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E-bikers are more often seriously injured in bicycle accidents: results from the Groningen bicycle accident database

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Abstract

Objective: Analysing injury types, injury severity and mortality in victims of accidents with electric bicycles in comparison with conventional bicycles. Design: Prospective cohort study. Method: Data of patients treated at the Accident & Emergency Department of the University Medical Center Groningen after a bicycle accident are being entered in a database since 2014. We have analysed this database for accidents with electric bicycles (e-bikes) and conventional bicycles occurring among adult patients for the period of July 2014 to May 2016. 'Propensity score matching' was used to match e-bikers to conventional cyclists, based on age, gender and the presence of comorbidities. Results: 107 of the 475 included victims were riding an e-bike. Average age of e-bikers and conventional cyclists was 65 years and 39 years respectively. Comorbidity was more common in e-bikers. E-bikers were injured significantly more severely than conventional cyclists. They had more severe injuries of the head and face, and upper and lower extremities. E-bikers were also admitted to the hospital more often, and for longer periods, and they underwent surgery more often. Mortality was the same. Propensity score matching revealed that e-bikers had multiple severe injuries (ISS > 15) twice as often as conventional cyclists, that they had more severe head injuries and were admitted for longer periods than conventional cyclists. Conclusion: E-bikers who had a bicycle accident had more severe injuries, more frequently had multiple injuries and had more severe head injuries than conventional cyclists. This resulted in a greater need for care. Preventive measures such as riding lessons and helmet use should be encouraged. Care providers should pay extra attention to the possibility of severe injuries when a patient had a bicycle accident with an e-bike.
NED TIJDSCHR GENEESKD. 2017;161: D1520
ONDERZOEK
Fietsen is een onderdeel van de Nederlandse cultuur. Er
zijn, met , miljoen, meer fietsen dan inwoners in
Nederland. Ongeveer  van alle verplaatsingen in
Nederland gebeurt per fiets en de Nederlander fietst
gemiddeld , km per dag. In ons buurland Duitsland
bedraagt dat gemiddelde slechts , km per dag.- De
verkoop van de elektrische fiets (e-bike) is de laatste jaren
enorm toegenomen. Momenteel zijn er al meer dan
, miljoen e-bikes verkocht, met name aan oudere ver-
keersdeelnemers. Van deze ‘e-bikers’ is  ouder dan
 jaar. De meest verkochte e-bike, formeel pedelec
geheten, is een fiets met elektrische hulpmotor die
trapondersteuning geeft tot  km/h. E-bikers fietsen
gemiddeld rond de  km per week; dit is meer dan het
totale gemiddelde van , km per dag.
Fietsen is gezond en goed voor het milieu, en het gebruik
van de e-bike kan hieraan bijdragen. Steeds vaker wordt
de e-bike ingezet door forensen en blijft de auto staan.
De fietser is echter een kwetsbare verkeersdeelnemer. In
Nederland zijn er jaarlijks rond de . bezoeken aan
de SEH en  doden naar aanleiding van een fietsonge-
val. Het aantal verkeersdoden door een auto-ongeval is
de laatste jaren afgenomen, maar het aantal fietsdoden is
al jaren stabiel en daalt niet. Het toenemende gebruik
DOEL Analyseren van het soort letsel, de letselerns t en de mortaliteit onder slachtof fers van een ongeval met een elek tri-
sche fiets vergeleken met een klassieke fiets.
OPZET Prospectief cohortonderzoek.
METHODE Sinds 2014 worden gegevens van patiënten die zijn behandeld na een fietsongeval op de SEH van het Universitair
Medisch Centrum Groningen geregistreerd in een database. Wij analyseerden gegevens uit deze database over de
ongevallen met een elektrische f iets (e-bike) of klassieke fiets die plaatsvonden bij volwassen patiënten in de peri-
ode juli 2014-mei 2016. Met ‘propensity score matching’ werden e-bikers gematcht met klassieke fietsers op basis
van leeftijd, geslacht en aanwezigheid van comorbiditeit.
RESULTATEN Van de 475 geïncludeerde slachtoffers bereden er 107 een e-bike. De gemiddelde leeftijd van e-bikers en klassieke
fietsers was respectievelijk 65 en 39 jaar; e-bikers hadden vaker comorbiditeit. De e-bikers raakten significant ern-
stiger gewond dan klassieke fietsers, zij hadden ernstiger schedel-hersenletsel en ernstiger letsel van het gezicht,
de bovenste en onderste extremiteit. Tevens werden e-bikers vaker en langer opgenomen in het ziekenhuis en
vaker geopereerd. De mortaliteit was gelijk. Na propensity-scorematching bleek dat e-bikers 2 maal zo vaak meer-
voudig ernstig gewond waren geraakt, ernstiger schedel-hersenletsel hadden opgelopen en langer waren opgeno-
men als klassieke fietsers.
CONCLUSIE E-bikers raken bij een fietsongeval ernstiger en vaker meervoudig gewond en hebben ernstiger schedel- hersenletsel
dan klassieke fietsers. Dit resulteert in een grotere zorgbehoefte. Preventieve maatregelen, zoals rijlessen en
helmgebruik, moeten daarom gestimuleerd worden. Zorgverleners dienen extra bedacht te zijn op ernstigere let-
sels wanneer een patiënt een fietsongeval met een e-bike heeft gehad.
Universitair Medisch Centrum Groningen, afd. Traumachirurgie,
Groningen.
Drs. H.P.A.M . Poos, drs. J.S . Harbers en dr. K.W. Wendt,
trauma chirurgen; drs . T.L. Lefarth, arts-onderz oeker (tevens: aios
traumachirurgie, Evangelisches Krankenhaus Oldenburg,
Oldenburg, Duitsland); dr. M. El Moumni, traumachirurg en
klinisch epidemi oloog ; dr. I.H.F. Reininga, klinisch e pidemioloog en
senior onderzoeker (tevens: onderzoekscoördinator, Acute
Zorgnetwerk Noord-Nederland, Groningen).
Contactpersoon: drs. H.P.A.M. Poos (h.poos@umcg.nl).
E-bikers raken vaker ernstig gewond na fietsongeval
RESULTATEN UIT DE GRONINGSE FIETSONGEVALLENDATABASE
H.P.A.M. (Jeroen) Poos, Tim L. Lefarth, Jorrit S. Harbers, Klaus W. Wendt, Mostafa El Moumni en Inge H.F. Reininga
NED TIJDSCHR GENEESKD. 2017;161: D1520
ONDERZOEK
van e-bikes en de vergrijzing dragen hier mogelijk aan bij.
