| Literature DB >> 23777563 |
Martin J Downes1, Rachel S Dean, Jenny H Stavisky, Vicki J Adams, Douglas J C Grindlay, Marnie L Brennan.
Abstract
BACKGROUND: There are a number of different methods that can be used when estimating the size of the owned cat and dog population in a region, leading to varying population estimates. The aim of this study was to conduct a systematic review to evaluate the methods that have been used for estimating the sizes of owned cat and dog populations and to assess the biases associated with those methods.A comprehensive, systematic search of seven electronic bibliographic databases and the Google search engine was carried out using a range of different search terms for cats, dogs and population. The inclusion criteria were that the studies had involved owned or pet domestic dogs and/or cats, provided an estimate of the size of the owned dog or cat population, collected raw data on dog and cat ownership, and analysed primary data. Data relating to study methodology were extracted and assessed for biases.Entities:
Mesh:
Year: 2013 PMID: 23777563 PMCID: PMC3689088 DOI: 10.1186/1746-6148-9-121
Source DB: PubMed Journal: BMC Vet Res ISSN: 1746-6148 Impact factor: 2.741
Figure 1Flow diagram showing the total number of records identified and the number of records filtered at each stage of the selection process from the literature search of a systematic review on pet population estimation.
Outcome of author contact and critical appraisal (CA) of 31 studies that satisfied the initial inclusion criteria in a systematic review examining methods to estimate owned dog and cat populations
| Acosta-Jamett et al. [ | Yes | | No |
| Agostini et al. [ | No | No author found | |
| Agostini et al. [ | Yes | | No |
| | |||
| Brooks [ | No | No author found | |
| | |||
| De Balogh et al. [ | Yes | | No |
| Degregorio et al. [ | No | No author found | |
| Dias et al. [ | No | Author responded | No |
| Egenvall et al. [ | No | No author found | |
| Gregory and Reid [ | No | No author found | |
| Griffiths and Brenner [ | Yes | | No |
| Ibarra et al. [ | Yes | | No |
| Kitala et al. [ | Yes | | No |
| Larrieu et al. [ | No | No author found | |
| | |||
| Martin et al. [ | No | No author found | |
| Morales et al. [ | No | No author found | |
| Author responded | |||
| Matter [ | No | No author found | |
| Okoh [ | No | No author found | |
| | |||
| Patronek et al. [ | No | No author found | |
| Rangel et al. [ | No | No author found | |
| Rautenbach et al. [ | No | No author found | |
| Serafini et al. [ | No | No author found | |
| | |||
| Subbaraj et al. [ | Yes | | No |
| | |||
| Pet Plan [ | No | No author found | |
| PFMA [ | No | Author responded | No |
1. Studies in bold were included in the final review.
2. Methods were judged to be clear (‘yes’) when the methods for calculating the population size estimate reported in the study were transparent and repeatable.
3. Where the methods were clear enough, no attempt was made to contact the author.
Figure 2Flow diagram showing the total number of records identified and the number of records filtered at each stage of the selection process of a Google search carried out as part of a systematic review on pet population estimation.
Characteristics of the seven studies included in the final analysis of a systematic review examining methods to estimate owned dog and cat populations
| AVMA [ | No aim stated. | Questionnaire mailed to a random selection of potential participants from a list supplied by a commercial company. | National population of the United States of America | Mean number of pets per pet owning household multiplied by (the proportion of pet owning households from the survey by the number of households from National statistics). |
| Dogs = 52.9 million | ||||
| Cats = 59.1 million | ||||
| AVMA [ | No aim stated. | Questionnaire mailed to a random selection of potential participants from a list supplied by a commercial company. | National population of the United States of America | Mean number of pets per pet owning household multiplied by (the proportion of pet owning households from the survey by the number of households from National statistics). |
| Dogs = 69.926 million | ||||
| Cats = 74.059 million | ||||
| Butler and Bingham [ | To provide baseline data on the demography and ecology of the dog population in communal lands in Zimbabwe. | Door to door survey. | National population of Zimbabwe. Seven communal lands surveyed: Ngorima, Soswe, Kandeya, Gokwe, Tsholotsho, Dande, Mtetengwe | Average number of dogs per capita from the survey multiplied by the number of people in Zimbabwe from human statistics. |
| Dogs = 1.36 million | ||||
| Lengerich et al. [ | To apply a random-digit dial telephone survey method for estimating the owned canine and feline populations, and estimate the proportion of dogs and cats with cancer. | Random-digit dial telephone survey. | Population of Marion and Tippecanoe counties of Indiana. | Total number of dogs and cats from the survey by the inverse of the sample fraction from the human census. |
| Cats: | ||||
| Marion = 94,998 (74,348 to 115,648) | ||||
| Tippecanoe = 17,165 (12,569 to 21,761) | ||||
| Dogs: | ||||
| Marion = 144,039 (121,55 to | ||||
| 166,523) | ||||
| Tippecanoe = 18,000 (14,445 to 21,555) | ||||
| Murray et al. [ | To identify characteristics of dog-owning and cat-owning households from a large cross-sectional study and to use these data to estimate the size of the dog and cat populations in the UK, using a method that could easily be repeated to enable pet ownership trends to be monitored. | Telephone survey of a random selection of telephone numbers from a commercially available list of numbers. | National population of the United Kingdom | The predicted cat and dog numbers for each category in the size of the household by the location were calculated from logistic regression of the data from the survey and multiplied by the number of households within each category from national statistics. |
