Pain symptoms and sleep problems among school-aged children. Long-term prevalence changes, and pain symptoms as predictors of later mental health

Children’s pain symptoms and sleep problems are among the most common health complaints. They distract children from activities, decrease the quality of life, contribute to a significant economic burden, and have shown continuity into adulthood. The main aims of this thesis were to investigate long-term changes in the prevalence of pain symptoms and sleep problems among Finnish school-aged children, and the later mental health of those who in childhood experience pain. Prevalence, co-occurrence, and associated psychosocial factors of pain symptoms and sleep problems were also assessed. In study I, prevalence changes in eight-year-old children’s pain symptoms and sleep problems were investigated in three cross-sectional population-based samples (years 1989: n=1038, 1999: n=1035, and 2005: n=1030). In study II, cross-sectional associations between pain symptoms, sleep problems, and psychosocial factors were assessed among 13-18-year-old adolescents (n=2476). In studies III and IV, associations between pain symptoms at age eight (n=6017), and register-based data on antidepressant use and severe suicidality by age 24, were examined in a nationwide birth cohort. Pain symptoms and sleep problems were common and often co-occurred. A considerable number of children’s pain symptoms remained unrecognized by the parents. The prevalence of pain symptoms, sleep problems, and multiple concurrent symptoms approximately doubled from 1989 to 2005. Psychiatric difficulties or demographic factors did not explain the increase. Psychosocial factors that were associated with pain, sleep problems, and a higher number of symptoms, were female sex, psychological difficulties, emotional symptoms, smoking, victimization, and feeling not cared about by teachers. In longitudinal analyses, the child’s own report of headache, and to a smaller degree the parental report of the child’s abdominal pain predicted later antidepressant use. Parental report of the child’s abdominal pain predicted severe suicidality among males. If one of the symptoms is present, health care professionals should inquire about other symptoms as well. Questions should be directed to the children, not only to their parents. Inquiring about psychiatric difficulties, substance use, victimization, and relations with teachers should be included as a part of the assessment. Further studies are needed to clarify the reasons that underlie the increased prevalence rates, and the factors that may increase or decrease the risk for later mental health problems among pain-suffering children.

Determinants of Bone Strength and Predictors of Hip Fracture among Finnish Adults. Results from the Health 2000 Survey and the Mini-Finland Health Survey

The objective of this thesis was to identify the determinants of bone strength and predictors of hip fracture in representative samples of Finnish adults. A secondary objective was to construct a simple multifactorial model for hip fracture prediction over a 10-year follow-up period. The study was based on the Health 2000 Survey conducted during 2000 to 2001 (men and women aged 30 years or over, n=6 035) and the Mini-Finland Health Survey conducted during 1978 to 1980 (women aged 45 years or over, n=2 039). Study subjects participated in health interviews and comprehensive health examination. In the Health 2000 Survey, bone strength was assessed by means of calcaneal quantitative ultrasound (QUS). The follow-up information about hip fractures was drawn from the National Hospital Discharge Register. In this study, age, weight, height, serum 25-hydroxyvitamin D (S-25(OH)D), physical activity, smoking and alcohol consumption as well as menopause and eventual HRT in women were found to be associated with calcaneal broadband ultrasound attenuation (BUA) and speed of sound (SOS). Parity was associated with a decreased risk of hip fracture in postmenopausal women. Age, height, weight or waist circumference, quantitative ultrasound index (QUI), S-25(OH)D and fall-related factors, such as maximal walking speed, Parkinson’s disease, and the number of prescribed CNS active medication were significant independent predictors of hip fracture. At the population level, the incremental value of QUS appeared to be minor in hip fracture prediction when the fall-related risk factors were taken into account. A simple multifactorial model for hip fracture prediction presented in this study was based on readily available factors (age, gender, height, waist circumference, and fallrelated factors). Prospective studies are needed to test this model in patient-based study populations.

