Scottish house condition survey: 2018 key findings

Figures from the 2018 survey, including updated fuel poverty rates, energy efficiency ratings, the condition of housing and the Scottish Housing Quality Standard.

This document is part of a collection

7 Technical Notes and Definitions

7.1 Survey Estimation

316. From 2012 onwards, the SHCS is a module of the Scottish Household Survey (SHS)[67]. In general, around one third of respondents to the SHS are invited to participate in a follow-up inspection by SHCS building surveyors. For 2018, this was increased to almost half of respondents to ensure that the required number of households for the physical survey sample was achieved.

7.1.1 Sample Sizes and Gross Dwelling Numbers

317. In Table 62 we provide the sample sizes in the social interview and physical dwelling inspection follow-up for all years of the annual SHCS to 2018.

Table 62: Achieved Samples for SHCS Streams of the Scottish Household Survey and Base Number of Occupied Dwellings by Survey Year, 2003/4-2018

Survey Year Social Interview Physical Survey Households (000s)
2003/4 3,870 3,090 2,269
2004/5 3,783 3,093 2,301
2005/6 3,679 3,147 2,315
2007 3,867 3,033 2,314
2008 3,763 3,015 2,331
2009 4,153 3,346 2,344
2010 3,853 3,115 2,357
2011 3,949 3,219 2,368
2012 3,813 2,787 2,386
2013 3,780 2,725 2,402
2014 3,787 2,682 2,420
2015 4,083 2,754 2,434
2016 4,220 2,850 2,452
2017 5,049 3,002 2,464
2018 4,843 2,964 2,477

318. Table 62 also shows the total number of households in Scotland for each survey year which provides the basis for grossing up the estimates of households and dwellings in this report. These figures are produced annually by the National Records of Scotland[68] as part of their inter-censal household estimates publication.

319. The SHCS is a sample survey. All survey figures are estimates of the true prevalence within the population and will contain some error associated with sampling variability. The likely size of such variability can be identified, by taking account of the size and design of the sample, as described in sections 7.1.2 to 7.1.5.

320. In addition to sampling variability, there are other sources of uncertainty, such as those arising from incomplete responses or failure to secure participation in the survey from each sampled household. Where non-response is not random, i.e. some types of household are less likely to participate than others, bias is introduced into the survey data. Such errors have not been quantified in this report.

321. In general, the smaller the sample size, the greater the likelihood the estimate could be misleading, so more care must be taken when using smaller subsets of the survey sample for analysis. In this report estimates representing 2 or fewer cases, or where the base sample is below 30 have been suppressed.

322. Different types of estimates are subject to different levels of uncertainty associated with sampling and design. For example, estimates of change (i.e. figures relating to comparisons across survey years) are generally subject to greater sampling error than point-in-time estimates (i.e. figures relating to one survey year only) and such errors would be understated by figures in Table 63. There is more uncertainty associated with complex measures, such as the fuel poverty rate and this is not quantified in this report or reflected by stated confidence intervals in Table 63.

7.1.2 Confidence Intervals

323. By convention, a 95% confidence interval is used to quantify the variability of a sample estimate, under which there is a 1 in 20 chance that the true value will fall outside the given confidence interval.

324. Table 63 shows the 95% confidence limits for estimates of proportions based on sub-samples of various sizes before design effects are taken into account.

Table 63: Approximate 95% Confidence Limits for Estimates Based on SHCS Sub-Samples of Various Sizes (Excluding Design Effects)

