Who has regular mammograms? Effects of knowledge, beliefs, socioeconomic status, and health-related factors

Preventive Medicine 41 (2005) 312 – 320 www.elsevier.com/locate/ypmed

Who has regular mammograms? Effects of knowledge, beliefs, socioeconomic status, and health-related factors Helen Achat, B.Ed., M.Sc., Sc.D.a,*, Glenn Close, M.B.B.S., M.P.H., F.A.F.P.H.M.a, Richard Taylor, M.B.B.S., F.A.F.P.H.M., Ph.D.b,c a

Centre for Epidemiology, Indicators, Research and Evaluation, Division of Service Development and Population Health, Sydney West Area Health Service, Locked Bag 7118, Parramatta BC NSW 2150, Australia b Monitoring, Evaluation and Research Unit, BreastScreen NSW State Co-ordination Unit, Australia c Department of Public Health and Community Medicine, The University of Sydney, Australia Available online 30 January 2005

Abstract Background. Breast cancer accounts for the largest proportion of female cancer deaths and new cases in New South Wales (NSW). Biennial screening is recommended for women aged 50–69 years. Objectives were to (1) identify associations between beliefs and knowledge about breast cancer and mammography, socioeconomic (SES) indicators, and health-related factors, and having a mammogram (a) ever and (b) within the last 2 years; and (2) describe utilization of mammography. Methods. 2974 women aged 50–69 years selected from the BreastScreen NSW (BSNSW) database and the NSW Electoral Roll were administered a structured telephone survey. Associations were assessed using weighted Chi squares and age-adjusted odds ratios from logistic regression with 95% confidence intervals. Results. Strong positive associations were found between age, married/de facto relationship, knowledge about and belief in the benefits of screening, indicators of health status and service utilization, and whether women had had a mammogram or had one within the recommended period. SES was weakly associated with regularity of mammography. Most respondents (97.4%) reported having had at least one mammogram. Conclusions. Specific aspects of knowledge and beliefs about mammograms and individual health-related factors would be important components of initiatives to encourage initial and repeat screening in the targeted age group. D 2005 Elsevier Inc. All rights reserved. Keywords: Mammography; Socioeconomic status; No cost program; New South Wales; Australia

Introduction Breast cancer is responsible for the largest proportion of female deaths from any form of cancer in Australia [1] and has accounted for approximately 16% of all cancer-related deaths in recent years [2,3]. While breast cancer mortality rates showed a downward trend in the 1990s [2], incidence rates, partly influenced by population screening [4], increased by 19% in the period from 1990 to 2000 [3]. In New South Wales (NSW), breast cancer is responsible for

* Corresponding author. Fax: +61 2 9840 3608. E-mail address: [email protected] (H. Achat). 0091-7435/$ - see front matter D 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.ypmed.2004.11.016

the largest proportion of new cancers that are reported [3], making up 29% of female cancers in 2000 [5]. These figures suggest that about 1 in 11 females would develop breast cancer by the age of 75 years [3]. Population-based studies have shown that mammography can be effective in early detection [6] and consequently significantly reduce breast cancer mortality [7,8]. Mammograms without direct charge can be obtained from BSNSW by women who are 40 years or older or from private providers (paid for via Medicare, the government-funded universal health insurance scheme if the purpose is identified as diagnostic). BSNSW is a government-funded organization that recruits and offers women aged 50 to 69 years two yearly breast screening. Its aim is to reduce

H. Achat et al. / Preventive Medicine 41 (2005) 312–320

morbidity and mortality attributable to breast cancer [9] and the way to achieve this is to promote screening at recommended intervals. Identifying and understanding barriers to the recruitment of women into a regular screening program is therefore a key concern. Although comparison of studies is difficult because of differences in access and availability of breast screening in different health systems, some predictors of mammographic screening have been consistent across studies. Two consistent findings are the positive associations of breast screening with high income [10,11] and having a dusualT or dregularT source of medical care [12,13]. Conflicting results have been reported regarding the effects of education [14,15], age [14,16], marital status [14,17], and the presence of co-morbidities [17,18]. Utilizing a BSNSW database, the present cross-sectional study aimed to examine how SES, beliefs and knowledge of women regarding breast cancer and mammography, health status, and health service utilization are associated with self-report of ever having a mammogram and mammography at regular intervals. An earlier report from this survey used BSNSW-defined mammography attendance to examine predictors of regular screening with BSNSW [19].

