Preadolescents and Their Mothers as Oral Health-Promoting Actors : Non-biologic Determinants of Oral Health among Turkish and Finnish Preadolescents

Is oral health becoming a part of the global health culture? Oral health seems to turn out to be part of the global health culture, according to the findings of a thesis-research, Institute of Dentistry, University of Helsinki. The thesis is entitled as “Preadolescents and Their Mothers as Oral Health-Promoting Actors: Non-biologic Determinants of Oral Health among Turkish and Finnish Preadolescents.” The research was supervised by Prof.Murtomaa and led by Dr.A.Basak Cinar. It was conducted as a cross-sectional study of 611 Turkish and 223 Finnish school preadolescents in Istanbul and Helsinki, from the fourth, fifth, and sixth grades, aged 10 to 12, based on self-administered and pre-tested health behavior questionnaires for them and their mothers as well as the youth’s oral health records. Clinically assessed dental status (DMFT) and self-reported oral health of Turkish preadolescents was significantly poorer than the Finns`. A similar association occurred for well-being measures (height and weight, self-esteem), but not for school performance. Turkish preadolescents were more dentally anxious and reported lower mean values of toothbrushing self-efficacy and dietary self-efficacy than did Finns. The Turks less frequently reported recommended oral health behaviors (twice daily or more toothbrushing, sweet consumption on 2 days or less/week, decreased between-meal sweet consumption) than did the Finns. Turkish mothers reported less frequently dental health as being above average and recommended oral health behaviors as well as regular dental visits. Their mean values for dental anxiety was higher and self-efficacy on implementation of twice-daily toothbrushing were lower than those of the Finnish. Despite these differences between the Turks and Finns, the associations found in common for all preadolescents, regardless of cultural differences and different oral health care systems, assessed for the first time in a holistic framework, were as follows: There seems to be interrelation between oral health and general-well being (body height-weight measures, school performance, and self-esteem) among preadolescents: • The body height was an explanatory factor for dental health, underlining the possible common life-course factors for dental health and general well-being. • Better school performance, high levels of self-esteem and self-efficacy were interrelated and they contributed to good oral health. • Good school performance was a common predictor for twice-daily toothbrushing. Self-efficacy and maternal modelling have significant role for maintenance and improvement of both oral- and general health- related behaviors. In addition, there is need for integration of self-efficacy based approaches to promote better oral health. • All preadolescents with high levels of self-efficacy were more likely to report more frequent twice-daily toothbrushing and less frequent sweet consumption. • All preadolescents were likely to imitate toothbrushing and sweet consumption behaviors of their mothers. • High levels of self-efficacy contributed to low dental anxiety in various patterns in both groups. As a conclusion: • Many health-detrimental behaviors arise from the school age years and are unlikely to change later. Schools have powerful influences on children’s development and well-being. Therefore, oral health promotion in schools should be integrated into general health promotion, school curricula, and other activities. • Health promotion messages should be reinforced in schools, enabling children and their families to develop lifelong sustainable positive health-related skills (self-esteem, self-efficacy) and behaviors. • Placing more emphasis on behavioral sciences, preventive approaches, and community-based education during undergraduate studies should encourage social responsibility and health-promoting roles among dentists. Attempts to increase general well-being and to reduce oral health inequalities among preadolescents will remain unsuccessful if the individual factors, as well as maternal and societal influences, are not considered by psycho-social holistic approaches.

