Diet quality as a predictor of cardiometabolic disease-free life expectancy: the Whitehall II cohort study

Background: Poor diet quality has been linked to increased risk of many chronic diseases and premature mortality. Less research has considered dietary habits in relation to disease-free life expectancy. Objectives: Our objective was to investigate the association of diet quality with cardiometabolic disease–free life expectancy between ages 50 and 85 y. Methods: Diet quality of 8041 participants of the Whitehall II cohort study was assessed with the Alternative Healthy Eating Index 2010 (AHEI-2010) in 1991–1994, 1997–1999, and 2002–2004. The measurement of diet quality closest to age 50 for each participant was used. We utilized repeat measures of cardiometabolic disease (coronary heart disease, stroke, and type 2 diabetes) from the first observation when participants were aged ≥50 y. Multistate life table models with covariates age, gender, occupational position, smoking, physical activity, and alcohol consumption were used to estimate total and sex-specific cardiometabolic disease–free life expectancy from age 50 to 85 y for each AHEI-2010 quintile, where the lowest quintile represents unhealthiest dietary habits and the highest quintile the healthiest habits. Results: The number of cardiometabolic disease–free life-years after age 50 was 23.9 y (95% CI: 23.0, 24.9 y) for participants with the healthiest diet, that is, a higher score on the AHEI-2010, and 21.4 y (95% CI: 20.6, 22.3 y) for participants with the unhealthiest diet. The association between diet quality and cardiometabolic disease–free life expectancy followed a dose–response pattern and was observed in subgroups of participants of different occupational position, BMI, physical activity level, and smoking habit, as well as when participants without cardiometabolic disease at baseline were excluded from analyses. Conclusions: Healthier dietary habits are associated with cardiometabolic disease–free life expectancy between ages 50 and 85

Diet quality as a predictor of cardiometabolic disease-free life expectancy: the Whitehall II cohort study

Background: Poor diet quality has been linked to increased risk of many chronic diseases and premature mortality. Less research has considered dietary habits in relation to disease-free life expectancy.Objectives: Our objective was to investigate the association of diet quality with cardiometabolic disease-free life expectancy between ages 50 and 85 y.Methods: Diet quality of 8041 participants of the Whitehall II cohort study was assessed with the Alternative Healthy Eating Index 2010 (AHEI-2010) in 1991-1994, 1997-1999, and 2002-2004. The measurement of diet quality closest to age 50 for each participant was used. We utilized repeat measures of cardiometabolic disease (coronary heart disease, stroke, and type 2 diabetes) from the first observation when participants were aged >= 50 y. Multistate life table models with covariates age, gender, occupational position, smoking, physical activity, and alcohol consumption were used to estimate total and sex-specific cardiometabolic disease-free life expectancy from age 50 to 85 y for each AHEI-2010 quintile, where the lowest quintile represents unhealthiest dietary habits and the highest quintile the healthiest habits.Results: The number of cardiometabolic disease-free life-years after age 50 was 23.9 y (95% CI: 23.0, 24.9 y) for participants with the healthiest diet, that is, a higher score on the AHEI-2010, and 21.4 y (95% CI: 20.6, 22.3 y) for participants with the unhealthiest diet. The association between diet quality and cardiometabolic disease-free life expectancy followed a dose-response pattern and was observed in subgroups of participants of different occupational position, BMI, physical activity level, and smoking habit, as well as when participants without cardiometabolic disease at baseline were excluded from analyses.Conclusions: Healthier dietary habits are associated with cardiometabolic disease-free life expectancy between ages 50 and 85

School meal provision, health, and cognitive function in a Nordic setting – the ProMeal-study: description of methodology and the Nordic context

BACKGROUND: School meals, if both nutritious and attractive, provide a unique opportunity to improve health equality and public health.OBJECTIVE: To describe the study rationale, data collection, and background of participants in the study 'Prospects for promoting health and performance by school meals in Nordic countries' (ProMeal). The general aim was to determine whether overall healthiness of the diet and learning conditions in children can be improved by school lunches, and to capture the main concerns regarding school lunches among children in a Nordic context.DESIGN: A cross-sectional, multidisciplinary study was performed in Finland, Iceland, Norway, and Sweden on pupils (n=837) born in 2003.RESULTS: In total 3,928 pictures of school lunches were taken to capture pupils' school lunch intake. A mean of 85% of all parents responded to a questionnaire about socioeconomic background, dietary intake, and habitual physical activity at home. Cognitive function was measured on one occasion on 93% of the pupils during optimal conditions with a Stroop and a Child Operation Span test. A mean of 169 pupils also did an Integrated Visual and Auditory Continuous Performance Test after lunch over 3 days. In total, 37,413 10-sec observations of classroom learning behavior were performed. In addition, 753 empathy-based stories were written and 78 focus groups were conducted. The pupils had high socioeconomic status.CONCLUSIONS: This study will give new insights into which future interventions are needed to improve pupils' school lunch intake and learning. The study will provide valuable information for policy making, not least in countries where the history of school meals is shorter than in some of the Nordic countries.</div

The Finnish psychiatric birth cohort consortium (PSYCOHORTS) - content, plans and perspectives

