To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
There is increasing interest in modelling longitudinal dietary data and classifying individuals into subgroups (latent classes) who follow similar trajectories over time. These trajectories could identify population groups and time points amenable to dietary interventions. This paper aimed to provide a comparison and overview of two latent class methods: group-based trajectory modelling (GBTM) and growth mixture modelling (GMM). Data from 2963 mother–child dyads from the longitudinal Southampton Women’s Survey were analysed. Continuous diet quality indices (DQI) were derived using principal component analysis from interviewer-administered FFQ collected in mothers pre-pregnancy, at 11- and 34-week gestation, and in offspring at 6 and 12 months and 3, 6–7 and 8–9 years. A forward modelling approach from 1 to 6 classes was used to identify the optimal number of DQI latent classes. Models were assessed using the Akaike and Bayesian information criteria, probability of class assignment, ratio of the odds of correct classification, group membership and entropy. Both methods suggested that five classes were optimal, with a strong correlation (Spearman’s = 0·98) between class assignment for the two methods. The dietary trajectories were categorised as stable with horizontal lines and were defined as poor (GMM = 4 % and GBTM = 5 %), poor-medium (23 %, 23 %), medium (39 %, 39 %), medium-better (27 %, 28 %) and best (7 %, 6 %). Both GBTM and GMM are suitable for identifying dietary trajectories. GBTM is recommended as it is computationally less intensive, but results could be confirmed using GMM. The stability of the diet quality trajectories from pre-pregnancy underlines the importance of promotion of dietary improvements from preconception onwards.
To identify peri-conceptional diet patterns among women in Bangalore and examine their associations with risk of gestational diabetes mellitus (GDM).
BAngalore Nutrition Gestational diabetes LifEstyle Study, started in June 2016, was a prospective observational study, in which women were recruited at 5–16 weeks’ gestation. Peri-conceptional diet was recalled at recruitment, using a validated 224-item FFQ. GDM was assessed by a 75-g oral glucose tolerance test at 24–28 weeks’ gestation, applying WHO 2013 criteria. Diet patterns were identified using principal component analysis, and diet pattern–GDM associations were examined using multivariate logistic regression, adjusting for ‘a priori’ confounders.
Antenatal clinics of two hospitals, Bangalore, South India.
Seven hundred and eighty-five pregnant women of varied socio-economic status.
GDM prevalence was 22 %. Three diet patterns were identified: (a) high-diversity, urban (HDU) characterised by diverse, home-cooked and processed foods was associated with older, more affluent, better-educated and urban women; (b) rice-fried snacks-chicken-sweets (RFCS), characterised by low diet diversity, was associated with younger, less-educated, and lower-income, rural and joint families; and (c) healthy, traditional vegetarian (HTV), characterised by home-cooked vegetarian and non-processed foods, was associated with less-educated, more affluent, and rural and joint families. The HDU pattern was associated with a lower GDM risk (adjusted odds ratio (aOR): 0·80/sd, 95 % CI (0·64, 0·99), P = 0·04) after adjusting for confounders. BMI was strongly related to GDM risk and possibly mediated diet–GDM associations.
The findings support global recommendations to encourage women to attain a healthy pre-pregnancy BMI and increase diet diversity. Both healthy and unhealthy foods in the patterns indicate low awareness about healthy foods and a need for public education.
Arachidonic acid (ARA) and DHA, supplied primarily from the mother, are required for early development of the central nervous system. Thus, variations in maternal ARA or DHA status may modify neurocognitive development. We investigated the relationship between maternal ARA and DHA status in early (11·7 weeks) or late (34·5 weeks) pregnancy on neurocognitive function at the age of 4 years or 6–7 years in 724 mother–child pairs from the Southampton Women’s Survey cohort. Plasma phosphatidylcholine fatty acid composition was measured in early and late pregnancy. ARA concentration in early pregnancy predicted 13 % of the variation in ARA concentration in late pregnancy (β=0·36, P<0·001). DHA concentration in early pregnancy predicted 21 % of the variation in DHA concentration in late pregnancy (β=0·46, P<0·001). Children’s cognitive function at the age of 4 years was assessed by the Wechsler Preschool and Primary Scale of Intelligence and at the age of 6–7 years by the Wechsler Abbreviated Scale of Intelligence. Executive function at the age of 6–7 years was assessed using elements of the Cambridge Neuropsychological Test Automated Battery. Neither DHA nor ARA concentrations in early or late pregnancy were associated significantly with neurocognitive function in children at the age of 4 years or the age of 6–7 years. These findings suggest that ARA and DHA status during pregnancy in the range found in this cohort are unlikely to have major influences on neurocognitive function in healthy children.
To evaluate the use of an administered eighty-item FFQ to assess nutrient intake and diet quality in 3-year-old children.
