65 research outputs found

    Contribution of food sources to the vitamin B12 status of South Indian children from a birth cohort recruited in the city of Mysore.

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    OBJECTIVE: There is evidence that subclinical vitamin B12 (B12) deficiency is common in India. Vegetarianism is prevalent and therefore meat consumption is low. Our objective was to explore the contribution of B12-source foods and maternal B12 status during pregnancy to plasma B12 concentrations. DESIGN: Maternal plasma B12 concentrations were measured during pregnancy. Children's dietary intakes and plasma B12 concentrations were measured at age 9.5 years; B12 and total energy intakes were calculated using food composition databases. We used linear regression to examine associations between maternal B12 status and children's intakes of B12 and B12-source foods, and children's plasma B12 concentrations. SETTING: South Indian city of Mysore and surrounding rural areas. SUBJECTS: Children from the Mysore Parthenon Birth Cohort (n 512, 47.1 % male). RESULTS: Three per cent of children were B12 deficient (<150 pmol/l). A further 14 % had 'marginal' B12 concentrations (150-221 pmol/l). Children's total daily B12 intake and consumption frequencies of meat and fish, and micronutrient-enriched beverages were positively associated with plasma B12 concentrations (P=0.006, P=0.01 and P=0.04, respectively, adjusted for socio-economic indicators and maternal B12 status). Maternal pregnancy plasma B12 was associated with children's plasma B12 concentrations, independent of current B12 intakes (P<0.001). Milk and curd (yoghurt) intakes were unrelated to B12 status. CONCLUSIONS: Meat and fish are important B12 sources in this population. Micronutrient-enriched beverages appear to be important sources in our cohort, but their high sugar content necessitates care in their recommendation. Improving maternal B12 status in pregnancy may improve Indian children's status

    Randomised controlled feasibility trial of a web-based weight management intervention with nurse support for obese patients in primary care

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    &lt;b&gt;Background&lt;/b&gt;&lt;p&gt;&lt;/p&gt; There is a need for cost-effective weight management interventions that primary care can deliver to reduce the morbidity caused by obesity. Automated web-based interventions might provide a solution, but evidence suggests that they may be ineffective without additional human support. The main aim of this study was to carry out a feasibility trial of a web-based weight management intervention in primary care, comparing different levels of nurse support, to determine the optimal combination of web-based and personal support to be tested in a full trial.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Methods&lt;/b&gt;&lt;p&gt;&lt;/p&gt; This was an individually randomised four arm parallel non-blinded trial, recruiting obese patients in primary care. Following online registration, patients were randomly allocated by the automated intervention to either usual care, the web-based intervention only, or the web-based intervention with either basic nurse support (3 sessions in 3 months) or regular nurse support (7 sessions in 6 months). The main outcome measure (intended as the primary outcome for the main trial) was weight loss in kg at 12 months. As this was a feasibility trial no statistical analyses were carried out, but we present means, confidence intervals and effect sizes for weight loss in each group, uptake and retention, and completion of intervention components and outcome measures.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt;&lt;p&gt;&lt;/p&gt; All randomised patients were included in the weight loss analyses (using Last Observation Carried Forward). At 12 months mean weight loss was: usual care group (n = 43) 2.44 kg; web-based only group (n = 45) 2.30 kg; basic nurse support group (n = 44) 4.31 kg; regular nurse support group (n = 47) 2.50 kg. Intervention effect sizes compared with usual care were: d = 0.01 web-based; d = 0.34 basic nurse support; d = 0.02 regular nurse support. Two practices deviated from protocol by providing considerable weight management support to their usual care patients.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions&lt;/b&gt;&lt;p&gt;&lt;/p&gt; This study demonstrated the feasibility of delivering a web-based weight management intervention supported by practice nurses in primary care, and suggests that the combination of the web-based intervention with basic nurse support could provide an effective solution to weight management support in a primary care context

    An internet-based intervention with brief nurse support to manage obesity in primary care (POWeR+): a pragmatic, parallel-group, randomised controlled trial

