Dogslife: A web-based longitudinal study of Labrador Retriever health in the UK
© Clements et al.; licensee BioMed Central Ltd. 2013
Received: 10 August 2012
Accepted: 23 November 2012
Published: 18 January 2013
Dogslife is the first large-scale internet-based longitudinal study of canine health. The study has been designed to examine how environmental and genetic factors influence the health and development of a birth cohort of UK-based pedigree Labrador Retrievers.
In the first 12 months of the study 1,407 Kennel Club (KC) registered eligible dogs were recruited, at a mean age of 119 days of age (SD 69 days, range 3 days – 504 days). Recruitment rates varied depending upon the study team’s ability to contact owners. Where owners authorised the provision of contact details 8.4% of dogs were recruited compared to 1.3% where no direct contact was possible. The proportion of dogs recruited was higher for owners who transferred the registration of their puppy from the breeder to themselves with the KC, and for owners who were sent an e-mail or postcard requesting participation in the project. Compliance with monthly updates was highly variable. For the 280 dogs that were aged 400 days or more on the 30th June 2011, we estimated between 39% and 45% of owners were still actively involved in the project. Initial evaluation suggests that the cohort is representative of the general population of the KC registered Labrador Retrievers eligible to enrol with the project. Clinical signs of illnesses were reported in 44.3% of Labrador Retrievers registered with Dogslife (median age of first illness 138 days), although only 44.1% of these resulted in a veterinary presentation (median age 316 days).
The web-based platform has enabled the recruitment of a representative population of KC registered Labrador Retrievers, providing the first large-scale longitudinal population-based study of dog health. The use of multiple different methods (e-mail, post and telephone) of contact with dog owners was essential to maximise recruitment and retention of the cohort.
To date there have been no longitudinal population-based epidemiological studies that estimate the incidence and/or prevalence of canine diseases. Representative information on the pattern of disease in the general canine population is impossible to obtain from data studies utilizing secondary (referral) centres, because of the well-recognised “referral bias” , owing to variables including geographical location and wealth of owners. Studies evaluating presentations to primary care practices alone  are rare. Furthermore the prevalence of clinical signs or illnesses in dogs which are not subsequently subjected to veterinary presentation has, to our knowledge, never been reported. The paucity of published data in this field is striking.
Reports of breed associated disease risks are either anecdotal, based on referral  or on insurance data  and are thus subject to sampling bias. Meta-analysis of the available information on breed-specific genetic diseases suggests that they have inadvertently arisen as a consequence of selection for breed standards or by chance [5, 6]. However most of the previous studies reported have been retrospective or cross-sectional, and did not capture longitudinal data regarding the clinical, lifestyle, environment, diet or reproductive history of individuals. Thus it is not surprising that non-genetic influences on common canine diseases remain poorly characterised.
Longitudinal studies of health are the most powerful mechanism for determining environmental and lifestyle influences on the development of disease . In comparison to cross-sectional studies, longitudinal studies avoid recall bias, enable sampling at appropriate time points and allow temporal association between risk factors and disease to be established and changes of phenotype with age to be identified. Studies of human birth cohorts, such as the Avon Longitudinal Study of Parents and Children , have revealed many unsuspected environmental and genetic risks and associations for a wide range of human phenotypes, such as obesity  and cognitive functions . The scale of such studies is ever increasing, with newer studies such as the 2012 Birth Cohort Study which will track the growth, development, health, well-being and social circumstances of over 100,000 UK children from gestation through the early years of their childhood. Similarly the UK Biobank project is collecting historical and prospective health data, biological samples and physiological measurements from over 500,000 participants aged 50–65 . No such large-scale studies have ever been attempted using a general dog population, although focused lifetime birth cohort studies of other species such as lambs [12, 13] and cattle  have been reported.
The internet potentially offers a rapid and efficient method for capturing data on health, wellbeing and lifestyle, and has been used to record information about pet ownership . Internet-based data capture and recording systems have been widely used to record human health data and provide a cost effective and simple method for obtaining epidemiological information [16, 17]. To date the internet has been used in veterinary medicine to capture end of life information . Internet-based recording systems are particularly attractive for assembling longitudinal data, since participants can submit data at their own convenience, as well as allowing the incorporation of inexpensive and unobtrusive electronic reminder systems into the study design and such systems are highly scalable. In 2009, 76% of household in the UK had access to the internet .
This paper describes the design and recruitment for the first large scale (national) longitudinal study of canine health, called “Dogslife”. The study is collecting information on the health and well-being of a cohort of Labrador Retrievers over their first few years of life. The ultimate goal of the study is to identify environmental and genetic risk factors for the development of canine diseases, and subsequently inform future risk reduction strategies.
The study was approved by the Veterinary Ethical Review Committee of the University of Edinburgh.
