Socio-Territorial Inequities in the French National Breast Cancer Screening Programme—A Cross-Sectional Multilevel Study
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Population and Sample
2.2. Variables
- Age at invitation
- Travel time to the nearest accredited radiology centre
- French version of the European Deprivation Index (EDI)
- Opportunistic screening
- Care offer
- Département socioeconomic level
2.3. Statistics
2.3.1. Centring and Standardization
2.3.2. Model Building
2.3.3. Additional Measures
3. Results
3.1. Population
3.2. Results
- Model 0: There was heterogeneity in FNBCSP participation (i.e., random intercepts variance) around the fixed intercept (OR = 1.32 [1.22–1.45]) at both IRIS (σ2 = 0.055; VPC = 1.6%) and département levels (σ2 = 0.082; VPC = 2.4%). Shrunken residuals used to estimate these variances are illustrated in Figure 2a,b (Model 0).
- Model 1: Overall, FNBCSP participation increased with age (OR = 1.05 [1.03–1.07]) and decreased with travel time (OR = 0.98 [0.96–0.99]). As shown by the random slopes, and illustrated in Figure 2c,d (Model 1), strength of these effects varied across départements, in such a way that the relation was insignificant or reversed in some cases. Random effects correlations showed that départements with higher intercepts tended to have a stronger effect for travel time and a weaker effect for age. It led to higher heterogeneity between départements for younger women and those closest to and furthest from the NARC (Figure 3a,b (Model 1)). There was an interaction between age and travel time (OR = 0.99 [0.98–1.00]), illustrated in Figure 4a.
- Model 2: Overall, an increase in EDI was associated with lower probability of FNBCS participation (OR = 0.84 [0.82–0.86]). Accounting for EDI reduced travel time effect heterogeneity (Figure 3b (Model 2)). As shown by the random slope and illustrated in Figure 2e, strength of the association between EDI and FNBCSP participation varied across départements, but few had a weak relationship. Random effects correlations showed that départements with higher random intercepts tended to have a stronger effect of EDI. It led to more heterogeneity in FNBCSP participation among the wealthiest women, and, to a lesser extent, the most deprived (Figure 3c (Model 2)). Accounting for EDI also reduced random intercepts variances at IRIS and département levels by 34% (Figure 2a (Model 2) and 12.2%.
- Model 3: FNBCSP participation was lower as départements’ opportunistic screening rates (OR = 0.84 [0.79–0.87]) and départements’ deprivation (OR = 0.91 [0.88–0.96]) increased. There were cross-level interactions between opportunistic screening rates and both age (OR = 1.02 [1.01–1.04]) and EDI (OR = 1.04 [1.03–1.06]). As illustrated in Figure 4b,c, FNBCSP participation in départements with high opportunistic screening rates was lower as age and deprivation decreased. There was a cross-level interaction between départements’ deprivation and EDI (OR = 1.02 [1.00–1.03]), with lower participation as deprivation decreased (Figure 4d). These effects reduced the remaining variance across départements by 79.2% (Figure 2b (Model 3)). They also strongly reduced heterogeneities between départements in the strength of the effects of age, travel time and EDI (Figure 2c–e (Model 3)). In addition, random effects correlations were reduced to statistical insignificance. Unexplained remaining variances between départements were thus independent of the lower-level variables. (Figure 3a–c (Model 3)). GDP-PPP and the number of radiology centres per 100,000 eligible women were not associated with FNBCSP participation.
