Snow avalanche deaths in Switzerland from 1995 to 2014-Results of a nation-wide linkage study.

OBJECTIVES: More than 20 people die each year in snow avalanches in Switzerland. Previous studies have primarily described these victims, but were not population based. We investigated sociodemographic factors for avalanche mortality between 1995 and 2014 in the entire Swiss resident population. DESIGN AND METHODS: Within the Swiss National Cohort we ascertained avalanche deaths by anonymous data linkage with the avalanche accident database at the Swiss WSL Institute of Snow and Avalanche Research SLF. We calculated incidence rates, by dividing the number of deaths from avalanches by the number of person-years, and hazard ratios (HRs) for sociodemographic and economic characteristics using Cox proportional hazard models.
RESULTS: The data linkage yielded 250 deaths from avalanche within the SNC population for the 20 years 1995 to 2014. The median distance between the place of residence and the place of the event (avalanche) was 61.1 km. Male gender, younger age (15-45 years), Swiss nationality, living in the Alpine regions, higher education, living in the highest socioeconomic quintile of neighbourhoods, being single, and living in a household with one or more children were associated with higher avalanche mortality rates. Furthermore, for younger persons (<40 years) the hazard of dying in an avalanche between 2005 and 2014 was significantly lower than in the years 1995 to 2004 (HR = 0.56, 95%-CI: 0.36-0.85).
CONCLUSION: Over a 20-year period in Switzerland, higher rates of dying in an avalanche were observed in men, in younger age groups, and persons with tertiary education, living in the highest socioeconomic quintile of neighbourhoods, and living in an Alpine region. For younger persons (<40 years), the hazard declined during the study period.

Introduction

Snow avalanches claim the lives of about 100 people each year in the European Alps [1]. About one-quarter of these deaths occur in Switzerland, where at least 200 persons are caught annually by more than 100 avalanches [2]. More than 90% of the victims lose their lives during recreational activities away from avalanche-secured areas [2]. A large proportion of deaths occur in the cantons of Valais and Grisons, which are known for ski touring and can have an unfavourable snowpack structure that might lead to more accidental avalanches [3]. In recent decades, substantial efforts have been devoted to preventing avalanche deaths, by increasing avalanche awareness and by use of specialised rescue equipment, including avalanche transceivers and airbag-systems [4-7].

Avalanche victims are typically characterized in accident statistics by age and gender, sometimes by nationality, and rarely by region of residence [8-10]. However, more detailed sociodemographic information about avalanche victims may help direct prevention programs to specific risk groups. Most studies of accident events do not look in detail at the at-risk or source groups. Approaches to consider these include extracting usage statistics from heli-ski logs, national park registrations, social media platforms, representative population surveys, or simply by counting people [11-14].

The Swiss National Cohort (SNC) is a cohort study of the entire Swiss-resident population that has allowed investigating cause-specific mortality rates [15,16]. We linked SNC death information with reported avalanche accidents to investigate whether the mortality rates for dying in an avalanche differ by sociodemographic factors and the relationship between place of residence and location of accident.

Data and methods

WSL Institute for Snow and Avalanche Research SLF (SLF)

The SLF documents deaths caused by snow avalanches, excluding deaths due to falling ice and snow sliding off buildings. Avalanches are reported by a dense network of observers and by rescue services, and may also be reported by cantonal authorities and members of the general public. Additionally, for accidents resulting in deaths, detailed police investigation reports are generally available [17].

Data for all victims of avalanches between 1 January 1995 and 31 December 2014 were retrieved from SLF’s database including information about cause of death, date of the avalanche accident, gender, year of birth, canton/country of residence, and nationality. The activity of the accident party at the time of the avalanche event also was extracted. Within this last group, we differentiated backcountry touring activities on skis or snowshoes from off-piste riding in unsecured terrain close to ski areas, based on the often detailed police investigation and rescue reports.

Due to incomplete data on nationality, canton/country of residence, year of birth, and gender, it was not always possible to distinguish between victims who were Swiss, foreigners living in Switzerland, and foreigners from abroad.

Swiss National Cohort

The SNC is a longitudinal study of mortality in Switzerland containing sociodemographic and economic information for the entire population of Switzerland. Owing to the lack of a unique person identifier, census data from 1990 and 2000 were linked to death or migration records using deterministic and probabilistic linkage methods based on sex, date of birth, place of residence, nationality, marital status, religion, and profession. From 2010 onwards, the census is performed yearly, data are registry-based, and information from different registries can be linked via a unique person identifier. The SNC database follows mortality and migration up to 2014. More information about the SNC is given elsewhere [15,16,18].

Ethical approval and consent to participate

Approval for the Swiss National Cohort study and a data center established at ISPM Bern was obtained from the Ethics Committees of the Cantons of Zurich and Bern. For this type of study, formal consent is not required. SNC and SLF data were fully anonymized.

SLF and SNC data linkage

The SLF database does not include socio-demographic data such as household type, marital status, neighbourhood index or education. Furthermore, the ICD 10 code X36 does not identify precisely just snow avalanche deaths in the SNC data. SNC data does not include type of activity when the avalanche happened. Therefore, we linked SLF and SNC data on Swiss and foreign inhabitants in Switzerland, identifying avalanche victims based on sex, year of birth, date of death/avalanche, nationality, canton of residence, and cause of death. The Swiss death certificate allows the recording of initial disease, a consecutive disease, and two concomitant diseases, which are used to determine the primary cause of death. The diseases and cause of death are coded using the International Classification of Disease, Injuries and Causes of Death, 10th revision (ICD-10).[19] ICD-10 has been used in Swiss death certificates since 1 January 1995. We restricted the study to the calendar years beginning and after 1995 in which the same ICD-10 coding was in use. The ICD-10 code X36 records a “victim of avalanche, landslip or other movement of soil”. We searched for X36 codes in all available disease or cause of death variables to identify avalanche victims, and used the variables mentioned above to link SLF avalanche victims to SNC avalanche victims. The linkage results indicated expansion of the search to include additional codes (W02, W15, W17, W77, X31, X59, and Y86; see S1 Table for explanation; see also WHO ICD-10 classification: http://apps.who.int/classifications/icd10/browse/2010/en#), and broadening the range between the day of the avalanche and the date of death (adding the days buried under snow, or 40 days) since not every avalanche victim dies immediately, or the day of finding the dead person has been recorded as the date of death. We also allowed for variation in the year of birth by ±1 year.