Sub-sample size (corresponding to 100%) Estimate (lookup to nearest multiple of 5%)
1% 2% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
or or or or or or or or or or or
99% 98% 95% 90% 85% 80% 75% 70% 65% 60% 55%
percentage points ( + / - )
100 2.0 2.7 4.3 5.9 7.0 7.8 8.5 9.0 9.3 9.6 9.8 9.8
150 1.6 2.2 3.5 4.8 5.7 6.4 6.9 7.3 7.6 7.8 8.0 8.0
200 1.4 1.9 3.0 4.2 4.9 5.5 6.0 6.4 6.6 6.8 6.9 6.9
250 1.2 1.7 2.7 3.7 4.4 5.0 5.4 5.7 5.9 6.1 6.2 6.2
300 1.1 1.6 2.5 3.4 4.0 4.5 4.9 5.2 5.4 5.5 5.6 5.7
350 1.0 1.5 2.3 3.1 3.7 4.2 4.5 4.8 5.0 5.1 5.2 5.2
400 1.0 1.4 2.1 2.9 3.5 3.9 4.2 4.5 4.7 4.8 4.9 4.9
450 0.9 1.3 2.0 2.8 3.3 3.7 4.0 4.2 4.4 4.5 4.6 4.6
500 0.9 1.2 1.9 2.6 3.1 3.5 3.8 4.0 4.2 4.3 4.4 4.4
600 0.8 1.1 1.7 2.4 2.9 3.2 3.5 3.7 3.8 3.9 4.0 4.0
700 0.7 1.0 1.6 2.2 2.6 3.0 3.2 3.4 3.5 3.6 3.7 3.7
800 0.7 1.0 1.5 2.1 2.5 2.8 3.0 3.2 3.3 3.4 3.4 3.5
900 0.7 0.9 1.4 2.0 2.3 2.6 2.8 3.0 3.1 3.2 3.3 3.3
1,000 0.6 0.9 1.4 1.9 2.2 2.5 2.7 2.8 3.0 3.0 3.1 3.1
1,100 0.6 0.8 1.3 1.8 2.1 2.4 2.6 2.7 2.8 2.9 2.9 3.0
1,200 0.6 0.8 1.2 1.7 2.0 2.3 2.5 2.6 2.7 2.8 2.8 2.8
1,300 0.5 0.8 1.2 1.6 1.9 2.2 2.4 2.5 2.6 2.7 2.7 2.7
1,400 0.5 0.7 1.1 1.6 1.9 2.1 2.3 2.4 2.5 2.6 2.6 2.6
1,500 0.5 0.7 1.1 1.5 1.8 2.0 2.2 2.3 2.4 2.5 2.5 2.5
1,600 0.5 0.7 1.1 1.5 1.7 2.0 2.1 2.2 2.3 2.4 2.4 2.5
1,700 0.5 0.7 1.0 1.4 1.7 1.9 2.1 2.2 2.3 2.3 2.4 2.4
1,800 0.5 0.6 1.0 1.4 1.6 1.8 2.0 2.1 2.2 2.3 2.3 2.3
1,900 0.4 0.6 1.0 1.3 1.6 1.8 1.9 2.1 2.1 2.2 2.2 2.2
2,000 0.4 0.6 1.0 1.3 1.6 1.8 1.9 2.0 2.1 2.1 2.2 2.2
2,200 0.4 0.6 0.9 1.3 1.5 1.7 1.8 1.9 2.0 2.0 2.1 2.1
2,400 0.4 0.6 0.9 1.2 1.4 1.6 1.7 1.8 1.9 2.0 2.0 2.0
2,600 0.4 0.5 0.8 1.2 1.4 1.5 1.7 1.8 1.8 1.9 1.9 1.9
2,800 0.4 0.5 0.8 1.1 1.3 1.5 1.6 1.7 1.8 1.8 1.8 1.9
3,000 0.4 0.5 0.8 1.1 1.3 1.4 1.5 1.6 1.7 1.8 1.8 1.8
3,200 0.3 0.5 0.8 1.0 1.2 1.4 1.5 1.6 1.7 1.7 1.7 1.7
3,400 0.3 0.5 0.7 1.0 1.2 1.3 1.5 1.5 1.6 1.6 1.7 1.7
3,600 0.3 0.5 0.7 1.0 1.2 1.3 1.4 1.5 1.6 1.6 1.6 1.6
3,800 0.3 0.4 0.7 1.0 1.1 1.3 1.4 1.5 1.5 1.6 1.6 1.6
4,000 0.3 0.4 0.7 0.9 1.1 1.2 1.3 1.4 1.5 1.5 1.5 1.5

7.1.3 Design Effects

325. The design effect is the ratio between the variance (average deviation of a set of data points from their mean value) of a variable under the sampling method used (actual) and the variance computed under the assumption of simple random sampling (standard). In short, a design effect of 2 would mean doubling the size of the sample used (actual) in order to obtain the same level of precision as with a simple random sample; a design effect of 0.5 implies the reverse. Design effect adjustments are necessary where standard errors are affected by the design and complexity of the survey.

