Participation in the German Mammography Screening Program

An Analysis of Data From the NAKO Health Study

Background: European guidelines recommend a minimum participation rate of 70% for mammography screening programs (MSP), but the rate in Germany has so far been only 50% per round. In this study, we identify factors associated with non-participation in MSP.

Methods: Cross-sectional data on women aged 50 to 69 from the population-based NAKO Health Study (2014–2019) were used to identify factors associated with MSP participation, and dimensions of participatory behavior were derived by principal component analysis (PCA).

Results: Of 48 057 women aged 50 to 69, 14.6% had never participated in MSP, 35.3% had participated once, and 50.2% had participated multiple times. Age-adjusted regression analyses of individual factors revealed that the use of other primary and secondary prevention measures was the strongest predictor of MSP participation. Smoking was associated with lower probability of participation (odds ratio [OR]: 0.70; 95% confidence interval: [0.67; 0.75]), and overweight with higher ones (OR: 1.26 [1.19; 1.34]). PCA enabled the aggregation of factors into three dimensions: “use of preventive measures,” “socioeconomic status,” and “lifestyle factors.”

Conclusion: In this study, marked differences were found between MSP non-participants and participants, especially with respect to their use of other preventive measures and their socioeconomic status. One limitation of this study was the self-reporting of MSP participation. Its findings nevertheless provide a basis for interventions directed at specific target groups, for example, education about preventive services (and MSP in particular) in the primary care setting.

Cite this as: Buschmann L, Bonberg N, Baurecht H, Becher H, Brenner H, Harth V, Heise JK, Holleczek B, Jaskulski S, Kantelhardt E, Keil T, Klett-Tammen CJ, Leitzmann M, Meinke-Franze C, Michels KB, Mikolajczyk R, Obi N, Ostrzinski S, Peters A, Schikowski T, Schipf S, Schmidt B, Schulze MB, Stallmann C, Stang A, Stübs G, Willich SN, Haug U, Minnerup H, Karch A: Participation in the German mammography screening program: An analysis of data from the NAKO Health Study. Dtsch Arztebl Int 2025; 122: 655–62. DOI: 10.3238/arztebl.m2025.0156

Since 2009, women in Germany aged between 50 and 69 have been invited every 2 years, through an organized invitation procedure, to participate in a population-based, quality-assured mammography screening program (MSP) and have been supported in their decision-making by information leaflets (1, 2). The aim of this screening program is to reduce breast cancer mortality by bringing forward the time of diagnosis to more prognostically favorable tumor stages (3). European guidelines recommend that the minimum participation rate among invited women should be 70% for the screening program to be cost-effective (4, 5). Despite 13 years of full MSP implementation, this target has still not been met, with participation rates of around 50% per screening round in Germany (1).

National and international observational studies have shown associations between MSP participation and demographic, socioeconomic, educational, and behavioral factors (6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22). For the German MSP, Pokora et al. (20) found that socioeconomic inequalities in equivalence income and educational status are associated with MSP participation. Schnoor et al. (21) found that medical reasons and personal attitudes may lead to MSP non-participation, while Heinig et al. (22) demonstrated an association between MSP participation and the use of other screening examinations.

In July 2024, the upper age limit for the German MSP was raised to 75 years, resulting in an increase in the number of eligible women from 12 to 14.5 million (23). As in other European countries, Germany is also evaluating whether the screening could be extended to younger age groups. In this context, a better understanding of MSP participation behavior in Germany is crucial to identify reasons associated with non-use of MSP. To date, no comprehensive investigation of the individual factors described here has been conducted using a broad primary dataset for the German MSP. Based on data from the NAKO Health Study (NAKO Gesundheitsstudie), factors described in the international context were investigated for their effects on MSP participation in Germany—in addition to those factors proposed by other German studies—and potentially modifiable components were identified.

Methods

Study population

Between March 2014 and September 2019, 204 733 individuals aged 20–69 years were recruited using random draws from compulsory residents’ registries, with an average response rate of 18.0% (24, 25, 26, 27). The baseline examination conducted at 18 study centers included an interview and assessments using standardized questionnaires, as well as medical examinations and the collection of biomaterials. A total of 48 057 women of eligible age were included in the main analyses (eSupplement – Chapter 2: Figure S1).

Characteristics assessed

MSP participation was assessed based on information regarding X-ray examination of the breast (“mammography”, “breast cancer screening”) and the response options “never”, “once”, and “multiple times”. More details on all variables used are presented in Table S1 in Chapter 2 of the eSupplement.

