Indoor environment quality (IEQ) factors

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Question

What established or possible indoor environment quality (IEQ) factors exist? What kind of dose-responses have been defined for them?

Answer

Indoor environment quality (IEQ) factors: Difference between revisions(-)

Obs	Exposure metric	Response	Response metric	Exposure route	Exposure unit	ERF parameter	ERF	Significance	Description/Reference
1	Visible dampness and/or mold or mold odor	Respiratory health effect		Inhalation	yes/no	OR	several, see Note 1		Note 1
2	Dampness and/or mold	General health problem		perception	yes/no	increased risk of health problems %	64%		Evans et al (2000)
3	Dampness and/or mold	Mental health problems		perception		OR	1.39(1.44-2.78)		Shenassa et al. 2007
4	Dampness and/or mold	Self-assessed health poorer		Inhalation, Other?					Note 2
5	Dampness and/or mold	Mental health problems		Inhalation, dermal and ingestion	yes/no	OR	1.76 (1.17-2.66)		Hopton and Hunt (1996)
6	Chronic illness	Mental health problems		not applicable	yes/no	OR	1.99 (1.32-3.02)		Hopton and Hunt (1996)
7	Living with children under 16 y	Mental health problems		not applicable	yes/no	OR	1.75 (1.15-2.68)		Hopton and Hunt (1996)
8	Living in a low income household	Mental health problems		not applicable	yes/no	OR	1.61 (1.06-2.44)		Hopton and Hunt (1996)
9	Respondent unemployed	Mental health problems		not applicable	yes/no	OR	1.55 (0.99-2.42)		Hopton and Hunt (1996)
10	Living in flat instead of house	Upper respitory infection		Inhalation	yes/no				D.Fanning (1967)
11	Living in flat instead of house	Minor mental health problems		not applicable	yes/no				D.Fanning (1967)
12	Living in flat instead of house	Morbidity		not applicable	yes/no	Increased morbidity (%)	57%		D.Fanning (1967)
13	Living in ground floor	Psychoneurotic disorder		not applicable	yes/no	Increased risk of psychoneurotic disorder (%)	6,3%		D.Fanning (1967)
14	Living in 1st floor	Psychoneurotic disorder		not applicable	yes/no	Increased risk of psychoneurotic disorder (%)	6,7%		D.Fanning (1967)
15	Living in 2nd floor	Psychoneurotic disorder		not applicable	yes/no	Increased risk of psychoneurotic disorder (%)	10,9%		D.Fanning (1967)
16	Living in 3rd floor	Psychoneurotic disorder		not applicable	yes/no	Increased risk of psychoneurotic disorder (%)	12,7%		D.Fanning (1967)
17	Wood smoke	Respiratory health effect		Inhalation					Note 3, Note 4
18	Wood smoke	Irritation of eyes and mucosa
19	Wood smoke	Respiratory health effect		Inhalation
20	Wood smoke	Odour problems		Inhalation
21	Wood smoke	Comfort of housing
22	Wood smoke	Chronic infections		Inhalation
23	Wood smoke	Cancer		Inhalation
24	Tobacco smoke	Respiratory health effect		Inhalation
25	Tobacco smoke	Irritation of eyes and mucosa
26	Tobacco smoke	Respiratory health effect
27	Tobacco smoke	Odour problems		Inhalation
28	Tobacco smoke	Comfort of housing
29	Tobacco smoke	Chronic infections		Inhalation
30	Tobacco smoke	Cancer
31	VOCs	irritation symptoms etc.
32	CO2	headache, tiredness etc.
33	CO	headache, tiredness etc.
34	Insufficient air exchange	Headache
35	Insufficient air exchange	Tiredness
36	Insufficient air exchange	Decreased ability to concentrate
37	Insufficient air exchange	Feeling of fug
38	Thermal conditions; heat	Tiredness
39	Thermal conditions; heat	Decreased ability to concentrate
40	Thermal conditions; heat	Increased respiratory symptoms
41	Thermal conditions; heat	Feeling of dryness
42	Thermal conditions; heat	Comfort of housing
43	Thermal comfort (draught or cold)	Mental health problems							Note 2
44	Thermal comfort (heat or cold)	Depression							Note 2
45	Thermal comfort (heat or cold; general perception of thermal problems)	Self-assessed health poorer							Note 2
46	Thermal conditions (cold)	Feeling of draught
47	Thermal conditions (cold)	Comfort of housing
48	Noise	Hearing injury
49	Noise	Sleep disturbance
50	Noise	Stress
51	Noise	Comfort of housing
52	Proximity to traffic	Mortality(?)
53	Radon	Lung cancer							Note 5
54	Relative humidity
