Dolores Romano
email: dromano@istas.net

Tatiana Santos

Rafael Gadea

Trade Union Priority List for REACH Authorisation

Keywords: Occupational Exposure, Hazardous Chemicals, REACH Regulation, Authorisation Process

Background

The new EU REACH Regulation to control the trade and use of chemicals has a great potential to reduce worker exposure to hazardous substances and therefore reduce chemical related occupational diseases. REACH requires manufacturers of substances of very high concern (SVHC) to request an authorisation for each use of these substances in order to continue marketing them. There are between 1,500 and 2,000 SVHC on the European market; however, to date, the European Chemicals Agency has published only 29 substances as candidates for the authorisation procedure. This work aims to contribute to the practical implementation of REACH by proposing a list of SVHC which from a union's perspective should have priority for inclusion in the authorisation procedure.

Methods

In a first stage SVHC for prioritisation were identified, following, prioritisation criteria were established and scores for each criterion were defined for finally developing the Trade Union List.

Results

Through previously presented criteria, the Trade Union List includes 305 high production volume chemicals that meet the requirements of the authorisation process under REACH. 190 of these substances are associated with recognised occupational diseases and 22 have been included in the REACH Candidate List.

Conclusions

In this paper, we present a precautionary but scientifically aligned process for identifying, scoring and ranking SVHC, including categories of substances not currently considered in other approaches to the REACH Regulation. This proposed methodology is advocated by Trade Unions to coherently prioritise SVHC in order to implement and enforce REACH in a way that will more effectively protect the health of the European working and general population.

BACKGROUND

On 1st June 2007, a new EU regulation for chemicals called REACH (Registration, Evaluation, Authorisation and Restriction of Chemical substances) came into force in the 27 EU Member States and in the European Economic Area (EEA). [START_REF]the European Parliament and of the Council of 18 December 2006 concerning the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH)[END_REF] REACH establishes a process by which substances of very high concern (SVHC) will need an authorisation for being placed on the market. The aims of authorisation are to ensure that the risks from SVHC are properly controlled and that these substances are progressively replaced by suitable safer alternative substances or technologies.

The list of substances subject to authorisation under REACH will be included in Annex XIV (Authorisation List) of the Regulation. Once a substance is included in Annex XIV, producers shall apply for an authorisation for each use of the substance within a set date. Substances will not be granted authorisation if they can not be adequately controlled and/or do not meet the required socio-economic criteria for ongoing use and suitable alternatives are available. The European Chemicals Agency (ECHA) -on request of the European Commission-and Member States suggest substances that fulfil the criteria of being a SVHC. This list is called the "Candidate List". ECHA must then draw up a recommendation of substances that will have priority in the authorisation process and the Commission makes the final decision on which of these substances will be included in Annex XIV, based upon ECHA's recommendations and taking into account the opinion of the Member State Committee. If a substance is included in the "Candidate List", suppliers of these substances or mixtures have the obligation to provide safety data sheets and distributors of articles containing these substances -in a concentration above 0,1 % weight by weight (w/w)-have the obligation to inform consumers of the presence of any authorised chemicals in the products they buy and how to use them safely. REACH has the potential to reduce the number of diseases and deaths caused by occupational exposure to toxic chemicals as well as to promote the development of safer alternatives for substances included in the authorisation process. Better information on dangerous properties of products and articles and on adequate control measures will be available throughout the supply chain for substances included in the Authorisation List. [START_REF] Pickvance | The impact of REACH on occupational health[END_REF] On October 2008, ECHA published its first Candidate List, which included only 15 chemicals. The second Candidate List was published on January 2010, with only 14 additional substances. [START_REF]ECHA. Candidate List of Substances of Very High Concern for Authorisation under REACH[END_REF] On 14 th January 2010, ECHA published its first draft recommendation for the inclusion of substances in Annex XIV (the list of substances subject to authorisation) which included only 7 substances from the original Candidate List. [START_REF]Draft recommendation of substances for inclusion in the list of substances subject to Authorisation[END_REF] In order to help authorities identify the most urgent SVHC for inclusion in the Candidate List and establish a comprehensive prioritisation methodology for inclusion in the Authorisation List, the European Trade Union Institute developed the Trade Union Priority List (TU List). [START_REF] Santos | Trade Union Priority List for REACH Authorisation[END_REF]

METHODOLOGY

The TU List was developed by chemists, health and safety consultants and environmental consultants from the Spanish Trade Union Institute for Work, Environment and Health (ISTAS) and the European Trade Union Institute (ETUI), with more than 20 years of experience in environmental and occupational chemical risk management.

To draw up the Trade Union Priority List these stages were followed: PBT/vPvB list of the Technical Committee on New and Existing Substances (TCNES). [START_REF]group on PBT/vPvB substances and POPs[END_REF] Endocrine disrupters (EDC) Substances included in the priority list developed within the EU-Strategy for Endocrine Disrupters classified as category 1 (evidence of endocrine disrupting activity in at least one species using intact animals) and category 2 (at least some in vitro evidence of biological activity related to endocrine disruption). [START_REF]Community Strategy for Endocrine Disrupters -a range of substances suspected of interfering with the hormone systems of humans and wildlife[END_REF][START_REF]Communication on the implementation of the Community Strategy for Endocrine Disrupters -a range of substances suspected of interfering with the hormone systems of humans and wildlife[END_REF][START_REF]Staff Working Document on the implementation of the Community Strategy for Endocrine Disrupters -a range of substances suspected of interfering with the hormone systems of humans and wildlife[END_REF][START_REF]Staff Working Document on the implementation of the Community Strategy for Endocrine Disrupters -a range of substances suspected of interfering with the hormone systems of humans and wildlife[END_REF] Neurotoxicants Provisional list for occupational neurotoxicants included in the review published by Vela et al. [START_REF] Vela | Neurotóxicos en el ambiente laboral: criterios de clasificación y listado provisional[END_REF] Sensitizers Substances classified as skin or respiratory sensitizers by CLP Regulation, identified in Annex VI with hazard statements H334 (may cause allergy or asthma symptoms or breathing difficulties if inhaled) and H317 (may cause an allergic skin reaction).

The data source used to document the Trade Union list is the RISCTOX database that contains (eco) toxicological information for more than 100,000 substances and includes substances that have been identified as carcinogenic, mutagenic, toxic for reproduction, endocrine disrupters, neurotoxicants, etc. by European legislation and different national and international organizations. [START_REF]RISCTOX Database[END_REF] 2. Prioritisation criteria Criteria used for prioritisation in the TU List were:

Known health effects on exposed workers; Environmental toxicity, persistence and potential to bioaccumulate; and Prevalence of exposure, estimated through production volume data. High Production Volume Chemicals (HPVC), are substances that are produced in, or imported into, the EU in quantities greater than 1,000 tonnes per year. [START_REF]European Chemical Substances Information System (ESIS)[END_REF] 3. Definition of scores for each criterion.

The European Union Risk Ranking Method (EURAM) was followed to score health effects, in a scale ranking from 1 (lowest score) to 10 (highest score). [START_REF] Hansen | Priority Setting for Existing Chemicals: The European Union Risk Ranking Method[END_REF] EURAM scores were applied for known CMR (10 points), for suspected CMR (9 points) and for sensitizers by inhalation (7 points). Health and environmental effects not included in EURAM have been given a score in accordance with the level of concern that REACH confers on them. For instance, known endocrine disrupters and PBTs are given a high score (9 points) as they are clearly established in REACH as substances of very high concern, whereas suspected endocrine disrupters and neurotoxicants are given a lower but still precautionary score (7 points), as shown in Table 1. Scores were applied by effect. Hence one substance that is a carcinogen according to CLP Regulation and also according to IARC, will be given the score associated with the most conservative (and maximum) designation. The scores of all the effects were added. Substances with several health effects score higher as a total of all the scores added together.

Development of the list

The High Production Volume Chemicals list (step 2) was combined with the selected lists of substances with hazardous properties (step 1) and given a score (step 3). Substances exempted by REACH Regulation (speisses, mattes, sludge, slimes, drosses, skims, calcines and residues; substances that only have pesticide or biocide use; and some complex hydrocarbon distillates) or already banned by other means (EU Regulation 850/2004 on POPs) were removed from the list.

[19] However, naphthas (petroleum derivatives) have not been removed as they are widely used as solvents, which are within the scope of REACH authorisation and Refractory Ceramic Fibres (RCF) were also included in the TU list.

Substances considered or suspected to cause occupational diseases in the EU have been highlighted.

[20]

RESULTS

The resulting TU List includes 305 HPVC entries with at least one of the selected dangerous properties represented by its score. From this listing, 190 of these entries are substances or groups of substances associated with recognised occupational diseases and 52 entries are substances that cause diseases suspected of being occupational in origin. Table 2 includes an example of how substances are scored in the list and subsequently ranked. The complete TU list of 305 substances can be consulted in the electronic version of this paper at JECH website.

LIMITATIONS OF THE TU LIST

Prioritising substances of high concern has become a need for many governments or supra-governmental organizations which aim to implement legislative actions that will limit or prohibit the use of certain chemicals considered particularly dangerous to human health or to the environment. [START_REF] Ieh | A Review of Prioritisation Methodologies for Screening Chemicals with Potential Human Health Effects as a Result of Low-Level Exposure (Web Report W13)[END_REF] Several lists of extremely hazardous chemicals have been developed by governmental agencies or non governmental organizations with the common denominator of containing large lists of substances that are considered of special concern due to their negative effects on human health or the environment The Candidate List of 29 SVHC published by ECHA and the resultant Authorisation List (that may include 7 SVHC by mid 2010) are clearly insufficient to effectively and quickly fulfil the goals of REACH to protect the health and environment from highly hazardous chemicals. Many other substances which also meet the required criteria could have been included in the initial Candidate List, such as the 1,000 CMR substances on the official list of hazardous substances with a harmonised classification and labelling at the European Community level, .

Millions of European workers are exposed to chemical substances on a daily basis, not only during the production of these chemicals but also in the many downstream sectors where these substances are used. The European Trade Union Institute (ETUI) estimates that around one in three of all occupational diseases recognised in Europe each year is due to exposure to hazardous chemicals based on European Occupational Diseases Statistics and occupational disease prevalence data. [START_REF] Musu | REACHing the workplace. How workers stand to benefit from the new European policy on chemical agents[END_REF] Furthermore, it is estimated that each year among 35,000 and 45,000 workers die in Europe due to their exposure to carcinogens in the workplace. [START_REF] Kogevinas | Estimation of the burden of occupational cancer in Europe. Final Report to the European Commission of a project funded by the, programme "Europe Against Cancer[END_REF] The aim of the TU List is to urgently contribute to the debate about the number and choice of substances of very high concern for inclusion in the REACH authorisation procedure. However, the TU List has several limitations that should be considered.