The study population was Kennel Club (KC) registered Labrador Retrievers born on or after 1st January 2010 and present in the United Kingdom (UK) at the time of registration. Puppies are registered with the KC after birth by the breeder. The breeder can keep their puppy, or transfer the puppy to a new owner, which typically occurs at around the time of their first routine vaccination between six and eight weeks of age. The new owner can transfer the KC registration of their puppy to themselves at any time after they obtain their puppy, but they are not obliged to do so.
Recruitment of dogs started with the launch of the website on the 1st July 2010. To maximise early recruitment all dogs born after 1st January 2010 were considered eligible for recruitment. The KC reported all new Labrador Retriever registrations (puppies registered at birth by the breeder) and transfers of registration (dogs moving to new homes from the breeder) to the Dogslife project. All KC registrations from 1st January to 30th June 2010 were provided as a single file but from 1st July 2010, they were provided on a daily basis through electronic data transfer directly into the Dogslife database. Registration data included a unique KC number, date of birth, names of the sire and dam, KC name, gender and colour. The KC number was used as the unique identifier of each dog. For all transfers of registration, the new owners were asked by the KC to give consent to their name, e-mail address and postal address being forwarded to third parties at the time of registration with the KC (41% consenting to contact by e-mail and 54% consenting to contact by post, resulting in 61% consenting to the use of one and/or the other).
To help launch the project and maximise recruitment, the project was actively publicised. The website was launched on the 1st July 2010 with a press release published on the 30th June 2010, which received national newspaper, television and press coverage. In January 2010 and January 2011 a short article detailing the aims of the project was sent to the secretaries of each Labrador Retriever breed club. Thirteen different Labrador Retriever breed clubs are listed on the Kennel Club website, and represent local or national groups with an interest in Labrador Retrievers. They were asked to disseminate it to their members through their yearbook or newsletter publication, and by adding information on the project to their breed club website. All breeders registering litters of Labrador Retriever puppies after the 1st July 2010 were sent a black and white A5 flyer with their puppy registration documentation inviting them to join the project. Between July and September 2010 1,292 breeders of Labrador Retrievers listed on the Accredited Breeder page of the KC website, “Champdogs” (http://www.champdogs.co.uk), the Breeders Online (http://www.breedersonline.co.uk), Chocolate Labs (http://www.chocolatelabs.co.uk), Dog Club (http://www.dogclub.co.uk), K9 Puppy (http://www.k9puppy.co.uk) and UK Gundogs (http://www.ukgundogs.org) websites were contacted using the telephone number or e-mail address provided, to inform them about the project and to request their advocacy to future puppy owners. In December 2010 an article requesting further participation was forwarded to each of the breed clubs. In January 2011, 4,827 non-accredited KC registered breeders were contacted with a letter about the project and five copies of the postcard to distribute to new puppy owners.
Enrolment, routine and ad-hoc data entry was all performed by owners within a project website interface. The website design was subject to open tender in December 2009. The project was developed under the name “Dogslife” and the internet domain http://www.dogslife.ac.uk was secured from JANET, the UK’s education and research network. The website was registered with Google Analytics (http://www.google.com/analytics/) to enable real-time monitoring of the site usage metrics.
All enrolments were a two-step process. The first required entry of the dog’s KC number, date of birth, age, gender and breed into a web page. If the KC number and date of birth matched those in the registration data supplied by the KC a second page requested an e-mail address and password. This process confirmed enrolment and entry to the dog’s “homepage”, where owners were requested to complete a single page questionnaire recording demographic information followed by a six-page questionnaire recording dog health and lifestyle information. The homepage also allowed owners to upload a photograph of their dog, visualise graphical representations of their dog’s data (height, weight, activity and illness episodes) and access links to the latest results from the study. Completion of the questionnaire could be deferred to the next site visit.
A web based questionnaire was designed and reviewed by epidemiologists, geneticists, veterinarians, and piloted with dog owners. A member of each Labrador breed club was invited by the KC to attend a focus group meeting in May 2010, where a draft version of the website was presented and subject to critique and open debate. The final version was pre-tested on dog-owners and amended accordingly.
The questionnaire requested information on the height and weight of the dog, the household environment, preventive healthcare measures, feeding, exercise, intended use, and health or illness. Data was collected in categorical, textural and nominal format and took a maximum of 10 minutes to complete. All questions on each page were compulsory (i.e. required answering for the website to allow progress onto the next page) with the exception of weight (which owners could leave blank). Weight data was not compulsory as it was perceived that some owners may have difficulty in obtaining this measure. When owners left the questionnaire section of the website before answering all of the questions, and did not return to complete the information within the data entry window (see below) the questionnaire was recorded as being “incomplete”. A paper version of the questionnaire was not offered due to the cost and logistical reasons.
