Prevalence of risk and protective factors associated with heat-related outcomes in Southern Quebec: a secondary analysis of the NuAge study.
Laverdiere, Emelie ; Genereux, Melissa ; Gaudreau, Pierrette 等
Extreme heat can cause a range of heat-related illnesses and
exacerbate certain pre-existing chronic conditions. (1) In Quebec,
extreme heat is defined as a temperature [greater than or equal
to]30[degrees]C and a humidex value [greater than or equal to]40 (2) and
heat wave definitions vary according to region (maximal and minimal
temperature thresholds are [greater than or equal to]31[degrees]C and
[greater than or equal to]18[degrees]C; [greater than or equal
to]33[degrees]C and [greater than or equal to]20[degrees]C for at least
3 days for Eastern Townships and Montreal/Laval respectively). (3)
During an intense and long heat wave that occurred from July 6 to 11,
2010, 106 deaths probably or possibly attributable to heat were observed
in the city of Montreal. (4) During the same week, 30.1% excess deaths
were observed, mainly among older adults ([greater than or equal to]75
years of age), in the province of Quebec as compared with 2008 and 2009.
(5)
Older adults are particularly at risk of heat-related outcomes (1)
owing to multimorbidity, polypharmacy, loss of autonomy, social
isolation, and altered physiological response to extreme thermal
conditions. (6)
Quebec's population heat vulnerability is expected to increase
due to predictable climate change. It has been estimated that the
expected mean annual numbers of hot temperature days (maximal
temperature [greater than or equal to]30[degrees]C) by 2039-2063 will be
double those from 1975-1999, and the extent of geographical areas at
risk will increase dramatically over the coming decades, particularly in
urbanized areas of Southern Quebec. (7) Heat vulnerability will also
increase given demographic changes. In Quebec, 11.7% of the population
was aged 65 years and over in 2011, a proportion projected to reach
almost a third of the population by 2056. (8) In 2011, 78% and 85% of
older adults aged 65-74 years and 75 years and over respectively lived
in urban areas. (9) Urban areas tend to have fewer green spaces and more
impervious cover, which contribute to the urban heat island (UHI)
effect. (10) Urbanization thus increases the probability of being
exposed to higher temperatures. (1)
Because adverse heat-related health outcomes is a growing public
health problem, it is essential to identify and support people deemed
most at risk based on factors that positively or negatively influence
their heat vulnerability. These factors mainly include medical (e.g.,
cardiovascular disease, diuretic use), social (e.g., living alone, low
income) and environmental (e.g., high land surface temperature)
predictors.
Few Heat Vulnerability Indexes (HVI), summarizing social and
environmental predictors of heat vulnerability (10-12) and, more rarely,
medical risk factors (10) and protective factors, (10,11) have been
created. In Quebec, a social vulnerability index to high temperature
events was developed using advanced age, low income, social isolation
and low education. (7) Only one study, conducted in Ontario, targeted
older adults, a highly vulnerable subgroup of the population, and
includes in its senior vulnerability index, factors specific to this
population, namely very old age (75 years and over), frailty,
disability, [greater than or equal to]30% of family income on housing,
and emergency visits. (13) Major risk factors, such as pre-existing
health conditions, medication use and the degree of social connections
among individuals within a community, were not included due to
insufficient data availability. (7, 10-13) Inclusion of major protective
factors was also limited by data availability. For example, air
conditioning (AC), a highly protective factor, was included in some HVI
(10, 11) but not in others. (7, 12, 13)
The HVI can be mapped to the study area. Using this method, a
substantial geographic variation across census tracts or census block
groups has been observed in heat vulnerability in some states in the
United States (10-12) and in the city of Toronto (Ontario, Canada). (13)
Development of previous HVI usually followed procedures outlined by
Reid et al. (2009). (10) Briefly, a principal components analysis is
applied and, for each factor retained, a range of possible values (where
higher ones denote higher vulnerability) is assigned and the sum
constitutes the HVI. However, this analysis can be quite complex. There
is a need for simple and easily computed HVI, encompassing all relevant
dimensions (i.e., medical, social and environmental) of heat
vulnerability, which could be useful for 1) public health practitioners
to locate vulnerable populations and 2) health and social care
professionals to identify and protect their most vulnerable clients.
Although some of these HVI have been linked with heat-related health
outcomes, mainly mortality, they do not appear to be well-validated
tools.