Methods

313

each of the three BSNSW attendance categories was used as a pool from which women were consecutively selected for inclusion into the survey. These three random samples were in turn matched to the electronic White Pages telephone directory using a multi-pass Automatch [21] algorithm [22] to provide contact phone numbers. Although telephone numbers were available on the BSNSW database for current and late/lapsed screeners, the White Pages was used to find numbers for all groups to avoid introducing bias, for example, against persons with silent numbers in the never screener group compared to the current and late/lapsed groups. The matching procedure can introduce a geographic bias because matches in rural areas may be more successful as there are fewer alternative matches in lower-density communities. However, no sign of geographic bias was detected in any of the samples. The large sample of women with address and telephone information was randomized and 6286 names were selected at random and provided to a market research company (MRC) for interview. Numbers were selected from each of the three BSNSW attendance groups to ensure sufficient numbers for analysis. The sample as provided to the MRC was exhausted and, to minimize the possibility of selection bias by excluding hard to find women, up to 10 attempts were made to contact each person. Seventy per cent (4381) of the telephone numbers selected enabled contact with a household of a potential respondent.

Participants Procedure With the approval of the NSW Department of Health Ethics Committee, women were selected from the BSNSW database (those who had had at least one mammogram at BSNSW) and from the NSW Electoral Roll (those who had never attended BSNSW for a mammogram). The sampling frame utilized BSNSW data (information on actual screening behavior) to provide a relatively unique data set enabling a better understanding of possible predictors of utilization of mammography. The BSNSW database consists of women aged 50–69 years invited from the Electoral Roll who have attended for at least one screen, supplemented by other women presenting for screening at BSNSW. The database contains women’s full names, dates of birth, postal addresses and in some cases telephone numbers. Similar information is available on the Electoral Roll, which is 90% complete for women aged 50–69 in the NSW population who are citizens of Australia [20]. Women aged 50 to 69 years as of February 2001 were categorized as dcurrentT, dlate/lapsedT, or dneverT screeners based on their participation in the BSNSW program. Current screeners had obtained a mammogram from BSNSW less than 27 months ago; late or lapsed screeners had their last mammogram at BSNSW more than 27 months ago; and never screeners were on the NSW Electoral Roll but were not on the BSNSW database. A large random sample of

All women who were selected were sent a letter of introduction approximately 2 weeks prior to a scheduled telephone contact. A minimum of six attempts was made to contact each potential respondent. The telephone interview lasted between 10 and 15 minutes. A pilot of 50 respondents identified necessary amendments, which were subsequently made to the questionnaire [23]. Statistical analysis Respondents were categorized using self-reported (i.e., as opposed to the BSNSW-defined groups that were the basis of the stratified sampling) mammography attendance status to enable two sets of comparisons. This study examined never versus ever attenders for mammography and also, those reporting mammography relatively recently (within about two years) versus those overdue. Women’s mammography utilization history was based on responses to the questions: bHave you ever had a mammogram?Q and bWhen did you last have a mammogram?Q dNever attendersT had never had a mammogram; dever attendersT had had at least one mammogram in their lifetime; drecent attendersT were women who reported having a mammogram bless than 1 year agoQ to babout 2 years agoQ; and those overdue comprised all women who had had their last mammogram

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at least babout 3 years agoQ. Factors of interest were grouped into one of four domains: demographics, knowledge and beliefs, health status, and health service utilization. Age was divided into four 5-year groups for ages from 50 years, the last of which included women aged 70 and 71 years. We examined the data using cross tabulations with Pearson chi-square statistics and reported within mammography attendance group proportions and odds ratios with 95% confidence intervals based on bivariate age-adjusted logistic regression models using SPSS [24] software. Women identified from BSNSW’s database as never screeners were sampled disproportionately in their favor to ensure this group would be sufficiently large to allow meaningful statistical analyses. Subsequently, the data were weighted to allow each group’s distribution in the sample to reflect its actual distribution in the population from which it was drawn [25]. The weights were calculated using a formula to adjust for disproportionate sampling as described in Aday [26]. The weighting for each of the three screening groups was calculated by determining its proportion in the sampling population{a}, its proportion in the sample{b}, and dividing {a} by {b}.

