Sampling and coverage issues of telephone surveys used for collecting health information in Australia: results from a face-to-face survey from 1999 to 2008

  • Eleonora Dal Grande1Email author and

    Affiliated with

    • Anne W Taylor1, 2

      Affiliated with

      BMC Medical Research Methodology201010:77

      DOI: 10.1186/1471-2288-10-77

      Received: 17 August 2009

      Accepted: 26 August 2010

      Published: 26 August 2010

      Abstract

      Background

      To examine the trend of "mobile only" households, and households that have a mobile phone or landline telephone listed in the telephone directory, and to describe these groups by various socio-demographic and health indicators.

      Method

      Representative face-to-face population health surveys of South Australians, aged 15 years and over, were conducted in 1999, 2004, 2006, 2007 and 2008 (n = 14285, response rates = 51.9% to 70.6%). Self-reported information on mobile phone ownership and usage (1999 to 2008) and listings in White Pages telephone directory (2006 to 2008), and landline telephone connection and listings in the White Pages (1999 to 2008), was provided by participants. Additional information was collected on self-reported health conditions and health-related risk behaviours.

      Results

      Mobile only households have been steadily increasing from 1.4% in 1999 to 8.7% in 2008. In terms of sampling frame for telephone surveys, 68.7% of South Australian households in 2008 had at least a mobile phone or landline telephone listed in the White Pages (73.8% in 2006; 71.5% in 2007). The proportion of mobile only households was highest among young people, unemployed, people who were separated, divorced or never married, low income households, low SES areas, rural areas, current smokers, current asthma or people in the normal weight range. The proportion with landlines or mobiles telephone numbers listed in the White Pages telephone directory was highest among older people, married or in a defacto relationship or widowed, low SES areas, rural areas, people classified as overweight, or those diagnosed with arthritis or osteoporosis.

      Conclusion

      The rate of mobile only households has been increasing in Australia and is following worldwide trends, but has not reached the high levels seen internationally (12% to 52%). In general, the impact of mobile telephones on current sampling frames (exclusion or non-listing of mobile only households or not listed in the White Pages directory) may have a low impact on health estimates obtained using telephone surveys. However, researchers need to be aware that mobile only households are distinctly different to households with a landline connection, and the increase in the number of mobile-only households is not uniform across all groups in the community. Listing in the White Pages directory continues to decrease and only a small proportion of mobile only households are listed. Researchers need to be aware of these telephone sampling issues when considering telephone surveys.

      Background

      With the rapid changes to the telecommunications industry, it is unknown whether telephone surveys can continue to be used to reliably collect representative information regarding health status and health risk behaviours. Telephone surveys, traditionally using landline telephones, have been used to collect and monitor health-related information over the last 30 years [13] and have been used to determine the prevalence of chronic conditions, health-related risk behaviours, and assess knowledge, attitudes, and opinions on health issues. Telephone surveys using Computer Assisted Telephone Interviewing (CATI) technology have been seen as a cost-effective and timely method of collecting health information [49] and have provided greater standardisation of administration through closer supervision of interviewers compared to traditional face-to-face methods.

      In Australia, for the last decade, the coverage of households with a telephone connected (landline) and the adequacy of the sampling frame(s) have been a concern for those involved in epidemiologically-sound telephone surveys. The proportion of people who do not have a landline telephone connected in the household is not uniformly distributed in the population[10, 11] and there is difficulty in obtaining a complete sampling frame[12]. With the exception of the Northern Territory, the landline telephone coverage in Australian households has been historically very high (96.8% in South Australia in 2002[10], 94.4% in Australia in 1991[13]). There are two main population sampling methods used in Australia: Australian Electronic White Pages (EWP) directory and Random Digit Dialling (RDD). EWP consists of all landline telephone numbers, names and address details for a household or business. All these telephone numbers are centrally located and routinely listed in the EWP regardless of the telecommunication carrier. Households can opt, at a cost, to not have their telephone number have listed in the EWP (also known as silent numbers). Mobile numbers are not routinely listed in the EWP, so owners can choose, at a cost, to have their mobile number listed in the EWP. This exclusion of unlisted numbers from the sampling frame can have an effect on the estimates for the population in telephone surveys and remains an important concern for researchers [11, 12]. RDD methods in Australia are based on the prefixes of the telephone numbers in the EWP to generate a sampling frame in order to include the silent numbers. This method is referred to as list-assisted RDD (LA-RDD). However, these RDD sampling methods do not include mobile numbers in their sampling frame. The differences and similarities between these two methods, in the Australian context, have been described elsewhere [1012, 14].

      Since the early 2000 s, international trends have seen households change to new telecommunications technologies, whereby individuals in the household are solely contactable by mobile phones or other means such as Voice over Internet Protocol (VoIP), not by the traditional landline telephone. This has negatively impacted on telephone surveys and sampling methodologies. International studies have shown a dramatic increase in mobile only households (those not having a landline telephone connected to the household). In 2006, 11.8% of households in the United States [15], 52% in Finland [16] and 17% in France [16] were mobile only. In 2002, 13.1% of households in Italy were mobile only households [17].

      As a result of these rapid changes both in Australia and worldwide, determining an adequate sampling frame to include these non-traditional telephone numbers and to demarcate geographic locations, is becoming increasingly important. This paper presents how two factors impact household telephone surveys in Australia; the presence of mobile only individuals and the lack of full enumeration of telephone numbers in a telephone directory. Mobile only households are not covered in the RDD sampling frame and unlisted telephone numbers (landlines and mobiles) are not covered in the EWP telephone directory. Both samplings frames exclude people with no mobiles or landline telephones. The aim of this study is to examine the trend of mobile only households and households that have a mobile telephone or landline telephone listing in the EWP, and to describe these groups by various socio-demographics and health indicators to determine the potential bias due to non-coverage in the sample in the Australian context.