The aim of this study was to assess, at small scale, a wide range
of risk and protective factors of heat-related outcomes that could occur
simultaneously among older adults living in Southern Quebec. Our
objectives were to 1) estimate the global frequency of risk and
protective factors associated with heat-related health outcomes, 2)
examine geographic variation across health regions of these factors and
3) construct a simple Older Adult Heat Vulnerability Index (OAHVI)
simultaneously taking into account these factors.
METHODS
Setting
This study was conducted in 3 of the 18 Quebec health regions
located in Southern Quebec: Eastern Townships (mix of urban, semi-urban,
and rural areas), Montreal (metropolitan area) and Laval (urban area).
In 2013, the population and population density (inhabitants/[km.sup.2])
of these regions were: 318,350 and 31.2 for Eastern Townships, 1,959,987
and 3,935.7 for Montreal, and 417,314 and 1,696.4 for Laval. In 2013,
older adults (65 years and over) represented 18.7%, 15.7% and 15.9% of
the population in Eastern Townships, Montreal and Laval respectively.
(14)
Participants and study design
The Quebec longitudinal study of nutrition as a determinant of
successful aging (The NuAge study) is a five-year longitudinal study of
generally healthy community-dwelling older adults (853 men and 940 women
born between 1921 and 1935) living in Eastern Townships, Montreal and
Laval health regions. A random sampling from the Regie de
l'assurance maladie du Quebec medico-administrative database was
used to identify potential participants and a sample stratified for age
(68-72, 73-77, 78-82 years), sex and region was set up. Approximately
equal proportions of participants were recruited at the two
participating research centres: the Geriatric University Institute of
Montreal (GUIM) covering the Montreal and Laval health regions, and the
Geriatric University Institute of Sherbrooke (GUIS) covering the Eastern
Townships health region. The participation rate was 58.6%.
Characteristics of the cohort were described previously. (15)
This secondary cross-sectional study includes all
community-dwelling participants still in the cohort at the 1st follow-up
(2005-2006) residing in Eastern Townships (n = 901), Montreal (n = 471)
and Laval (n = 307) health regions; no participants were excluded. At
that time, only 6% of participants were lost to follow-up.
Variables
Health Canada Extreme Heat Events Guidelines (2011) provide an
up-to-date overview of the national and international literature
regarding health impacts of extreme heat. A systematic approach was used
to identify factors associated with heat-related morbidity and
mortality. (1) All factors examined in the current study were selected
from these guidelines and are presented in Figure 1. Explaining the
mechanisms linking these factors to heat-related disorders is beyond the
scope of this study. All data, except those relating to material
deprivation, living in a UHI or in a coolness island (which were
obtained from the Institut national de sante publique du Quebec
(INSPQ)), were self-reported during in-person interviews with trained
nurses or dietitians using validated questionnaires. (15)
[FIGURE 1 OMITTED]
Health Conditions
Self-reported physical health disorder variables were obtained via
the Older Americans' Resources and Services (OARS) Multidimensional
Functional Assessment Questionnaire (16) and classified according to the
International Classification of Diseases, ninth revision, except for
obesity, defined as a body mass index [greater than or equal to]30
kg/[m.sup.2]. (17) The 30-item Geriatric Depression Scale (GDS), (18)
the Modified Mini-Mental State examination (3MS) (19) and the Functional
Autonomy Measurement System (SMAF) (20) have been used to assess the
presence of depressive symptoms (GDS [greater than or equal to] 11),
cognitive impairment (3MS < 80) and disability in activities of daily
living (needing help in [greater than or equal to]1 activity)
respectively. Staying in bed for health reasons was measured during the
6-month follow-up phone calls.
Medication Use
Central nervous system and cardiovascular medication use were
classified according to the American hospital formulary system.
Social Factors
Material deprivation was calculated at the dissemination area level
(assigned based on the postal code of participant's residence)
using the Pampalon deprivation index. (21) Participants in the fifth
quintile (Q5) were considered to be living in materially deprived
neighbourhoods.
Environmental Factor
Using participants' personal address transformed into unique
latitude and longitude, a geomatic specialist of the INSPQ determined
whether this localization was in a UHI, a coolness island or neither
according to analysis of thermal information from Landsat satellite
images.
Protective Factors
Social participation was measured using a 10-item questionnaire
scored on a 5-point scale ranging from 1-almost every day to 5-never.
Final scores ranged from 10 to 50; a score [less than or equal to] 30
reflected several activities at least once a week to almost daily,
indicating high social participation. Visiting places with AC was
defined as visiting at least one air-conditioned place almost every day.