In het Universitair Medisch Centrum Groningen
(UMCG) worden sinds juli  alle fietsongevallen
waarvoor mensen op de SEH zijn behandeld, gedocu-
menteerd in een database. Het doel van de huidige studie
was het letselpatroon, de ernst van de letsels en de mor-
taliteit in kaart te brengen van slachtoffers na een fiets-
ongeval. Hierbij vergeleken wij e-bikers met de klassieke
fietsers.
METHODE
PATIËNTEN
Uit de UMCG-database werden alle patiënten van  jaar
of ouder geselecteerd die in de periode juli -mei 
op de SEH van het UMCG waren behandeld na een onge-
val met een e-bike of klassieke fiets. Alleen pedelecs
(maximale snelheid:  km/h) en klassieke fietsen werden
geanalyseerd; andere type fietsen, zoals de zogenoemde
UITLEG
Eenzijdig ongeval en botsing
Bij een eenzijdig ongeval is alleen de verkeersdeelnemer zelf
betrokken, bijvoorbeeld bij een val van een fiets door plotse-
ling remmen, gladheid of bij op- en afstappen. Wij spreken van
een botsing wanneer  of meer fietsers, andere verkeersdeel-
nemers, dieren of objecten (zoals een lantaarnpaal of verkeers-
bord) bij het ongeva l betrokken zijn.
TABEL 1 Patiëntkenmerken, letselernst, type letsel, opnamegegevens en mortaliteit na een ongeval met een e-bike of klassieke fiets
kenmerk e-bike
(n = 107)
klassieke fiets
(n = 368)
p-waarde
leeftijd in jaren; gemiddelde (SD) 65,4 (12,3) 39,2 (19,4) < 0,001
mannelijk geslacht; n (%) 45 (42) 173 (47) 0,37
comorbiditeit aanwezig; n (%)* 86 (80) 135 (37) < 0,001
helm gedragen; n (%) 1 (0) 0 (0) 0,23
eenzijdig ongeval; n (%) 62 (58) 223 (61)† 0,56
botsing; n (%) 45 (42) 142 (39)† 0,56
ISS; mediaan (uitersten) 6 (0-38) 3 (0-41) < 0,001
meervoudig ernstig letsel; n (%)‡ 24 (22) 24 (7) < 0,001
AIS-regio; gemiddelde (SD)
hoofd 3,0 (1,3) 2,2 (1,1) < 0,001
gezicht 1,5 (0,5) 1,2 (0,5) 0,02
nek§ 1,0 1,0 (0,0) 1,00
thorax 2,4 (1,4) 1,7 (1,0) 0,06
abdomen 2,0 (0,7) 1,3 (0,6) 0,06
wervelkolom 2,4 (0,5) 2,3 (0,7) 0,61
bovenste extremiteit 2,0 (0,8) 1,5 (0,6) < 0,001
onderste extremiteit 1,8 (0,8) 1,4 (0,7) 0,01
opname; n (%) 53 (50) 96 (26) < 0,001
opnameduur in dagen; mediaan (uitersten) 6 (1-51) 2 (1-29) < 0,001
IC-opname; n (%) 18 (17) 16 (4) < 0,001
IC-opnameduur in dagen; mediaan (uitersten) 6 (1-34) 2 (1-29) < 0,001
operatie; n (%) 27 (25) 34 (9) < 0,001
mortaliteit binnen 30 dagen; n (%) 4 (4) 6 (2) 0,24
AIS = ‘Abbreviated injury scale’; ISS = ‘Injury severity score’.
Bij statistisch significante verschillen tussen berijders van e-bikes en klassieke fietsen zijn de waarden rood afgedrukt.
* Comorbiditeit: cardiale, pulmonale, neurologische, musculoskeletale of endocriene ziekten.
† Van 14 patiënten ontbrak informatie.
‡ Van meervoudig letsel is sprake bij een ISS-score > 15.
§ Er was 1 e-biker met nekletsel (geen SD); van alle 12 klassieke fietsers met nekletsel was de AIS-score 1.
NED TIJDSCHR GENEESKD. 2017;161: D1520
ONDERZOEK
speedbikes (maximale snelheid:  km/h), racefietsen en
mountainbikes, werden niet meegenomen.
In de analyse gebruikten wij de volgende variabelen: pati-
entkenmerken, ongevalsmechanisme (eenzijdig of bot-
sing, zie uitleg), letseldiagnose, letselernst, opnameduur,
verblijf op IC, aantal operaties en mortaliteit binnen
 dagen. Comorbiditeit werd gedefinieerd als de aanwe-
zigheid van cardiale, pulmonale, neurologische, muscu-
loskeletale of endocriene ziekten.
De letseldiagnose werd gecodeerd volgens de ‘Abbrevia-
ted injury scale’ (AIS, versie AIS revisie ). Een
AIS-score ≥  is een maat voor ernstig traumatisch letsel.
Voor het bepalen van de letselernst werd voor iedere
patiënt de ‘Injury severity score’ (ISS) berekend. Meer-
voudig ernstig letsel is gedefinieerd als ISS > . We
hielden de gegevens prospectief bij; deze gegevens wer-
den geverifieerd met gegevens van de regionale trauma-
registratie van het Acute Zorg Netwerk Noord Neder-
land, als die beschikbaar waren.
STATISTISCHE ANALYSE
Om na te gaan of er verschillen waren tussen de e-bikers
en klassieke fietsers gebruikten wij de χ-toets, de exacte
toets van Fisher, de Students t-toets en de Mann-Whit-
ney-toets. Normaal verdeelde variabelen gaven wij weer
als gemiddelde met standaarddeviatie (SD), niet-normaal
verdeelde variabelen als mediaan met spreiding (uiter-
sten). Met ‘propensity score matching’ werd uit de groep
klassieke fietsers een controlegroep geselecteerd die qua
geslacht, leeftijd en aanwezigheid van comorbiditeit
gelijk was aan de groep e-bikers. De propensity-score-
matching voerden wij uit met SAS-software (Statistical
Analysis System, versie .) en voor de statistische analy-
ses gebruikten wij IBM SPSS statistics for Windows
(versie .).
RESULTATEN
In een periode van  maanden werden  slachtoffers
na een fietsongeval op de SEH behandeld, respectievelijk
 e-bikers (,) en  klassieke fietsers (,). De
gemiddelde leeftijd van patiënten na een ongeval met een
e-bike of een klassieke fiets was respectievelijk , en
, jaar. Er was significant meer comorbiditeit onder
e-bikers dan onder klassieke fietsers, respectievelijk  en
. Een helm werd door  van de  (,) fietsers
gedragen; dit was een e-biker (tabel ).