326. Generally speaking, disproportionate stratification and sampling with non-equal probabilities tends to increase standard errors, giving a design effect greater than 1. However, this can be controlled by deliberately over-sampling in stratum where the item of interest is either very rare or variable. The impact of non-response weighting on standard errors tends to be, although with exceptions, comparatively limited. The sampling design of the SHCS meets the criteria above in that disproportionate stratification is applied across the 32 Local Authority areas with over-sampling of remote rural areas - for example in Shetland and Orkney. As a result, one would expect the design effect to be above 1 although only modestly so.

327. Table 64 shows the design effects for all the SHCS surveys since 2003/4. When using a mixture of the physical and social survey data, the physical survey design effect must be used. The design effects for the 2018 SHCS are 1.11 for the physical and 1.08 for the social surveys.

328. When producing estimates at Local Authority level, no design effect adjustment of standard errors is necessary because simple (actually equal interval) random sampling was carried out within each Local Authority.

Table 64: Design Effects for the Annual SHCS, 2003/4 to 2018

Survey Year Design Effect
Physical Weight Social Weight
2003/04 1.14 1.13
2004/05 1.18 1.17
2005/06 1.14 1.14
2007 1.13 1.11
2008 1.11 1.11
2009 1.09 1.08
2010 1.11 1.1
2011 1.12 1.11
2012 1.09 1.08
2013 1.09 1.08
2014 1.09 1.08
2015 1.10 1.08
2016 1.10 1.08
2017 1.10 1.08
2018 1.11 1.08

7.1.4 Example: Accounting for Sampling Variation

329. Both confidence intervals and the design effect must be accounted for when quoting confidence levels on a statistic. For example we may wish to find the confidence interval for the proportion of pre-1919 detached houses in Table 1.

330. The stated proportion is 4%. The sub-sample size for the group (the sample size of 100% of the group) is also provided in the table, which in this case is the full survey sample: n=2,964. Reading from Table 63 in the row labelled 3,000 (the closest value to our n value) in the column for 5% we find the confidence interval for this estimate is 0.8 percentage points.

331. To account for the design effect, we must multiply this value by the physical design effect value from Table 64 since this statistic relates to the physical properties of the dwelling. So the true confidence interval is 0.8 x 1.11 = 0.888 ≈ 0.9 percentage points. We can therefore be 95% confident that the true proportion of pre-1919 detached houses is between 3.1% and 4.9%.

7.1.5 Statistical Significance

332. Because the survey’s estimates may be affected by sampling errors, apparent differences may not reflect real differences in the population. A difference is significant if it is so large that a difference of that size is unlikely to have occurred purely by chance.

333. Comparisons in this publication are tested at the 5 per cent level as described in section 7.1.2. Testing significance involves comparing the difference between two statistics (for example, the per cent of households rated as EPC band C or better in 2018 compared to 2017 or for the social sector compared to the private sector) with the 95 per cent confidence limits for each of the two estimates taken into account.

334. Our approach to testing statistical significance follows that described in Annex 3 of the Scottish Household Survey annual report[69].

7.1.6 Table Conventions

335. The following conventions are used in tables:

0 indicates value is rounded to 0.

- indicates no sample cases in this category

* indicates base sample too small to report (below 30 cases) or estimate representing 2 or fewer sampled households

336. Because of rounding, figures in tables and charts may not always add exactly.

7.2 Missing Tenure Information

337. Because of a routing error tenure information is not available for a small number of cases in the 2012 and 2013 surveys (46 in 2012, 42 in 2013). This was rectified for the 2014 fieldwork and the full sample has been used when reporting on tenure for subsequent years. This introduces some discontinuities in comparing statistics for the social (or the private) sector between 2014 and 2015, on the one hand, and previous years, on the other. For further details please refer to the respective earlier Key Findings reports.

7.3 Energy Models

338. Two different models are used to produce the energy efficiency outputs in this report. They are based on the same core methodology but have some different assumptions and calculations which affect the output values.

Table 65: Summary of Domestic Energy Models used on SHCS Data

Model SAP BREDEM 2012
Version SAP 2009[70]

SAP 2012[71] and RdSAP 9.92 for 2014 onwards. Additionally, RdSAP 9.93 for 2018.
Version 1.0 for data up to 2013

Version 1.1 for data from 2014 onwards
Outputs Energy Efficiency Rating

Environmental Impact Rating

  • Fuel poverty energy use
    • Carbon emissions
    • Fuel poverty running costs
Fuel Prices SAP standard Based on a range of sources[72]
Occupancy Number of occupants derived based on total floor area of the dwelling Actual number of occupants in the dwelling
Heating regime 21°C in the main living area and 18°C elsewhere;
9 hours per weekday and 16 hours at the weekend
As SAP, except for vulnerable households for fuel poverty related statistics, where:
23°C in the main living area and 20°C elsewhere;
16 hours per day
Climate East Pennines Based on geographical location
Energy end-use included
  • space heating
    • water heating
    • fixed lighting
    • gains from renewable energy technologies.
As SAP but also energy used for:
• cooking
• running appliances

339. Energy related statistics presented in this report are based on RdSAP 9.92 and additionally 9.93 for SAP derived variables for 2018 only, as version 9.93 was released in November 2017.

