80 research outputs found
Prevalence of vitamin D deficiency and insufficiency among schoolchildren in Greece: The role of sex, degree of urbanisation and seasonality
The current study was aiming to report the prevalence of suboptimal vitamin D status among schoolchildren in Greece and investigate the role of sex, urbanisation and seasonality on vitamin D status. A sample of 2386 schoolchildren (9–13 years old) from four distinct prefectures was examined. The prevalence of 25-hydroxyvitamin D (25(OH)D) concentration <30 and <50 nmol/l (vitamin D deficiency and insufficiency respectively) was 5·2 and 52·5 %, respectively. Girls had a higher prevalence of 25(OH)D<30 (7·2 v. 3·2 %) and 50 nmol/l (57·0 v. 48·0 %) than boys (P<0·001). The highest prevalence rates of 25(OH)D<30 and 50 nmol/l (9·1 and 73·1 %, respectively) were observed during spring (April to June), whereas the lowest (1·5 and 31·9 %, respectively) during autumn (October to December). The prevalence of 25(OH)D<50 nmol/l was higher in urban/semi-urban than rural regions, particularly during spring months (74·6 v. 47·2 %; P<0·001). Female sex, urban/semi-urban region of residence and spring months were found to increase the likelihood of vitamin D deficiency and insufficiency, with the highest OR observed for spring months (7·47; 95 % CI 3·23, 17·3 and 5·14; 95 % CI 3·84, 6·89 for 25(OH)D<30 and 50 nmol/l respectively). In conclusion, despite the southerly latitude, the prevalence of low vitamin D status among primary schoolchildren in Greece is comparable to or exceeds the prevalence reported among children and adolescents on a European level. Sub-populations at highest risk are girls in urban/semi-urban areas during spring months, thus indicating the need for effective initiatives to support adequate vitamin D status in these population groups
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Effects of a web-based personalized intervention on physical activity in European adults: a randomized controlled trial
Background: The high prevalence of physical inactivity worldwide calls for innovative and more effective ways to promote physical activity (PA). There are limited objective data on the effectiveness of Web-based personalized feedback on increasing PA in adults.
Objective: It is hypothesized that providing personalized advice based on PA measured objectively alongside diet, phenotype, or genotype information would lead to larger and more sustained changes in PA, compared with nonpersonalized advice.
Methods: A total of 1607 adults in seven European countries were randomized to either a control group (nonpersonalized advice, Level 0, L0) or to one of three personalized groups receiving personalized advice via the Internet based on current PA plus diet (Level 1, L1), PA plus diet and phenotype (Level 2, L2), or PA plus diet, phenotype, and genotype (Level 3, L3). PA was measured for 6 months using triaxial accelerometers, and self-reported using the Baecke questionnaire. Outcomes were objective and self-reported PA after 3 and 6 months.
Results: While 1270 participants (85.81% of 1480 actual starters) completed the 6-month trial, 1233 (83.31%) self-reported PA at both baseline and month 6, but only 730 (49.32%) had sufficient objective PA data at both time points. For the total cohort after 6 months, a greater improvement in self-reported total PA (P=.02) and PA during leisure (nonsport) (P=.03) was observed in personalized groups compared with the control group. For individuals advised to increase PA, we also observed greater improvements in those two self-reported indices (P=.006 and P=.008, respectively) with increased personalization of the advice (L2 and L3 vs L1). However, there were no significant differences in accelerometer results between personalized and control groups, and no significant effect of adding phenotypic or genotypic information to the tailored feedback at month 3 or 6. After 6 months, there were small but significant improvements in the objectively measured physical activity level (P<.05), moderate PA (P<.01), and sedentary time (P<.001) for individuals advised to increase PA, but these changes were similar across all groups.