In tabel  staan tevens de letselernst, het type letsel, de
opnamegegevens en de mortaliteit na een ongeval met
een e-bike of klassieke fiets weergegeven. De ernst van
het letsel – afgelezen aan de ISS – verschilde significant
tussen e-bikers (mediane score: ) en klassieke fietsers
(mediane score: ). Daarnaast raakten e-bikers  maal zo
vaak meervoudig ernstig gewond als klassieke fietsers
( vs. ). De meest voorkomende letsels betroffen let-
sels van het hoofd, het aangezicht, en de bovenste en
onderste extremiteit.
De e-bikers hadden significant vaker letsel van de wervel-
kolom en de onderste extremiteit dan de klassieke fietsers
(figuur a). De ernst van de letsels van het hoofd (schedel-
hersenletsel), gezicht, en bovenste en onderste extremi-
teit was significant hoger in de groep e-bikers. De helft
van de e-bikers moest worden opgenomen in het zieken-
huis voor verdere behandeling, van wie meer dan een
FIGUUR Verdeling van letsels per lichaamsregio volgens de ‘Abbreviated injury scale’ na een ongeval met een e-bike of klassieke fiets, (a) voor de volledige
patiëntenpopulatie (107 e-bikers, percentages groen; 368 klassieke fietsers, percentages zwart) en (b) na ‘propensity score matching’ (92 e-bikers, groen; 92
klassieke fietsers, zwart). *Statistisch significant verschil tussen e-bikers en klassieke fietsers.
ab
thorax: 11 / 7 %
wervelkolom: 8 / 3 %*
abdomen: 5 / 4 %
onderste extremiteit: 46 / 31 %*
gezicht: 31 / 38 %
hoofd: 41 / 37 %
nek: 1 / 3 %
bovenste extremiteit: 39 / 39 %
thorax: 13 / 14 %
wervelkolom: 9 / 2 %
abdomen: 5 / 1 %
onderste extremiteit: 48 / 39 %
gezicht: 29 / 29 %
hoofd: 41 / 36 %
nek: 1 / 1 %
bovenste extremiteit: 39 / 40 %
NED TIJDSCHR GENEESKD. 2017;161: D1520
ONDERZOEK
derde werd opgenomen op de IC. Daarnaast moest 
van de e-bikers een operatie ondergaan. De klassieke
fietsers werden significant minder vaak opgenomen en
geopereerd. Er was geen verschil in mortaliteit tussen
beide groepen.
EBIKE VERSUS KLASSIEKE FIETS NA PROPENSITYSCOREMATCHING
Met propensity-scorematching matchten wij  klassieke
fietsers met  e-bikers. In tabel  staan de kenmerken en
de letselernst, het type letsel, de opnamegegevens en de
mortaliteit binnen  dagen na een ongeval met een
e-bike of klassieke fiets na propensity-scorematching. Er
was nu geen significant verschil meer in ISS tussen de
e-bikers (mediane score: ) en de gematchte klassieke
fietsers (mediane score: ). E-bikers raakten echter
 maal zo vaak meervoudig gewond ( vs. ). Bij
e-bikers was de ernst van hoofdletsels (schedel-hersen-
letsel) significant hoger (AIS-score: ,) dan bij klassieke
fietsers (AIS-score: ,).
De meest voorkomende letsels betroffen het hoofd, het
aangezicht, en de bovenste en onderste extremiteit; er
was geen significant verschil in het aantal letsels per let-
selregio (figuur b). Er was geen significant verschil in het
aantal fietsers dat werd opgenomen, maar de opname-
duur was voor e-bikers significant langer. IC-opname
was bij e-bikers wel  maal zo vaak noodzakelijk als bij
klassieke fietsers, maar dit verschil was statistisch niet
significant (p = ,). Wij vonden geen verschil in morta-
liteit.
TABEL 2 Patiëntkenmerken, letselernst, type letsel, opnamegegevens en mortaliteit na een ongeval met een e-bike of klassieke fiets na
‘propensity score matching
kenmerk e-bike
(n = 107)
klassieke fiets
(n = 368)
p-waarde
leeftijd in jaren; gemiddelde (SD) 64,1 (12,1) 63,8 (12,9) 0,90
mannelijk geslacht; n (%) 38 (41) 37 (40) 0,88
comorbiditeit aanwezig; n (%)* 71 (77) 73 (79) 0,72
helm gedragen; n (%) 1 (1) 0 (0) 0,88
eenzijdig ongeval; n (%) 52 (57) 53 (58) 1,00
botsing; n (%) 40 (44) 39 (42) 1,00
ISS; mediaan (uitersten) 6 (0-38) 4 (0-34) 0,07
meervoudig ernstig letsel; n (%)† 20 (22) 10 (11) 0,05
AIS-regio; gemiddelde (SD)
hoofd 3,1 (1,3) 2,4 (1,3) 0,04
gezicht 1,4 (0,5) 1,3 (0,6) 0,32
nek‡ 1,0 1,0 1,00
thorax 2,4 (1,4) 1,8 (1,1) 0,30
abdomen‡ 2,0 (0,7) 1,0 0,33
wervelkolom 2,4 (0,5) 3,0 (0,0) 0,27
bovenste extremiteit 1,9 (0,8) 1,7 (0,7) 0,13
onderste extremiteit 1,8 (0,8) 1,7 (0,8) 0,64
opname; n (%) 43 (47) 35 (38) 0,23
opnameduur in dagen; mediaan (uitersten) 6 (1-51) 3 (1-21) 0,004
IC-opname; n (%) 15 (16) 7 (8) 0,07
IC-opnameduur in dagen; mediaan (uitersten) 8 (1-34) 2 (1-9) 0,09
operatie; n (%) 21 (23) 14 (15) 0,19
mortaliteit binnen 30 dagen; n (%) 2 (2) 5 (5) 0,44
AIS = ‘Abbreviated injury scale’; ISS = ‘Injury severity score’.
Bij statistisch significante verschillen tussen berijders van e-bikes en klassieke fietsen zijn de waarden rood afgedrukt.
* Comorbiditeit: cardiale, pulmonale, neurologische, musculoskeletale of endocriene ziekten.
† Van meervoudig letsel is sprake bij een ISS-score > 15.
‡ 1 klassieke fietser en 1 e-biker hadden nekletsel, beide met AIS-score 1 (geen SD); 1 klassieke fietser had letsel van het abdomen met AIS-score 1 (geen SD).