55	PM	mortality							Note 3
56	PM	chronic bronchitis
57	PM	lung cancer
58	Reduced space (house/flat)	Depression							Note 2
59	Reduced space (house/flat)	Mental health problems							Note 2
60	Reduced space (house/flat)	Self-assessed health poorer							Note 2
61	Garden	Depression							Note 2
62	Floor level	Mental health problems							Note 2
63	Overcrowding	Mental health problems							Note 2
64	Overcrowding	Self assessed health poorer							Note 2
65	Sensory IAQ	Various health and well-being parameters
66	Maternal employment	Maltreatment of Children		Other	no/yes	OR	2.82 (1.59-5.00)		Sidebotham et al. 2002
67	No. of house moves in previous 5 years	Maltreatment of Children		Other	2-3 vs. 0-1	OR	1.32 (0.77-2.27)		Sidebotham et al. 2002
68	No. of house moves in previous 5 years	Maltreatment of Children		Other	4 or more vs. 0-1	OR	2.81 (1.59-4.96)		Sidebotham et al. 2002
69	Overcrowed accomodation	Maltreatment of Children		Other	yes/no	OR	2.16 (1.27-3.70)		Sidebotham et al. 2002
70	Accomodation	Maltreatment of Children		Other	Council vs. owned/mortgarged	OR	7.65 (3.30-17.75)		Sidebotham et al. 2002
71	Accomodation	Maltreatment of Children		Other	Rented vs. owned/mortgarged	OR	4.47 (1.82-10.98)		Sidebotham et al. 2002
72	Social Network Score < 21	Maltreatment of Children		Other	yes/no	OR	3.09 (1.84-5.19)		Sidebotham et al. 2002
73	Paternal employement	Maltreatment of Children		Other	no/yes	OR	2.33 (1.43-3.77)		Sidebotham et al. 2002
74	Car use	Maltreatment of Children		Other	no/yes	OR	2.33 (1.41-3.83)		Sidebotham et al. 2002
75	No. of deprivation indicators	Maltreatment of Children		Other	1 vs. 0	OR	9.58 (2.64-34.81)		Note6; Sidebotham et al. 2002
76	No. of deprivation indicators	Maltreatment of Children		Other	2 vs. 0	OR	23.44 (6.61-83.15)		Note6; Sidebotham et al. 2002
77	No. of deprivation indicators	Maltreatment of Children		Other	3 vs. 0	OR	59.30 (17.52-200.76)		Note6; Sidebotham et al. 2002
78	No. of deprivation indicators	Maltreatment of Children		Other	4 vs. 0	OR	111.36 (32.31-383.801)		Note6; Sidebotham et al. 2002
79	House dampness	Smoking	38.2	Inhalation other	yes/no				Packer et al. 1994
80	House dampness	use of low fat milk	40.0	Digestion, other	yes/no				Packer et al. 1994
81	House dampness	Exercise 3 last week	15.4	Other	yes/no				Packer et al. 1994
82	House dampness	Body mass index >25	34.2	Other	yes/no				Packer et al. 1994
83	House dampness	Alcohol over limit	14.3	Drinking	yes/no				Packer et al. 1994
84	House dampness	Energy	38.5	Other	yes/no				Packer et al. 1994
85	House dampness	Social isolation	22.7	Other	yes/no				Packer et al. 1994
86	House dampness	Sleep	40.5	Other	yes/no				Packer et al. 1994
87	House dampness	Emotional reactions	39.5	Other	yes/no				Packer et al. 1994
88	House dampness	Physical mobility	16.7	other	yes/no				Packer et al. 1994
89	House dampness	Pain	14.4	other	yes/no				Packer et al. 1994
90	Smoking	chronic respiratory disease		Inhalation	yes/no	OR	4.36(2.46-7.74)		Blackman et al. (2001)
91	Dampness	chronic respiratory disease		Inhalation	yes/no	OR	2.10(1.36-3.50)		Blackman et al. (2001)
92	Unwaged household	chronic respiratory disease		other	yes/no	OR	1.73(1.24-2.41)		Blackman et al. (2001)
93	Unsafe neighborhood	mental health problems		other	yes/no	OR	2.35(1.41-3.92)		Blackman et al. (2001)
94	Chronic respiratory problems	mental health problems		other	yes/no	OR	2.35(1.50-3.69)		Blackman et al. (2001)
95	Draughts	mental health problems		other	yes/no	OR	2.28(1.41-3.69)		Blackman et al. (2001)
96	Rehousing	palpitation/breathlessness	0.8	other	yes/no		-7.8		Pettricrew et al. 2009
97	Rehousing	persistence cough	-11.0	Inhalation	yes/no		-2.1		pettricrew et al. 2009
98	Rehousing	painful joint	32.9	Inhalation	yes/no		-8.7		Pettricrew et al. 2009
99	Rehousing	faints/dizziness	12.6	not applicable	yes/no		-5.7		Pettricrew et al. 2009
100	Rehousing	difficulty in sleeping	8.6	not applicable	yes/no		-17.4		Pettricrew et al. 2009
101	Rehousing	sinus trouble/catarh	-0.3	Other	yes/no		-4.7		Pettricrew et al. 2009

