Correlates of food choice in unemployed young people: The role of demographic factors, self-efficacy, food involvement, food poverty and physical activity

Associations between socio-demographic and psychological factors and food choice patterns were explored in unemployed young people who constitute a vulnerable group at risk of poor dietary health. Volunteers (N = 168), male (n = 97) and female (n = 71), aged 15–25 years were recruited through United Kingdom (UK) community-based organisations serving young people not in education training or employment (NEET). Survey questionnaire enquired on food poverty, physical activity and measured responses to the Food Involvement Scale (FIS), Food Self-Efficacy Scale (FSS) and a 19-item Food Frequency Questionnaire (FFQ). A path analysis was undertaken to explore associations between age, gender, food poverty, age at leaving school, food self-efficacy (FS-E), food involvement (FI) (kitchen; uninvolved; enjoyment), physical activity and the four food choice patterns (junk food; healthy; fast food; high fat). FS-E was strong in the model and increased with age. FS-E was positively associated with more
frequent choice of healthy food and less frequent junk or high fat food (having controlled for age, gender and age at leaving school). FI (kitchen and enjoyment) increased with age. Higher FI (kitchen) was associated with less frequent junk food and fast food choice. Being uninvolved with food was associated with
more frequent fast food choice. Those who left school after the age of 16 years reported more frequent physical activity. Of the indirect effects, younger individuals had lower FI (kitchen) which led to frequent junk and fast food choice. Females who were older had higher FI (enjoyment) which led to less frequent fast food choice. Those who had left school before the age of 16 had low food involvement (uninvolved) which led to frequent junk food choice. Multiple indices implied that data were a good fit to the model which indicated a need to enhance food self-efficacy and encourage food involvement in order to improve dietary health among these disadvantaged young people.

Increasing Fruit and Vegetable Intake Has No Dose-Response Effect on Conventional Cardiovascular Risk Factors in Overweight Adults at High Risk of Developing Cardiovascular Disease

BACKGROUND: Improving diet and lifestyle is important for prevention of cardiovascular disease (CVD). Observational evidence suggests that increasing fruit and vegetable (FV) consumption may lower CVD risk, largely through modulation of established risk factors, but intervention data are required to fully elucidate the mechanisms by which FVs exert benefits on vascular health.

OBJECTIVE: The aim of this study was to examine the dose-response effect of FV intake on cardiovascular risk factors in adults at high CVD risk.

METHODS: This was a randomized controlled parallel group study involving overweight adults (BMI: >27 and ≤35 kg/m(2)) with a habitually low FV intake (≤160 g/d) and a high total risk of developing CVD (estimated ≥20% over 10 y). After a 4-wk run-in period where FV intake was limited to <2 portions/d (<160 g/d), 92 eligible participants were randomly assigned to 1 of 3 groups: to consume either 2, 4, or 7 portions (equivalent to 160 g, 320 g, or 560 g, respectively) of FVs daily for 12 consecutive weeks. Fasting venous blood samples were collected at baseline (week 4) and post-intervention (week 16) for analysis of lipid fractions and high-sensitivity C-reactive protein (hsCRP) concentrations. Compliance with the FV intervention was determined with use of self-reported FV intake and biomarkers of micronutrient status. Ambulatory blood pressure and body composition were also measured pre- and post-intervention.

RESULTS: A total of 89 participants completed the study and body composition remained stable throughout the intervention period. Despite good compliance with the intervention, no significant difference was found between the FV groups for change in measures of ambulatory blood pressure, plasma lipids, or hsCRP concentrations.

CONCLUSIONS: There was no evidence of a dose-response effect of FV intake on conventional CVD risk factors measured in overweight adults at high CVD risk. This trial was registered at clinicaltrials.gov as NCT00874341.

Effect of a Web-Based Behavior Change Program on Weight Loss and Cardiovascular Risk Factors in Overweight and Obese Adults at High Risk of Developing Cardiovascular Disease:Randomized Controlled Trial

BACKGROUND: Web-based programs are a potential medium for supporting weight loss because of their accessibility and wide reach. Research is warranted to determine the shorter- and longer-term effects of these programs in relation to weight loss and other health outcomes.

OBJECTIVE: The aim was to evaluate the effects of a Web-based component of a weight loss service (Imperative Health) in an overweight/obese population at risk of cardiovascular disease (CVD) using a randomized controlled design and a true control group.

