Studies have consistently found that obesity is associated with poor self-rated health, but how body mass index (BMI) developed in the lead up to poor self-rated health is unknown.
We nested a ...longitudinal case-control study in the English Longitudinal Study of Ageing (1998-2015) to investigate BMI trajectories in the years preceding a first self-report of poor health. Participants rated their health at each data collection; every other collection included a BMI assessment by a nurse. Case status was defined as a first report of poor health during follow-up. Three age- and sex-matched controls were identified per case using density sampling. BMI trajectories were fitted to time backwards prior to first report of poor health using mixed-effects models. Age and sex were potential modifiers. We conducted subgroup analyses of those not reporting certain chronic diseases or smoking.
We identified 732 cases and 2195 controls. Age, but not sex, modified the association between BMI and self-rated health. Participants reporting poor health at age 60 had a 1.5 kg/m2 (95%CI: 0.8 to 2.1) higher BMI at the time of reporting than controls, and their BMI had previously increased markedly (1.3 kg/m2 95%CI: 0.9 to 1.8 over ten years). After age 75, cases no longer had higher BMI than controls, and their BMI had decreased sharply prior to reporting poor health (e.g. -2.0 kg/m2 95%CI: -2.6 to -1.5 per decade on average for those reporting poor health at age 90). Age was also an effect modifier among those without diabetes, however BMI trajectories were more similar among the middle-aged. The subgroup analysis of those without cardiovascular disease, cancer and chronic lung disease showed similar results to the main findings.
Development of BMI was associated with poor self-rated health; however, the nature of the association depended markedly on age.
Food substitutions revisited Ibsen, Daniel B; Dahm, Christina C
The American journal of clinical nutrition,
11/2022, Volume:
116, Issue:
5
Journal Article
We investigated the association between adherence to the EAT-Lancet diet, a sustainable and mostly plant-based diet, and risk of stroke and subtypes of stroke in a Danish population. For comparison, ...we also investigated the Alternate Healthy Eating Index-2010 (AHEI).
We used the Danish Diet, Cancer and Health cohort (n=55 016) including adults aged 50 to 64 years at baseline (1993-1997). A food frequency questionnaire was used to assess dietary intake and group participants according to adherence to the diets. Stroke cases were identified using a national registry and subsequently validated by review of medical records (n=2253). Cox proportional hazards models were used to estimate hazard ratios and 95% CIs for associations with the EAT-Lancet diet or the AHEI and risk of stroke and stroke subtypes.
Adherence to the EAT-Lancet diet was associated with a lower risk of stroke, although not statistically significant (highest versus lowest adherence: hazard ratio, 0.91 95% CI, 0.76-1.09). A lower risk was observed for AHEI (0.75 95% CI, 0.64-0.87). For stroke subtypes, we found that adherence to the EAT-Lancet diet was associated with a lower risk of subarachnoid hemorrhage (0.30 95% CI, 0.12-0.73), and the AHEI was associated with a lower risk of ischemic stroke (0.76 95% CI, 0.64-0.90) and intracerebral hemorrhage (0.58 95% CI, 0.36-0.93).
Adherence to the EAT-Lancet diet in midlife was associated with a lower risk of subarachnoid stroke, and the AHEI was associated with a lower risk of total stroke, mainly ischemic stroke and intracerebral hemorrhage.
General obesity is a recognized risk factor for various metabolically related diseases, including hypertension, dyslipidemia, and pre-diabetes. In epidemiological studies, anthropometric variables ...such as height and weight are often self-reported. However, misreporting of self-reported data may bias estimates of associations between anthropometry and health outcomes. Further, few validation studies have compared self-reported and measured waist circumference (WC). This study aimed to quantify the agreement between self-reported and measured height, weight, body mass index (BMI), WC, and waist-to-height ratio (WHtR), and to investigate associations of these anthropometric measures with cardiometabolic biomarkers. A total of 39,514 participants aged above 18 years were included into the Diet, Cancer, and Health-Next Generation Cohort in 2015-19. Self-reported and measured anthropometric variables, blood pressure, and cardiometabolic biomarkers (HbA1c, lipid profiles, C-reactive protein and creatinine) were collected by standard procedures. Pearson correlations (r) and Lin's concordance correlations were applied to evaluate misreporting. Misreporting by age, sex and smoking status was investigated in linear regression models. Multivariable regression models and Receiver Operating Characteristic analyses assessed associations of self-reported and measured anthropometry with cardiometabolic biomarkers. Self-reported height was overreported by 1.07 cm, and weight was underreported by 0.32 kg on average. Self-reported BMI and WC were 0.42 kg/m2 and 0.2 cm lower than measured, respectively. Self-reported and measured height, weight, BMI, WC and WtHR were strongly correlated (r = 0.98, 0.99, 0.98, 0.88, 0.86, respectively). Age, sex, smoking, and BMI contributed to misreporting of all anthropometric measures. Associations between self-reported or measured anthropometric measures and cardiometabolic biomarkers were similar in direction and strength. Concordance between self-reported and measured anthropometric measures, including WC, was very high. Self-reported anthropometric measures were reliable when estimating associations with cardiometabolic biomarkers.
