Browsing by Subject "OBESITY PREVENTION"

Sort by: Order: Results:

Now showing items 1-5 of 5
  • Kaukonen, Riikka; Lehto, Elviira; Ray, Carola; Vepsäläinen, Henna; Nissinen, Kaija; Korkalo, Liisa; Koivusilta, Leena; Sajaniemi, Nina; Erkkola, Maijaliisa; Roos, Eva (2019)
    Although evidence exists of the association between children's temperament and weight, only few studies have examined how temperament is associated with actual food consumption among preschoolers. We examined concurrent associations between children's temperament and the consumption of different foods, and investigated whether the association between children's temperament and vegetable consumption is mediated by vegetable-related parenting practices. We utilized the data from the cross-sectional DAGIS study of 864 preschool children aged between three to six and their families, conducted between 2015 and 2016 in Finland. The parents reported their children's temperament, food consumption, and their vegetable-related parenting practices. Adjusted logistic regression analyses found positive associations between surgency and vegetable consumption as well as between effortful control and vegetable consumption. Both associations were mediated by one examined vegetable-related parenting practice: enhanced availability and autonomy support. No associations were found between children's negative affectivity and food consumption or vegetable-related parenting practices. In conclusion, children's temperament may be an important factor behind food-related parenting practices and children's diet. However, further longitudinal research and research covering different food-related parenting practices and home environment factors is necessary to better understand the complex associations between temperament and food consumption among young children.
  • Ahrens, W.; Siani, A.; Adan, R.; De Henauw, S.; Eiben, G.; Gwozdz, W.; Hebestreit, A.; Hunsberger, M.; Kaprio, J.; Krogh, V.; Lissner, L.; Molnar, D.; Moreno, L. A.; Page, A.; Pico, C.; Reisch, L.; Smith, R. M.; Tornaritis, M.; Veidebaum, T.; Williams, G.; Pohlabelnu, H.; Pigeot, I.; I Family Consortium (2017)
  • Lehto, Reetta; Ray, Carola; Korkalo, Liisa; Vepsäläinen, Henna; Nissinen, Kaija; Koivusilta, Leena; Roos, Eva; Erkkola, Maijaliisa (2019)
    Preschool is a major factor affecting food consumption among young children in Finland, given that most preschoolers eat three meals a day in that setting. Thus, it is important to recognise the determinants of dietary intake at preschool. The aim of this study was to examine food-related factors at the preschool and manager level, and their association with the dietary intake of children in childcare. The study was a part of the cross-sectional DAGIS survey conducted in 2015 to 2016 in Finland. The managers of 58 preschools filled in a questionnaire related to food and nutrition at their preschools. Preschool personnel kept food records for the children (n = 585) on two preschool days. Multilevel linear and logistic regression analyses were conducted with age, gender, and municipality as covariates, preschool-level factors as independent variables, and children's vegetable (g/day) and fruit (yes vs. no) consumption and fibre intake (g/MJ) as outcome variables. Having many written food policies in the preschool was associated with a higher intake of vegetables (p = 0.01) and fibre (p = 0.03) among the children. Having at least two out of three cooperation-related challenges with the catering service was associated with a higher intake of fibre (p = 0.03) and lower odds of eating fruit (p = 0.01). Factors that are relatively distal from meal situations may have an effect, and should be taken into account in the promotion of healthy eating at preschool, but more studies are needed.
