To describe four different methods of identifying indicator foods that are high, medium or low in fat with reference to dietary patterns and to use these indicator foods to test three sets of definitions of ‘high’, ‘medium’ and ‘low’ in fat from ‘banding schemes’ developed by the Coronary Prevention Group (CPG), the Food Standards Agency (FSA) and Sainsbury’s.

Indicator foods were developed using food intake data from the UK National Diet and Nutrition Survey and two parameters: (i) probability of the food being consumed by an individual with a high-fat diet (Method 1); and (ii) the contribution of the food to the fat intake of the average diet of consumers (Methods 3 and 4). Method 2 used both parameters. The three banding schemes were tested by assessing their levels of agreement with methods in categorising indicators.

Sensitivity in identifying high, medium and low fat indicators was highest with the CPG banding scheme (high and medium fat indicators) and Sainsbury’s scheme (low fat indicators) (Methods 2, 3 and 4). The levels of agreement (kappa coefficient) were 0·68 for the CPG scheme; 0·51 for the Sainsbury’s scheme; and 0·41 for the FSA scheme (Method 3).

It is possible to use indicator foods related to dietary patterns of a specific population to generate more rational definitions of ‘high’, ‘medium’ and ‘low’ in fat. This could be the starting point for the development of indicator foods for testing more complex nutrient profile models (i.e. those that consider more than one nutrient).

The current study aimed to assess the relationship between protein intake and bone parameters among dynapenic-obese older adults.

The current study is a secondary analysis with an a posteriori and exploratory design.

Subjects were recruited from the community via social communication (flyers and meetings in community centres) in the Great Montreal area.

Twenty-six subjects were divided a posteriori into two groups according to their usual protein intake: PROT−: < 1 g/kg per d (n 13; women: 53·8 %; 66·5 (sd 3·3) years) and PROT+: > 1·2 g/kg per d (n 13; women: 61·5 %; 67·2 (sd 2·7) years).

Both groups were comparable for age (PROT−: 66·5 (sd 3·3) v. PROT+: 67·2 (sd 2·7) years, P = 0·61) and gender (women: PROT−: n 7; 53·8 % v. PROT+: n 8; 61·5 %, P = 0·69). The PROT− group had a higher marrow area (P = 0·049), a greater bone compressive strength (P = 0·048) and a larger total bone area (P = 0·045) than the PROT+ group. However, no significant difference between the two groups was observed regarding body composition (fat and lean masses) or muscle composition.

A lower protein intake seems to be associated with bone sizes, which influence bone strength, but do not influence bone density among dynapenic-obese older people.

To investigate the association between a lifestyle score and all-cause mortality in the Chilean population.

Prospective study.

The score was based on seven modifiable behaviours: salt intake, fruit and vegetable intake, alcohol consumption, sleep duration, smoking, physical activity and sedentary behaviours. 1-point was assigned for each healthy recommendation. Points were summed to create an unweighted score from 0 (less healthy) to 7 (healthiest). According to their score, participants were then classified into: less healthy (0–2 points), moderately healthy (3–4 points) and the healthiest (5–7 points). Associations between the categories of lifestyle score and all-cause mortality were investigated using Cox proportional hazard models adjusted for confounders. Nonlinear associations were also investigated.

2706 participants from the Chilean National Health Survey 2009–2010.

After a median follow-up of 10·9 years, 286 (10·6 %) participants died. In the maximally adjusted model, and compared with the healthiest participants, those less healthy had 2·55 (95 % CI 1·75, 3·71) times higher mortality risk due to any cause. Similar trends were identified for the moderately healthy group. Moreover, there was a significant trend towards increasing the mortality risk when increasing unhealthy behaviours (hazard ratio model 3: 1·61 (95 % CI 1·34, 1·94)). There was no evidence of nonlinearity between the lifestyle score and all-cause mortality.

Individuals in the less healthy lifestyle category had higher mortality risk than the healthiest group. Therefore, public health strategies should be implemented to promote adherence to a healthy lifestyle across the Chilean population.

The present study examined military families’ use of food distribution resources and military (e.g. rank) and non-military (e.g. race/ethnicity) characteristics associated with using food distribution resources.

Secondary data analyses from a cross-sectional survey in the first 6 months of 2021.

A national sample of eligible families completed an online survey.

8326 enlisted military families with an active duty service member in the United States Army or Air Force who applied for supplemental childcare funding distributed by National Military Family Association.

13·2 % of the families reported utilising a food distribution resource in the past 12 months. Those with lower financial well-being were more likely to utilise such resources. Older (OR = 1·04, 95 % CI = 1·02, 1·05, P < 0·001), single-earner (OR = 0·73, 95 % CI = 0·61, 0·89, P = 0·001) families with a lower rank (OR = 0·69, 95 % CI = 0·64, 0·75, P < 0·001) and Army affiliation (compared with Air Force) (OR = 2·31, 95 % CI = 2·01, 2·67, P < 0·001) were more likely to utilise food distribution resources. Members of certain racial/ethnic minority groups were more likely to utilise food distribution resources than White respondents (OR from 1·47 for multi-racial to 1·69 for Asians), as were families with more dependent children (OR = 1·35, 95 % CI = 1·25, 1·47, P < 0·001).

