Journal of Public Health Advance Access originally published online on October 18, 2005
Journal of Public Health 2005 27(4):359-365; doi:10.1093/pubmed/fdi059
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Were less disabled patients the most affected by 2003 heat wave in nursing homes in Paris, France?
Josiane Holstein
Josiane Holstein, MD, Department of Medical Information, Assistance Publique-Hôpitaux de Paris, 3 Avenue Victoria, 75004 Paris Cedex 04, France
Florence Canouï-Poitrine
Florence Canouï-Poitrine, MD, Epidemiology and Public Health Department, Hôpital Bicêtre, Assistance Publique-Hôpitaux de Paris, 78 rue du Général Leclerc, 94275 Le Kremlin-Bicêtre Cedex 08, France
Anke Neumann
Eric Lepage
Anke Neumann, PhD, Eric Lepage, MD PhD, Department of Medical Information, Assistance Publique-Hôpitaux de Paris, 3 Avenue Victoria, 75004 Paris Cedex 04, France
Alfred Spira
Alfred Spira, MD PhD, Epidemiology and Public Health Department, Hôpital Bicêtre, Assistance Publique-Hôpitaux de Paris, 78 rue du Général Leclerc, 94275 Le Kremlin-Bicêtre Cedex 08, France
Address correspondence to Josiane Holstein. Email: josiane.holstein{at}sap.ap-hop-paris.fr
Objective To analyse the change of mortality rates (MRs) and their contributing medical factors among nursing home patients during the 2003 heat wave in France.
Methods A retrospective observational study was conduced in all nursing homes of the Assistance-Publique-Hôpitaux de Paris (AP-HP), the French largest public hospital group. All AP-HP nursing home patients (4403) who were institutionalized in May, 2003, were concerned. The MRs of patients between three periods (before, during and after the August 2003 heat wave period) were compared according to their demographic characteristics, level of dependence and medical condition.
Results The MR increased from 2.2 per cent persons month (ppm) (1.9–2.4) before heat wave up to 9.2 ppm (8.0–10.4) during heat wave and back to 2.4 ppm (2.2–2.7) after heat wave. MRs before heat wave were higher among highly dependent patients compared to those less dependent [mortality rate ratio (MRR) = 2.66 (1.69–4.21)]. This difference disappeared during the heat wave [MRR = 1.28 (0.91–1.81)] and appeared again after heat wave [MRR = 2.21 (1.52–3.23)]. The same pattern was observed for several medical conditions, such as severe malnutrition or swallowing disorders.
Conclusion These results suggest that medical care during heat wave has been directed towards more fragile patients, helping to limit deaths in this group. Less frail patients made the largest contribution to excess mortality during the heat wave. During extreme weather conditions, specific attention should be paid not only to frail persons, but to all the elderly community.
Keywords: heat wave, mortality, nursing home
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Introduction |
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The number of deaths increased sharply during the heat wave in France between 4 and 14 August, 2003. There were 14 802 excess deaths between 1 and 20 August, 2003, compared with the mean number of deaths of the three previous years (2000–01–02), which represented an excess mortality of 60 per cent. A public health event with such extent had never happened before in France.1 Sixty-three per cent of heat-related deaths occurred in institutions; of these a quarter occurred in nursing homes.2
Assistance Publique-Hôpitaux de Paris (AP-HP) is the largest public hospital group in the Paris region with 41 hospitals. There are 22 nursing homes for the elderly with a total of 4400 beds. Patients in these units have a mean age of 83 years, have multiple severe medical conditions, are highly dependent and require long-term medical care.3 There were 194 extra deaths in these nursing homes between 1 and 20 August, 2003, which represented a fivefold increase compared to the number of deaths during the same period in the three previous years (from AP-HP administrative data).
The aim of our study was to analyse changes in the mortality rates (MRs) and the contributing medical factors in AP-HP nursing homes patients during the 2003 heat wave compared to the periods before and after the heat wave.
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Methods |
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TOPIntroductionMethodsResultsDiscussionLimitations of this studyConclusionAuthor contributionsAppendix: List of severe...AcknowledgementsReferences |
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Population
Unlike the short stay and rehabilitation sectors, there is no routine collection of medical data in AP-HP nursing homes.4 A 1-week survey is conducted each year to determine the health status and level of dependence of all patients present in the units. Patients present in a unit at least one of the days during the week of the survey are included regardless of the length of stay and outcome during the week (including death or transfer to another center).