Compliance and retention
The owners of participating dogs were requested to complete the web-based questionnaire about their dog’s health and welfare at 30 day intervals for the first year of the dog’s life and at three monthly intervals thereafter. Reminders for non-completed monthly questionnaires were sent by automated e-mail one week after the deadline (30 + 7 days) and by telephone or non-automated e-mail two weeks after the deadline (30 + 14 days). If the questionnaire was still not completed, further reminders were sent 84 (automated e-mail) and 91 days (telephone or non-automated e-mail contact) after the date of the last completed data entry. If no response was received after 91 days the dog was listed as lapsed. All contacts by telephone or non-automated e-mail were made on the date, or as close after the date as possible (for example if the contact date was at a weekend, the contact was made on the following Monday). For entries up to the first year of age, the reminder timeline was reset after the data entry. For example, if the owner joined the project and completed their first data entry when their dog was 90 days old, and was due to complete the next data entry 30 days later, when their dog was 120 days old, but did not complete it until their dog was 130 days old (10 days after the data entry was expected (120 days) and three days after a reminder e-mail was sent (120 days +7 days =127 days)) then the following data entry was expected 30 days later when their dog was 160 days old (130 days + 30 days), and if this did not occur, the next e-mail reminder would occur at 167 days (130 days + 30 days + 7 days). However, there was considerable ‘slippage’ in the interval between data entries, so after one year of age when the response frequency dropped to every three months, a data entry window was established to facilitate responses and control this problem. This extended from 21 days before to 35 days after each of 3 monthly expected data entry dates. Non-responders were sent an e-mail reminder at 7 days after the expected date and contacted by telephone or non-automated e-mail 14 days after the expected date. Owners could also enter data outside these timelines, and as frequently as they wished.
To encourage retention, a monthly newsletter containing articles about canine health, Labrador Retrievers and project updates was started in August 2010. The newsletter was e-mailed to all participants wishing to receive it, and to members of the general public who had registered an e-mail address with the website.
A three monthly prize draw was instigated for the first twelve months of the study to incentivise enrolment and retention. Each complete data entry was accorded one entry in the draw, with thirteen prizes to the value of £100 (one), £50 (two) and £10 (ten) awarded. The Dogslife website hosted an editable scrapbook with the facility to upload photographs and input text detailing memorable events. Owners had the opportunity to nominate their pet as “Featured Dog”. A picture and description of these dogs appeared on the website home-page.
In the last section of the questionnaire, owners were asked to report any illness their dog(s) suffered. This section could also be accessed at any time point. Owners classified their dog’s illness into one or more of six broad clinical syndromes: vomiting, diarrhoea, scratching, licking and chewing themselves, coughing, and lameness. An open question also allowed the owner to describe any illnesses or clinical signs not listed. When an illness was reported, participants were asked to detail the duration, frequency, veterinary visits, and treatment.
If the owner made a visit to their veterinary surgeon, they were asked in addition to complete a Dogslife Health Record form or ask the veterinary surgeon to do so for them. This was a single page form available from the website which enabled details of the clinical signs, diagnosis and treatment of non-routine veterinary presentations to be recorded. Owners were encouraged to print the form, keep it with their pet’s vaccination reminder, and ask the veterinarian to complete it at non-routine presentation. They were then asked to transfer this information to the on-line questionnaire. The presenting signs and diagnosis were coded using the VeNom standard veterinary nomenclature code list  by an experienced clinician (DNC). Ambiguities in clinical signs or diagnosis were resolved by contacting the owner by telephone or e-mail.
If the dog was less than 434 days of age and a data entry was recorded in the 1 year of age window (between 344 and 400 days of age),
If the dog was between 434 and 490 days of age and a data entry was recorded in either the 1 year of age window (between 344 and 400 days of age) or the 1 year 3 months of age window (between 434 and 490 days),
If the dog was older than 490 days of age and a data entry was recorded in the 1 year of age window (between 434 and 490 days).
The number of participants entering data outside the requested windows (between 401 and 433 days of age and after 490 days of age) was also recorded.
The geographical distribution of recruited dogs was determined by using the first two letters of the postal code which localised the dog to a postal delivery area. The proportion of dogs recruited from each area was estimated from the number of dogs recruited from each postcode divided by the total number of Labrador Retrievers reported by the KC to be from that postcode. Dogs missing postcodes were removed. The maps were produced using the R software environment .
The time to the first owner-reported illness and the time to the first non-routine veterinary presentation were estimated using standard Kaplan-Meier survival model with 95% confidence intervals (using the R 'survival' package ). The data were naturally left truncated as dogs were not enrolled in the study from birth and were right censored at their last data entry.
Withdrawal from the study
Participants were able to withdraw from the study at any point by e-mailing the study team. For members leaving the study because they no longer had their dog the reasons for exit from the study were requested in a free text field.
