a Research Unit In Health, Behaviour and Change, The University of Edinburgh Medical School, Teviot Place, Edinburgh EH8 9AG, UK. E-mail: Richard.Mitchell{at}ed.ac.uk
b Department of Social Science and Medicine, Imperial College of Science, Technology and Medicine, London, UK.
c Department of Epidemiology and Public Health, University College London, UK.
Abstract
Background In previous work the authors identified an inverse housing law in Britain such that housing quality tends to be worse in areas of harsh climate than in areas where the climate is more benign. This study investigates whether an individuals risk of hypertension is associated with such a mismatch between the quality of their housing and the climate to which they have been exposed.
Methods Cross-sectional observational study based on Britain. Data came from the 5663 Health and Lifestyle Survey (HALS) participants for whom all relevant items were available. A two-stage study design was employed. First, the relationship between exposure to colder climate and housing quality was established. Second, the impact on risk of hypertension was determined for level of exposure to colder climate and housing quality.
Results Analysis confirmed that amongst survey respondents, those with greater exposure to colder climate are more likely (1.32, 95% CI: 1.181.42) to live in poor quality housing than those with lower exposure to colder climate. This combination of higher exposure to colder climate plus residence in worse quality housing raises significantly the risk of diastolic hypertension (1.45, 95% CI: 1.181.77) and, more weakly, systolic hypertension (1.25, 95% CI: 1.011.53).
Conclusions There appears to be an inverse housing law in Britain, whereby longer term residents of relatively cold areas are also more likely to live in worse quality housing and this combination of circumstances is associated with significantly higher risk of diastolic hypertension. The findings provide an example of how long term exposure to an adverse environment, which may stem from material disadvantage, can damage health.
Accepted 12 March 2002
In previous work1 the authors used Tudor Harts article2 on the inverse care law as a premise for exploring other health consequences of the relationships between need and provision. This work demonstrated the existence of an inverse housing law in Britain, and its impact on respiratory health. The inverse housing law suggests that housing quality tends to be worse in areas of harsh climate than in areas where the climate is more benign. For this study the methodology has been enhanced through better model specification and the focus has shifted to hypertension. The study has two aims: to determine whether there is any mismatch between the quality of their housing and the climate to which residents are exposed; and, if so, whether this is associated with an individuals risk of hypertension (diastolic blood pressure >90 mmHg, systolic blood pressure >140 mmHg).
The health impacts of high blood pressure are well documented.35 Risk factors for hypertension are numerous and complex, and they include age, gender, pre-existing cardiovascular disease, smoking status, obesity, alcohol consumption and socioeconomic status.3 A considerable literature on the relationship between exposure to cold and hypertension has been established, though much focuses on the implications of seasonal change in temperature, rather than longer term exposure to a colder climate.612 A useful review of the effects of cold weather on the heart is provided by Vuori.13 As Vuori points out, even exposure of the face to cold air, when the rest of the body is protected by clothing, is sufficient to induce considerable physiological response (ref. 13, p. 160). Vuori also comments that ... the most important means of preventing harmful cardiac effects of the cold is protection from unnecessary and prolonged exposure (p. 160).
The Eurowinter group14 have specifically explored the relationship between exposure to cold and personal measures to protect body temperature, finding strong relationships between health and regional variations in both clothing habits and the maintenance of a warm home. They also suggest that the impact of colder weather on winter mortality appears greater in regions with relatively mild winters than in those with very cold winters. This study develops their ideas by focussing on the ability to maintain a warm home in relation to the prevailing climatic regime the home must cope with. The research examined long term exposure to relatively colder and warmer environments within the comparatively mild British climate.
McCarron et al.15 demonstrate that elevated blood pressure in young and mid adulthood is closely related to high blood pressure in older adulthood. This makes the need for lifelong control of hypertension paramount.16,17 Together, the literature on hypertension and cold, and life-long risks of hypertension raise questions about the differential impact of long term residence in a relatively cold area and the influence of housing as a potentially protective factor.
Data Sources and Methods
The analysis combined data describing climate, individual circumstances (including housing quality) and measures of hypertension.
Study participants
The sample population, aged 18+ and living in private households, was drawn from The Health and Lifestyle Survey (HALS). This has been described elsewhere.18 The survey was carried out between 1984 and 1985 and is both socially and spatially representative. This analysis is based on the 5663 respondents for whom valid data were available (2564 men, 3099 women). Exclusion of those without valid data on all measures did not render the sample unrepresentative.