Statistical analysis

Relative and absolute frequencies (age-standardized for MSP non-participants [eSupplement – Chapter 1 : Section S1]) were calculated for discrete variables, while means were calculated for continuous variables. Logistic regression, adjusted for age (per year), was used to evaluate the association between MSP participation at least once and demographic, socioeconomic, educational, and behavioral variables. For the 16 identified variables whose confidence intervals did not include 1, a polychoric principal component analysis (PCA) was conducted to identify meaningful dimensions of MSP participation behavior. To determine the number of principal components, testing procedures for the extraction of different PCA models were applied, from which a three-component solution was selected based on content. Standardized values of the principal components were then included as independent variables in the multivariable regression model. In addition to principal components, age and family history of breast cancer were included, depending on the model, as factors that were not included in the PCA or could not be assigned to a component.

Detailed information on the statistical methods can be found in Section S2 of Chapter 1 in the eSupplement.

All analyses were conducted in R 4.4.0 using the following packages: readr (version 2.1.5), tidyverse (version 2.0.0), dplyr (version 1.1.4), flextable (version 0.9.6), nFactors (version 2.4.1.1), EFAtools (version 0.4.4), gt (version 0.10.1), scales (version 1.3.0), gtsummary (version 2.0.2), psych (version 2.4.3), ggplot2 (version 3.5.1), and ggforestplot (version 0.1.0).

Sensitivity analyses

The PCA and multivariable regression analyses were repeated without the factor “clinical breast examination,” since this screening measure is performed at a different medical center but serves the same purpose as the MSP.

Furthermore, sensitivity analyses were conducted with varying study populations. More information on this can be found in Section S1 of Chapter 4 in the eSupplement.

Results

Of a total of 48 057 women included in the study, 14.6% had never participated in the MSP, 35.2% had participated once, and 50.2% had participated multiple times (Table 1, eSupplement – Chapter 2: Figure S2). In the age-standardized frequency analyses, women living in southern Germany were most likely to report non-participation in the MSP (17.8%). Women without a partner (19.7%) more often reported never having participated in the MSP compared with women in a partnership (13.0%). Women with a medium level of education were less likely than other women to report non-use of the MSP (13.0%). Among women with a relative income position of less than 60% of the median income and who are at risk of poverty, the proportion of non-participants in the MSP is highest (17.7%) compared with women in higher income groups. Women with private health insurance more frequently reported never having participated in the MSP (19.7%) than did women with statutory health insurance (13.7%). Of the women who reported breast cancer in their mother, 11.1% stated that they had never participated in the MSP, 27.7% once, and 61.3% multiple times. Overall, women who also used other preventive services, such as flu vaccinations and other screening examinations, were more likely to report having participated in the MSP at least once. The same applied to women who had taken the contraceptive pill and/or hormone replacement therapy at least once. Current smokers were more likely never to have participated in the MSP (19.2%) compared with non- and ex-smokers. Among women with overweight or obesity, multiple participation was more common (50.7%) than among women with underweight and normal weight (38.1% and 49.7%, respectively). Furthermore, it was observed that women who had participated multiple times in the MSP also had larger social networks (Table 1).

Table 1

Sociodemographic characteristics and specific factors (use of medical [preventive] measures, cancer [family] history, lifestyle factors) of the study cohort, stratified by MSP participation status

The factors identified in the age-adjusted regression analyses (confidence intervals not including 1) (Table 2) were combined in the PCA into three principal components—“use of preventive measures” (RC1), “socioeconomic status” (RC2), and “lifestyle factors” (RC3)—which together explained 43.0% of the variance (eSupplement – Chapter 2: Table S3). The variable “family history of breast cancer” was the only one of altogether 16 variables that could not be assigned to any of the three extracted principal components (Figure 1).

Figure 1

Radar chart of the principal component analysis loadings

Table 2

Odds ratios for individual factors influencing participation in the Mammography Screening Program (ever versus never) after age adjustment

In the multivariable regression analyses, an odds ratio (OR) of 1.42 (95% confidence interval [1.39; 1.44]) was calculated for RC1, an OR of 0.81 [0.79; 0.83] for RC2, and an OR of 1.14 [1.11; 1.17] per standard deviation of the standardized principal component (Figure 2, Model 1). After adjusting for age and family history of breast cancer, these three principal components showed virtually unchanged estimates and confidence intervals, with family history of breast cancer (OR: 1.35 [1.13; 1.62]) and higher age at the time of the survey (OR: 1.02 [per life year] [1.01; 1.03]) each being positively associated with MSP participation (Figure 2, Model 4).

Figure 2

Models of the multivariable regression analyses

Sensitivity analyses

Analyses without “clinical breast examination” yielded results comparable to those of the main analyses. All dimensions showed overall comparable loadings and variances (eSupplement – Chapter 2: Figure S3 and Table S4).