Older Adults Heat Vulnerability Index (OAHVI)
The OAHVI was developed to assess the cumulative risk of
heat-related health outcomes. A score ranging from 0 to 9 was calculated
from the sum of factors (0 or 1 point/category): physical health
disorders, mental health and cognitive disorders, loss of autonomy
factor, central nervous system medication use, cardiovascular medication
use, social isolation factor, low socioeconomic status (SES) factor,
environmental risk factor, and absence of highly protective/protective
factor. Higher values reflect elevated heat vulnerability.
Data analysis
As the NuAge sample was stratified for age, sex and region, overall
and health region-specific analyses were weighted for age and sex, and
weights for regions were also applied for overall analyses. The
prevalence of each factor was calculated in the total sample and within
each region and corresponds to the valid percentage (no replacement of
missing data). Partial non-response rates were computed separately for
each risk and protective factor (i.e., dividing the number of
participants with missing data by 1,679 participants for each factor
examined) and ranged from 0 to 14%. Pearson's chi-squared ([chi
square]) test was used to compare the prevalence of factors between
regions. Some p-values were not reported when the [chi square] test
could not be performed where basic assumptions were not met. Because of
stratification of the sample, Fisher's exact test could not be
performed. For the OAHVI, the Kruskal-Wallis test was carried out.
Analyses were performed with SPSS 18 and SAS 9.2 statistical software
and level of statistical significance was set at 0.05.
Ethics
The NuAge study has been approved by the ethics committees of the
GUIM and GUIS. All participants signed the consent form, including
authorization for their data and biological samples to be included in
the NuAge Database and Biobank for investigative work by NuAge
investigators and their collaborators. The current study has been
approved by the ethics committee of the GUIS.
RESULTS
Table 1 shows global and health region-specific prevalence of risk
and protective factors associated with heat-related outcomes in Southern
Quebec. Health conditions and medication use were frequent in our sample
(78.3% and 53.6% respectively). Overall, frequency of physical health
disorders was higher than that of mental health and cognitive disorders
or loss of autonomy, and was more elevated in the Eastern Townships
relative to the other regions under study. About 10% of participants had
depressive symptoms or took antidepressants, with the highest prevalence
observed in Montreal (p = 0.02). More than half of the sample had social
risk factors, with major differences between regions. Social isolation
was more frequent among Montreal participants, whereas low SES was twice
as frequent in the Eastern Townships as in Montreal or Laval. More than
a third of participants lived in a UHI in the Eastern Townships and
Montreal, compared to only 18.3% in Laval. Having at least one
protective factor was frequent overall (69.4%) and significant
differences were observed between regions (p < 0.0001). While
participants living in Montreal were more likely to report high social
participation, visiting places with AC, and talking on the phone daily,
a higher proportion of Eastern Townships participants lived in a cooling
island. Globally, a median of 3.0 factors per participant was computed,
increasing their heat vulnerability, yet significant disparities were
observed between regions (p < 0.0001).
Figure 2 shows global and regional distributions of the OAHVI
score. Having more than one factor increasing heat vulnerability was
very common (92.9% Eastern Townships, 87.1% Montreal, 82.7% Laval).
DISCUSSION
Montreal/Laval and Eastern Townships residents were bothered by
more than several hot temperature days (i.e., 45 and 34 days
respectively) during the 2006-2010 summer seasons. Describing the
prevalence of potential factors contributing the most to heat
vulnerability is essential in order to inform public health authorities.
Overall, this study showed that heat vulnerability was very common
among older adults in Southern Quebec, as the simultaneous presence of
several factors increasing vulnerability was observed in most
participants.
The most prevalent risk factors were cardiovascular conditions,
with approximately 60% of older adults having cardiovascular disease or
hypertension and half of them reporting cardiovascular medication use.
These prevalences are similar to previous observations in Montreal. (22)
Our results show that physical health disorders are five times more
prevalent than mental health and cognitive disorders. However, these
results might reflect the general good health and autonomy of NuAge
participants at baseline. Nevertheless, depressive symptoms were present
in 12% of participants, which is similar to previous observations made
for the province of Quebec. (23) Clinicians should consider
cardiovascular diseases and depression when assessing patients'
vulnerability to heat, given that they are frequent, relatively easy to
detect, and have been identified as major underlying causes of
heat-related mortality in Quebec (4) and elsewhere.
