Takeaway food consumption and its associations with diet quality and abdominal obesity: a cross-sectional study of young adults

Background : Few studies have investigated the associations of takeaway food consumption with overall diet quality and abdominal obesity. Young adults are high consumers of takeaway food so we aimed to examine these associations in a national study of young Australian adults.Methods : A national sample of 1,277 men and 1,585 women aged 26&ndash;36 completed a self-administered questionnaire on demographic and lifestyle factors, a 127 item food frequency questionnaire, usual daily frequency of fruit and vegetable consumption and usual weekly frequency of takeaway food consumption. Dietary intake was compared with the dietary recommendations from the Australian Guide to Healthy Eating. Waist circumference was measured for 1,065 men and 1,129 women. Moderate abdominal obesity was defined as &ge; 94 cm for men and &ge; 80 cm for women. Prevalence ratios (PR) were calculated using log binomial regression. Takeaway food consumption was dichotomised, with once a week or less as the reference group.Results : Consumption of takeaway food twice a week or more was reported by more men (37.9%) than women (17.7%, P &lt; 0.001). Compared with those eating takeaway once a week or less, men eating takeaway twice a week or more were significantly more likely to be single, younger, current smokers and spend more time watching TV and sitting, whereas women were more likely to be in the workforce and spend more time watching TV and sitting. Participants eating takeaway food at least twice a week were less likely (P &lt; 0.05) to meet the dietary recommendation for vegetables, fruit, dairy, extra foods, breads and cereals (men only), lean meat and alternatives (women only) and overall met significantly fewer dietary recommendations (P &lt; 0.001). After adjusting for confounding variables (age, leisure time physical activity, TV viewing and employment status), consuming takeaway food twice a week or more was associated with a 31% higher prevalence of moderate abdominal obesity in men (PR: 1.31; 95% CI: 1.07, 1.61) and a 25% higher prevalence in women (PR: 1.25; 95% CI: 1.04, 1.50).Conclusion : Eating takeaway food twice a week or more was associated with poorer diet quality and a higher prevalence of moderate abdominal obesity in young men and women.<br /

Five-Year Change in Body Mass Index Predicts Conversion to Mild Cognitive Impairment or Dementia Only in APOE ɛ4 Allele Carriers

Background: Body mass index (BMI) has been identified as an important modifiable lifestyle risk factor for dementia, but less is known about how BMI might interact with Apolipoprotein E ɛ4 (APOE ɛ4) carrier status to predict conversion to mild cognitive impairment (MCI) and dementia. Objective: The aim of this study was to investigate the interaction between APOE ɛ4 status and baseline (bBMI) and five-year BMI change (ΔBMI) on conversion to MCI or dementia in initially cognitively healthy older adults. Methods: The associations between bBMI, ΔBMI, APOE ɛ4 status, and conversion to MCI or dementia were investigated among 1,289 cognitively healthy elders from the National Alzheimer’s Coordinating Center (NACC) database. Results: After five years, significantly more carriers (30.6%) converted to MCI or dementia than noncarriers (17.6%), p \u3c 0.001, OR = 2.06. Neither bBMI (OR = 0.99, 95%CI = 0.96–1.02) nor the bBMI by APOE interaction (OR = 1.02, 95%CI = 0.96–1.08) predicted conversion. Although ΔBMI also did not significantly predict conversion (OR = 0.90, 95%CI = 0.78–1.04), the interaction between ΔBMI and carrier status was significant (OR = 0.72, 95%CI = 0.53–0.98). For carriers only, each one-unit decline in BMI over five years was associated with a 27%increase in the odds of conversion (OR = 0.73, 95%CI = 0.57–0.94). Conclusion: A decline in BMI over five years, but not bBMI, was strongly associated with conversion to MCI or dementia only for APOE ɛ4 carriers. Interventions and behaviors aimed at maintaining body mass may be important for long term cognitive health in older adults at genetic risk for AD

Which aspects of socio-economic status are related to health in mid-aged and older women?