Exposure to colder climate
Climate data were obtained from the Climatic Research Unit (CRU)19 in the form of a 10 km2 grid model (Figure 1). All climatic variables were measured at mean elevation above sea level. A variable was derived to represent each respondents degree of exposure to a colder climate. This variable was a combination of the physical climate prevailing in their area of residence and the length of time they had been resident there. A geographical information system20 was used to match the climate data to individual HALS respondents (and thus, all modelling took place at the individual level). The average number of days per month with ground frost was selected to represent the coldness of climate, giving an indication of both general climatic regime and representing the frequency of cold snaps. This indicator was dichotomized such that it recorded whether the respondent was exposed to above or below the average number of ground frost days, representing a relatively colder climate or warmer climate, respectively. It should be noted that the average number of ground frost days was calculated relative to the sample rather than the whole British range, since there were no HALS respondents living in Britains coldest upland areas. HALS provides a measure of the length of residency in an area and this was combined with the climate indicator such that those living in a colder area for 10 years or more (about 40% of the sample), were categorized as having higher exposure to colder climate, relative to the rest.
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Heating was described as inefficient when it was recorded as being switched on but room temperature was recorded at below 15°C. Although room temperature was measured in the living room, this was taken as a reasonable proxy for living space temperature. The Eurowinter group14 found that houses with a warm living room were highly likely to be warm elsewhere too. Following Blane et al.1 these measures were summed for each HALS respondent and then dichotomized to give a better or worse housing indicator. About 30% of the respondents were in the worse housing category.
Combination of exposure to colder climate and housing quality
These two variables (exposure to colder climate and housing quality) provided the means by which the inverse care law was tested. Our hypothesis regarding the mis-match between housing and climate combined the two dimensions, therefore we specified a categorical variable defining a respondent group who had experienced both lower housing quality and exposure to colder climate. This variable is described in Table 1.
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Outcome variables
The outcome variables were dichotomous measures of systolic and diastolic blood pressure. HALS recorded four measures of both diastolic and systolic blood pressure. Measurement was made by a trained nurse in the respondents home, using an Accutorr automatic instrument. The four measurements were made at one-minute intervals. The mean of the last two measures was dichotomized such that readings greater than 90 mmHg were labelled as diastolic hypertension and those greater than 140 mmHg were labelled as systolic hypertension. This is congruent with both the WHO Hypertension Guidelines and those from the British Hypertension Society.5,21 About 22% of the sample included in the analysis were in the diastolic hypertensive category, about 27% were in the systolic hypertensive category, and 18% were in both. Blood pressure was dichotomized because the study was interested in differences that represent a presence or absence of clinical risk (as defined by globally accepted standards) rather than small-scale differences in blood pressure without clinical implications.
Confounding variables
Several potentially confounding variables were included. Age (measured continuously in years), sex, body mass index, social class, room temperature (which has an influence on the measured blood pressure), consumption of alcohol (units in the previous week), taking anti-hypertensive medication and smoking status were all controlled for. Squared measures of body mass index and room temperature were also tested but made no difference to substantive model results. The models shown here therefore contain linear terms. By including a measure of room temperature in the model there was, arguably, over-control for aspects of housing quality since the balance of temperature and heating provision formed part of the assessment of housing quality. However, since room temperature has a powerful impact on blood pressure measurement, its inclusion was appropriate. Models were re-run without including room temperature and no substantive difference in results was observed. In any case, including room temperature in the model was likely to make the results conservative, thus strengthening the conclusions.
The smoking status variable included any potential impact of passive smoking by scoring a non-smoker in a non-smoking household as 0, a non-smoker in a smoking household as 1 and a smoker as 2. Although Registrar Generals Social Class (IV) was included in the model development process, it does not feature in any results shown here because it made no significant contribution to any model.
Analysis
Analysis was divided into two sections. Stage 1 sought to confirm that the general relationship between exposure to colder climate and worse quality housing conformed to the inverse housing law. The second stage employed multivariate logistic regression to determine the relationships between environmental risk and odds of hypertension. Models were run in SPSS and the same sample was used in each. Since all these data were held at the individual level, multilevel modelling was not appropriate. However, model residuals were examined for systematic regional variation which might have indicated a systematic regional or county-level bias in measurement (observer is known to be an important influence on blood pressure measurement). No such variation was found.
Results
Stage 1: Demonstrating the Inverse Housing Law
Figure 1 presents a sequence of maps showing the aggregate level relationships between the distribution of colder climate, longer term exposure to cold, and worse quality housing. It also illustrates the geography of diastolic hypertension within the HALS survey.