The characteristics of our study population were obtained at two times, in the 1990 and the 2000 census (see Fig 1 in [15]). Except for age, we assumed characteristics did not change from 1990 to 1995. Between 1990 and 2000, people could have been born, died, or migrated into or out of Switzerland. Consequently, not all persons appear again in the census 2000 and new persons have been included. We used the latest sociodemographic information available (either 1990 or 2000) and mortality information through the end of 2014. In Table 1 we present the characteristics of our study population in 1995 and 2000, and report avalanche mortality rates for the whole study period 1995–2014.

Table 1

Characteristics of the study population at 1 January 1995 and 5 December 2000 and the 250 avalanche deaths and rates per 1 million population occurring during the periods 1 January 1995 to 4 December 2000, and from 5 December 2000 to 31 December 2014.

Characteristics	Dec 1995		Dec 1995 –Nov 2000		Dec 2000		Dec 2000 –Dec 2014		Avalanche victims (overall)
	Population		Avalanche vicitims		Population		Avalanche vicitims		Crude rate per 1000000
	Freq.	Percent	Freq.	Percent	Freq.	Percent	Freq.	Percent	Rate	95% CI
Total	6516102	100.0	72	100.0	7280041	100.0	178	100.0	1.93	1.70–2.18
Sex			p<0.0000				p<0.0000
Male	3201750	49.1	65	90.3	3563896	49.0	152	85.4	3.41	2.99–3.90
Female	3314352	50.9	7	9.7	3716145	51.0	26	14.6	0.50	0.35–0.70
Age			p<0.0000				p<0.0000
<15	805966	12.4	4	5.6	1207802	16.6	19	10.7	1.67	1.25–2.23
15–24	795624	12.2	25	34.7	848718	11.7	36	20.2	4.12	3.23–5.26
25–34	1121669	17.2	14	19.4	1059796	14.6	48	27.0	2.61	2.03–3.34
35–44	1047261	16.1	10	13.9	1201443	16.5	40	22.5	1.84	1.35–2.52
45–54	961149	14.8	12	16.7	1005390	13.8	23	12.9	1.41	0.95–2.08
55–64	718497	11.0	6	8.3	808560	11.1	9	5.1	0.98	0.56–1.73
65+	1065936	16.4	1	1.4	1148332	15.8	3	1.7	0.09	0.01–0.61
Education			p<0.4352				p<0.0000
Compulsory education or less, not known	3110399	47.7	29	40.3	3149550	43.3	45	25.3	1.39	1.11–1.75
Upper secondary level education	2739930	42.0	34	47.2	2987240	41.0	81	45.5	2.06	1.72–2.47
Tertiary level education	665773	10.2	9	12.5	1143251	15.7	52	29.2	2.92	2.27–3.75
Nationality			p<0.0836				p<0.0001
Swiss	5378114	82.5	65	90.3	5779574	79.4	163	91.6	2.16	1.90–2.46
Non-Swiss	1137988	17.5	7	9.7	1500467	20.6	15	8.4	0.91	0.60–1.38
Marital status			p<0.0000				p<0.0000
Single	2817112	43.2	50	69.4	3058321	42.0	102	57.3	2.86	2.44–3.35
Married/Widowed/Divorced	3698990	56.8	22	30.6	4221720	58.0	76	42.7	1.28	1.05–1.56
Type of household			p<0.0083				p<0.0231
Single person household	1214521	18.6	10	13.9	1631727	22.4	40	22.5	1.73	1.31–2.28
Couple without children	1434958	22.0	6	8.3	1730000	23.8	26	14.6	1.02	0.72–1.44
Couple with 1 or more children	3489403	53.6	49	68.1	3531076	48.5	103	57.9	2.39	2.04–2.81
Others	377220	5.8	7	9.7	387238	5.3	9	5.1	2.66	1.63–4.34
Region			p<0.0000				p<0.0000
Swiss alpine regions
Eastern Alps	157683	2.4	1	1.4	178145	2.4	16	9.0	5.36	3.33–8.62
Southern Alps	273991	4.2	1	1.4	314240	4.3	4	2.2	0.89	0.37–2.14
Western Alps	201259	3.1	10	13.9	229701	3.2	33	18.5	10.46	7.76–14.11
Northern Alps	1030793	15.8	15	20.8	1164732	16.0	44	24.7	2.83	2.19–3.65
Swiss non-alpine regions
≤ 25km from the Northern Alps	2062229	31.6	14	19.4	2298583	31.6	33	18.5	1.14	0.86–1.52
> 25km from the Northern Alps	2790147	42.8	31	43.1	3094640	42.5	48	27.0	1.44	1.15–1.79
Urbanization			p<0.8487				p<0.0197
urban	1952189	30.0	21	29.2	2075785	28.5	50	28.1	1.94	1.54–2.45
periurban	2854920	43.8	30	41.7	3263827	44.8	65	36.5	1.63	1.33–1.99
rural	1708993	26.2	21	29.2	1940429	26.7	63	35.4	2.41	1.95–2.99
Religious affiliation			p<0.7202				p<0.0027
Protestant	2655775	40.8	32	44.4	2567354	35.3	61	34.3	1.99	1.62–2.44
Roman Catholic	3002792	46.1	33	45.8	3045762	41.8	85	47.8	2.14	1.79–2.56
No religious affiliation	487246	7.5	5	6.9	809255	11.1	26	14.6	2.19	1.54–3.12
Other/ unknown	370289	5.7	2	2.8	857670	11.8	6	3.4	0.58	0.29–1.16
Swiss neighbourhood index of SEP			p<0.0300				p<0.3644
Lowest quintile	1618864	24.8	20	27.8	1688519	23.2	45	25.3	2.17	1.70–2.77
Second quintile	1341649	20.6	11	15.3	1427617	19.6	30	16.9	1.60	1.18–2.18
Third quintile	1253474	19.2	9	12.5	1362470	18.7	25	14.0	1.39	0.99–1.94
Fourth quintile	1179493	18.1	11	15.3	1319232	18.1	31	17.4	1.76	1.30–2.38
Highest quintile	1050945	16.1	21	29.2	1190818	16.4	35	19.7	2.60	2.00–3.38
Missing	71677	1.1	0	0.0	291385	4.0	12	6.7	-	-
Language region			p<0.0218				p<0.0065
German	4728695	72.6	45	62.5	5241390	72.0	115	64.6	1.70	1.46–1.99
French	1507980	23.1	26	36.1	1718485	23.6	59	33.1	2.81	2.27–3.47
Italian	279427	4.3	1	1.4	320166	4.4	4	2.2	0.88	0.36–2.10