340. Carbon emissions are calculated on the basis of the standard heating regime, applying carbon intensity values to each type of fuel used. Emissions factors for the BREDEM 2012 model come from SAP 2012 and are provided in Table 66.

Table 66: Carbon Intensity of Common Heating Fuels, SAP 2012

Fuel kg CO2 per kWh
Mains gas 0.216
LPG 0.241
Oil 0.298
Coal 0.394
Anthracite 0.394
Smokeless fuel 0.433

- logs


- pellets


- chips

Electricity 0.519

341. For 2018 data, SAP based energy variables under both RdSAP v9.92 and v9.93 are reported. Compared to v9.92, U-values for solid, insulated stone and uninsulated cavity walls have improved, whereas they have declined for insulated cavity walls. As a result, the mean SAP rating under v9.93 is 0.16 SAP points less than under v9.92.

7.4 Fuel prices for pre-payment meters

342. The 2016 SHCS collected information about the presence of pre-payment meters for energy supply. This allowed us to assign the appropriate fuel price which in 2016 was higher than the overall weighted average of all payment methods. In 2017 and 2018 this approach has continued, although prepayment electricity and gas prices have decreased in this time, while non-prepayment electricity prices increased compared to 2016.

7.5 Fuel Poverty Income

343. For the 2017 SHCS, an updated set of questions collecting council tax information were incorporated and accounted for in fuel poverty analysis. Previously respondents were only asked to provide what they paid in council tax whether or not they received any deductions or reductions. The survey now distinguishes between reported council tax after any deductions or reductions, and full council tax. This reduces the risk of double counting Council Tax Reduction in household income in the former case.

344. As described in section 4.5, income for fuel poverty analysis is total household income (a sum of the highest income householder and their spouse/partner’s income), net of council tax and housing costs. For income poverty analysis, this income is equivalised, and compared against an adjusted FRS poverty threshold for a couple with no children, to account for the fact the latest published FRS data relate to 2017/18. 2017 income poverty results use the published FRS poverty threshold, rather than the adjusted threshold.

345. As figures presented in this report are a best estimate of fuel poverty and extreme fuel poverty rates under the proposed new definition of fuel poverty, following amendments agreed at Stage 2 of the Fuel Poverty (Targets, Definition and Strategy) Bill, income poverty and fuel poverty figures will not match those published in the 2017 Key Findings report.

7.6 Bedroom Standard Correction

346. A minor correction to how bedrooms are allocated to households as part of Bedroom Standard derivations was applied in the 2018 SHCS Key Findings report. The impact was small, with point estimates changing by one percentage point or less, where affected.

7.7 Basic Disrepair Correction

347. In the 2018 Key Findings report, a minor correction to the derivation of basic disrepair was applied to properly include disrepair to doors and frames. Affected statistics reported in Table 46 typically changed by less than a percentage point, although the 2016 no basic disrepair rate changed from 32% to 31%.

7.8 Extent of Disrepair Correction

348. The methodology for deriving two measures of disrepair were revised in the 2013 Key Findings report: “extensive disrepair” (see section 6.5 of SHCS 2013 Key Findings report) and “serious disrepair” under the Scottish Housing Quality Standard. These revisions affected statistics up to 2013. Further details are available in the Methodology Notes to the 2013 Key Findings report[73].

7.9 Boilers

349. Testing compliance of boilers with current Scottish Building Standards for domestic properties is carried out by comparing the boiler efficiency to minimum requirements. Data on the efficiency of households’ heating systems was first produced by BRE for the 2012 SHCS. However, there was a change to the methodology for the 2014 and 2015 SHCS which made an adjustment to the modelling to allow for the assumption that a poorly controlled system is in effect less efficient.

