J7ournal of Epidemiology and Community Health 1995;49(Suppl 2):S39-S44

Census based deprivation indices: theirweighting and validation

David Gordon

AbstractKey issues - Over one hundred years ofsocial science research has shown thatdifferent social groups have different prob-abilities of suffering from multiple dep-rivation; yet census based deprivationindices frequently assign equal weightingsto each oftheir component variables. Thisbecomes highly problematic when theseindices are used as the basis for allocatingresources to local and health authorities.In order to ensure fairness and accuracyin resource allocation these indices shouldbe both weighted and validated.Study results - Weightings are derivedfrom the Breadline Britain in the 1990ssurvey to produce a census based dep-rivation index that estimates the per-centage of poor households at electoralward level. Examples of validationmethodology are discussed and the es-

timate of the proportion of poor house-holds is shown to be highly correlated withboth low income and morbidity as es-

timated from the 1991 census.

Data sources - The 1991 census local basestatistics (LBS) and small area statistics(SAS) aggregated for the 8519 electoralwards of England. The Breadline Britainin the 1990s survey: a nationally rep-resentative survey of 1831 households spe-cifically designed to measure poverty andmultiple deprivation.

(J7 Epidemiol Comm Health 1995;49(Suppl 2):S39-S44)

Department ofSocial Policy andSocial Planning,University of Bristol,Bristol BS8 lTND Gordon

Correspondence to:D Gordon.

The construction of census based deprivationindices is one of the most economically im-portant uses of social statistics since they forma key element in the allocation of both localgovernment and health resources. However,none of the questions in the 1991 census was

specifically designed to measure either povertyor deprivation and any census based indexmust comprise variables that are, at best, proxy

indicators of deprivation rather than directmeasures. It is not surprising therefore that a

bewildering array of indices has been proposed,using different combinations of variables anddifferent statistical methods.The key question is, "Which index is the

best?" This question can be divided into twoparts: firstly, what does the index measure (ifanything) and, secondly, which index providesthe most accurate and precise measurement?Answering these questions is often a far froma simple matter. Advocates ofnew census baseddeprivation indices rarely make detailed com-

parisons between their index and others. Sim-ilarly, theoretical discussions on the nature andmeasurement of deprivation are often dealtwith in a cursory manner or are entirely lackingfrom many papers. Indeed, many deprivationindices seem to be composed of combinationsof variables that the authors think measuresomething "bad". Although, what this "bad"thing is is often unclear. Various statistical pro-cedures and transformations are often per-formed on the indices components, usually inorder to ensure equal weighting - that is so thateach variable provides an equal contributionto the final index. The justification for suchstatistical procedures, however, is often absent.The terms "deprivation" and "multiple dep-rivation" are generally used loosely, with littlereference to their specific technical meanings.Under these circumstances, it is not sur-

prising that the non-specialist (and often thespecialist) has difficulty in selecting a dep-rivation index. Despite these problems, it isrelatively easy to describe the broad pattern ofthe distribution of poverty within a region.Figure 1 shows the estimated percentage ofpoor households (for the definition of poorhouseholds see below) in the 366 local authoritydistricts of England.' The districts have beendivided into approximate quartiles (the poorest25% of authorities, the next 25% and so forth),and a clear pattern is evident on the map.There are high numbers of poor householdsliving in inner London, Tyneside, Merseyside,Greater Manchester, and into Yorkshire. Poorhouseholds are also found in the major citiesand in rural districts of Cornwall, East Anglia,Kent, Cumbria, and Northumberland.The same pattern is evident from maps pro-

duced using the social deprivation (SOCDEP)index of Forrest and Gordon,2 the "Townsendindex" Z score3 (the most widely used dep-rivation index) and the Department of En-vironment's index of local conditions4 (thecurrent "official" deprivation index). Sincethese indices use different combinations ofvari-ables and different statistical methods, thesestriking similarities are remarkable and indicatethat by 1991, poverty had become so wide-spread in England and its manifestations wereso varied, that the same broad patterns can bediscerned almost irrespective of the methodsused to measure it. To put it bluntly, whenthere is a lot of poverty, it becomes relativelyeasy to measure.'Although there are broad similarities be-

tween the results obtained from these differentindices, there are considerable differences inthe specific rankings. This is important if theseindices are to be used to allocate resources.