We used data from the annual survey of patients in nursing homes which had been conducted from 12 to 18 May, 2003. As data had been obtained less than 3 months before the heat wave, we considered that these data were characteristic of the patient population throughout the study period.
Annual survey conducted in nursing homes
Data collected during the survey included age, sex and the functional status of each patient. The presence of dementia regardless of its cause and stage of progression and the presence or absence of severe or complex chronic diseases (SCCD) were also recorded (Appendix). The list of SCCD collected during the annual survey was established by geriatricians who defined those conditions which require intensive medical and care management and influence short-term prognosis. Functional status assessment was based on the Autonomie Gérontologique Groupes Iso-Ressources (GIR) score. This score is used throughout France to measure the level of dependence of elderly in-patients and out-patients. It consists of 10 discriminatory items including coherence, orientation, personal hygiene, dressing, feeding, continence and mobility. Patients are classified into one of six ‘GIR-groups’ (from 1 to 6). Patients in GIR Group 1 are the most dependent and those in GIR Group 6 are the least dependent.5
Follow-up survey
In December 2003, a questionnaire was sent to all AP-HP nursing homes units to determine the outcome of each person who had been included in the May 2003 survey. Information requested was on whether the patient had died, returned home or been transferred to another structure and the date when the event occurred, for the period between the end of the survey and the end of November 2003. Data were validated by the head of department of each unit.
Statistical analysis
The analysis of the patient population was based on the number of deaths in the period between 12 May and 30 November, 2003, split into three subperiods. The before heat wave period was from 12 May to 31 July, the heat wave period was from 1 to 20 August as defined in a study of all deaths throughout France1 and the after heat wave period was from 21 August to 30 November.
The MR per person-month was calculated for each period and for each of the following variables: sex, age group (less than 81 years and 81 years and older), class of dependence defined as either highly dependent (GIR Groups 1 and 2) or slightly and moderately dependent (GIR Groups 3–6), presence of dementia and each SCCD. The MR was multiplied by 100 to obtain the rate in per cent person month (ppm). The 95% confidence interval (CI) was calculated for each MR. For each period, the mortality rate ratio (MRR) was calculated for each variable (e.g. the mortality rate ratio of patients with dementia compared to those without) by adjusting for sex and age using a Poisson regression.6 For each MRR, the 95% Wald CI was calculated. The fit with the Poisson model was tested by Pearson’s chi-square test. For each variable, we compared the sex- and age-adjusted effect before and during the heat wave by a statistical test within the frame work of a Cox model with a time-dependent explanatory variable. Statistical tests were performed using SAS 8.2 .
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Results |
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TOPIntroductionMethodsResultsDiscussionLimitations of this studyConclusionAuthor contributionsAppendix: List of severe...AcknowledgementsReferences |
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Data were analysed on a total of 4403 patients who were present during the morbidity survey between 12 and 18 May, 2003, in 48 units of 22 hospitals in Paris and the surrounding suburbs. Mean age was 82.6 years, the sex ratio was 3 females to one male, 3485 (80 per cent) patients were highly dependent (GIR Groups 1 and 2), 2610 (60 per cent) had at least one SCCD and 3310 (76 per cent) were demented (Table 1). The follow-up survey provided information on the outcome for 4361 (99 per cent) of these patients.
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As shown in Fig. 1, there was a marked increase in the number of deaths between 1 and 20 August MRs for the periods before, during and after the heat wave according to patients’ characteristics are summarized in Table 1. The age and sex adjusted MRRs for the three periods are summarized in Table 2. Of the total of 785 deaths during the study period, 245 occurred before the heat wave (MR = 2.2, 95% CI = 1.9–2.4), 241 during the heat wave (MR = 9.2, 95% CI = 8.0–10.4) and 299 after the heat wave (MR = 2.4, 95% CI = 2.2–2.7). After a marked increase in the MR during the heat wave as compared to the period before the heat wave, we did not observe a significant change in the risk of death after the heat wave period as compared to the period before the heat wave (p = 0.86 for the exact Wilcoxon test comparing the weekly number of deaths before and after the heat wave). The risk of death was similar in men and women before the heat wave [MR, 2.2 versus 2.1; crude MRR = 1.04 (0.79–1.39)], significantly higher among men during the heat wave (MR, 12.3 versus 8.1; crude MRR = 1.51 (1.15–1.97)] and the same for both sexes after the heat wave [MR, 2.5 versus 2.4; crude MRR = 1.02 (0.79–1.33)]. Crude MRR during the heat wave was significantly higher than the crude MRRs before and after the heat wave (p = 0.033 and p = 0.018, respectively). By contrast, the crude MRRs for the oldest patients (older than 80 years) did not differ significantly between distinct time periods (before heat wave, MRR = 1.58 (1.19–2.08); during heat wave, MRR = 1.42 (1.07–1.87) and after the heat wave, MRR = 1.60 (1.24–2.05).