350. In the 2016 SHCS report, the full boiler efficiency dataset was revised to ensure it was on a consistent basis across years and represents the efficiency of the heating system before any adjustments for lack of controls. Efficiencies are taken directly from the Product Characteristics Database whenever possible and from the SAP default efficiencies for that system otherwise. This is therefore more representative of the actual boiler efficiency.

351. Furthermore, the thresholds used to test compliance for oil condensing boilers were also updated in 2016 to reflect current minimum standards. The full time series presented in the 2017 and 2018 report continues to reflect these changes.

7.10 Scottish Housing Quality Standard

352. 2015 data on compliance with the SHQS was revised in the 2016 publication. An error was identified in the method used to compile the data for the failure rate of the Energy Efficiency criterion in that year. This also affected the overall SHQS failure rate for 2015.

7.11 Definitions of Categories in the Key Findings Report

7.11.1 Dwelling Types

353. The SHCS uses the following definitions of dwelling types:

  • Detached house: a house that is free standing with no party walls;
  • Semi-detached house: a house that is only attached to one other dwelling, commercial premise etc. The two properties taken together should be detached from any other properties
  • Terraced house: a house forming part of a row of three or more dwellings, commercial premises etc.
  • Tenement flat: a dwelling within a common block of two or more floors (commonly up to five storeys but may be higher in certain circumstances) where some or all of the flats have a shared or common vertical access. The selected dwelling need not share the access, but may be situated within the block with shared/common access (own door flat)
  • 4-in-a-block: each flat in a block has its own independent access. Flats on the upper level have an internal or external stair
  • Tower/slab: flats in a high rise (ten or more storeys) or flats where the common circulation is predominantly horizontal (maisonette, balcony or gallery access)
  • Flat from a conversion: flats resulting from the conversion of a house only. A flat converted from a non-residential building (e.g. a warehouse) is classified according to the above flat types.

7.11.2 Household Types

354. This report uses the following classification of household types:

  • Families: Households which contain at least one child aged under 16. Resident adults may be of any age.
  • Older households: Small households made up of one or two residents, at least one of which is aged 65 or older.
  • Other households. These are all other households with adult residents (of any age) and no children.

355. This classification is derived from the more detailed grouping used in the Scottish Household Survey[74] as set out in Table 67.

Table 67: Household Types Classification Used in the SHCS and the SHS Reports

Families A single parent household – contains one adult of any

age and one or more children.

A small family household – contains two adults of any

age and one or two children.

A large family household – contains two adults of any

age and three or more children, or three or more adults of any age and one or more children.
Older households A single older household - contains one adult of pensionable age and no children.

An older smaller household – contains one adult aged 16-64 and one of pensionable age and no children, or two adults of pensionable age and no children.
Other households A single adult household – contains one adult aged 16-64 and no children.

A small adult household – contains two adults aged 16-64 and no children.

A large adult household – contains three or more adults and no children

356. The pensionable age threshold used for the 2015 to 2018 SHCS Key Findings reports is 65 years for both men and women. Previous publications used 65 for men and 60 for women. Therefore the categories ‘Older households’ and ‘Other households’ used from 2015 are not fully comparable with previous years.

7.11.3 Urban Rural Classifications

357. The urban/rural classification in this report is the Scottish Government 2 fold and 6 fold Urban Rural Classification[75]. Dwellings in settlements with over 3,000 people are considered urban by this definition. The Scottish Government published the 2016 Urban Rural Classification in 2017. However, to remain consistent with the classification underpinning survey weight derivations, the 2013/14 Urban Rural Classification (2011 datazone edition) is used for reporting 2016, 2017 and 2018 data. Prior to 2016, 2001 datazones are used.

7.11.4 Gas Grid Coverage Derivation

358. Determining whether a dwelling is within the coverage of the gas grid is based on its proximity to gas distribution pipes. The current methodology for deriving gas grid coverage was first used for the 2013 Key Findings Report. A dwelling is considered to be “on the gas grid” if it is within 63m of a low/ medium/ intermediate pressure pipe, the usual maximum distance for a standard domestic connection.

359. Figure 33 shows how this is derived using GIS mapping. From the dwelling location information of surveyed properties, a 63m buffer is drawn. Where this buffer intersects a gas distribution pipe, the dwelling is said to be on the gas network. In the example, dwelling A is on the network, while dwelling B is not.