Identification of SVHC for prioritisation

From a Trade Union point of view, several aspects should be considered when prioritising substances subject to the REACH authorisation process, such as intrinsic hazardous properties, relationship to occupational diseases, and human or environmental exposure. However, there is little or incomplete information on most of these factors. For example, EU Member States have completed only 138 risk assessment reports on individual substances with a wide set of toxicity and ecotoxicity data; EU registers on occupational diseases offer data on only a limited number of substances related to occupational diseases and data on environmental exposure is based mainly on estimations and do not cover all European countries. [START_REF]Summary if Existing Chemicals Risk Assessments[END_REF][START_REF]FIOH International Information System on Occupational Exposure to Carcinogens[END_REF][31][START_REF] Eea | European Pollutant Release and Transfer Register (E-PRTR)[END_REF] Taking into account the above limitations, the most reliable information that could be used to set up the priority list, was information on the intrinsic hazard properties of substances but this in itself is often incomplete for many endpoints such as disruption of the immune system, acute toxicity, depletion of ozone layer, and ecotoxicity, as examples.

Therefore, the list may not include substances of high toxicity or ecotoxicity that deserve attention from authorities and perhaps should also be eliminated from the market through the REACH authorisation process. However, only substances included in official EU and international publications or regulations have been taken into account and these documents are not regularly updated with available knowledge on toxicity.

REACH considers substances of very high concern (SVHC) as those meeting the criteria for classification as carcinogenic, mutagenic or toxic for reproduction (CMR) category 1A or 1B in accordance with CLP regulation. However, the TU List has also included substances identified by IARC as human carcinogens (IARC 1) and probable human carcinogens (IARC 2A). This is because the scientific evidence behind IARC reports is internationally recognized and strong enough to raise a level of concern equivalent to those substances classified as carcinogenic category 1A or 1B in CLP Regulation.

Taking a precautionary approach, the TU list also includes CMR substances category 2 according to the EU Regulation 1272/2008 as there is partial evidence (although not conclusive) of carcinogenicity, mutagenicity and toxicity for reproduction from appropriate human and animal studies. Other EU legislations have included restriction to these substances along the same reasoning. For example, Directive 76/768/EEC includes a provision in Article 4b that prohibits the use in cosmetic products of carcinogenic, mutagenic and substances that are toxic for reproduction (CMR) with category 1A, 1B and 2 as classified by CLP Regulation. [START_REF]Carcinogens. Notes for Guidance[END_REF][START_REF] Sccnfp | The Scientific Committee on Cosmetic Products and Non-Food Products Intended for Consumers opinion concerning chemical ingredients in cosmetic products classified as carcinogenic, mutagenic or toxic to reproduction according to the chemicals Directive 67/548/EEC[END_REF] Another limitation of the TU List is the number of neurotoxicants considered, since there is no available official data on substances that cause major permanent functional changes in the central or peripheral nervous system. CLP regulation only includes narcotic effects; therefore it does not have a classification for neurotoxicity itself nor specific hazardous statements.

For that reason, literature review was used to identify occupational neurotoxicants and add them to the list.

The TU List also includes the PBT list of the OSPAR Convention for the Protection of the Marine Environment of the North-East Atlantic. These substances do not meet all the PBT/vPvB criteria established in Annex XIII of REACH. However, scientific evidence behind the OSPAR list of PBT substances is strong enough to be considered as being of an equivalent level of concern to substances classified as PBT or vPvB by REACH. [START_REF]Guidance on identification of SVHC[END_REF] Because there is little or no publicly available toxicity data for 75.000 substances on the European market the 138 substances for which complete risk assessment reports have been published -and therefore have more complete available data -might be over-represented at the top of the Trade Union List. [START_REF]Chemicals in the European Environment: Low Doses High Stakes? The EEA and UNEP Annual Message on the State of Europe's Environment[END_REF] Other substances that have not gone through the EU risk assessment program may not be included in the TU List.

Errors leading to an underestimation of toxicity of certain substances might be introduced into the prioritisation scheme due to these data gaps.

Prioritisation criteria.

Because of the large number of chemicals produced annually, and their lack of fully comprehensive assessments of human exposure and possible health effects, it would be prudent to calculate an acceptable estimation of exposure with the available data. From a Trade Union point of view, it is important to choose substances widely used in the workplace, and, or, in different sectors. To find out which substances are widely used, we explored occupational exposure databases. However, it is complicated to find updated occupational exposure databases that cover all EU countries, and most of the existing databases are private. [START_REF] Fioh | CAREX-International Information System on Occupational Exposure to Carcinogens[END_REF]38] An additional source to obtain workers´ exposure data is the European list of occupational diseases. These substances have been marked in the list as stated previously.

The high production volume data used for this project was obtained from the Ex-European Chemicals Bureau and was published in 1999. This high production chemicals database was established by the Council Regulation 793/93, for substances produced in the European market between 1971 and 1981. [START_REF]No 793/93 of 23 March 1993 on the evaluation and control of the risks of existing substances[END_REF] Thus this information may not be properly updated and it is clear that many substances currently produced in high production volumes in Europe, are not considered in the TU List. For instance, triethyl arsenate, has been identified as a SVHC in the REACH Candidate list published by ECHA, but it is not in the TU List because it was registered after 1981 and it is not included in the Ex-ECB HPVC database. Another example of a substance not updated is musk xylene which is recommended by ECHA for inclusion in Annex XIV, although is registered as Low Production Volume Chemical (LPVC) in the Ex-ECB database.

Definition of scores for each criterion.

Confirmed PBTs and EDs were given the same rank (9) than possible CMRs (CMR 2) in the TU List although PBTs, CMRs and EDs are equally identified as SVHC under REACH. This decision was taken due to the high impact of cancer and reproductive disorders due to occupational exposure to CMR.

Development of the list.

RCF, or aluminium silicate wools, were included in the TU List although they were not included in the HPVC list. However 25,000 tonnes of these materials was used in Europe in 2005. About 25,000 workers are exposed annually in Europe to these types of high temperature wools. RCF have been also proposed by the Commission as candidate substances for which an Occupational Exposure Limit Value might be defined at EU level, signalling that they are recognized to be highly relevant for workers health. [START_REF]European Association representing the High Temperature Insulation Wool Industry (ECFIA) Website[END_REF]41] Recently, in January 2010, Zirconia Aluminosilicate Refractory Ceramic Fibres have been included in the REACH Candidate List.

Inclusion of substances linked to occupational diseases in REACH candidate and authorisation lists is crucial for the improvement of workers health. The list of substances considered or suspected to cause occupational diseases in the EU was used as a baseline since these substances are involved in scientifically recognised occupational diseases liable for compensation in most EU countries. Nevertheless, it is very difficult to relate with certainty an occupational disease to a particular substance. On the other hand, the procedure to include substances related with occupational diseases is long and complicated. Therefore, some widely used substances that are related with occupational diseases might not be included in our project. No specific scoring was applied to the substances capable of producing an occupational disease, since this approach would not have been consistent with the other criteria based on human and environmental endpoints.

CONCLUSIONS

Workers are exposed to substances of very high concern (SVHC) in their workplaces and for longer periods of time than the general population. Therefore, from a Trade Union point of view these SVHC must be targeted for priority action.

Experience with the ongoing pre-registration procedure in REACH now reveals that more chemicals are being pre-registered than anticipated. The list of pre-registered substances published in the ECHA Website contains more than 143,000 different substances (this is more than 2 times the 70,000 chemical substances and intermediates substances expected by the Commission when drawing up the REACH Regulation). These substances are being pre-registered as required based on their production volume and the hazardous properties of the substance. Approximately 50,000 different substances are envisaged to be registered by the 30 November 2010 deadline. These substances are thus being produced in more than 1,000 t/y, and are carcinogenic, mutagenic or toxic for reproduction (CMR) in categories 1A or 1B produced in more than 1 t/y; or very toxic to aquatic life and very toxic to aquatic life with long lasting effects (H400/H410) produced in more than 100 t/y. Based on such criteria, these substances are directly related to workers´ exposure or can be considered as substances of very high concern.

Of this total, 38,500 substances are estimated to be produced in more than 1,000 tonnes per year. If this new data is compared with the 2,782 substances previously covered by the Ex-European Chemicals Bureau (Ex-ECB) HPVC database, it becomes clear that the number and the amount of highly produced substances are dramatically increasing in Europe. This signals that a revision of the TU List should be the list of substances registered under REACH and published by ECHA. The REACH registration process will potentially deliver information on uses and exposure scenarios for substances produced or imported in more than 10 t/y and this information will begin to be accessible by the end of 2010.

At the time the TU List was developed it had 88 substances in common with the SIN List 1.0, the other list also developed to influence the REACH authorisation process. [START_REF] Chemsec | SIN (Substitute It Now!) LIST. The International Chemical Secretariat (ChemSec)[END_REF] The SIN List 1.0 included 267 chemicals of high concern and used commonly in consumer goods (which has now expanded to 356 substances and substance groups in the revised version updated in October 2009). The main difference between the two lists is that the TU List takes into account the specific issues concerning workers´ health in the workplace, applies a precautionary approach towards chemicals 'suspected' of certain harmful effects, and includes a proposal for ranking SVHC. Both lists however, combined together to total 484 substances, consist of substances that present well known risks to human health and the environment, and should consequently be included in the REACH candidate lists and substituted as soon as possible with safer alternatives. It is noteworthy that 66 of these common substances are linked to occupational diseases.

Including the TU List into the REACH Candidate List will improve information on the risks of these substances and how to control them throughout the supply chain, as suppliers of these substances or mixtures have the obligation to provide safety data sheets and distributors of articles containing these substances have the obligation to inform consumers of the presence of any authorised chemicals in the products they buy and how to use them safely. Substances that already have a harmonised classification would not need a complete Annex XV authorisation dossier. Therefore, including them in the Candidate List would have an important impact on the protection of human health and the environment and would not excessively impact ECHA's limited resources.

Furthermore, 74,000 workers die each year from exposure to pollutants at work in EU-27. [START_REF]Report -Expert forecast on emerging chemical risks related to occupational safety and health[END_REF] Including the TU list into both the REACH candidate and authorisation lists would promote the development of safer alternatives and reduce the incidence of chemical-related occupational diseases and the attendant costs for communities, workers and industry itself.