Results Inability to contact potential respondents by phone and insufficient English proficiency were the most common factors contributing to the 49% participation rate detailed elsewhere [23]. Of the 4381 eligible women telephoned to request their participation in the survey, 3106 completed the survey, resulting in a response rate of 71%. Two participants were excluded from the analyses because their screening status on the BSNSW register categorized them as dcurrent screenersT but they reported that they had never had a mammogram. A further 130 women who had previously been diagnosed with breast cancer were excluded because of specialized treatment they would likely receive. A total of 2974 respondents were included in the following analyses to which the abovementioned weights were applied. Participants ranged in age from 50 to 71 years, with the majority (92.2%) aged 50 to 69 years. Women aged 70 or 71 years were respondents because of either the lag time between the sampling and interviewing (February to June) or inconsistent date of birth information from the BSNSW database and self-report. Being on the BSNSW database, their responses were considered relevant to this research. A comparison with the 2001 Census data for all ages in NSW showed the survey sample provided a reasonable representation with regard to the proportion of women born in Australia versus overseas. Approximately three-quarters (76.7%) of the women were born in Australia (4% of whom were Aboriginal or Torres Strait Islander), compared with

total population figures from the 2001 Census of 70.5% (1.9% of whom identified as Indigenous). Almost all women had heard of a mammogram (99.8%) and the majority of all respondents reported having had at least one mammogram (97.4%). Among women who had had at least one mammogram, the main providers of the most recent mammogram were BSNSW (85.3%), a bprivate practice under MedicareQ (8.8%) and a bhospitalQ (4.8%). Demographic characteristics of respondents grouped according to self-reported mammography attendance are shown in Table 1. dNever attendersT were most likely to be in the youngest age group (51.3%). Women who reported having a mammogram within about the last two years were more likely to be married or in a de facto relationship (77.2%) than single (3.5) or widowed, separated or divorced (19.3%). dRecent attendersT were more likely to be not employed (67.5%) and to speak English at home (94.5%). The highest level of education completed and annual household income did not differ across groups. Knowledge of mammographic screening recommendations among deverT and dnever attendersT is presented in Table 2. Overall, fewer respondents accurately stated the recommended ages for starting and stopping regular mammographic screening (20.5% and 15.3%, respectively) than the recommended interval between screens (74.0%) and whether a doctor’s referral was needed to obtain a mammogram (86.2%). A significantly larger proportion of dneverT (37.1%) than dever attendersT (20.0%) knew the recommended age to start having mammograms, but women who had ever had a mammogram were more likely to know the recommended screening interval (74.6% versus 49.3%). Many respondents thought that women should bneverQ stop screening (dnever attendersT: 42.5%; dever attendersT: 60.3%). Significantly more dever attendersT (86.7%) than dnever attendersT (67.1%) were aware that a doctor’s referral is not necessary to obtain a mammogram. For all the knowledge questions, a higher proportion of dnever attendersT (ranging from 17.8% to 38.4%) than dever attendersT (ranging from 3.1% to 17.5%) reported that they did not know. Age-adjusted odds ratios and 95% confidence intervals for two sets of comparisons, one examining self-reported never versus ever and the second, recent versus overdue, mammography are presented in Table 3. Factors examined for associations with each comparison were grouped under one of four headings: bdemographicsQ, bknowledge and beliefsQ, bhealth statusQ, and bhealth service utilizationQ. Never versus ever having had a mammogram Women who were bwidowed, separated, or divorcedQ were significantly more likely than those in a married or de facto relationship to have never had a mammogram (OR = 1.97). Not knowing the recommended screening interval and that a doctor’s referral is not needed were each associated

H. Achat et al. / Preventive Medicine 41 (2005) 312–320

315

Table 1 Demographic characteristics of respondents categorized by self-reported mammography attendance Demographic characteristics

Age groups 50–54 years 55–59 years 60–64 years 65–71 years Marital status Single Married/de facto Widowed/separated/divorced Education completed Primary or lower Secondary Skilled trade/technical University or higher Employment status Full or part time Not employed Household income ($1000) b20 20–39 40–59 N60 Language spoken at home English Other

Self-reported mammography attendance (%) Sub-group chi square

Up to babout 2 years agoQ (95% CI)

bAbout 3 years agoQ or more (95% CI)

Never had a mammogram (95% CI)