A population-based study was conducted to validate gender- and age-specific indexes of socio-economic status (SES) and to investigate the associations between these indexes and a range of health outcomes in 2 age cohorts of women. Data from 11,637 women aged 45 to 50 and 9,510 women aged 70 to 75 were analyzed. Confirmatory factor analysis produced four domains of SES among the mid-aged cohort (employment, family unit, education, and migration) and four domains among the older cohort (family unit, income, education, and migration). Overall, the results supported the factor structures derived from another population-based study (Australian Bureau of Statistics, 1995), reinforcing the argument that SES domains differ across age groups. In general, the findings also supported the hypotheses that women with low SES would have poorer health outcomes than higher SES women, and that the magnitude of these effects would differ according to the specific SES domain and by age group, with fewer and smaller differences observed among older women. The main exception was that in the older cohort, the education domain was significantly associated with specific health conditions. Results suggest that relations between SES and health are highly complex and vary by age, SES domain, and the health outcome under study.<br /

Cross-Sectional Associations between Dietary Fat-Related Behaviors and Continuous Metabolic Syndrome Score among Young Australian Adults

Dietary guidelines recommend removing visible fat from meat, choosing low-fat options and cooking with oil instead of butter. This study examined cross-sectional associations between fat-related eating behaviors and a continuous metabolic syndrome (cMetSyn) score among young adults. During 2004-2006, 2071 participants aged 26-36 years reported how often they trimmed fat from meat, consumed low-fat dairy products and used different types of fat for cooking. A fasting blood sample was collected. Blood pressure, weight and height were measured. To create the cMetSyn score, sex-specific principal component analysis was applied to normalized risk factors of the harmonized definition of metabolic syndrome. Higher score indicates higher risk. For each behavior, differences in mean cMetSyn score were calculated using linear regression adjusted for confounders. Analyses were stratified by weight status (Body mass index (BMI) < 25 kg/m(2) or 25 kg/m(2)). Mean cMetSyn score was positively associated with consumption of low-fat oily dressing (P-Trend = 0.013) among participants who were healthy weight and frequency of using canola/sunflower oil for cooking (P-Trend = 0.008) among participants who were overweight/obese. Trimming fat from meat, cooking with olive oil, cooking with butter, and consuming low-fat dairy products were not associated with cMetSyn score. Among young adults, following fat-related dietary recommendations tended to not be associated with metabolic risk

Associations between partnering and parenting transitions and dietary habits in young adults

Background Partnering and parenting are important life-stage transitions that often occur during young adulthood. Little is known about how these transitions affect two dietary behaviors linked to increased cardiometabolic disease risk: skipping breakfast and takeaway-food consumption. Objective Our aim was to examine whether partnering and parenting transitions during a 5-year period were associated with change in diet quality, skipping breakfast, and takeaway-food consumption. Design We conducted a cohort study. Questionnaires were completed at baseline (2004 to 2006) and follow-up (2009 to 2011). Marital status and number of children were self-reported. Participants/setting Australian participants (n=1,402 [39% men]) aged 26 to 36 years were included. Main outcomes measures Diet quality was assessed using a Dietary Guideline Index. Breakfast skipping (not eating before 9 am the previous day) and frequent takeaway-food consumption (≥2 times/week) were reported. Statistical analysis Linear regression (mean differences in Dietary Guideline Index) and log binomial regression (relative risks for skipping breakfast and frequent takeaway-food consumption) were adjusted for age, education, follow-up duration, day of the week (skipping breakfast only), the other transition, and baseline behavior. Results During the 5-year follow-up, 101 men and 93 women became married/living as married, and 149 men and 155 women had their first child. Diet quality improved among all groups and was similar at follow-up between those who experienced the transitions and those who did not. Compared to having no children, having a first child was associated with a lower risk of skipping breakfast for men (relative risk 0.65; 95% CI 0.42 to 1.01) and women (relative risk 0.47; 95% CI 0.31 to 0.72). Men who became partnered also had a lower risk of skipping breakfast than those who remained single (relative risk 0.64; 95% CI 0.42 to 0.98). The transitions were not significantly associated with takeaway-food consumption. Conclusions Life-stage transitions were not associated with better diet quality. Participants who became partnered or parents were more likely to eat breakfast at follow-up than those who remained single or had no children