NED TIJDSCHR GENEESKD. 2017;161: D1520
ONDERZOEK
BESCHOUWING
Het groeiende gebruik van e-bikes zorgt ervoor dat oude-
ren langer mobiel blijven en forensen de auto vaker laten
staan. Op de fietspaden wordt het echter drukker en de
snelheidsverschillen nemen toe. Wij verrichtten een ana-
lyse van de letsels na een ongeval met een elektrische of
klassieke fiets. Deze analyse toont aan dat slachtoffers bij
een ongeval met een e-bike ernstiger gewond raakten en
vaker meervoudig ernstig letsel hadden dan slachtoffers
met een klassieke fiets, wat resulteerde in langere zieken-
huisopname, vaker opname op de IC en meer operaties
bij e-bikers.
Uit dit onderzoek bleek ook dat e-bikers verschilden van
klassieke fietsers in diverse patiëntgebonden kenmerken.
E-bikebestuurders bleken gemiddeld ouder te zijn en
vaker comorbiditeit te hebben dan klassieke fietsers. Ook
na propensity-scorematching, waarmee wij een groep
klassieke fietsers selecteerden die voor wat betreft de
patiëntkenmerken vergelijkbaar was met de groep
e-bikers, bleken de genoemde verschillen grotendeels te
blijven bestaan. Na matching bleek de e-biker  maal zo
vaak ernstig meervoudig gewond te raken, ernstiger
schedel-hersenletsel op te lopen en langer te moeten
worden opgenomen in het ziekenhuis. Deze observatie
bevestigt het onderbuikgevoel van veel zorgverleners dat
het toenemende gebruik van e-bikes bepaalde risico’s
met zich meebrengt.
WEINIG VERGELIJKBAAR ONDERZOEK
Er is weinig vergelijkbaar onderzoek naar letsels na een
ongeval met een e-bike gedaan. Recent Nederlands
onderzoek toont aan dat e-bikers na een ongeval vaker
behandeling op een SEH nodig hebben. Dat onderzoek
bevatte echter geen gegevens over letselernst. Een stu-
die uit Zwitserland rapporteerde over de ernst van onge-
vallen met e-bikes, waarbij de gemiddelde ISS van de
slachtoffers , bedroeg. Deze gemiddelde score is verge-
lijkbaar met ons resultaat. In de Zwitserse studie werd
echter geen vergelijking met klassieke fietsers gemaakt.
Een andere Zwitserse studie vond geen verschil in letsel-
ernst tussen e-bikers en klassieke fietsers, maar laat wel
zien dat e-bikeslachtoffers ouder zijn dan de klassieke
fietsers. In Azië raken e-bikers significant vaker ernstig
gewond dan klassieke fietsers. Hierbij moet worden
opgemerkt dat de verkeerssituatie in Azië niet te vergelij-
ken is met die in Nederland.
LEEFTIJD SPEELT EEN ROL
De vergrijzing en het groeiende aantal ouderen dat nog
mobiel is zorgen voor een toename van ouderen die
betrokken raken bij verkeersongevallen. Een recent
Nederlands overzicht laat zien dat van de ruim .
fietsers per jaar die een ongeval krijgen,  slachtoffers
ouder zijn dan  jaar. Dit komt overeen met onze
bevinding dat de gemiddelde e-biker die een ongeval
doormaakt –gemiddelde leeftijd  jaar – ouder is dan de
klassieke fietser. Wij zagen dat e-bikers  maal zo vaak
meervoudig gewond raakten als klassieke fietsers en dat
bijna de helft van de e-bikers ernstig schedel-hersenletsel
had. Verder kwamen lichte letsels aan de extremiteiten
veel voor bij e-bikers. Naast de bekende impact van ern-
stig schedel-hersenletsel blijken ook licht gewonde fiet-
sers op de langere termijn vaak nog persisterende klach-
ten te hebben.
Leeftijd speelt ook een grote rol in het verkeer als het
gaat om de mortaliteit. De kans dat een fietser ouder
dan  jaar overlijdt, is  keer hoger dan de kans dat
een jonge fietser overlijdt. In  vielen de meeste
verkeersdoden onder -plussers, van wie  als gevolg
van een fietsongeval overleed. De mortaliteit binnen
 dagen na het ongeval was  in onze geanalyseerde
groep.
Momenteel wordt lokaal in Nederland een preventieve
maatregel toegepast in de vorm van een fietskeuring voor
ouderen door een geriater en een gespecialiseerde ergo-
therapeut. Hierbij wordt een advies op maat aan oude-
ren gegeven over het wel of niet gaan fietsen en over de
eventuele noodzaak voor fietsaanpassingen, zoals
trapondersteuning, meerdere wielen, zijwielen of spie-
gels. Dergelijke keuringen kunnen bijdragen aan de vei-
ligheid van oudere fietsers, maar worden slechts op kleine
schaal toegepast. Het is aan te bevelen dit initiatief te
stimuleren. Ook kan rijles voor e-bikers bijdragen aan
veiliger gebruik ervan.
GEBRUIK VAN EEN HELM
Uit ons onderzoek blijkt dat ernstig schedel-hersenletsel
significant vaker voorkomt onder e-bikers. Een opval-
lende bevinding in deze studie is dat slechts één fietser,
een e-biker, een helm droeg. Op  januari  is een
helmplicht ingevoerd voor bestuurders van een zoge-
noemde speedbike. Van alle verkochte e-bikes is echter
slechts een klein percentage speedbikes, zodat het abso-
lute aantal e-bikers dat een helm draagt waarschijnlijk
amper zal toenemen.
Onderzoek heeft aangetoond dat gebruik van een helm
leidt tot een reductie van - in het risico op schedel-
hersenletsel, onafhankelijk van het soort ongeval, eenzij-
dig of botsing. Het verplichten van de helm voor fietsers
heeft in het verleden in de Verenigde Staten en Canada
geleid tot een forse toename van het gebruik ervan, met
een reductie van ernstig schedel-hersenletsel, zonder
afname van het fietsgebruik. - Alleen in Australië werd
na invoering van de helmplicht een afname van fietsge-
bruik door kinderen gezien. Anderzijds is gebleken dat
NED TIJDSCHR GENEESKD. 2017;161: D1520
ONDERZOEK
alleen al het stimuleren van helmgebruik – zonder helm-
plicht – in ieder geval bij kinderen heeft geleid tot het
vaker dragen van de helm.