84.2, df = 6***

weighted n = 2748 14.9 (13.6–16.2) 30.5 (28.7–32.2) 24.3 (22.7–25.9) 30.3 (28.6–32.1) weighted n = 2749 3.5 (2.8–4.3) 77.2 (75.7–78.8) 19.3 (17.8–20.8) weighted n = 2748 11.7 (10.5–12.9) 62.2 (60.4–64.0) 15.4 (14.0–16.7) 10.7 (9.6–11.9) weighted n = 2748 32.5 (30.7–34.2) 67.5 (65.8–69.3) weighted n = 2194 33.9 (31.9–35.9) 29.2 (27.3–31.1) 16.8 (15.2–18.3) 20.1 (18.5–21.8) weighted n = 2748 94.5 (93.6–95.3) 5.5 (4.7–6.5)

weighted n = 185 22.2 (16.4–28.8) 24.9 (18.8–31.7) 29.2 (22.7–36.3) 23.8 (17.8–30.6) weighted n = 184 10.3 (6.3–15.7) 62.5 (55.1–69.5) 27.2 (20.9–34.2) weighted n = 184 13.0 (8.5–18.8) 60.9 (53.4–68.0) 15.2 (10.4–21.2) 10.9 (6.8–16.3) weighted n = 184 39.1 (32.0–46.6) 60.9 (53.4–68.0) weighted n = 138 39.9 (31.6–48.5) 26.8 (19.6–35.0) 18.1 (12.1–25.6) 15.2 (9.7–22.3) weighted n = 184 90.2 (85.0–94.1) 9.8 (5.9–15.0)

weighted n = 78 51.3 (39.7–62.8) 20.5 (12.2–31.2) 11.5 (5.4–20.8) 16.7 (9.2–26.8) weighted n = 78 6.4 (2.1–14.3) 65.4 (53.8–75.8) 28.2 (18.6–39.5) weighted n = 78 12.8 (6.3–22.3) 56.4 (44.7–67.6) 17.9 (10.2–28.3) 12.8 (6.3–22.3) weighted n = 78 47.4 (36.0–59.1) 52.6 (40.9–64.0) weighted n = 65 32.3 (21.2–45.1) 24.6 (14.8–36.9) 16.9 (8.8–28.3) 26.2 (16.0–38.5) weighted n = 78 89.7 (80.8–95.5) 10.3 (4.5–19.2)

35.6, df = 4***

1.44, df = 6

10.7, df = 2**

5.06, df = 6

8.3, df = 2*

* P b 0.05. ** P b 0.01. *** P b 0.001.

with approximately a threefold increase in the risk of being a dnever attenderT (OR = 2.81 and OR = 2.79, respectively). In response to the question bIf something shows up on a mammogram, does this always mean that the woman has breast cancer?Q, women who said yes or were unsure were 2.72 times more likely to have never had a mammogram. Women who believed that mammograms were at best only bsomewhat effectiveQ or were unsure or did not think that mammograms save lives were significantly more likely to have never had a mammogram than women who believed screening was effective and did save lives (OR = 2.36 and OR = 5.07, respectively). Women who had undergone a hysterectomy or had been prescribed hormone replacement treatment (HRT) in the past 2 years were less likely to report never having a mammogram (OR = 0.46 and OR = 0.34, respectively). Neither a family history of breast cancer nor poor self-rated general health status was associated with ever having had a mammogram (Table 3). dNever attendersT were more likely to report visiting a doctor twelve or more months ago (OR = 2.59) and not having health insurance (OR = 1.77) or someone they usually see about health concerns (OR = 3.06). Never having a clinical breast examination or a Pap test were also significantly associated with never having had a mammogram (OR = 3.16 and OR = 3.36, respectively).

Mammography within babout 2 yearsQ (drecentT) versus babout 3 years or moreQ (doverdueT) Women who were either bsingleQ or bwidowed, separated, or divorcedQ were significantly more likely to be overdue for a mammogram (OR = 3.48 and OR = 1.86, respectively) compared to those in a married or de facto relationship. Respondents were also significantly more likely to be overdue if their household income was less than $20,000 (compared with one of $60,000 or more) or if they did not speak English at home (OR = 1.90 and OR = 1.82, respectively). Lack of knowledge about the recommended period between screens (OR = 2.59), that a doctor’s referral is not needed to obtain a mammogram (OR = 2.10), and that something showing up on a mammogram does not always indicate breast cancer (OR = 2.27) were all significantly associated with being overdue for a mammogram. Beliefs that mammograms were at best only bsomewhat effectiveQ in detecting breast cancer and increasing the number of lives saved from breast cancer were associated with increased risk of being overdue (OR = 1.72 and OR = 4.27, respectively). Being overdue for a mammogram was positively associated with fair or poor self-rated health (OR = 1.55) and inversely associated with being prescribed hormone