Map (a)top leftillustrates the grid-based surface climate model from the CRU data. It depicts the distribution of average number of days with ground frost in Britain for each 10 km2 of land. Map (b)top rightcombines the information in map (a) with data describing the length of residence amongst survey respondents to give an exposure score. The boundaries are counties. Counties with no shading had no HALS respondents living in them. The other counties are shaded according to the proportion of the HALS sample who were categorized as having longer term exposure to colder climate. Note the concentration of respondents categorized as having high exposure to cold in the north east of England, Midlands, central southern England and Scotland. Map (c)bottom leftillustrates the distribution of the HALS sample living in worse quality housing. Note the concentrations in north east England, east central Scotland and the southern portion of Englands Midlands. Map (d)bottom rightillustrates the distribution of HALS participants with diastolic hypertension within the sample. The map is shaded using an index standardized to the age and sex of the HALS sample used in this analysis. Areas with values below 100 have a prevalence of hypertension below the sample average, areas with values above 100 have a prevalence above the sample average.
The first three maps presented indicative evidence for an inverse housing law in that they suggested those areas where climate is worse, tend also to be those where housing is worse. Chi-square tests were carried out to formally test this visual association. Table 2 illustrates the relationship between higher exposure to colder climate and the chances of also living in a worse quality house.
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Stage 2: The relationship between environmental risk and hypertension
Table 3 shows the unadjusted odds of hypertension for each category of the environmental risk variable.
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Logistic regression models were used to control for potential confounders. Two sets of multivariate models are presented (Table 4), one set for systolic hypertension (models 1 and 2) and one for diastolic hypertension (models 3 and 4).
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Environmental risk was entered in model 2. When compared to those with lower exposure to colder climate, in better quality housing, the odds of systolic hypertension were raised in all other groups. This excess risk was significant and greatest amongst those for whom higher exposure to colder climate was combined with worse quality housing, i.e. those experiencing the inverse housing law. However, although the confidence intervals for those with higher exposure to colder climate but better housing did straddle 1.0, whilst those for the group experiencing the inverse housing law did not, there was no significant difference between the parameter estimates for these groups. Thus, evidence for an association between increased risk of systolic hypertension and the inverse housing law is rather weak.
Results for diastolic hypertension are shown in models 3 and 4. In model 3, with only the confounding variables present, female sex and having blood pressure measured in a warmer room were associated with significantly lower odds of diastolic hypertension, with higher body mass index and higher alcohol consumption associated with significantly higher odds of diastolic hypertension. Again, smoking and taking anti-hypertensives were associated with higher odds, but not significantly. Whilst counter-intuitive, the non-significant relationships with smoking in both the systolic and diastolic models are congruent with some other studies.22 Given that about 40% of those taking anti-hypertensive drugs were not classified as having diastolic hypertension (presumably because their medication was successfully controlling the condition), the absence of a significant statistical relationship between medication and outcome was expected. In addition, the HALS data were gathered during an era in which diastolic hypertension was regarded as of greater clinical significance and the medication received may well have been aimed more at tackling diastolic hypertension, than systolic.
The environmental risk variable was added in model 4. When compared to those with lower exposure to colder climate, in better quality housing, the odds of diastolic hypertension were raised in all other groups. This excess risk was significant and greatest amongst those for which higher exposure to cold was combined with worse quality housing, i.e. those experiencing the inverse housing law. Their odds of diastolic hypertension were about 45% greater than for those with lower exposure to cold, who lived in better housing.
Discussion
Data from a representative survey of the British population were augmented through integration with climatic variables known to be related to the behaviour of the cardiovascular system. Aggregate analyses demonstrated that respondents who live in the relatively cold parts of Britain tend also to live in worse housing (Figure 1, Table 2
). If the quality of housing was matched to the demands placed upon it by climate, this relationship should be reversed. Following earlier work1,2 it seems reasonable to label this an inverse housing law, in the same way that the inverse care law marks the lack of health care services in areas where need is greatest.
The second stage of analysis demonstrated that respondents with higher exposure to colder climate (i.e. living in a colder area for a long period of time) and living in worse quality housing had significantly greater odds of diastolic hypertension, relative to those with lower exposure to colder climate, living in better quality housing. Although the direction of association between environmental risk and increased odds of systolic hypertension was similar, evidence for an impact of the inverse housing law on systolic hypertension is weak in comparison to that presented for diastolic hypertension.
