Prenatal risk factors influencing childhood BMI and overweight independent of birth weight and infancy BMI: a path analysis within the Danish National Birth Cohort.

BACKGROUND AND OBJECTIVES: Prenatal risk factors for childhood overweight may operate indirectly through development in body size in early life and/or directly independent hereof. We quantified the effects of maternal and paternal body mass index (BMI), maternal age, socioeconomic position (SEP), parity, gestational weight gain, maternal smoking during pregnancy, caesarean section, birth weight, and BMI at 5 and 12 months on BMI and overweight at 7 and 11 years. METHODS: Family triads with information on maternal, paternal and child BMI at ages 7 (n=29 374) and 11 years (n=18 044) were selected from the Danish National Birth Cohort. Information originated from maternal interviews and medical health examinations. Path analysis was used to estimate the direct and indirect effects of prenatal risk factors on childhood BMI z-scores (BMIz per unit score of the risk factor). Logistic regression was used to examine associations with overweight. RESULTS: The strongest direct effects on BMIz at age 7 were found for maternal and paternal BMI (0.19 BMIz and 0.14 BMIz per parental BMIz), low SEP (0.08 BMIz), maternal smoking (0.12 BMIz) and higher BMIz at 5 and 12 months (up to 0.19 BMIz per infant BMIz). For BMIz at age 11 with BMIz at age 7 included in the model, similar effects were found, but the direct effects of BMIz at age 5 and 12 months were mediated through BMI at age 7 (0.62 BMIz per BMIz). Same results were found for overweight. The sum of the direct effects can be translated to approximate absolute measures: 2.4 kg at 7 years, 5.7 kg at 11 years, in a child with average height and BMI. CONCLUSIONS: Parental BMI, low SEP and smoking during pregnancy have persisting, strong and direct effects on child BMI and overweight independent of birth weight and infancy BMI.

Tracking of body mass index from 7 to 69 years of age.

BACKGROUND: Heavy children have an increased risk of being overweight young adults. Whether this risk remains in late adulthood is not well-understood. We investigated body mass index (BMI; kg m(-2)) tracking from childhood to late adulthood. METHODS: From the Copenhagen School Health Records Register, 72 959 men and 25 252 women born between 1930 and 1989 with BMI values at 7 and/or 13 years and as adults were included. Using a meta-regression approach, age- and sex-specific partial correlation analyses and logistic regressions were performed. RESULTS: Correlations between BMI at 7 years and young adult ages (18-19 years) were r=0.55 for men and r=0.55 for women. At late ages (60-69 years) these were r=0.28 for men and r=0.26 for women. The correlations did not differ by birth years. Compared with normal-weight 7-year-olds, overweight children had a higher odds of overweight at 18-19 years; odds ratio (OR)=14.02 (95% confidence interval (CI): 12.14-16.19) for men and 10.46 (95% CI: 4.82-22.70) for women. At ages 60-69 years ORs were 5.46 (95% CI: 0.95-31.36) for men and 1.61 (95% CI: 0.83-3.15) for women. Correlations and ORs were stronger at age 13 years than age 7 years as expected, but the overall patterns were similar. CONCLUSIONS: BMI tracking was weaker at late adult ages than at young adult ages. Although BMI tracks across the life course, childhood BMI is relatively poor at identifying later adult overweight or obesity at ages when chronic diseases generally emerge.

Is the adiposity-associated FTO gene variant related to all-cause mortality independent of adiposity? Meta-analysis of data from 169,551 Caucasian adults.

Previously, a single nucleotide polymorphism (SNP), rs9939609, in the FTO gene showed a much stronger association with all-cause mortality than expected from its association with body mass index (BMI), body fat mass index (FMI) and waist circumference (WC). This finding implies that the SNP has strong pleiotropic effects on adiposity and adiposity-independent pathological pathways that leads to increased mortality. To investigate this further, we conducted a meta-analysis of similar data from 34 longitudinal studies including 169,551 adult Caucasians among whom 27,100 died during follow-up. Linear regression showed that the minor allele of the FTO SNP was associated with greater BMI (n = 169,551; 0.32 kg m(-2) ; 95% CI 0.28-0.32, P < 1 × 10(-32) ), WC (n = 152,631; 0.76 cm; 0.68-0.84, P < 1 × 10(-32) ) and FMI (n = 48,192; 0.17 kg m(-2) ; 0.13-0.22, P = 1.0 × 10(-13) ). Cox proportional hazard regression analyses for mortality showed that the hazards ratio (HR) for the minor allele of the FTO SNPs was 1.02 (1.00-1.04, P = 0.097), but the apparent excess risk was eliminated after adjustment for BMI and WC (HR: 1.00; 0.98-1.03, P = 0.662) and for FMI (HR: 1.00; 0.96-1.04, P = 0.932). In conclusion, this study does not support that the FTO SNP is associated with all-cause mortality independently of the adiposity phenotypes.

Dietary protein and urinary nitrogen in relation to 6-year changes in fat mass and fat-free mass.