      Methods

      Survey design and sample section

      Questions regarding landline telephone, mobile, and internet connections were included in the 1999, 2004, 2006, 2007 and 2008 South Australian Health Omnibus Surveys (HOS)[18, 19]. HOS is a multi-stage, systematic, clustered area sample of households conducted face-to-face annually in spring based on the Australian Bureau of Statistics (ABS) collector districts (CDs). The HOS samples included households randomly selected from CDs, from the metropolitan Adelaide area and country towns with a population of 1,000 people or more. Within each CD, a random starting point was selected and from this point 10 households were then selected in a given direction with a fixed skip interval. Hotels, motels, hospitals, hostels and other institutions were excluded from the sample. Approach letters were sent to selected households informing them of the survey. One person aged 15 years or over, who was last to have a birthday, was randomly selected from each household for interview. The interviews were conducted in people's homes by trained interviewers. Up to six call back visits were made to the chosen households to interview the selected person. There was no replacement for non-respondents. Response rates (and sample size) from the surveys were 70.6% (n = 3012) in 1999, 68.4% (n = 2982) in 2004, 54.9% (n = 2969) in 2006, 51.9% (n = 2507) in 2007 and 53.6% (n = 2824) in 2008. Each individual data set was weighted by five year age groups, sex, area (metropolitan Adelaide and SA country) and household size to the most recent ABS Census or Estimated Residential Population for South Australia to provide population estimates.

      Data items

      Questions about landline telephone connection and listing in the EWP (alphabetic directory of non-silent phone numbers belonging to residential households and businesses which include surname and address details) were included in the 1999, 2004, 2006, 2007 and 2008 surveys. These surveys also included questions on mobile phone ownership and usage in the household. Additional questions on mobile phone listing in the EWP, and future landline and mobile phone ownership plans were included in 2006, 2007 and 2008.

      Identical demographic variables included in each survey were age, sex, area of residence, country of birth, education level, marital status, gross annual household income, and work status. The Index of Relative Social Disadvantage (IRSD) developed by the ABS was also calculated to identify the geographical areas that were relatively disadvantaged[20]. The IRSD is a composite measure based on selected Census variables such as income, educational attainment and employment status. The IRSD scores were grouped into quintiles for analysis where the highest quintile comprises postcodes with the highest IRSD scores (most advantaged areas).

      Chronic conditions included medically confirmed diabetes, current asthma, arthritis and osteoporosis. Self-reported health risk factor data included smoking status and body mass index (BMI) which was derived from self-reported weight and height and recoded into four categories (underweight, normal weight, overweight and obese) [21]. Mobile only households were defined as households with no landline telephone connected to the house and if mobile phones were currently being used by members of the household.

      The questionnaire and methodology for these surveys were approved by the Human Research Ethics Committee of the South Australian Department of Health (SA Health).

      Data analyses

      Data analysis was conducted using SPSS for Windows Version 15.0. The conventional p value of 0.05 was used as the criterion for statistical significance. To compare prevalence over time (from 1999 to 2008), χ2 test for trend was used for mobile only households, households with landline telephone only connections and households with both a landline telephone connection and mobile. A comparison between 2006, 2007 and 2008 using χ2 tests for trend was undertaken to assess for change in various socio-demographic and health-related variables between mobile only households and households with a landline or a mobile telephone number listed in the EWP.

      Separate univariate analyses using χ2 tests were undertaken for 2006, 2007 and 2008, to assess mobile only households, and households with a landline or a mobile telephone number listed in the EWP on a range of socio-demographic and health-related variables.

      Results

      Table 1 shows the trends of mobile only and landline households from 1999, 2004, 2006 to 2008. The proportion of mobile only households has been steadily increasing over the eight years (χ2 trend = 177.01, p < 0.001). There was a statistically significant decline in the proportion of households with landline telephone only connections (χ2 trend = 1693.6, p < 0.001) from 44.6% in 1999 to 6.9% in 2008, and a statistically significant increase in households with both a landline telephone connection and mobile (χ2 trend = 1188.6, p < 0.001) from 52.7% in 1999 to 83.8% in 2008.
      Table 1

      Telephone (landline) and mobile status of household, and household has landline and/or mobile telephone listed in the Australian Electronic White Pages by year

        

      Telephone (landline) and mobile status of household

      Household has landline and/or at least one mobile telephone listed in directory

        

      No landline telephone or mobile

      Mobile only household

      Landline telephone only

      Landline telephone and mobile

      Not stated

       

      No

      Yes

      Year

      n

      % (95% CI)

      % (95% CI)

      % (95% CI)

      % (95% CI)

      %

      n

      % (95% CI)

      % (95% CI)

      1999

      3012

      1.3 (1.0 - 1.8)

      1.4 (1.0 - 1.8)

      44.6 (42.9 - 46.4)

      52.7 (50.9 - 54.5)

          

      2004

      2982

      1.2 (0.8 - 1.6)

      3.4 (2.8 - 4.1)

      95.4 (94.6 - 96.1) *

      0.1

         

      2006

      2969

      0.3 (0.1 - 0.5)

      5.2 (4.4 - 6.0)

      9.7 (8.7 - 10.8)

      84.7 (83.4 - 86.0)

      0.1

      2961

      26.2 (24.6 - 27.8)

      73.8 (72.2 - 75.4)

      2007

      2507

      1.1 (0.7 - 1.6)

      7.1 (6.1 - 8.1)

      11.1 (9.9 - 12.3)

      80.6 (79.0 - 82.1)

      0.2

      2480

      28.5 (26.8 - 30.3)

      71.5 (69.7 - 73.2)

      2008

      2824

      0.3 (0.2 - 0.6)

      8.7 (7.7 - 9.8)

      6.9 (6.1 - 7.9)

