2012 – starting with overweight and obesity

Consumption of ultra-processed foods and associated sociodemographic factors in the USA between 2007 and 2012: evidence from a nationally representative cross-sectional study

OBJECTIVES

To compare ultra-processed food consumption across sociodemographic groups and over time (2007-2008, 2009-2010, 2011-2012) in the USA.

DESIGN

Cross-sectional study.

SETTING

National Health and Nutrition Examination Survey (NHANES) 2007-2012.

PARTICIPANTS

All individuals aged ≥2 years with at least one 24-hour dietary recall were included (n=23 847).

MAIN OUTCOME MEASURES

Average dietary contribution of ultra-processed foods (expressed as a percentage of the total caloric value of the diet), obtained after classifying all food items according to extent and purpose of industrial food processing using NOVA classification.

DATA ANALYSIS

Linear regression was used to evaluate the association between sociodemographic characteristics or NHANES cycles and dietary contribution of ultra-processed foods.

RESULTS

Almost 60% of calories consumed in the period 2007-2012 came from ultra-processed foods. Consumption of ultra-processed foods decreased with age and income level, was higher for non-Hispanic whites or non-Hispanic blacks than for other race/ethnicity groups and lower for people with college than for lower levels of education, all differences being statistically significant. Overall contribution of ultra-processed foods increased significantly between NHANES cycles (nearly 1% point per cycle), the same being observed among males, adolescents and high school education-level individuals.

CONCLUSIONS

Ultra-processed food consumption in the USA in the period 2007-2012 was overall high, greater among non-Hispanic whites or non-Hispanic blacks, less educated, younger, lower-income strata and increased across time.

Use of calorie information at fast-food and chain restaurants among US adults, 2009

BACKGROUND

The aim of this study was to examine reading and use of calorie information at fast-food/chain restaurants.

METHODS

A cross-sectional analysis was conducted on a sample of 4363 US adults using the 2009 HealthStyles survey. The outcome variable was reading calorie information when available while ordering at fast-food/chain restaurants. Among those who go to fast-food/chain restaurants, we conducted multivariable logistic regression to examine associations between sociodemographic variables and reading calorie information when available. Among those who report reading calorie information when available, we assessed the proportion using calorie information.

RESULTS

Among those who reported eating at fast-food/chain restaurants, 36.4% reported reading calorie information when available. Reading calorie information was not related to race/ethnicity, income or education. Compared with men, women had higher odds [adjusted odds ratio (OR) = 1.8; 95% confidence interval (CI) = 1.5-2.1] of reading calorie information when available while those who frequented fast-food/chain restaurants ≥3 times/week (aOR = 0.6; 95% CI = 0.4-0.8) had lower odds compared with those going <4 times/month. Of those who reported reading calorie information when available, 95.4% reported using calorie information at least sometimes.

CONCLUSIONS

Almost all who read calorie information when available use the information at least sometimes. Research is needed on how calorie information is being used.

The evolution of nutrition research

"The doctor of the future will no longer treat the human frame with drugs, but will rather cure and prevent disease with nutrition". Thomas Edison's contemplation may come to fruition if the nutritional revolution continues in its current course. Two realizations have propelled the world into a new age of personalized nutrition: (i) food can provide benefits beyond its intrinsic nutrient content, and (ii) we are not all created equal in our ability to realize to these benefits. Nutrigenomics is concerned with delineating genomic propensities to respond to various nutritional stimuli and the resulting impact on individual health. This review will examine the current technologies utilized by nutrigeneticists, the available literature regarding nutrient-gene interactions, and the translation of this new awareness into public health.

Effects of a healthy food supply intervention in a military setting: positive changes in cereal, fat and sugar containing foods

BACKGROUND

In Finland, all men are liable to military service and a clear majority completes service. The increasing prevalence of obesity also among soldiers concerns conscripts' food choices. Conscripts are served nutritionally planned regular main meals but individual choices take place in free-time eating. This study assesses the effects in conscripts' eating habits in an intervention targeting the supply of healthy foods available in the military setting.

METHODS

Participants were 604 18-21-year old male conscripts of whom 242 belonged to Control Group and 362 to Intervention Group. Participants of Control Group were historical controls performing military service one year before Intervention Group. The intervention targeted selection, placement, and attractiveness of healthy foods in garrison refectories and soldier's home cafeterias, the two main food providers in the military. Dietary intake data was collected by self-administered questionnaire at three time points: before/beginning of military service (T0), 8 weeks (T1) and 6 months (T2) of military service. Outcome measures were food consumption frequencies and four dietary indexes (Cereal Index, Fruit and Vegetable Index, Fat Index and Sugar Index) developed to characterize the diet. Changes between study groups in outcome variables and in time were analysed by repeated-measures analysis of covariance.

RESULTS

Significant (p < 0.05) intervention effects and time-intervention interactions mostly in favor of Intervention Group were found. In Intervention Group, Cereal Index was significantly higher at T2 and the overall level of porridges and cereals was higher during follow-up when comparing to Control Group. Also, the overall levels of Fat Index, potato chips, soft drinks and desserts as well as sweet pastries at T1 were significantly lower in Intervention Group. At the same time, Fruit and Vegetable Index and the level of fruit and berries were lower in Intervention Group during follow-up.

CONCLUSIONS

In the military setting, healthier food choices can be promoted by intervening on the main food environments by improving the supply of healthy foods. However, impacting on conscripts' individual selection as fruit and vegetable consumption is more challenging.