We calculated crude rates (CR) by dividing the number of avalanche deaths by the number of person-years (per 1 000 000). To compare individuals with different sociodemographic and economic characteristics, we fitted Cox proportional hazard models and estimated corresponding hazard ratios (HR), which express the ratios of event hazards of compared groups. Hazard can be seen as an instantaneous event rate defined as the probability of an event occurring in the next time interval, standardized by the length of that interval [20]. For the time-to-event analyses, the time at risk per person starts on 1 January 1995 or 5 December 2000 and ends on the date of loss to follow-up at 4 December 2000, migrating out of Switzerland, death, or 31 December 2014, whichever occurred first. We used individual’s age as time axis, that is, the age at which a person entered the study and the age at which the avalanche death occurred, or observation stopped. With the choice of this time axis, Cox proportional hazard regression models provide hazard ratios that are automatically age-adjusted. To account for calendar effects, we divided the time of observation into an early (1995–2004) and a later period (2005–2014). We also assessed interactions between the covariates.

We included the following sociodemographic and economic characteristics in our analyses: sex, age, education (compulsory education or less, not known; upper secondary education; tertiary level education), nationality (Swiss, non-Swiss), marital status (single, married/widowed/divorced), type of household (single-person household, couple without children, couple with one or more children, others), urbanization level of the municipality of residence (urban, periurban, rural), religious affiliation (Protestant, Roman Catholic, no religious affiliation, other/unknown), and language region (German, French, Italian). We introduced a region variable dividing Switzerland into four Alpine regions (Western, Southern, Eastern, and Northern Alps, as in Techel et al.[3]), and two regions defined by the distance to the Alps (an area within 25 km of the northern border of the Alps and an area more than 25 km away from the northern border of the Alps, see Fig 1). Finally, we used the Swiss neighbourhood index of socioeconomic position (SSEP), divided into quintiles, that has been constructed based on several variables surveyed at the censuses [21].

Fig 1

Map of Switzerland illustrating the regional variable and places of residence and of avalanche accidents.

Statistical analyses were carried out with Stata 15 (Stata Corporation, College Station, Texas, USA). We used the STROBE cohort reporting guidelines [22].

Results

Between 1995 and 2014, 439 died (range 12–34 annually) after being caught by an avalanche. Excluding 157 persons who were foreigners who lived abroad, 282 persons from the SLF database were possible linkage candidates. The flowchart in Fig 2 summarizes how we finally identified 250 avalanche victims by linking SLF records to the SNC database.

Fig 2

Flowchart illustrating the linkage process and selection of the study participants for the final analysis.

Table 1 lists characteristics of the study population at the two time points 1 January 1995 and 5 December 2000 and the 250 avalanche deaths for the two time periods from the 1 January 1995 to 4 December 2000, and from 5 December 2000 to 31 December 2014. We report overall mortality rates per 1 million person-years Most avalanche victims were overwhelmingly male, in their twenties and thirties, resided in the non-Alpine region more than 25 km from the Northern Alps, and lived in the German language region. The crude death rate for males was almost 7 times higher than that for females. Swiss citizens had a crude rate more than double that of non-Swiss residents. The geographical region with the highest death rate of 10.46 per 1 million person-years (95% CI 7.76–14.11) was the Western Alps. The crude rate for residents of the Swiss Alpine regions was 4.23 per 1 million person-years (95% CI 3.54–5.06) about 3 times higher than for residents of non-Alpine regions.

We then restricted our Cox regression analyses to 6 639 174 persons 15 years or older with information on education and available SSEP information (see Fig 2). In this restricted population, there were 215 avalanche victims. Among these 215 victims, 143 died while backcountry touring, 59 died off-piste riding, and 13 died in a building, skiing on an open ski run, or while travelling on a public transportation corridor. A sensitivity analysis excluding these 13 persons gave almost identical results.

The median linear distance between the place of residence and the place of the avalanche accident was 61.1 km, ranging from 1.2 km to 285.3 km (interquartile range 20–111.2 km). Not surprisingly, this distance was significantly larger for those living outside the Alps or in the Southern Alps (median 79–118 km) compared to those who lived in the other Alpine regions (p-value < .00001). Residents in the Eastern, Western, and Northern Alps generally died close to their place of residence (median 12–31 km), and within their Alpine region (84%, see S2 Table). Fig 1 illustrates places of residence and of avalanche accidents.

We omitted language region in the Cox regression analyses since it is highly collinear with region of residence (the Italian language region and the Southern Alps are almost identical). Because we found significant interactions between age and education, we conducted separate analyses for the younger (15–39 years) and older (40+ years) age groups.

Table 2 displays the results of the Cox analyses of the overall, younger, and older cohorts. The pronounced reduced risk for women of dying in an avalanche compared to men persisted in all three adjusted Cox models (overall HR = 0.18, 95% CI 0.12–0.26). Non-Swiss had a lower hazard than Swiss residents did in the overall analysis (HR = 0.54, 95%-CI 0.32–0.90). The hazard associated with living in one of the three Alpine regions was clearly higher in the overall analyses than living in the region more than 25 km away from the northern border of the Alps. These associations were similarly strong in the younger and older age groups.

Table 2

Results of the Cox regression analyses for dying in an avalanche for the overall, younger, and older cohorts.