Compliance and retention
Number of complete and partial data entries at the first visit to the website and at subsequent visits
Full Data Entry
Partial Data Entry
Height and weight (Page 1)
Bathing / Veterinary Care (Page 2)
Exercise (Page 3)
Feeding (Page 4)
Routine Healthcare (Page 5)
Illness (Page 6)
Thirty nine per cent (110) of the 280 dogs aged 400 days or older on the 30th June 2011 were considered to be “actively” participating in the project. A further 6% (18) had a completed data entry after the last data entry window in which they were requested to enter data, but not within the data windows requested (Figure 3).
Overall twelve dogs were withdrawn from the study by 30th June 2010; one dog died, two dogs were put to sleep (one with severe hip dysplasia; the aetiology of the second case was not reported), two dogs were rehomed for behavioural problems, and seven were rehomed without the reason reported.
Signalment of participants
The distribution of coat colours of dogs enrolled in the cohort was: black 691 (49.2%, 95% Confidence intervals [CI] 46.5%, 51.7%), yellow 367 (26.1%, 95% CI 23.8%, 28.4%), chocolate 314 (22.4% 95% CI 20.2%, 24.5%), other 32 (2.3%, 95% CI 1.5%, 3.1%). Coat colour was not recorded in three dogs. In comparison the distribution of coat colours of eligible dogs was: black 30,630 (52.2%, 95% CI 51.7%, 52.6%), yellow 16,850 (28.7%, 95% CI 28.3%, 29.1%), chocolate 11,157 (19.0%, 95% CI 18.7%, 19.3%), other 98 (0.17%, 95% CI 0.13%, 0.20%). The number of males and females registered was roughly equal (721 (51.3%, 95% CI 48.7%, 51.9%) males, 686 (48.7%, 95% CI 46.1%, 50.3%) females), which was similar to that of the eligible population of 29,464 (50.2%, 95% CI 49.8%, 50.6%) males, 29,271 (49.8%, 95% CI 49.4%, 50.2%) females.
1,372 owners registered a single dog, 12 owners registered two dogs, two owners registered three dogs and one owner registered five dogs. The type of households owning dogs was reported as: 45.7% (627) “Family” (one or more adults and one or more children), 39.9% (548) “More than one adult and no children”, 6.0% (82) “Single or couple retired”, 5.7% (78) “Single adult”, 0.6% (7) “Other household type” and no response was given by 34 (2.5%). 235 (17.1%) of households joining the project reportedly contained a smoker. 1,323 (96.1%) of households contained another pet. Most commonly this was another dog (46.0%) or a cat (29.7%), a combination of other dogs and cats (8.2%), or other species with or without dogs and/or cats (12.2%).
Source of new website traffic to http://www.dogslife.ac.uk
Number of visitors
Motivation for participation
Of the 149 dogs nominated as “featured dogs” all owners reported one or more reasons for joining the project. They were: to help with research (104 owners, 71%), to compare or monitor their own dog’s health, progress or development (40 owners, 27%), or other reasons (usually for interest or further information, 22 owners, 15%).
Newsletter and scrapbook
91% (1262 participants) requested the newsletter. An additional 152 non-participants also requested to be included in the newsletter distribution list. The scrapbook feature was taken up by 47% of participants (652), and the scrapbook page was viewed 3,724 times.
Recruitment and retention of a representative population, and compliance and the collection of accurate data are the four cornerstones of longitudinal studies. Recruitment of a representative population is a major challenge for all longitudinal studies. This is commonly attempted by targeting a birth cohort restricted in either time or location, but it is rarely achieved as participation will be influenced by many factors. Assessment of the representativeness of the recruited population is usually achieved by comparison to reference values collected in the general population such as demographics or weight , or by comparison to other measures such as disease incidence in other similar cohorts . In production animals this has been achieved by studying individual herds and flocks [12–14]. In pets it presents a major problem because in most countries there is no national registration system for all animals and so the demographics of the general population are unknown. To overcome these difficulties we chose one breed of UK Kennel Club registered pedigree animals. The Labrador Retriever breed was chosen as it is the most common pedigree dog in the UK. They are bred by individuals and registration of their dogs with the KC confers certified pedigree status on these animals.
The overall response rate (2.4%) was very similar to that reported for a human internet-based birth cohort study (3.7%) . Although it appears limited, a large proportion of the eligible population were not actively targeted either because the owner did not transfer the dog’s registration with the KC or did not consent to be contacted by post and/or email. Thus 71% of eligible dogs were not actively recruited. When targeted with flyers, e-mail and postcards, then the recruitment rate increased to 8.4%. Offering a paper-based alternative questionnaire may have increased the recruitment [17, 26–28] and retention rates . The use of repeated e-mail and postal reminders may also have increased the recruitment rate further . However a significant cost implication is associated with using postal services; the limited budget of this project restricted postal communications to a single invitation to each potential new member (where we had permission to do so). We did not request owners to detail where they heard about the project to support the inferences we have made based on the time of enrolment relative to the recruitment timeline.