Note 1 ERF of indoor dampness on respiratory health effects

Note 2 WP6 well-being report (password-protected)

Note 3 ERF of PM2.5 on mortality in general population

Note 4 Concentration-response to PM2.5

Note 5 Health impact of radon in Europe

Note 6 Indicators of deprication: overcrowded accommodation, accomodation ownership, paternal employment, car use

⇤--#: . Comments on Hopton and Hunt (1996):

• Row 5: Are you sure that the only possible exposure route is inhalation?
• Rows 6 to 9: Instead of "no", exposure route should be "not applicable".
• Rows 5 to 9: Use periods instead of commas as decimal points. --Marjo 10:22, 4 February 2013 (EET) (type: truth; paradigms: science: attack)

←--#: . Comments have been considered. --Juho Kutvonen 13:52, 4 February 2013 (EET) (type: truth; paradigms: science: defence)

⇤--#: . Comments on Sidebotham et al. (2002)

• Rows 59, 66 and 67 are filled correctly. What comes to rows 60 to 65, small but essential changes should be done in columns "exposure metric" and "exposure unit". An example: "exposure metric" of row 60 should be "2 to 3 house moves in previous 5 years" and the respective "exposure unit" should be "medium vs. low". Based on this example, can you figure out the correct structures of rows 61 to 65? --Marjo 10:41, 4 February 2013 (EET) (type: truth; paradigms: science: attack)

←--#: . Good revisions, you have the right idea. However, some minor modifications would be appropriate: in row 62 "exposure unit" can simply be "yes/no", as the accomodation either is overcrowded or is not; no other possibilities exist. In row 65 the "exposure metric" should be "Social network score < 21" and "exposure unit" again simply "yes/no". --Marjo 15:44, 6 February 2013 (EET) (type: truth; paradigms: science: defence)

⇤--#: . Comments on Packer et al. (1994)

• In the paper of Packer et al. (1994) no ORs are given. Instead, they have measured prevalences. Therefore, "response metric" should be "prevalence" and "ERF parameter" should be "percentage unit change".
• Row 69: According the Table 4, "exposure metric" is damp housing and "response" is "smoking". Based on this, can you figure out the correct structures of rows 70 to 73? --Marjo 11:05, 4 February 2013 (EET) (type: truth; paradigms: science: attack)