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i ~~~~~~~~~~~~~.............r. W;1 1 X'<~~ ~ ~ ~ ~ i..C..I...9.1.. <9

Figure~~~~~~~.IPecntgofpoo houEhod inSloa auhIt diti't of Engand

These differences become even more markedwhen smaller and more homogeneous geo-graphical areas (such as electoral wards) arecompared.

The theory of poverty and deprivationTo measure deprivation/poverty more ac-curately, it is necessary to be precise about themeaning of these terms. There are two basicconcepts in social science: the "absolute" and"relative" theories. The "absolute" concept ofpoverty is dominated by the individual's re-quirements for physiological efficiency. How-ever, this is a very limited view ofhuman needs,especially when considering the roles that menand women play in society. People are not justphysical beings, they are social beings. Theyhave obligations as workers, parents, neigh-bours, friends, and citizens that they are ex-pected to meet and which they themselves wantto meet. Studies of people's behaviour afterthey have experienced a drastic cut in resources

show that they sometimes act to fulfil theirsocial obligations before they act to satisfy theirphysical wants. They require income to fulfiltheir various roles and participate in the socialcustoms and associations to which they havebecome habituated and not only to satisfy theirphysical wants.5

Poverty can be defined as the situation inwhich resources are so seriously below thosecommanded by the average individual or familythat the poor are, in effect, excluded fromordinary living patterns, customs, and ac-tivities. As resources for any individual or familyare diminished, there is a point at which thereoccurs a sudden withdrawal from participationin the customs and activities sanctioned bythe culture. The point at which withdrawalescalates disproportionately to falling resourcescan be defined as the poverty line orthreshold.67

This "relative" concept of poverty is nowwidely accepted.8 It is not easy, however, tomeasure poverty directly,9-" but it is possible

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Weighting and validation of census based indices

to obtain measures of "deprivation". These twoconcepts are tightly linked and there is generalagreement that the concept of deprivation cov-ers the various conditions, independent of in-come, experienced by people who are poor,while the concept of poverty refers to the lackof income and other resources which makesthose conditions inescapable or at least highlylikely. 2

The measurement of poverty anddeprivationFrom these definitions, it is clear that to meas-ure poverty/deprivation accurately, surveys orcensuses must be used that establish both the"normal" or "average" standard of living of themajority in a society/culture and any "enforced"reductions in this standard dut to lack of re-sources.

Social scientists have been using deprivationsurveys to study poverty in Britain for over ahundred years. All these surveys have shownthat some groups are more likely to suffer frommultiple deprivation than others (that is, loneparents and the unemployed are not equallylikely to be living in poverty and indices thatconsider them to be so are probably wrong.)Therefore, census based deprivation indicesthat give equal weight to their component vari-ables are likely to yield inaccurate results.

Since all census based deprivation indicesare generally composed of surrogate or proxymeasures of deprivation rather than directmeasures, there are two basic requirementsthey should fulfil to ensure accuracy:

* The components of the index should beweighted to reflect the different probabilitythat each group has of suffering from dep-rivation; and

* The components of the index must be ad-ditive - for example, if an index is composedof two variables, unemployment and loneparenthood, then researchers must be con-fident that unemployed lone parents arelikely to be poorer than either lone parentsin employment or unemployed people whoare not lone parents.

Weighted indices also have the advantagethat their results are often much easier to un-derstand, for example, that in Brent 25% ofhouseholds are living in poverty has a muchgreater intuitive meaning than saying that Brenthas a Townsend Z-score of 7-86 or a De-partment of Environment index of local con-ditions signed X2 score of 22A46.