METHODS: A total of 65 overweight/obese adults at high risk of CVD were randomly allocated to 1 of 2 groups. Group 1 (n=32) was provided with the Web-based program, which supported positive dietary and physical activity changes and assisted in managing weight. Group 2 continued with their usual self-care (n=33). Assessments were conducted face-to-face. The primary outcome was between-group change in weight at 3 months. Secondary outcomes included between-group change in anthropometric measurements, blood pressure, lipid measurements, physical activity, and energy intake at 3, 6, and 12 months. Interviews were conducted to explore participants' views of the Web-based program.

RESULTS: Retention rates for the intervention and control groups at 3 months were 78% (25/32) vs 97% (32/33), at 6 months were 66% (21/32) vs 94% (31/33), and at 12 months were 53% (17/32) vs 88% (29/33). Intention-to-treat analysis, using baseline observation carried forward imputation method, revealed that the intervention group lost more weight relative to the control group at 3 months (mean -3.41, 95% CI -4.70 to -2.13 kg vs mean -0.52, 95% CI -1.55 to 0.52 kg, P<.001), at 6 months (mean -3.47, 95% CI -4.95 to -1.98 kg vs mean -0.81, 95% CI -2.23 to 0.61 kg, P=.02), but not at 12 months (mean -2.38, 95% CI -3.48 to -0.97 kg vs mean -1.80, 95% CI -3.15 to -0.44 kg, P=.77). More intervention group participants lost ≥5% of their baseline body weight at 3 months (34%, 11/32 vs 3%, 1/33, P<.001) and 6 months (41%, 13/32 vs 18%, 6/33, P=.047), but not at 12 months (22%, 7/32 vs 21%, 7/33, P=.95) versus control group. The intervention group showed improvements in total cholesterol, triglycerides, and adopted more positive dietary and physical activity behaviors for up to 3 months verus control; however, these improvements were not sustained.

CONCLUSIONS: Although the intervention group had high attrition levels, this study provides evidence that this Web-based program can be used to initiate clinically relevant weight loss and lower CVD risk up to 3-6 months based on the proportion of intervention group participants losing ≥5% of their body weight versus control group. It also highlights a need for augmenting Web-based programs with further interventions, such as in-person support to enhance engagement and maintain these changes.

Combining vitamin C and carotenoid biomarkers better predicts fruit and vegetable intake than individual biomarkers in dietary intervention studies

PURPOSE: The aim of this study was to determine whether combining potential biomarkers of fruit and vegetables is better at predicting FV intake within FV intervention studies than single biomarkers.

DESIGN: Data from a tightly controlled randomised FV intervention study (BIOFAV; all food provided and two meals/day on weekdays consumed under supervision) were used. A total of 30 participants were randomised to either 2, 5 or 8 portions FV/day for 4 weeks, and blood samples were collected at baseline and 4 weeks for plasma vitamin C and serum carotenoid analysis. The combined biomarker approach was also tested in three further FV intervention studies conducted by the same research team, with less strict dietary control (FV provided and no supervised meals).

RESULTS: The combined model containing all carotenoids and vitamin C was a better fit than either the vitamin C only (P < 0.001) model or the lutein only (P = 0.006) model in the BIOFAV study. The C-statistic was slightly lower in the lutein only model (0.85) and in the model based upon factor analysis (0.88), and much lower in the vitamin C model (0.68) compared with the full model (0.95). Results for the other studies were similar, although the differences between the models were less marked.

CONCLUSIONS: Although there was some variation between studies, which may relate to the level of dietary control or participant characteristics, a combined biomarker approach to assess overall FV consumption may more accurately predict FV intake within intervention studies than the use of a single biomarker. The generalisability of these findings to other populations and study designs remains to be tested. 

Community Sanctions and Measures

This chapter explores the use of community sanctions in the Republic of Ireland and in Northern Ireland. It locates this discussion within a wider international landscape, where the numbers of people subject to supervision in the community has risen markedly. It explores some of the reasons for this growth alongside the rationalities that are deployed to promote the use of community sanctions over time. The differing trajectories of the two jurisdictions in respect of the evolution and use of community sanctions are explored, as are some of the factors that explain areas of divergence and commonality. The chapter concludes by critically considering penal reductionism as a point of policy convergence in the two jurisdictions.