Needing help in activities of daily living (ADL) was prevalent
(26.5%) and much higher than proportions reported in surveys for the
province of Quebec among individuals aged 65 years and older (range
2.2%-6.29%). (24) However, ADL disabilities were self-reported in these
surveys while the SMAF is based on a clinical evaluation of functional
autonomy, including disabilities and handicaps. Knowing that older
adults tend to overestimate their level of functioning, (25) clinical
assessment, rather than self-reported information, is needed to
adequately assess this risk factor. Presence of disability in self-care
could translate to difficulties in taking appropriate actions to prevent
heat-related health issues, such as voluntary hydration or effective
cooling. (1) Living alone was highly prevalent (39.2%) in this study
sample and, as previously reported, prevalence varies greatly according
to regions, (26) with the highest proportion in Montreal, (22)
highlighting the need for region-tailored prevention strategies.
About a third (34.7%) of our participants were living in a UHI. In
2011, 18.7% of the adult population, including older adults, were living
in a UHI in Sherbrooke (main city in Eastern Townships). (27) Thus, the
likelihood of living in a UHI may vary greatly according to place of
residence and possibly by age. Our study also suggests that this factor
is not solely related to the level of urbanization, since our results
show similar proportions of participants living in a UHI in the Eastern
Townships and Montreal, despite important differences in residential
density between these areas. UHIs more frequently occur in large cities;
however, they can form over any built-up area, (1) depending on
climatic, energetic, geographic, morphologic, politic and structural
factors. (28)
This study showed that heat vulnerability varied by health region
and was mainly due to social and environmental factors rather than
medical conditions. To our knowledge, this is the first study examining
variation of a wide range of risk and protective factors at a small
scale. The important and numerous disparities observed between regions
in several potential predictors of heat-related outcomes support the
need for small-scale assessment of heat vulnerability among older
adults.
Examination of the OAHVI developed for this study showed that
simultaneous presence of risk factors (or absence of protective factors)
was the norm among study participants. A median of 3.0 factors per
participant was observed, suggesting heat vulnerability; however, this
varied significantly across the three regions investigated. Using mainly
social and environmental predictors, spatial clustering of heat
vulnerability has been observed in the US (10-12) and Canada. (13) The
predictive validity of the OAHVI should be examined in further studies
in relation to heat morbidity or mortality. Once validated, this index
would be useful in clinical settings to identify heatvulnerable older
adults and implement intensive interventions among these high-risk
individuals.
Strengths
Based on a large representative sample of older adults living in
Southern Quebec, with a very low rate of loss to follow-up (6%), our
findings contribute to current knowledge on global and health
region-specific frequency of risk and protective factors associated with
heat-related health outcomes. All factors examined were previously
identified in the 2011 Health Canada guidelines. Moreover, our study
went further than published literature by examining the distribution of
these factors at a smaller scale and by providing information on a wider
range of factors, including health conditions and medication use.
Finally, our study proposed a new HVI, targeting older adults (OAHVI),
which could be an important predictor of individuals' global risk
of heat-related outcomes.
Limitations
Our study presents limitations. First, all factors were measured in
2005 or 2006 and not necessarily during hot temperature days. This could
lead to an over- or underestimation of social factors, such as being
homebound vs. high social participation or visiting locations with AC,
that may vary over time.
Global participation rate was 58.6%. Non-responders were more
likely to be older and living in a metropolitan area. This might have
led to underestimation of the prevalence rates of risk and protective
factors globally (e.g., medical factors which may be more frequent with
advanced age) and among the Montreal/ Laval subsample.
Furthermore, no data were available on AC at home (highly
protective factor in Health Canada guidelines). However, this protective
factor was indirectly considered through the inclusion of the low family
household income variable. Indeed, Quebecers with a lower household
income (<$20,000) are 1.3 to 2.8 times less likely to have AC at home
compared to their more affluent counterparts (household income [greater
than or equal to]$80,000). (27, 29) AC utilization might be less
frequent among low SES persons due to purchase and operation costs. (12)
Other heat-related factors were not available in the NuAge database,
such as living on the top floor of a building, history of heat
stroke/illness and lack of or improper acclimatization. (1) Finally, as
our sample is composed of generally healthy community-dwelling older
adults residing in private households in the Eastern Townships, Montreal
and Laval, generalizability of our results to other contexts might be
limited.
