The role of socio-economic status (SES) on the misreporting of food and energy intakes is not well understood with disagreement in the literature. The aim of this study was to examine the associations between low energy reporting, dietary quality and SES in a representative sample of adults. Dietary data were collected using 2 d of 24-h recalls for 6114 adults aged 19 years and over, participating in the Australian National Nutrition and Physical Activity Survey 2011–2012. Low energy reporters (LER) and plausible reporters (PR) were identified. Discretionary food intake was used as a proxy indicator of diet quality. SES was determined using area-level SES and educational attainment. Regression analysis was applied to examine the effects of LER and SES on diet quality, adjusting for potential confounders. LER was more common in populations of lower SES than higher SES (area-level OR 1·46 (95 % CI 1·06, 2·00); education OR 1·64 (95 % CI 1·28, 2·09). LER and SES were independently associated with diet quality, with LER reporting lower percentage energy from discretionary foods compared with PR (27·4 v. 34·2, P < 0·001), and those of lower area-level SES and education reporting lower diet quality compared with those of higher SES (33·7 v. 31·2, P < 0·001; and 33·5 v. 29·6, P < 0·001, respectively). No interaction effect was found between LER and SES, indicating percentage energy in discretionary foods was not differentially misreported across the SES areas (0·3078) or education (P = 0·7078). In conclusion, LER and higher SES were associated with better diet quality.

From 2008, the UK’s National Diet and Nutrition Survey (NDNS) changed the method of dietary data collection from a 7-d weighed diary to a 4-d unweighed diary, partly to reduce participant burden. This study aimed to test whether self-reported energy intake changed significantly over the 4-d recording period of the NDNS rolling programme. Analyses used data from the NDNS years 1 (2008/2009) to 8 (2015/2016) inclusive, from participants aged 13 years and older. Dietary records from participants who reported unusual amounts of food and drink consumed on one or more days were excluded, leaving 6932 participants. Mean daily energy intake was 7107 kJ (1698 kcal), and there was a significant decrease of 164 kJ (39 kcal) between days 1 and 4 (P < 0·001). There was no significant interaction of sex or low-energy reporter status (estimated from the ratio of reported energy intake:BMR) with the change in reported energy intake. The decrease in reported energy intake on day 4 compared with day 1 was greater (P < 0·019) for adults with higher BMI (>30 kg/m2) than it was for leaner adults. Reported energy intake decreased over the 4-d recording period of the NDNS rolling programme suggesting that participants change their diet more, or report less completely, with successive days of recording their diet. The size of the effect was relatively minor, however.

Coffee is central to the economy of many developing countries, as well as to the world economy. However, despite the widespread consumption of coffee, there are very few available data showing the usual intake of this beverage. Surveying usual coffee intake is a way of monitoring one aspect of a population's usual dietary intake. Thus, the present study aimed to characterise the usual daily coffee intake in the Brazilian population. We used data from the National Dietary Survey collected in 2008–9 from a probabilistic sample of 34 003 Brazilians aged 10 years and older. The National Cancer Institute method was applied to obtain the usual intake based on two nonconsecutive food diaries, and descriptive statistical analyses were performed by age and sex for Brazil and its regions. The estimated average usual daily coffee intake of the Brazilian population was 163 (se 2·8) ml. The comparison by sex showed that males had a 12 % greater usual coffee intake than females. In addition, the highest intake was recorded among older males. Among the five regions surveyed, the North-East had the highest usual coffee intake (175 ml). The most common method of brewing coffee was filtered/instant coffee (71 %), and the main method of sweetening beverages was with sugar (87 %). In Brazil, the mean usual coffee intake corresponds to 163 ml, or 1·5 cups/d. Differences in usual coffee intake according to sex and age differed among the five Brazilian regions.

High dietary Na intake is associated with multiple health risks, making accurate assessment of population dietary Na intake critical. In the present study, reporting accuracy of dietary Na intake was evaluated by 24 h urinary Na excretion using the EPIC-Soft 24 h dietary recall (24-HDR). Participants from a subsample of the European Food Consumption Validation study (n 365; countries: Belgium, Norway and Czech Republic), aged 45–65 years, completed two 24 h urine collections and two 24-HDR. Reporting accuracy was calculated as the ratio of reported Na intake to that estimated from the urinary biomarker. A questionnaire on salt use was completed in order to assess the discretionary use of table and cooking salt. The reporting accuracy of dietary Na intake was assessed using two scenarios: (1) a salt adjustment procedure using data from the salt questionnaire; (2) without salt adjustment. Overall, reporting accuracy improved when data from the salt questionnaire were included. The mean reporting accuracy was 0·67 (95 % CI 0·62, 0·72), 0·73 (95 % CI 0·68, 0·79) and 0·79 (95 % CI 0·74, 0·85) for Belgium, Norway and Czech Republic, respectively. Reporting accuracy decreased with increasing BMI among male subjects in all the three countries. For women from Belgium and Norway, reporting accuracy was highest among those classified as obese (BMI ≥ 30 kg/m2: 0·73, 95 % CI 0·67, 0·81 and 0·81, 95 % CI 0·77, 0·86, respectively). The findings from the present study showed considerable underestimation of dietary Na intake assessed using two 24-HDR. The questionnaire-based salt adjustment procedure improved reporting accuracy by 7–13 %. Further development of both the questionnaire and EPIC-Soft databases (e.g. inclusion of a facet to describe salt content) is necessary to estimate population dietary Na intakes accurately.