360. The gas grid information used for this mapping is provided by SGN. It includes both the national gas network and the Scottish Independent Undertakings (SIUs), where gas is provided in areas remote from the national gas grid. It does not however include information on pipes owned and operated by Independent Gas Transporters (IGTs). Therefore, dwellings classified as off-grid by the survey may be within 63m of an IGT operated gas distribution pipe and potentially have a connection to the gas grid and the methodology may therefore slightly undercount dwellings within the range of the gas grid.

Figure 33: Gas Grid Derivation with GIS

Figure 33: Gas Grid Derivation with GIS

7.11.5 Reasons Why Home Heating is Difficult

361. The full text of this question is: “Which of these things, if any, make it difficult to heat your home”[76]. Response categories have been grouped for reporting, as described in Table 68. Respondents were able to choose any combination of reasons why heating their home was difficult.

Table 68: Potential Responses to Question ht14

Group Response Number Response
Poor or inadequate heating ht14_01 No Central Heating
ht14_02 Not enough heaters/radiators
ht14_03 Position of heaters/radiators
ht14_04 Poor/need new heating system
ht14_05 Radiators not large enough
ht14_06 Heating not working
ht14_07 Dislike storage heaters
ht14_08 Inadequate heating
ht14_10 Heating in part of house
ht14_17 Can’t afford to replace system
Hard to control heating ht14_09 Difficult to control/regulate
ht14_11 Hard to control heat
Need new windows ht14_12 Need new windows
Poor insulation ht14_13 Poor insulation
Draughty ht14_14 Draughty
Rooms too big ht14_15 Rooms too big
Can’t afford to heat house ht14_16 Can’t afford to heat house
Other ht14_18 Other
No answer ht14_19 No answer

7.11.6 Hard to Treat Cavity Walls

362. In this report we use the ECO definition of HTTCs[77] to provide a breakdown of the remaining insulation potential of cavity wall dwellings in the Scottish housing stock (see Table 13).

363. A cavity wall is considered hard to treat if:

  • The building has three or more storeys. Dwelling spaces in lofts are not counted as storeys.
  • The building is severely exposed to wind-driven rain. The SHCS is not able to collect this information, which will lead to an underestimation of hard to treat cavity walls.
  • Walls at risk of water penetration i.e. walls requiring urgent repair to the wall finish and walls with penetrating damp[78].
  • Non-traditional building types e.g. timber frame, metal-frame, prefabricated concrete.
  • Partially filled, narrow or uneven cavities as well as cavities with failed CWI. The SHCS is not able to capture this information. As a result hard to treat cavity walls may be underestimated.
  • Note that the presence of a conservatory alone does not cause a dwelling to be considered hard to treat under ECO.

7.11.7 Disrepair

364. This report uses our categories of disrepair to describe the state of disrepair of a dwelling.

365. A range of elements - both internal and external - are assessed for the extent of disrepair, the urgency of disrepair (for external and common elements only), and in some cases the residual life of the element.

366. Extent of disrepair is usually measured on a 5- or 10-point scale relating to the area of the element which is in disrepair. Any (Basic) Disrepair

367. Any (Basic) disrepair is recorded where any element of the dwelling is found to have any level of disrepair, no matter how small. Extensive Disrepair

368. Extensive disrepair is recorded where:

  • Any building element has an overall disrepair score exceeding 20% by area
  • Any building element assessed has a score of 'medium' or 'renew' on the 5-point repair scale (equivalent to an area of around 25% or more of the element) or
  • Dry/wet rot is recorded in two or more rooms

369. Extensive disrepair is calculated in order to identify those dwellings where any disrepair present is of a relatively greater severity. Disrepair to Critical Elements

370. Disrepair to critical elements is recorded where there is any disrepair, no matter how small, to the critical elements of the dwelling.

371. The critical elements are those whose condition is central to a dwelling being wind and weather proof, structurally stable and safeguarded against further rapid deterioration. They are as follows:

  • Roof covering;
  • Roof structure;
  • Chimney stacks;
  • Flashings;
  • Roof gutters and downpipes;
  • External walls - finish;
  • External walls - structure;
  • Access decks and balustrades (common areas - flats only);
  • Foundations;
  • Damp-proof course;
  • External doors and windows (dwelling only);
  • Doors, screens, windows and roof lights (common areas - flats only);
  • Internal walls/partitions[79];
  • Floor structure;
  • Floor finish;
  • Dry rot/wet rot. Urgent Disrepair

372. Urgent disrepair is recorded where the SHCS surveyor deems that a dwelling has any disrepair which, if not rectified, would cause the fabric of the building to deteriorate further and/or place the health and safety of the occupier at risk.

