Beeckman et al. BMC Public Health 2010, 10:527 http://www.biomedcentral.com/1471-2458/10/527 Table 2 Poisson regression describing differences in adjusted number of antenatal visits Adjusted visit ratiof Variable Adjusted visits Predisposing characteristics Origin EU 15a 10.60 e 1 e Maghreb and Turkey 0.86 Sub-Saharan African 0.94 Other 0.94 9.18 e 1 e Educational level Not finished secondary school Secondary school 1.03 Higher education 1.22 Enabling characteristics Equivalent income b Pregnancy related characteristics Parity Gestational age at initiation of care High risk status during antenatal carec Gestational age at delivery Continuity Of Care indexd Low Moderate High Primiparae Multiparae Before week 14 After week 14 Yes No Before week 37 After week 37 COC <50% COC >= 50% 9.20e 10.72 e 11.89 e 10.56 e 8.98 e 10.56 e 1 e 1.09 1.14 1 e 0.85 1 e 0.69 1 e 0.88 1 e 1.22 1 e Page 7 of 9 95%CIg p-value 0.79-0.92 0.85-1.03 0.85-1.05 0.93-1.14 1.10-1.35 1.01-1.19 1.02-1.27 0.0001 0.2059 0.3193 0.5198 0.0001 0.0353 0.0196 0.80-0.91 <0.0001 0.58-0.82 <0.0001 0.81-0.96 1.07-1.39 0.0036 0.0028 0.88 0.82-0.94 0.0009 a Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Austria, Portugal, Spain, Sweden and the United Kingdom; bΣ incomes in the household/(1+(a*0.5)+(c*0.3)) with a: number of adults living in the same household of the wife(wife not included), c: number of children under the age of 18 living in the same household (OECD scale)[26]; c hypertension, pre-eclampsia, gestational diabetes mellitus, preterm contractions, hospitalization, anaemia d Bice index or Continuity of Care index: COC = ∑nj2−nn(n−1) (Bice, 1977)[31,32] nj is the total number of visits to a provider n is the total number of visits; e baseline; f Adjusted for effects of origin, educational level, equivalent income, parity, gestational age at booking, risk status during antenatal care, gestational age at delivery and Continuity of carer index; g CI = Confidence interval. Some limitations in our study need to be addressed. First, our findings are based on self-reported data. Although events during pregnancy are considered as major life events and are therefore likely to be remem- bered [38] the number of visits recalled might differ from the actual number. To minimize this discrepancy, recall bias was reduced by performing bimonthly follow- up calls. Second, the sample of our study is rather small. A balance needed to be found between the level of detail of the data collection and the number of cases to be included. However, additional analyses showed that the mean number of antenatal visits in our sample was comparable with the number of consultations in the whole of the Brussels Metropolitan Region (12.9 and 13.3, respectively) [39]. These numbers are comparable to those in other European countries [14,35,36]. To our knowledge, this is the first study in Europe in which individual factors at all three levels of the behaviour model were considered when examining the number of antenatal visits. Also the study is original in its prospec- tive design; provision of bimonthly follow-up ensures accuracy of gathered data. Conclusions Until now, international consensus about the number of antenatal visits has been lacking and the definition of optimal antenatal care differs between guidelines [40]. Therefore, our study focused more on the identification of women at risk of having fewer antenatal visits rather than on the exact number of visits. This approach offered insights into the dynamics behind variations in the number of antenatal visits, based on the behavioural model. Analysis of predisposing, enabling and preg- nancy-related determinants of the number of antenatal visits received showed barriers to service use. Our study suggests that variations might be reduced when health