CONCLUSION
Risk and protective factors associated with heat-related health
outcomes were prevalent among older adults in Southern Quebec, and the
vast majority of respondents presented multiple factors. Heat
vulnerability also varied according to health regions. Our proposed
OAHVI should be tested further by linking it to heat-related morbidity
or mortality data in order to evaluate its predictive validity.
REFERENCES
(1.) Health Canada. Extreme Heat Events Guidelines: Technical Guide
for Health Care Workers. 2011. Available at:
http://www.hc-sc.gc.ca/ewh-semt/pubs/
dimat/workers-guide-travailleurs/index-eng.php (Accessed March 5, 2012).
(2.) Environnement Canada. Criteres d'avertissements publics.
2014. Available at: http://ec.gc.ca/meteo-weather/default.asp?lang=Fr&n=D9553AB5-1#chaleurhumidite (Accessed August 31, 2013).
(3.) Institut National de Sante Publique du Quebec. Indicateurs et
seuils meteorologiques pour les systemes de veille-avertissement lors de
vagues de chaleur au Quebec. 2010. Available at:
http://www.inspq.qc.ca/pdf/publications/1151_IndicVeilleAvertissementVagueChaleur.pdf (Accessed August 31, 2013).
(4.) Agence de la Sante et des Services Sociaux. Canicule 2010 a
Montreal. Rapport du directeur de Sante Publique. 2011. Available at:
http://publications.
santemontreal.qc.ca/uploads/tx_asssmpublications/978-2-89673-036-0.pdf
(Accessed September 15, 2011).
(5.) Institut National de Sante Publique du Quebec. Surveillance
des impacts sanitaires des vagues de chaleur au Quebec. Bilan de la
saison estivale 2010. 2011. Available at:
http://www.inspq.qc.ca/pdf/publications/1275_
SurvImpactsChaleurBilanEte2010.pdf (Accessed October 4, 2011).
(6.) Institut National de Prevention et d'Education pour la
Sante. Fortes chaleurs: prevenir les risques sanitaires chez la personne
agee. 2007. Available at: http://
www.inpes.sante.fr/CFESBases/catalogue/pdf/1033.pdf (Accessed October 5,
2011).
(7.) Vescovi L, Rebetez M, Rong F. Assessing public health risk due
to extremely high temperature events: Climate and social parameters.
Clim Res 2005; 30:71-78. doi: 10.3354/cr030071.
(8.) Gouvernement du Quebec. Les atnes du Quebec, quelques donnees
recentes. 2012. Available at:
http://www.aines.gouv.qc.ca/documents/sommaire-vieilliret-vivre-ensemble.pdf (Accessed November 20, 2013).
9. Societe Canadienne d'hypotheques et de logement. Quelles
proportions de Canadiens ages vivent dans les zones urbaines et rurales
du Canada? 2015. Available at:
http://www.cmhc-schl.gc.ca/lang.cfm?pid=275371 (Accessed September 3,
2015).
10. Reid CE, O'Neill MS, Gronlund CJ, Brines SJ, Brown DG,
Diez-Roux AV et al. Mapping community determinants of heat
vulnerability. Environ Health Perspect 2009; 117(11):1730-36. PMID:
20049125. doi: 10.1289/ehp.0900683.
11. Harlan SL, Declet-Barreto JH, Stefanov WL, Petitti DB.
Neighborhood effects on heat deaths: Social and environmental predictors
of vulnerability in Maricopa County, Arizona. Environ Health Perspect
2013; 121(2):197-204. PMID: 23164621. doi: 10.1289/ehp.1104625.
(12.) Johnson DP, Stanforth A, Lulla V, Luber G. Developing an
applied extreme heat vulnerability index utilizing socioeconomic and
environmental data. Appl Geogr 2012; 35:23-31. doi:
10.1016/j.apgeog.2012.04.006. 0 factor 1 factor ? 2 factors ? 3 factors
? 4 factors ? 5 factors ? 6 factors ? 7 factors ? 8 factors ? 9 factors
(13.) Rinner C, Patychuk D, Briggs S. Implementation of a Map-Based
Heat Vulnerability Assessment and Decision Support System, Final Project
Report and Map Series. 2011. Available at:
http://www.climateontario.ca/doc/
ORAC_Products/TPH/implementation_mapping_heat_vulnerability1.pdf
(Accessed March 1, 2014).
(14.) Institut de la statistique du Quebec. Panorama des regions du
Quebec, edition. 2014. Available at:
http://www.stat.gouv.qc.ca/statistiques/profils/panoramaregions.html
(Accessed August 8, 2014).