Logistic regression results

Relative weights Odds ratio 95% Confidence Interval

Unemployment 0 094 1-7 2-5, 1-1Long term illness 0-108 1-9 2-5, 1-1Social class IV & V 0-159 2-5 3-4, 1-9No car 0-217 3-6 4-8, 2-7Not owner occupied 0-203 3-3 4-3, 2-4Lone parents 0-160 2-5 4-6, 1-4

Relative weights have been calculated from the coefficient.

Obtaining weightings for census baseddeprivation indicesThe easiest method of obtaining weightings forcomponent variables in census based dep-rivation indices is to use a survey (conductedat or around the same time as the census) thatwas specifically designed to measure povertyand deprivation. The weightings used to es-timate the percentage of poor households,shown in figure 1, were derived from the Bread-line Britain in the 1 990s survey3 5- a nationallyrepresentative survey designed specifically tomeasure the extent and nature of poverty inBritain at the end of 1990 (that is, a few monthsbefore the census). (For the Breadline Britainin the 1 990s survey, MORI interviewed a quotasample of 1319 adults aged 16 +, face-to-facein their homes, between 14 and 25 July 1990.Additional fieldwork among households livingin particularly deprived areas was carried outbetween 26 November and 9 December 1990,with 512 quota interviews conducted face toface in home. Quotas were based on sex, ageand working status. Aggregated data wereweighted by age, household type, tenure andACORN housing type to be representative ofthe population ofGreat Britain.) 3 The previousbreadline Britain survey, in 1983, had pi-oneered the "consensual" or "perceived dep-rivation" approach to measuring poverty, whichis defined from the viewpoint of the public'sperception of minimum need:"This study tackles the questions 'how poor is toopoor?' by identifying the minimum acceptable wayof life in Britain in the 1980s. Those who have nochoice but to fall below this minimum level can besaid to be 'in poverty'. This concept is developedin terms of those who have an enforced lack ofsocially perceived necessities. This means that the'necessities' of life are identified by public opinionand not by, on the one hand, the views of expertsor, on the other hand, the norms of behaviour perse. ,,16The 1990 survey asked respondents about a

list of 44 items designed to cover the range ofpossessions and activities that people mightconsider important. Respondents (and theirhouseholds) were assigned a deprivation indexscore each time they answered that they "don'thave and can't afford" an item that was con-sidered to be a necessity by more than 50%of respondents (32 out of the 44 items wereconsidered to be necessities by more than 50%of respondents after the sample had beenweighted to represent the population.) Theresulting 32 item deprivation index has beenshown to be highly reliable (Cronbach's Alpha0-8754) and effectively identical results wouldhave been obtained if different sets of questionson deprivation had been asked.'5The "poverty line" was identified at a dep-

rivation index score of 3 (that is, people/house-holds lacking three or more socially perceivednecessities) using the discriminant analysismethodology of Townsend and Gordon.'5'7The existence of a clear poverty "threshold"has been independently confirmed, using adifferent methodology by Hallerod, Bradshawand Holmes.'8 Weightings were obtained usinglogistic regression for the best subset of dep-

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Gordon

rivation indicator variables that were measuredin both the 1991 census and the breadlineBritain survey.

Eleven variables, which have been used inone or more census based indices, were ex-amined:

* Unemployment* Lone parents* Limiting long term illness/disability* Unskilled/low social class* No access to a car* Living in rented accommodation (not owner

occupied)* Single pensioners* Divorced people* Widows* Lacking or sharing basic amenities (indoor

toilet, bath/shower)* Not self contained accommodation

There was a considerable degree of overlapbetween single pensioners and widows and bothvariables were excluded because they were notgood predictors of poverty. Divorced peoplewere excluded because of their high overlapwith single parenthood, which was a betterpredictor of poverty. "Lacking basic amenities"and "not self contained accommodation" weredropped because they were found not to beadditive,6 eg households which containedsomeone with a limiting long term illness andalso lacked basic amenities were not likely tobe poorer than a household with an ill personbut with basic amenities. The reason for thisis that many poor disabled people live in localauthority accommodation which invariablyhave indoor toilets and bathrooms. Standardstatistical techniques were used to establishadditivity. First order interaction plots wereproduced using the Minitab v 10-2 package andfully saturated ANOVA and GLM models wereused to examine higher order interactions.The relative weightings and the odds ratios