      83.8 (82.4 - 85.1)

      0.3

      2814

      31.3 (29.5 - 32.9)

      68.7 (66.7 - 70.1)

      * In 2004 HOS, households with a landline were not asked if there were any person in the household that had a mobile phone

      Respondents were asked if their mobile or landline telephones were listed in the EWP. Of mobile only households, 6.9% had their mobile number listed in the EWP in 2008 (8.0% in 2006; 3.4% in 2007). Of households with both a mobile and landline telephone connected, 7.4% had their mobile number listed in 2008 (7.3% in both 2006 and 2007). Examination of households with a landline telephone connection revealed that 77.0% of these households in 2006, 76.3% in 2007 and 74.1% in 2008, had their landline telephone numbers listed in the EWP (χ2 trend = 18.6, p < 0.001). Hence, 68.7% of South Australian households in 2008 had at least a mobile phone and/or landline telephone listed in the EWP (73.8% in 2006, 71.5% in 2007) (Table 1).

      When the proportion of mobile only household respondents was compared on selected demographics and health indicators over the three years (2006 to 2008) (Table 2), increased trends were significant for a wide range of variables. When households with a mobile or landline telephone number listed in the EWP (Table 3) were examined over the three years (2006 to 2008), decreasing trends were apparent for a range of variables.
      Table 2

      Proportion of people living in mobile only households by selected demographic, health conditions, and health related risk factors from 2006 to 2008

        

      2006

        

      2007

        

      2008

       

      Test for trend

       

      n

      % (95% CI)

      P value 1

      n

      % (95% CI)

      P value 1

      n

      % (95% CI)

      P value 1

      P value 2

      DEMOGRAPHICS

                

      Gender

        

      0.007

        

      < 0.001

        

      0.149

       

      Male

      92/1460

      6.3 (5.2 - 7.7)

       

      109/1222

      8.9 (7.4 - 10.6)

       

      131/1382

      9.4 (8.0 - 11.1)

       

      0.002

      Female

      62/1509

      4.1 (3.2 - 5.2)

       

      68/1285

      5.3 (4.2 - 6.7)

       

      114/1433

      7.9 (6.6 - 9.4)

       

      < 0.001

      Age Groups

        

      < 0.001

        

      < 0.001

        

      < 0.001

       

      15 to 29 years

      73/708

      10.4 (8.3 - 12.8)

       

      73/587

      12.7 (10.2 - 15.7)

       

      114/571

      17.9 (15.2 - 20.9)

       

      < 0.001

      30 to 44 years

      47/777

      6.1 (4.7 - 8.1)

       

      67/644

      10.5 (8.4 - 13.2)

       

      76/693

      11.0 (8.9 - 13.6)

       

      0.001

      45 years and over

      34/1485

      2.3 (1.6 - 3.2)

       

      38/1276

      3.0 (2.2 - 4.0)

       

      43/1420

      3.0 (2.2 - 4.0)

       

      0.213

      Country of Birth

        

      0.935

        

      0.001

        

      < 0.001

       

      Australia

      116/2197

      5.3 (4.4 - 6.3)

       

      152/1911

      8.0 (6.8 - 9.3)

       

      209/2110

      9.9 (8.7 - 11.3)

       

      < 0.001

      UK & Ireland

      17/354

      4.9 (3.1 - 7.7)

       

      5/242

      1.9 #

       

      6/296

      2.1 (1.0 - 4.5)

       

      0.040

      Other

      21/418

      5.0 (3.3 - 7.5)

       

      20/354

      5.8 (3.8 - 8.7)

       

      29/409

      7.0 (4.9 - 9.8)

       

      0.218

      Marital status a

        

      < 0.001

        

      < 0.001

        

      < 0.001

       

      Married/defacto

      66/1862

      3.5 (2.8 - 4.5)

       

      53/1534

      3.5 (2.7 - 4.5)

       

      111/1765

      6.3 (5.2 - 7.5)

       

      < 0.001

      Separated/divorced

      24/248

      9.6 (6.5 - 13.9)

       

      36/227

      16.0 (11.8 - 21.3)

       

      27/237

      11.3 (7.8 - 15.9)

       

      0.560

      Widowed

      3/156

      1.6 #

       

      4/141

      3.1 #

       

      5/149

      3.6 (1.6 - 7.9)

       

      0.286

      Never married

      62/694

      8.9 (7.0 - 11.2)

       

      83/602

      13.8 (11.3 - 16.8)

       

      101/661

      15.2 (12.6 - 18.1)

       

      < 0.001

      Educational Attainment b

        

      0.007

        

      < 0.001

        

      0.002

       

      None to secondary schooling

      81/1385

      5.8 (4.7 - 7.2)

       

      107/1234

      8.7 (7.2 - 10.4)

       

      134/1281

      10.4 (8.9 - 12.2)

       

      < 0.001

      Trade qualifications,

      Certificate, Diploma

      64/1086

      5.8 (4.6 - 7.4)

       

      60/843

      7.1 (5.6 - 9.1)

       

      82/1015

      8.1 (6.6 - 9.9)

       

      0.042

      Bachelor Degree or higher

      10/488

      2.1 (1.1 - 3.8)

       

      10/428

      2.4 (1.3 - 4.3)

       

      27/514

      5.2 (3.6 - 7.5)

       

      0.005

      Area of residence

        

      0.089

        

      < 0.001

        

      < 0.001

       

      Metropolitan

      101/2123

      4.8 (3.9 - 5.8)

       

      107/1847

      5.8 (4.8 - 7.0)

       

      160/2152

      7.4 (6.4 - 8.6)

       

      < 0.001

      Country

      53/846

      6.3 (4.8 - 8.1)

       

      70/660

      10.6 (8.5 - 13.2)

       