Welk effect een helmplicht in Nederland zal hebben op
fietsgebruik is onbekend. In de genoemde landen wordt
de fiets vooral gebruikt voor sportieve activiteiten. In
Nederland gebruikt men de fiets echter veelvuldig voor
dagelijks transport. Wij verwachten daarom dat een
afname van het fietsgebruik zal meevallen. Helmgebruik
is onzes inziens aan te bevelen voor fietsende ouderen,
met name voor e-bikers. Door het gebruik van helmen in
Nederland meer te stimuleren hopen we dat deze daad-
werkelijk vaker gedragen zullen worden.
BEPERKINGEN VAN DIT ONDERZOEK
Een beperking van dit onderzoek is dat we de oorzaak
van de fietsongevallen niet hebben geanalyseerd. E-bikes
zijn zwaarder en kunnen met een hogere snelheid bere-
den worden dan klassieke fietsen; dit kan van invloed zijn
op het ontstaan van ongevallen., Tevens is uit onder-
zoek gebleken dat de snelheid van e-bikes lastig in te
schatten is voor andere weggebruikers, doordat e-bikers
een lagere trapfrequentie hebben, maar wel meer snel-
heid genereren.
Verder hebben wij niet gekeken naar de relatie tussen het
soort ongeval en de ernst van het letsel. Het is bekend dat
een fietser bij een botsing met een motorvoertuig vaker
schedel-hersenletsel oploopt dan een fietser die betrok-
ken is bij een eenzijdig ongeval. Bij een eenzijdig ongeval
komt juist vaker letsel van de bovenste extremiteit voor.
In vervolgonderzoek zullen wij diverse oorzaken van
fietsongevallen onderzoeken om verdere preventieve
adviezen te kunnen geven.
CONCLUSIE
E-bikers raken vaker ernstig en meervoudig ernstig
gewond dan klassieke fietsers wanneer zij betrokken
raken bij een verkeersongeval. Tevens loopt bijna de helft
van de e-bikers ernstig schedel-hersenletsel op. E-bikers
die een ongeval doormaken zijn weliswaar ouder en heb-
ben vaker comorbiditeit dan klassieke fietsers, maar ook
na correctie voor deze kenmerken blijft onze conclusie
gerechtvaardigd. Preventieve maatregelen in de vorm
van helmgebruik en rijlessen voor e-bikers dienen gesti-
muleerd te worden. Daarnaast is het raadzaam voor
hulpverleners om extra bedacht te zijn op de mogelijk
ernstigere letsels bij een patiënt die een ongeval met een
e-bike heeft gehad. Meer onderzoek naar de oorzaak van
fietsongevallen is noodzakelijk om verdere preventieve
maatregelen te kunnen adviseren.
Drs. E. Poos-ten Dam gaf grafische en tekstuele ondersteuning bij dit
manuscript.
Belangenconflict en financiële ondersteuning: geen gemeld.
Aanvaard op 23 maart 2017
Citeer als: Ned Tijdschr Geneeskd. 2017;161:D1520
> KIJK OOK OP WWW.NTVG.NL/D1520
LEERPUNTEN
• Demeestgebruiktee-bikeszijnfietsenmet
trapondersteuningtot25km/h.
• Slachtof fersvaneenongevalmeteene-bikezijn
gemiddeld65jaaroudenhebbenvakercomorbiditeitdan
klassieke fietsers.
• E-bikebestuurdersvormeneengroeiendegroepvan
kwetsbare verkeersdeelnemers.
• Ernstigschedel-hersenletselnaeenfietsongevalkomtbij
e-bikers vaak voor.
• Hetgroeiendegebruikvane-bikeskanleidentoteen
toename van de ernst van schedel-hersenletsel bij
fietsongevallen.
• Hetdragenvaneenhelmdoore-bikebestuurderskanhet
risico op schedel-hersenletsel mogelijk beperken.
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... In terms of safety, e-bikers seem subject to higher risk (Fishman and Cherry 2015). For instance, a study in the Netherlands found that they are twice as likely to suffer injury from a crash than bicycle users (Poos et al. 2017). However, this may be partly a result of the large share of older, more vulnerable e-bike users. ...
... The differences in attitudes towards e-bikes between users and non-users revolve around aspects of safety, fun and health benefits which have previously been found to constitute recurring themes in the e-bike literature (Berntsen et al. 2017;Haustein and Møller 2016;Langford et al. 2017;Plazier et al. 2017b;Poos et al. 2017;Schepers et al. 2014;Vlakveld et al. 2015). The present study provides further support for the importance of these aspects in individual decisions of rural residents to use an e-bike. ...
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Objectives Electrically Assisted Pedal Cycles (EAPCs) are pedal bikes that are fitted with a motor that travel at higher speeds than conventional bicycles. Recent international data shows that there is an association with increased severity of injury, particularly in paediatric populations. Currently, EAPCs are subject to the same legislation regarding helmet use as pedal bikes in the UK and EU which does not mandate the use of a helmet. Here we examine safety concerns surrounding EAPCs in the context of existing EU and UK legislation to assess whether changes to these should be made by public health bodies to mitigate the increased risk of injury. Methods A retrospective international literature review looking at electric bicycle-related trauma and legislation was conducted using a systematic search of internet databases. Peer-reviewed articles and online resources were reviewed based on relevance to the above objective. Results EAPCS can travel at up to 17.5 mph, resulting in higher speeds of travel and collision. The use of EAPCs has been associated with increased severity of head injuries. Bicycle helmets have been shown to reduce the severity of head injury in accidents involving both EAPCs and pedal cycles. Healthcare providers should pay extra attention to the possibility of severe injuries when a patient had a bicycle accident with an EAPC, especially in paediatric populations. Conclusions Given that EAPCS have been associated internationally with increased severity of head injuries we propose that existing EU and UK legislation may not be fit for purpose with respects to increased EAPC usage and criteria for impact protection of existing helmets. Further research and audit with more accurate recording of data associated with EAPCs use and associated injuries would inform enhanced regulation regarding EAPC usage in the future.
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... 5,6 Especially craniofacial injuries, including maxillofacial fractures, are often seen in accidents involving (electronic) bicycles and scooters. [7][8][9][10] In literature, the incidence rate of cycling related facial fractures varies (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19).7%). [11][12][13] The highest incidence (19.7%) was found in Amsterdam, the Netherlands. ...
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... Although several earlier studies reported similar findings concerning higher injury severity among e-bikers [9,11,[14][15][16][17], little to no difference in the severity of injuries between the groups was detected in other studies [10,11,18,19]. A positive correlation has been observed between increasing age and injury severity in e-bikers [11,[20][21][22]. ...