The relatively low “conversion rate” of website visitors to participants (17.6%) suggests that although many people found the study intriguing enough to view the website, they did not necessarily go on to register. The relatively high frequency of data input (monthly until one year of age) may also have been a deterrent to potential participants. Although not specifically studied, informal verbal feedback from non-participants indicated that the time required to participate in the study was the primary reason for non- participation, which is consistent with reasons given in other longitudinal studies . Clearly, follow up of a cohort of non-participants is required to determine the representativeness of the cohort, although comparison with the geographical, coat-colour and gender data available from the population of dogs eligible to register did not identify any overt differences.
Designing and populating a website to appeal to a section of the dog-owning public was challenging. The spectrum of households owning a dog in the UK is broad, although dog ownership is strongly associated with families who have children , and this was supported by the household types reported by participants in the project. Consequently the colour pallet and graphics of the website were designed to be relatively neutral to appeal to all age groups whom might use the site. We used many of the recommendations known to increase responses to paper and electronic questionnaires, namely the assurance of confidentiality, the use of non-monetary incentive, the notification of results, using a university affiliation, designing the questionnaire with simple headers and a white background and giving textural representation of response categories . We also obtained an “academic” domain name (ending .ac.uk) to validate the authenticity of the project. Over half of new visitors found the website directly or via a Google search, which implies that they were directed to the website by the flyer, reminder e-mail or postal contact. This was also supported by the observation that the registration trend line is relatively linear throughout the year, rather than demonstrating an exponential increase in activity, which might have been expected if the project had gained awareness or popularity through other means. Although social media sites, such as Twitter and Facebook, can be used to recruit new participants to longitudinal studies , we avoided this form of communication in the first year of the project as we wished to maintain the independence of participants and avoid the potential influence of inter-participant communication through the network.
Compliance and retention
One of the findings of our analysis was that the timelines for data entry were generally not adhered to, and “questionnaire fatigue” was undoubtedly a factor in participant loss and the low compliance with the data entry timelines. The aim was to collect data every 30 days but the data entry intervals were between 10 and 100 days.
The compliance with entering the requested data to the questionnaire was reasonably high, with nearly 80% of data entries being complete. Unsurprisingly the proportion of complete data entries increased after the first data entry, as participants completing their first data entry would be expected to be more likely to complete subsequent entries. Partial data entries occurred with members stopping data entry at any point of the questionnaire, although the vast majority stopped on the first two web-pages of the questionnaire. The first web-page required owners to have measured the dogs’ height and weight, and the second requested information about bathing their dog. Progress from one web-page to the next was conditional on the owner having completed the answers to the questions on the previous page (with the exception of the weight of the dog). The subsequent four web-pages were completed in the majority of cases, with roughly 1% of data entries being stopped at each page, although the number of questions on the subsequent web-pages (exercise, feeding, routine healthcare and illness) was greater than on the second page. This supports comments made to the project secretary during telephone conversations with participants, that members found obtaining the physical measurements onerous, and the repetitiveness of questionnaire tiresome. It is possible that a memo on the first page of the questionnaire reminding participants of the need for these measures, reordering these questions or pre-populating data entries with the previous results, might have increased the proportion of complete data entries. Clearly, if owners had gone to the trouble of taking the measures of height and weight they were likely to persist with the remaining data entry into the questionnaire.
Owners of 39% of dogs were estimated to be actively involved in the study after their dog had reached 400 days of age, and a further 6% provided data entries outside the requested guidelines. This rate is less than that reported for other internet based longitudinal studies of human health (60-72%) , and a conventional longitudinal study of health utilising internet, telephone and paper-based communication (79%) . Considering the relatively high commitment by participants of the study, both in the number of measures taken and frequency of data entry, and the absence of direct reward to participants, the retention rate was not surprising. We used wide “windows” to calculate data retention, as it was felt unnecessary to request re-entry of data less than 21 days from the optimal data entry timelines (1 year of age, and 1 year 3 months of age). Similarly, we arbitrarily closed the data entry 21 days after the second reminder (telephone), because the profile of data entries showed that many participants would take up to 3 weeks after a phone call to enter data into the website. The peaks in data entry frequency around the date of reminders showed the value of these in encouraging punctuality. However, participants who did not respond to reminders at 37 and 44 days did not commonly respond to the reminders at 84 and 91 days, suggesting this second reminder timeline was not particularly beneficial. It is possible that the time interval between the second and third reminders was too great and that more frequent reminders around the end of each 30 day period may be more satisfactory in enhancing retention.