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Table 2 Women’s knowledge of mammographic screening recommendations from BreastScreen Australia categorized by self-designated mammography attendance Knowledge of recommendations

Proportion of women by mammography attendance (95% CI) n

Age one should start screening b39 years 40–49 years 50–59 years 60–69 years Don’t know Age one should stop screening b69 years 70–79 years 80–90 years Never Don’t know Interval one should have between screens Once a year Once every 2 years Once every 3 to 5 years When feels need/suggested Don’t know/other Is a doctor’s referral needed Yes No Don’t know

Sub-groups’ chi square

Ever attenders

Never attenders

All respondents

37.9, df = 4***

weighted n = 2863 33.8 (32.1–35.5) 37.0 (35.2–38.8) 20.0 (18.6–21.5) 0.3 (0.1–0.6) 8.8 (7.8–9.9) weighted n = 2896 2.1 (1.7–2.7) 15.3 (14.0–16.6) 4.7 (4.0–5.6) 60.3 (58.8–62.1) 17.5 (16.1–18.9) weighted n = 2932 19.9 (18.5–21.4) 74.6 (73.0–76.2) 1.1 (0.7–1.5) 1.4 (1.0–1.9) 3.1 (2.5–3.8) weighted n = 2933 8.4 (7.4–9.4) 86.7 (85.4–87.9) 5.0 (4.2–5.8)

weighted n = 70 17.1 (9.2–28.0) 21.4 (12.5–32.9) 37.1 (25.9–49.5) 0.0 24.3 (14.8–36.0) weighted n = 73 4.1 (0.9–11.5) 12.3 (5.8–22.1) 2.7 (0.3–9.6) 42.5 (31.0–54.6) 38.4 (27.2–50.5) weighted n = 73 28.8 (18.8–40.6) 49.3 (37.4–61.3) 0.0 4.1 (0.9–11.5) 17.8 (9.8–28.5) weighted n = 73 11.0 (4.9–20.5) 67.1 (55.1–77.7) 21.9 (13.1–33.1)

weighted 33.4 36.6 20.5 0.3 9.2 weighted 2.2 15.3 4.7 59.9 18.0 weighted 20.1 74.0 1.0 1.4 3.4 weighted 8.4 86.2 5.4

980 1074 600 9 270 23.3, df = 4*** 65 453 139 1778 534 58.6, df = 4*** 605 2223 31 43 103 22.9, df = 1*** 253 2591 162

n = 2933

n = 2969

n = 3005

n = 3006

Section columns may not equal 100 because of rounding. BreastScreen Australia recommendations in italic. *** P b 0.001.

replacement treatment in the last 2 years (OR = 0.56) and having a family history of breast cancer (OR = 0.53). Women were more likely to be overdue for a mammogram if they had not visited their doctor within the last 12 months (OR = 2.16), did not have a usual health provider (OR = 2.06), did not have private health insurance (OR = 1.59), or had never had either a clinical breast examination (OR = 2.08) or a Pap test (OR = 2.93).

Discussion We examined four mammography attendance status groups, defined according to self-reported utilization of mammography, comparing ever with never and recent with overdue mammography. With the exception of an inverse association between the lowest-income category and mammography use, the present findings did not support previous reports of strong associations between SES indicators and mammography

Notes to Table 3: a n: Weighted numbers of total respondents for specific characteristic. b OR: Odds ratio. c CI: 95% confidence interval. * P b 0.05. ** P b 0.001. *** P b 0.0001.

utilization [15,27]. The relatively limited effect of SES indicators on mammography utilization, although contrary to North American findings [27,28], is not surprising for a program that does not impose a direct cost on the individual [29]. Such programs may reduce barriers that are related not only to income, but also to education and employment [29]. Increased availability in the 1990s of mammography without direct charge, media campaigns, and personal invitations to women aimed at heightening awareness of recommendations may have also contributed to a lesser effect of educational attainment, employment status, and household income. Earlier studies have found similar [30] or higher [31] proportions of women aged 50 to 59, compared to those aged 60 to 69 years, reporting ever or regular mammography. The present findings showed a positive association between age and utilization of mammography, with younger women being more likely to have never had or to be overdue for a mammogram. This may in part be a result of BSNSW commencing active recruitment no earlier than age