Characteristics	All persons		15–39 yrs		40+ yrs
	Hazard ratio	95% CI	Hazard ratio	95% CI	Hazard ratio	95% CI
Sex		p<0.001		p<0.001		p<0.001
Male	1		1		1
Female	0.178	0.120–0.263	0.172	0.0997–0.297	0.201	0.115–0.352
Education		p = 0.274		p = 0.138		p = 0.012
Compulsory education or less, not known	1		1		1
Upper secondary level education	1.176	0.805–1.718	0.711	0.452–1.120	2.943	1.139–7.608
Tertiary level education	1.432	0.915–2.240	0.512	0.258–1.019	4.146	1.560–11.02
Nationality		p = 0.018		p = 0.051		p = 0.243
Swiss	1		1		1
Non-Swiss	0.536	0.319–0.900	0.483	0.233–1.004	0.648	0.312–1.344
Marital status		p<0.001		p<0.001		p = 0.350
Single	1		1		1
Married/Widowed/Divorced	0.419	0.279–0.627	0.182	0.0918–0.359	0.732	0.381–1.407
Type of household		p = 0.014		p = 0.482		p = 0.010
Single person household	1		1		1
Couple without children	0.937	0.581–1.511	1.506	0.817–2.777	0.637	0.301–1.347
Couple with 1 or more children	1.645	1.119–2.419	1.393	0.856–2.265	1.698	0.896–3.220
Others	1.210	0.607–2.409	1.118	0.486–2.574	1.546	0.450–5.312
Region		p<0.001		p<0.001		p<0.001
Swiss alpine regions
Eastern Alps	3.855	2.099–7.079	2.452	1.026–5.862	6.358	2.691–15.02
Southern Alps	0.631	0.195–2.044	0.620	0.146–2.632	0.638	0.084–4.815
Western Alps	9.913	6.120–16.06	7.291	3.856–13.79	14.90	7.111–31.24
Northern Alps	2.399	1.643–3.503	1.545	0.915–2.607	3.944	2.253–6.906
Swiss non-alpine regions
≤ 25km from the Northern Alps	0.852	0.579–1.253	0.618	0.364–1.052	1.237	0.697–2.195
> 25km from the Northern Alps	1		1		1
Urbanization		p = 0.739		p = 0.839		p = 0.583
urban	1		1		1
periurban	0.928	0.661–1.303	1.049	0.655–1.682	0.795	0.489–1.294
rural	1.065	0.724–1.566	1.168	0.688–1.981	0.985	0.562–1.726
Religious affiliation		p = 0.187		p = 0.163		p = 0.691
Protestant	1		1		1
Roman Catholic	0.777	0.566–1.068	0.755	0.490–1.163	0.823	0.515–1.316
No religious affiliation	0.834	0.520–1.338	0.601	0.290–1.244	1.108	0.590–2.084
Other/unknown	0.477	0.222–1.029	0.352	0.120–1.038	0.669	0.227–1.973
Swiss neighbourhood index of SEP		p<0.001		p = 0.325		p = 0.001
Lowest quintile	1		1		1
Second quintile	0.791	0.514–1.217	0.733	0.415–1.295	0.831	0.428–1.614
Third quintile	0.879	0.555–1.393	0.841	0.461–1.531	0.869	0.424–1.781
Fourth quintile	1.300	0.827–2.043	1.125	0.617–2.051	1.427	0.717–2.841
Highest quintile	2.072	1.312–3.273	1.419	0.754–2.671	2.784	1.407–5.509
Observation interval		p = 0.930		p = 0.007		p = 0.238
1995–2004	1		1		1
2005–2014	0.987	0.738–1.320	0.556	0.361–0.854	1.281	0.849–1.933

Persons 40 years or older with an upper secondary or tertiary level of education had a higher hazard of avalanche death than those with only compulsory education or less. The hazard did not seem to differ by the level of urbanization of the municipality of residence. However, in the overall analysis the hazard for persons living in neighbourhoods with an SSEP in the highest quintile was higher that of persons in neighbourhoods in the lowest quintile; the result was more pronounced in the older age group. When comparing the years 2005–2014 to 1995–2004, we found a reduced hazard in the younger cohort, but not the older, during the later period.

Discussion

Over a period of 20 years (1995–2014), the rate of dying in an avalanche was clearly lower in the 2nd decade in those younger than 40 years. We observed increased rates for males, and for persons with an education beyond the compulsory minimum level, being single, and living in a household with one or more children. With a median distance between place of death and place of residence of 61.1 km, most victims died not far from home which was reflected in a higher rate for those living in Alpine areas.

Strengths and limitations

This is the first study to analyse the risk to different groups in the Swiss population of dying in an avalanche. The ICD-10 code X36 defines not only snow avalanches but also death from landslides or other earth movements. A major strength of our study derives from our linkage of SNC and SLF data that teased out snow avalanche deaths, alone, in the SNC data. This direct linkage provided detailed socio-demographic data, such as household type, marital status, socioeconomic data or education and allowed us to connect avalanche victims' places of residence with the locations of their fatal accidents.

Among the limiting factors in this study is that some of the sociodemographic indicators that were derived at the time of each census, e.g., marital status, type of household and SSEP, may have changed. Also, due to incomplete information in the SLF database not all avalanche deaths recorded could be linked to the SNC statistics. Finally, Swiss residents may also die in avalanches outside Switzerland; this appears to be true for about 10% of all Swiss avalanche victims [11].

To strengthen prevention efforts, a better knowledge of the activity profiles of participants in these outdoor activities would be needed [8-14]. The SLF accident statistics and the SNC data are clearly limited in this regard.

Interpretation

The profile of avalanche victims in this study might primarily echo the profile of ski tourers and off-piste skiers in general. We noted that victims residing in the Alps died close to their place of residence (12–31 km distance). We could therefore speculate that this might be a typical traveling distance between place of residence and place of recreation, but also that many of these victims were likely rather familiar with that region and its specific circumstances.