from the logistic regression results are shown

300 r

200 h-

100

10 20 30 40

Households living in poverty (%)

o0

Figure 2 Estimated percentage ofpoor households in relation to the standrates for the 8519 electoral wards of England.

in the table. The regression equation classifies82% of the cases correctly, which means thateven using the best weighted subset of variablesavailable from the census, there is still a onein five error rate. Basically, the census is notdesigned to measure poverty and therefore doesnot do it particularly well. However, an estimateof the number of poor households in an areacan be calculated as: 21-7% of the number ofhouseholds with no access to a car +20-3%of the number of households not in owneroccupied accommodation + 16% of the num-ber of lone parent households + 15-9% of thenumber of workers in social classes IV and V+ 10 8% of the number of households con-taining a person with a limiting long term illness+ 9 4% of unemployed workers.

Poverty, low income, and state benefitsRecently, Davies et all9 used the family ex-penditure survey (FES) and general householdsurvey (GHS) to produce a set of weightingsthat can be used with census variables to predictthe number of low income households (thebottom quintile): and Noble et al20 have sug-gested weightings to predict households in re-ceipt of state benefits (income support).Although there is a considerable overlap be-tween poor households, low income house-holds, and households on benefit, these groupsare not identical. Specifically, pensioners, loneparents, and the self employed often have lowincomes (as measured in the FES and GHS)but have a reasonable standard of living dueto previously accumulated wealth. Similarly,people who have only recently got a job after aperiod of unemployment, may have reasonableincomes but a low standard of living. Thesefactors mean that there is only a 55-75% over-lap between low income households and poorhouseholds.' 521The correspondence between low income

households and households in receipt of statebenefits is of a similar magnitude. The DSShouseholds below average income statistics22show that, in 1991/92, only 59% of householdsin the bottom decile of income received anystate benefits (including pensions). Similarly,the last set of low income statistics, producedfor 199223 showed that, of the 13680000people in families with incomes at or below theincome support level, only 65% were receivingincome support. The breadline Britain in the1990s survey found that only 56% of non-pensioner households, in receipt of incomesupport, were also living in poverty.

Validation of census based deprivationindices

To test the accuracy of a census based dep-rivation index, it is advisable to use one or more

validation procedures. Since the publication ofThe Black report,24 literally hundreds of studies

50 60 have been published demonstrating that,

age and gender, poverty is one of the majordeterminants of ill health. Similarly, all things

!ardised illness being equal, poor households are likely to haveless income than non-poor households. There-

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fore, ill health and income can be used asvalidation criteria for deprivation indices.

Figure 2 shows a scatter plot of the estimatedpercentage of poor households against thestandardised illness ratio (SIR) for the 8519electoral wards of England. The regression linewith a 95% confidence interval is also shown.There seems to be very good agreement be-tween these two variables (Pearson's productmoment correlation 0-82). The SIRs were cal-culated at the individual level, from the resultsof the limiting long term illness question in the1991 census, using the indirect standardisationmethodology of Forrest and Gordon.2 The pre-valence rates of limiting long term illness in the1991 census for people under 75 have beenshown to be very similar to the prevalencerates of disability as "objectively" measuredin 1985-88 by the OPCS disability surveys.2Response bias for the limiting long term illnessquestion is not thought to vary by geographicalarea.26Although the 1991 census collected no in-

formation on income, detailed information onoccupation is available. Table 99 of the localbase statistics lists occupation grouped into 77categories by gender. It is possible to estimatethe average income from earnings for an areaby multiplying the number ofmen and womenin each occupational group by the averageweekly full time earnings of that occupation asrecorded in the 1991 new earnings survey.Adjustments are then made for the numbers inpart time work, those on government schemes,and the unemployed. Finally, this total figureis divided by the economically active populationto give an average estimated income from earn-ings.