H. Achat et al. / Preventive Medicine 41 (2005) 312–320

317

Table 3 Predictors of self-designated never and overdue mammography attendance among women in NSW, 2001 Characteristic Demographics Marital status Single Married/de facto Widowed, separated or divorced Language spoken at home English Other Gross annual household income b20,000 $20–39,000 $40–59,000 $60,000+ Employment status Full or part time Not employed Knowledge and beliefs Recommended interval Mammograms every 2 years Other/or don’t know Need doctor’s referral Don’t need doc referral Yes or DK Something shows on mammogram Not always mean cancer Always mean cancer Effectiveness in detecting cancer Mammograms effective Somewhat to not at all effective Save lives Mammograms save lives No or don’t know Health status General health Good to excellent Fair or worse Hysterectomy Yes No Family history of breast cancer Yes No or don’t know HRT Yes No or don’t know Health service utilization Last visit to doctor b12 months ago z12 months ago Usual health provider to visit Yes No Health insurance Yes No or don’t know Clinical breast examination Clinical beast examination No examination Pap test Yes No

na

n a, never

Never attenders age-adjusted ORb (CIc)

na

n a, overdue

Overdue attenders age-adjusted ORb (CIc)

120 2288 602

5 51 22

1.58 (0.62–4.08) 1.00 1.97 (1.17–3.32)*

115 2238 580

19 115 50

3.48 (2.05–5.91)*** 1.00 1.86 (1.31–2.63)***

2832 178

70 8

1.00 1.66 (0.76–3.63)

2762 170

166 18

1.00 1.82 (1.09–3.04)*

820 694 404 480

21 16 11 17

1.58 (0.77–3.22) 1.06 (0.52–2.16) 0.87 (0.40–1.88) 1.00

799 677 393 463

55 37 25 21

1.90 (1.09–3.31)* 1.40 (0.80–2.46) 1.47 (0.81–2.66) 1.00

1001 2010

37 41

1.00 1.04 (0.62–1.74)

964 1968

72 112

1.00 0.82 (0.58–1.17)

2223 787

36 38

1.00 2.81 (1.75–4.50)***

2188 746

101 84

1.00 2.59 (1.91–3.52)***

2591 415

49 24

1.00 2.79 (1.68–4.66)***

2542 390

141 43

1.00 2.10 (1.47–3.02)***

2845 161

65 8

1.00 2.72 (1.26–5.88)*

2780 152

166 18

1.00 2.27 (1.35–3.82)**

2627 378

54 19

1.00 2.36 (1.37–4.08)**

2573 359

149 35

1.00 1.72 (1.17–2.53)**

2926 80

66 8

1.00 5.07 (2.22–11.55)***

2861 73

170 15

1.00 4.27 (2.35–7.76)***

2417 592

60 17

1.00 1.34 (0.77–2.32)

