3. HOMELESSNESS INDICATOR

TABLE 1 – INDICATOR DESCRIPTION

Information component	Pg 4 Health Summary – Indicator 3
Subject category / domain(s)	Our Communities
Indicator name (* Indicator title in health profile)	*Homelessness
PHO with lead responsibility	NEPHO
Date of PHO dataset creation	Dec 2006
Indicator definition	Statutory homeless households, percentage of total households on the local authority housing register, all ages, 2004 to 2005, persons
Geography	England, GOR, Local Authority: Counties, County Districts, Metropolitan County Districts, Unitary Authorities, London Boroughs
Timeliness	This indicator is updated annually by Neighbourhood Statistics.  However it should be noted that quarterly statistics are published on the Department for Communities and Local Government website: www.communities.gov.uk
Rationale:What this indicator purports to measure	Estimates of homelessness amongst the most needy and vulnerable groups in society
Rationale:Public Health Importance	Homelessness is associated with severe poverty and is a social determinant of health.  Homelessness is associated with adverse health, education and social outcomes, particularly for children.  To be deemed statutorily homeless a household must have become unintentionally homeless and must be considered to be in priority need.  As such, statutorily homeless households contain some of the most vulnerable and needy members of our communities.  The statutory homeless statistics suggest that 62% of officially accepted homeless households include dependent children or an expectant mother.  Preventing and tackling homelessness requires sustained and joined-up interventions by central and local government, health and social care and the voluntary sector.
Rationale: Purpose behind the inclusion of the indicator	To reduce the level of homelessness, particularly amongst the most vulnerable and needy groups in society.
Rationale:Policy relevance	The Department for Communities and Local Government (DCLG) has published a strategy document, ‘Sustainable Communities: Settled Homes: Changing Lives’ which sets out the Government’s plans on reducing homelessness with the aim of halving the number of homeless households in temporary accommodation by 2010.
Interpretation: What a high / low level of indicator value means	A high indicator value (red circle in health summary chart) represents a statistically significant higher level of statutory homelessness for that local authority when compared to the national value.A low indicator value (amber circle in health summary chart) represents a statistically significant lower level of statutory homelessness for that local authority when compared to the national value. However no amount of homelessness is acceptable, and therefore a low indicator value should not mean that public health action is not needed.
Interpretation: Potential for error due to type of measurement method	The statistic necessarily only measures the incidence of official homelessness.  The number of households who are homeless but do not apply to the local authority and are therefore not considered under Housing Act legislation is not known.  Reasons may include a lack of knowledge of the legislation, a correct or misplaced belief that they will not qualify for assistance, and / or a desire not to rely on state support.This statistic does not include households that have become unintentionally homeless but are not considered to be in priority need or households that have become intentionally homeless.  Rough sleepers are also not included.Therefore, the measure is an underestimate of the extent of homelessness, both of those populations who would qualify for assistance and for the larger number of people who fall outside of the legislation.See: Poverty: the outcomes for children. 2001. ESRC. Edited by: Jonathan Bradshaw.
Interpretation: Potential for error due to bias and confounding	Potential confounding factors associated with the homelessness statistic include: housing affordability, housing capacity, variation in local authority methods of collection and collation of housing and homelessness statistics, local variation in demand for housing.
Confidence Intervals: Definition and purpose	A confidence interval is a range of values that is normally used to describe the uncertainty around a point estimate of a quantity, for example, a mortality rate. This uncertainty arises as factors influencing the indicator are subject to chance occurrences that are inherent in the world around us. These occurrences result in random fluctuations in the indicator value between different areas and time periods. In the case of indicators based on a sample of the population, uncertainty also arises from random differences between the sample and the population itself.The stated value should therefore be considered as only an estimate of the true or ‘underlying’ value. Confidence intervals quantify the uncertainty in this estimate and, generally speaking, describe how much different the point estimate could have been if the underlying conditions stayed the same, but chance had led to a different set of data. The wider is the confidence interval the greater is the uncertainty in the estimate.Confidence intervals are given with a stated probability level. In Health Profiles 2007 this is 95%, and so we say that there is a 95% probability that the interval covers the true value. The use of 95% is arbitrary but is conventional practice in medicine and public health. The confidence intervals have also been used to make comparisons against the national value. For this purpose the national value has been treated as an exact reference value rather than as an estimate and, under these conditions, the interval can be used to test whether the value is statistically significantly different to the national. If the interval includes the national value, the difference is not statistically significant and the value is shown on the health summary chart with a white symbol. If the interval does not include the national value, the difference is statistically significant and the value is shown on the health summary chart with a red or amber symbol depending on whether it is worse or better than the national value respectively.