Successful prevention of deaths in avalanches in Switzerland needs to be tailored to patterns of winter sport activities of the Swiss resident population. Information on these activities exists and comes from different sources, and studies conducted by the Federal Office for Sports [23-25] and the Swiss Council for Accident Prevention [26]. In recent years, the number of persons pursuing winter sports in unsecured terrain has increased [11]. Results from surveys in the year 2014 suggest that approximately 2% of the population do backcountry tours [23] and that about a quarter are riding off-piste at times when skiing in terrains accessible from ski areas [23,26]. Persons riding off-piste are more often male [23,26] and 15 to 29 years old [26], while persons undertaking ski tours and snowshoeing are generally older [23]. We observed similar patterns for avalanche mortality rates (see S3 and S4 Tables).

The median age at death of the avalanche victims in our analysis increased from 31 years in the first ten years of our study period (1995–2004: N = 123) to 42 years in the last ten years of our study period (2005–2014: N = 127). This is also reflected in the hazard for younger persons (15–39 years), which was significantly lower for the years 2005–2014 than for the years 1995–2004. Whether this is linked to an increased use of avalanche safety gear in this age group, changes in risk behaviour, or whether fewer younger people participate in these outdoor-activities, is unclear. However, similar ageing trends have also been noted for the users of the Swiss avalanche forecast, but also for avalanche victims in France [9,27].

As only a small proportion of the resident population is exposed to avalanche hazard, we suggest that contrasting the socio-economic profiles of avalanche victims with that of the population in general, is one way to explore patterns in avalanche victims’ profiles. However, as has been the case in many previous studies (e.g. [9]) the lack of knowledge concerning the true population at risk of dying in an avalanche also impacts the interpretation of our findings.

Conclusion

Over a 20 year period in Switzerland, higher rates of dying in an avalanche were observed in men, in younger age groups, and persons with tertiary education, living in the highest socioeconomic quintile of neighbourhoods, and living in an Alpine region. However, for younger persons (<40 years), the rate declined during the study period.

Additional used ICD 10 codes indicating the cause of death.

(PDF)

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Place of residence and place of avalanche of the 215 avalanche victims by region (1995–2014).

(PDF)

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Results of the Cox regression analyses for dying in an avalanche while undertaking backcountry touring on skis or snowshoes for the overall, younger, and older cohorts.

(PDF)

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Results of the Cox regression analyses for dying in an avalanche while riding off-piste for the overall, younger, and older cohorts.

(PDF)

Click here for additional data file.

STROBE cohort checklist.

(DOCX)

Click here for additional data file.

21 Aug 2019

PONE-D-19-17260

Snow avalanche deaths in Switzerland from 1995 to 2014 – results of a nation-wide linkage study

PLOS ONE

Dear Dr. Berlin,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Reviewer #1: Partly

Reviewer #2: Yes

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Reviewer #1: I Don't Know

Reviewer #2: I Don't Know

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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5. Review Comments to the Author

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Reviewer #1: This paper tackles an important topic that has been poorly investigated until now, mostly because of methods constraints and difficulties.

In order to help direct prevention towards specific risk groups, the authors intend to provide detailed sociodemographic information about avalanche victims in Switzerland: do some sociodemographic factors impact exposure to avalanche mortality?

The originality of the approach lies in the linking of 2 databases: the "Snow and Avalanche Research" (SLF) which lists deaths caused by avalanches in Switzerland; the Swiss National Cohort (SNC) which reports the broader causes of mortality in Switzerland.

The authors highlight three main results.

The most interesting one is the connection revealed between avalanche victims’ places of residence and the locations of their fatal accidents. This is an important insight that should be developed further, in terms of interpretation, for the paper to provide a significant contribution.

The second result is the rate of 2 fatalities in avalanche for 1 million swiss residents each year. This information does not fit the research's objective and does not provide helpful information in terms of prevention, since it does not make it possible to estimate the risk exposure of actual mountain sports practitioners.

The third result is a very general profile of avalanche victims: mostly (young) men, with tertiary education, a privileged economic situation, living in an Alpine region. This result is not key since this merely echoes the profile of ski tourers and off-piste skiers. In other words, the methods used led to confirm that peoppe dying in avalanches are people involved in those dangerous activities, which is tautologic.

As a consequence, linking specific data (SLF) to global ones (SNC) does not prove relevant regarding the objective stated in the introduction: basing prevention on a more detailed picture of victims socio-demographics.

In order to get their paper published, the authors should address a couple of concerns, and acknowledge some limitations of their study:

- the methodological and scientific justification of the linkage between the databases must be explained more thoroughly. What does it make possible? What does it add to SLF data, in concrete terms? Currently, it is not celar why this linkage is useful and what limitation it makes it possibe to overcome.

- in the introduction, the authors state that « none of these studies allows a direct linkage between those recreating and those becoming a victim of an avalanche ». The problem is, broadening the scope to the swiss population does not help neither. By doing so, the authors don't focus on those recreating, which is the gap they identified in the literature. It must be made clearer why it helps to turn to general population data.

According to prevention experts, what is needed to enhance prevention is less a comparison with general population, than a better knowledge of the plural profiles of participants in the dangerous activities.

Beyond this central remark, some minor issues (easier to address) can be pointed out:

- the methods used by SLF to gather information regarding avalanches and avalanche victims must be precised. It will make it easier to understand if the data are precise and exhaustive. A better knowledge of such criteria would also help to understand the facts that are included or excluded in the data base

- what does « to be caught in an avalanche » mean? There are many envisageable outputs while an avalanche occurs: being swept away in the avalanche, and/or being buried in snow, and/or getting injured in tha avalanche, and/or being rescued (by specialized rescuers or members of the group), etc. This point is all the most crucial to address since it is further stated that 10% of the population that gets « caught » dies because of the avalanche. More precision is needed here.

- The authors write that « the activity of the accident party at the time of the avalanche event also was extracted » : is it always possible to identify the activity in question ? Especially when differentiating between off-piste skiing and ski touring: can we be positive on this distinction? What is it based on?

- « Persons voluntarily expose themselves to avalanche risk » : it seems more appropriate to replace voluntarily by knowingly

- Regarding the ICD-10 code X36: sometimes, while reporting the cause of deaths, physicians only use generic physiological terms. How can we be sure that this seemingly precise codification is properly used?