These results identify the extent of food distribution resource utilisation in military families with young children approximately 1 year into the COVID-19 pandemic. The results also identify characteristics associated with their use of food distribution resources. Findings are discussed with an emphasis on prevention and intervention implications for military families.

Low dietary guideline adherence is persistent, but there is limited understanding of how individuals with varying socio-economic backgrounds reach a certain dietary intake. We investigated how quantitative and qualitative data on dietary guidelines adherence correspond and complement each other, to what extent determinants of guideline adherence in quantitative data reflect findings on determinants derived from qualitative data and which of these determinants emerged as interdependent in the qualitative data.

This mixed-methods study used quantitative questionnaire data (n 1492) and qualitative data collected via semi-structured telephone interviews (n 24). Quantitative data on determinants and their association with total guideline adherence (scored 0–150) were assessed through linear regression. Directed content analysis was used for qualitative data.

Dutch urban areas.

Adults aged 18–65 years.

A range of determinants emerged from both data sources, for example higher levels of cognitive restraint (β 5·6, 95 % CI 4·2, 7·1), habit strength of vegetables (β 4·0, 95 % CI 3·3, 4·7) and cooking skills (β 4·7, 95 % CI 3·5, 5·9), were associated with higher adherence. Qualitative data additionally suggested the influence of food prices, strong dietary habits and the social aspect of eating, and for the determinants cognitive restraint, habit strength related to vegetables, food prices and home cooking, some variation between interviewees with varying socio-economic backgrounds emerged in how these determinants affected guideline adherence.

This mixed-methods exploration provides a richer understanding of why adults with varying socio-economic backgrounds do or do not adhere to dietary guidelines. Results can guide future interventions promoting healthy diets across populations.

We investigated the missed treatment opportunities affecting programmes using mid-upper arm circumference (MUAC) as the sole anthropometric criterion for identification and monitoring of children suffering from severe acute malnutrition (SAM).

Alongside MUAC, we assessed weight-for-height Z-score (WHZ) in children screened and treated according to the national MUAC only protocol in Pakistan. Besides, we collected parents’ perceptions regarding the treatment received by their children through qualitative interviews.

Data were collected from October to December 2021 in Tando Allah Yar District, Sindh.

All children screened in the health facilities (n 8818) and all those discharged as recovered (n 686), throughout the district, contributed to the study. All children screened in the community in the catchment areas of five selected health facilities also contributed (n 8459). Parents of forty-one children randomly selected from these same facilities participated in the interviews.

Overall, 80·3 % of the SAM cases identified during community screening and 64·1 % of those identified in the health facilities presented a ‘WHZ-only’ diagnosis. These figures reached 93·9 % and 84·5 %, respectively, in children aged over 24 months. Among children treated for SAM and discharged as recovered, 25·3 % were still severely wasted according to WHZ. While parents positively appraised the treatment received by their children, they also recommended to extend eligibility to other malnourished children in their neighbourhood.

In this context, using MUAC as the sole anthropometric criterion for treatment decisions (referral, admission and discharge) resulted in a large number of missed opportunities for children in need of timely and adequate care.

Improved food availability and a growing economy in Tanzania may insufficiently decrease pre-existing nutritional deficiencies and simultaneously increase overweight within the same individual, household or population, causing a double burden of malnutrition (DBM). We investigated economic inequalities in DBM at the household level, expressed as a stunted child with a mother with overweight/obesity, and the moderating role of dietary diversity in these inequalities.

We used cross-sectional data from the 2015–2016 Tanzania Demographic and Health Survey.

A nationally representative survey.

Totally, 2867 children (aged 6–23 months) and their mothers (aged 15–49 years). The mother–child pairs were categorised into two groups based on dietary diversity score: achieving and not achieving minimum dietary diversity.

The prevalence of DBM was 5·6 % (sd = 0·6) and significantly varied by region (ranging from 0·6 % to 12·2 %). Significant interaction was observed between dietary diversity and household wealth index (Pfor interaction < 0·001). The prevalence of DBM monotonically increased with greater household wealth among mother–child pairs who did not achieve minimum dietary diversity (Pfor trend < 0·001; however, this association was attenuated in those who achieved minimum dietary diversity (Pfor trend = 0·16), particularly for the richest households (P = 0·44). Analysing household wealth index score as a continuous variable yielded similar results (OR (95 % CI): 2·10 (1·36, 3·25) for non-achievers of minimum dietary diversity, 1·38 (0·76, 2·54) for achievers).

Greater household wealth was associated with higher odds of DBM in Tanzania; however, the negative impact of household economic status on DBM was mitigated by minimum dietary diversity.