Energy density of the Scottish diet estimated from food purchase data: relationship with socio-economic position and dietary targets

Longitudinal Association of Dietary Energy Density with Abdominal Obesity among Chinese Adults from CHNS 1993–2018

Few studies have explored the longitudinal association between dietary energy density and waist circumference and abdominal obesity in adults in China. This study aimed to analyze the relationship between dietary energy density and waist circumference and abdominal obesity in Chinese residents aged 18–64. Using data from the CHNS from 1993 to 2018, 25,817 adult residents aged 18 to 64 were selected for the study. Three consecutive 24-h dietary recalls and home-weighed seasonings were used to assess food intake. A multilevel model was used to analyze the relationship between dietary energy density and waist circumference and abdominal obesity. The results showed that compared with the lowest dietary energy density group, females had an increased risk of abdominal obesity (OR = 1.16, 95% CI: 1.05, 1.29), and females’ waist circumference increased significantly by 0.24 cm (95% CI: 0.39–1.09) in the highest dietary energy density group. No association between dietary energy density and waist circumference and abdominal obesity was observed in males. This study shows that higher dietary energy density is significantly associated with females’ waist circumference and abdominal obesity. Further research on high dietary energy density and abdominal obesity will provide scientific basis for the effective control of abdominal obesity.

Determinants of Household Food Basket Composition: A Systematic Review

Background:

Demographic, socioeconomic, and environmental determinants are important to population health status in all countries and diet is the main way that these factors could affect health. We aimed to conduct a systematic review of recent research evidence about these determinants of household food basket composition.

Methods:

The PRISMA guideline was used to the reproducibility of this systematic review. Three databases including PubMed, Scopus and Google Scholar were systematically searched from 1991 to Dec 2017.

Results:

Thirty four studies were included. Most studies were done in the United States. Three categories of determinants including the demographic, socioeconomic, and environmental define the contribution of different food groups in the household food basket. These factors determine the healthiness of family diet.

Conclusion:

Many determinants affect household food basket. Comprehensive consideration of policymakers to these factors is essential to creating and maintaining a healthy society.

Community-based cooking programme 'Eat Better Feel Better' can improve child and family eating behaviours in low socioeconomic groups

BACKGROUND

The immediate and sustained impacts of the Eat Better Feel Better cooking programme (EBFBCP) on food choices and eating behaviours in families and children were evaluated.

METHODS

The EBFBCP (6 weeks, 2 hours/week) was delivered by community-based organisations in Greater Glasgow and Clyde, Scotland. Before, after and at follow-up, parents/caregivers completed short pictorial questionnaires to report family/child eating behaviours and food literacy.

RESULTS

In total, 83 EBFBCPs were delivered and 516 participants enrolled, of which 432 were parents and caregivers. Questionnaire completion rates were 57% (n=250) for before and after and 13% (n=58) for follow-up. Most participants (80%) were female, 25-44 years old (51%) and considered socioeconomically deprived (80%). The immediate effects of the EBFBCP on eating behaviours and food literacy were families ate less takeaway/fast foods (10% reduction, p=0.019) and ready meals (15% reduction, p=0.003) and cooked more from scratch (20% increase, p<0.001). Children's consumption of discretionary food/drinks was significantly reduced after the EBFBCP for sugary drinks (10% reduction, p=0.012), savoury snacks (18%, p=0.012), biscuits (17%, p=0.007), sweets/chocolates (23%, p=0.002), fried/roasted potatoes (17%, p<0.001) and savoury pastries (11%, p<0.001). The number of fruit (15%, p=0.008) and vegetable portions (10%, p<0.001) increased, while the number of biscuit portions decreased (13%, p=0.005). Parental food label reading increased (calories, 22%; fat, 23%; sugar, 22%; ingredients, 19%; and portion size, 19%). Most changes were sustained at a median of 10 months' follow-up.

CONCLUSION

The EBFBCP improved children's and families' food choices and behaviours. The EBFBCP can be recommended to support families to make better food choices.

Dietary Energy Density in the Australian Adult Population from National Nutrition Surveys 1995 to 2012

BACKGROUND

It is hypothesized that the observed proliferation of energy-dense, nutrient-poor foods globally is an important contributing factor to the development of the obesity epidemic. However, evidence that the population's dietary energy density has increased is sparse. The World Cancer Research Fund recommends that dietary energy density be <1.25 kcal/g to prevent weight gain.