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    Background The obesity epidemic has major public health consequences. Expert dietetic and behavioural counselling with intensive follow-up is effective, but resource requirements severely restrict widespread implementation in primary care, where most patients are managed. We aimed to estimate the effectiveness and cost-effectiveness of an internet-based behavioural intervention (POWeR+) combined with brief practice nurse support in primary care. Methods We did this pragmatic, parallel-group, randomised controlled trial at 56 primary care practices in central and south England. Eligible adults aged 18 years or older with a BMI of 30 kg/m2 or more (or ≥28 kg/m2 with hypertension, hypercholesterolaemia, or diabetes) registered online with POWeR+—a 24 session, web-based, weight management intervention lasting 6 months. After registration, the website automatically randomly assigned patients (1:1:1), via computer-generated random numbers, to receive evidence-based dietetic advice to swap foods for similar, but healthier, choices and increase fruit and vegetable intake, in addition to 6 monthly nurse follow-up (control group); web-based intervention and face-to-face nurse support (POWeR+Face-to-face [POWeR+F]; up to seven nurse contacts over 6 months); or web-based intervention and remote nurse support (POWeR+Remote [POWeR+R]; up to five emails or brief phone calls over 6 months). Participants and investigators were masked to group allocation at the point of randomisation; masking of participants was not possible after randomisation. The primary outcome was weight loss averaged over 12 months. We did a secondary analysis of weight to measure maintenance of 5% weight loss at months 6 and 12. We modelled the cost-effectiveness of each intervention. We did analysis by intention to treat, with multiple imputation for missing data. This trial is registered as an International Standard Randomised Controlled Trial, number ISRCTN21244703. Findings Between Jan 30, 2013, and March 20, 2014, 818 participants were randomly assigned to the control group (n=279), the POWeR+F group (n=269), or the POWeR+R group (n=270). Weight loss averaged over 12 months was recorded in 666 (81%) participants. The control group lost almost 3 kg over 12 months (crude mean weight: baseline 104·38 kg [SD 21·11; n=279], 6 months 101·91 kg [19·35; n=136], 12 months 101·74 kg [19·57; n=227]). The primary imputed analysis showed that compared with the control group, patients in the POWeR+F group achieved an additional weight reduction of 1·5 kg (95% CI 0·6–2·4; p=0·001) averaged over 12 months, and patients in the POWeR+R group achieved an additional 1·3 kg (0·34–2·2; p=0·007). 21% of patients in the control group had maintained a clinically important 5% weight reduction at month 12, compared with 29% of patients in the POWeR+F group (risk ratio 1·56, 0·96–2·51; p=0·070) and 32% of patients in the POWeR+R group (1·82, 1·31–2·74; p=0·004). The incremental overall cost to the health service per kg weight lost with the POWeR+ interventions versus the control strategy was £18 (95% CI −129 to 195) for POWeR+F and –£25 (−268 to 157) for POWeR+R; the probability of being cost-effective at a threshold of £100 per kg lost was 88% and 98%, respectively. No adverse events were reported. Interpretation Weight loss can be maintained in some individuals by use of novel written material with occasional brief nurse follow-up. However, more people can maintain clinically important weight reductions with a web-based behavioural program and brief remote follow-up, with no increase in health service costs. Future research should assess the extent to which clinically important weight loss can be maintained beyond 1 year

    Improving women’s diet quality pre-conceptionally and during gestation: effects on birth weight and prevalence of low birth weight; a randomized controlled efficacy trial in India (Mumbai Maternal Nutrition Project)

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    BACKGROUND: Low birth weight (LBW) is an important public health problem in undernourished populations.OBJECTIVE: We tested whether improving women's dietary micronutrient quality before conception and throughout pregnancy increases birth weight in a high-risk Indian population.DESIGN: The study was a nonblinded, individually randomized controlled trial. The intervention was a daily snack made from green leafy vegetables, fruit, and milk (treatment group) or low-micronutrient vegetables (potato and onion) (control group) from ? 90 d before pregnancy until delivery in addition to the usual diet. Treatment snacks contained 0.69 MJ of energy (controls: 0.37 MJ) and 10-23% of WHO Reference Nutrient Intakes of ?-carotene, riboflavin, folate, vitamin B-12, calcium, and iron (controls: 0-7%). The primary outcome was birth weight.RESULTS: Of 6513 women randomly assigned, 2291 women became pregnant, 1962 women delivered live singleton newborns, and 1360 newborns were measured. In an intention-to-treat analysis, there was no overall increase in birth weight in the treatment group (+26 g; 95% CI: -15, 68 g; P = 0.22). There was an interaction (P &lt; 0.001) between the allocation group and maternal prepregnant body mass index (BMI; in kg/m(2)) [birth-weight effect: -23, +34, and +96 g in lowest (&lt;18.6), middle (18.6-21.8), and highest (&gt;21.8) thirds of BMI, respectively]. In 1094 newborns whose mothers started supplementation ? 90 d before pregnancy (per-protocol analysis), birth weight was higher in the treatment group (+48 g; 95% CI: 1, 96 g; P = 0.046). Again, the effect increased with maternal BMI (-8, +79, and +113 g; P-interaction = 0.001). There were similar results for LBW (intention-to-treat OR: 0.83; 95% CI: 0.66, 1.05; P = 0.10; per-protocol OR = 0.76; 95% CI: 0.59, 0.98; P = 0.03) but no effect on gestational age in either analysis.CONCLUSIONS: A daily snack providing additional green leafy vegetables, fruit, and milk before conception and throughout pregnancy had no overall effect on birth weight. Per-protocol and subgroup analyses indicated a possible increase in birth weight if the mother was supplemented ? 3 mo before conception and was not underweight. This trial was registered at www.controlled-trials.com/isrctn/ as ISRCTN62811278<br/

    Energy balance and obesity: what are the main drivers?

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    Purpose The aim of this paper is to review the evidence of the association between energy balance and obesity. Methods: In December 2015, the International Agency for Research on Cancer (IARC), Lyon, France convened a Working Group of international experts to review the evidence regarding energy balance and obesity, with a focus on Low and Middle Income Countries (LMIC). Results: The global epidemic of obesity and the double burden, in LMICs, of malnutrition (coexistence of undernutrition and overnutrition) are both related to poor quality diet and unbalanced energy intake. Dietary patterns consistent with a traditional Mediterranean diet and other measures of diet quality can contribute to long-term weight control. Limiting consumption of sugar-sweetened beverages has a particularly important role in weight control. Genetic factors alone cannot explain the global epidemic of obesity. However, genetic, epigenetic factors and the microbiota could influence individual responses to diet and physical activity. Conclusion: Energy intake that exceeds energy expenditure is the main driver of weight gain. The quality of the diet may exert its effect on energy balance through complex hormonal and neurological pathways that influence satiety and possibly through other mechanisms. The food environment, marketing of unhealthy foods and urbanization, and reduction in sedentary behaviors and physical activity play important roles. Most of the evidence comes from High Income Countries and more research is needed in LMICs

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    Design consepts in Nutritional Epidemiology

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