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... For example, the large amount of cycling injuries could (re)start the debate on mandatory helmet use. In addition, the e-bike is gaining popularity amongst the elderly in the Netherlands and injuries from e-bike accidents are more severe than for regular bicycles and less than 1% wears a helmet 26 . Helmets could prevent TBI or at least lower the chances of severe TBI and need for neurosurgical intervention for cyclists 27 . ...
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Among the problems resulting from the continuous urbanization process, inefficient urban mobility and high pollution levels have been complex challenges that have demanded a lot of public investments and research efforts. Recently, some alternative transportation means have been leveraged as sustainable options for such challenges, which has brought bicycles to a more relevant setting. Besides the sometimes obvious benefits of adopting bikes for transportation, technologies around the Internet of Things (IoT) paradigm have been advocated as important supportive tools to boost smart cycling initiatives. Actually, new technologies can be exploited to improve the efficiency of bike paths and parking spots, while reducing accidents and enhancing the cycling experience of the users. Therefore, in this highly vibrating scenario, this article facilitates the understating of current research trends and promising developments, surveying and classing recent works. Since there is a global interest for the promotion of cleaner and more sustainable solutions in large cities, this survey can be valuable when supporting new developments in this highly relevant research area.
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Purpose With the increased use of both e-bike and conventional bicycle, the number of bicycle related accidents has increased accordingly. To determine whether there are differences in maxillofacial injuries between these two types of bicycle accidents, e-bike and conventional bicycle accidents were compared. Material and Methods A retrospective cohort study was conducted of all the consecutive patients with maxillofacial injury due to e-bike and conventional bicycle accidents attending the emergency department of four hospitals in the Netherlands between May 2018 and October 2019. Primary outcomes are maxillofacial fractures present or absent and the severity of maxillofacial injury using the Maximum Abbreviated Injury Scale (MAIS) and Facial Injury Severity Scale (FISS) after e-bike and conventional bicycle accidents. A binary logistic regression analysis was used to assess differences in risk between an e-bike and conventional bicycle accident, where age, alcohol use and comorbidities were added as covariates, for maxillofacial fractures, dental injury and severe maxillofacial fractures. Results In total, 311 patients were included (73 e-bikers and 238 conventional cyclists). Sex distribution was equal in both groups (45% male vs 55% female). The e-bike group was older (66 vs 53 median age in years, p<0.001) and had more comorbidities (0 vs 1, p<0.001), whilst alcohol use was higher in the conventional bicycle group (32% vs 16%, p=0.008). E-bikers sustained midfacial fractures more frequently (47% vs. 34%, p=0.04), whereas conventional cyclists more often had mandibular fractures (1% vs. 11%, p=0.01). Although median MAIS and FISS scores did not differ between e-bike and conventional bicycle accidents, severe maxillofacial fractures (FISS score ≥ 2) were observed more often in the conventional cyclists (45% vs. 25%, p=0.04). No significant differences in risk of midfacial, mandibular and severe maxillofacial fractures were found between e-bikers and conventional cyclists irrespective of their age, alcohol use and comorbidities. Conclusion Both the distribution and the severe maxillofacial fractures differed between the e-bike and conventional bicycle accidents patients. Patient specific characteristics, such as age, alcohol use and comorbidities may have a greater influence on sustaining maxillofacial fractures than the type of bicycle ridden.
Article
Compared to other cyclists, food delivery drivers travel under specific time limits, and traffic regulations for electric bikes (e-bikes) are relatively lax compared with those for motor vehicles in China. Therefore, the present study conducts an intercept survey in Tianjin, China, to investigate the influence of external and internal regulators on food delivery and normal e-bike riders, accounting for occupation-related factors (time pressure). Our results suggest that both traffic enforcement and personal norms negatively influence the frequency of self-reported aggressive driving behaviors, which means that both external and internal regulations can effectively reduce the tendency of riders to drive aggressively. Furthermore, group differences showed that, for food delivery drivers, time pressure was positively correlated with aggressive driving behaviors. Traffic enforcement has a powerful inhibiting effect on the aggressive driving behaviors of food delivery drivers, while for normal e-bike riders, personal norms were stronger regulators than perceived traffic enforcement. Based on these findings, some feasible suggestions (e.g., limit the number of orders at a time, provide consumers a safe delivery time) are proposed to regulate food delivery e-bike drivers’ aggressive driving behaviors.
Article
Background For years e‑bike (Pedelec) sales have been steadily increasing. Therefore, the incidence of e‑bike-related injuries and deaths has been growing. Due to clinical experience, emergency personnel are suspecting that e‑bikers might be injured more severely compared to conventional bicyclists suffering from an accident. This topic has not yet been analyzed for Germany.Objective Analysis of injury severity and mortality following e‑bike and conventional bicycle accidents in a level I trauma center in Germany.Material and methodsData of patients treated after a bicycle accident at the accident and emergency department as well as the clinic for traumatology and orthopedics of the Evangelical Hospital (Evangelisches Krankenhaus) Oldenburg were gathered from 1 March 2017 to 1 March 2019.ResultsIn this study 59 electric bicycle users (e-bikers) and 164 conventional cyclists were included. The average age of e‑bikers was 62 years compared to 48 years in the group of conventional cyclists. Comorbidities were significantly more frequent in the e‑bike group compared to classical cyclists. The e‑bikers were found to be significantly more severely injured than conventional bicyclists, the mean injury severity scores (ISS) were 5.2 and 3.4, respectively. E‑bikers were admitted to the hospital more often and for longer periods than the control group. There was no significant difference in mortality.ConclusionE‑bikers are more severely injured in accidents compared to conventional cyclists. Due to older age and comorbidity they form a sensitive trauma subgroup. Based on demographics, an increase of old age, more frail cyclists and a growing incidence of serious e‑bike accidents is to be expected. Preventive measures, such as helmet usage and riding lessons should be introduced, especially in e‑bikers. E‑bikers in the emergency department should be examined and treated with special care and aggressive diagnostics. A low threshold for an initial interdisciplinary assessment (shock room management) is advised.
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In 2003, Seattle implemented an all-ages bicycle helmet law; King County outside of Seattle had implemented a similar law since 1994. For the period 2000-2010, the effect of the helmet legislation on helmet use, helmet-preventable injuries, and bicycle-related fatalities was examined, comparing Seattle to the rest of King County. Data was retrieved from the Washington State Trauma Registry and the King County Medical Examiner. Results comparing the proportions of bicycle related head injuries before (2000-2002) and after (2004-2010) the law show no significant change in the proportion of bicyclists admitted to the hospital and treated for head injuries in either Seattle (37.9 vs 40.2 % p = 0.75) nor in the rest of King County (30.7 vs 31.4 %, p = 0.84) with the extension of the helmet law to Seattle in 2003. However, bicycle-related major head trauma as a proportion of all bicycle-related head trauma did decrease significantly in Seattle (83.9 vs 64.9 %, p = 0.04), while there was no significant change in King County (64.4 vs 57.6 %, p = 0.41). While the results do not show an overall decrease in head injuries, they do reveal a decrease in the severity of head injuries, as well as bicycle-related fatalities, suggesting that the helmet legislation was effective in reducing severe disability and death, contributing to injury prevention in Seattle and King County. The promotion of helmet use through an all ages helmet law is a vital preventative strategy for reducing major bicycle-related head trauma.
