Conflicting associations between dietary patterns and changes of anthropometric traits across subgroups of middle-aged women and men.

BACKGROUND: Individuals respond differently to dietary intake leading to different associations between diet and traits. Most studies have investigated large cohorts without subgrouping them. OBJECTIVE: The purpose was to identify non-uniform associations between diets and anthropometric traits that appeared to be in conflict with one another across subgroups. DESIGN: We used a cohort comprising 43,790 women and men, the Danish Diet, Cancer and Health study, which includes a baseline examination at age 50-64 years and a follow-up about 5 years later. The baseline examination involved anthropometrics, body fat percentage, a food frequency questionnaire and information on lifestyle. From the questionnaire data we computed association rules between the intake of food groups and changes in waist circumference and body weight. Using association rule mining on subgroups and gender-specific cohorts, we identified non-uniform associations. The two gender-specific cohorts were stratified into subgroups using a non-linear, self-organizing map based method. RESULTS: We found 22 and 7 cases of conflicting rules in 8 participant subgroups for different anthropometric traits in women and men, respectively. For example, in a subgroup of women moderate waist loss was associated with a dietary pattern characterized by low intake in both cabbages and wine, in conflict with the association trends of both dietary factors in the female cohort. The finding of more conflicting rules in women suggests that inter-individual differences in response to dietary intake are stronger in women than in men. CONCLUSIONS: This combined stratification and association discovery approach revealed epidemiological relationships between dietary factors and changes in anthropometric traits in subgroups that take food group interactions into account. Conflicting rules adds an additional layer of complexity that should be integrated into the study of these relationships, for example in relation to genotypes.

The U-shaped association of body mass index with mortality: Influence of the traits height, intelligence, and education.

OBJECTIVE: The U-shaped association between body mass index (BMI) and mortality may depend on other traits with permanent health effects. Whether the association between BMI and mortality depends on levels of health-related traits known to be inversely associated with mortality throughout adult life such as height, intelligence, and education was investigated. METHODS: The study was based on a cohort of young men with data on weight, height, intelligence test score, and education from the Danish Conscription Database. In total, 346,500 men born 1939 to 1959 were followed until December 2013. The association between BMI and mortality was analyzed using Cox-regression models including interactions between BMI and height, intelligence, and education, respectively. RESULTS: BMI and mortality showed the U-shaped association from the start of the follow-up period, and it persisted through the subsequent 56 years. As expected, the mortality was inversely associated with height, intelligence, and education, but the U shape of the association between BMI and mortality was unaffected by the levels of these traits except at higher BMI values, where the slopes were steeper for men with higher levels of height, intelligence, and education. CONCLUSIONS: High and low BMI was associated with higher mortality throughout life regardless of the levels of height, intelligence, and education.

How Suitable Are Registry Data for Recurrence Risk Calculations? Validation of Diagnoses on 1,593 Families With Congenital Heart Disease.

BACKGROUND: Congenital heart disease (CHD) occurs in approximately 1% of all live births, and 3% to 8% of these have until now been considered familial cases, defined as the occurrence of two or more affected individuals in a family. The validity of CHD diagnoses in Danish administrative registry data has only been studied previously in highly selected patient populations. These studies identified high positive predictive values (PPVs) and recurrence risk ratios (RRRs-ratio between probabilities of CHD given family history of CHD and no family history). However, the RRR can be distorted if registry data are used indiscriminately. Here, we investigated the consequences of misclassifications for the RRR using validated diagnoses on Danish patients with familial CHD. METHODS: Danish citizens are assigned a civil registration number (CPR number) at birth or immigration, which acts as a unique identifier in the Danish registries, thus enabling connection of information from several registries. Utilizing the CPR number, we identified Danish patients with familial CHD and reviewed each patient's file. We compared diagnoses from the registries with those manually assigned, which enabled calculation of the PPVs of diagnoses in the Danish registries, and from this, we deduced the false discovery rate (FDR). To measure the consequences on the RRR, the FDR was applied to a simulated data set with true RRR values of 2 and 10. RESULTS: We validated diagnoses of 2,442 patients from 1,593 families. Of these, 874 patients were misclassified corresponding to an FDR of 36%. Applying this FDR on the simulated data sets, we found that the RRR decreased from 2 and 10 to 1.4 and 5.1, respectively. Lastly, we estimated that 11% of all cases with CHD were familial. CONCLUSION: We found that approximately one of nine of all cases with CHD are familial, and we also found that 36% of individuals with CHD in administrative medical registries are misclassified, which distort the RRR in simulated scenarios.

Cohort Profile: The Danish Conscription Database(DCD): A cohort of 728,160 men born from 1939 through 1959.

The Danish Conscription Database (DCD) was established to enable studies of the influence of early physical and mental exposures on adverse health and social outcomes from a life-course perspective. In Denmark, all young men are requested to appear before the conscription board when they turn 18 years, to be assessed for military service. The DCD was established by digitizing information from conscription board register cards on the height, weight, educational level, intelligence test score and examination details of Danish conscripts. The DCD contains information on 728,160 men born from 1939 through 1959 and examined by the conscription board from 1957 through 1984. The unique Danish personal identification number of each individual conscript has been traced, and this allows linkage of the DCD to all Danish health and socioeconomic registers. More than 130,000 deaths have been identified in a recent linkage to the Danish Register of Cause of Death. We encourage collaboration, and interested researchers should contact: danishconscriptiondatabase.glostrup-hospital@regionh.dk.