In this paper, we present a precautionary but scientifically aligned process for identifying, scoring and ranking Substances of Very High Concern including categories of substances not currently considered in other approaches to the REACH regulation. This proposed methodology is advocated by Trade Unions to coherently prioritise SVHC in order to implement and enforce REACH in a way that will more effectively protect the health of the European working and general population. [START_REF] Musu | How workers stand to benefit from REACH?[END_REF]

  may cause cancer) and H351 (suspected of causing cancer). Hazard statement is a phrase assigned to a hazard class and category that describes the nature of the hazards of a substance or mixture, including, where appropriate, the degree of hazard.[START_REF]Parliament and of the Council of 16 December 2008 on classification, labelling and packaging of substances and mixtures[END_REF]7] Substances classified by the International Agency for Research on Cancer (IARC) as human carcinogens (IARC 1), that are probable human carcinogens (IARC 2A) and that are possible human carcinogens (IARC 2B).[START_REF]IARC Monographs on the evaluation of carcinogenic risks to humans[END_REF]

	Mutagenic substances
	Substances classified as mutagenic category 1A, 1B and 2 in accordance with CLP Regulation (categories 1, 2 and 3
	in accordance with Directive 67/548/EEC) identified in Annex VI with hazard statements H340 (may cause genetic
	defects) and H341 (suspected of causing genetic defects).
	Substances that are toxic for reproduction
	Substances classified as toxic for reproduction category 1A, 1B or 2 in accordance with CLP Regulation (categories
	1, 2 and 3 in accordance with Directive 67/548/EEC) identified in Annex VI with hazard statements H360 (may damage fertility or the unborn child), H361 (suspected of damaging fertility or the unborn child).
	Persistent, Bioaccumulative and Toxic substances (PBT) and very Persistent and very Bioaccumulative substances (vPvB).
	PBT list of the OSPAR Convention for the Protection of the Marine Environment of the North-East Atlantic.[9]
	1. Identification of SVHC for prioritisation.
	2. Prioritisation criteria.
	3. Definition of scores for each criterion.
	4. Development of the list.
	1. Identification of SVHC for prioritisation

SVHC included in the TU

List were: Carcinogenic substances Substances classified as category 1A, 1B and 2 in accordance with EU Regulation 1272/2008, so called CLP Regulation (categories 1, 2 and 3 in accordance with Directive 67/548/EEC) identified in Annex VI with hazard statements H350 (

Table 1 .

 1 Health and environmental effect scores, used by European Union Risk Ranking Method (EURAM) and the Trade Union Priority List.

	SUBSTANCES	EURAM score TU List score
	EU Carcinogens cat. 1A or 1B	10	10
	IARC Carcinogens 1 or 2A group		10
	EU Mutagens cat.1A or 1B	10	10
	EU Reprotoxicants cat.1A or 1B	10	10
	EU known Endocrine Disrupters		9
	PBT		9
	EU Carcinogens cat.2	9	9
	IARC Carcinogens 2B group		9
	EU Mutagens cat. 2	9	9
	EU Reprotoxicants cat.2	9	9
	Sensitizers by skin contact	6	7
	Sensitizers by inhalation	7	7
	Neurotoxicants		7
	EU suspected Endocrine Disrupters		7

Table 2 .

 2 Examples of the scoring system used in the Trade Union Priority List for REACH Authorisation: selected substances from a total of 305 entries in the List.

	Name	C 1A,1B	IARC 1, 2A	M 1A,1B	R 1A, 1B	ED 1	PBT / vPvB	C 2, IARC 2B	M 2 R 2 S N ED 2 TOTAL
	acrylamide	10	0	10					9	7 7	43
	nitrotoluene * 10		10		9			9	38
	diphenyl ether, derivative octabromo				10	9	9	9		37
	sodium chromates * 10	0	10	10					7	37
	bisphenol A					9	9		9	7	34
	styrene					9		9		7	25
	* : several isomers of this group might have different extent (or lack) of available test data. In those cases, most hazardous substance was taken as a reference for
	the whole group.
	C 1A, 1B: Carcinogen Category 1A or 1B according to EU Regulation 1272/2008 classification criteria
	C2: Carcinogen Category 2 according to EU Regulation 1272/2008 classification criteria IARC 1: Human carcinogen according to IARC criteria
	IARC 2A: Probable human carcinogen according to IARC criteria
	IARC 2B: Possible human carcinogen according to IARC criteria
	M 1A, 1B: Mutagen category 1A or 1B according to EU Regulation 1272/2008 classification criteria M2: Mutagen category 2 according to EU Regulation 1272/2008 classification criteria
	R 1A, 1B: Reprotoxic category 1A, 1B according to EU Regulation 1272/2008 classification criteria

R2: Reprotoxic category 2 according to EU Regulation 1272/2008 classification criteria ED1: Known to be endocrine disrupter according with Community Strategy for Endocrine Disrupters ED2: Suspected to be endocrine disrupter according with Community Strategy for Endocrine Disrupters PBT: Toxic, Persistent and Bioaccumulative N: neurotoxicant S: sensitizer

  . Some examples are the Extremely Hazardous Substance List of the United States Environmental Protection Agency (US-EPA); the List of Undesirable Substances of the Danish Environmental Protection Agency (EPA); the Priority Substances List of Environment Canada; the PRIO database of the Swedish Chemicals Inspectorate and the Substitute It Now! List (SIN List) developed by ChemSec together with a group of European NGOs.[START_REF] Us Epa | Extremely Hazardous Substances List and Threshold Planning Quantities[END_REF][START_REF]List of Undesirable Substances[END_REF][START_REF]Priority Substances List[END_REF][START_REF] Kemi | PRIO -a tool for risk reduction of chemicals[END_REF][START_REF] Chemsec | SIN (Substitute It Now!) LIST. The International Chemical Secretariat (ChemSec)[END_REF]

Acknowledgements

We thank Ana M García (ISTAS, University of Valencia, Spain) and Beverley Thorpe (Clean Production Action, Canada) for their thorough review and useful comments on a previous version of the manuscript. We thank Tony Musu, Henning Wriedt, and Emilio Gatti for their contributions during the development of the Trade Union List.

Competing Interest: None declared.

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Programme Leader Alastair H Leyland
email: a.leyland@sphsu.mrc.ac.uk

Ruth Dundas

The social patterning of deaths due to assault in Scotland, 1980-2005: population based study

Objectives: To explore the extent of the social gradient for deaths due to assault and its impact on overall inequalities in mortality. To investigate the contribution to assault mortality of knives and other sharp weapons. Design: Analysis of death records and contemporaneous population estimates. Setting: Scotland Participants: Deaths between 1980 and 2005 due to assault. Main measurements: Mortality rates were standardised to the European standard population. Time trends were analysed and inequalities were assessed, using rate ratios and the slope index of inequality, along axes defined by individual occupational socioeconomic status and area deprivation. Results: An increase in mortality due to assault was most pronounced at ages 15-44 and was steeper among assaults involving knives. The mortality rate among men in routine occupations aged 20-59 was nearly 12 times that of those in higher managerial and professional occupations. Men under 65 living in the most deprived quintile of areas had a mortality rate due to assault 31.9 times (95% C.I. 13.1-77.9) that of those living in the least deprived quintile; for women this ratio was 35.0 (4.8-256.2). Despite comprising just 3.2% of all male deaths between 15-44 years, assault accounted for 6.4% of the inequalities in mortality. Conclusions: Inequalities in mortality due to assault in Scotland exceed those in other countries and are greater than for other causes of death in Scotland. Reducing mortality and inequalities depends on addressing the problems of deprivation as well as targeting known contributors such as alcohol use, the carrying of knives and gang culture.