  • Gakidou, Emmanuela; Afshin, Ashkan; Abajobir, Amanuel Alemu; Abate, Kalkidan Hassen; Abbafati, Cristiana; Abbas, Kaja M.; Abd-Allah, Foad; Abdulle, Abdishakur M.; Abera, Semaw Ferede; Aboyans, Victor; Abu-Raddad, Laith J.; Abu-Rmeileh, Niveen M. E.; Abyu, Gebre Yitayih; Adedeji, Isaac Akinkunmi; Adetokunboh, Olatunji; Afarideh, Mohsen; Agrawal, Anurag; Agrawal, Sutapa; Kiadaliri, Aliasghar Ahmad; Ahmadieh, Hamid; Ahmed, Muktar Beshir; Aichour, Amani Nidhal; Aichour, Ibtihel; Aichour, Miloud Taki Eddine; Akinyemi, Rufus Olusola; Akseer, Nadia; Alahdab, Fares; Al-Aly, Ziyad; Alam, Khurshid; Alam, Noore; Alam, Tahiya; Alasfoor, Deena; Alene, Kefyalew Addis; Ali, Komal; Alizadeh-Navaei, Reza; Alkerwi, Ala'a; Alla, Francois; Allebeck, Peter; Al-Raddadi, Rajaa; Alsharif, Ubai; Altirkawi, Khalid A.; Alvis-Guzman, Nelson; Amare, Azmeraw T.; Amini, Erfan; Ammar, Walid; Kivimaki, Mika; Lallukka, Tea; Meretoja, Atte; Meretoja, Tuomo J.; Weiderpass, Elisabete; GBD Risk Factors Collaborators (2017)
    Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22 717 randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according to the GBD 2016 source counting methods. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. Finally, we explored four drivers of trends in attributable burden: population growth, population ageing, trends in risk exposure, and all other factors combined. Findings Since 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and household air pollution showed the most significant declines, while metabolic risks, such as body-mass index and high fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors in terms of attributable DALYs at the global level for men were smoking (124.1 million DALYs [95% UI 111.2 million to 137.0 million]), high systolic blood pressure (122.2 million DALYs [110.3 million to 133.3 million], and low birthweight and short gestation (83.0 million DALYs [78.3 million to 87.7 million]), and for women, were high systolic blood pressure (89.9 million DALYs [80.9 million to 98.2 million]), high body-mass index (64.8 million DALYs [44.4 million to 87.6 million]), and high fasting plasma glucose (63.8 million DALYs [53.2 million to 76.3 million]). In 2016 in 113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains an 9.3% (6.9-11.6) decline in deaths and a 10.8% (8.3-13.1) decrease in DALYs at the global level, while population ageing accounts for 14.9% (12.7-17.5) of deaths and 6.2% (3.9-8.7) of DALYs, and population growth for 12.4% (10.1-14.9) of deaths and 12.4% (10.1-14.9) of DALYs. The largest contribution of trends in risk exposure to disease burden is seen between ages 1 year and 4 years, where a decline of 27.3% (24.9-29.7) of the change in DALYs between 2006 and 2016 can be attributed to declines in exposure to risks. Interpretation Increasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to global disease burden, increasing trends, and variable patterns across countries at the same level of development. GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively small part in the past decade. Copyright (C) The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
  • Lehto, Reetta; Lehto, Elviira; Konttinen, Hanna; Vepsalainen, Henna; Nislin, Mari; Nissinen, Kaija; Vepsalainen, Ciara; Koivusilta, Leena; Erkkola, Maijaliisa; Roos, Eva; Ray, Carola (2019)
    Aims: Certain feeding practices, such as role modeling healthy eating and encouragement are recommended to be used in preschools. Little is known about whether preschool characteristics are associated with the use of these feeding practices. Our aim was to examine whether the socioeconomic status (SES) of the preschool neighborhood is associated with the feeding practices in preschools. Methods: This study was part of the cross-sectional DAGIS study. We studied 66 municipal preschools and 378 early childhood educators (ECEs). Preschool neighborhood SES was assessed with map grid data. Feeding practices were assessed by questionnaires and lunchtime observation. Associations between preschool neighborhood SES and feeding practices were tested with logistic regression analyses adjusted for ECEs' educational level and municipal policies on ECEs' lunch prices, and on birthday foods. Results: The crude model showed that in high-SES neighborhood preschools ECEs were more likely to eat the same lunch as the children (OR 2.46, 95% CI 1.42-4.24) and to reward children with other food for eating vegetables (OR 2.48, 95% CI 1.40-4.41). Furthermore, in high-SES preschools it was less likely that birthday foods outside of the normal menu were available on birthdays (OR 0.29, 95% CI 0.12-0.71). In the adjusted model, rewarding with other food remained associated with preschool neighborhood SES (OR 2.13, 95% CI 1.12-4.07). Conclusions: After adjustments, preschool neighborhood SES was mostly unassociated with the feeding practices in preschools. Municipal policies may have a significant impact on feeding practices and ultimately on young children's food intake in Finland where most children attend municipal preschools.