Search for genetic variants influencing human height

Human growth and attained height are determined by a combination of genetic and environmental effects and in modern Western societies > 80% of the observed variation in height is determined by genetic factors. Height is a fundamental human trait that is associated with many socioeconomic and psychosocial factors and health measures, however little is known of the identity of the specific genes that influence height variation in the general population. This thesis work aimed to identify the genetic variants that influence height in the general population by genome-wide linkage analysis utilizing large family samples. The study focused on analysis of three separate sets of families consisting of: 1) 1,417 individuals from 277 Finnish families (FinnHeight), 2) 8,450 individuals from 3,817 families from Australia and Europe (EUHeight) and 3) 9,306 individuals from 3,302 families from the United States (USHeight). The most significant finding in this study was found in the Finnish family sample where we a locus in the chromosomal region 1p21 was linked to adult height. Several regions showed evidence for linkage in the Australian, European and US families with 8q21 and 15q25 being the most significant. The region on 1p21 was followed up with further studies and we were able to show that the collagen 11-alpha-1 gene (COL11A1) residing at this location was associated with adult height. This association was also confirmed in an independent Finnish population cohort (Health 2000) consisting of 6,542 individuals. From this population sample, we estimated that homozygous males and females for this gene variant were 1.1 and 0.6 cm taller than the respective controls. In this thesis work we identified a gene variant in the COL11A1 gene that influences human height, although this variant alone explains only 0.1% of height variation in the Finnish population. We also demonstrated in this study that special stratification strategies such as performing sex-limited analyses, focusing on dizygous twin pairs, analyzing ethnic groups within a population separately and utilizing homogenous populations such as the Finns can improve the statistical power of finding QTL significantly. Also, we concluded from the results of this study that even though genetic effects explain a great proportion of height variance, it is likely that there are tens or even hundreds of genes with small individual effects underlying the genetic architecture of height.

The effect of temperature on height growth of Scots pine in northern Finland

The effect of temperature on height growth of Scots pine in the northern boreal zone in Lapland was studied in two different time scales. Intra-annual growth was monitored in four stands in up to four growing seasons using an approximately biweekly measurement interval. Inter-annual growth was studied using growth records representing seven stands and five geographical locations. All the stands were growing on a dry to semi-dry heath that is a typical site type for pine stands in Finland. The applied methodology is based on applied time-series analysis and multilevel modelling. Intra-annual elongation of the leader shoot correlated with temperature sum accumulation. Height growth ceased when, on average, 41% of the relative temperature sum of the site was achieved (observed minimum and maximum were 38% and 43%). The relative temperature sum was calculated by dividing the actual temperature sum by the long-term mean of the total annual temperature sum for the site. Our results suggest that annual height growth ceases when a location-specific temperature sum threshold is attained. The positive effect of the mean July temperature of the previous year on annual height increment proved to be very strong at high latitudes. The mean November temperature of the year before the previous had a statistically significantly effect on height increment in the three northernmost stands. The effect of mean monthly precipitation on annual height growth was statistically insignificant. There was a non-linear dependence between length and needle density of annual shoots. Exceptionally low height growth results in high needle-density, but the effect is weaker in years of average or good height growth. Radial growth and next year s height growth are both largely controlled by current July temperature. Nevertheless, their growth variation in terms of minimum and maximum is not necessarily strongly correlated. This is partly because height growth is more sensitive to changes in temperature. In addition, the actual effective temperature period is not exactly the same for these two growth components. Yet, there is a long-term balance that was also statistically distinguishable; radial growth correlated significantly with height growth with a lag of 2 years. Temperature periods shorter than a month are more effective variables than mean monthly values, but the improvement is on the scale of modest to good when applying Julian days or growing-degree-days as pointers.

Effects of seed origin latitude on the timing of height growth cessation and field performance of silver birch

The aim of this thesis was to increase our knowledge about the effects of seed origin on the timing of height growth cessation and field performance of silver birch from different latitudes, with special attention paid to the browsing damage by moose in young birch plantations. The effect of seed origin latitude and sowing time on timing of height growth cessation of first-year seedlings was studied in a greenhouse experiment with seven seed origins (lat. 58º - 67ºN). Variation in critical night length (CNL) for 50 % bud set within two latitudinally distant stands (60º and 67ºN) was studied in three phytotron experiments. Browsing by moose on 5-11 -year-old silver birch saplings from latitudinally different seed origins (53º - 67ºN) was studied in a field experiment in southern Finland. Yield and stem quality of 22-year-old silver birch trees of Baltic, Finnish and Russian origin (54º - 63ºN) and the effect of latitudinal seed transfers were studied in two provenance trials at Tuusula, southern and Viitasaari, central Finland. The timing of height growth cessation depended systematically on latitude of seed origin and sowing date. The more northern the seed origin, the earlier the growth cessation and the shorter the growth period. Later sowing dates delayed growth cessation but also shortened the growth period. The mean CNL of the southern ecotype was longer, 6.3 ± 0.2 h (95 % confidence interval), than that of the northern ecotype, 3.1 ± 0.3 h. Within-ecotype variance of the CNL was higher in the northern ecotype (0.484 h2) than in the southern ecotype (0.150 h2). Browsing by moose decreased with increasing latitude of seed origin and sapling height. Origins transferred from more southern latitudes were more heavily browsed than the more northern native ones. Southern Finnish seed origins produced the highest volume per unit area in central Finland (lat. 63º11'N). Estonian and north Latvian stand seed origins, and the southern Finnish plus tree origins, were the most productive ones in southern Finland (lat. 60º21'N). Latitudinal seed transfer distance had a significant effect on survival, stem volume/ha and proportion of trees with a stem defect. The relationship of both survival and stem volume/ha to the latitudinal seed transfer distance was curvilinear. Volume was increased by transferring seed from ca. 2 degrees of latitude from the south. A longer transfer from the south, and transfer from the north, decreased the yield. The proportion of trees with a stem defect increased linearly in relation to the latitudinal seed transfer distance from the south.