INTRODUCTION

The homicide rate in Scotland has been increasing since 1980. [START_REF] Leyland | Homicides involving knives and other sharp objects in Scotland, 1981-2003[END_REF] This increase has accompanied rising mortality rates due to suicide (among men), chronic liver disease, and mental and behavioural disorders due to the use of drugs and alcohol. [START_REF] Leyland | Inequalities in mortality in Scotland, 1981-2001[END_REF][START_REF] Leyland | Cause-specific inequalities in mortality in Scotland: two decades of change. A population-based study[END_REF] The changes in mortality from these causes have been most noticeable amongst younger adults, particularly young men, for whom the effect has been so strong that all cause mortality rates at these ages have begun to rise. [START_REF] Mcloone | Increasing mortality among adults in Scotland 1981 to 1999[END_REF] Much of the previous research on the social patterning of homicide has been conducted in the USA; this has shown the victims of homicide to be more likely to be drawn from certain social groups: generally, homicide rates are higher among black [START_REF] Cubbin | Socioeconomic status and the occurrence of fatal and nonfatal injury in the United States[END_REF][START_REF] Cubbin | Socioeconomic status and injury mortality: individual and neighbourhood determinants[END_REF][START_REF] Cubbin | Social context and geographic patterns of homicide among US black and white males[END_REF][START_REF] Howard | Race, socioeconomic status, and cause-specific mortality[END_REF][START_REF] Krueger | Neighbourhoods and homicide mortality: an analysis of race/ethnic differences[END_REF], low income [START_REF] Cubbin | Socioeconomic status and the occurrence of fatal and nonfatal injury in the United States[END_REF][START_REF] Krueger | Neighbourhoods and homicide mortality: an analysis of race/ethnic differences[END_REF], poorly educated [START_REF] Cubbin | Socioeconomic status and the occurrence of fatal and nonfatal injury in the United States[END_REF][START_REF] Cubbin | Socioeconomic status and injury mortality: individual and neighbourhood determinants[END_REF][START_REF] Krueger | Neighbourhoods and homicide mortality: an analysis of race/ethnic differences[END_REF], unemployed [START_REF] Cubbin | Socioeconomic status and the occurrence of fatal and nonfatal injury in the United States[END_REF][START_REF] Cubbin | Socioeconomic status and injury mortality: individual and neighbourhood determinants[END_REF][START_REF] Krueger | Neighbourhoods and homicide mortality: an analysis of race/ethnic differences[END_REF], and manual workers. [START_REF] Howard | Race, socioeconomic status, and cause-specific mortality[END_REF][START_REF] Wilkinson | Mortality, the social environment, crime and violence[END_REF] Research from Finland has also noted elevated rates among the unemployed and manual workers [START_REF] Kivivuori | The social composition of homicide in Finland, 1960-2000[END_REF], and in Sweden there was an association with early life socioeconomic position. [START_REF] Lawlor | Association of childhood socioeconomic position with cause-specific mortality in a prospective record linkage study of 1,839,384 individuals[END_REF] Area characteristics with noted associations with homicide rates include degree of urbanisation (USA) [START_REF] Cubbin | Social context and geographic patterns of homicide among US black and white males[END_REF], income inequality (USA and internationally) [START_REF] Cubbin | Social context and geographic patterns of homicide among US black and white males[END_REF][START_REF] Krueger | Neighbourhoods and homicide mortality: an analysis of race/ethnic differences[END_REF][START_REF] Wilkinson | Mortality, the social environment, crime and violence[END_REF][START_REF] Pickett | Adolescent birth rates, total homicides, and income inequality in rich countries[END_REF], per capita income (USA) [START_REF] Cubbin | Socioeconomic status and injury mortality: individual and neighbourhood determinants[END_REF], and deprivation or poverty (USA, the Netherlands and Great Britain). [START_REF] Cubbin | Socioeconomic status and injury mortality: individual and neighbourhood determinants[END_REF][START_REF] Krueger | Neighbourhoods and homicide mortality: an analysis of race/ethnic differences[END_REF][START_REF] Middelkoop | Urban cause-specific socioeconomic mortality differences. Which causes of death contribute most?[END_REF][START_REF] Shaw | Increasing inequalities in risk of murder in Britain: trends in the demographic and spatial distribution of murder, 1981-2000[END_REF] The effect of homicide on social inequalities in mortality may be disproportionate. The (area-based) socioeconomic gradient for homicide was shown to be steeper than for many other causes of death in the Hague and, although contributing just 1.3% and 0.7% of all male and female deaths under 65, contributed 6.4% and 3.9% of the excess mortality in the quartile of regions with the highest deprivation scores compared to the quartile with the lowest scores. [START_REF] Middelkoop | Urban cause-specific socioeconomic mortality differences. Which causes of death contribute most?[END_REF] In New York City inequalities patterned by neighbourhood poverty (as measured by the relative index of inequality, RII), for men and women combined, were 1.7 for all causes and 9.0 for homicide. [START_REF] Karpati | Neighbourhood mortality inequalities in New York City, 1989-1991 and 1999-2001[END_REF] Neither study reported the significance of these results. In Sweden, males with manual social class in early life had a hazard ratio of death from homicide of 2.11 compared to those with non-manual social class; for all cause mortality the ratio was 1.31. For women the ratios were 1.40 and 1.18 respectively. [START_REF] Lawlor | Association of childhood socioeconomic position with cause-specific mortality in a prospective record linkage study of 1,839,384 individuals[END_REF] This difference was significant for men but not for women. In Estonia the rate ratio for homicide mortality comparing the lowest educated group to those with university education (2.21) was about the same as that for all cause mortality (2.38) among men, whilst the homicide rate ratio for women (5.46) was higher than that for all causes (2.23), although the difference was not significant. [START_REF] Leinsalu | Estonia 1989-2000: enormous increase in mortality differences by education[END_REF] Earlier research has shown the increasing importance of homicides involving the use of knives or other sharp weapons among all homicides in Scotland. [START_REF] Leyland | Homicides involving knives and other sharp objects in Scotland, 1981-2003[END_REF] Whilst the male homicide rate increased by 83% between 1982 and 2002, the rate involving knives or similar increased by 164% and more than trebled for those aged 15 to 34. Between 1983 and 1998 inequalities in homicide in Britain increased as homicide rates decreased in the more affluent areas whilst increasing in the more deprived areas. [START_REF] Shaw | Increasing inequalities in risk of murder in Britain: trends in the demographic and spatial distribution of murder, 1981-2000[END_REF] Over this period the rate ratio in the poorest decile compared to the richest increased from 4.50 to 5.68. Murders involving a knife or a broken glass/bottle showed a social gradient [START_REF] Shaw | Increasing inequalities in risk of murder in Britain: trends in the demographic and spatial distribution of murder, 1981-2000[END_REF], such a method constituting 52% of all homicide deaths in the poorest decile but only about 35% in the least poor decile. Given the high proportion of deprived areas that lie within Scotland, and the West of Scotland in particular, and the high rate of homicides involving knives in Scotland (47% in Scotland between 1981 and 2003 [START_REF] Leyland | Homicides involving knives and other sharp objects in Scotland, 1981-2003[END_REF] compared to 38% in England and Wales between 1993 and 1997 [START_REF] Rooney | Recent trends in deaths from homicide in England and Wales[END_REF]), it is possible that the social gradient reported reflects in part this high Scottish rate. The importance of knife use in assaults and homicides has led to policy changes or proposals targeting knives, including the licensing of the sale of non-domestic knives [START_REF]Knives licensing[END_REF] and a ban on the sale of all long pointed kitchen knives. [START_REF] Hern | Reducing knife crime[END_REF] It is against this background that we investigate the social patterning of homicide in Scotland between 1980 and 2005, both by individual socioeconomic status and by area-based measures of deprivation. We explore the extent to which inequalities in homicide have increased, the extent to which this may be attributable to homicide involving the use of knives or other sharp weapons, and the contribution of homicide to all cause mortality and to inequalities in mortality.

METHODS

Data

The analyses presented in this paper are based on death records for Scotland for the years 1980-82, 1990-92 and 2000-05, obtained from the General Register Office for Scotland (GROS). Information on the death certificates includes the age and sex of the deceased as well as the cause of death and a measure of individual socioeconomic status. They also contain the postcode of residence of the deceased, enabling linkage to area-based deprivation scores. The estimation of rates for population groups defined by area of residence requires denominator populations in addition to the events (deaths); for this reason small area population estimates for these years by age and sex were also obtained from GROS.

Homicides were defined as deaths where the underlying cause was homicide and injury purposely inflicted by other persons (ICD9 E960-E969) or assault or sequelae of assault (ICD10 X85-Y09 & Y87.1). We conducted separate analyses for deaths where the cause was assault by a cutting or piercing instrument (ICD9 E966) or assault by sharp object (ICD10 X99).

The measure of individual socioeconomic status that we have used is the National Statistics SocioEconomic Classification (NS-SEC). [START_REF] Rose | The NS-SEC: Origins, development and use[END_REF] NS-SEC is based on occupation and employment status but has rules to provide coverage of the whole adult population. It is constructed to measure employment relations and conditions of employment. There are several versions of the classification and the one used here has 8 classes (subsequently detailed in table 2, together with those who could not be classified). [START_REF]The National Statistics Socio-economic Classification (NS-SEC) User Manual[END_REF] The proportion of the population assigned an NS-SEC from age 60 is low and so becomes unreliable to use. In addition the completeness of NS-SEC for ages 16-19 is also low due to delayed entry into the labour market. [START_REF] Leyland | Inequalities in mortality in Scotland, 1981-2001[END_REF] For these reasons, analyses using NS-SEC focused on the age group 20-59. Earlier results have cast doubt on the reliability of NS-SEC coding for the analysis of female mortality [START_REF] Leyland | Inequalities in mortality in Scotland, 1981-2001[END_REF], and we therefore restrict the analysis to men. Population estimates by NS-SEC were only available from the 2001 population Census (earlier Censuses used the alternative Social Class based on Occupation); we use these estimates for men aged 20-59 to standardise the male mortality rate by NS-SEC.

We used two different measures of area deprivation. The Carstairs score is a Censusbased deprivation score derived from levels of male unemployment, social class of the head of household, overcrowding and (lack of) car ownership, and has been calculated by adding together the standardised values of the variables following the 1981, 1991 and 2001 Censuses. [START_REF] Carstairs | Deprivation and Health in Scotland[END_REF][START_REF] Mcloone | Carstairs scores for Scottish postcode sectors from the 1991 Census[END_REF][START_REF] Mcloone | Carstairs scores for Scottish postcode sectors from the 2001 Census[END_REF] The continuous score was used to divide areas into (population-weighted) quintiles. The income domain of the Scottish Index of Multiple Deprivation (SIMD) is based on the proportion of the population living in households in receipt of means-tested benefits, and was calculated based on the numbers claiming different allowances or benefits in 2001 and 2004. [START_REF] Executive | Scottish Index of Multiple Deprivation 2004: summary technical report[END_REF][START_REF] Executive | Scottish Index of Multiple Deprivation 2006: General Report[END_REF] Areas were ranked and these ranks were used to divide areas into (population-weighted) quintiles.

In 2001 the population of Scotland was 5,062,011. The Carstairs score is calculated for postcode sectors; in 2001 there were 1010 postcode sectors in Scotland (including part postcode sectors when their boundaries crossed Local Council Areas) with a mean population of 5012 (range 51-20,512). The SIMD uses a geographical area with lower mean population size and less variability in population size, the data zone; in 2001 there were 6505 data zones in Scotland with a mean population of 778 (range 476-2813). To match populations to these deprivation measures we used Census populations for 1981, 1991 and 2001 by age, sex and postcode sector; Census populations for 2001 by age, sex and data zone; and GROS population estimates for 2004 by age, sex and data zone. We confined the area-based analyses around the 1991 Census to 1991-92 because of difficulties matching addresses on death records and the Census following changes to some postcode sectors in 1990.

Statistical methods

All mortality rates and 95% Confidence Intervals (CIs) were calculated by direct standardisation to the European standard population for men and women by age group for the selected years. [START_REF] Clayton | Statistical Models in Epidemiology[END_REF] Standardised rates were also calculated for population groups defined by NS-SEC group or quintile of area deprivation. All rates reported were per million population per year. P-values indicating the significance of trends over time or across deprivation quintiles were calculated using Poisson regression. Tests for trends were not appropriate for the analysis by NS-SEC group since this classification is not hierarchical or ordered [START_REF] Rose | The NS-SEC: Origins, development and use[END_REF], so tests of the differences between groups were conducted instead. Rate ratios and 95% CIs were calculated to show the extent of inequality at each time by making comparisons between the populations living in each of the most and least deprived quintiles and the population living in the middle three quintiles. [START_REF] Rothman | Modern Epidemiology[END_REF] P-values indicating the significance of differences in the trends over time (from 1981 to 2001) in deaths in the most or least deprived quintile (assessed using the Carstairs score), relative to the population in the middle three quintiles, were calculated using Poisson regression. Finally, we calculated the slope index of inequality (SII) across quintiles of the income domain of the SIMD by age and sex for 2000-02, for all causes and for homicides, and used this to assess the proportion of the inequality in mortality that was attributable to homicide. [START_REF] Regidor | Measures of health inequalities: part 2[END_REF] We chose to examine the relative contribution of homicides to inequalities in all cause mortality for the period 2000-02 because this was the most recent period for which we were able to use populations derived from the Census rather than from estimates.

