‘No social security claimants’ housing clauses are associated with disproportionate difficulty and harm for disabled people in the UK. [Draft, not reviewed]

Many private landlords stipulate that they will not let their property to social security claimant, for example by advertising ‘No DSS’ in the UK. This is a contentious practice, with some claiming it is a necessary business practice while others argue it is discriminatory. Retrospective survey data (N=521), analysed by log-linear frequency analysis, shows significant interactions between disability, social security claims and both difficulty and harm when finding accommodation. Disabled claimants more frequently (OR = 4.97, 95% CI 2.59 – 9.57) experience difficulty and harm (OR = 2.79, 95% CI 1.59 – 4.90) due to No DSS clauses than non-disabled claimants.

Keywords: disability; housing; social security; discrimination


In the UK private housing rental market, advertisements of properties often contain the phrase ‘No DSS’ or similar (e.g. http://tinyurl.com/jcwpf24). This refers to the now-defunct Department of Social Security and, when used in this context is well understood to mean that the landlord will not consider letting the property to anyone in receipt of social security benefits. This is an issue of contention, particularly given the current economic climate. Homelessness is rising (Cooper, 2016) while the number of Housing Benefit claims have increased by approximately 570,000 since 2008 (Department for Work and Pensions, 2016).

Property owners claim they need to refuse benefit claimants for financial stability (e.g. Property Investment Project’s Landlord Blog at http://tinyurl.com/RefuseDSS) or because they are perceived as a risk to the property (Lawrenson, 2012). Conversely, some argue that ‘No DSS’ clauses are discriminatory and thus illegal (e.g. blog by Johnny Void, http://tinyurl.com/JVoid). Under the Equality Act (2010), indirect discrimination on the grounds of disability is illegal. Indirect discrimination is the situation in which, when a rule or policy (for example) is enforced uniformly but has a negative effect on particular groups, putting them at a particular disadvantage.

As there has been little to no academic or legal work on this topic and the existing evidence is anecdotal, the purpose of this study is to establish whether disabled truly people face greater difficulty than non-disabled people in the private rental market due to ‘No DSS’ clauses, and whether this causes harm.


Ethical Considerations

As I am not affiliated with any institution, I was not able to get approval from an Ethics Review Board for this project. However, the project was carried out according to the principles of the British Psychological Society, my accrediting body. To ensure security and anonymity for participants, limited data was collected and links to appropriate services (eg housing organisations) were provided.


521 participants completed one of two online surveys. The surveys were advertised on social networks in multiple ways to encourage responses from disabled and non-disabled people. Respondents were encouraged to share the surveys. Thus, participants were recruited by snowball and convenience sampling. 115 participants provided age data. Counts of responses are shown in Table 1.

Of the 115 participants reporting age, the median for disabled participants was 33 years (N = 38, IQR 9) while for non-disabled participants the median age was 30.50 (N = 77, IQR 16). This difference was not significant (Mann-Whitney U, z = .375, p = .71. There was also no significant difference (z = .272, p = .79) in the median age of benefit claimants (N = 46, Median = 32.50, IQR 15) and non-claimants (N = 69, Median = 33.00, IQR = 10).

Table 1.

Response Frequencies with Percentages

Answer Benefits Disabled Difficulty Harm
  N % N % N % N %
No 311 59.70 375 72.00 338 64.90 374 71.80
Yes 210 40.30 146 28.00 183 35.10 147 28.20



The questionnaire consisted of 8 questions; one multiple choice question to determine which benefits the respondent claims (if any), and a series of mutually exclusive yes-no questions on disability, difficulty due to No DSS clauses, and harm from inappropriate accommodation.  A separate questionnaire asked for age, gender and whether they had completed the previous questionnaire.


The frequencies of responses are shown above in Table 1. From this point, ‘Benefits’ refers to whether the participant claims any benefits, ‘Disabled’ refers to whether the participant identifies as disabled, ‘Difficulty’ refers to whether the participant experienced difficulty finding accommodation due to No DSS policies and ‘Harm’ refers to whether the participant or their household experienced harm from living in unsuitable accommodation when landlords would not consider renting to them due to their circumstances. The three-way (Difficulty x Benefits x Disability, and Harm x Benefits x Disability) contingency tables are shown in Table 2.

