited in Oxfordshire in the more deprived wards.

FCCC-recruitment (April, 21st, 2005) 9 Table 9. Correlations between numbers of persons recruited per ward and ward s deprivation indices, by site North London (n = 120) p Oxfordshire (n = 139) p All wards (n = 259) p housing deprivation 0.21 *** 0.07 ns 0.43 *** income deprivation 0.21 *** 0.09 ns 0.63 *** child poverty deprivation 0.22 *** 0.06 ns 0.62 *** Employment deprivation 0.10 ns -0.01 ns 0.50 *** health deprivation 0.17 ** -0.01 ns 0.44 *** education deprivation 0.35 *** 0.16 ns 0.56 *** multiple deprivation deprivation 0.19 ** 0.06 ns 0.62 *** Note: * = p<.05; ** = p<.01; *** = p<.001. In Table 10 the Child Poverty Index and the Index of Multiple Deprivation of wards from which FCCC participants were recruited are compared with national averages. Table 10. Comparison of wards from which FCCC families were recruited with National averages Child Poverty Index (CPI) Index of Multiple Deprivation (IMD) FCCC FCCC National All North London Oxfordshire National All North London Oxfordshire Mean 26.74 29.50 38.56 20.90 21.70 23.58 32.39 15.22 Median 22.45 26.62 38.67 17.51 16.93 19.77 32.38 11.04 Std 17.02 17.34 16.43 13.34 15.39 15.86 15.06 11.45 Skewness 0.87 0.40-0.08 0.82 1.27 0.69 0.20 1.49 Kurtosis 0.09-0.95-0.95-0.43 1.24-0.62-0.84 1.37 Minimum 0.54 1.57 3.83 1.57 1.16 1.88 1.88 3.25 Maximum 88.71 74.06 74.06 49.82 83.77 71.11 71.11 46.05 25%-ile 13.14 14.68 24.03 10.08 10.18 9.84 19.77 7.06 50%-ile 22.45 26.62 38.67 17.51 16.93 19.77 32.38 11.04 75%-ile 37.43 45.04 51.10 30.16 29.14 36.56 44.31 20.31 The average scores for the whole FCCC sample were slightly above (i.e., more deprived) national values, but these were not significantly different from the national average as indicated by one-group t-tests (p=.068 for the CPI, and p =.075 for the IMD, respectively). Looking at each site separately North London scores were above (ps <.001) and the Oxfordshire-values below (ps <.001) the national values. Next, the distribution of the CPI deciles for the FCCC participants were examined. The lowest decile indicates that the ward was ranked among the 10% most deprived, and the

FCCC-recruitment (April, 21st, 2005) 10 highest decile, ranked among the 10% least deprived wards in England. In Figure 3a the Child Poverty Index (CPI) deciles for the 259 wards from which the participants were recruited are presented for North London, Oxfordshire and the whole sample, indicating how many wards of a certain poverty level the mothers were recruited from. In Figure 3b, the individual level CPI deciles are presented, indicating how many participants living in a ward of a certain poverty level participated in the study. Replicating the findings described above, mothers were recruited from more deprived wards in North London and from less deprived wards in Oxfordshire. The graph for the total sample shows that more mothers were recruited from both highly deprived and less deprived wards, but not from averagely deprived wards.

FCCC-recruitment (April, 21st, 2005) 11 30 North London 50 Oxfordshire 50 All 40 40 20 30 30 10 20 20 Frequency 0 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 Std. Dev = 2.49 Mean = 3.8 N = 120.00 Frequency 10 0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 Std. Dev = 2.11 Mean = 8.0 N = 139.00 Frequency 10 0 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 Std. Dev = 3.13 Mean = 6.0 N = 259.00 10.5 Figure 3a. Ward level deciles of the Child Poverty Index (lower decile indicates higher level of deprivation) for the wards mothers lived in, for North London, Oxfordshire and the full sample respectively.

FCCC-recruitment (April, 21st, 2005) 12 160 140 120 100 North London 120 100 80 Oxfordshire 200 All 80 60 100 60 40 40 Frequency 20 0 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 Std. Dev = 2.37 Mean = 3.5 N = 570.00 9.5 10.5 Frequency 20 0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 Std. Dev = 2.67 Mean = 6.5 N = 600.00 10.0 Frequency 0 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 Std. Dev = 2.96 Mean = 5.0 N = 1170.00 9.5 10.5 Figure 3b. Ward level deciles of the Child Poverty Index (lower values indicate higher level of deprivation) at the individual level, for North London, Oxfordshire and the combined sample respectively.

FCCC-recruitment (April, 21st, 2005) 13 It was also observed that a larger group of mothers who lived in deprived areas were recruited from relatively fewer wards in Oxfordshire than in North London (Figure 3b). These comparisons do not, however, give any information on whether a mother who is recruited from a deprived ward is deprived. In order to examine the success or otherwise of the selective recruitment to balance the distribution of socio-economic groups in the sample, the time of the interview was correlated with the ward-deprivation indices (i.e., whether a late interview corresponded with recruitment from a deprived ward). All 3- month interviews were conducted between 20th May 1998 and 9th April 2001 (see Figure 4). Figure 4. Distribution of interview dates in the North London and Oxfordshire samples respectively. Spearman s rank order coefficients were used, due to non-normalities in the date and the income variables. As shown in Table 9 (first column), the interview date were positively associated with all the deprivation indices, indicating that mothers from more deprived areas were indeed recruited later in the sampling. When the relationships between the individual demographics and the indices of deprivation were examined (Table 11 Columns 2-6) (higher scores mean more deprivation), all correlations between the deprivation indices and mother s educational level, mothers and partners occupational status, and family income were found to be negative and the correlations between the deprivation indices and individual environmental adversity positive. With a few exceptions only, all the coefficients were significant at the p<.001 level. Overall the findings indicate that more disadvantaged mothers lived in more deprived areas.