Indian diets derive almost 60 % of their protein from cereals with relatively low digestibility and quality. There have been several surveys of diets and protein intakes in India by the National Nutrition Monitoring Board (NNMB) over the last 25 years, in urban and rural, as well as in slum dwellers and tribal populations. Data of disadvantaged populations from slums, tribals and sedentary rural Indian populations show that the protein intake (mainly from cereals) is about 1 gm/kg/day. However, the protein intake looks less promising in terms of the protein digestibility corrected amino acid score (PDCAAS), using lysine as the first limiting amino acid, where all populations, particularly rural and tribal, appear to have an inadequate quality to their protein intake. The protein: energy (PE) ratio is a measure of dietary quality, and has been used in the 2007 WHO/FAO/UNU report to define reference requirement values with which the adequacy of diets can be evaluated in terms of a protein quality corrected PE ratio. It is likely that about one third of this sedentary rural population is at risk of not meeting their requirements. These levels of risk of deficiency are in a population with relatively low BMI populations, whose diets are also inadequate in fruits and vegetables. Therefore, while the burden of enhancing the quality of protein intake in rural India exists, the quality of the diet, in general, represents a challenge that must be met.

Under-reporting (UR) of energy intake (EI) by self-reported dietary methods is well-documented but the methods used to estimate UR in population-based studies commonly assume a sedentary lifestyle. We compared estimated UR using individualised estimates of energy requirements with a population cut-off based on minimum energy needs. UR was estimated for 1551 adults aged 19–64 years enrolled in the National Diet and Nutrition Survey. Physical activity diaries and 7 d weighed dietary records were completed concurrently. Mean daily EI (kJ/d) was calculated from the dietary records. Reported physical activity was used to assign each subject's activity level, and then to calculate estimated energy requirements (EER) from published equations. UR was calculated both as EER – EI with an adjustment for daily EER and EI variation, and also by a population method. By the individual method UR was approximately 27 % of energy needs in men and 29 % in women, with 75 % of men and 77 % of women classified as under-reporters; by the population method 80 and 88 % were classified as under-reporters respectively. When subjects who reported their eating being affected by dieting or illness during dietary recording were excluded, UR was 25 % of energy needs in both sexes. UR was higher in overweight and obese men and women compared with their lean counterparts (P < 0·001). UR of EI must be considered in dietary surveys. The EER method allows UR to be quantified and takes into account an individual's activity level. Measures of physical activity and questions to identify under-eating during dietary recording may help to evaluate secular trends in UR.

The objective of this project was to collect and evaluate data on nutrient intake and status across Europe and to ascertain whether any trends could be identified. Surveys of dietary intake and status were collected from across Europe by literature search and personal contact with country experts. Surveys that satisfied a defined set of criteria – published, based on individual intakes, post-1987, adequate information provided to enable its quality to be assessed, small age bands, data for sexes separated above 12 years, sample size over 25 and subjects representative of the population – were selected for further analysis. In a small number of cases, where no other data for a country were available or where status data were given, exceptions were made. Seventy-nine surveys from 23 countries were included, and from them data on energy, protein, fats, carbohydrates, alcohol, vitamins, minerals and trace elements were collected and tabulated. Data on energy, protein, total fat and carbohydrate were given in a large number of surveys, but information was very limited for some micronutrients. No surveys gave information on fluid intake and insufficient gave data on food patterns to be of value to this project. A variety of collection methods were used, there was no consistency in the ages of children surveyed or the age cut-off points, but most surveys gave data for males and females separately at all ages. Just under half of the surveys were nationally representative and most of the remainder were regional. Only a small number of local surveys could be included. Apart from anthropometric measurements, status data were collected in only seven countries. Males had higher energy intakes than females, energy intake increased with age but levelled off in adolescent girls. Intakes of other nutrients generally related to energy intakes. Some north–south geographical trends were noted in fat and carbohydrate intakes, but these were not apparent for other nutrients. Some other trends between countries were noted, but there were also wide variations within countries. A number of validation studies have shown that misreporting is a major problem in dietary surveys of children and adolescents and so all the dietary data collected for this project should be interpreted and evaluated with caution In addition, dietary studies rely on food composition tables for the conversion of food intake data to estimated nutrient intakes and each country uses a different set of food composition data which differ in definitions, analytical methods, units and modes of expression. This can make comparisons between countries difficult and inaccurate. Methods of measuring food intake are not standardised across Europe and intake data are generally poor, so there are uncertainties over the true nutrient intakes of children and adolescents across Europe. There are insufficient data on status to be able to be able to draw any conclusions about the nutritional quality of the diets of European children and adolescents.