      84/663

      12.6 (10.3 - 15.4)

       

      < 0.001

      Annual household income

        

      0.001

        

      0.001

        

      0.001

       

      Up to $20,000

      25/387

      6.5 (4.4 - 9.4)

       

      38/335

      11.2 (8.3 - 15.1)

       

      34/342

      9.8 (7.1 - 13.4)

       

      0.105

      $20,001-$40,000

      42/509

      8.2 (6.1 - 10.9)

       

      33/437

      7.6 (5.5 - 10.5)

       

      44/431

      10.2 (7.7 - 13.4)

       

      0.297

      $40,001-$60,000

      24/451

      5.3 (3.6 - 7.8)

       

      28/383

      7.2 (5.0 - 10.2)

       

      41/353

      11.7 (8.8 - 15.5)

       

      < 0.001

      $60,001-$80,000

      11/350

      3.1 (1.7 - 5.4)

       

      22/274

      8.0 (5.3 - 11.8)

       

      23/326

      7.0 (4.7 - 10.3)

       

      0.027

      $80,001 or more

      20/675

      2.9 (1.9 - 4.5)

       

      22/600

      3.7 (2.5 - 5.5)

       

      42/784

      5.4 (4.0 - 7.2)

       

      0.018

      Not stated

      33/597

      5.6 (4.0 - 7.7)

       

      34/477

      7.2 (5.2 - 9.9)

       

      61/580

      10.4 (8.2 - 13.1)

       

      0.002

      Work status c

        

      < 0.001

        

      < 0.001

        

      < 0.001

       

      Work full time

      69/1109

      6.2 (4.9 - 7.8)

       

      76/920

      8.2 (6.6 - 10.2)

       

      109/1091

      10.0 (8.4 - 11.9)

       

      0.001

      Work part time

      30/566

      5.2 (3.7 - 7.4)

       

      27/455

      5.9 (4.1 - 8.5)

       

      40/494

      8.2 (6.1 - 10.9)

       

      0.055

      Home Duties

      16/272

      5.7 (3.5 - 9.2)

       

      28/255

      10.9 (7.7 - 15.4)

       

      26/227

      11.6 (8.1 - 16.5)

       

      0.019

      Unemployed

      16/79

      20.9 (13.4 - 31.1)

       

      22/76

      28.6 (19.7 - 39.6)

       

      19/77

      24.1 (15.9 - 34.8)

       

      0.634

      Retired

      3/578

      0.6 #

       

      6/505

      1.2 (0.6 - 2.6)

       

      10/575

      1.8 (1.0 - 3.2)

       

      0.068

      Student

      9/220

      4.1 (2.2 - 7.6)

       

      9/217

      4.2 (2.2 - 7.7)

       

      23/227

      10.0 (6.7 - 14.6)

       

      0.009

      Other/Not working because

      of work related injury

      11/104

      10.8 (6.2 - 18.2)

       

      10/79

      12.3 (6.8 - 21.3)

       

      15/123

      12.3 (7.6 - 19.3)

       

      0.735

      SEIFA IRSD Quintiles d

        

      0.001

        

      < 0.001

        

      < 0.001

       

      Lowest/low (most

      disadvantaged)

      90/1293

      7.0 (5.7 - 8.5)

       

      118/1124

      10.5 (8.9 - 12.4)

       

      159/1247

      12.7 (11.0 - 14.7)

       

      < 0.001

      Middle

      25/578

      4.3 (2.9 - 6.3)

       

      31/496

      6.3 (4.5 - 8.8)

       

      31/520

      5.9 (4.2 - 8.3)

       

      0.314

      High/Highest (least

      disadvantaged)

      39/1088

      3.6 (2.6 - 4.9)

       

      25/882

      2.8 (1.9 - 4.1)

       

      55/1048

      5.3 (4.1 - 6.8)

       

      0.017

      HEALTH CONDITIONS

      AND HEALTH RELATED

      RISK FACTORS

                

      Diabetes

      13/197

      6.4 (3.8 - 10.8)

      0.413

      6/168

      3.3 (1.5 - 7.3)

      0.051

      24/214

      11.0 (7.5 - 15.9)

      0.181

      0.053

      Arthritis

      18/694

      2.6 (1.6 - 4.0)

      < 0.001

      27/595

      4.6 (3.2 - 6.5)

      0.006

      31/707

      4.3 (3.1 - 6.1)

      < 0.001

      0.092

      Osteoporosis

      2/184

      1.3 #

      0.013

      6/168

      3.3 (1.5 - 7.3)

      0.051

      3/158

      2.1 #

      0.002

      0.618

      Asthma (current)

      37/364

      10.1 (7.4 - 13.6)

      < 0.001

      31/290

      10.7 (7.7 - 14.8)

      0.009

      47/385

      12.1 (9.2 - 15.8)

      0.009

      0.377

      Smoking status e

        

      < 0.001

        

      < 0.001

        

      < 0.001

       

      Non/Ex smoker

      78/2357

      3.3 (2.7 - 4.1)

       

      87/2009

      4.3 (3.5 - 5.3)

       

      138/2264

      6.1 (5.2 - 7.2)

       

      < 0.001

      Current smoker

      76/611

      12.4 (10.1 - 15.3)

       

      90/495

      18.2 (15.1 - 21.9)

       

      106/551

      19.2 (16.2 - 22.7)

       

      0.002

      Body mass index (BMI) f

        

      0.058

        

      < 0.001

        

      0.049

       

      Underweight <18.5

      3/64

      4.8 #

       

      14/76

      18.9 (11.7 - 29.1)

       

      4/63

      5.7 #

       

      0.998

      Normal 18.5-24.9

      65/1144

      5.7 (4.5 - 7.2)

       

      79/925

      8.5 (6.9 - 10.5)

       

      99/1005

      9.8 (8.2 - 11.8)