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Background. Between 2005 and 2012, annual sales of E-bikes in Switzerland increased from 1,792 to 52,941. This continuous and rapid transition from human-powered bicycles to an electric bicycle technology may indicate the increasing demand for low-cost transportation technology in combination with a healthy lifestyle. Material and Methods. In the present study, from April 2012 to September 2013, we retrospectively analysed E-bike accidents treated in the Emergency Department of our hospital by focusing on the following parameters: age, gender, time, period, and cause of the accident, as well as injury and outcome. Results. Patients were predominantly male. The mean age of injured E-cyclists was 47.5 years. The main causes of injury were self-accident. Most injuries were to the head/neck. The mean ISS was 8.48. The outcome showed that 9 patients were treated as outpatients, 9 were inpatients, and 5 patients were kept in the Intensive Care Unit (ICU). Only six patients underwent surgery (S). Discussion. This is the first attempt to evaluate E-bike injuries in Switzerland in an acute hospital setting. Since there is increasing popular preference for E-bikes as means of transportation and injuries to the head or neck are prevalent among E-cyclists, the hazard should not to be underestimated.
Fietsende ouderen zijn steeds vaker betrokken bij een ongeval, met vaak ernstig letsel of zelfs overlijden tot gevolg. Bij hen dreigt enerzijds het staken van een belangrijke vorm van autonome en gezonde mobiliteit en anderzijds een fietsincident. Aan de hand van een casusbeschrijving wordt geïllustreerd welke stappen een arts kan nemen in de begeleiding van ouderen, met als doel hen zo lang mogelijk veilig te laten fietsen.
Article
Given their potential to reach higher speed levels than conventional bicycles, the growing market share of e-bikes has been the reason for increased concerns regarding road safety. Previous studies have shown a clear relationship between object approach speed and an observers' judgment of when the object would reach a predefined position (i.e., time to arrival, TTA), with higher speed resulting in longer TTA estimates. Since TTA estimates have been linked to road users' decisions of whether or not to cross or turn in front of approaching vehicles, the higher potential speeds of e-bikes might result in an increased risk for traffic conflicts. The goal of the two experiments presented in this paper was to examine the influence of speed and a variety of other factors on TTA estimation for conventional bicycles and for e-bikes. In both experiments, participants from two age groups (20-45 years old and 65 years or older) watched video sequences of bicycles approaching at different speeds (15-25km/h) and were asked to judge the TTA at the moment the video was stopped. The results of both experiments showed that an increase in bicycle approach speed resulted in longer TTA estimates (measured as the proportion of estimated TTA relative to actual TTA) for both bicycle types (ηp(2)Exp.1=.489, ηp(2)Exp.2=.705). Compared to younger observers, older observers provided shorter estimates throughout (Exp. I: MDiff=0.35, CI [0.197, 0.509], ηp(2)=.332, Exp. II: MDiff=0.50, CI [.317, 0.682], ηp(2)=.420). In Experiment I, TTA estimates for the conventional bicycle were significantly shorter than for the e-bike (MDiff=0.03, CI [.007, 0.044], ηp(2)=.154), as were the estimates for the elder cyclist compared to the younger one (MDiff=0.05, CI [.025, 0.066], ηp(2)=.323). We hypothesized that the cause for this effect might lie in the seemingly reduced pedaling effort for the e-bike as a result of the motor assistance it provides. Experiment II was able to show that a high pedaling frequency indeed resulted in shorter TTA estimates compared to a low one (MDiff=0.07, CI [0.044, 0.092], ηp(2)=.438). Our findings suggest that both the e-bikes' potential to reach higher speeds and the fact that they reduce the perceived cycling effort increase the risk of TTA misjudgments by other road users.
Article
Introduction: Bicycle crashes often affect individuals in working age, and can impair quality of life (QoL) as a consequence. The aim of this study was to investigate QoL in bicycle trauma patients and to identify those at risk of impaired QoL. Patients and methods: 173 bicycle trauma patients who attended a level I trauma centre from 2010 to 2012 received Hadorn's QoL questionnaire six months after their crash. Medical data was collected from the patient's records. Univariate ordinal logistic regression was used to investigate the association between QoL and other factors. Results: 148 patients returned the questionnaire (85.5%). The majority had only mild or minor injuries (85.1%; n=126). However, 72.1% (n=106) still suffered from pain or other physical symptoms more than six months after their bicycle crash. Patients with a Glasgow Coma Scale (GCS) ≤13 or an Injury Severity Score (ISS) >15 experienced impaired emotions/outlook on life (p-values 0.003 and 0.045, respectively). Physical suffering was reported by patients with a GCS ≤13 and in those with injuries to the cervical spine (p-values 0.02 and 0.025, respectively). Patients with an ISS >15 or facial fractures experienced limitations in daily activities (p-values 0.031 and 0.025, respectively). Conclusions: More than 70% of bicycle trauma patients suffered physically more than six months after their crash, even though only 15% were severely injured. Risk factors for an impaired QoL were cervical spine injuries or facial fractures, a GCS ≤13 and an ISS >15.
Article
Use of electrically assisted bicycles with a maximum speed of 25 km/h is rapidly increasing. This growth has been particularly rapid in the Netherlands, yet very little research has been conducted to assess the road safety implications. This case–control study compares the likelihood of crashes for which treatment at an emergency department is needed and injury consequences for electric bicycles to classic bicycles in the Netherlands among users of 16 years and older. Data were gathered through a survey of victims treated at emergency departments. Additionally, a survey of cyclists without any known crash experience, drawn from a panel of the Dutch population acted as a control sample. Logistic regression analysis is used to compare the risk of crashes with electric and classical bicycles requiring treatment at an emergency department. Among the victims treated at an emergency department we compared those being hospitalized to those being send home after the treatment at the emergency department to compare the injury consequences between electric and classical bicycle victims. The results suggest that, after controlling for age, gender and amount of bicycle use, electric bicycle users are more likely to be involved in a crash that requires treatment at an emergency department due to a crash. Crashes with electric bicycles are about equally severe as crashes with classic bicycles. We advise further research to develop policies to minimize the risk and maximize the health benefits for users of electric bicycles.