Background: Psychiatric disorders tend to be developmental, and longitudinal settings are required to examine predictors of psychiatric phenomena. Replicating and combining data and results from different birth cohorts, which are a source of reliable data, can make research even more valuable. The Finnish Psychiatric Birth Cohort Consortium (PSYCOHORTS) project combines birth cohorts in Finland. Aim: The aim of this paper is to introduce content, plans and perspectives of the PSYCOHORTS project that brings together researchers from Finland. In addition, we illustrate an example of data harmonization using available data on causes of death. Content: PSYCOHORTS includes eight Finnish birth cohorts. The project has several plans: to harmonize different data from birth cohorts, to incorporate biobanks into psychiatric birth cohort research, to apply multigenerational perspectives, to integrate longitudinal patterns of marginalization and inequality in mental health, and to utilize data in health economics research. Data on causes of death, originally obtained from Finnish Cause of Death register, were harmonized across the six birth cohorts using SAS macro facility. Results: Harmonization of the cause of death data resulted in a total of 21,993 observations from 1965 to 2015. For example, the percentage of deaths due to suicide and the sequelae of intentional self-harm was 14% and alcohol-related diseases, including accidental poisoning by alcohol, was 13%. Conclusions: PSYCOHORTS lays the foundation for complex examinations of psychiatric disorders that is based on compatible datasets, use of biobanks and multigenerational approach to risk factors, and extensive data on marginalization and inequality

BMI Development of Normal Weight and Overweight Children in the PIAMA Study

Background: There is evidence that rapid weight gain during the first year of life is associated with overweight later in life. However, results from studies exploring other critical periods for the development of overweight are inconsistent. Objective: The objective was to investigate BMI development to assess at what ages essential differences between normal weight and overweight children occur, and to assess which age intervals the most strongly influence the risk of overweight at 8 years of age. Methods: Longitudinal weight and height data

Impact of maternal body mass index and gestational weight gain on pregnancy complications : an individual participant data meta-analysis of European, North American and Australian cohorts

Objective To assess the separate and combined associations of maternal pre-pregnancy body mass index (BMI) and gestational weight gain with the risks of pregnancy complications and their population impact. Design Individual participant data meta-analysis of 39 cohorts. Setting Europe, North America, and Oceania. Population 265 270 births. Methods Information on maternal pre-pregnancy BMI, gestational weight gain, and pregnancy complications was obtained. Multilevel binary logistic regression models were used. Main outcome measures Gestational hypertension, pre-eclampsia, gestational diabetes, preterm birth, small and large for gestational age at birth. Results Higher maternal pre-pregnancy BMI and gestational weight gain were, across their full ranges, associated with higher risks of gestational hypertensive disorders, gestational diabetes, and large for gestational age at birth. Preterm birth risk was higher at lower and higher BMI and weight gain. Compared with normal weight mothers with medium gestational weight gain, obese mothers with high gestational weight gain had the highest risk of any pregnancy complication (odds ratio 2.51, 95% CI 2.31- 2.74). We estimated that 23.9% of any pregnancy complication was attributable to maternal overweight/obesity and 31.6% of large for gestational age infants was attributable to excessive gestational weight gain. Conclusions Maternal pre-pregnancy BMI and gestational weight gain are, across their full ranges, associated with risks of pregnancy complications. Obese mothers with high gestational weight gain are at the highest risk of pregnancy complications. Promoting a healthy pre-pregnancy BMI and gestational weight gain may reduce the burden of pregnancy complications and ultimately the risk of maternal and neonatal morbidity.Peer reviewe

Gestational weight gain charts for different body mass index groups for women in Europe, North America, and Oceania

BackgroundGestational weight gain differs according to pre-pregnancy body mass index and is related to the risks of adverse maternal and child health outcomes. Gestational weight gain charts for women in different pre-pregnancy body mass index groups enable identification of women and offspring at risk for adverse health outcomes. We aimed to construct gestational weight gain reference charts for underweight, normal weight, overweight, and grades 1, 2 and 3 obese women and to compare these charts with those obtained in women with uncomplicated term pregnancies.MethodsWe used individual participant data from 218,216 pregnant women participating in 33 cohorts from Europe, North America, and Oceania. Of these women, 9065 (4.2%), 148,697 (68.1%), 42,678 (19.6%), 13,084 (6.0%), 3597 (1.6%), and 1095 (0.5%) were underweight, normal weight, overweight, and grades 1, 2, and 3 obese women, respectively. A total of 138, 517 women from 26 cohorts had pregnancies with no hypertensive or diabetic disorders and with term deliveries of appropriate for gestational age at birth infants. Gestational weight gain charts for underweight, normal weight, overweight, and grade 1, 2, and 3 obese women were derived by the Box-Cox t method using the generalized additive model for location, scale, and shape.ResultsWe observed that gestational weight gain strongly differed per maternal pre-pregnancy body mass index group. The median (interquartile range) gestational weight gain at 40weeks was 14.2kg (11.4-17.4) for underweight women, 14.5kg (11.5-17.7) for normal weight women, 13.9kg (10.1-17.9) for overweight women, and 11.2kg (7.0-15.7), 8.7kg (4.3-13.4) and 6.3kg (1.9-11.1) for grades 1, 2, and 3 obese women, respectively. The rate of weight gain was lower in the first half than in the second half of pregnancy. No differences in the patterns of weight gain were observed between cohorts or countries. Similar weight gain patterns were observed in mothers without pregnancy complications.ConclusionsGestational weight gain patterns are strongly related to pre-pregnancy body mass index. The derived charts can be used to assess gestational weight gain in etiological research and as a monitoring tool for weight gain during pregnancy in clinical practice.Peer reviewe

Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood: An individual participant data meta-analysis

Maternal obesity and excessive gestational weight gain may have persistent effects on offspring fat development. However, it remains unclear whether these effects differ by severity of obesity, and whether these effects are restricted to the extremes of maternal body mass index (BMI) and gestational weight gain. We aimed to assess the separate and combined associations of maternal BMI and gestational weight gain with the risk of overweight/obesity throughout childhood, and their population impact</p