       

      < 0.001

      Overweight 25.0-29.9

      28/848

      3.3 (2.3 - 4.7)

       

      47/769

      6.1 (4.6 - 8.0)

       

      52/820

      6.4 (4.9 - 8.2)

       

      0.005

      Obese 30.0+

      33/565

      5.9 (4.2 - 8.2)

       

      20/471

      4.2 (2.7 - 6.4)

       

      46/560

      8.3 (6.3 - 10.8)

       

      0.081

      Overall

      154/2969

      5.2 (4.5 - 6.1)

       

      177/2507

      7.1 (6.1 - 8.1)

       

      244/2816

      8.7 (7.7 - 9.8)

       

      < 0.001

      1 p values that are bold denotes statistical significance at the 0.05 level from the X2 test for that variable;

      2 p values that are bold denotes statistical significance at the 0.05 level from the X2 test for trend for the 2006 to 2008 time period for that category; CI confidence interval of proportion

      a 10 cases missing for 2006, 4 cases missing for 2007 and 7 cases missing for 2008; b 9 cases missing for 2006, 1 case missing for 2007 and 9 cases missing for 2008; c 42 cases missing for 2006, 1 case missing for 2007 and 10 cases missing for 2008; d 10 cases missing for 2006, 5 cases missing for 2007; e 2 cases missing for 2006, 2 cases missing for 2007; f 348 cases missing for 2006, 265 cases missing for 2007 and 369 cases for 2008

      Table 3

      Proportion of people living in households where mobile phone or landline telephone is listed in the White Pages by selected demographic, health conditions, and health related risk factors from 2006 to 2008

        

      2006

        

      2007

        

      2008

       

      Test for

      trend

       

      n

      % (95% CI)

      P value 1

      n

      % (95% CI)

      P value 1

      n

      % (95% CI)

      P value 1

      P value 2

      DEMOGRAPHICS

                

      Gender

        

      0.625

        

      0.557

        

      0.842

       

      Male

      1106/1507

      74.2 (71.9 - 76.4)

       

      915/1271

      70.9 (68.3 - 73.4)

       

      989/1436

      68.5 (66.0 - 70.9)

       

      0.006

      Female

      1079/1454

      73.4 (71.1 - 75.6)

       

      857/1209

      72.0 (69.5 - 74.4)

       

      944/1379

      68.9 (66.4 - 71.2)

       

      0.001

      Age Groups

        

      < 0.001

        

      < 0.001

        

      < 0.001

       

      15 to 29 years

      440/707

      62.2 (58.6 - 65.7)

       

      317/571

      55.6 (51.5 - 59.6)

       

      306/570

      53.3 (49.6 - 57.0)

       

      0.002

      30 to 44 years

      554/773

      71.7 (68.4 - 74.7)

       

      429/636

      67.4 (63.6 - 70.9)

       

      438/692

      63.3 (59.6 - 66.8)

       

      0.001

      45 to 59 years

      563/751

      75.0 (71.8 - 78.0)

       

      466/627

      74.4 (70.9 - 77.7)

       

      493/676

      73.0 (69.5 - 76.2)

       

      0.384

      60 years and over

      628/730

      86.1 (83.4 - 88.4)

       

      560/647

      86.7 (83.8 - 89.1)

       

      628/746

      84.3 (81.5 - 86.7)

       

      0.313

      Country of Birth

        

      0.639

        

      0.004

        

      < 0.001

       

      Australia

      1627/2191

      74.3 (72.4 - 76.1)

       

      1367/1886

      72.5 (70.4 - 74.4)

       

      1460/2104

      69.4 (67.4 - 71.3)

       

      < 0.001

      UK & Ireland

      256/353

      72.7 (67.8 - 77.0)

       

      179/241

      74.4 (68.5 - 79.5)

       

      221/298

      74.3 (69.0 - 78.9)

       

      0.633

      Other

      302/417

      72.4 (68.0 - 76.5)

       

      227/353

      64.2 (59.0 - 69.0)

       

      251/413

      60.9 (56.2 - 65.5)

       

      < 0.001

      Marital status a

        

      < 0.001

        

      < 0.001

        

      < 0.001

       

      Married/defacto

      1465/1860

      78.8 (76.8 - 80.5)

       

      1188/1525

      77.9 (75.8 - 79.9)

       

      1301/1764

      73.8 (71.7 - 75.8)

       

      < 0.001

      Separated/divorced

      155/246

      62.9 (56.7 - 68.7)

       

      138/222

      61.9 (55.3 - 68.0)

       

      142/236

      60.0 (53.7 - 66.1)

       

      0.518

      Widowed

      118/154

      76.5 (69.2 - 82.5)

       

      110/141

      78.2 (70.7 - 84.2)

       

      118/148

      79.9 (72.7 - 85.5)

       

      0.483

      Never married

      444/690

      64.4 (60.8 - 67.9)

       

      336/588

      57.1 (53.1 - 61.0)

       

      370/659

      56.1 (52.3 - 59.9)

       

      0.002

      Educational Attainment b

        

      0.032

        

      0.494

        

      < 0.001

       

      None to secondary

      schooling

      990/1378

      71.8 (69.4 - 74.1)

       

      854/1216

      70.2 (67.6 - 72.7)

       

      840/1275

      65.9 (63.2 - 68.4)

       

      0.001

      Trade qualifications,

      Certificate, Diploma

      826/1085

      76.1 (73.4 - 78.5)

       

      611/836

      73.1 (70.0 - 76.0)

       

      741/1016

      73.0 (70.2 - 75.6)

       

      0.105

      Bachelor Degree or

      higher

      361/488

      74.0 (70.0 - 77.7)

       

      307/427

      72.0 (67.5 - 76.0)

       

      348/514

      67.7 (63.6 - 71.6)