----#: . we updated the data --Soroushm 23:25, 10 February 2013 (EET) (type: truth; paradigms: science: comment) ⇤--#: . I see that you have updated the data using the table 1. Unfortunately, that is not correct. You should update the data using tables 4 and 8, where relationships of dampness and various health-related endpoints are shown. --Marjo 15:27, 11 February 2013 (EET) (type: truth; paradigms: science: attack)----#: . Table updated --Adnank 10:19, 13 February 2013 (EET) (type: truth; paradigms: science: comment)

⇤--#: . Comments on Blackman et al. (2001)

• "Response metric" should describe how the response was measured: number of cases, incidence, prevalence,... I see that you have filled "response metric" boxes according earlier versions of this table, unfortunately, "response metric" was not used correctly there. The information you now have in boxes "response" and "response metric" all belongs to "response". You could do the following: decide and formulate the most accurate responses and put them into "response" -boxes and empty the "response metric" -boxes. If you can define the response metric, i.e. number of cases, incidence, prevalence etc.. used in the article, you can put it into "response metric" box. --Marjo 14:39, 4 February 2013 (EET) (type: truth; paradigms: science: attack)

⇤--#: . Don´t you think that the most likely exposure route in case of smoking and chronic respiratory disease as well as in case of dampness and chronic respiratory disease would be inhalation? --Marjo 16:31, 7 February 2013 (EET) (type: truth; paradigms: science: attack)

----#: . Data tables updated, and correct, most likely exposure route to those exposure metrics would be inhalation --Jukka Hirvonen 09:11, 11 February 2013 (EET) (type: truth; paradigms: science: comment)

⇤--#: . Comments on Fanning (1967)

• This article does not express ORs, which makes it a bit tricky in terms of this exercise. Anyhow, the idea is to find numerical value for ERF to be added into table. At least for morbidity a numerical value can be found in the article, although it is not OR. Can you find it?
• If no numerical value can be found for the two other responses, they should be removed. Instead, you could try to put the data of Table VIII of the article into the IEQ table.
• Exposure route can not be "neurosis" or "common sickness". I suggest exposure route in these cases is "not applicable". --Marjo 17:29, 8 February 2013 (EET) (type: truth; paradigms: science: attack)

←--#: . I see that you have made good corrections in the IEQ table. Still something:

• "ERF parameter" should be "percentage unit change" in all cases.
• Use periods instead of commas as decimal separator. --Marjo 16:13, 12 February 2013 (EET) (type: truth; paradigms: science: defence)

⇤--#: . Comments on Petticrew et al. 2009

• You have both incorrect and correct parts here. Your "exposure metrics" are mostly wrong. I admit, this is tricky, as what you have written as "exposure metrics" could well be that. However, here "exposure metric" in all cases is "rehousing" for which a number of "responses" are described in tables 3,4,5 and 6. As there are so many responses, I suggest that you select only 6 of them to be included into the IEQ table above. Select those 6 responses you consider most interesting.
• Your article does not express ORs, instead prevalences and changes in them are given. Therefore, the "response metric" is here "prevalence" and "ERF parameter" is "percentage unit change". --Marjo 17:34, 11 February 2013 (EET) (type: truth; paradigms: science: attack)

←--#: . Correct parts include:

• "exposure unit"
• many of the responses and their values, however these values should be moved to column "ERF". For example, "painful joint" is a correct response, its "ERF parameter" is -8.7 as you have stated (but move this to the right place!). However, the respective exposure is not "housing dampness", instead it is here "rehousing", since the values are given in relation to it (table 5). --Marjo 17:34, 11 February 2013 (EET) (type: truth; paradigms: science: defence)----#: . table updated --Matthew 13:12, 13 February 2013 (EET) (type: truth; paradigms: science: comment)

Thomasa and Joshuan Evans et al. (2000).

Rationale

An example for RefTag functionality: Pope et al. (2002)

john agyemang and emmanuel Shenassa et al. (2007).