- « We speculate that persons with higher education, which often goes along with higher socioeconomic status and higher income, have more resources for leisure activities like ski-touring » : it seems simplistic to link a priviledged position, on an economical plan, and involvement in ski touring. The diffusion of this technical, distinctive activity is also, not to say mostly, a social and cultural process

- Some data from Switzerland or France highlight that over time, people dying in avalanche are older and older (from 37 to 42 for example, in France, in 25 or 30 years). This is a point that should be mentioned in the paper

- Last, avalanche safety equipment should be quantified; the reader actually needs a figure of equipment rate, and type of equipment. By the way, it seems that avalanche airbags are more commonly used in Switzerland than in Italy or France

Reviewer #2: This paper presents the most comprehensive review of Swiss avalanche fatality statistics to date and provides details of sociodemographic status and place of residence not previously reported. Additionally, larger trends of reduced fatalities in younger age groups over time is demonstrated raising some hope that avalanche safety technology and education may be successful.

The statistical analysis is complex and difficult to follow as currently written in the methods and results and clarification is needed. That being said, the discussion and conclusions follow logically from the stated objectives and the overall paper adds to the knowledge base regarding avalanche fatalities in Switzerland.

Line:

47- “still, 10%...die” needs reference.

72- Data regarding cause of avalanche death, time of burial, not relevant to study objective. Not reported in results or discussion. Eliminate.

76- One could argue that any skiing in mountainous terrain, “avalanche-secured” or otherwise, is a voluntary exposure to avalanches. Skiing is clearly a different exposure than occupying buildings or moving through transportation corridors. Your project does not address risk taking behavior specifically and voluntary/involuntary distinction as you describe does not change results. Would remove or re-word the voluntary/involuntary definitions.

91- add comma after nationality

96- SLF and SNC data linkage-

The statistical analysis and linkage is complex but the description of how and why two cohorts were developed (as shown in figure 2) does not follow from the methods. Was the 1995 census data extrapolated directly from the 1990 census? Why were two cohorts, 1990-2014 and 1995-2014, chosen? It seems that there is a significant overlap between the two cohorts. One would think that the Swiss population between 1990-2014, understanding influences from deaths and migration, is a single cohort. Overall the methods section needs to be clarified and the explanation simplified in regards to the time periods evaluated and then carried over with consistent time periods to the results.

108- would like to see a few examples of the expanded ICD9 codes.

142- “two regions defined by distance from the Alps…” Using the <=>25 km distinction adds little to the demographic data as you found a median distance of 61 km from residence to place of death and described victims as predominantly from an Alpine region. This would suggest that all of Switzerland is an Alpine region, which may be true. The 25 km measure offers little useful detail beyond just place of residence and location of death.

159- Table 1. Two time periods 1/1/1995-2000 and 5/12/1995-2014 are given but it is not clear why or how these two periods were chosen. See above for line 96, there is a lack of clarity on how cohorts and time periods were determined. You also list “time periods” in line 160 then report in line 172-3 “two points in time”, both for same table. This is confusing.

**********

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Reviewer #1: No

Reviewer #2: No

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4 Oct 2019

Revision letter

We would like to thank both reviewers for their thoughtful comments to our manuscript.

Please find a point by point discussion below.

Reviewer 1:

1) This paper tackles an important topic that has been poorly investigated until now, mostly because of methods constraints and difficulties.

In order to help direct prevention towards specific risk groups, the authors intend to provide detailed sociodemographic information about avalanche victims in Switzerland: do some sociodemographic factors impact exposure to avalanche mortality?

The originality of the approach lies in the linking of 2 databases: the "Snow and Avalanche Research" (SLF) which lists deaths caused by avalanches in Switzerland; the Swiss National Cohort (SNC) which reports the broader causes of mortality in Switzerland.

Authors` response: Thank you!

2) The authors highlight three main results.

The most interesting one is the connection revealed between avalanche victims’ places of residence and the locations of their fatal accidents. This is an important insight that should be developed further, in terms of interpretation, for the paper to provide a significant contribution.

Authors` response: We have added the following statement to the Discussion section (page 14):

« The profile of avalanche victims in this study might primarily echo the profile of ski tourers and off-piste skiers in general. We noted that victims residing in the Alps died close to their place of residence (12 – 31 km distance). We could therefore speculate that this might be a typical traveling distance between place of residence and place of recreation, but also that many of these victims were likely rather familiar with that region and its specific circumstances.«

The second result is the rate of 2 fatalities in avalanche for 1 million swiss residents each year. This information does not fit the research's objective and does not provide helpful information in terms of prevention, since it does not make it possible to estimate the risk exposure of actual mountain sports practitioners.

Authors` response: This information has been deleted in the Abstract, as well as in the manuscript (Results section, page 9 and Discussion section, page 13).

The third result is a very general profile of avalanche victims: mostly (young) men, with tertiary education, a privileged economic situation, living in an Alpine region. This result is not key since this merely echoes the profile of ski tourers and off-piste skiers. In other words, the methods used led to confirm that peoppe dying in avalanches are people involved in those dangerous activities, which is tautologic.

As a consequence, linking specific data (SLF) to global ones (SNC) does not prove relevant regarding the objective stated in the introduction: basing prevention on a more detailed picture of victims socio-demographics.

Authors` response: The authors agree that the profile of avalanche victims in this study might echo the profile of ski tourers and off-piste skiers in general. However, this has not been investigated by a population-based study before. Furthermore, previous studies do not provide detailed socio-demographic data, such as household type, marital status, neighbourhood index or education.

The following statement has been added to the Discussion section (page 13):

«This direct linkage provided detailed socio-demographic data, such as household type, marital status, socioeconomic data or education and allowed us to connect avalanche victims' places of residence with the locations of their fatal accidents.«

And on page 14:

«The profile of avalanche victims in this study might echo the profile of ski tourers and off-piste skiers in general.«

3) In order to get their paper published, the authors should address a couple of concerns, and acknowledge some limitations of their study:

- The methodological and scientific justification of the linkage between the databases must be explained more thoroughly. What does it make possible? What does it add to SLF data, in concrete terms? Currently, it is not celar why this linkage is useful and what limitation it makes it possibe to overcome.