Conclusions: Different levels of personalization produced similar small changes in objective PA. We found no evidence that personalized advice is more effective than conventional “one size fits all” guidelines to promote changes in PA in our Web-based intervention when PA was measured objectively. Based on self-reports, PA increased to a greater extent with more personalized advice. Thus, it is crucial to measure PA objectively in any PA intervention study
Association between diet-quality scores, adiposity, total cholesterol and markers of nutritional status in European adults: findings from the Food4Me study
Diet-quality scores (DQS), which are developed across the globe, are used to define adherence to specific eating patterns and have been associated with risk of coronary heart disease and type-II diabetes. We explored the association between five diet-quality scores (Healthy Eating Index, HEI; Alternate Healthy Eating Index, AHEI; MedDietScore, MDS; PREDIMED Mediterranean Diet Score, P-MDS; Dutch Healthy Diet-Index, DHDI) and markers of metabolic health (anthropometry, objective physical activity levels (PAL), and dried blood spot total cholesterol (TC), total carotenoids, and omega-3 index) in the Food4Me cohort, using regression analysis. Dietary intake was assessed using a validated Food Frequency Questionnaire. Participants (n = 1480) were adults recruited from seven European Union (EU) countries. Overall, women had higher HEI and AHEI than men (p < 0.05), and scores varied significantly between countries. For all DQS, higher scores were associated with lower body mass index, lower waist-to-height ratio and waist circumference, and higher total carotenoids and omega-3-index (p trends < 0.05). Higher HEI, AHEI, DHDI, and P-MDS scores were associated with increased daily PAL, moderate and vigorous activity, and reduced sedentary behaviour (p trend < 0.05). We observed no association between DQS and TC. To conclude, higher DQS, which reflect better dietary patterns, were associated with markers of better nutritional status and metabolic health
Prevalence of obesity in preschool Greek children, in relation to parental characteristics and region of residence
<p>Abstract</p> <p>Background</p> <p>The aim of this retrospective cohort study was to record the prevalence of overweight and obesity in relation to parental education level, parental body mass index and region of residence, in preschool children in Greece.</p> <p>Methods</p> <p>A total of 2374 children (1218 males and 1156 females) aged 1–5 years, stratified by parental educational level (Census 1999), were examined from 105 nurseries in five counties, from April 2003 to July 2004, Weight (kg) and height (cm) were obtained and BMI (kg/m<sup>2</sup>) was calculated. Both the US Centers for Disease Control (CDC) and the International Obesity Task Force (IOTF) methods were used to classify each child as "normal", "at risk of overweight" and "overweight". Parental demographic characteristics, such as age and educational level and parental anthropometrical data, such as stature and body weight, were also recorded with the use of a specifically designed questionnaire.</p> <p>Results</p> <p>The overall estimates of at risk of overweight and overweight using the CDC method was 31.9%, 10.6 percentage points higher than the IOTF estimate of 21.3% and this difference was significant (p < 0.001). Children with one obese parent had 91% greater odds for being overweight compared to those with no obese parent, while the likelihood for being overweight was 2.38 times greater for children with two obese parents in the multivariate model.</p> <p>Conclusion</p> <p>Both methods used to assess prevalence of obesity have demonstarted that a high percentage of the preschool children in our sample were overweight. Parental body mass index was also shown to be an obesity risk factor in very young children.</p
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Correlates of overall and central obesity in adults from seven European countries: findings from the Food4Me Study