(15.) Gaudreau P, Morais JA, Shatenstein B, Gray-Donald K, Khalil
A, Dionne I, et al. Nutrition as a determinant of successful aging:
Description of the Quebec longitudinal study NuAge and results from
cross-sectional pilot studies. Rejuvenation Res 2007; 10(6):377-86.
PMID: 17708689. doi: 10.1089/rej. 2007.0596.
(16.) Fillenbaum GG, Smyer MA. The development, validity and
reliability of the OARS multidimensional functional assessment
questionnaire. J Gerontol 1981; 36:428-34. PMID: 7252074. doi:
10.1093/geronj/36.4.428.
(17.) World Health Organization. Obesity and Overweight. 2013.
Available at: http://www.who.int/mediacentre/factsheets/fs311/en/
(Accessed February 21, 2013).
(18.) McDowell I, Newell C. Measuring Health: A Guide to Rating
Scales and Questionnaires. New York, NY, Oxford: Oxford University
Press, 1996; pp. 314-23.
(19.) Teng EL, Chui HC. The Modified Mini-Mental State (3MS)
examination. J Clin Psychiatry 1987; 48(8):314-18. PMID: 3611032.
(20.) Hebert R, Guilbault J, Desrosiers J, Dubuc N. The Functional
Autonomy Measurement System (SMAF): A clinical-based instrument for
measuring disabilities and handicaps in older people. J Can Geriatr Soc
2001; 4:141-47.
(21.) Institut national de sante publique du Quebec. Guide
methodologique: <<L'indice de defavorisation materielle et
sociale: en bref ". 2010. Available at:
http://www2.inspq.qc.ca/santescope/documents/Guide_Metho_Indice_
defavo_Sept_2010.pdf (Accessed June 17, 2014).
(22.) Direction de sante publique, Agence de la sante et des
services sociaux de Montreal. Vieillir a Montreal, Un portrait des
arnes. 2008. Available at: http://
ccpsc.qc.ca/sites/ccpsc.qc.ca/files/vieilliramontreal_v2.pdf (Accessed
July 19, 2014).
(23.) Institut de la statistique du Quebec. Sante et bien-etre,
Troubles mentaux, toxicomanie et autres problemes lies a la sante
mentale chez les adultes quebecois. Enquete sur la sante dans les
collectivites canadiennes (cycle 1.2). 2008. Available at:
http://www.stat.gouv.qc.ca/statistiques/sante/etat-sante/
mentale/troubles-mentaux-toxicomanie.pdf (Accessed July 19, 2014).
(24.) Institut national de sante publique du Quebec. Vieillissement
de la population, etat fonctionnel despersonnes dgees et besoins futurs
en soins de longue duree au Quebec. 2010. Available at:
http://www.inspq.qc.ca/pdf/publications/1082_ VieillissementPop.pdf
(Accessed July 30, 2014).
(25.) Schaie KW, Lawton MP. Annual Review of Gerontology and
Geriatrics. New York, NY: Behavioral Science & Aging, Springer
Publishing Company, 1991; pp. 100-1.
(26.) Institut national de sante publique du Quebec en
collaboration avec le Ministere de la sante et des services sociaux du
Quebec et l'Institut de la statistique du Quebec. Portrait de sante
du Quebec et de ses regions 2006: les statistiques--Deuxieme rapport
national sur l'etat de sante de la population. 2006. Available at:
www.inspq.qc.ca/pdf/publications/545-PortraitSante2006_ Statistiques.pdf
(Accessed August 5, 2014).
(27.) Roy M, Genereux M, Laverdiere E, Vanasse A. Surveillance of
social and geographical inequalities in housing-related issues: The case
of Eastern Townships, Quebec (Canada). Int J Environ Res Public Health
2014; 11(5):4825-44. PMID: 24806192. doi: 10.3390/ijerph110504825.
(28.) Lachance G, Baudouin Y, Guay F. Etude des Hots de chaleur
montrealais dans une perspective de sante publique. 2006. Available at:
http://www.inspq.qc.ca/
bise/post/2006/06/15/Etude-des-ilots-de-chaleur-montrealais-dans-uneperspective- de-sante-publique.aspx (Accessed May 1, 2014).
(29.) Gosselin P, Belanger D, Doyon B. Chapitre 6--Les effets des
changements climatiques sur la sante au Quebec. 2008. Available at:
http://www.ouranos. ca/fr/pdf/ouranos_chapitre-6.pdf (Accessed April 30,
2014).