This methodology does not give accurateabsolute figures for income since no estimateis made of unearned income (for exampledividends from stocks and shares, etc). How-ever, since people of working age with thehighest earned income tend also to have

400-

300 F..cP-,

200 F

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higher unearned income,27 the variations inaverage income between areas can be con-sidered to be minimum estimates. Figure 3shows a scatterplot of the estimated percentageof poor households against estimated averageearnings for the 8519 electoral wards ofEngland. The regression line with a 95%confidence interval is also shown. There seemsto be good agreement between these twovariables (Pearson's product moment cor-relation -073).

ConclusionTo obtain accurate estimates of deprivationfrom the UK census it is necessary to use aweighted index. Allowance must be made forthe fact that different groups have differentprobabilities of suffering from deprivation andpoverty.

Validation is a crucial step in establishing thelikely accuracy and precision of any censusbased deprivation index. Validation criteria areavailable both internally to the 1991 census(for example standardised illness ratios (SIRs)and estimated income) and also externally (forexample standardised mortality ratios (SMRs)and benefit statistics).The method of estimating the number of

poor households in an area suggested by Gor-don and Forrest' has been shown to yield validand reasonably accurate results for the 8519electoral wards of England.

I thank Virginia Knight and Keith Cole of the Census Dis-semination Unit, Manchester Computing Centre, and EdThomas of the Department of Geography, Bristol University.Particular thanks to Helen Anderson, for typing and editingthis paper. The programming and work involved in creating theestimated mean weekly income was undertaken jointly withPeter Lee at CURS, Birmingham University. I also thankAlastair Beattie for providing the details of the Townsenddeprivation index.Data from The Breadline Bnitain in the 1990s Survey were used

to create the weightings used in estimating the percentage ofpoor households. This survey was funded by London WeekendTelevision (LWT) with additional funding from the JosephRowntree Foundation and was carried out by Marketing andOpinion Research International (MORI). It was conceived anddesigned by Joanna Mack and Stewart Lansley for DominoFilms, with the help of Brian Gosschalk of MORI. Researchfor the six television programmes was by Harold Frayman withadditional research by David Gordon and John Hills. ChristinaPantazis has done extensive work on the data to make it easyto use.The source of the Census data are the 1991 Local Base

Statistics (100% and 10%) which are Crown Copyright.© The Breadline Britain in the 1990s Survey is copyright ofMORIand Domino Films.© The 1991 census local base statistics and small area statistics(100% and 10%) are Crown Copyright.

1 Gordon D, Forrest R. People andplaces 2. Social and economicdistinctions in England 1991. Bristol; SAUS and the Stat-istical Monitoring Unit, 1995; 135.

2 Forrest R, Gordon D. People and places. A 1991 census atlasof England. Bristol: SAUS and the Statistical MonitoringUnit, 1993.

3 Townsend P, Phillimore P, Beattie A. Inequalities in healthin the Northern Region: an interim report. Newcastle uponTyne and Bristol: Northern Regional Health Authorityand the University of Bristol, 1986.

4 Department of the Environment Index of local conditions: ananalysis based on 1991 census data. London: DOE. 1994.

5 Townsend P, Gordon D. What is enough? New evidenceon poverty in Greater London allowing the definition ofa minimum benefit. Memorandum of evidence to the Houseof Commons Social Services Select Committee on MinimumIncome 579: London; HMSO; 1989;45-73.

50 60 6 Townsend P. Poverty in the United Kingdom. Har-mondsworth, Middlesex and Berkeley: Allen Lane andPenguin Books; University of California Press, 1979.