Blood pressure
The greater increase in odds, and the most robust distinction between those experiencing the inverse housing law and those in the other categories environmental risk, was for diastolic hypertension. We suggest that since diastolic pressure reflects the structure of musculature in the arteriolar wall23 it is, arguably, the component of arterial pressure which better reflects longer term processes, including long term exposure to cold. Although systolic blood pressure is also sensitive to environment it does not reflect arteriole structure in the same way and is therefore less likely to reflect long term exposure to cold through elevation. The weaker evidence for elevated odds of systolic hypertension amongst those experiencing the inverse housing law, relative to others, was thus as expected.
Cross-sectional data
Some caution is required in the interpretation of results since they are based on cross-sectional data. The measurement of blood pressure at one point in time, for example, was not ideal for the classification of respondents as hypertensive, particularly with regard to any medication which they may, or may not, have been taking. No clinician would classify a patient as hypertensive based on readings taken at one point in time and a degree of white coat hypertension can be expected in the readings. However, unless the incidence of white coat hypertension has a geography that closely matches the distribution of cold climate or is related to housing quality, this will not have an effect on the studys substantive results. The cross-sectional data are likely to be responsible for the apparently high levels of hypertension within the study.
By choosing to measure longer term exposure to colder climate, rather than simply including prevailing climate as an independent variable, it was possible to guard against selective migration as a confounder in observed associations between climate, housing and health. However, one disadvantage of this approach is that it grouped those resident in colder parts of Britain for a relatively short period of time together with those who live in warmer parts. However, given our hypothesis that longer term exposure to colder environment might be needed for a clinically damaging response in diastolic blood pressure, the approach adopted represents the best use of available information. Given that hypertension, typically, is asymptomatic for much of its natural history it seems unlikely that it would play any significant role in a selective migration processes.
Confounding
Controlling for alcohol consumption, smoking status and body mass index rules out the possibility that these results were due to the higher prevalence of drinking, smoking and/or obesity in areas of Britain which also happen to have a colder climate. However, one possible source of confounding in the relationships described would be a geographical bias in the quality of hypertension treatment which closely matched the geographical distribution of risk as defined in this study. Many of the colder parts of Britain tend to be more remote rural areas in which GP recruitment can be problematic. The HALS data provided a limited opportunity to test this possibility using a proxy for quality of hypertension care in the respondents area of residence. A variable was computed to represent the proportion of the sample with no or poor hypertension control in each respondents county of residence (no or poor control was defined as presence of hypertension without, or despite, use of anti-hypertensive drugs). There was no correlation (Pearsons r = 0.009, P > 0.500) between environmental risk, through exposure to colder climate and worse quality housing, and this proxy for quality of care. This suggested that geographical variation in quality of hypertension care was not a mediating or confounding factor in the inverse housing law explored here.
The absence of an effect of social class suggested that this is a genuine relationship between physical environment and housing circumstances. However, the nature of the housing system means that an inability to correct housing problems, such as inadequate heating or insulation, is likely to be linked to financial circumstances. The inverse housing law is therefore not seen as an alternative to an effect of income, but rather as one of the ways in which such as effect may operate.
Conclusion
The results suggest that a significant portion of the inequality in the spatial distribution of diastolic hypertension (Figure 1, map [d]) might be explained by the distribution of poor quality housing in Britain, in relation to the climatic environment. As a whole, the results appear to confirm a genuine influence of area of residence on health (via climate)the so called area effect.24,25 However, in this case the area effect will primarily influence those for whom longer term exposure to adverse climate is combined with residence in poor quality housing; not all residents of the same area may be affected.
On a population basis, it has been estimated that a reduction in diastolic blood pressure of 2 mmHg would result in a 15% reduction in risk of stroke and transient ischaemic attacks and a 6% reduction in risk of coronary heart disease.26 Coronary heart disease alone costs the NHS about £1600 million a year. Only 1% of this figure is spent on prevention outside of primary care.27 This study provides evidence that the widespread existence of housing of a quality that is inadequate relative to the physical environment is implicated in high levels of hypertension. Britains climate cannot be intentionally altered such that it gets warmer in areas of poor quality housing, but investment in housing where its protective role is most needed might yield considerable health benefits.
KEY MESSAGES
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Acknowledgments
Funding: RM is employed by the Research Unit in Health, Behaviour and Change (RHUBC). RHUBC is funded by the Chief Scientist Office of The Scottish Executive Health Department (SEHD) and the Health Education Board for Scotland (HEBS). The opinions expressed in this paper are those of the author(s) not of SEHD or HEBS. The authors would like to thank Prof. Steve Platt and Dr Simon Mitchell for helpful comments on earlier drafts.
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