Frequency of consumption and portion size of the foods listed on the FFQ during the 3 months preceding the interview were reported by the child's main caregiver; after the interview a 2 d prospective food diary (FD) was completed on behalf of the child. Nutrient intakes from the FFQ and FD were estimated using UK food composition data. Diet quality was assessed from the FFQ and FD according to the child's scores for a principal component analysis-defined dietary pattern (‘prudent’ pattern), characterised by high consumption of fruit, vegetables, water and wholemeal cereals.
Children (n 892) aged 3 years in the Southampton Women's Survey.
Intakes of all nutrients assessed by the FFQ were higher than FD estimates, but there was reasonable agreement in terms of ranking of children (range of Spearman rank correlations for energy-adjusted nutrient intakes, rs = 0·41 to 0·59). Prudent diet scores estimated from the FFQ and FD were highly correlated (r = 0·72). Some family and child characteristics appeared to influence the ability of the FFQ to rank children, most notably the number of child's meals eaten away from home.
The FFQ provides useful information to allow ranking of children at this age with respect to nutrient intake and quality of diet, but may overestimate absolute intakes. Dietary studies of young children need to consider family and child characteristics that may impact on reporting error associated with an FFQ.
It is recognised that eating habits established in early childhood may track into adult life. Developing effective interventions to promote healthier patterns of eating throughout the life course requires a greater understanding of the diets of young children and the factors that influence early dietary patterns. In a longitudinal UK cohort study, we assessed the diets of 1640 children at age 3 years using an interviewer-administered FFQ and examined the influence of maternal and family factors on the quality of the children's diets. To describe dietary quality, we used a principal components analysis-defined pattern of foods that is consistent with healthy eating recommendations. This was termed a ‘prudent’ diet pattern and was characterised by high intakes of fruit, vegetables and wholemeal bread, but by low intakes of white bread, confectionery, chips and roast potatoes. The key influence on the quality of the children's diets was the quality of their mother's diets; alone it accounted for almost a third of the variance in child's dietary quality. Mothers who had better-quality diets, which complied with dietary recommendations, were more likely to have children with comparable diets. This relationship remained strong even after adjustment for all other factors considered, including maternal educational attainment, BMI and smoking, and the child's birth order and the time spent watching television. Our data provide strong evidence of shared family patterns of diet and suggest that interventions to improve the quality of young women's diets could be effective in improving the quality of their children's diets.
The impact of variations in current infant feeding practice on bone mineral accrual is not known. We examined the associations between duration of breast-feeding and compliance with infant dietary guidelines and later bone size and density at age 4 years. At total of 599 (318 boys) mother–child pairs were recruited from the Southampton Women's Survey. Duration of breast-feeding was recorded and infant diet was assessed at 6 and 12 months using FFQ. At 6 and 12 months the most important dietary pattern, defined by principal component analysis, was characterised by high consumption of vegetables, fruits and home-prepared foods. As this was consistent with infant feeding recommendations, it was denoted the ‘infant guidelines’ pattern. At age 4 years, children underwent assessment of whole-body bone size and density using a Hologic Discovery dual-energy X-ray absorptiometry instrument. Correlation methods were used to explore the relationships between infant dietary variables and bone mineral. There was no association between duration of breast-feeding in the first year of life and 4-year bone size or density. ‘Infant guidelines’ pattern scores at 6 and 12 months were also unrelated to bone mass at age 4 years. We observed wide variations in current infant feeding practice, but these variations were not associated with differences in childhood bone mass at age 4 years.
There is growing interest in the use of dietary patterns as measures of exposure in studies of diet–disease relationships. However, relatively little is known about the impact of the type of dietary assessment method on the patterns observed. Using FFQ and food diary data collected from 585 women in early pregnancy we used principal component analysis to define dietary patterns. The first pattern was very similar in both datasets and was termed the ‘prudent’ diet. The second pattern, whilst comparable for the FFQ and food diaries, showed greater variation in coefficients than the prudent pattern; it was termed the ‘Western’ diet. Differences between the FFQ and diary scores were calculated for each woman for both the prudent and Western diet patterns. Of the differences in the prudent diet score, 95 % lay within ± 1·58 sd of the mean, and 95 % of the differences in the Western diet scores lay within ± 2·22 sd of the mean. Pearson's correlation coefficients were 0·67 (P < 0·001) for the prudent diet score and 0·35 (P < 0·001) for the Western diet score. The agreement between the FFQ and diary scores was lowest amongst respondents who were younger, had lower educational attainment and whose diaries were coded as ‘poor, probably incomplete’, although these effects were small. The first two dietary patterns identified in this cohort of pregnant women appear to be defined similarly by both FFQ and diary data, suggesting that FFQ data provide useful information on dietary patterns.
Email your librarian or administrator to recommend adding this to your organisation's collection.