The purpose of this study was to investigate the effect of breast density on breast cancer (BC) mortality in a mammography screening programme. The cohort included 48 052 women participating in mammography screening in Copenhagen, Denmark, where biennial screening is offered to women aged 50 -69 years. We collected information for the years 1991 -2001 on screening outcome, incident BCs (screen-, interval-, and later detected), and BC deaths. Breast density was dichotomised into fatty (F) and mixed/dense (M/D) breasts. Screening sensitivity was measured as the odds ratio of interval versus screen-detected cancer for dense versus F breasts. Poisson regression was used to estimate the ratios for BC incidence, case fatality, and mortality between women with M/D and F breasts. For women with M/D breasts, the odds ratio of an interval cancer was 1.62 (95% confidence interval, CI, 1.14 -2.30), and the age-adjusted rate ratios were 2.45 (95% CI 2.14 -2.81) for BC incidence, 0.60 (95% CI 0.43 -0.84) for case fatality, and 1.78 (95% CI 1.17 -2.72) for BC mortality. The study shows that BC in women with M/D breasts is more frequent, but on average less severe, than in women with F breasts. British Journal of Cancer (2009) Breast density is a measure of the composition of the breast tissue. Breasts with low density have a high proportion of fatty (F) tissue, whereas breasts with high density have a high proportion of epithelial and connective tissue. Mammography has a lower sensitivity in women with mixed/dense (M/D) breasts than in women with F breasts (Mandelson et al, 2000, Ciatto et al, 2004Chiarelli et al, 2006), and women with M/D breasts have a higher incidence of breast cancer (BC) than women with F breasts (McCormack and dos Santos Silva, 2006;Boyd et al, 2007). We therefore examined whether breast density affects the outcome of mammography screening using data from the organised mammography screening programme in Copenhagen, Denmark, earlier shown to reduce BC mortality in targeted women by 25% and in participating women by 37% (Olsen et al, 2005).We tested the following hypotheses: compared with women with F breasts, (1) the sensitivity of mammography is lower in women with M/D breasts, and (2) women with M/D breasts have a higher BC incidence. Our results were well in accordance with those of earlier studies. We further tested whether: (3) because of the lower sensitivity the case fatality rate of BC patients with M/D breasts will be higher than that of patients with F breasts, and (4) screened women with M/D breasts will experience a higher BC mortality than screened women with F breasts. This study is the first to report on the effect of breast density on BC mortality in screened women.

IntroductionHigh breast density, a strong predictor of breast cancer may be determined early in life. Childhood anthropometric factors have been related to breast cancer and breast density, but rarely simultaneously. We examined whether mammographic density (MD) mediates an association of birth weight, childhood body mass index (BMI), and height with the risk of breast cancer.Methods13,572 women (50 to 69 years) in the Copenhagen mammography screening program (1991 through 2001) with childhood anthropometric measurements in the Copenhagen School Health Records Register were followed for breast cancer until 2010. With logistic and Cox regression models, we investigated associations among birth weight, height, and BMI at ages 7 to 13 years with MD (mixed/dense or fatty) and breast cancer, respectively.Results8,194 (60.4%) women had mixed/dense breasts, and 716 (5.3%) developed breast cancer. Childhood BMI was significantly inversely related to having mixed/dense breasts at all ages, with odds ratios (95% confidence intervals) ranging from 0.69 (0.66 to 0.72) at age 7 to 0.56 (0.53 to 0.58) at age 13, per one-unit increase in z-score. No statistically significant associations were detected between birth weight and MD, height and MD, or birth weight and breast cancer risk. BMI was inversely associated with breast cancer, with hazard ratios of 0.91 (0.83 to 0.99) at age 7 and 0.92 (0.84 to 1.00) at age 13, whereas height was positively associated with breast cancer risk (age 7, 1.06 (0.98 to 1.14) and age 13, 1.08 (1.00 to 1.16)). After additional adjustment for MD, associations of BMI with breast cancer diminished (age 7, 0.97 (0.88 to 1.06) and age 13, 1.01 (0.93 to 1.11)), but remained with height (age 7, 1.06 (0.99 to 1.15) and age 13, 1.09 (1.01 to 1.17)).ConclusionsAmong women 50 years and older, childhood body fatness was inversely associated with the breast cancer risk, possibly via a mechanism mediated by MD, at least partially. Childhood tallness was positively associated with breast cancer risk, seemingly via a pathway independent of MD. Birth weight was not associated with MD or breast cancer in this age group.

Suicide is a major public health concern. High-dose lithium is used to stabilize mood and prevent suicide in patients with affective disorders. Lithium occurs naturally in drinking water worldwide in much lower doses, but with large geographical variation. Several studies conducted at an aggregate level have suggested an association between lithium in drinking water and a reduced risk of suicide; however, a causal relation is uncertain. Individual-level register-based data on the entire Danish adult population (3.7 million individuals) from 1991 to 2012 were linked with a moving five-year time-weighted average (TWA) lithium exposure level from drinking water hypothesizing an inverse relationship. The mean lithium level was 11.6 μg/L ranging from 0.6 to 30.7 μg/L. The suicide rate decreased from 29.7 per 100,000 person-years at risk in 1991 to 18.4 per 100,000 person-years in 2012. We found no significant indication of an association between increasing five-year TWA lithium exposure level and decreasing suicide rate. The comprehensiveness of using individual-level data and spatial analyses with 22 years of follow-up makes a pronounced contribution to previous findings. Our findings demonstrate that there does not seem to be a protective effect of exposure to lithium on the incidence of suicide with levels below 31 μg/L in drinking water.