373. Urgency of disrepair is only assessed for external and common elements.

7.11.8 Damp and Condensation

  • Penetrating damp is usually the result of a defect in the building fabric, such as damage to the walls or roof, water ingress due to damaged seals on doors or windows or damp as a result of leaking plumbing.
  • Rising damp is the result of defective or missing damp proof coursing, leading to water leaching into the building fabric.
  • Condensation is the build-up of moisture inside a dwelling, which may be the result of insufficient or ineffective ventilation.

7.11.9 Bedroom Standard

374. The Bedroom Standard is defined in the Housing (Overcrowding) Bill 2003 based on the number of bedrooms in a dwelling and the people in a household who can share a bedroom[80].

375. Each of the following groups or individuals requires a separate bedroom:

  • Any couple;
  • a person aged 21 years or more;
  • two people of the same sex[81] aged between 10 and 20;
  • two children (whether of the same sex or not) under 10 years;
  • two people of the same sex where one person is aged between 10 years and 20 years and the other is aged less than 10 years;
  • any further person who cannot be paired appropriately.

376. This definition is distinct from the rules introduced by the UK Government in April 2013 for the size of accommodation that Housing Benefit will cover for working age tenants renting in the social sector, known as the ‘spare room subsidy’[82]. Applying the rules of the spare room subsidy requires information not collected in the SHCS. Statistics in this report relate to the Bedroom Standard only.

7.11.10 Tolerable Standard

377. The Tolerable Standard is a minimum standard for habitability introduced in the 1969 Housing (Scotland) Act, and updated by the 1987, 2001 and 2006 Acts[83].

378. Additional criteria for electrical installations and thermal insulation were added by the 2006 Act[84]. These requirements came into force in April 2009 and were first reported by the SHCS in 2010. The change in definition caused the fail rate for the standard to increase from 0.7% in 2009 to 3.9% in 2010 in the full time series tables[85].

379. A dwelling meets the tolerable standard if it:

  • is structurally stable;
  • is substantially free from rising or penetrating damp;
  • has satisfactory provision for lighting, ventilation and heating;
  • has an adequate piped supply of wholesome water available within the house;
  • has a sink provided with a satisfactory supply of both hot and cold water within the house;
  • has a water closet or waterless closet available for the exclusive use of the occupants of the house and suitably located within the house;
  • has a fixed bath or shower and a wash-hand basin, each provided with a satisfactory supply of both hot and cold water and suitably located within the house;
  • has an effective system for the drainage and disposal of foul and surface water;
  • has satisfactory facilities for the cooking of food within the house;
  • has satisfactory access to all external doors and outbuildings;
  • has electrical installations that are adequate and safe to use. The "electrical installation" is the electrical wiring and associated components and fittings, but excludes equipment and appliances;
  • has satisfactory thermal insulation.

7.11.11 Scottish Housing Quality Standard

380. The Scottish Housing Quality Standard (SHQS) was announced by the Minister for Communities in February 2004[86]. A target was agreed that all social landlords must ensure that all their dwellings pass the SHQS by 2015. Private owners and private landlords are currently under no obligation to bring their properties up to a standard which meets the SHQS. However SHCS collects the same data for all dwellings to allow comparison across the housing stock.

381. The SHQS is an aggregation of the results from 55 different elements grouped into 5 higher-level criteria, which in turn provide a single pass/fail classification for all dwellings. The 5 higher-level criteria specify that the dwelling must be:

  • above the statutory tolerable standard;
  • free from serious disrepair;
  • energy efficient;
  • with modern facilities and services;
  • healthy, safe and secure.

382. A full list of assessed elements is available on the Scottish Government website[87]. Only one element of the SHQS is not assessed using SHCS data: no information is collected on external noise insulation[88].

383. Figures on SHQS failure rates for 2014 and 2015 are not entirely comparable to previous years published in this report. Because of missing tenure information a small number of dwellings (see section 7.2 for more detail), are excluded from tenure breakdowns in figures relating to years prior to 2014.

384. In addition, small changes to data processing relating to failure thresholds for the energy efficiency criterion[89], as well as other minor data processing corrections were introduced in 2014. Although the effect of these corrections on the overall failure rates in the social sector was neutral, some discontinuities with previous years cannot be ruled out, especially when considering more detailed breakdowns.



Back to top