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Additional file 1. Supplementary Figure S1. Flow chart of the Norwegian Covid-19 cohort study.

Additional file 3. Supplementary Figure S2. Proportion of new positive SARS-CoV-2 tests in Norway during different time points indicating different test criteria.

Additional file 1. Supplementary Tables S1���S3.

Additional file 1. Tables S1 and S2: Supplementary data providing results from sensitivity analyses of pooled models adjusted for a population-specific weight-for-height index instead of BMI

Additional file 2. Supplementary Table S1. Adjusted odds ratio and 95% confidence interval (CI) for the association between the use of public transport (baseline only) and risk of SARS-CoV-2.

Additional file 2. Contains a supplementary figure with figure title and legend.

Additional file 1. Contains two supplementary tables.

Additional file 3. Contains the STROBE checklist for observational studies.

Age and tumor subtype are prognostic factors for breast cancer survival, but it is unclear which matters the most. We used population‐based data to address this question. We identified 21,384 women diagnosed with breast cancer at ages 20–89 between 2005 and 2015 in the Cancer Registry of Norway. Subtype was defined using estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor 2 (HER2) status as luminal A‐like (ER+PR+HER2‐), luminal B‐like HER2‐negative (ER+PR‐HER2‐), luminal B‐like HER2‐positive (ER+PR+/‐HER2+), HER2‐positive (ER‐PR‐HER2+) and triple‐negative (TNBC) (ER‐PR‐HER2‐). Cox regression estimated hazard ratios (HR) for breast cancer‐specific 7‐year survival by age and subtype, while adjusting for year, grade, TNM stage and treatment. Young women more often had HER2‐positive and TNBC tumors, while elderly women (70–89) more often had luminal A‐like tumors. Compared to age 50–59, young women had doubled breast cancer‐specific mortality rate (HR = 2.26, 95% CI 1.81–2.82), while elderly had two to five times higher mortality rate (70–79: HR = 2.25, 1.87–2.71; 80–89: HR = 5.19, 4.21–6.41). After adjustments, the association was non‐significant among young women but remained high among elderly. Young age was associated with increased breast cancer‐specific mortality among luminal A‐like subtype, while old age was associated with increased mortality in all subtypes. Age and subtype were strong independent prognostic factors. The elderly always did worse, also after adjustment for subtype. Tumor‐associated factors (subtype, grade and stage) largely explained the higher breast cancer‐specific mortality among young. Future studies should address why luminal A‐like subtype is associated with a higher mortality rate in young women.

BACKGROUND: Mammographic density is a potentially modifiable risk factor for breast cancer. To what extent mammographic density is a predictor for both hormone receptor-positive and hormone receptor-negative tumors is unclear. Even less is known about whether mammographic density predicts subtypes of breast cancer defined by expression status of the three receptors: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER-2). METHODS: We estimated the association of percent mammographic density with subtypes of invasive breast cancer among 479 population-based female breast cancer patients and 376 control subjects ages 35 to 64 years. The expression status of ER, PR, and HER-2 was assessed using immunohistochemistry methods in a single laboratory. We considered ER+ or PR+ plus HER-2- tumors as luminal A breast cancer and ER-/PR-/HER-2- tumors as triple-negative breast cancer. We used unconditional logistic regression methods to estimate odd ratios (95% confidence intervals) for both case-control and case-case comparisons. RESULTS: Mammographic density was associated with increased risk of both invasive breast cancer subtypes, luminal A and triple-negative, in the case-control analysis. Results from case-case comparisons yielded no differences between the two subtypes among all women combined or in analyses done separately by race (White versus African American women) or menopausal status (premenopausal versus postmenopausal women; all P values > 0.05). CONCLUSIONS: Our results suggest that percent mammographic density is positively associated with both luminal A and triple-negative breast cancer.

There is some evidence that women with a higher number of CAG repeat lengths on the androgen receptor (AR) gene have increased breast cancer risk. We evaluated the association between AR-CAG repeat length and mammographic density, a strong breast cancer risk factor, in 404 African-American and Caucasian breast cancer patients. In postmenopausal estrogen progestin therapy users, carriers of the less active AR-CAG had statistically significantly higher mean percentage of density (41.4%) than carriers of the more active AR-CAG (25.7%; P = 0.04). Our results raise the question of whether the number of AR-CAG repeats predicts breast cancer risk in estrogen progestin therapy users.

The extent of radiodense tissue on a mammogram (mammographic densities) is strongly associated with breast cancer risk among (non-Latina) white women, but few data exist for African-American and Asian-American women. We collected prediagnostic mammograms from 622 breast cancer patients and 443 control subjects ages 35-64 years from three different ethnic groups (whites, African Americans, and Asian Americans) who participated as cases and controls in one of two ongoing breast cancer studies. Percent and absolute mammographic density were assessed using a previously validated computer-assisted method. In all three ethnic groups combined, breast cancer risk increased with increasing percent mammographic density. After adjustment for ethnicity, age, body mass index, age at menarche, breast cancer family history, age at and number of full-term pregnancies, menopausal status, and hormone replacement therapy use, women with the highest percent density had 5-fold greater breast cancer risk than women with no density (P(trend) = 0.0001). The impact of percent density on risk was stronger for older than for younger women (>/=50 versus

Background: Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors. Methods: We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases = 46,325, controls = 42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively. Results: In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR] = 0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56–0.75, p = 3.32 × 10−10). The associations were similar for both premenopausal (OR = 0.44, 95% CI:0.31–0.62, p = 9.91 × 10−8) and postmenopausal breast cancer (OR = 0.57, 95% CI: 0.46–0.71, p = 1.88 × 10−8). This association was replicated in the data from the DRIVE consortium (OR = 0.72, 95% CI: 0.60–0.84, p = 1.64 × 10−7). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p < 0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk. Conclusions: BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.