Received: February 25, 2015
Accepted: May 25, 2015
Emelie Laverdiere, BSc, [1] Melissa Genereux, MD, MSc, FRCPC, [2-4]
Pierrette Gaudreau, PhD, [5] Jose A. Morais, MD, [6] Bryna Shatenstein,
PhD, [7] Helene Payette, PhD [3, 4]
Author Affiliations
[1.] Faculty of Medicine and Health Sciences, Universite de
Sherbrooke, Sherbrooke, QC
[2.] Eastern Townships Public Health Department, Sherbrooke, QC
[3.] Department of Community Health Sciences, Universite de
Sherbrooke, Sherbrooke, QC
[4.] Research Centre on Aging, Health and Social Services
Centre-University Institute of Geriatrics of Sherbrooke, Sherbrooke, QC
[5.] Centre Hospitalier de l'Universite de Montreal Research
Center and Department of Medicine, University of Montreal, Montreal, QC
[6.] Division of Geriatric Medicine, Faculty of Medicine, McGill
University and MUHC Crabtree Nutrition Laboratories, Montreal, QC
[7.] Research Center-University Institute of Geriatrics of Montreal
and Department of Nutrition, University of Montreal, Montreal, QC
Correspondence: Dr. Melissa Genereux, 300, rue King Est, bureau
300, Sherbrooke, QC J1G 1B1, Tel: [telephone] 819-829-3400, ext. 42453,
E-mail: mgenereux.agence05@ssss. gouv.qc.ca
Funding Source of Support: The NuAge study was supported by the
Canadian Institutes of Health Research (CIHR) (Grant # MOP-62842), and
the Quebec Network for Research on Aging, a network funded by the Fonds
de Recherche du Quebec--Sante.
Acknowledgements: We acknowledge the excellent contribution of
Steve Toutant, geomatic specialist at the INSPQ, for the determination
of ecological data.
Conflict of Interest: None to declare.
Table 1. Prevalence of risk and protective factors associated with
heat-related outcomes in a community-dwelling cohort of older adults
Total Eastern Montreal
sample Townships (n = 471)
(n = 1679) (n = 901)
Risk factors (%)
Health conditions
Physical health disorders
Cardiovascular disease 36.9 43.5 35.9
Pulmonary disease 4.7 5.0 4.7
Neurological disease 0.8 1.7 0.5
Renal disease 3.2 5.1 2.3
Hypertension 46.7 58.0 44.9
Diabetes 11.4 11.2 11.5
Obesity 25.2 27.4 25.4
[greater than or equal to]1 72.1 81.0 70.5
physical health disorder
Mental health and cognitive
disorders
Depressive symptoms 12.0 9.1 13.2
Cognitive impairment 1.9 3.9 1.6
Bipolar disorders 0.3 0 0.4
[greater than or equal to]1 13.7 12.3 14.7
mental health or cognitive
disorder
Loss of autonomy
Needing help in activities of 26.5 23.0 28.9
daily living
Obligation to stay in bed 7.5 11.8 7.1
[greater than or equal to]1 30.3 29.4 32.5
factor related to loss of
autonomy
[greater than or equal to]1 78.3 83.3 78.1
health condition (physical or
mental health and cognitive
disorders, or loss of
autonomy)
Medication use
Cardiovascular medication use
Diuretics 20.7 19.7 21.2
Antiarrhythmics and cardiotonics 36.2 40.5 35.7
Nitrate vasodilators 4.6 7.7 4.2
Angiotensin-converting enzyme 16.8 22.4 15.4
inhibitors
Calcium channel blockers 17.9 23.8 17.0
[greater than or equal to]1 50.8 55.9 49.8
cardiovascular medication use
Central nervous system
medication (CNS) use
Antipsychotics/neuroleptics 1.1 0.1 1.3
Antidepressants 7.3 6.4 8.1
Lithium 0.1 0.1 0
Antiepileptics 1.9 2.0 1.9
Anti-Alzheimer's agents 0.1 0.3 0
Anti-Parkinson's agents 0.8 1.5 0.5
[greater than or equal to]1 CNS 9.2 9.6 9.2
medication use
[greater than or equal to]1 CNS 53.6 59.6 52.1
or cardiovascular medication
use
Social factors
Social isolation
Living alone 39.2 32.1 42.9
Knowing nobody enough to visit 1.3 1.2 1.5
them
Not leaving home 6.7 4.1 6.7