       

      0.027

      Area of residence

        

      < 0.001

        

      < 0.001

        

      0.001

       

      Metropolitan

      1523/2120

      71.8 (69.9 - 73.7)

       

      1264/1830

      69.1 (66.9 - 71.2)

       

      1443/2152

      67.1 (65.0 - 69.0)

       

      0.001

      Country

      663/841

      78.8 (75.9 - 81.5)

       

      508/650

      78.2 (74.9 - 81.2)

       

      490/663

      74.0 (70.5 - 77.2)

       

      0.030

      Annual household

      income

        

      0.121

        

      0.005

        

      0.039

       

      Up to $20,000

      486/675

      74.5 (69.9 - 78.6)

       

      446/597

      66.2 (60.9 - 71.1)

       

      569/784

      64.1 (58.9 - 69.1)

       

      0.812

      $20,001-$40,000

      273/350

      74.5 (70.6 - 78.1)

       

      206/273

      74.3 (70.0 - 78.2)

       

      229/328

      68.7 (64.1 - 72.9)

       

      0.013

      $40,001-$60,000

      341/449

      75.9 (71.8 - 79.6)

       

      269/380

      70.8 (66.0 - 75.1)

       

      241/353

      68.3 (63.3 - 72.9)

       

      0.016

      $60,001-$80,000

      379/509

      78.1 (73.5 - 82.2)

       

      322/434

      75.6 (70.1 - 80.3)

       

      295/429

      69.8 (64.7 - 74.5)

       

      0.049

      $80,001 or more

      284/381

      72.0 (68.5 - 75.2)

       

      218/330

      74.6 (71.0 - 78.0)

       

      216/336

      72.6 (69.4 - 75.6)

       

      0.003

      Not stated

      422/597

      70.8 (67.0 - 74.3)

       

      312/467

      66.7 (62.3 - 70.8)

       

      384/585

      65.6 (61.7 - 69.3)

       

      0.058

      Work status c

        

      < 0.001

        

      < 0.001

        

      < 0.001

       

      Work full time

      796/1109

      71.8 (69.1 - 74.4)

       

      641/909

      70.4 (67.4 - 73.3)

       

      751/1091

      68.9 (66.0 - 71.5)

       

      0.127

      Work part time

      422/565

      74.7 (71.0 - 78.2)

       

      327/450

      72.7 (68.4 - 76.6)

       

      346/494

      70.0 (65.8 - 73.9)

       

      0.084

      Home Duties

      198/270

      73.2 (67.7 - 78.2)

       

      170/252

      67.2 (61.2 - 72.7)

       

      134/222

      60.2 (53.7 - 66.4)

       

      0.002

      Unemployed

      39/78

      50.3 (39.4 - 61.1)

       

      35/74

      47.8 (36.8 - 59.0)

       

      36/76

      47.2 (36.4 - 58.3)

       

      0.707

      Retired

      489/574

      85.2 (82.1 - 87.9)

       

      435/504

      86.2 (82.9 - 88.9)

       

      482/575

      83.8 (80.6 - 86.6)

       

      0.502

      Student

      141/220

      64.3 (57.8 - 70.3)

       

      129/215

      59.8 (53.2 - 66.2)

       

      114/226

      50.5 (44.1 - 57.0)

       

      0.003

      Other/Not working

      because of work

      related injury

      71/104

      68.1 (58.6 - 76.3)

       

      35/74

      48.1 (37.1 - 59.3)

       

      67/121

      55.4 (46.5 - 64.0)

       

      0.067

      SEIFA IRSD

      Quintiles d

        

      0.080

        

      < 0.001

        

      < 0.001

       

      Lowest/low (most

      disadvantaged)

      827/1088

      72.0 (69.5 - 74.4)

       

      666/876

      67.5 (64.7 - 70.2)

       

      804/1237

      64.9 (62.2 - 67.5)

       

      0.001

      Middle

      421/575

      73.3 (69.5 - 76.7)

       

      359/495

      72.5 (68.4 - 76.2)

       

      368/520

      70.7 (66.7 - 74.5)

       

      0.634

      High/Highest (least

      disadvantaged)

      927/1288

      76.0 (73.4 - 78.5)

       

      745/1103

      76.0 (73.1 - 78.7)

       

      761/1048

      72.6 (69.9 - 75.2)

       

      0.123

      HEALTH CONDITIONS

      AND HEALTH RELATED

      RISK FACTORS

                

      Diabetes

      144/197

      73.3 (66.7 - 79.0)

      0.863

      132/168

      78.7 (71.9 - 84.2)

      0.033

      158/214

      73.9 (67.7 - 79.4)

      0.104

      0.994

      Arthritis

      550/693

      79.4 (76.2 - 82.2)

      < 0.001

      452/593

      76.2 (72.6 - 79.5)

      0.003

      534/705

      75.8 (72.5 - 78.8)

      < 0.001

      0.090

      Osteoporosis

      161/184

      87.4 (81.9 - 91.5)

      < 0.001

      132/168

      78.7 (71.9 - 84.2)

      0.033

      111/158

      70.3 (62.8 - 76.9)

      0.703

      < 0.001

      Asthma (current)

      256/364

      70.3 (65.4 - 74.8)

      0.105

      193/283

      68.3 (62.6 - 73.4)

      0.203

      245/385

      63.6 (58.7 - 68.3)

      0.017

      0.048

      Smoking status e

        

      < 0.001

        

      < 0.001

        

      < 0.001

       

      Non/Ex smoker

      1817/2351

      77.3 (75.5 - 78.9)

       

      1492/1994

      74.9 (72.9 - 76.7)

       

      1642/2262

      72.6 (70.7 - 74.4)

       

      < 0.001

      Current smoker

      368/608

      60.5 (56.6 - 64.3)

       