OBJECTIVE

The aim of this research was to determine whether the dietary energy density of the Australian population has changed between 1995 and 2012.

DESIGN

A secondary analysis of two cross-sectional Australian national nutrition surveys from 1995 and 2011/2012 was conducted.

PARTICIPANTS/SETTING

Participants of the surveys included adults aged 18 years and older (1995 n=10,986 and 2011/2012 n=9,435) completing 24-hour dietary recalls, including a second recall for a subset of the population (10.4% in 1995 and 64.6% in 2011/2012).

MAIN OUTCOME MEASURES

Outcome measures included the change in dietary energy density (calculated as energy/weight of food [kcal/g] for food only) between surveys.

STATISTICAL ANALYSIS

The National Cancer Institute method for "estimating ratios of two dietary components that are consumed nearly every day" was used to determine the usual distribution and the percentage of participants reporting energy density <1.25 kcal/g.

RESULTS

The mean (standard deviation) dietary energy density was 1.59 (0.26) kcal/g and 1.64 (0.32) kcal/g (P<0.0001) in 1995 and 2011/2012, respectively, with 13% and 5% (P<0.0001) of the population meeting dietary energy-density recommendations. For those aged 70 years and older, the percentage with energy density <1.25 kcal/g decreased from 22% to 6% (P<0.0001) for men and from 33% to 11% (P<0.0001) for women in 1995 and 2011/2012, respectively. Among those aged 18 to 29 years, 1% of men in both surveys (P=0.8) and 4% of women in 1995 and 2% in 2011/2012 (P=0.01) reported energy density <1.25 kcal/g.

CONCLUSIONS

Dietary energy density has increased between the two surveys and few people consumed low energy-dense diets in line with recommendations. The change was largely due to increased energy density of older adult's diets, while young adults had high dietary energy density at both time points. These data suggest efforts now focus on the evaluation of the role of modifying energy density of the diet to reduce the risk of weight gain in adults.

A comparison of dietary estimates from the National Aboriginal and Torres Strait Islander Health Survey to food and beverage purchase data

OBJECTIVE

We compared self-reported dietary intake from the very remote sample of the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (VR-NATSINPAS; n=1,363) to one year of food and beverage purchases from 20 very remote Indigenous Australian communities (servicing ∼8,500 individuals).

METHODS

Differences in food (% energy from food groups) and nutrients were analysed using t-test with unequal variance.

RESULTS

Per-capita energy estimates were not significantly different between the surveys (899 MJ/person/day [95% confidence interval -152,1950] p=0.094). Self-reported intakes of sugar, cereal products/dishes, beverages, fats/oils, milk products/dishes and confectionery were significantly lower than that purchased, while intakes of meat, vegetables, cereal-based dishes, fish, fruit and eggs were significantly higher (p<0.05).

CONCLUSION

Differences between methods are consistent with differential reporting bias seen in self-reported dietary data. Implications for public health: The NATSINPAS provides valuable, much-needed information about dietary intake; however, self-reported data is prone to energy under-reporting and reporting bias. Purchase data can be used to track population-level food and nutrient availability in this population longitudinally; however, further evidence is needed on approaches to estimate wastage and foods sourced outside the store. There is potential for these data to complement each other to inform nutrition policies and programs in this population.

Social Determinants and Poor Diet Quality of Energy-Dense Diets of Australian Young Adults

This research aimed to determine the diet quality and socio-demographic determinants by level of energy-density of diets of Australian young adults. Secondary analysis of the Australian National Nutrition and Physical Activity Survey-2011/2012 for adults aged 18–34 years (n = 2397) was conducted. Diet was assessed by 24-h recalls. Dietary energy-density was calculated as dietary energy/grams of food (kJ/g) and the Healthy-Eating-Index-for-Australians (HEIFA-2013) was used to assess diet quality (highest score = 100). Dietary energy-density was examined with respect to diet quality and sociodemographic determinants including gender, highest tertiary-education attainment, country-of-birth, age, income, and socio-economic-index-for-area (SEIFA). Higher dietary energy-density was associated with lower diet quality scores (β = −3.71, t (2394) = −29.29, p < 0.0001) and included fewer fruits and vegetables, and more discretionary foods. The mean dietary energy-density was 7.7 kJ/g and 7.2 kJ/g for men and women, respectively. Subpopulations most at risk of consuming high energy-dense diets included those with lower education, Australian and English-speaking countries of birth, and men with low income and women from areas of lower socio-economic status. Young adults reporting low energy-dense diets had higher quality diets. Intensive efforts are needed to reduce the high energy-density of young adults’ diets, and should ensure they include populations of lower socio-economic status.