Juho Kutvonen and Salla Mönkkönen Hopton and Hunt (1996)

Isabell Rumrich and Stefania Caporaso Sidebotham et al. (2002)

Soroush Majlesi and Adnan Ahmad Packer et al. (1994)

Jukka Hirvonen and Sami Rissanen Blackman et al. (2001)

Niklas Holopainen and Kasperi Juntunen Fanning D. M. et al. (1967)

Matthew Adeboye and Adedayo Mofikoya Petticrew et al. (2009)

Precision and Plausability of Hopton and Hunt (1996)

- Reporting bias: Perhaps ít´s difficult to use subjective data due to reporting bias. This is because people may answer in different ways or they don´t answer at all. In addition, people experience household conditions differently.←--#: . Good points. --Marjo 14:50, 4 February 2013 (EET) (type: truth; paradigms: science: defence)

- Possible confounding variables were controlled. ----#: . Can you give examples of the confounding variables mentioned in the paper? --Marjo 14:50, 4 February 2013 (EET) (type: truth; paradigms: science: comment)←--#: . Sociodemographic and economic variables, e.g. age and income. --Juho Kutvonen 12:23, 6 February 2013 (EET) (type: truth; paradigms: science: defence)

- Selection bias: The sample is clearly not representative of the general population and therefore the analysis focuses on differences within the sample. Thus it´s worth considering if the results can be generalized to whole population.←--#: . Good points. --Marjo 14:50, 4 February 2013 (EET) (type: truth; paradigms: science: defence)

Precision and Plausability of Sidebotham et al. (2002)

- Maltreatment is defined and measured as registration for physical injury, neglect, sexual abuse, emotional abuse. That way all maltreatments, which are not registred are not taken into account.

- The measurement of the social class is not too accurate, because no allowance for nonworking mothers and no parental social class allocated for single mothers can be applied.

- The nature of relationship with child maltreatment is complex (confounder, cultural values, etc). That causes problems finding an association or causality between an exposure factor and maltreatment. Moreover, maltreatment has different definition in different cultural groups.

- The parental income is not measured directly, but car ownership as a proxy indicator and the receipt of welfare payment are used.

- Controlling for social factors was done.

- Large amount of prospectively data are collected and used in in the study, which is a clear strength.

- The participation is lower among the maltreated group, which might influence the outcome of the statistical analysis or bias the results of the study.

- The risk of social bias and no way of measuring the effect of such bias. A social bias can be defined as a prejudgement of a specific social group. In this case, it might be that those, who collected the data might have expectations, that parents which lower or higher social background are more prone to maltreat their child and let this expectation influence their interpretation of the results. This is not very likely here, though, because all parameters which were used for the analysis can me measured and there is not much freedome for interpretation.

----#: . You have listed correct points that may affect precision and plausibility of the ERF; well done. However, it would be easier for the reader if you would use full sentences or otherwise would explain a bit more in detail how these issues affect the precision and plausibity of ERF.

• What is meant with "social bias" here? --Marjo 15:06, 4 February 2013 (EET) (type: truth; paradigms: science: comment)

----#: . We added explanations. --Isabell Rumrich 09:58, 7 February 2013 (EET) (type: truth; paradigms: science: comment)

Precision and Plausability of Packer et al. (1994)

- health problems: possibility of headache, mental problems, emotional reactions, social isolation and pain.

- social factors: unemployment, single parent, lone adult and unemployment with sickness or disability

- lifestyle: consumption of alcohol and smoking

----#: . It might be helpful for the reader if you would use full sentences in order to explain how the above issues affect the precision and plausibility of ERF. --Marjo 15:28, 4 February 2013 (EET) (type: truth; paradigms: science: comment)

- it is still difficult to understand the housing condition because none of the studies are complete and detailed so that direct comparison with the questions cannot be made and measurements of parameters, potential confounding factors as well as clear dose-response relationship should be adjusted for example physical effect of damp is responsible for muscle tension, backache and headache but on the other hand the study poins out that there is a strong relationship between damp housing and adverse health impact. ----#: . I see that the two last points are in concordance with each other. --Marjo 15:28, 4 February 2013 (EET) (type: truth; paradigms: science: comment)

Precision and Plausability of Blackman et al. (2001)

- Bias in respondents answers to realistically evaluate their and family members health.←--#: . Good. --Marjo 16:25, 7 February 2013 (EET) (type: truth; paradigms: science: defence)

- Some housings that where targets on first survey were demolished during second survey.