[greater than or equal to]1 44.3 36.4 47.6
factor related to social
isolation
Low SES
Family household income <$20,000 14.9 21.4 14.2
Primary school level or less 10.2 30.0 6.5
Material deprivation 8.9 10.8 9.2
[greater than or equal to]1 25.7 46.5 23.0
factor related to lower SES
[greater than or equal to]1 53.2 61.7 53.9
social factor
Environmental factor
Living in an urban heat island 34.7 39.6 36.8
Protective factors (%)
Highly protective factors (%)
High social participation 13.6 10.2 15.1
Visiting places with AC 10.6 7.3 12.0
Living in a coolness island 1.2 5.4 0.5
Protective factor
Talking on the phone daily 70.9 54.9 74.6
[greater than or equal to]1 69.4 59.8 72.8
highly protective or
protective factor
OAHVI score (0-9) (median) 3.0 4.0 3.0
Laval [chi square]
(n = 307) test p-value
Risk factors (%)
Health conditions
Physical health disorders
Cardiovascular disease 36.4 0.10
Pulmonary disease 4.1 0.89
Neurological disease 1.7 0.12
Renal disease 6.9 0.002
Hypertension 46.3 0.002
Diabetes 11.3 0.99
Obesity 22.1 0.46
[greater than or equal to]1 72.9 0.006
physical health disorder
Mental health and cognitive
disorders
Depressive symptoms 7.8 0.02
Cognitive impairment 1.5 0.09
Bipolar disorders 0 --
[greater than or equal to]1 9.1 0.06
mental health or cognitive
disorder
Loss of autonomy
Needing help in activities of 15.6 <0.0001
daily living
Obligation to stay in bed 5.4 0.03
[greater than or equal to]1 18.2 <0.0001
factor related to loss of
autonomy
[greater than or equal to]1 74.4 0.07
health condition (physical or
mental health and cognitive
disorders, or loss of
autonomy)
Medication use
Cardiovascular medication use
Diuretics 18.7 0.64
Antiarrhythmics and cardiotonics 35.2 0.37
Nitrate vasodilators 4.0 0.07
Angiotensin-converting enzyme 19.7 0.02
inhibitors
Calcium channel blockers 17.2 0.05
[greater than or equal to]1 51.9 0.24
cardiovascular medication use
Central nervous system
medication (CNS) use
Antipsychotics/neuroleptics 0.6 0.16
Antidepressants 3.5 0.02
Lithium 0.6 --
Antiepileptics 2.1 0.98
Anti-Alzheimer's agents 0.3 --
Anti-Parkinson's agents 2.2 0.05
[greater than or equal to]1 CNS 8.4 0.91
medication use
[greater than or equal to]1 CNS 57.2 0.07
or cardiovascular medication
use
Social factors
Social isolation
Living alone 24.1 <0.0001
Knowing nobody enough to visit 0.2 0.10
them
Not leaving home 9.0 0.12
[greater than or equal to]1 32.5 <0.0001
factor related to social
isolation
Low SES
Family household income <$20,000 12.8 0.03
Primary school level or less 13.7 <0.0001
Material deprivation 5.4 0.08
[greater than or equal to]1 22.4 <0.0001
factor related to lower SES
[greater than or equal to]1 42.0 <0.0001
social factor
Environmental factor
Living in an urban heat island 18.3 <0.0001
Protective factors (%)
Highly protective factors (%)
High social participation 7.7 0.002
Visiting places with AC 5.4 0.0009
Living in a coolness island 1.4 <0.0001
Protective factor
Talking on the phone daily 64.4 <0.0001
[greater than or equal to]1 58.2 <0.0001
highly protective or
protective factor
OAHVI score (0-9) (median) 3.0 <0.0001 *
* Kruskal-Wallis test for independent samples.
Figure 2. Distribution of the OAHVI score in a community-dwelling
cohort of older adults
Total Eastern Montreal Laval
sample Townships
0 factor 1% 1% 1% 1%
1 factors 12% 6% 12% 16%
2 factors 19% 14% 19% 21%
3 factors 21% 22% 20% 23%
4 factors 21% 23% 20% 27%
5 factors 17% 18% 18% 9%
6 factors 8% 11% 9% 2%
7 factors 1% 4% 1% 1%
8 factors 0% 1% 0% 0%
9 factors 0% 0% 0% 0%
Note: Table made from pie chart.