      280/486

      57.6 (53.2 - 61.9)

       

      291/544

      53.6 (49.4 - 57.7)

       

      0.014

      Body mass index

      (BMI) f

        

      0.011

        

      < 0.001

        

      < 0.001

       

      Underweight <18.5

      44/64

      68.9 (56.8 - 78.9)

       

      36/76

      47.7 (36.9 - 58.7)

       

      43/63

      67.2 (54.9 - 77.5)

       

      0.963

      Normal 18.5-24.9

      816/1140

      71.5 (68.8 - 74.1)

       

      635/923

      68.7 (65.7 - 71.6)

       

      641/1005

      63.8 (60.8 - 66.7)

       

      < 0.001

      Overweight 25.0-29.9

      657/847

      77.6 (74.7 - 80.3)

       

      569/762

      74.7 (71.5 - 77.6)

       

      602/820

      73.5 (70.4 - 76.4)

       

      0.053

      Obese 30.0+

      428/565

      75.8 (72.1 - 79.2)

       

      350/463

      75.6 (71.5 - 79.3)

       

      402/560

      71.7 (67.9 - 75.3)

       

      0.108

      Overall

      2186/2961

      73.8 (72.2 - 75.4)

       

      1773/2480

      71.5 (69.7 - 73.2)

       

      1993/2814

      68.7 (66.9 - 70.4)

       

      < 0.001

      1 p values that are bold denotes statistical significance at the 0.05 level from the X2 test for that variable; 2 p values that are bold denotes statistical significance at the 0.05 level from the X2 test for trend for the 2006 to 2008 time period for that category; CI confidence interval of proportion

      a 10 cases missing for 2006, 4 cases missing for 2007 and 7 cases missing for 2008; b 9 cases missing for 2006, 1 case missing for 2007 and 9 cases missing for 2008; c 42 cases missing for 2006, 1 case missing for 2007 and 10 cases missing for 2008; d 10 cases missing for 2006, 5 cases missing for 2007; e 2 cases missing for 2006; f 345 cases missing for 2006, 265 cases missing for 2007 and 366 cases for 2008

      When examined by selected demographics for 2006, 2007 and 2008 (Table 2), respondents who lived in a mobile only household were statistically significantly more likely to be in the younger age groups, separated, divorced or never married, unemployed, born in Australia, have at least obtained secondary schooling, living in rural areas of South Australia, from low income households or from low SES areas of South Australia, and statistically significantly less likely to be in the older age groups, widowed, married or in a defacto relationship, born in UK/Ireland, living in metropolitan Adelaide, from high income households ($80,000 or more per annum), retired, to have a bachelor degree or higher and from high SES areas of South Australia. In terms of health conditions and health related risk factors, respondents who live in mobile only households were statistically significantly more likely to be current smokers, classified as having normal BMI or diagnosed with current asthma, and were statistically significantly less likely to be classified as overweight.

      Respondents from households with a mobile or landline telephone number listed in the EWP (Table 3) were statistically significantly more likely to be in the older age groups, married or in a defacto relationship or widowed, retired, living in rural areas and from high SES areas of South Australia, and statistically significantly less likely to be in the younger age groups, never married, separated or divorced, a student, unemployed or not working because of an injury, living in metropolitan Adelaide or from low SES areas of South Australia. They were also statistically significantly more likely to be classified as being overweight, to have arthritis, or statistically significantly less likely to be current smokers and have normal BMI.

      Further questions were asked to determine the likelihood of people with a landline telephone switching to being a mobile only household. Overall, 6.9% in 2006, 5.9% in 2007, and 8.1% in 2008 indicated that they were 'very likely' while 11.0%, 10.8%, and 12.1% respectively indicated they were 'somewhat likely' to discontinue their landline connection.

      Discussion

      This study has shown, using large representative surveys, the proportion of mobile only households has been increasing in Australia and is following international trends. The prevalence of mobile only households in South Australia among people aged 15 years and over (8.7% in 2008), is not as high as other international studies: 11.8% in the United States[15]; 52% in Finland[16] and 17% in France in 2006[16] and, 13.1% in Italy in 2002[17]. However, the pattern of increasing prevalence remains the same and there are also changes among a range of demographic, health status and health risk behaviours groups. The prevalence of households with neither a mobile phone nor landline telephone has remained low and is likely to have a minimal effect on surveys using mobile phone or landline telephones. However, the mobile only prevalence may increase in South Australia over the next few years since 8% of survey respondents indicated they were very likely to become a mobile only household.

      From this study, using LA-RDD methodology to generate a sampling frame to include unlisted landline telephone numbers excludes mobile only households as well as households with no landline telephone connection which is 9% of the population. This could be considered small [22] and one could argue that excluding this group would have minimal impact on health estimates. However, the results presented in this study indicate that mobile only households have different demographic characteristics to households with landline and/or mobiles. These demographic differences are similar to US studies [15, 23] with a higher proportion of males, younger people, people who are unemployed, separated, divorced or never married, people living in rural areas of South Australia, and low SES households (low income households and reside in the most disadvantaged areas) living in mobile only households. From this study, in terms of health indicators, people classified as overweight, having current asthma and current smokers would also be under-represented in these surveys.

      There are some data quality and collection issues that need to be taken into account when including mobile telephones into the sample frame. One is the location or the situation of the respondent at the time of the interview: respondents may choose not to answer a call to save battery life; answering a call which may incur a cost to both the respondent and the researcher (if the respondent is overseas the fee may be much higher depending on distance from Australia and contractual agreement with individual telecommunication providers); and safety and legal issues, eg the respondent may be driving and using their mobile (texting and talking) at the same time which is illegal in Australia [16]. A study conducted in the US [24] found that those respondents who participated in the survey using a mobile phone, 56% were at home while undertaking the survey, 14% were driving and 13% were at work. The remaining respondents were at other locations such as in public areas, in another person's home, in a car but not driving or on holidays. Another issue found in this US study [24] was the higher proportion of calls to mobile phones resulting in ineligible respondents due to age (people excluded if less than 18 years of age), a lower response rate than calls to landline telephones and a higher refusal rate.