Table 2.

Three-Way Contingency Tables

Disabled Benefits Difficulty     Benefits Harm  
No No No Yes     No Yes
    257 23   No 251 29
  Yes 44a 51a   Yes 61a 34a
Yes No 20 11   No 17 14
  Yes 17a 98a   Yes 45a 70a

Notes. a denotes values used to construct Odds Ratios

Loglinear Frequency Analysis

Results of the loglinear frequency analyses (see Tabachnick & Fidell, 2007) of the two contingency tables shown in Table 2 are shown below in Table 3 (for Difficulty) and Table 4 (for Harm). For both Harm and Difficulty, there are significant interactions with disability and ongoing benefit claims. The significant association between disability and difficulty, and disability and harm, remains significant after the effect of benefit claims is removed.

Table 3.

Loglinear Analysis Effects for Difficulty x Benefits x Disability Contingency Table

Effect G2 df p
Three-Way Interaction 375.68 4 <.0001
Benefits x Difficulty 207.70 1 <.0001
Benefits x Disabled 127.12 1 <.0001
Difficulty x Disabled 137.64 1 <.0001
Benefits x Difficulty * 110.92 2 <.0001
Benefits x Disabled * 30.34 2 <.0001
Difficulty x Disabled * 40.86 2 <.0001

Notes. G2 ≈ χ2. * denotes partial relationship with third variable removed.

Table 4.

Loglinear Analysis Results for Harm x Benefits x Disability Contingency Table

Effect G2 df p
Three-Way Interaction 236.74 4 <.0001
Benefits x Harm 76.86 1 <.0001
Benefits x Disabled 124.36 1 <.0001
Harm x Disabled 82.24 1 <.0001
Benefits x Harm * 30.14 2 <.0001
Benefits x Disabled * 77.64 2 <.0001
Harm x Disabled* 35.52 2 <.0001

Notes. G2 ≈ χ2. * denotes partial relationship with third variable removed.

On inspection of the residual plots (Figure 1 and 2) for Difficulty and Harm, it is apparent that this relationship occurs because disabled participants are significantly over-represented in both the Yes-Benefit-Yes-Difficulty and Yes-Benefit-Yes-Harm cells of the contingency tables. Comparing non-disabled and disabled benefit claimants, more frequently (OR = 4.97, 95% CI 2.59 – 9.57) experience difficulty due to No DSS clauses, and harm from not being able to find suitable accommodation (OR = 2.79, 95% CI 1.59 – 4.90).

Figure 1.

Mosaic plot of Difficult x Disability x Social Security Claim. Shaded areas represent standardised residuals >=4.

Difficulty mosiac

Figure 2.

Mosaic plot of Harm x Disability x Social Security Claim. Shaded areas represent standardised residuals >=4.

Harm mosaic


First, we can conclude that No DSS clauses are harmful to all benefit claimants, disabled and non-disabled alike. However, they disproportionately affect disabled people. There is a significant interaction between disability and ongoing benefit claims when trying to find a home and experiencing difficulty due to No DSS clauses and harm from not finding suitable accommodation.

King (personal communication, 2016) raised the potential confound of age – given the logical association between increasing age and decreasing health, perhaps the effects observed are related to age discrimination rather than disability per se. This is not supported by the present data. In the sample that gave demographic data, there were no significant differences in age between disabled and non-disabled participants, or benefit claimants and non-claimants.

There are flaws in the present study which may limit its generalisability. For example, information was only collected online and thus data could not be collected from people who, for whatever reason, lack an internet connection. Further, to keep the questionnaire as short and simple as possible, it was not possible to ask about specific types of harm or consequences which limited the depth of the analysis that was possible. This presents a further avenue for research, as does the fact that this analysis considered social security benefits as a homogenous group. No differentiation was made between Jobseeker’s Allowance claimants and Child Benefit payments, and ‘No DSS’ clauses, which ostensibly applying to all benefits, may not be applied universally across all benefit types.