BACKGROUND: In contrast to the physiological expectation, observational studies show that greater protein intake is associated with subsequent body weight (BW) gain. An increase in fat-free mass (FFM) due to the anabolic effects of protein could explain this. OBJECTIVE: To examine associations between protein intake and subsequent changes in fat mass (FM) and FFM in longitudinal, observational data. DESIGN: A health examination, including measures of FM and FFM by bioelectrical impedance at baseline and follow-up 6 years later, was conducted. Diet history interviews (DHI) were performed, and 24-h urinary nitrogen collection at baseline was done. In total, 330 participants with DHI, of whom 227 had validated and complete 24-h urine collection data, were analyzed. Macronutrient energy substitution models were used. RESULTS: Mean estimated protein intake was 14.6 E% from DHI and 11.3 E% from urinary nitrogen. Estimated from DHI, FM increased 46 g per year, with every 1 E% protein substituted for fat (95% confidence interval (CI) = 13, 79; P = 0.006), and FFM increased 15 g per year (1, 30; P = 0.046). Results were similar in other substitution models. Estimated from urinary nitrogen, FM increased 53 g per year, with 1 E% protein substituted for other macronutrients (24, 81; P < 0.0005), and FFM increased 18 g per year (6, 31; P = 0.004). CONCLUSION: Within a habitual range, a greater protein intake was associated with BW gain, mostly in FM. This is in contrast to the expectations based on physiological and clinical trials, and calls for a better understanding of how habitual dietary protein influences long-term energy balance, versus how greater changes in dietary proteins may influence short-term energy balance.

Compass: a hybrid method for clinical and biobank data mining.

We describe a new method for identification of confident associations within large clinical data sets. The method is a hybrid of two existing methods; Self-Organizing Maps and Association Mining. We utilize Self-Organizing Maps as the initial step to reduce the search space, and then apply Association Mining in order to find association rules. We demonstrate that this procedure has a number of advantages compared to traditional Association Mining; it allows for handling numerical variables without a priori binning and is able to generate variable groups which act as "hotspots" for statistically significant associations. We showcase the method on infertility-related data from Danish military conscripts. The clinical data we analyzed contained both categorical type questionnaire data and continuous variables generated from biological measurements, including missing values. From this data set, we successfully generated a number of interesting association rules, which relate an observation with a specific consequence and the p-value for that finding. Additionally, we demonstrate that the method can be used on non-clinical data containing chemical-disease associations in order to find associations between different phenotypes, such as prostate cancer and breast cancer.

Combined influence of leisure-time physical activity and hip circumference on all-cause mortality.

UNLABELLED: Hip circumference has been shown to be inversely associated with mortality. Muscle atrophy in the gluteofemoral region may be a possible explanation and thus physical activity is likely to play an important role. OBJECTIVE: To estimate the combined effects of hip circumference and physical activity on mortality. DESIGN AND METHODS: From the Copenhagen City Heart Study, 3,358 men and 4,350 women aged 21 to 93 years without pre-existing diagnosis of diabetes, stroke, ischemic heart disease, or cancer in 1991-1994 and with complete information on the variables of interest were included in the analyses. The participants were followed to 2009 in the Danish Civil Registration System, with 1.3% loss to follow-up and 2,513 deaths. Hazard ratios (HR) were estimated for combinations of physical activity and hip circumference. RESULTS: Hip circumference was inversely associated with mortality irrespective of being physically active or not. However, being physically active seemed to counterbalance some of the adverse health effects of a small hip circumference; when comparing inactive to active, the excess mortality at the 25th percentile of hip circumference is 40% in men (HR = 1.40, 95% CI: 1.14-1.72) and 33% in women (HR = 1.33, CI: 1.10-1.62). These associations were observed after adjustment for waist circumference and weight change in the 6 months before the examination. CONCLUSION: Less effects of physical activity were found in individuals with greater hip circumferences. A small hip circumference appears hazardous to survival. However, being physically active may counterbalance some of the hazardous effects of a small hip circumference.

Long-term weight changes in obese young adult men and subsequent all-cause mortality.

BACKGROUND: Although the expectation is that weight gain increases mortality and weight loss among those overweight reduces mortality, results on weight gain and mortality in young adults are conflicting, and weight loss is less explored. We investigated the association between long-term weight change and all-cause mortality in a broad range of body mass index (BMI) in young men. METHODS: Among 362200 Danish draftees, examined between 1943 and 1977, all obese (BMI 31.0 kg m(-2); n=1930), and a random 1% sample of the others (n=3601) were identified at a mean age of 20 years (range: 18-25 years). All the obese and half the controls were re-examined between 4 and 40 years later (mean age 35 years). Weight changes were defined as: weight loss <-0.1 kg m(-2) per year, weight stability within ±0.1 kg m(-2) per year and weight gain >0.1 kg m(-2) per year. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox regression. RESULTS: Among the 908 obese and 1073 controls followed for 30 years after re-examination 220 and 232 died. HR of the weight stable obese was 2.32 (CI: 1.56-3.44) compared with the weight stable controls. In the obese cohort there was no association between weight loss, adjusted for initial BMI, and mortality (HR: 0.99; CI: 0.68-1.45) compared with weight stable obese. Too few controls lost weight to allow assessment of weight loss. Weight gain was associated with increased mortality in the obese (HR: 1.50; CI: 1.07-2.10) and controls (HR: 1.54; CI: 1.14-2.09) compared with weight stable obese and controls, respectively. Neither the time between the two examinations, life-style factors nor exclusion of diseased individuals influenced the results. CONCLUSIONS: Although there were increased mortality of the weight-stable obese compared with controls, there was no association between weight loss and mortality in the obese. Weight gain increased mortality regardless of the initial weight.