The motivation to participate in the study was primarily altruism, based on information supplied to the “featured dog” section and informal discussions with participants during telephone reminders. For the majority of participants in the “featured dog” section it was the desire to help research into their dog’s breed, rather than the personal benefits of the record keeping or desire to find information, that was stated as the reason for joining the project. This was also indicated by the observation that the fun features of the website such as the “featured dog” and scrapbook pages were more popular than the health information links.
The colour and gender data of the cohort suggest that Dogslife is broadly representative of the general Labrador Retriever population. The slight increase in the number of chocolate and other coat coloured dogs in the Dogslife cohort when compared to the general Labrador Retriever population was not perceived to intimate an important bias in the representativeness of the cohort. A relatively low prevalence of smoking (17%) was recorded in the owner cohort compared to that reported for the adult population in England and Wales (21% ) or Scotland (24% ). It is well recognised that both adults and children owning dogs are more physically active [37, 38], and thus might be less likely to smoke. Smokers are also more likely to be of low socioeconomic status  and hence less able to afford to purchase and maintain a large pedigree dog.
The frequency of clinical signs or illnesses reported in the first year of life was high, although only a proportion resulting in veterinary visits, suggesting that many were regarded as being of low severity or unimportant. The estimated frequency of non-routine veterinary presentations (54%) in the first year of life of dogs participating in the project was much higher than the reported annual risk of making a veterinary care insurance claim from the age of two onwards , and is an underestimate as most of the cohort had not reached one year of age. Young children also show an increase in the number of primary healthcare presentations per annum in comparison to other age groups, although the rate we recorded in the Dogslife cohort was still lower than the comparative values for children (a mean of 6 general practitioner consultations per person-year in children aged 0–4 years) .
One of the major challenges for the study was to quantify the validity and reliability of the clinical data provided. We anticipated that the Health Record form would provide a means of expediting transfer of this data, but its usage appeared limited. Integration with computerised health records for veterinary epidemiological studies has been performed , but the plethora of different record management systems used and the requirement to obtain agreement from participating veterinarians make this unachievable in the short term in a nationwide study such as Dogslife. Consequently, recall of veterinary health records of a random selection of the cohort is being undertaken to ascertain the accuracy and completeness of the data recorded to date.
Although difficult to quantify, we believe that secretarial support was fundamental to the recruitment and retention process, in facilitating the postal contact, telephone reminders, answering queries, troubleshooting website problems and providing a point of human contact to an otherwise computerised process.
The Dogslife project has demonstrated the utility and problems associated with internet-based longitudinal observational studies. Recruitment to such studies can be enhanced additively by e-mail or postcard contact with the target population. We believe Dogslife will provide a useful insight into the demographics of Labrador Retriever ownership and health status through the recording of health information and will allow us to investigate a wide range of environmental influences on reported illnesses in the future.
Kim M Summers and B Mark C de Bronsvoort are the joint last authors.
This project was funded by the Kennel Club Charitable Trust. CAP was funded by the Biotechnology and Biological Sciences Research Council. The Roslin Institute is supported by Biotechnology and Biological Sciences Resources Council Institute Strategic Grant funding.
- Bartlett PC, Van Buren JW, Neterer M, Zhou C: Disease surveillance and referral bias in the veterinary medical database. Prev Vet Med. 2010, 94: 264-271. 10.1016/j.prevetmed.2010.01.007.PubMedView ArticleGoogle Scholar