FCCC-recruitment (April, 21st, 2005) 14 Summary The aims of this paper were to (1) provide an overview of the recruitment procedures for the Families, Children and Child Care study, (FCCC) (2) investigate whether nonparticipation was related to ward poverty level, and (3) examine the relationship between ward and individual level indicators of poverty in the recruited sample. To do so available demographic information at the individual and ward level were analyzed. In total 1862 mothers gave contact details for a later approach of which 217 were found not to meet eligibility criteria and 444 subsequently decided not to participate. The rate of participation was lower for mothers recruited in more deprived wards (as measured by the Child Poverty Index, CPI; Noble et al., 2000). Although the two recruitment sites, North London and Oxfordshire differed with regard to levels of deprivation; the North London participants were in relatively deprived areas (below the national average) and the Oxfordshire participants were in less deprived areas (above the national average), the combined sample reflected the national distribution of deprivation. Mothers self-reported socio-economic information was related to area level of poverty. While the FCCC study is not necessarily nationally representative it does constitute a relatively balanced sample with regard to area level deprivation.

FCCC-recruitment (April, 21st, 2005) 15 Table 11. Interview date, individual mother, partner and family indicators in relation to ward deprivation indices, for the total sample and for North London and Oxfordshire respectively (r s ). Total sample Interview date Mother's education Mother's occupation Partner's occupation Environmental adversity (3-18m) Family income (3-18m) Housing deprivation 0.24 *** -0.02 ns -0.09 ** -0.19 *** 0.30 *** -0.20 *** Income deprivation 0.42 *** -0.16 *** -0.20 *** -0.32 *** 0.33 *** -0.30 *** Child Poverty 0.39 *** -0.16 *** -0.19 *** -0.32 *** 0.33 *** -0.31 *** Employment deprivation 0.35 *** -0.09 ** -0.13 *** -0.25 *** 0.34 *** -0.24 *** Health deprivation 0.39 *** -0.14 *** -0.18 *** -0.30 *** 0.32 *** -0.28 *** Education deprivation 0.52 *** -0.25 *** -0.26 *** -0.39 *** 0.18 *** -0.36 *** Multiple deprivation 0.42 *** -0.15 *** -0.20 *** -0.31 *** 0.32 *** -0.30 *** North London Housing deprivation 0.05 ns -0.09 * -0.13 ** -0.19 *** 0.19 *** -0.25 *** Income deprivation 0.42 *** -0.28 *** -0.27 *** -0.41 *** 0.23 *** -0.40 *** Child Poverty 0.33 *** -0.25 *** -0.24 *** -0.37 *** 0.25 *** -0.38 *** Employment deprivation 0.31 *** -0.22 *** -0.22 *** -0.33 *** 0.25 *** -0.34 *** Health deprivation 0.29 *** -0.23 *** -0.21 *** -0.32 *** 0.23 *** -0.34 *** Education deprivation 0.61 *** -0.32 *** -0.33 *** -0.49 *** 0.17 *** -0.42 *** Multiple deprivation 0.42 *** -0.27 *** -0.27 *** -0.40 *** 0.23 *** -0.39 *** Oxfordshire Housing deprivation 0.35 *** -0.16 *** -0.22 *** -0.28 *** 0.21 *** -0.30 *** Income deprivation 0.41 *** -0.21 *** -0.24 *** -0.31 *** 0.24 *** -0.32 *** Child Poverty 0.38 *** -0.20 *** -0.22 *** -0.31 *** 0.23 *** -0.30 *** Employment deprivation 0.39 *** -0.19 *** -0.22 *** -0.31 *** 0.21 *** -0.30 *** Health deprivation 0.41 *** -0.20 *** -0.23 *** -0.33 *** 0.23 *** -0.31 *** Education deprivation 0.41 *** -0.19 *** -0.20 *** -0.27 *** 0.16 *** -0.28 *** Multiple deprivation 0.41 *** -0.21 *** -0.24 *** -0.30 *** 0.21 *** -0.32 *** Note: all Ns are 1170, except the relationships between partner s occupational status and the deprivation indices where n = 1165; * = p<.05; ** = p<.01; *** = p<.001.

FCCC-recruitment (April, 21st, 2005) 16 References Elias, P., Halstead, K., & Prandy, K. (1993). Computer assisted standard occupational coding. London: HMSO. Noble, M., Penhale, B., Smith, G., Wright, G., Dibben, C., Owen, T., Lloyd, M. (2000). Indices of deprivation 2000 (Regeneration Research Summary, No 31). London: Department of Environment, Transport and the Regions. National Statistics (2005). Census 2001. Crown copyright. www.statistics.gov.uk Rasbash, J., Steele, F., Browne, W., & Prosser, B., (2004). A user s guide to MLWin. London: Centre for Multilevel Modelling, University of London. Rose, D., & O Reilly, K. (1998). The ESRC review of Government social classifications. London: Office of National Statistics.