Article
Background: The acceptance and usage of electric bicycles has rapidly increased in Switzerland in the last years. Hence this topic has been addressed by policy makers with the aim to facilitate new transport modes and, moreover, to improve their safety. Methods: Police-recorded accidents of the years 2011 and 2012 involving a total of 504 e-bikers and 871 bicyclists were analysed. National figures were compared with those of a rural and an urban environment. Results: Most e-bikers who were involved in accidents were 40-65 years old. It was found that most e-bikers sustained single accidents and that helmet usage was higher in the investigated rural environment than in the investigated urban area. The evaluation of the injury severity of e-bikers, particularly compared to bicyclists, lead to diverging results. Conclusions: The findings presented in this study are intended to serve as a benchmark since basic information on characteristics of e-bike accidents is provided. With respect to differences between the injury severity of e-bikers and bicyclists to-date no clear statement can be drawn. It is suggested to regularly evaluate e-bike accidents to show trends and/or identify changes.
Article
Objective: To explore the related risk factors of injuries caused by e-bike and bicycle crashes in Hefei, Anhui. Methods: Between June 2009 and June 2011, the records of injuries were triggered by e-bike and bicycle crashes in Hefei maintained by 105th Hospital of PLA. A form was designed to document patient age, gender, road user category (driver, passenger, pedestrian), safety factors (safety devices present, speed, traffic violations), environmental factors (time of trauma, light conditions, road surface), crash mode, impact type, and vehicle type. Results: Of the 205 cases, 108 were female and 97 were male. One hundred forty-six patients suffered injuries due to e-bike accidents and 59 due to bicycle accident. The chi-squared test compared distribution of categorical variables suggested that age (P =.0250), road user category (P =.0278), traffic rule violations (P =.0132), crash mode (P =.0027), impact type (P =.0019), and vehicle type (P =.0219) are related to the severity of injuries caused by e-bike/bicycle crashes in Hefei. The multiple-factor nonconditional logistic regression analysis showed that injury severity is the most commonly sustained within the vehicle type (odds ratio [OR] = 14.418; 95% confidence interval [CI], 4.680-44.418), followed by crash mode (OR = 11.556; 95% CI, 4.430-30.142), traffic rule violations (OR = 4.735; 95% CI, 1.934-11.594), and age (OR = 2.910; 95% CI, 1.213-6.979). Conclusions: With the study of e-bike/bicycle crashes in Hefei, primary identification of the risk factors for the traffic injuries is obtained. These findings are important in decision making regarding preventive measures.
Article
Background: Helmets reduce bicycle-related head injuries, particularly in single vehicle crashes and those where the head strikes the ground. We aimed to identify non-legislative interventions for promoting helmet use among children, so future interventions can be designed on a firm evidence base. Objectives: To assess the effectiveness of non-legislative interventions in increasing helmet use among children; to identify possible reasons for differences in effectiveness of interventions; to evaluate effectiveness with respect to social group; to identify adverse consequences of interventions. Search methods: We searched the following databases: Cochrane Injuries Group Specialised Register; the Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE; EMBASE; PsycINFO (Ovid); PsycEXTRA (Ovid); CINAHL (EBSCO); ISI Web of Science: Science Citation Index Expanded (SCI-EXPANDED); Social Sciences Citation Index (SSCI); Conference Proceedings Citation Index-Science (CPCI-S); and PubMed from inception to April 2009; TRANSPORT to 2007; and manually searched other sources of data. Selection criteria: We included RCTs and CBAs. Studies included participants aged 0 to 18 years, described interventions promoting helmet use not requiring enactment of legislation and reported observed helmet wearing, self reported helmet ownership or self reported helmet wearing. Data collection and analysis: Two independent review authors selected studies for inclusion and extracted data. We used random-effects models to estimate pooled odds ratios (ORs) (with 95% confidence interval (CI)). We explored heterogeneity with subgroup analyses. Main results: We included 29 studies in the review, 21 of which were included in at least one meta-analysis. Non-legislative interventions increased observed helmet wearing (11 studies: OR 2.08, 95% CI 1.29 to 3.34). The effect was most marked amongst community-based interventions (four studies: OR 4.30, 95% 2.24 to 8.25) and those providing free helmets (two studies: OR 4.35, 95% CI 2.13 to 8.89). Significant effects were also found amongst school-based interventions (eight studies: OR 1.73, CI 95% 1.03 to 2.91), with a smaller effect found for interventions providing education only (three studies: OR 1.43, 95% CI 1.09 to 1.88). No significant effect was found for providing subsidised helmets (seven studies: OR 2.02, 95% CI 0.98 to 4.17). Interventions provided to younger children (aged under 12) may be more effective (five studies: OR 2.50, 95% CI 1.17 to 5.37) than those provided to children of all ages (five studies: OR 1.83, 95% CI 0.98 to 3.42).Interventions were only effective in increasing self reported helmet ownership where they provided free helmets (three studies: OR 11.63, 95% CI 2.14 to 63.16).Interventions were effective in increasing self reported helmet wearing (nine studies: OR 3.27, 95% CI 1.56 to 6.87), including those undertaken in schools (six studies: OR 4.21, 95% CI 1.06 to 16.74), providing free helmets (three studies: OR 7.27, 95% CI 1.28 to 41.44), providing education only (seven studies: OR 1.93, 95% CI 1.03 to 3.63) and in healthcare settings (two studies: OR 2.78, 95% CI 1.38 to 5.61). Authors' conclusions: Non-legislative interventions appear to be effective in increasing observed helmet use, particularly community-based interventions and those providing free helmets. Those set in schools appear to be effective but possibly less so than community-based interventions. Interventions providing education only are less effective than those providing free helmets. There is insufficient evidence to recommend providing subsidised helmets at present. Interventions may be more effective if provided to younger rather than older children. There is evidence that interventions offered in healthcare settings can increase self reported helmet wearing.Further high-quality studies are needed to explore whether non-legislative interventions increase helmet wearing, and particularly the effect of providing subsided as opposed to free helmets, and of providing interventions in healthcare settings as opposed to in schools or communities. Alternative interventions (e.g. those including peer educators, those aimed at developing safety skills including skills in decision making and resisting peer pressure or those aimed at improving self esteem or self efficacy) need developing and testing, particularly for 11 to 18 year olds. The effect of interventions in countries with existing cycle helmet legislation and in low and middle-income countries also requires investigation.