Discovering hidden structures in molecular data using a Bayesian partition model approach

Advancements in the analysis techniques have led to a rapid accumulation of biological data in databases. Such data often are in the form of sequences of observations, examples including DNA sequences and amino acid sequences of proteins. The scale and quality of the data give promises of answering various biologically relevant questions in more detail than what has been possible before. For example, one may wish to identify areas in an amino acid sequence, which are important for the function of the corresponding protein, or investigate how characteristics on the level of DNA sequence affect the adaptation of a bacterial species to its environment. Many of the interesting questions are intimately associated with the understanding of the evolutionary relationships among the items under consideration. The aim of this work is to develop novel statistical models and computational techniques to meet with the challenge of deriving meaning from the increasing amounts of data. Our main concern is on modeling the evolutionary relationships based on the observed molecular data. We operate within a Bayesian statistical framework, which allows a probabilistic quantification of the uncertainties related to a particular solution. As the basis of our modeling approach we utilize a partition model, which is used to describe the structure of data by appropriately dividing the data items into clusters of related items. Generalizations and modifications of the partition model are developed and applied to various problems. Large-scale data sets provide also a computational challenge. The models used to describe the data must be realistic enough to capture the essential features of the current modeling task but, at the same time, simple enough to make it possible to carry out the inference in practice. The partition model fulfills these two requirements. The problem-specific features can be taken into account by modifying the prior probability distributions of the model parameters. The computational efficiency stems from the ability to integrate out the parameters of the partition model analytically, which enables the use of efficient stochastic search algorithms.

Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.

Clustering Users of Online Content Service

Online content services can greatly benefit from personalisation features that enable delivery of content that is suited to each user's specific interests. This thesis presents a system that applies text analysis and user modeling techniques in an online news service for the purpose of personalisation and user interest analysis. The system creates a detailed thematic profile for each content item and observes user's actions towards content items to learn user's preferences. A handcrafted taxonomy of concepts, or ontology, is used in profile formation to extract relevant concepts from the text. User preference learning is automatic and there is no need for explicit preference settings or ratings from the user. Learned user profiles are segmented into interest groups using clustering techniques with the objective of providing a source of information for the service provider. Some theoretical background for chosen techniques is presented while the main focus is in finding practical solutions to some of the current information needs, which are not optimally served with traditional techniques.

Test of the Clustering Hypothesis in the Helsinki Exchanges

This paper investigates the clustering pattern in the Finnish stock market. Using trading volume and time as factors capturing the clustering pattern in the market, the Keim and Madhavan (1996) and the Engle and Russell (1998) model provide the framework for the analysis. The descriptive and the parametric analysis provide evidences that an important determinant of the famous U-shape pattern in the market is the rate of information arrivals as measured by large trading volumes and durations at the market open and close. Precisely, 1) the larger the trading volume, the greater the impact on prices both in the short and the long run, thus prices will differ across quantities. 2) Large trading volume is a non-linear function of price changes in the long run. 3) Arrival times are positively autocorrelated, indicating a clustering pattern and 4) Information arrivals as approximated by durations are negatively related to trading flow.