BackgroundThe range of influence refers to the average distance between locations at which the observed outcome is no longer correlated. In many studies, missing data occur and a popular tool for handling missing data is multiple imputation. The objective of this study was to investigate how the estimated range of influence is affected when 1) the outcome is only observed at some of a given set of locations, and 2) multiple imputation is used to impute the outcome at the non-observed locations.MethodsThe study was based on the simulation of missing outcomes in a complete data set. The range of influence was estimated from a logistic regression model with a spatially structured random effect, modelled by a Gaussian field. Results were evaluated by comparing estimates obtained from complete, missing, and imputed data.ResultsIn most simulation scenarios, the range estimates were consistent with ≤25% missing data. In some scenarios, however, the range estimate was affected by even a moderate number of missing observations. Multiple imputation provided a potential improvement in the range estimate with ≥50% missing data, but also increased the uncertainty of the estimate.ConclusionsThe effect of missing observations on the estimated range of influence depended to some extent on the missing data mechanism. In general, the overall effect of missing observations was small compared to the uncertainty of the range estimate.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-072X-14-1) contains supplementary material, which is available to authorized users.

Multiple sclerosis has been hypothesized to be the result from an aberrant immune response possibly triggered by delayed exposure to a common childhood infection. Because the vast majority of previous studies testing this hypothesis have been based on a history of childhood infections recalled years to decades later in adulthood, we investigated whether age at six common childhood infections was associated with risk of multiple sclerosis, using information recalled in the childhood of a historical cohort of school children in Denmark. Cases included all individuals with multiple sclerosis in the country born between 1940 and 1975, who had attended school in the capital, Copenhagen. Controls were age- and sex-matched peers. School health records were obtained for all subjects. The records contained information on measles, pertussis, scarlet fever, birth order, sibship size, social class of the father, school years, and name of school and attended school classes for children born since 1940 (n(cases) = 455, n(controls) = 1801). For children born since 1950, the records also contained information on rubella, varicella and mumps (n(cases) = 182, n(controls) = 690). Neither age at infection with measles, rubella, varicella, mumps, pertussis and scarlet fever (upper age limit, 14 years) nor the cumulative number of these infections between the ages of 10 and 14 years was associated with the risk of multiple sclerosis. In addition, the risk of multiple sclerosis was not associated with birth order or social class. No clustering of multiple sclerosis in school classes was observed. Our findings suggest that measles, rubella, mumps, varicella, pertussis and scarlet fever, even if acquired late in childhood, are not associated with increased risk of multiple sclerosis later in life.

The incidence of intussusception among Danish children declined significantly during the 1990s, particularly among infants 3 to 5 months of age.

ObjectiveThis study examined whether geographical patterns in incident acute myocardial infarction (AMI) were explained by neighbourhood-level and individual-level sociodemographic characteristics.DesignAn open cohort study design of AMI-free adults (age ≥30 years) with a residential location in Denmark in 2005–2014 was used based on nationwide administrative population and health register data linked by the unique personal identification number. Poisson regression of AMI incidence rates (IRs) with a geographical random effect component was performed using a Bayesian approach. The analysis included neighbourhood-level variables on income, ethnic composition, population density and population turnover and accounted for individual-level age, sex, calendar year, cohabitation status, income and education.SettingResidents in Denmark (2005–2014).ParticipantsThe study population included 4 128 079 persons (33 907 796 person-years at risk) out of whom 98 265 experienced an incident AMI.Outcome measureIncident AMI registered in the National Patient Register or the Register of Causes of Death.ResultsIncluding individual and neighbourhood sociodemographic characteristics in the model decreased the variation in IRs of AMI. However, living in certain areas was associated with up to 40% increased IRs of AMI in the adjusted model and accounting for sociodemographic characteristics only moderately changed the geographical disease patterns.ConclusionsDifferences in sociodemographic characteristics of the neighbourhood and individuals explained part, but not all of the geographical inequalities in incident AMI. Prevention strategies should address the confirmed social inequalities in incident AMI, but also target the areas with a heavy disease burden to enable efficient allocation of prevention resources.

Aims This study described the interplay between geographical and social inequalities in survival after incident acute myocardial infarction (AMI) and examined whether geographical variation in survival exists when accounting for sociodemographic characteristics of the patients and their neighbourhood. Methods Ringmap visualization and generalized linear models were performed to study post-AMI mortality. Three individual-level analyses were conducted: immediate case fatality, mortality between days 1 and 28 after admission and 365-day survival among patients who survived 28 days after admission. Results In total, 99,013 incident AMI cases were registered between 2005 and 2014 in Denmark. Survival after AMI tended to correlate with sociodemographic indicators at the municipality level. In individual-level models, geographical inequality in immediate case fatality was observed with high mortality in northern parts of Jutland after accounting for sociodemographic characteristics. In contrast, no geographical variation in survival was observed among patients who survived 28 days. In all three analyses, odds and rates of mortality were higher among patients with low educational level (odds ratio (OR) (95% credible intervals) of 1.20 (1.12–1.29), OR of 1.12 (1.01–1.24) and mortality rate ratio of 1.45 (1.30–1.61)) and low income (OR of 1.24 (1.15–1.33), OR of 1.33 (1.20–1.48) and mortality rate ratio of 1.25 (1.13–1.38)). Conclusion Marked geographical inequality was observed in immediate case fatality. However, no geographically unequal distribution of survival was found among patients who survived 28 days after AMI. Results additionally showed social inequality in survival following AMI.