Some concerns were raised about the validity of self-report data in this context. It was suggested that participants may try and bias the results, given the highly political subject matter and current socio-political climate. The questionnaire was designed to limit this – participants were told the project was looking at issues that can arise when trying to find a home without explicit reference to disability or social security. Ultimately, there is ‘no strong evidence to lead us to conclude that self-report data are inherently flawed’ (Chan, p. 330), and self-report was the only practical method of collecting this data. There is no other feasible way that we could determine whether participants had experienced harm, for example.  While it is possible that some participants may have intended to bias the results, the sample size, large effects, and previous research (eg Gosling, Vazire, Srivastava & John, 2004) suggest this is unlikely and the effects would be minimal.

To better understand the relationship between disability, benefit claims and housing discrimination, future research could examine this issue prospectively, observing the relative difficulties of disabled and non-disabled benefit claimants. Approaching the issue from a qualitative perspective, to better understand the particular difficulties and harms disabled people experience and the reason why landlords use No DSS clauses, would be valuable and provide insights that may be applied to reduce this discrimination.

It would be worthwhile for future work to also consider this issue from an international perspective given the currently socio-political climate in the UK, which has undergone significant social security reforms which have been demonstrated to disadvantage poorer, less healthy claimants (Hume, in press). It is possible that other states have implemented discrimination legislation or social security regulations which either protect against this ‘No DSS’ effect or make it irrelevant. For example, landlords cite the insecurity of social security payments due to conditionality as a reason they refuse any social security tenants. In states where this is not the case, the continued existence of the ‘No DSS’ effect would provide evidence against this practice. Such insights would be valuable in tackling disability discrimination housing in the UK and elsewhere.

In the UK, indirect discrimination, as defined by the Equality Act 2010, occurs when one rule is universally enforced but causes particular disadvantages for members of protected groups, including disabled people. While the Act requires that the discriminatory act not be a “proportionate means of achieving a legitimate aim” (a legal question beyond the scope of this study), this study establishes that disabled people are significantly more likely to experience difficulty finding a home due to No DSS clauses, and that this difficulty is associated with harm to the person or their household. Amongst benefit claimants, the odds of a disabled person experiencing difficulty finding accommodation due to No DSS clauses are approximately 5 times that of non-disabled people, thus disabled people face a particular disadvantage from these rules.


Chan, D. (2009) “So why ask me? Are self-report data really that bad?” In Statistical and methodological myths and urban legends: Doctrine, verity and fable in the organizational and social sciences, edited by Charles E. Lance and Robert J. Vanderberg, 309-336. London: Routledge.

.Cooper, C. (2016). Homelessness: Number of rough sleepers in England rises at ‘unprecedented’ Rate. Independent, February 25, http://www.independent.co.uk/news/uk/home-news/homelessness-number-of-rough-sleepers-in-england-rises-at-unprecedented-rate-a6895826.html

Department for Work and Pensions. Housing benefit caseload Statistics. 2016 [cited 03/04 2016]. Available from https://www.gov.uk/government/statistics/housing-benefit-caseload-statistics.

Gosling, S. D., S. Srivastava and O. P. John (2004) Should we trust web-based Studies? A comparative analysis of six preconceptions about Internet Questionnaires. American Psychologist, 59(2), pp. 93-104.

Hume, J. N. (In press) Bias in the Work Capability Assessment: A human rights issue? Radical Statistics.

Lance, C. E., and R. J. Vanderberg, eds. (2009). Statistical and methodological myths and urban Legends: Doctrine, verity and fable in the organizational and social Sciences. London: Routledge.

Lawrenson, D. (2012). The seven reasons why landlords won’t let to tenants on Benefits. The Guardian, May 2. http://www.theguardian.com/housing-network/2012/may/02/tenants-housing-benefit-private-landlords

Tabachnick, B. G., and L. S. Fidell. (2007). Using multivariate statistics. London: Pearson


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