RESULTS

Based on the analysis of 1109 deaths due to assault in the 12 years covered, table 1 presents mortality rates by age and sex, with deaths due to assault further broken down into those due to the use of knives and other sharp objects and other assaults. Also shown are the total number of deaths by cause and sex in each three year period and p-values indicating the significance of trends over time. Mortality rates under the age of 1 remained high, supporting an analysis of infanticide that is separate from other forms of homicide. [START_REF] Kivivuori | The social composition of homicide in Finland, 1960-2000[END_REF] Male rates tended to be higher between the ages of 15 and 44 than at other ages, and at these ages the rate more than doubled between 1980-82 and 2003-05. Most of these deaths, and most of the increase, can be seen to be attributable to assaults involving sharp objects; however, the increase in the all age mortality rate associated with other assaults also showed a significant increase. Female mortality rates were much lower than male rates and were not dominated by sharp objects as male rates were. The all age mortality rate showed a significant decrease over time due to decreases at older ages.

Table 2 shows mortality rates by age and NS-SEC for men in Scotland in 2000-2002. The table also shows the number and proportion of the population in each NS-SEC category. Steep social gradients are evident, with the rate among those in routine occupations (127 per 1,000,000 population) being nearly 12 times that of those in higher managerial and professional occupations [START_REF] Kivivuori | The social composition of homicide in Finland, 1960-2000[END_REF]. The gradient was steeper for those aged 20-39 than at ages 40-59, and was also steeper for assaults involving sharp objects. Table 2 highlights the fact that the 193,473 men in routine occupations form a particularly vulnerable group, with rates being more than double those for men in semi-routine occupations. Differences between the NS-SEC groups were significant for both age groups and for assaults involving sharp objects and other assaults. High rates are also evident for the 9% of men whose occupations could not be classified (particularly at ages 20-39), but the rather low rate for the 4% who had never worked or were long-term unemployed illustrates the extent of our concerns about the coding to NS-SEC differing between death certificates and the Census. The information collected on death records in Scotland is not able to distinguish those who have never worked or are long-term unemployed with any accuracy; similar findings have been reported for England & Wales. [START_REF] White | Social inequalities in adult male mortality by the National Statistics Socio-economic classification, England and Wales, 2001-03[END_REF] Table 3 examines inequalities in male and female deaths according to area-based deprivation and how these have changed over time. The measures used are rate ratios comparing the rates in each of the most deprived quintile (quintile 5) and the least deprived quintile (quintile 1) with the rates in the middle three quintiles. Changes in the rate ratios for all assaults between 1980-82 and 2000-02, based on the Carstairs score for postcode sectors, showed the relative experience of those living in the most deprived quintile little changed with male rates typically 3-4 times those in the middle 3 quintiles and female rates 2-2.5 times. In contrast, the rate ratio for men of all ages in the least deprived quintile fell from 0.86 in 1980-82 to 0.28 in 2000-02 (p=0.022). Relative to the middle three quintiles, the rate ratio in the most deprived quintile for assaults involving sharp objects decreased over time (p=0.035), although in 2000-02 the rate ratio was still 3.38 (95% C.I. 2.27-5.03). No other trends were significant. When area deprivation was assessed for data zones using the SIMD income domain in 2000-02 there was a notable tendency for inequalities to be wider than for postcode sectors assessed using the Carstairs score in the same period, with the rate ratios assessed using the SIMD for the most deprived areas mostly higher and those for the least deprived areas tending to be lower. This is likely to be a result of the smaller area employed by the SIMD with its consequent ability to identify pockets of deprivation set in (relatively) more affluent surroundings and the consequent homogeneity afforded by a classification based on data zones.

Figure 1 shows how deaths that are due to assault vary as a proportion of all deaths by age for men in 2000-02. Although representing just 0.3% of male deaths at all ages, assault accounts for 1.0% of deaths under the age of 65 and 3.2% between the ages of 15 and 44. Also shown in figure 1 is the percentage of inequalities in mortality at each age that is due to assault. The fact that the contribution to inequalities is greater than the proportion of deaths reflects the steeper social gradient that is seen for deaths due to assault than for other causes. Assault accounts for 1.1% of inequalities in male mortality at all ages, rising to 2.4% under 65 and 6.4% between the ages of 15 and 44.

DISCUSSION

Mortality rates in Scotland due to assault are high; the all age rates in table 1 of 32 and 8 per 1,000,000 men and women respectively in 2000-02 compare very unfavourably with rates of 14 and 6 per 1,000,000 for high income countries in the European region in 2000. [START_REF]World report on violence and health[END_REF] The steep social gradient is a notable feature of mortality due to assault in Scotland as in other countries. The extremely high mortality rate seen among men of working age in routine occupations (127 per 1,000,000) is comparable to the Scottish mortality rate for stroke amongst men of this age and higher than the mortality rate for colorectal cancer. [START_REF] Leyland | Inequalities in mortality in Scotland, 1981-2001[END_REF] Although it is not possible to make direct comparisons between tables 2 and 3, inequalities (as measured by the ratio) between the most and least deprived quintiles as measured by SIMD appear stronger than those between routine occupations and higher managerial and professional occupations. For all assaults in 2000-02 the lowest rate ratio between the most and least deprived quintile by age group was that seen for all ages (RR=5.19/0.27=19.2); by contrast, the highest rate ratio between the extreme groups of NS-SEC was 13.5 (=150/11) for those aged 20-39. Whilst it is possible that the results would differ if other individual and area socioeconomic factors were employed, we believe that this work suggests that contextual influences of the neighbourhood of residence might be more important than individual characteristics in determining the victims of assault. However, we have previously noted the mismatch between the coding of NS-SEC from death certificates and that from the Census [START_REF] Leyland | Inequalities in mortality in Scotland, 1981-2001[END_REF], and for this reason are cautious about placing too much emphasis on the interpretation of the results by individual socioeconomic status. Furthermore, formal separation of the contextual and compositional effects can only be conducted in a multilevel framework.

Mortality rates due to assault in the most deprived areas have not deteriorated significantly over time relative to those in the middle three quintiles. The only significant increase in inequalities has been the widening of the gap between the least deprived areas and the rest of Scotland. However, the magnitude of the inequalities seen -patterned by the deprivation level of the area of residence -is extreme. Between 2000-02 a man under 65 living in the most deprived quintile was 31.9 (95% C.I. 13.1-77.9) times more likely to die due to assault than one living in the most affluent quintile; for women this ratio was 35.0 (4.8-256.2). The equivalent rate ratios for all-cause mortality were 3.5 (3.3-3.6) and 2.6 (2.5-2.8) for men and women respectively. Not only do these inequalities for assault exceed those for other causes of death in Scotland, they far exceed the ratio reported for homicide in Great Britain [START_REF] Shaw | Increasing inequalities in risk of murder in Britain: trends in the demographic and spatial distribution of murder, 1981-2000[END_REF] (5.7 comparing the top and bottom deciles, 1996-2000) and that for emergency hospital admissions for assault in England [START_REF] Bellis | Contribution of violence to health inequalities in England: demographics and trends in emergency hospital admissions for assault[END_REF] (6.3 comparing the top and bottom quintiles in 2005-06). The reasons for the different findings are unclear; the measures reported in these studies have some differences (for example, both refer to men and women combined and to all ages) but these could not account for the stark inequalities observed in Scotland. Earlier research has suggested that inequalities in all cause mortality are wider in Scotland than in the rest of Britain; the Scottish excess mortality in 2001 ranged from 2% in the least deprived decile to 17% in the most. [START_REF] Hanlon | Why is mortality higher in Scotland than in England and Wales? Decreasing influence of socioeconomic deprivation between 1981 and 2001 supports the existence of a 'Scottish Effect[END_REF] It is possible that the greater inequalities in mortality due to assault in Scotland reflect greater social inequalities and more acute deprivation. The prioritisation of the harm caused by violence in the Scottish Government's report of the ministerial task force on health inequalities [START_REF] Equally | Report of the ministerial task force on health inequalities[END_REF] is recognition that the small numbers of deaths have a marked impact on inequalities, particularly amongst young men.

Maxwell et al showed that whilst in a single year from April 2004 to March 2005, 4891 patients were admitted to hospital in England with an assault-related stabbing injury, there were just 139 deaths in 2004 due to assault from a sharp object. [START_REF] Maxwell | Trends in admission to hospital involving an assault using a knife or other sharp instrument, England, 1997-2005[END_REF] This figure of 35 victims requiring hospital treatment for every homicide fits in with an estimated range of 20-40 for youth violence internationally. [START_REF] Mercy | Youth violence[END_REF] The suggestion that there might be so many hospital admissions for every fatality means that the analysis presented in this paper probably represents no more than the tip of the iceberg in terms of the number of events. Throughout Scotland it has been estimated that "Violence costs the Scottish economy around £3 billion each year in health care, law enforcement and lost productivity". [START_REF]Violence reduction unit[END_REF] What are the known correlates of violent behaviour? Alcohol and drug use have been shown to contribute to homicides and to violence more generally. Shaw et al estimated that alcohol or drugs (taken by the perpetrator) contributed to 45% of a national sample of homicides in England and Wales collected over three years between 1996 and 1999 [START_REF] Shaw | The role of alcohol and drugs in homicides in England and Wales[END_REF], although they believed this figure to be conservative. A similar level of alcohol use was reported in several international studies of homicide. [START_REF] Brookman | Reducing homicide: a review of the possibilities[END_REF] More generally, alcohol use has been shown to contribute to violent behaviour among adolescents [START_REF] Rossow | Young, wet and wild? Associations between alcohol intoxication and violent behaviour in adolescence[END_REF], whilst in Scotland school children who used drugs were more likely to carry weapons. [START_REF] Mckeganey | Association between illegal drugs and weapon carrying in young people in Scotland: schools' survey[END_REF] Social correlates have also been promoted; Heath suggested that carrying a knife is another dimension of poverty. [START_REF] Heath | R-E-S-P-E-C-T -find out what it means[END_REF] The existence of inequalities between social groups has been recognised as an important risk factor for violence [START_REF] Rutherford | Violence: a priority for public health? (part 2)[END_REF], and an ecological cross-national study showed a negative correlation between GNP per capita and a country's homicide rate. [START_REF] Moniruzzaman | Age-and sex-specific analysis of homicide mortality as a function of economic development: a cross-national comparison[END_REF] So what can be done about the high homicide rate and the associated inequalities? Brookman and Maguire made a range of policy recommendations for the reduction of homicides in the categories of domestic homicide, the killing of infants, alcohol-related homicide, and homicide with guns or knives. [START_REF] Brookman | Reducing homicide: a review of the possibilities[END_REF] The Scottish Government is already seeking ways to reduce alcohol-related problems including violence. [START_REF]Changing Scotland's relationship with alcohol: a discussion paper on our strategic approach[END_REF] As a means of reducing knife crime, Hern et al advocated a ban on the sale of long pointed knives [START_REF] Hern | Reducing knife crime[END_REF], something that could be considered in Scotland given the considerable role that knives play. For interventions to reduce youth violence to succeed, Kellermann et al recommended that they should take place before the age of 6 years and must either address multiple risk factors simultaneously or else should be tailored for specific target groups. [START_REF] Kellermann | Preventing youth violence: what works?[END_REF] Addressing the gang culture is an example of such a targeted approach. [START_REF] Kmietowicz | Glasgow gang members offered way out of violent lifestyle[END_REF] But the extent of the inequalities seen for assault in Scotland, coupled with high mortality rates for causes associated with alcohol and drug use and mental wellbeing among the most disadvantaged groups, emphasises the need to understand and address the multiplicity of problems associated with deprivation and poverty.