Authors` response: The SLF database just record avalanche deaths and accidents but does not include socio-demographic data such as household type, marital status, neighbourhood index or education. Furthermore, the ICD 10 code X36 does not identify precisely just snow avalanche deaths in the SNC data. SNC data does not include type of activity when the avalanche happened. Therefore, the data linkage has been performed.

The following statement has been added to the Methods section (page 6):

« The SLF database does not include socio-demographic data such as household type, marital status, neighbourhood index or education. Furthermore, the ICD 10 code X36 does not identify precisely just snow avalanche deaths in the SNC data. SNC data does not include type of activity when the avalanche happened. Therefore, we linked SLF recorded deaths and SNC data […]«

- in the introduction, the authors state that « none of these studies allows a direct linkage between those recreating and those becoming a victim of an avalanche ». The problem is, broadening the scope to the swiss population does not help neither. By doing so, the authors don't focus on those recreating, which is the gap they identified in the literature. It must be made clearer why it helps to turn to general population data.

Authors` response: This sentence has been deleted from the Introduction section (page 3). Please, also see our statement to your previous comment.

4) According to prevention experts, what is needed to enhance prevention is less a comparison with general population, than a better knowledge of the plural profiles of participants in the dangerous activities.

Authors` response: The following statement has been added to the Discussion section (page 13):

« To strengthen prevention efforts, a better knowledge of the activity profiles of participants in these outdoor activities would be needed (8–10,19–22). The SLF accident statistics and the SNC data are clearly limited in this regard.«

5) Beyond this central remark, some minor issues (easier to address) can be pointed out:

- the methods used by SLF to gather information regarding avalanches and avalanche victims must be precised. It will make it easier to understand if the data are precise and exhaustive. A better knowledge of such criteria would also help to understand the facts that are included or excluded in the data base

Authors` response: We explain the reporting system of the SLF at the beginning of data and methods (starting in line 77). SLF’s avalanche accident database is cross-checked annually for missing accidents or details with the mountain accident statistic by the Swiss Alpine Club. The latter receives the incidence reports of all the accidents, when the alpine rescue services were on site and therefore has a rather complete database. The number of variables describing avalanche accidents in SLF’s database is large, though the information is often incomplete. However, accidents resulting in fatalities are generally well documented. Variables, which were relevant for this study, have been listed. We added the following statement to the data description on page 5.

“Additionally, for accidents resulting in deaths, detailed police investigation reports are generally available (13).”

6) what does « to be caught in an avalanche » mean? There are many envisageable outputs while an avalanche occurs: being swept away in the avalanche, and/or being buried in snow, and/or getting injured in tha avalanche, and/or being rescued (by specialized rescuers or members of the group), etc. This point is all the most crucial to address since it is further stated that 10% of the population that gets « caught » dies because of the avalanche. More precision is needed here.

Authors’ response: As “caught in an avalanche” counts when a person is swept away by an avalanche (the person can’t ski or snowboard in a controlled way out of the avalanche). As a result, the person is either partially or fully buried, or remains on the snow surface. As “caught” counts also when a vehicle or train is hit by an avalanche and there are people inside. - It is of note, that an unknown number of less severe avalanche incidents go unreported. Therefore the 10% is an upper limit and reflects the known proportion of the people who were caught in avalanches. The most recent numbers, always for 20 years, are shown in a table published in the annual report by SLF (e.g. Zweifel et al., 2016). We have removed the 10% from the abstract and introduction, and rephrased accordingly.

7) The authors write that « the activity of the accident party at the time of the avalanche event also was extracted » : is it always possible to identify the activity in question ? Especially when differentiating between off-piste skiing and ski touring: can we be positive on this distinction? What is it based on?

Authors` response: The activity of the accident party is based on information of the SLF database. The key criteria for this distinction are whether the accident party accessed the backcountry from ski areas ascending by means of ski lifts or cable cars with only short additional hikes, or whether they ascended primarily by hiking up. For fatal accidents SLF has rather detailed police investigation reports available, generally allowing this distinction. We added the following statement in the respective section (page 5):

“Within this last group, we differentiated backcountry touring activities on skis or snowshoes from off-piste riding in unsecured terrain close to ski areas, based on the often detailed police investigation and rescue reports.”

8) « Persons voluntarily expose themselves to avalanche risk » : it seems more appropriate to replace voluntarily by knowingly

Authors` response: Thank you for this comment. This part has been completely removed from the Methods section (page 5). See also comment 5, Reviewer 2.

9) Regarding the ICD-10 code X36: sometimes, while reporting the cause of deaths, physicians only use generic physiological terms. How can we be sure that this seemingly precise codification is properly used?

Authors` response: You are right. The X36 code can also be used for non-avalanche victims as we pointed out on page 5. The linkage of the SNC and SLF databases has also been performed to identify just snow avalanche victims. Only victims, who could be linked / identified as avalanche victims, were included in the analysis.

10) «We speculate that persons with higher education, which often goes along with higher socioeconomic status and higher income, have more resources for leisure activities like ski-touring » : it seems simplistic to link a priviledged position, on an economical plan, and involvement in ski touring. The diffusion of this technical, distinctive activity is also, not to say mostly, a social and cultural process

Authors` response: We deleted this sentence (page 14).

11) Some data from Switzerland or France highlight that over time, people dying in avalanche are older and older (from 37 to 42 for example, in France, in 25 or 30 years). This is a point that should be mentioned in the paper

Authors` response: Thank you for this comment. We checked whether this is true for the 250 avalanche victims we analyzed. The median age at death for the 123 persons died between 1995 – 2004 is 31 years and the median age for the 127 persons died between 2005 – 2014 increased to 42 years. We agree that over the last decades, avalanche victims are getting older and older. This information has been added to the Discussion section (page 15). We also reference two studies, who observed similar trends.

“The median age at death of the avalanche victims in our analysis increased from 31 years in the first ten years of our study period (1995-2004: N=123) to 42 years in the last ten years of our study period (2005-2014: N=127). This is also reflected in the hazard for younger persons (15-39 years), which was significantly lower for the years 2005-2014 than for the years 1995-2004. Whether this is linked to an increased use of avalanche safety gear in this age group, changes in risk behaviour, or whether fewer younger people participate in these outdoor-activities, is unclear. However, similar ageing trends have also been noted for the users of the Swiss avalanche forecast, but also for avalanche victims in France (9,27).”