Although food supply statistics are commonly used in ecological studies of diet and disease, little information is available on how they compare with reported intakes of foods. The objective of the present study was to compare fruit and vegetable availability with estimates of national mean intakes derived from national food consumption surveys. Food availability statistics from the FAO were used. For each country, mean national supply, based on at least 3 years of FAO data, was calculated. National estimates of mean fruit and vegetable intakes were derived from population-based surveys from fifteen countries, gathered for the World Health Organization Global Burden of Disease Study revision for 2000. Extrapolations were made when survey data did not cover all age groups. For each country, the FAO:survey estimate ratio was calculated. This ratio ranged from 0·93 to 2·70 (median value=1·39). Although there was a tendency for FAO data to overestimate intakes (fourteen out of fifteen countries), the degree of overestimation varied greatly among the countries included in this study (5–270 %). As food supply statistics are the only source of information on dietary patterns in most countries of the world, further information on how they reflect food intakes is needed. Obtaining detailed and valid estimates of dietary intakes in more countries around the world will be essential for such comparisons.

The aim of the present cross-sectional study was to examine the agreement and disagreement between a 7 d diet diary (7DD) and a self-administered machine-readable food-frequency questionnaire (FFQ) asking about diet in the previous year, and to validate both methods with biomarkers of nutrient intake. The subjects were an age- and employment-grade-stratified random subsample of London-based civil servants (457 men and 403 women), aged 39–61 years, who completed both a 7DD and a FFQ at phase 3 follow-up (1991–1993) of the Whitehall II study. Mean daily intakes of dietary energy, total fat, saturated, monounsaturated and polyunsaturated fatty acids, linoleic acid, total carbohydrate excluding fibre, sugars, starch, dietary fibre, protein, vitamin C, vitamin E (as α-tocopherol equivalents), folate, carotenes (as total β-carotene activity), Fe, Ca, Mg, K and alcohol were measured. Serum cholesteryl ester fatty acids (CEFA), plasma α-tocopherol and β-carotene were also measured as biomarkers. Estimates of mean energy intake from the two methods were similar in men, and some 10 % higher according to the FFQ in women. Compared with the 7DD, the FFQ tended to overestimate plant-derived micronutrient intakes (carotenes from FFQ v. 7DD men 2713 (SD 1455) V. 2180 (sd 1188) μg/d, women 3100 (sd 1656) v. 2221 (sd 1180) μg/d, both differences P<0·0001) and to underestimate fat intake. Against plasma β-carotene/cholesterol, carotene intake was as well estimated by the FFQ as the 7DD (Spearman rank correlations, men 0·32 v. 0·30, women 0·27 v. 0·22, all P≤0·0001, energy-adjusted data). Ranking of participants by other nutrient intakes tended to be of the same order according to the two dietary methods, e.g. rank correlations for CEFA linoleic acid against FFQ and 7DD estimates respectively, men 0·38 v. 0·41, women 0·53 v. 0·62, all P≤0·0001, energy-adjusted % fat). For α-tocopherol there were no correlations between plasma level and estimated intakes by either dietary method. Quartile agreement for energy-adjusted nutrient intakes between the two self-report methods was in the range 37–50 % for men and 32–44 % for women, and for alcohol, 57 % in both sexes. Disagreement (misclassification into extreme quartiles of intake) was in the range 0–6 % for both sexes. The dietary methods yielded similar prevalences (about 34 %) of low energy reporters. The two methods show satisfactory agreement, together with an expected level of systematic differences, in their estimates of nutrient intake. Against the available biomarkers, the machine-readable FFQ performed well in comparison with the manually coded 7DD in this study population. For both methods, regression-based adjustment of nutrient intake to mean dietary energy intake by gender appears on balance to be the optimal approach to data presentation and analysis, in view of the complex problem of low energy reporting.