To identify predictors of obesity in adults and investigate to what extent these predictors are independent of other major confounding factors. Data collected at baseline from 1441 participants from the Food4Me study conducted in seven European countries were included in this study. A food frequency questionnaire was used to measure dietary intake. Accelerometers were used to assess physical activity levels (PA), whereas participants self-reported their body weight, height and waist circumference via the internet. The main factors associated (p < 0.05) with higher BMI per 1-SD increase in the exposure were age (β:1.11 kg/m2), intakes of processed meat (β:1.04 kg/m2), red meat (β:1.02 kg/m2), saturated fat (β:0.84 kg/m2), monounsaturated fat (β:0.80 kg/m2), protein (β:0.74 kg/m2), total energy intake (β:0.50 kg/m2), olive oil (β:0.36 kg/m2), sugar sweetened carbonated drinks (β:0.33 kg/m2) and sedentary time (β:0.73 kg/m2). In contrast, the main factors associated with lower BMI per 1-SD increase in the exposure were PA (β:-1.36 kg/m2), intakes of wholegrains (β:-1.05 kg/m2), fibre (β:-1.02 kg/m2), fruits and vegetables (β:-0.52 kg/m2), nuts (β:-0.52 kg/m2), polyunsaturated fat (β:-0.50 kg/m2), Healthy Eating Index (β:-0.42 kg/m2), Mediterranean diet score (β:-0.40 kg/m2), oily fish (β:-0.31 kg/m2), dairy (β:-0.31 kg/m2) and fruit juice (β:-0.25 kg/m2). These findings are important for public health and suggest that promotion of increased PA, reducing sedentary behaviours and improving the overall quality of dietary patterns are important strategies for addressing the existing obesity epidemic and associated disease burden
Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood : An individual participant data meta-analysis
Background Maternal obesity and excessive gestational weight gain may have persistent effects on offspring fat development. However, it remains unclear whether these effects differ by severity of obesity, and whether these effects are restricted to the extremes of maternal body mass index (BMI) and gestational weight gain. We aimed to assess the separate and combined associations of maternal BMI and gestational weight gain with the risk of overweight/obesity throughout childhood, and their population impact. Methods and findings We conducted an individual participant data meta-analysis of data from 162,129 mothers and their children from 37 pregnancy and birth cohort studies from Europe, North America, and Australia. We assessed the individual and combined associations of maternal pre-pregnancy BMI and gestational weight gain, both in clinical categories and across their full ranges, with the risks of overweight/obesity in early (2.0-5.0 years), mid (5.0-10.0 years) and late childhood (10.0-18.0 years), using multilevel binary logistic regression models with a random intercept at cohort level adjusted for maternal sociodemographic and lifestylerelated characteristics. We observed that higher maternal pre-pregnancy BMI and gestational weight gain both in clinical categories and across their full ranges were associated with higher risks of childhood overweight/obesity, with the strongest effects in late childhood (odds ratios [ORs] for overweight/obesity in early, mid, and late childhood, respectively: OR 1.66 [95% CI: 1.56, 1.78], OR 1.91 [95% CI: 1.85, 1.98], and OR 2.28 [95% CI: 2.08, 2.50] for maternal overweight; OR 2.43 [95% CI: 2.24, 2.64], OR 3.12 [95% CI: 2.98, 3.27], and OR 4.47 [95% CI: 3.99, 5.23] for maternal obesity; and OR 1.39 [95% CI: 1.30, 1.49], OR 1.55 [95% CI: 1.49, 1.60], and OR 1.72 [95% CI: 1.56, 1.91] for excessive gestational weight gain). The proportions of childhood overweight/obesity prevalence attributable to maternal overweight, maternal obesity, and excessive gestational weight gain ranged from 10.2% to 21.6%. Relative to the effect of maternal BMI, excessive gestational weight gain only slightly increased the risk of childhood overweight/obesity within each clinical BMI category (p-values for interactions of maternal BMI with gestational weight gain: p = 0.038, p <0.001, and p = 0.637 in early, mid, and late childhood, respectively). Limitations of this study include the self-report of maternal BMI and gestational weight gain for some of the cohorts, and the potential of residual confounding. Also, as this study only included participants from Europe, North America, and Australia, results need to be interpreted with caution with respect to other populations. Conclusions In this study, higher maternal pre-pregnancy BMI and gestational weight gain were associated with an increased risk of childhood overweight/obesity, with the strongest effects at later ages. The additional effect of gestational weight gain in women who are overweight or obese before pregnancy is small. Given the large population impact, future intervention trials aiming to reduce the prevalence of childhood overweight and obesity should focus on maternal weight status before pregnancy, in addition to weight gain during pregnancy.Peer reviewe
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