Viral Networks: Connecting Digital Humanities and Medical History

This volume of original essays explores the power of network thinking and analysis for humanities research. Contributing authors are all scholars whose research focuses on a medical history topic—from the Black Death in fourteenth-century Provence to psychiatric hospitals in twentieth-century Alabama. The chapters take readers through a variety of situations in which scholars must determine if network analysis is right for their research; and, if the answer is yes, what the possibilities are for implementation. Along the way, readers will find practical tips on identifying an appropriate network to analyze, finding the best way to apply network analysis, and choosing the right tools for data visualization. All the chapters in this volume grew out of the 2018 Viral Networks workshop, hosted by the History of Medicine Division of the National Library of Medicine (NIH), funded by the Office of Digital Humanities of the National Endowment for the Humanities, and organized by Virginia Tech

The metabolomic signatures of alcohol consumption in young adults

BackgroundMetabolomic analysis may help us to understand the association between alcohol consumption and cardio-metabolic health. We aimed to: (i) replicate a previous study of alcohol consumption and metabolic profiles, (ii) examine associations between types of alcoholic beverages and metabolites and (iii) include potential confounders not examined in previous studies.MethodsCross-sectional data of 1785 participants (age 26–36 years, 52% women) from the 2004–2006 Childhood Determinants of Adult Health study were used. Consumption of beer, wine and spirits was assessed by questionnaires. Metabolites were measured by a high-throughput nuclear magnetic resonance platform and multivariable linear regression examined their association with alcohol consumption (combined total and types) adjusted for covariates including socio-demographics, health behaviours and mental health.ResultsAlcohol consumption was associated with 23 out of 37 lipids, 12 out of 16 fatty acids and six out of 20 low-molecular-weight metabolites independent of confounders with similar associations for combined total alcohol consumption and different types of alcohol. Many metabolites (lipoprotein lipids in high-density lipoprotein (HDL) subclasses, HDL cholesterol, apolipoprotein A-1, phosphotriglycerides, total fatty acids, monounsaturated fatty acids, omega-3 fatty acids) had positive linear associations with alcohol consumption but some showed negative linear (low-density lipoprotein particle size, omega-6 fatty acids ratio to total fatty acids, citrate) or U-shaped (lipoprotein lipids in very-low-density lipoprotein (VLDL) subclasses, VLDL triglycerides) associations.ConclusionsOur results were similar to those of the only previous study. Associations with metabolites were similar for total and types of alcohol. Alcohol consumption in young adults is related to a diverse range of metabolomic signatures associated with benefits and harms to health.</p

Retrospectively Estimating Energy Intake and Misreporting From a Qualitative Food Frequency Questionnaire: An Example Using Australian Cohort and National Survey Data

Qualitative food frequency questionnaires (Q-FFQ) omit portion size information from dietary assessment. This restricts researchers to consumption frequency data, limiting investigations of dietary composition (i.e., energy-adjusted intakes) and misreporting. To support such researchers, we provide an instructive example of Q-FFQ energy intake estimation that derives typical portion size information from a reference survey population and evaluates misreporting. A sample of 1,919 Childhood Determinants of Adult Health Study (CDAH) participants aged 26-36 years completed a 127-item Q-FFQ. We assumed sex-specific portion sizes for Q-FFQ items using 24-h dietary recall data from the 2011-2012 Australian National Nutrition and Physical Activity Survey (NNPAS) and compiled energy density values primarily using the Australian Food Composition Database. Total energy intake estimation was daily equivalent frequency x portion size (g) x energy density (kJ/g) for each Q-FFQ item, summed. We benchmarked energy intake estimates against a weighted sample of age-matched NNPAS respondents (n = 1,383). Median (interquartile range) energy intake was 9,400 (7,580-11,969) kJ/day in CDAH and 9,055 (6,916-11,825) kJ/day in weighted NNPAS. Median energy intake to basal metabolic rate ratios were 1.43 (1.15-1.78) in CDAH and 1.35 (1.03-1.74) in weighted NNPAS, indicating notable underreporting in both samples, with increased levels of underreporting among the overweight and obese. Using the Goldberg and predicted total energy expenditure methods for classifying misreporting, 65 and 41% of CDAH participants had acceptable/plausible energy intake estimates, respectively. Excluding suspected CDAH misreporters improved the plausibility of energy intake estimates, concordant with expected body weight associations. This process can assist researchers wanting an estimate of energy intake from a Q-FFQ and to evaluate misreporting, broadening the scope of diet-disease investigations that depend on consumption frequency data