- Lund EM, Armstrong PJ, Kirk CA, Kolar LM, Klausner JS: Health status and population characteristics of dogs and cats examined at private veterinary practices in the United States. J Am Vet Med Assoc. 1999, 214: 1336-1341.PubMedGoogle Scholar
- LaFond E, Breur GJ, Austin CC: Breed Susceptibility for Developmental Orthopedic Diseases in Dogs. J Am Anim Hosp Assoc. 2002, 38: 467-477.PubMedView ArticleGoogle Scholar
- Dobson JM, Samuel S, Milstein H, Rogers K, Wood JL: Canine neoplasia in the UK: estimates of incidence rates from a population of insured dogs. J Small Anim Pract. 2002, 43: 240-246. 10.1111/j.1748-5827.2002.tb00066.x.PubMedView ArticleGoogle Scholar
- Asher L, Diesel G, Summers JF, McGreevy PD, Collins LM: Inherited defects in pedigree dogs. Part 1: Disorders related to breed standards. Vet J. 2009, 182: 402-411. 10.1016/j.tvjl.2009.08.033.PubMedView ArticleGoogle Scholar
- Summers JF, Diesel G, Asher L, McGreevy PD, Collins LM: Inherited defects in pedigree dogs. Part 2: Disorders that are not related to breed standards. Vet J. 2010, 183: 39-45. 10.1016/j.tvjl.2009.11.002.PubMedView ArticleGoogle Scholar
- Ness AR: The Avon Longitudinal Study of Parents and Children (ALSPAC)–a resource for the study of the environmental determinants of childhood obesity. Eur J Endocrinol. 2004, 151: U141-U149. 10.1530/eje.0.151U141.PubMedView ArticleGoogle Scholar
- Golding J: Children of the nineties. A longitudinal study of pregnancy and childhood based on the population of Avon (ALSPAC). West Engl Med J. 1990, 105: 80-82.PubMedGoogle Scholar
- Elks CE, Loos RJF, Sharp SJ, Langenberg C, Ring SM, Timpson NJ, Ness AR, Ness AR, Davey Smith G, Dunger DB, Wareham NJ, et al: Genetic markers of adult obesity risk are associated with greater early infancy weight gain and growth. PLoS Med. 2010, 7: e1000284-10.1371/journal.pmed.1000284.PubMedPubMed CentralView ArticleGoogle Scholar
- Barnett JH, Heron J, Ring SM, Golding J, Goldman D, Xu K, Jones PB: Gender-Specific Effects of the Catechol-O-Methyltransferase Val108/158Met Polymorphism on Cognitive Function in Children. Am J Psychiatry. 2007, 164: 142-149. 10.1176/appi.ajp.164.1.142.PubMedView ArticleGoogle Scholar
- Ollier W, Sprosen T, Peakman T: UK Biobank: from concept to reality. Pharmacogenomics. 2005, 6: 639-646. 10.2217/14622422.214.171.1249.PubMedView ArticleGoogle Scholar
- Green LE, Berriatua E, Morgan KL: A multi-level model of data with repeated measures of the effect of lamb diarrhoea on weight. Prev Vet Med. 1998, 36: 85-94. 10.1016/S0167-5877(98)00086-5.PubMedView ArticleGoogle Scholar
- French NP, Wall R, Morgan KL: Lamb tail docking: a controlled field study of the effects of tail amputation on health and productivity. Vet Rec. 1994, 134: 463-467. 10.1136/vr.134.18.463.PubMedView ArticleGoogle Scholar
- Carson C, McKay JS, Brooks HW, Kelly DF, Stidworthy MF, Wibbelt G, Morgan KL: Establishment and maintenance of a longitudinal study of bovine spongiform encephalopathy (the ULiSES scheme). Prev Vet Med. 2001, 51: 245-257. 10.1016/S0167-5877(01)00216-1.PubMedView ArticleGoogle Scholar
- Tower RB, Nokota M: Pet companionship and depression: Results from a United States Internet sample. Anthrozoos. 2006, 19: 50-64. 10.2752/089279306785593874.View ArticleGoogle Scholar
- Smith B, Smith TC, Gray GC, Ryan MAK, Millennium Cohort Study Team: When epidemiology meets the internet: web-based surveys in the millennium cohort study. Am J Epidemiol. 2007, 166: 1345-1354. 10.1093/aje/kwm212.PubMedView ArticleGoogle Scholar
- Ekman A, Dickman PW, Klint A, Weiderpass E, Litton JE: Feasibility of using web-based questionnaires in large population-based epidemiological studies. Eur J Epidemiol. 2006, 21: 103-111. 10.1007/s10654-005-6030-4.PubMedView ArticleGoogle Scholar
- Gobar GM, Case JT, Kass PH: Program for surveillance of causes of death of dogs, using the Internet to survey small animal veterinarians. J Am Vet Med Assoc. 1998, 213: 251-256.PubMedGoogle Scholar
- van Gelder MMHJ, Bretveld RW, Roeleveld N: Web-based Questionnaires: The Future in Epidemiology?. Am J Epidemiol. 2010, 172: 1292-1298. 10.1093/aje/kwq291.PubMedView ArticleGoogle Scholar
- VeNom Veterinary Nomenclature. http://www.venomcoding.org.
- The R Project for Statistical Computing. http://www.R-project.org.
- Therneau T: A Package for Survival Analysis in S. R package version 2.36-14. 2012, Available at: http://cran.r-project.org/web/packages/survival/Google Scholar
- Avon Longitudinal Study of Parents and Children: Representativeness. http://www.bristol.ac.uk/alspac/sci-com/resource/represent/.