Analyses based on varying study populations also yielded virtually identical results (eSupplement – Chapter 4: Figures S1.1 and S2.1, and Tables S1.1–S1.3, S2.1–S2.3).

Discussion

Using primary data from the NAKO Health Study, factors influencing MSP participation behavior in Germany were investigated. In the study population, 85.5% of women reported having participated in the MSP at least once. This cumulative use, recorded by self-reporting and relating retrospectively to several years (that is, over multiple screening rounds), is by nature higher than the likelihood of participating in a single screening round. Assuming that all women aged 50 and older had had the opportunity to participate in the MSP up to their age at the baseline examination—which was the case according to the NAKO baseline examination conducted 5 years after full implementation of the MSP—and that the probability of participation per screening round was 50% (1), this cumulative MSP participation rate is plausible (eSupplement – Chapter 1 : Section S3) and, taking into account the age structure of the respective cohorts, comparable with previous studies (9, 20). Our study confirmed the findings published by the German Mammography Cooperation Group (Kooperationsgemeinschaft Mammografie) (1) regarding regional differences in the use of the German MSP (28).

Using PCA, the individual factors could be aggregated into “use of preventive measures” (RC1), “socioeconomic status” (RC2), and “lifestyle factors” (RC3), thereby demonstrating their association with MSP participation. As comparative studies are lacking, the individual factors aggregated in the principal components are considered below and compared with the existing evidence.

In our study, analyses of the use of other preventive measures offered by the health care system showed consistent results, as participation in other screening programs or uptake of flu vaccines was always associated with higher MSP participation. This confirms the findings of Heinig et al. (22), suggesting, overall, more health-conscious behavior among MSP participants.

Analyses of the individual lifestyle factors yielded heterogeneous results. For example, smoking was associated with lower MSP participation, as also shown in international studies by Loewen et al. (14) and Aro et al. (15). In contrast, overweight and obesity were associated with a higher participation rate. Lower MSP uptake was observed among underweight women, possibly indicating serious illnesses that, in turn, prevent MSP participation.

Unlike our study, previous studies have shown that adequate physical activity and the absence of alcohol abuse were associated with having participated in the MSP at least once (16, 11); however, in these studies, the response categories for these factors were defined somewhat differently and therefore had different research objectives (e.g., risky alcohol consumption versus dependence) (Tables 1–2, eSupplement – Chapter 2: Tables S1–2; eSupplement – Chapter 3: Tables S1–S2).

When considering the sociodemographic and socioeconomic factors individually, the data from the NAKO Health Study—as in international studies (11, 15, 17, 18, 20) and the first German study (20)—showed that women with a lower educational level and lower income participated less frequently in the MSP than women in higher educational and income categories. In agreement with the results of Aro et al. (15), we demonstrated a slightly U-shaped association, whereby women of medium educational level and medium income were most likely to participate in the MSP. The modest decline among women of high educational level may be attributable to a higher proportion of privately insured women, since our study—as well as a cross-sectional study in Schleswig-Holstein (21)—showed that women with private health insurance were less likely to participate in the MSP. This could be due to the fact that, although privately insured women are legally entitled to participate in the mammography screening program (2), they often receive mammograms outside the MSP or use alternative examination methods such as magnetic resonance imaging (MRI) and ultrasound as part of their gynecological care—methods that, according to the S3 guideline (29, 30), are recommended only for women at high risk or as possible supplementary, but not sole, methods of breast cancer screening (29, 30). By the same token, non-participation in the MSP may be due to the effect of costs on the patient’s deductible or premium refund, depending on the insurance plan (31). Furthermore, it was observed that women who were married, did not live alone, and had a social network were more likely to participate in the MSP—a finding compatible with international study results (10, 11, 12, 13). The remaining results of this study, such as those regarding the use of hormone replacement therapy, are also in agreement with international studies (9).

Although numerous factors were analyzed as part of our broad study concept, the three principal components explain only 43.0% of the total variance. Thus, the larger proportion of 57.0% remains unexplained, for which there could be various explanations. On the one hand, women are advised to inform themselves using the information material provided and to decide for or against MSP participation. It is conceivable that unassessed or difficult-to-assess factors also play a role in informed decision-making against uptake of the MSP. Furthermore, other individual factors that were not investigated in this study may also be possible explanations, such as refusal to undergo X-ray examinations. On the other hand, there are factors such as a positive family history of breast cancer that were considered but could not be included in the principal components. However, for this individual factor, the multivariable regression analysis also showed an OR of 1.35 ([1.13; 1.62]) (Figure 2). International studies conducted by Tracy et al. (32) and Murabito et al. (33), which investigated, among other factors, the impact of a positive first-degree family history compared with a negative family history of breast cancer, showed stronger associations (OR: 3.2 [1.4; 7.7]; OR: 2.13 [1.35; 3.37]). It should be noted that the NAKO Health Study recorded only breast cancer diagnoses in mothers, meaning that the true prevalence of a family history of breast cancer is likely to be underestimated in the present data. Another factor contributing to the observed results is that, in Germany, women with a positive family history of breast cancer are more likely to undergo opportunistic screening (16, 22); in cases of a positive family history with a confirmed genetic predisposition, other screening measures outside the MSP are also used (30), and women may be under the care of centers for familial breast and ovarian cancer.