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Ethics Approval and Consent to Participate
Consent for Publication
References
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Level 1—Individual Level | Mean | Standard Deviation | Minimum | Maximum |
---|---|---|---|---|
Travel time (minutes) | 8.70 | 7.47 | 0.00 | 132.48 |
Age (years) | 60.73 | 7.11 | 50 | 74 |
FNBCSP a participation (%) | 55.06 | / | / | / |
Level 2—IRIS b | ||||
EDI c,d (dimensionless) | 0.97 | 5.12 | −11.08 | 35.96 |
Level 3—Départements | ||||
Opportunistic screening rates (%) | 8.91 | 6.06 | 2.30 | 28.00 |
Mean of EDI c,d (dimensionless) | 0.97 | 2.29 | −1.67 | 9.63 |
GDP (PPP) e per capita (US$) | 20,638 | 6134 | 17,310 | 23,360 |
Number of accredited radiology centres/100,000 eligible women | 21.88 | 8.55 | 7.69 | 59.06 |
Model 0: Empty Model | Model 1: Level 1 Variables | Model 2: Level 2 Variable | Model 3: Level 3 Variables | |
---|---|---|---|---|
Level 1—Individuals | ||||
Intercept | 1.32 [1.22–1.45] | 1.35 [1.24–1.47] | 1.32 [1.22–1.43] | 1.32 [1.27–1.37] |
Age | / | 1.05 [1.03–1.07] | 1.05 [1.03–1.07] | 1.05 [1.04–1.06] |
Travel time | / | 0.98 [0.96–0.99] | 0.95 [0.93–0.96] | 0.94 [0.93–0.95] |
Age × travel time | / | 0.99 [0.98–1.00] | 0.99 [0.98–1.00] | 0.99 [0.98–1.00] |
Level 2—IRIS | ||||
Fixed effects | ||||
EDI | / | / | 0.84 [0.82–0.86] | 0.84 [0.83–0.85] |
Random effects | ||||
Random intercept (σ20I) | 0.055 [0.048–0.058] | 0.053 [0.048–0.058] | 0.035 [0.030–0.039] | 0.035 [0.031–0.039] |
VCP | 1.60% | 1.55% | 1.03% | 1.05% |
PCV (compared with empty model) | / | −3.64% | −36.36% | −36.36% |
Level 3—Départements | ||||
Fixed effects | ||||
Individual screening rates | / | / | / | 0.84 [0.79–0.87] |
Deprivation | / | / | / | 0.91 [0.88–0.96] |
Cross-level interactions | ||||
Individual screening rates × Age | / | / | / | 1.02 [1.01–1.04] |
Individual screening rates × EDI | / | / | / | 1.04 [1.03–1.06] |
Mean of EDI × EDI | / | / | / | 1.02 [1.00–1.03] |
Random effects | ||||
Random intercept (σ20D) | 0.082 [0.053–0.130] | 0.082 [0.048–0.123] | 0.072 [0.044–0.108] | 0.015 [0.007–0.021] |
VPC | 2.39% | 2.39% | 2.12% | 0.45% |
PCV (compared with empty model) | / | 0% | −12.20% | −81.71% |
Age random slope (σ21D) | / | 2.3 × 10−3 [1.2 × 10−3–3.7 × 10−3] | 2.3 × 10−3 [1.2 × 10−3–3.6 × 10−3] | 1.4 × 10−3 [5.3 × 10−4–2.2 × 10−3] |
Travel time random slope (σ22D) | / | 2.1 × 10−3 [1.0 × 10−3–3.4 × 10−3] | 1.4 × 10−3 [5.3 × 10−4–2.3 × 10−3] | 1.2 × 10−3 [4.0 × 10−4–2.2 × 10−3] |
EDI random slope (σ23D) | / | / | 4.1 × 10−3 [1.8 × 10−3–6.7 × 10−3] | 1.1 × 10−3 [1.0 × 10−4–1.8 × 10−3] |
Random effects correlation | ||||
σ20D, σ21D | / | −0.55 [−0.77; −0.19] | −0.55 [−0.78; −0.23] | −0.18 [−0.57; 0.23] |
σ20D, σ22D | / | −0.60 [−0.83; −0.31] | −0.71 [−0.94; −0.42] | −0.32 [−0.67; 0.13] |
σ20D, σ23D | / | / | −0.76 [−0.91; −0.54] | −0.03 [−0.65; 0.59] |
σ21D, σ22D | / | 0.49 [0.12; 0.82] | 0.68 [0.34; 0.95] | 0.55 [0.10; 0.93] |
σ21D, σ23D | / | / | 0.43 [0.08; 0.75] | −0.04 [−0.72; 0.70] |
σ22D, σ23D | / | / | 0.60 [0.17; 0.89] | −0.09 [−0.87; 0.52] |
Deviance | 536,474 | 535,848 | 534,615 | 534,549 |
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Rollet, Q.; Guillaume, É.; Launay, L.; Launoy, G. Socio-Territorial Inequities in the French National Breast Cancer Screening Programme—A Cross-Sectional Multilevel Study. Cancers 2021, 13, 4374. https://doi.org/10.3390/cancers13174374
Rollet Q, Guillaume É, Launay L, Launoy G. Socio-Territorial Inequities in the French National Breast Cancer Screening Programme—A Cross-Sectional Multilevel Study. Cancers. 2021; 13(17):4374. https://doi.org/10.3390/cancers13174374
Chicago/Turabian StyleRollet, Quentin, Élodie Guillaume, Ludivine Launay, and Guy Launoy. 2021. "Socio-Territorial Inequities in the French National Breast Cancer Screening Programme—A Cross-Sectional Multilevel Study" Cancers 13, no. 17: 4374. https://doi.org/10.3390/cancers13174374