TABLE 2 – INDICATOR SPECIFICATION

Indicator definition: Variable	Statutory homeless households
Indicator definition: Statistic	Percentage of total households on the local authority housing register
Indicator definition: Gender	Persons
Indicator definition: age group	All ages
Indicator definition: period	1 April 2004 to 31 March 2005
Indicator definition: scale
Geography: geographies available for this indicator from other providers	England, GOR, Local Authority: Counties, County Districts, Metropolitan County Districts, Unitary Authorities, London Boroughs available fromhttp://neighbourhood.statistics.gov.uk
Dimensions of inequality: subgroup analyses of this dataset available from other providers	Data relating to the ethnicity of households is collected as part of the HSSA.
Data extraction: Source	Department for Communities and Local Government
Data extraction: source URL	http://www.communities.gov.uk/index.asp?id=1156546
Data extraction: date	Data extracted from source as at: 13th December 2006
Numerator: definition	Count of households (2004/2005) who are eligible, unintentionally homeless and in priority need, for which the local authority accepts responsibility for securing accommodation under part VII of the Housing Act 1996 or part III of the Housing Act 1985.
Numerator: source	Department for Community and Local Government.
Denominator: definition	Count of households (2004/2005) on the local authority housing register (a register of all households that have applied for social rented housing).
Denominator: source	2004/2005 Housing Strategy Statistical Appendix (HSSA) – Section C (The Housing Register) DCLG.
Data quality: Accuracy and completeness	Each LA checks the data prior to sending it to the Housing Statistics Department of the ODPM. A built-in-validation system allows each LA to check the accuracy of the data (see detailed on the ‘Validation’ section)Once the data has been submitted to the ODPM, validation checks are carried out manually.The HSSA and P1E guidance notes help to provide LAs with universal definitions.Again, for financial management purposes, each LA has to maintain accurate and up-to-date information on homelessness.As ethnicity figures are not provided for each quarterly return for: South Staffordshire, there are no breakdown figures available for this LA however, a combined total figure is provided.At LA level, 7% of total entries are missing. This is due to incomplete returns and methods used to safeguard the confidentiality of the data (see ‘Disclosure Control’ Section). 3% of the missing entries are due to LAs not making the returns or providing incomplete returns to the Housing Statistics Department of the ODPM.There has been no imputation at LA, Regional or National level. Figures registered as missing values at LA level have not been estimated and have therefore been considered to be zeros when aggregating to a higher level.

TABLE 3 – INDICATOR TECHNICAL METHODS

Numerator: extraction	Simple download.
Numerator: aggregation /allocation	Counts had already been allocated to local authorities.
Numerator data caveats	To be classified as statutorily homeless, the following must be satisfied: § They are homeless, defined as those without any right to access secure accommodation for that night i.e. they are not legal tenants of any property, nor own any property. Or they can also be classed as ‘potentially homeless’ if they are about to lose their dwelling, be evicted, within 28 days. § They must have a local connection (lived or worked in the area, family in the area, have a care responsibility or need care from relatives in the area). § They are in priority need i.e. had dependent children in them (aged under 16 years) or are an older person household, or vulnerable. § The homeless household must not be intentionally homeless i.e. losing their previous accommodation through their own action such as not paying rent or a mortgage.By contrast the ‘non-statutory’ homeless are, those to whom no duty is owed either because they are deemed intentionally homeless, or are not in a priority need categories. These include the ‘single homeless’, many of whom are now young people of both sexes and, in the larger cities, of different ethnic groups, as well as some older white men.
Denominator data caveats	The total number of households on the local authority housing register was not available for one local authority – in this case the total from the most recently available year of collection was used (2002).  This is consistent with the approach used by the Office for National Statistics.
Methods used to calculate indicator value	Number of households deemed to be statutorily homeless during the period April 2004 to March 2005, divided by the number of households on the local authority housing register as at 1st April 2005, multiplied by 100.  This method is used by the Office for National Statistics in deriving their homelessness indicator.
Small Populations: How Isles of Scilly and City of London populations have been dealt with	Isles of Scilly and City of London have been included in regional and England numerators and denominators.  Isles of Scilly have been included in the numerator and denominator for the County of Cornwall.
Disclosure Control	Data have been suppressed in this dataset to protect both the confidentiality of individual information and the potential statistical instability caused by low counts. As a consequence, sums of counts may not equal related totals.
Confidence Intervals calculation method	The 95% confidence intervals are calculated with the method described by Wilson and by Newcombe which is a good approximation of the exact method.First calculate the estimated proportions of subjects with (p) and without (q) some feature of interest from a sample of size n.proportion with feature of interest = p = r/n. proportion without feature of interest = q = 1 – p, where r is the observed number of subjects with the feature of interest. Second, calculate the three quantities: A = 2r + z2;     ;     and     C=2(n+z2),where z is the appropriate value, z1-α/2, from the standard Normal distribution.  Then the confidence interval for the population proportion is given by (A-B)/C    to   (A+B)/CThis method has the considerable advantage that it can be used for any data.  When there are no observed events, r and hence p are both zero, and the recommended confidence interval simplifies to 0 to z2/(n+z2).  When r = n so thatp = 1, the interval becomes n/(n+z2) to 1.Wilson EB. J Am Stat Assoc 1927, 22, 209-212Newcombe, RG.  Two-sided confidence intervals for the single proportion: comparison of seven methods.  Stat Med 1998;17:857-72.

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