12) Last, avalanche safety equipment should be quantified; the reader actually needs a figure of equipment rate, and type of equipment. By the way, it seems that avalanche airbags are more commonly used in Switzerland than in Italy or France.

Authors` response: Unfortunately, we were not able to find exact information about changes in equipment use. Some newspaper articles emphasize increased availability and sales for ski touring equipment, and mainly avalanche airbags since 2010.

Reviewer 2:

1) This paper presents the most comprehensive review of Swiss avalanche fatality statistics to date and provides details of sociodemographic status and place of residence not previously reported. Additionally, larger trends of reduced fatalities in younger age groups over time is demonstrated raising some hope that avalanche safety technology and education may be successful.

Authors` response: Thank you!

2) The statistical analysis is complex and difficult to follow as currently written in the methods and results and clarification is needed. That beeing said, the discussion and conclusions follow logically from the stated objectives and the overall paper adds to the knowledge base regarding avalanche fatalities in Switzerland.

Authors` response: The statistical analysis is a standard time-to-event analysis in a cohort study. However, the situation is somewhat complicated by the fact that the SNC is not a closed cohort but based on 2 census rounds, one in 1990 and 2000 with “new” persons entering the cohort in 2000. We discuss this in more detail in our response to point 7) of reviewer 2.

3) Line: 47- “still, 10%...die” needs reference.

Authors’ response: We removed the 10% statement. It is based on the annual reports by SLF. These reports state, however, that particularly concerning less severe accidents, there is an unknown number of unreported cases.

4) 72- Data regarding cause of avalanche death, time of burial, not relevant to study objective. Not reported in results or discussion. Eliminate.

Authors` response: This information has been deleted in the Methods section (page 4).

5) 76- One could argue that any skiing in mountainous terrain, “avalanche-secured” or otherwise, is a voluntary exposure to avalanches. Skiing is clearly a different exposure than occupying buildings or moving through transportation corridors. Your project does not address risk taking behavior specifically and voluntary/involuntary distinction as you describe does not change results. Would remove or re-word the voluntary/involuntary definitions.

Authors` response: Thank you. This part has been removed from the manuscript (Methods section, page 5).

6) 91- add comma after nationality

Authors` response: Thank you. This has been added.

7) 96- SLF and SNC data linkage-

The statistical analysis and linkage is complex but the description of how and why two cohorts were developed (as shown in figure 2) does not follow from the methods. Was the 1995 census data extrapolated directly from the 1990 census? Why were two cohorts, 1990-2014 and 1995-2014, chosen? It seems that there is a significant overlap between the two cohorts. One would think that the Swiss population between 1990-2014, understanding influences from deaths and migration, is a single cohort. Overall the methods section needs to be clarified and the explanation simplified in regards to the time periods evaluated and then carried over with consistent time periods to the results.

Authors` response: Thank you for this comment. The SNC is a cohort study, which, at each of the censuses, includes new persons not seen in the previous census. The starting census was in 1990 with 6.8 Mio persons and the census in 2000 was based on 7.3 Mio persons (see cohort profile 2009). The SNC population was then followed for mortality until 2014 (including cause of death information, ICD 10 codes). Therefore we splitted the follow-up time into two time periods before and after 2000 to accommodate the new persons from the 2000 census.

The reason to start follow-up in 1995 was the fact that ICD 10 codes have been introduced in Switzerland in 1995 to code diseases or accidents on the death certificates. Before 1995, ICD 8 codes have been used and it is even more difficult to identify snow avalanche victims using ICD 8 codes. Consequently, we report in table 1 in column “1995” the socio-demographic data of the census 1990 and the people still alive in 1995.

We do report the data of both censuses to show how the cohort/population characteristics have changed and how the cohort grew over time.

8) 108- would like to see a few examples of the expanded ICD9 codes.

Authors` response: We report the additional ICD 10 codes (besides ICD 10 codes X36: victim of avalanche, landslip or other movement of soil), which we used for the linkage of SNC and SLF data bases in the supplement (see table S1).

9) 142- “two regions defined by distance from the Alps…” Using the <=>25 km distinction adds little to the demographic data as you found a median distance of 61 km from residence to place of death and described victims as predominantly from an Alpine region. This would suggest that all of Switzerland is an Alpine region, which may be true. The 25 km measure offers little useful detail beyond just place of residence and location of death.

Authors` response: Another advantage of the linkage of the SNC and the SLF databases is that we now have information of the place of residence and the exact place of the avalanche for all avalanche victims. On page 7, line 146-149 we introduced the geographical areas, which we used to zone Switzerland. We used a commonly used division of the Alps into four Alpine regions and divided the area North of the Alps (which is not part of the Alps) into 2 areas according to the distance from the North border of the Alps. The majority of the Swiss population (around three quarters, see table 1 in the manuscript) is living in these two areas because most of the settlements are located there. Compared to that around half of the avalanche victims lived in the two non-Alpine regions and the other half in the Alpine regions. The 25 km distance from the Northern border of the Alps was an arbitrary choice to divide the non-Alpine region into 2 areas. 25 km seemed to be a proximity for reaching the Alps within a reasonable time for frequent leisure activities in the Alps. We intended to compare Alpine areas, areas close to the Alps and areas further away from the Alps concerning where the avalanche victims came from.

10) 159- Table 1. Two time periods 1/1/1995-2000 and 5/12/1995-2014 are given but it is not clear why or how these two periods were chosen. See above for line 96, there is a lack of clarity on how cohorts and time periods were determined. You also list “time periods” in line 160 then report in line 172-3 “two points in time”, both for same table. This is confusing.

Authors` response: We agree that this is confusing. We clarified this in the text and in the table description and column description (see page 9).

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12 Nov 2019

Snow avalanche deaths in Switzerland from 1995 to 2014 – results of a nation-wide linkage study

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21 Nov 2019

PONE-D-19-17260R1

Snow avalanche deaths in Switzerland from 1995 to 2014 – results of a nation-wide linkage study

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