An age- and sex-specific dietary guidelines index is a valid measure of diet quality in an Australian cohort during youth and adulthood

Measuring diet quality over time is important due to health impacts, but to our knowledge, a Dietary Guidelines Index (DGI) with consistent scoring across childhood/adolescence (youth) and adulthood has not been validated. We hypothesized that a DGI that reflected age- and sex-specific guidelines would be a valid measure of diet quality in youth and adulthood. The DGI is based on the 2013 Australian Dietary Guidelines to reflect current understanding of diet quality and comprises 9 indicators, with a maximum score of 100 points. DGI scores were calculated for participants of the Australian Childhood Determinants of Adult Health study, which included a 24-hour food record during youth (1985, n = 5043, age: 10-15 years) and a 127-item food frequency questionnaire during adulthood (2004-2006, n = 2689, age: 26-36 years). We evaluated construct validity (distribution of scores, principal components analysis, correlation with nutrient density of intakes) and criterion validity (linear regression with population characteristics). DGI scores were multidimensional in underlying structure and normally distributed. Among youth, a lower DGI was significantly associated (P < .05) with smoking and with lower academic achievement and socioeconomic status. DGI scores were negatively correlated with energy, sugar, and fat and positively correlated with fiber, protein, and micronutrients. Among adults, a lower DGI was associated with lower education and self-reported health and higher waist circumference, insulin resistance, and total and low-density lipoprotein serum cholesterol. The DGI is an appropriate measure of diet quality in youth and adulthood because higher scores reflect nutrient-dense, rather than energy-dense, intake and discriminate between population characteristics consistent with the literature. (C) 2019 Elsevier Inc. All rights reserved

Childhood socioeconomic status and lifetime health behaviors : The Young Finns Study

Background: Differences in health behaviors partly explain the socioeconomic gap in cardiovascular health. We prospectively examined the association between childhood socioeconomic status (SES) and lifestyle factors in adulthood, and the difference of lifestyle factors according to childhood SES in multiple time points from childhood to adulthood. Methods and results: The sample comprised 3453 participants aged 3-18 years at baseline (1980) from the longitudinal Young Finns Study. The participants were followed up for 31 years (N = 1675-1930). SES in childhood was characterized as reported annual family income and classified on an 8-point scale. Diet, smoking, alcohol intake and physical activity were used as adult and life course lifestyle factors. Higher childhood SES predicted a healthier diet in adulthood in terms of lower consumption of meat (beta +/- SE -3.6 +/- 0.99, p <0.001), higher consumption of fish (1.1 +/- 0.5, p = 0.04) and higher diet score (0.14 +/- 0.044, p = 0.01). Childhood SES was also directly associated with physical activity index (0.059 +/- 0.023, p = 0.009) and inversely with the risk of being a smoker (RR 0.90 95%CI 0.85-0.95, p <0.001) and the amount of pack years (-0.47 +/- 0.18, p = 0.01). Life course level of smoking was significantly higher and physical activity index lower among those below the median childhood SES when compared with those above the median SES. Conclusions: These results show that childhood SES associates with several lifestyle factors 31 years later in adulthood. Therefore, attention could be paid to lifestyle behaviors of children of low SES families to promote cardiovascular health. (C) 2017 Elsevier B.V. All rights reserved.Peer reviewe