      Furthermore, the selection of the respondent differs between mobile and landline telephones. The mobile telephone is usually individually owned and accessed by that one individual most of the time, compared to landline telephones that belong to a household which may be accessed by one or more people. Hence, consideration needs to be given when sampling strategies in terms of randomly selecting a single person to interview versus a number of eligible people in a household [16].

      This study has highlighted the need to acquire a representative sampling frame and sampling methodology for household telephone (landline) surveys that minimises selection bias and is efficient in terms of administration and cost. With landline telephone numbers, the majority of the telephone numbers are listed in the EWP and the prefix of the telephone numbers are geographically based. Mobile telephones are the opposite; they are rarely listed (7.3% of mobile telephone users found in this study) and the number structure does not provide any details of geographical location, hence making it difficult to generate a sampling frame similar to current cost effective RDD methods. The large proportional difference in the EWP directory listing between landline and mobile telephone numbers would be mainly due to the options provided to the owners: owners of landline telephone need to pay to have their telephone numbers not listed in the EWP, and owners of mobile telephone need to pay to have their mobile telephone numbers in the EWP. Hence EWP samples are likely to continue to have a small proportion (6.9% in 2008) of mobile only households in the sampling frame. According to these results, if the option is to sample from the EWP, approximately 30% of the population will be excluded, particularly young people, those who have never married, those who reside in rural areas, people on lower income levels, the unemployed and students. In terms of health indicators, people in the normal weight range and current smokers could be under-represented.

      Another emerging technology that has not been examined in this study is VoIP (Voice over Internet Protocol). In Australia, the impact of VoIP on sampling frames is not known. VoIP is seen as a cost effective system that utilises broadband data lines. Similar to mobile phones, the structure of VoIP telephone numbers (or also known as virtual number) are not geographically based and owners have the option of listing their VoIP telephone number in the EWP directory. More research is required on the uptake of VoIP including usage and impact on sampling frames.

      The results of this study are potentially biased due to survey non-response. The response rates from these surveys (51.9% to 70.6%) could be considered moderately acceptable for a population survey of this kind. With increasingly inaccessible buildings (eg locked gates), busy lifestyles, and security and privacy concerns, an ongoing impact on response rates is expected, following patterns and trends interstate and overseas [25]. The unweighted age distribution had a higher proportion of older people and a lower proportion of younger people. This indicates the proportion of mobile only households could be under-estimated, and listings in the EWP over-estimated. Another limitation is the self-reported nature of this study. People might not want to divulge that they have a landline or mobile phone that is listed in the EWP because they want to avoid telephone calls from telemarketers or researchers [22] resulting in an under-estimation of telephone listings.

      What does this mean for telephone (landline) surveys? Researchers need to be aware of the rapid changes in the telecommunication industry that potentially have an impact on collecting representative and reliable data on health-related issues using household telephone (landline) surveys. Studies like this are important because of the increasing need to monitor public health issues in a timely manner in an environment with limited and sometimes conflicting resources. Within these limits, there is a need to determine valid and reliable methods to verify the health estimates used for policy, planning of resources, and evaluation of health promotion interventions. Further research is needed in the area of mobile telephones such as how often the mobile is turned on, whether telephone calls are made more on the mobile or landline, and the likelihood of completing a health survey on a mobile telephone. Further Australian research is also required in terms of different weighting or post-survey adjustment strategies (eg raking) [26], improved sampling strategies [27] and the advantages and disadvantages of mixed mode surveying [28] (such as telephone, face-to-face, mail or internet), in order to improve the coverage of the sampling frame and minimise bias.

      Conclusion

      Coverage of households with a telephone connected (landline) and the adequacy of the sampling frame(s) have been a concern for those involved in epidemiologically-sound telephone surveys. The rate of mobile only households in South Australia has been increasing and is following worldwide trends but has not reached the high levels seen internationally (12% to 52%). Presently, the impact of mobile telephones on current sampling frames (exclusion of mobile only households or non-listings in the White Pages directory) may be small in relation to the health estimates obtained using telephone surveys. However, researchers need to be aware that mobile only households have distinctly different characteristics compared to households with a landline connection and the increase in the number of mobile-only households is not uniform across all groups in the community. Listing in the White Pages directory is continuing to decrease and only a small proportion of mobile only households are listed. Researchers need to be aware of these telephone sampling issues when considering telephone surveys.

      Abbreviations

      ABS: 

      Australian Bureau of Statistics

      BMI: 

      Body Mass Index

      CD: 

      Collector Districts

      EWP: 

      Electronic White Pages

      IRSD: 

      Index of Relative Social Disadvantage

      LA-RDD: 

      List-assisted Random Digit Dialling

      RDD: 

      Random Digit Dialling

      SPSS: 

      Statistical Package for Social Sciences

      VOIP: 

      Voice over Internet Protocol

      Declarations

      Acknowledgements

      With thanks to Melissa Atkinson, Population Research & Outcome Studies Unit, SA Health, for assistance with data analysis, Gillian Leach, CEO, Arthritis SA, Dr Patrick Phillips, Endocrinology Unit, The Queen Elizabeth Hospital, Professor Richard Ruffin, University of Adelaide for providing health data from their questions in the HOS, and Tobacco Control Research and Evaluation Program for their smoking data.

      Authors’ Affiliations

      (1)
      Department of Health, Population Research and Outcome Studies
      (2)
      Faculty of Health Sciences, The University of Adelaide

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      © Grande and Taylor. 2010

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