Our study has demonstrated the extent of inequalities in deaths due to assault in Scotland and the role played by knives and other sharp weapons. Although we have no information on the perpetrators of the assaults from death records, we have offered a comprehensive insight into the inequalities that occur and the extent to which they are patterned by socioeconomic circumstances.

• Social inequalities in mortality due to assault in Scotland are of far greater magnitude than those reported elsewhere. • The scale of these inequalities means that any attempt to address inequalities in mortality in Scotland -particularly amongst young men -must tackle the problem of assault, particularly that involving knives and other sharp weapons.

Table and figure captions

Table 1 Male and female standardised mortality rates per 1,000,000 population due to assault, assault involving sharp weapons and other assaults, Scotland, 1980-82, 1990-92, 2000-02 and 2003-05.

Table 2 Standardised mortality rates per 1,000,000 population due to assault, assault involving sharp weapons and other assaults, by NS-SEC category. Men, Scotland, 2000-02.

Table 3 Age-specific mortality rate ratios due to assault, assault involving sharp weapons and other assaults, for most and least deprived quintiles relative to the middle 3 quintiles. Men and women, Scotland, 1980-82, 1991-92 and 2000-02 based on Carstairs scores; 2000-02 and 2003-05 based on SIMD income domain.

Figure 1 Proportion of all male deaths that were due to assault (bars) and the proportion of inequalities in mortality due to assault (line), by age, Scotland 2000-02.

  Figure 1

Table 1

 1

	Age
	group			Assault				Sharp weapon				Other assault
	Male	1980-82 1990-92 2000-02	2003-05 p		1980-82 1990-92	2000-02 2003-05 p		1980-82 1990-92 2000-02 2003-05 p
	<1	40	70	59	37	0.973	0	0	0	0		40	70	59	37	0.973
		(1-80) (18-122)	(7-110)	(0-79)							(1-80) (18-122)	(7-110)	(0-79)
	1-4	13	15	9	3	0.209	3	0	0	0		10	15	9	3	0.346
		(2-24)	(3-27)	(0-19)	(0-9)		(0-7)					(0-20)	(3-27)	(0-19)	(0-9)
	5-14	3	4	2	2	0.473	1	1	0	0	0.324	2	3	2	2	0.765
		(0-6)	(0-8)	(0-5)	(0-5)		(0-2)	(0-3)				(0-5)	(0-7)	(0-5)	(0-5)
	15-24	32	55	58	59	0.002	21	37	44	45 <0.001	11	18	14	14	0.574
		(22-42)	(41-69)	(42-73)	(44-74)		(13-29)	(26-48)	(31-57)	(32-58)		(5-16)	(10-26)	(6-21)	(7-21)
	25-34	25	48	44	55	0.003	16	37	34	40	0.004	9	12	10	15	0.401
		(15-34)	(36-61)	(31-57)	(40-70)		(8-23)	(26-47)	(23-46)	(27-52)		(3-15)	(6-18)	(4-16)	(7-23)
	35-44	25	41	52	58 <0.001	12	19	34	34 <0.001	13	22	18	24	0.197
		(15-36)	(29-53)	(39-65)	(44-72)		(5-20)	(10-27)	(23-45)	(23-45)		(6-21)	(13-31)	(10-25)	(15-33)
	45-59	22	27	32	41	0.008	9	13	12	16	0.160	13	14	20	24	0.024
		(14-30)	(18-36)	(23-41)	(31-51)		(4-14)	(7-19)	(6-17)	(10-22)		(7-20)	(8-21)	(13-27)	(17-33)
	60+	16	16	14	11	0.294	4	7	3	1	0.175	12	9	10	10	0.695
		(8-24)	(9-23)	(7-20)	(5-17)		(1-8)	(2-12)	(0-6)	(0-3)		(5-19)	(4-15)	(5-16)	(4-15)
	15-44	27	48	51	57 <0.001	16	31	38	40 <0.001	11	18	14	18	0.115
		(22-33)	(41-56)	(43-59)	(49-66)		(12-21)	(25-37)	(31-44)	(32-47)		(7-15)	(13-22)	(10-18)	(13-23)
	All ages	20	31	32	35 <0.001	10	17	19	20 <0.001	11	14	13	15	0.057
		(17-24)	(27-35)	(28-36)	(31-39)		(7-12)	(14-20)	(15-22)	(17-23)		(8-13)	(11-17)	(11-16)	(12-18)
	Deaths	147	226	228	256		74	129	137	147		73	97	91	109

Table 3

 3 -1.35) (0.16-0.87) (0.04-0.46) (0.05-0.53) (0.06-0.64) (0.19-2.37) (0.21-1.43) (0.04-0.60) (0.04-0.69) (0.09-0.95) (0.09-1.75) (0.02-1.06) (0.02-1.00) (0.02-1.27) .65) (2.00-4.39) (2.14-4.25) (3.83-7.84) (3.66-7.30) (4.03-14.48) (2.61-6.89) (2.27-5.03) (4.07-9.49) (3.35-7.76) (1.27-5.34) (0.65-2.79) (1.08-4.31) (1.94-7.65) (2.90-9.77) -1.26) (0.01-0.81) (0.17-1.12) (0.01-0.67) (0.26-1.33) (0.11-2.38) (0.14-1.70) (0.11-2.33) (0.03-1.54) (0.12-1.32) (0.02-1.32) (0.23-2.03) .36-5.03) (1.26-4.82) (2.39-6.30) (3.05-7.85) (3.84-9.16) (1.25-8.38) (0.99-7.14) (3.19-14.40) (2.42-9.47) (3.33-11.27) (0.86-5.33) (0.93-5.74) (1.25-4.79) (2.59-9.62) (3.09-10.66)

						Assault				Sharp weapons				Other assault
					Carstairs		SIMD		Carstairs		SIMD		Carstairs		SIMD
	Male	1980-82		1991-92	2000-02	2000-02	2003-05	1980-82	1991-92	2000-02	2000-02	2003-05	1980-82	1991-92	2000-02	2000-02	2003-05
	15-39
	Dep quin 1			0.52	0.37	0.14	0.17	0.20	0.68	0.55	0.15	0.17	0.29	0.40	0.14	0.13	0.17	0.00
	(0.20Dep quin 5	4.82	2.96	3.02	5.48	5.17	7.64	4.24	3.38	6.21	5.10	2.61	1.34	2.16	3.86	5.33
	(3.04-7p <0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	0.002	0.005	<0.001	<0.001	<0.001
	p 1				0.090					0.076					0.481
	p 5				0.122					0.035					0.727
	40-59
	Dep quin 1			0.29	0.11	0.43	0.09	0.59	0.00	0.00	0.52	0.00	0.49	0.51	0.20	0.39	0.17	0.68
	(0.07Dep quin 5	2.61	2.47	3.88	4.89	5.93	3.23	2.66	6.78	4.78	6.12	2.14	2.31	2.45	4.99	5.74
	(1p	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	0.003	<0.001	<0.001	<0.001	0.104	0.006	<0.001	<0.001	<0.001
	p 1				0.525					0.980					0.829
	p 5				0.274					0.175					0.811
	All ages
	Dep quin 1			0.86	0.25	0.28	0.27	0.39	0.46	0.35	0.21	0.11	0.34	1.12	0.16	0.35	0.47	0.47
		(0.49-1.49) (0.12-0.51) (0.15-0.52) (0.13-0.56) (0.21-0.71) (0.16-1.33) (0.14-0.89) (0.08-0.58) (0.03-0.46) (0.15-0.79) (0.58-2.16) (0.05-0.51) (0.16-0.77) (0.20-1.11) (0.20-1.11)
	Dep quin 5			3.71	2.31	3.24	5.19	5.50	5.36	3.47	4.07	5.68	5.23	2.59	1.38	2.34	4.57	5.89
		(2.64-5.21) (1.69-3.15) (2.49-4.22) (3.97-6.80) (4.24-7.14) (3.27-8.77) (2.28-5.28) (2.88-5.75) (4.00-8.09) (3.72-7.37) (1.59-4.22) (0.84-2.26) (1.54-3.56) (3.00-6.94) (3.93-8.80)
	p		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	0.001	<0.001	<0.001	<0.001	<0.001
	p 1				0.022					0.250					0.064
	p 5				0.680					0.376					0.962

ACKNOWLEDGEMENT

We are grateful to the General Register Office (Scotland) for the provision of data and to the referees for their helpful comments.

Competing interests: The authors do not have any competing interests. Contributors: Both authors contributed to the study design and analysis. AHL wrote the first draft of the paper. Both authors contributed to subsequent drafts and approved the final version. AHL is guarantor for the paper.

Ethical approval: This study was based on the analysis of anonymised mortality data and as such did not require ethical approval.

License statement: The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non-exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Journal of Epidemiology and Community Health and any other BMJPGL products to exploit all subsidiary rights, as set out in our licence (http://jech.bmj.com/ifora/licence.pdf).