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As compared with the least dependent patients, the most dependent patients had a higher risk of death before the heat wave [MR = 2.5 versus 0.9, MRR = 2.66 (1.69–4.21)] and after the heat wave [MR = 2.8. versus 1.2, MRR = 2.21 (1.52–3.23)], but there was no significant difference between highly dependant and less dependant patients during the heat wave [MR = 9.7 versus 7.3, MRR = 1.28 (0.91–1.81)].
Morbidity factors were classified based on the relative progression in MRs during the three phases of the study period (Table 2). A first group consisted of severe malnutrition, chronic sores, respiratory insufficiency, chronic pain, swallowing disorders, severe peripheral arterial disease and cardiac insufficiency. Before the heat wave, the MRs in patients with one of these conditions were significantly higher than among those without one of these conditions [e.g. severe malnutrition: MRR = 4.20 (3.18–5.54)]. The MRs among patients with or without these conditions were similar or nearly similar during the heat. During the after heat wave period, MRRs remained not significantly different from 1 (chronic sores, respiratory insufficiency, chronic pain and cardiac insufficiency) or nearly nondifferent from 1 (severe malnutrition and severe peripheral arterial disease). A second group consisted of conditions with elevated MRs before the heat wave [palliative care: MR = 15.2, adjusted MRR = 8.80 (6.63–11.68); progressive cancer: MR = 5.7, adjusted MRR = 2.67 (1.77–4.01); repeated bronchopulmonary infections: MR = 4.6, adjusted MRR = 2.29 (1.69–3.09)]. During the heat wave the MRRs remained higher than for patients without these conditions mortality rates after the heat wave were also nonsignificantly different than those before the heat wave. A third group consisted of dementia, hemiplegia sequel, Parkinson, disease terminal renal insufficiency, epilepsy and psychotic states. For this group, the MRRs were not different from one before the heat wave and remained the same during after the heat wave (except for dementia with an after heat wave MRR significantly >1).
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Discussion |
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TOPIntroductionMethodsResultsDiscussionLimitations of this studyConclusionAuthor contributionsAppendix: List of severe...AcknowledgementsReferences |
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Main findings of this study
A high level of dependence was identified as a risk factor for mortality during the heat wave in Chicago in 1995 (the odds ratio for death in bedridden patients compared to nonbedridden was 5.5).7 Even though MR among the most dependent patients in our study was 3.9 times higher during the heat wave, those who were less dependent had an 8.3 times greater risk of mortality compared to the period before the heat wave. One hypothesis to explain this finding may be that the staff took special care to maintain hydration and refreshment in the most dependent patients and thereby avoided complications and prevented death in these patients.
The MRR of patients with dementia or at least one severe condition was significantly >1 in the period before the heat wave but this became nonsignificantly different from one during the heat wave (Table 2). This is consistent with the fact that many deaths occurred in France and in other countries among persons without severe conditions and altered functional autonomy.8
Contrary to reports of heat waves in other countries, we did not find any compensating under-mortality or a ‘mortality displacement’ in the weeks and months following the heat wave.9,10 Thus, in this population of extremely frail patients with multiple severe medical conditions, death concerned patients who may have remained alive much longer. Moreover, we also did not observe any mortality excess in the period after the heat wave as this was the case in Marseille in 1983.11
What is already known on this topic
In France, about 5 per cent of patients over 60 are cared for in nursing homes. Of these, 85 per cent are in retirement homes which come under the social sector, and the other 15 per cent are in nursing homes within the health sector. The nursing homes are in hospitals and admit patients with several severe medical conditions, very little or no autonomy, and who are most often in their eighties or nineties.3,12,13
There were very few data on mortality in nursing homes during the summer of 2003 because the number of deaths was included in the overall number of deaths which occurred in hospitals.1 A study confirmed that 63 per cent of the heat-related deaths in August 2003 occurred in institutions and among these deaths, 25 per cent occurred in nursing homes and 47 per cent in retirement homes.2
Our results confirm previous findings of a marked increase in the risk of death among elderly and sick persons during heat waves.10,14–16 The risk of death was significantly higher in men than in women in our study and this was similar to an American study,7 whereas other studies reported conflicting results.17,18
What this study adds
Our data were collected prospectively and thus excluded any differential bias in classification of medical conditions and the level of dependence between the persons who died during the heat wave and those who did not die during the heat wave. The very few persons lost to follow-up (1 per cent) excluded bias due to missing data on deceased persons. We also adjusted for age and sex as these may have confounded our results.