7 Townsend P. The International analysis of poverty, MiltonKeynes: Harvester Wheatsheaf, 1993.

average 8 Piachaud D. Problems in the definition and measurementof poverty. Journal of Social Policy 1987;16(2):125-46.

in

0)c

._

L-

0 10 20 30 40Households living in poverty (%)

Figure 3 Estimated percentage ofpoor households in relation to estimatedearnings for the 8519 electoral wards of England.

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9 Atkinson AB. How should we measure poverty? Some conceptualissues. Discussion Paper No 82, ESRC Programme onTaxation, Incentives and Distribution of Income. London:London School of Economics; 1985.

10 Atkinson AB. On the measurement of poverty. DiscussionPaper no 90, ESRC Programme on Taxation, Incentivesand the Distribution of Income. London: London Schoolof Economics, 1985.

11 Lewis GW, Ulph DT. Poverty, inequality and welfare. TheEconomic Journal, 1988;98: 117-31.

12 Townsend P. Deprivation. 3ournal of Social Policy 1987;16(2): 125-46.

13 Frayman H. Breadline Britain - 1990s: The findings of thetelevision series, London: Domino Films and London Week-end Television, 1991.

14 Gosschalk B, Frayman H. The changing nature of dep-rivation in Britain - an inner cities perspective. Politicaland social issues in urban industrial societies - joint sessionwith WAPOR; 1991.

15 Gordon D, Pantazis C eds. Breadline Britain in the 1990s.Report to the Joseph Rowntree Foundation. York: JosephRowtree Foundation, 1995;251.

16 Mack J, Lansley S. Poor Britain. London: Allen and Unwin,1985.

17 Gordon D, Townsend P. Measuring the poverty line. RadicalStatistics 1990;47:5-12.

18 Hallerod B, BradshawJ, Holmes H. Adapting the consensualdefinition of poverty. In: Gordon D, Pantazis C eds.Breadline Britain in the 1990s, Report to the Joseph Rown-tree Foundation. York: Joseph Rowntree Foundation1995, 161-82.

19 Davies H, Joshi H, Clarke L. Is it cash the deprived areshort of? T R Stat Soc A. (in press).

20 Noble M, Cheung SY, Smith G and Smith T. Using censusdata to predict income support dependency. Policy andPolitics (in press).

21 Callaghan T, Nolan B, Whelan CT. Resources, deprivationand the measurement of poverty. J7ournal of Social Policy.1993;22(12):141-72.

22 Department of Social Security. Households below averageincome: a statistical analysis 1979-1991192. London:HMSO, 1994;178.

23 Goodman A, Webb S. Low inconie statistics: low inconiefamilies 1989-1992. Social Security Committee. House ofCommons Official Report (Hansard) 1995;254:xxxii.

24 Townend P, Davidson N. Inequalities in health: the Blackreport. 2nd ed. Harmondsworth: Penguin Books, 1988.

25 OPCS. The Autumn 1987 census wording test: variation oflong-term illness between areas. Consultation paper. London:OPCS, 1988.

26 Charlton J, Wallace M, White I. Long-term illness: resultsfrom the 1991 census. Population Trends. 1994;75:18-25.

27 Banks J, Dilnot A, Low H. The distribution of wealth in theUK. London: IFS. Commentary no 45; 1994.

Open discussionJOSHI - This methodology appears to me to pre-suppose that there is a unidimensional "thing" un-derlying all these indicators - that they are all beingused as indicators of one type of deprivation. Mightthere not be various different ways in which peoplemight be deprived?

GORDON - Yes, deprivation is multivariate, almost bydefinition. We define poverty in terms of multipledeprivation. When we do this analysis we dividethe groups into "poor" or "not poor" using themultivariate technique of discriminant analysis: welook at the different aspects of deprivation in relationto income, housing deprivation, deprivation of work,clothing deprivation, etc. But we do assume thatthere is such a thing as "poverty" and "not poverty".

JOSHI - Or maybe there is cash poverty and timepoverty.

GORDON - Certainly, these indices do not measuretime poverty.

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