2357 575

136 48

1.00 1.55 (1.10–2.19)*

1001 2010

13 65

0.46 (0.25–0.83)* 1.00

988 1944

71 113

1.30 (0.96–1.78) 1.00

444 2567

5 73

0.41 (0.16–1.04) 1.00

439 2494

16 168

0.53 (0.32–0.90)* 1.00

1230 1596

14 46

0.34 (0.18–0.62)*** 1.00

1217 1550

55 114

0.56 (0.40–0.78)** 1.00

2806 205

64 14

1.00 2.59 (1.40–4.81)**

2742 190

161 23

1.00 2.16 (1.36–3.44)**

2913 97

71 7

1.00 3.06 (1.32–7.06)**

2843 90

174 10

1.00 2.06 (1.06–4.01)*

1934 1077

44 34

1.00 1.77 (1.11–2.84)*

1890 1043

102 82

1.00 1.59 (1.17–2.16)**

2459 552

50 28

1.00 3.16 (1.94–5.16)***

2409 523

131 53

1.00 2.08 (1.48–2.92)***

2878 113

69 5

1.00 3.36 (1.32–8.55)*

2809 108

168 15

1.00 2.93 (1.64–5.23)***

318

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50. For younger women, hindrances to having a mammogram might include busy schedules, paid employment, and the greater likelihood of pain during mammography [32]. Consistent with findings from the 1995 National Health Survey (NHS) [33], we identified a positive association between mammography and being married or in a de facto relationship. The favorable effect of social networks and support on health [34] may partly explain this finding. In addition, the widowed, separated or divorced, similar to the unmarried, were also more likely to have had their last mammogram three or more years ago. Knowledge of BSNSW recommendations and requirements for mammographic screening and belief in the effectiveness of mammograms were positively associated with having ever had a mammogram and having one within 2 years or so. Although most women knew that biennial screening is recommended, most did not know the recommended age to commence screening. Aside from their incorrect answers, significantly more dnever attendersT than dever attendersT said they did not know the recommended ages to start and stop having regular mammograms. Strong associations were found between most indicators of health status and all indicators of health service utilization and attendance status. Doctors’ recommendation for screening and use of opportunities for discussion about the procedure [35], perceived vulnerability [36], and personal risk [37], as well as efforts to ensure minimal discomfort and embarrassment [36] can optimize uptake. However, interventions aimed at having doctors increase awareness of mammography would need to ensure that women of low income and those who have infrequent medical visits [38,39] were also targeted. Women who were prescribed HRT within the 2 years prior to the survey were more likely to attend for, and to report a recent mammogram. Prescription of HRT is often accompanied with specific information about mammography because of the associated risk of missing breast cancer early [40]. It is reasonable to expect the effects of strong predictors of mammography utilization, such as regular doctor visits would be attenuated by barriers stemming from social, economic, and regional factors [41]. Access to services influences mammography attendance [13,33,42,43], particularly for rural and remote areas and underprivileged groups. In situations where public screening services are not readily available or absent, cost, however small, may be a real consideration [44]. Our sampling frame was the BSNSW database (derived from the NSW Electoral roll but also including women who attend without invitation) combined with Electoral Roll data on women who had never had a BSNSW screening mammogram. In fact, many of the BSNSWdefined dnever screenersT had had mammograms in other settings at some time. The reported rates of ever having a mammogram described here are therefore somewhat higher than (although not inconsistent with) rates reported in

occasional research [45], regularly repeated surveys such as the NSW Health Survey [46] and the National Health Survey [30]. One limitation of this study is the effect of recall bias on self-reported time since last mammogram. Nevertheless, studies on the accuracy of self-reported mammography suggest relatively high concordance with databases of actual behavior [47–49]. Although women do tend to underestimate the time since their last mammogram, the sensitivity and specificity of self-reported mammography have been reported at 0.97 and 0.78, respectively [50]. For our sample, we assessed regularity of mammography utilization using questions about busual time period between mammogramsQ and time since blast mammogramQ to optimize reliability [51], and found consistency between the two responses. The response rate of 71% compares well with other similar surveys [31,52]. Extrapolation from the present findings must also take into account the absence of information about non-English speaking women and those without a telephone or with unlisted numbers. Ideally, we would have liked to accurately distinguish dscreeningT from ddiagnosticT mammograms. The question concerning reasons for last mammogram did not, however, enable us to make this distinction in the analysis. Although prompted by a desire to provide information to improve time-appropriate mammographic screening in the target group, this paper was concerned with triggers for having a mammogram rather than screening as such. Women who nominated bbreast problemsQ as the prompt for their last mammogram were therefore included because, for most, it was simply a trigger to have a mammogram at BSNSW. Re-analysis excluding these women yielded virtually identical results to those reported.

Conclusion A lack of knowledge and inaccurate beliefs about mammographic screening and poor health service utilization must be addressed if more women in their early 50s are to reap the benefits of early detection [53]. Women need to be reminded that mammography is an effective screening procedure and mammograms cannot be replaced by breast examination [54]. Recent debates on the effectiveness of mammograms [55] and populationbased [56] versus high-risk individual [57] screening, necessitate reassurance that most experts recommend screening [58]. Doctor recommendation and perceived breast problems are two important influences on mammography utilization. In view of this, the substantial minority of women having mammograms outside public screening services, even if mostly for specific breast problems, warrants further study.

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Acknowledgments This study was funded in part by a grant from the Commonwealth Department of Health and Ageing. We thank the following people for their assistance with the survey: Leendert Moerkerken, Rajah Supramaniam, Teresa Tomczyk, and Michelle Phillips.

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