Funding: The Social and Public Health Sciences Unit is jointly funded by the Medical Research Council (MRC) and the Chief Scientist Office (CSO) of the Scottish Government Health Directorates. This work was funded by the Chief Scientist Office as part of the "Measuring health, variations in health and the determinants of health" programme, wbs U.1300.00.001. Neither the MRC nor the CSO had any role in study design, analysis or the interpretation of the results.

WHAT THIS PAPER ADDS What is already known on this subject

• Scotland has a high mortality rate due to assault compared to other countries.

• Mortality from assault is known to be higher among more disadvantaged populations.

What this study adds


Ms Helen Atherton
email: helen.atherton07@imperial.ac.uk

Pippa Oakeshott

Adamma Aghaizu

Phillip Hay

Kerry Sally

USE OF AN ONLINE QUESTIONNAIRE FOR FOLLOW UP OF YOUNG FEMALE STUDENTS RECRUITED TO A RANDOMISED CONTROLLED TRIAL OF CHLAMYDIA SCREENING

Keywords: Electronic mail, Internet, Follow-up studies, Students, Chlamydia trachomatis

Background

Randomised controlled trials often rely on questionnaires for follow up.

Objective

To compare response rates to an online and postal 12 month follow up questionnaire on sexual health in female students who took part in a chlamydia screening trial.

Methods

1329 sexually active female students aged 16-27 were recruited from 12 universities and further education (FE) colleges. The 299 participants recruited between September 2004 and February 2005 were sent a postal questionnaire after 12 months. The 1030 participants recruited between March and December 2005 were contacted by email after 12 months and given a weblink to an online questionnaire..

Results

The response rates to the 12 months questionnaire in the online and postal groups were 51% and 29% 4 weeks after follow up commenced (relative risk RR 1.78 (1.47 to 2.14)) and 72% and 59% after 3 months. After adjusting for ethnicity, smoking, type of educational institution (university or FE college) and subject studied (health related or not), the RR at 4 weeks was 1.88 (1.42 to 2.50). However, a prior telephone call to confirm contact details increased response rate at 3 months in the postal group. In the online group, university students, those of white ethnicity and non-smokers had higher response rates at 4 weeks.

Conclusions

In this young student population, an online questionnaire was quicker, cheaper and more efficient than a postal questionnaire. However some FE college students did not have an email address. Telephone prompts and postal questionnaires were essential in obtaining a good response rate.

INTRODUCTION

Many randomised controlled trials and epidemiological cohort studies rely on questionnaires for follow up. High response rates are important to maintain the effective sample size and reduce the possibility of bias, but this can be difficult to achieve. [START_REF] Edwards | Methods to increase response to postal and electronic questionnaires[END_REF] Postal questionnaires are often used as they are relatively inexpensive and easy to distribute. [START_REF] Nakash | Maximising response to postal questionnaires--a systematic review of randomised trials in health research[END_REF] They may be supported by telephone reminders and repeat postal questionnaires which have been shown to increase follow up rates. [START_REF] Nakash | Maximising response to postal questionnaires--a systematic review of randomised trials in health research[END_REF] However, postal questionnaires where sensitive information is collected elicit lower response rates. [START_REF] Edwards | Methods to increase response to postal and electronic questionnaires[END_REF][START_REF] Edwards | Increasing response rates to postal questionnaires: systematic review[END_REF] and attempts at gaining questionnaire responses to sensitive questions over the telephone can lead to a response bias. [START_REF] Pealer | The feasibility of a web-based surveillance system to collect health risk behavior data from college students[END_REF] For such issues web based surveys offer an increasingly popular alternative. [START_REF] Wright | A Comparison of Computer-Assisted and Paper-and-Pencil Self-Administered Questionnaires in a Survey on Smoking, Alcohol, and Drug Use[END_REF] They may also be useful in younger populations. In 2008 93% of people in the UK aged 16-24 had used the internet within the last three months, compared with 63% of people aged 55-64. [START_REF] Dillman | Design effects in the transition to web-based surveys[END_REF]. Disadvantages of web based surveys include variable access to the internet, and issues relating to computer literacy or web security. [START_REF] Dillman | Design effects in the transition to web-based surveys[END_REF][START_REF] Kongsved | Response rate and completeness of questionnaires: a randomized study of Internet versus paper-andpencil versions[END_REF] The Prevention of Pelvic Infection (POPI) trial aimed to see if screening young female students for chlamydia using self-taken vaginal swabs reduced the incidence of pelvic inflammatory disease over one year. [START_REF] Oakeshott | P Screening for Chlamydia trachomatis to prevent pelvic inflammatory disease: the POPI (prevention of pelvic infection) trial[END_REF] Twelve months after participation women were sent a follow up questionnaire asking about possible symptoms of pelvic inflammatory disease. Here we describe the response rates for two different follow up strategies. In the first, participants were initially sent the questionnaire via post. In the second participants were initially contacted by email and asked to complete an online questionnaire.

METHODS

Between September 2004 and December 2005 1329 sexually active female students aged between 16 and 27 were recruited from 12 universities and colleges across London. At recruitment participants were informed that they would be contacted 12 months later and asked to complete a follow up questionnaire. They were asked to provide the following contact details; term time address, home address, email address, mobile telephone number, landline telephone number, General Practitioner (GP) details, college and course. Not all participants were able or willing to provide all of these details but all were required to provide at least one method of contact which was usually a mobile phone number.

After 12 months, the first 299 participants, who were recruited between September 2004 and February 2005 and provided a valid postal address, were sent a postal follow up questionnaire with freepost envelope. The questionnaire asked about development of possible symptoms of pelvic infection, testing for sexually transmitted infections and numbers of sexual partners in the previous year. As response rates were poor at this early stage, from January 2006 researchers started contacting participants by mobile phone to confirm addresses before sending out postal questionnaires. Nine participants did not want to be contacted at home so were followed up by mobile phone or email.

In February 2006 we developed a web-based questionnaire using an online survey company. A link to the questionnaire was emailed to participants, who clicked it to gain access to the questionnaire. Password protected results were collected via the online survey company's website. The questionnaires were downloaded into a Microsoft Excel spreadsheet and also printed directly from the website.

The 1030 participants recruited between March and December 2005 formed the 'online group'.

Participants in this group providing an email address (n=806) were sent a link to the online questionnaire. Those without an email address were followed up with an initial attempt to call the student to confirm their contact details followed by a postal questionnaire, unless the student provided an email address over the phone.

Non-responders for both methods were followed up with calls to their mobile phones and repeat postal questionnaires and emails with a link to the online questionnaire (after it was set up in February 2006). Phone calls were limited to 3 per participant, as were mailings and emails.

Statistical analysis

Relative risk was used to compare response rates to the 12 month questionnaire at 2 weeks; 4 weeks and 3 months after follow up commenced. Primary analysis compared response rates in the online group compared to the post group. A secondary analysis compared three groups, dividing the post group into those who were followed up in the first 4 months when the initial contact was by post (n=167), and those followed up in the subsequent 2 months where we tried to telephone to confirm contact details before posting the questionnaire (n=132). The third group was the online group (n=1030).

Binomial regression was used to adjust the relative risk for age, ethnicity and type of educational institution (university or FE college), subject studied (health and social care or not), number of partners (more than 2) age of sexual debut (under 16, 16-17 and over 18), smoking and time of year recruited (2 month bands). We investigated the effect of these variables on response rates at 4 weeks and on whether or not participants responded electronically in the online group.

A stepwise approach was used adding variables into the model which were significant at the 5% level until no more variables would have significantly improved the fit or until the model failed to converge. All analyses were carried out in Stata 10. [9] Results are presented as relative risks adjusted for all other significant variables.

RESULTS

Table 1. Characteristics and methods of contact for the postal and online follow up groups.

Of the 1329 participants recruited, 972 (73%) were from universities and 357 from further education colleges. Although the age distribution of the participants were similar for the two methods of follow up, the postal group were less likely to be at university or to describe their ethnicity as white and more likely to smoke (Table 1). Table 1 also shows how many participants required single or repeated postal mailings in each group. In the post group only 32% of participants responded to a single mailing, while in the online group 43% responded electronically without the need for a follow up postal questionnaire. In the 12 months since participation 31% of participants changed their postal address, 14% their email address and 12% their mobile phone number. Fifty eight (4%) participants either did not provide a postal address or requested we did not use it.

Table 2 Response rates to postal or online questionnaire.

Participants in the online group responded faster than those in the post group and this difference persisted to 3 months (RR =1.21 (1.09 to 1.34)) (Table 2). Even after adjusting for other variables (age, ethnicity, educational institution, studying a health and social care course, smoking, sexual debut and time of year) where they fitted the model, the online group had significantly higher response rates at all time points Table 3 Response rates to the postal questionnaire (n=299), with and without a prior telephone call to confirm contact details, compared to the online group (n=1030).

Participants in the post group who received a prior phone call to confirm contact details were significantly more likely than those who did not, to respond to the questionnaire by three months after adjusting for confounding factors. However the online group responded more quickly than either of the post groups (Table 3). Table 4. Response rates within four weeks by any method (online, post, telephone) for the 1030 participants in the online group, related to demographic and behavioural characteristics.

In the online group, participants over 21, those of white ethnicity, non-smokers, university students, those studying health and social care and those followed up in March-May had higher response rates at 4 weeks (Table 4). After adjustment age was no longer related to response rates but all other factors remained significant.

Table 5. Participants who responded electronically compared to post or telephone for the 526 in the online group who replied within 4 weeks

Among the 526 students in the online group who responded within 4 weeks, 429 (82%) responded electronically. University students were more likely to respond electronically but age and ethnicity were unrelated to use of the internet to return questionnaires.

Practical observations from the follow-up phase are outlined in Box 1.

DISCUSSION

Principle findings

The response rates to the 12 months questionnaire in the online and postal groups were 51% and 29% 4 weeks after follow up commenced (relative risk RR 1.78 (1.47 to 2.14)) and 72% and 59% after 3 months (RR 1.21 (1.09 to 1.34). The difference remained significant after adjusting for ethnicity, smoking, type of educational institution (university or FE college) and whether or not the student was studying health and social care. However, a prior telephone call to confirm contact details increased response rate in the postal group. In the online group, university students, those of white ethnicity and non-smokers had higher response rates.

Strengths and weaknesses

This is the first community based study of response rates to a follow up questionnaire on sexual health comparing postal and online questionnaires. It included young, sexually active women students, with over 40% from ethnic minorities, recruited outside healthcare facilities. Many of the educational institutions were located in Lambeth and Southwark, two of the most deprived boroughs in England. [START_REF]Indices of Deprivation[END_REF] Such participants might be expected to be very difficult to locate and follow up 12 months after recruitment.