A simulation in which the MR of patients without dementia or SCCD was applied to patients with either or both of these conditions resulted in 400 expected deaths, whereas 224 actually occurred. It is highly likely that the staff concentrated on preventive measures and treatment of the effects of the extreme heat in the most severely ill patients and those least prone to drink, and thereby prevented deaths in this particularly vulnerable subpopulation. The three groups of conditions which were identified in our study support this explanation. The first group included conditions associated with a risk of dehydration (dementia, hemiplegia sequelae often with swallowing disorders and advanced Parkinson disease).19,20 As staff pay particular attention to electrolyte balance during periods of extreme heat, this probably explains why the MR increased to a smaller extent for these patients. The decrease of MR in the second group which included terminally-ill patients (palliative care and advanced cancer) between the before heat wave period and the after heat wave period probably indicates a selection process with the most frail patients dying early and those who survived the heat wave being more resistant.
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Limitations of this study |
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TOPIntroductionMethodsResultsDiscussionLimitations of this studyConclusionAuthor contributionsAppendix: List of severe...AcknowledgementsReferences |
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Although our list included the most severe chronic conditions according to a group of experts in geriatrics, it may not have been exhaustive and patients with other chronic or acute conditions may have been excluded. Obesity, which has also been identified as a risk factor for mortality during heat waves,21 was not considered as a SCCD and thus was not included in our analysis.
A major limitation of our study was the lack of data on the treatment administered to these patients during the study period. It is well known that patients in nursing homes often have multiple conditions and receive several medications.22,23 Because of the prevalence of cardiac insufficiency and behavioral or psychiatric disorders in this population, it is highly likely that these patients were receiving medications such as diuretics or phenothiazines that have been associated with high MRs during heat waves.24,25 Finally, we did not take into account building architecture (shutters, air conditioning and elevated floors) which is also known to have a significant impact on the risk of death during extreme weather conditions.26,27
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Conclusion |
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TOPIntroductionMethodsResultsDiscussionLimitations of this studyConclusionAuthor contributionsAppendix: List of severe...AcknowledgementsReferences |
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Our findings show a marked increase in the risk of death for all patients in nursing homes. Mortality increase during the heat wave was reduced in patients with dementia and with severe chronic conditions through targeted interventions in the most vulnerable patients at risk of dehydration and other deleterious effects of extreme heat. This resulted in an apparent more important mortality increase among the less disabled patients. On top of essential measures to prevent excess mortality during further heat waves such as architectural renovations and the installation of air-conditioning,7,8,28 it seems of prime importance to establish careful routine monitoring of all patients as well as those who are physiologically stable or than the most frail. The same considerations should also be envisaged in general populations.
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Author contributions |
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TOPIntroductionMethodsResultsDiscussionLimitations of this studyConclusionAuthor contributionsAppendix: List of severe...AcknowledgementsReferences |
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Josiane Holstein collected data, helped to analyse the data and coordinated the study. She wrote the paper jointly with Florence Canouï-Poitrine and Alfred Spira. Florence Canouï-Poitrine performed the literature search and helped to analyse the data. She wrote the paper jointly with Josiane Holstein and Alfred Spira. Anke Neumann performed the data analysis. She revised the various drafts of the paper. Eric Lepage contributed to the data analysis. He revised the various drafts of the paper. Alfred Spira had the original idea and helped to analyse the data. He wrote the paper jointly with Josiane Holstein and Florence Canouï-Poitrine.
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Appendix: List of severe and/or complex conditions |
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Acknowledgements |
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TOPIntroductionMethodsResultsDiscussionLimitations of this studyConclusionAuthor contributionsAppendix: List of severe...AcknowledgementsReferences |
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The authors thank the staffs of all the AP-HP long-term care units and the personnel at Meteo France for their help in providing data.
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References |
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