| Cats = 10,332,955 (9,395,642 to 11,270,269) | ||||
| Dogs = 10,522,186 (9,623,618 to 11,420,755) | ||||
| Ortega-Pacheco et al. [ | To generate information regarding the size and structure of the owned-dog populations, and learn about people’s opinions about their dogs and how they take care of them in three rural areas and a large city of Yucatan, Mexico. | Random-digit dial telephone survey in one large urban area and door to door survey in three rural areas. | Three rural areas (Molas, Dzununczn and San Jose Tzal) and one urban area (Merida city) in Yucatan state, Mexico. | Mean number of dogs per household from the survey multiplied by the number of households from National statistics. |
| Molas = 568.5 | ||||
| Dzununczn = 560 | ||||
| San Jose Tzal = 844.5 | ||||
| Merida = 1163 | ||||
| Slater et al. [ | To document the owned pet population size and type including reproduction and dog registration. | Telephone survey of a random selection of telephone numbers from a commercially available list of numbers. | Province of Teramo, Italy | Mean number of pets per pet owning household by the proportion of pet owning households from the survey multiplied by the number of households from National statistics. |
| Cats = 37,081 | ||||
| Dogs = 67,183 |
Advantages and disadvantages of four different collection methods that were used in the seven studies included in the final analysis of a systematic review examining methods to estimate owned dog and cat populations
| Mail out survey using a commercial list of contacts | AVMA [ | Reduces bias towards wealthier participants associated with telephone surveys. | Selection bias introduced as households that are not on the commercial list are excluded. May introduce measurement bias as the participant will be aware what the study is about. |
| Overestimation of population may be introduced as a period prevalence is measured in these studies. | |||
| Door to door survey | Butler and Bingham [ | Reduces non-response. | Costly and time consuming, probably only feasible in a small study area. |
| Selection bias may have been introduced as only houses that were within 500 meters of a road were included and only roads that were passable by vehicle were used. Also true random selection was not used. | |||
| Ortega-Pacheco et al. [ | Costly and time consuming, probably only feasible in a small study area. | ||
| Selection bias may have been introduced in this study as only households with a telephone could be included, this may have led to households with a higher SEC being over represented. Random selection was not used in the door to door surveys. | |||
| Random-digit dialled telephone survey | Lengerich et al. [ | Cost effective and logistically allows a large number of participants to be recruited in a short period of time. | Large numbers of non-domestic based numbers may be included leading to greater non-response. |
| Selection bias may have been introduced in this study as only households with a telephone could be included; this may have led to households with a higher social economic class (SEC) being over-represented. | |||
| Randomised telephone survey using a list of numbers | Slater et al. [ | Cost effective and logistically allows a large number of participants to be recruited in a short period of time. Reduces number of non-household based numbers associated with random digit dial surveys. | Selection bias may have been introduced in this study as only households with a telephone could be included, and if the telephone number was not listed it could not be included. |
| An explanation of the study was given at the start of the interview, which may lead to measurement bias as households with pets might be more likely to complete the questionnaire. | |||
| Murray et al. [ | Selection bias may have been introduced in this study as only households with a telephone could be included, and if the telephone number was not listed it could not be included. |
Advantages and disadvantages of the three different analytical/statistical methods that were used to estimate the pet population in the seven studies included in the final analysis of a systematic review examining methods to estimate owned dog and cat populations
| Mean number of dogs/cats per household multiplied by the number of households in the area | Lengerich et al. [ | Simple method that does not require complex statistics. Does not rely on large sample sizes. | Prone to selection and measurement biases. |
| Human density multiplied by number of dogs per human | Slater et al. [ | Simple method that does not require complex statistics. Does not rely on large sample sizes. | Prone to selection and measurement biases. |
| Calculations using predictors of ownership | Murray et al. [ | Improves precision of the population estimates. | Requires large numbers of participants so may be more costly. Can be prone to measurement bias. |
The definition of potential biases as they affect pet ownership studies
| Selection bias | Selection bias is a systematic error that occurs when the distribution of factors associated with pet ownership in the target population differs from those in the study population [ |
| Non-response bias | Non-response bias is when the characteristics that are associated with pet ownership of respondents differ from the characteristics of those that did not respond [ |
| Measurement bias | Measurement bias is caused by inaccurate responses to survey questions which can result in misclassification of pet owners [ |
| Length of sampling bias | Biases introduced by length of sampling time are introduced by estimating point prevalence (number of owned pets) over a relatively long sampling time, or by using period prevalence (number of owned pets in a given time period) to estimate point prevalence [ |