Evaluation of the "Eat Better Feel Better" Cooking Programme to Tackle Barriers to Healthy Eating

We evaluated a 6-week community-based cooking programme, “Eat Better Feel Better”, aimed at tackling barriers to cooking and healthy eating using a single-group repeated measures design. 117 participants enrolled, 62 completed baseline and post-intervention questionnaires, and 17 completed these and a 3–4 months follow-up questionnaire. Most participants were female, >45 years, and socioeconomically deprived. Confidence constructs changed positively from baseline to post-intervention (medians, scale 1 “not confident” to 7 “very confident”): “cooking using raw ingredients” (4, 6 p < 0.003), “following simple recipe” (5, 6 p = 0.003), “planning meals before shopping” (4, 5 p = <0.001), “shopping on a budget (4, 5 p = 0.044), “shopping healthier food” (4, 5 p = 0.007), “cooking new foods” (3, 5 p < 0.001), “cooking healthier foods” (4, 5 p = 0.001), “storing foods safely” (5, 6 p = 0.002); “using leftovers” (4, 5 p = 0.002), “cooking raw chicken” (5, 6 p = 0.021), and “reading food labels” (4, 5 p < 0.001). “Microwaving ready-meals” decreased 46% to 39% (p = 0.132). “Preparing meals from scratch” increased 48% to 59% (p = 0.071). Knowledge about correct portion sizes increased 47% to 74% (p = 0.002). Spending on ready-meals/week decreased. Follow-up telephone interviewees (n = 42) reported developing healthier eating patterns, spending less money/wasting less food, and preparing more meals/snacks from raw ingredients. The programme had positive effects on participants’ cooking skills confidence, helped manage time, and reduced barriers of cost, waste, and knowledge.

Comparing Prices for Food and Diet Research: The Metric Matters

An important issue in research into access to healthy food is how best to compare the price of foods. The appropriate metric for comparison has been debated at length, with proponents variously stating that food prices should be compared in terms of their energy content, their edible mass, or their typical portion size. In this article we assessed the impact of using different food price metrics on the observed difference in price between food groups and categories of healthiness, using United Kingdom consumer price index data for 148 foods and beverages in 2012. We found that the choice of metric had a marked effect on the findings and conclude that this must be decided in advance to suit the reason for comparing food prices.

Estimating population food and nutrient exposure: a comparison of store survey data with household panel food purchases

Population exposure to food and nutrients can be estimated from household food purchases, but store surveys of foods and their composition are more available, less costly and might provide similar information. Our aim was to compare estimates of nutrient exposure from a store survey of packaged food with those from household panel food purchases. A cross-sectional store survey of all packaged foods for sale in two major supermarkets was undertaken in Auckland, New Zealand, between February and May 2012. Longitudinal household food purchase data (November 2011 to October 2012) were obtained from the nationally representative, population-weighted New Zealand Nielsen HomeScan® panel. Data on 8440 packaged food and non-alcoholic beverage products were collected in the store survey. Food purchase data were available for 1229 households and 16 812 products. Store survey data alone produced higher estimates of exposure to Na and sugar compared with estimates from household panel food purchases. The estimated mean difference in exposure to Na was 94 (95 % CI 72, 115) mg/100 g (20 % relative difference; P<0·01), to sugar 1·6 (95 % CI 0·8, 2·5) g/100 g (11 %; P<0·01), to SFA −0·3 (95 % CI −0·8, 0·3) g/100 g (6 %; P=0·3) and to energy −18 (−71, 35) kJ/100 g (2 %; P=0·51). Compared with household panel food purchases, store survey data provided a reasonable estimate of average population exposure to key nutrients from packaged foods. However, caution should be exercised in using such data to estimate population exposure to Na and sugar and in generalising these findings to other countries, as well as over time.