- No data from comparison neighbourhood without renewal to back up observed health changes after renewal program. ←--#: . Good point. --Marjo 16:25, 7 February 2013 (EET) (type: truth; paradigms: science: defence)

- Relationship between dampness, draughts and mental health is uncertain, because the mechanism is unknown.←--#: . Again good, although you could specify this. Is it so that associations have been found but the mechanisms are unclear? --Marjo 16:25, 7 February 2013 (EET) (type: truth; paradigms: science: defence)

- Multivariate analysis using regression model was used to control variables, such as economic, housing, respiratory and mental health related to increase plausability----#: . So in contrast to the previous points, this increases the plausibility of ERF, is this what you mean? --Marjo 16:25, 7 February 2013 (EET) (type: truth; paradigms: science: comment)

----#: . Precisions and plausabilities updated --Jukka Hirvonen 09:30, 11 February 2013 (EET) (type: truth; paradigms: science: comment)

Precision and Plausability of D. Fanning (1967)

- The study is so old that the exposures and responses are real but the accuracy is quite poor. The basics are almost same as today but measurement techniques are so old that the results are not comparable to modern results. ⇤--#: . Which specific measurement techniques do you mean? For example, they have measured first attendances by general practitioners, and I don´t think the accuracy of counting has changed significantly. --Marjo 18:08, 8 February 2013 (EET) (type: truth; paradigms: science: attack)←--#: . However, I agree with you that the oldness of study is a bit striking. Probably today many other parameters in addition to those used in the article would be measured when conducting this kind of study. --Marjo 18:08, 8 February 2013 (EET) (type: truth; paradigms: science: defence)

- The study has considered the difference between children and adults.←--#: . Good point. --Marjo 18:08, 8 February 2013 (EET) (type: truth; paradigms: science: defence)

- The study has not considered the differences between different flats and houses. They have only categories for houses and flats but the differences between houses are not considered. This causes bias to the study.----#: . Well, it is possible. However, it is always a question of e.g. resources how specific and detailed a study can be. Maybe they could more apparently mention whether there were any significant dissimilarities between houses. --Marjo 18:08, 8 February 2013 (EET) (type: truth; paradigms: science: comment)

Precision and Plausability of Petticrew et al. (2009)

- Data collection at the three occassions in the intervention group before moving, one year after moving and 2 years after moving to the social housing gives strenght to the study in analysing changes in the housing circumstances and in neighbourhood.

- Recruitment into the study was discussed by the landlord to the tenant once they have accepted the housing offer which dosn't gives the RSL direct contact with the participant though this serves as a way of good recruitments but it dose not guarantee the authenticity of the data collected. e.g RSL couldn't supply the number of people who refuse to participate in the study to the SHARP research team.

- Broad range of adult household categories in the intervention group which was used as a base for recruiting the comparism group stenghthen the study. (family households, with children under age of sixteen years, older households where the respondents and adult members of the households were of pensionable age, and adult households with a combination of relationships, including parents with children atleast 16 years of age, people unrelated to one and another and couples )

- Qualitative and quantitative findings were only presented for 1 year(wave 2) in the study which dose not proof if the effects are sustained and probabely if differences in health outcomes occur at two years in the intervention and comparism groups.

- recollection bias may occur during interview if participant in the groups if they can not recall adequately past occurences relating to health, housing and neighbourhood questions after one year and two years of movement to the new house.

- Bias in subsequent analysis can also occur if there is any significant changes in the groups associated with self reported health.

←--#: . Good points and thorough work! By checking the spelling you could increase the elegancy of your work. --Marjo 17:46, 11 February 2013 (EET) (type: truth; paradigms: science: defence)----#: . updated --Matthew 12:43, 13 February 2013 (EET) (type: truth; paradigms: science: comment)

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Indoor environment quality (IEQ) factors. Opasnet . [1]. Accessed 02 Nov 2024.