We considered using the Index of Multiple Deprivation to assess socio-economic status.

However, the majority of participants at Universities provided only a term-time address, which would not have provided a true representation of socio-economic status. Instead we controlled for other factors that are linked with socioeconomic status; cigarette smoking. [START_REF] Harman | Socioeconomic gradients in smoking among young women: A British survey[END_REF] and age at sexual debut. [START_REF] Wellings | Sexual behaviour in Britain: early heterosexual experience[END_REF] Cigarette smoking was found to significantly affect response rates at 4 weeks.

The main weakness is that this is a descriptive study and participants were not randomised to different follow up strategies. Recruitment took place in different institutions at different times resulting in the online group including more participants at university and fewer from ethnic minorities. These participants might be expected to have higher response rates. However after adjustment for these factors the online group still had higher response rates. These preliminary results need to be confirmed in a randomised trial.

The other main limitation is that the findings may only apply to a young, female student population who had already had contact with the researchers a year previously. They may not apply to different populations such as men, non-students, older people, or those with no previous contact with researchers.

We found that 30% of participants had changed their postal address during the year and this is likely to be an underestimate. In the follow up questionnaire we asked if they would be willing to provide a further postal sample and requested contact details. We also contacted participants by phone if they did not provide an email address or they did not reply to an email, and asked them to confirm all contact details. It is likely that some participants' change of details may have been missed.

Comparison with other studies

Much of what is reported about response to questionnaires concerns population groups who have not already been actively involved in a trial or have not already been consented to enter a trial, for example one off surveys or baseline recruitment.

Having prior contact with participants has been shown to increase response rates in postal questionnaires. [START_REF] Edwards | Increasing response rates to postal questionnaires: systematic review[END_REF] We found that a prior phone call improved response rates in the post group at 4 weeks and 3 months. It is likely that no effect was seen at 2 weeks because of the length of time taken for postal questionnaire delivery and return.

Previously, where online methods have been used for follow up in large trials this has involved sending a participant information in the post containing the web address of the online questionnaire, which is administered via a website. [START_REF] Kongsved | Response rate and completeness of questionnaires: a randomized study of Internet versus paper-andpencil versions[END_REF] Participants have to sign into the website using specific details. We used a simpler approach sending an email with a link to the questionnaire embedded.

Participants at university were more likely than those at FE colleges to respond to the questionnaire in any format. In addition a recent UK study showed that those with educational qualifications were more likely to use the internet than those who do not. [START_REF]Household and Individual Use of the Internet[END_REF] Access to the internet would be generally available for those in higher education but institutional access is less likely to be available for under 18s. Finally, participants studying courses in health & social care were more likely to respond than participants on other courses. It has been shown that a highly salient questionnaire (containing questions particularly relevant to the study participants) will increase the odds of gaining a response in both postal and electronic questionnaires. [START_REF] Edwards | Methods to increase response to postal and electronic questionnaires[END_REF]

Implications

Although this was a descriptive study it suggests that using an initial online questionnaire may be quicker, more efficient and cheaper than initial postal follow up in a young, mobile, student population. However electronic follow up still needs to be backed up by telephone prompts and postal questionnaires. 1 Adjusted for educational institution and time of year 2 Jan/Feb group were not in the online group and received only postal questionnaires.

Box 1. Advantages and disadvantages of electronic follow up

Advantages

• Requires less administration and incurs no postal costs.

• Most replies are received within a week of sending.

• Replies do not tend to get lost or delayed as they do in the postal service.

• Emails can be sent en-masse using the blind carbon copy function.

• Greater confidentiality than postal questionnaires for participants still living at home who do not want parents to know they are sexually active.

• Replies can be downloaded from the website into an excel spreadsheet.

Disadvantages

• Not all of the participants may have an email address or access to email facilities.

• Email may go straight into a junk mail folder when sent using the blind carbon copy function.

• Email may not be recognised by the participant and thus ignored.

• The online questionnaire can have sporadic technical problems.

• Email addresses can be incorrect, often because they are illegible e.g. eye2sw1@hotmail.com is actually eyezsw1@hotmail.com but handwriting can make distinction between the two impossible.

Table 1 . Characteristics and methods of contact for the postal and online follow up groups.

 1 Postal changes may be underreported for students who replied electronically and vice versa. Participants who replied electronically within a few days were not telephoned. 5. This includes students where the letter was returned to sender, the email bounced back or the phone was not working

	Online group	Post group	P-value*
	n=1030	n=299
	%(n)	%(n)

Table 2 Response rates to postal or online questionnaire.

 2

	Time since	Online group	Post group	Relative risk	P-value	Adjusted relative	P-value
	posting to	n=1030	n=299	(95% CI)		risk
	return of					(95% CI)
	questionnaire	% (n)	% (n)
	2 weeks	41 (419)	22 (67)	1.82 (1.45 to 2.27)	P<0.001	1.64 (1.31 to 2.06) 1 P<0.001
	4 weeks	51 (526)	29 (86)	1.78 (1.47 to 2.14)	P<0.001	1.88 (1.42 to 2.50) 2 P<0.001
	3 months	72 (739)	59 (177)	1.21 (1.09 to 1.34)	P<0.001	1.29 (1.11 to 1.51) 3 P=0.001

Table 3 . Response rates to the postal questionnaire (n=299), with and without a prior telephone call to confirm contact details, compared to the online group (n=1030).

 3

	Time since	Group			Response	Relative risk	P-value	Adjusted relative
	posting to				rate	(95% CI)		risk*
	return of				% (n)			(95% CI)
	questionnaire
	2 weeks	Post group without	21 (35)	1.00	P<0.0001	1.00 1	P=0.0001
		prior	phone	call
		(n=167)
		Post group with prior	24(32)	1.16 (0.76 to 1.76)		1.46 (0.96 to 2.22)
		phone call (n=132)
		Online group (n=1030) 41 (419)	1.94 (1.43 to 2.63)		1.93 (1.42 to 2.63)
	4 weeks	Post group without	25 (42)	1.00	P<0.0001	1.00 2	P=0.0001
		prior	phone	call
		(n=167)
		Post group with prior	33 (44)	1.33 (0.93 to 1.89)		1.62 (1.13 to 2.31)
		phone call (n=132)
		Online group (n=1030) 51 (526)	2.03 (1.55 to 2.66)		1.85 (1.40 to 2.44)
	3 months	Post group without	53 (88)	1.00	P<0.0001	1.00 3	P=0.001
		prior	phone	call
		(n=167)
		Post group with prior	67 (89)	1.27 (1.06 to 1.54)		1.39 (1.17 to 1.66)
		phone call (n=132)
		Online group (n=1030) 72 (739)	1.36 (1.17 to 1.58)		1.27 (1.09 to 1.48)

Table 5 . Participants who responded electronically compared to post or telephone for the 526 in the online group who replied within 4 weeks.

 5

		Number of responders in online group	% (n) responding electronically	Relative risk	P value	Adjusted relative risk	1	P value
	Age
	<18	39	54 (21)	0.64 (0.48 to 0.86)		0.70 (0.50 to 0.98)
	18-20	209	83 (174)	0.99 (0.91 to 1.07)		0.98 (0.91 to 1.06)
	21 and over	278	84 (234)	1.00	P=0.12	1.00		P=0.11
	Ethnicity
	White	351	83 (293)	1.00	P=0.18	1.00		P=0.99
	Black	131	76 (99)	0.90 (0.81 to 1.01)		1.00 (0.90 to 1.10)
	Other	44	84 (37)	1.01 (0.88 to 1.15)		1.01 (0.88 to 1.15)
	University	450	84 (379)	1.26 (1.07 to 1.48)	P=0.004	1.28 (1.09 to 1.52)		P=0.004
	Studying health and social care	230	82(188)	1.00 (0.93 to 1.09)	P=0.93	1.02 (0.95 to 1.10)		P=0.55
	Cigarette smoking	137	80 (110)	0.98 (0.89 to 1.08)	P=0.66	0.95 (0.87 to 1.04)		P=0.24
	Age first sexual
	intercourse
	<16	124	75 (93)	1.00	P=0.14	1.00		P=0.36
	16-17	238	84 (200)	1.12 (1.00 to 1.26)		1.08 (0.97 to 1.20)
	18 and over	157	83 (131)	1.11 (0.98 to 1.26)		1.07 (0.95 to 1.20)
	Two or more partners	204	79 (161)	0.95 (0.87 to 1.03)	P=0.23	0.95 (0.88 to 1.03)		P=0.24
	Time of year
	Sept/Oct	164	87 (142)	1.00	P=0.08	1.00		P=0.045
	Nov/Dec 2	122	77 (94)	0.89 (0.79 to 1.00)		0.90 (0.81 to 1.00)
	Mar/Apr/May	240	80 (193)	0.93 (0.85 to 1.01)		0.92 (0.84 to 0.99)

adjusted for ethnicity, educational institution, whether or not study health and social care, smoking and age at sexual debut

adjusted for ethnicity, educational institution, whether or not study health and social care, smoking and time of year

adjusted for ethnicity, educational institution and time of year. Model did not converge when studying health and social care was fitted to the adjusted model.

adjusted for ethnicity, educational institution, whether or not study health and social care, smoking and age at sexual debut

adjusted for ethnicity, educational institution, whether or not study health and social care, smoking and summer (April-Jun )

adjusted for ethnicity, educational institution and whether or not studying health and social care and summer (April-Jun). Model failed to converge with more variables in the model.It was not possible to fit time of year as defined inTable 3 because of complete confounding with follow up group

Acknowledgements: We thank Gen-Probe Incorporated San Diego for providing the TMA chlamydia testing kits. We thank Debbie Banks, Ruth Harbit and Linzie Long for helping with the follow up of participants.

Funding: This study was funded by The BUPA Foundation.

Copyright licence statement:

The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non-exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd, and its Licensees to permit this article (if accepted) to be published in Journal of Epidemiology and Community Health and any other BMJPGL products and to exploit all subsidiary rights, as set out in our licence (http://jech.bmjjournals.com//ifora/licence.pdf).

Competing interests

The authors declare that they have no competing interests.

Ethical approval: Ethical approval was granted by Wandsworth Local Research Ethics

Committee. 1 Adjusted for ethnicity, educational institution, studying health and social care, smoking, time of year. 2 Only 67 participants were recruited in May and so these were added to the Mar/Apr group for the purposes of analysis.