- Leaverton PE, Sorlie PD, Kleinman JC, Dannenberg AL, Ingster-Moore L, Kannel WB, Cornoni-Huntley JC: Representativeness of the Framingham risk model for coronary heart disease mortality: a comparison with a national cohort study. J Chronic Dis. 1987, 40: 775-784. 10.1016/0021-9681(87)90129-9.PubMedView ArticleGoogle Scholar
- Richiardi L, Baussano I, Vizzini L, Douwes J, Pearce N, Merletti F: Feasibility of recruiting a birth cohort through the Internet: the experience of the NINFEA cohort. Eur J Epidemiol. 2007, 22: 831-837. 10.1007/s10654-007-9194-2.PubMedView ArticleGoogle Scholar
- Leece P, Bhandari M, Sprague S, Swiontkowski MF, Schemitsch EH, Tornetta P, Devereaux PJ, Guyatt GH: Internet versus mailed questionnaires: a controlled comparison (2). J Med Internet Res. 2004, 6: e39-10.2196/jmir.6.4.e39.PubMedPubMed CentralView ArticleGoogle Scholar
- Leece P, Bhandari M, Sprague S, Swiontkowski MF, Schemitsch EH, Tornetta P, Devereaux PJ, Guyatt GH: Internet versus mailed questionnaires: a randomized comparison (2). J Med Internet Res. 2004, 6: e30-10.2196/jmir.6.3.e30.PubMedPubMed CentralView ArticleGoogle Scholar
- Kongsved SM, Basnov M, Holm-Christensen K, Hjollund NH: Response rate and completeness of questionnaires: a randomized study of Internet versus paper-and-pencil versions. J Med Internet Res. 2007, 9: e25-10.2196/jmir.9.3.e25.PubMedPubMed CentralView ArticleGoogle Scholar
- Brown WJ, Bryson L, Byles JE, Dobson AJ, Lee C, Mishra G, Schofield M: Women's Health Australia: recruitment for a national longitudinal cohort study. Women Health. 1998, 28: 23-40.PubMedView ArticleGoogle Scholar
- Westgarth C, Pinchbeck G, Bradshaw J, Dawson S, Gaskell R, Christley R: Factors associated with dog ownership and contact with dogs in a UK community. BMC Veterinary Research. 2007, 3: 5-10.1186/1746-6148-3-5.PubMedPubMed CentralView ArticleGoogle Scholar
- Edwards PJ, Roberts I, Clarke MJ, Diguiseppi C, Wentz R, Kwan I, Cooper R, Felix LM, Pratap S: Methods to increase response to postal and electronic questionnaires. Cochrane Database Syst Rev. 2009, MR000008-10.1002/14651858.MR000008.pub4.Google Scholar
- Richiardi L, Pivetta E, Merletti F: Recruiting study participants through Facebook. Epidemiology. 2012, 23: 175.PubMedView ArticleGoogle Scholar
- Robroek SJ, Lindeboom DE, Burdorf A: Initial and sustained participation in an internet-delivered long-term worksite health promotion program on physical activity and nutrition. J Med Internet Res. 2012, 14: e43-10.2196/jmir.1788.PubMedPubMed CentralView ArticleGoogle Scholar
- Walker J, Fairley C, Urban E, Chen M, Bradshaw C, Walker S, Donovan B, Tabrizi S, McNamee K, Currie M, et al: Maximising retention in a longitudinal study of genital Chlamydia trachomatis among young women in Australia. BMC Public Health. 2011, 11: 156-10.1186/1471-2458-11-156.PubMedPubMed CentralView ArticleGoogle Scholar
- Office for National Statistics: Smoking and drinking among adults. Newport: South Wales 2009.Google Scholar
- The Scottish Government: Annual report: Results from 2009/2010 Scottish Household Survey. Edinburgh: The Scottish Government 2011.Google Scholar
- Owen CG, Nightingale CM, Rudnicka AR, Ekelund U, McMinn AM, van Sluijs EMF, Griffin SJ, Cook DG, Whincup PH: Family Dog Ownership and Levels of Physical Activity in Childhood: Findings From the Child Heart and Health Study in England. Am J Public Health. 2010, 100: 1669-1671. 10.2105/AJPH.2009.188193.PubMedPubMed CentralView ArticleGoogle Scholar
- Cutt H, Giles-Corti B, Knuiman M, Burke V: Dog ownership, health and physical activity: A critical review of the literature. Health & Place. 2007, 13: 261-272. 10.1016/j.healthplace.2006.01.003.View ArticleGoogle Scholar
- Hiscock R, Bauld L, Amos A, Fidler JA: Munaf+Â¦ M: Socioeconomic status and smoking: a review. Ann N Y Acad Sci. 2012, 1248: 107-123. 10.1111/j.1749-6632.2011.06202.x.PubMedView ArticleGoogle Scholar
- Bonnett BN, Egenvall A: Age Patterns of Disease and Death in Insured Swedish Dogs, Cats and Horses. J Comp Pathol. 2010, 142: S33-S38.PubMedView ArticleGoogle Scholar
- Hippisley-Cox J, Fenty J, Heaps M: Trends in Consultation Rates in General Practice 1995 to 2006: Analysis of the QRESEARCH database. 2007, London: The Information Centre for Health and Social CareGoogle Scholar
- Mateus A, Brodbelt DC, Barber N, Stark KDC: Antimicrobial usage in dogs and cats in first opinion veterinary practices in the UK. J Small Anim Pract. 2012. in pressGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.