Based on the results obtained here, initial approaches for possible interventions and target groups can be identified. Although the MSP has an organized invitation procedure, it was found that women who use other screening programs are also more likely to participate in the MSP. This means that medical personnel, such as general practitioners whom women consult for other reasons, could be more actively involved in providing information about the various screening options available, thereby helping to ensure that women can make an informed decision for or against screening examinations—and thus also for or against participation in the MSP. Women with private health insurance could also represent a target group for which specific approaches can be derived, since here too, the MSP participation rate was low.

One of the limitations of this study is the representativeness of the study population. Although the underlying primary data from the largest population-based cohort study in Germany were collected at 18 locations in urban and rural areas (27), they tend to more closely reflect an urban population. Moreover, given that health-conscious individuals are more likely to participate in the NAKO Health Study, the uptake of screening examinations is higher here than the national average (34, 35).

In addition to the limitations in collecting family history of breast cancer, there are also constraints in defining MSP participation status, since not only was no supplementary explanatory information provided, but the date of the respective examination was also not requested to verify age-based eligibility. Thus, it is possible that diagnostic mammograms were also included, although only MSP participation was intended to be collected. One indication of the presence of this type of misclassification is the reporting of multiple instances of participation among women aged 50 or 51 (eSupplement – Chapter 4: Figure S2.1 and Tables S2.1–S2.3); however, excluding these women in the sensitivity analysis did not alter the results. Misclassifications in the remaining information cannot be ruled out if, for example, older women additionally reported mammograms performed prior to MSP participation.

Summary

Using primary data from the NAKO Health Study, relevant factors for MSP participation were identified and aggregated into principal components. These principal components offer initial starting points for the development of targeted interventions to support the decision-making process among eligible women.

Additional authors

Hansjörg Baurecht, Heiko Becher, Hermann Brenner, Volker Harth, Jana-Kristin Heise, Bernd Holleczek, Stefanie Jaskulski, Eva Kantelhardt, Thomas Keil, Carolina J. Klett-Tammen, Michael Leitzmann, Claudia Meinke-Franze, Karin B. Michels, Rafael Mikolajczyk, Nadia Obi, Stefan Ostrzinski, Annette Peters, Tamara Schikowski, Sabine Schipf, Börge Schmidt, Matthias Bernd Schulze, Christoph Stallmann, Andreas Stang, Gunthard Stübs, Stefan N. Willich, Ulrike Haug, Heike Minnerup

Affiliations of the additional authors

Acknowledgments

We would like to thank all participants and staff of the NAKO Health Study.

We also thank Nicole Rübsamen, PhD, and PD Dr. Jürgen Wellmann for the scientific exchange regarding the analyses conducted here.

Declarations

All participants were fully informed and provided their written informed consent to participate in the study. The study was conducted in compliance with national law and the 1975 Declaration of Helsinki (in its current revised form) and was approved by the ethics committees responsible for the study centers.

Funding

This project was conducted using data from the NAKO Gesundheitsstudie (NAKO Health Study, NAKO-847) (www.nako.de). The NAKO Health Study is funded by the German Federal Ministry for Education and Research (Bundesministerium für Bildung und Forschung, BMBF) (Grant Nos. 01ER1301A/B/C, 01ER1511D, 01ER1801A/B/C/D, and 01ER2301A/B/C), the German federal states, and the Helmholtz Association (Helmholtz-Gemeinschaft), and also receives financial support from the participating universities and institutes of the Leibniz Association (Leibniz-Gemeinschaft).

Conflict of interest statement

AS served as a member of the advisory board of the Mammography Screening
Cooperation Group (Beirat der Kooperationsgemeinschaft Mammografiescreening) until March 2025.

The remaining authors declare that no conflict of interest exists.

Manuscript submitted on 26 March 2025, revised version accepted on
27 August 2025.

Translated from the original German by Christine Rye.

Corresponding author
Prof. Dr. med. André Karch, MSc

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