The advantage of using specified substitution analysis in nutritional epidemiology has been clearly demonstrated in studies of macronutrient intake and disease risk. However, the method has not been ...widely applied in studies of food intake. The aim of this article is to describe and compare the interpretation and application of different food substitution models in epidemiologic studies on diet and disease development. Both theoretically and in the context of a specific example, we discuss methodologic issues to be considered, including modeling of food substitutions using diet at a single time point or at multiple time points (focusing on dietary changes), choice of substitution unit, adjustment for total energy intake, and adjustment for confounding. We argue that specified food substitution analyses can be used to identify optimal food composition of the diet and that these analyses are thus highly relevant to inform public health policy decision makers.
Primary liver cancer is globally on the rise, partially due to poor diets and sedentary lifestyles. Shifting to more plant-based diets may lower the risk. We aimed to estimate the effect of replacing ...total red meat, unprocessed red meat and processed red meat with legumes on primary liver cancer in a free-living population. We analyzed data from 126,744 UK Biobank participants who completed ≥ two 24 h diet recalls. Baseline characteristics were collected from the initial assessment visit. Information on liver cancer diagnoses was collected via external linkage to inpatient hospital episodes or central cancer registries. Cox proportional hazards regression models were used to estimate the substitution of 15 g/day of legumes with 15 g/day of total red meat, unprocessed red meat or processed red meat on liver cancer risk, using the leave-one-out food substitution model. During a median follow-up time of 11.1 years, 173 participants developed liver cancer. In the fully adjusted models, no association was observed when substituting 15 g/day of legumes with total red meat (HR: 1.02 (95% CI 0.96–1.08)), unprocessed red meat (HR: 1.00 (95% CI 0.94–1.06)) or processed red meat (HR: 1.09 (95% CI 0.99–1.21)). Overall, little evidence of an association between replacing red meat with legumes and liver cancer was observed. Further research in other study populations with longer follow-up time is warranted.
Infant feeding practices have been hypothesized to influence offspring's body mass index (BMI) later in life, and women with overweight or obesity tend to wean their infants earlier than women with ...healthy BMI. We, therefore, aimed to investigate how much early age of weaning mediated the maternal-offspring adiposity relationship. The study included 4920 mother-child pairs from the Avon Longitudinal Study of Parents and Children birth cohort. G-computation was applied to estimate the natural direct (NDE) and indirect (NIE) effects, via the age of weaning (<3 months, 3 months, >3 months), of maternal pre-pregnancy overweight or obesity on offspring's BMI and fat mass index. The NDE of maternal overweight or obesity on offspring BMI at 17 years old was 2.63 kg/m
(95% CI: 2.27 to 2.99). The NIE via the age of weaning was 0.02 kg/m
(95% CI: 0.00 to 0.04), corresponding to 0.8% of the total effect. Similar results were observed for the offspring's fat mass index. The NDE and NIE were similar to the main analyses when we looked at the relationship stratified by breastfeeding status. Our study found a minimal influence of age of weaning on the pathway between maternal and offspring adiposity, indicating the age of weaning may not be a key mediator.
Background and Purpose- Studies indicate that consuming breakfast every day, and particularly oatmeal, is associated with lower risk of stroke. However, few studies have considered replacement foods ...when considering foods usually consumed at breakfast. We, therefore, aimed to model substitutions between the breakfast food products oatmeal, eggs, yogurt, or white bread and subsequent risk of stroke. Methods- Participants from the Danish cohort study (Diet, Cancer and Health; n=55 095) were followed for 13.4 years, during which 2260 subjects experienced a first-ever stroke. Breakfast foods were assessed using a validated 192-item food-frequency questionnaire at baseline. Cox proportional hazards models were used to estimate adjusted hazard ratios and 95% CIs for associations between hypothetical substitutions of standard portion sizes of breakfast foods and stroke. Results- Modeling replacement of white bread or eggs with oatmeal was associated with a lower rate of total stroke (hazard ratio HR=0.96 95% CI, 0.95-0.98; HR=0.96 95% CI, 0.93-0.98, respectively), total ischemic stroke (HR=0.96 95% CI, 0.94-0.98; HR=0.96 95% CI, 0.94-0.99, respectively), and ischemic stroke due to small-artery occlusion (HR=0.95 95% CI, 0.93-0.98; HR=0.95 95% CI, 0.91-0.99, respectively). Furthermore, modeling replacement of eggs with oatmeal was associated with a lower rate of total hemorrhagic stroke (HR=0.94 95% CI, 0.89-0.99). Modeling replacement of yogurt with oatmeal was not associated with stroke. Conclusions- Our findings suggest that a diet containing oatmeal instead of white bread or eggs may be associated with a lower rate of stroke.
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