Quantification of Toxin Biosynthesis Genes In Cyanobacteria and Dinoflagellates - Genetic Factors as Predictors of Toxin Production in the Environment

Harmful algal blooms (HABs) are events caused by the massive proliferation of microscopic, often photosynthetic organisms that inhabit both fresh and marine waters. Although HABs are essentially a natural phenomenon, they now cause worldwide concern. Recent anthropogenic effects, such as climate change and eutrophication via nutrient runoff, can be seen in their increased prevalence and severity. Cyanobacteria and dinoflagellates are often the causative organisms of HABs. In addition to adverse effects caused by the sheer biomass, certain species produce highly potent toxic compounds: hepatotoxic microcystins are produced exclusively by cyanobacteria and neurotoxic saxitoxins, also known as paralytic shellfish toxins (PSTs), by both cyanobacteria and dinoflagellates. Specific biosynthetic genes in the cyanobacterial genomes direct the production of microcystin and paralytic shellfish toxins. Recently also the first paralytic shellfish toxin gene sequences from dinoflagellate genomes have been elucidated. The public health risks presented by HABs are evident, but the monitoring and prediction of toxic events is challenging. Characterization of the genetic background of toxin biosynthesis, including that of microcystins and paralytic shellfish toxins, has made it possible to develop highly sensitive molecular tools which have shown promise in the monitoring and study of potentially toxic microalgae. In this doctoral work, toxin-specific genes were targeted in the developed PCR and qPCR assays for the detection and quantification of potentially toxic cyanobacteria and dinoflagellates in the environment. The correlation between the copy numbers of the toxin biosynthesis genes and toxin production were investigated to assess whether the developed methods could be used to predict toxin concentrations. The nature of the correlation between gene copy numbers and amount of toxin produced varied depending on the targeted gene and the producing organism. The combined mcyB copy numbers of three potentially microcystin-producing cyanobacterial genera showed significant positive correlation to the observed total toxin production. However, the presence of PST-specific sxtA, sxtG, and sxtB genes of cyanobacterial origin was found to be a poor predictor of toxin production in the studied area. Conversely, the dinoflagellate sxtA4 was a good qualitative indicator of a neurotoxic bloom both in the laboratory and in the field, and population densities reflected well the observed toxin concentrations. In conclusion, although the specificity of each potential targeted toxin biosynthesis gene must be assessed individually during method development, the results obtained in this doctoral study support the use of quantitative PCR -based approaches in the monitoring of toxic cyanobacteria and dinoflagellates.

Modeling of burden distribution in the blast furnace

The blast furnace is the main ironmaking production unit in the world which converts iron ore with coke and hot blast into liquid iron, hot metal, which is used for steelmaking. The furnace acts as a counter-current reactor charged with layers of raw material of very different gas permeability. The arrangement of these layers, or burden distribution, is the most important factor influencing the gas flow conditions inside the furnace, which dictate the efficiency of the heat transfer and reduction processes. For proper control the furnace operators should know the overall conditions in the furnace and be able to predict how control actions affect the state of the furnace. However, due to high temperatures and pressure, hostile atmosphere and mechanical wear it is very difficult to measure internal variables. Instead, the operators have to rely extensively on measurements obtained at the boundaries of the furnace and make their decisions on the basis of heuristic rules and results from mathematical models. It is particularly difficult to understand the distribution of the burden materials because of the complex behavior of the particulate materials during charging. The aim of this doctoral thesis is to clarify some aspects of burden distribution and to develop tools that can aid the decision-making process in the control of the burden and gas distribution in the blast furnace. A relatively simple mathematical model was created for simulation of the distribution of the burden material with a bell-less top charging system. The model developed is fast and it can therefore be used by the operators to gain understanding of the formation of layers for different charging programs. The results were verified by findings from charging experiments using a small-scale charging rig at the laboratory. A basic gas flow model was developed which utilized the results of the burden distribution model to estimate the gas permeability of the upper part of the blast furnace. This combined formulation for gas and burden distribution made it possible to implement a search for the best combination of charging parameters to achieve a target gas temperature distribution. As this mathematical task is discontinuous and non-differentiable, a genetic algorithm was applied to solve the optimization problem. It was demonstrated that the method was able to evolve optimal charging programs that fulfilled the target conditions. Even though the burden distribution model provides information about the layer structure, it neglects some effects which influence the results, such as mixed layer formation and coke collapse. A more accurate numerical method for studying particle mechanics, the Discrete Element Method (DEM), was used to study some aspects of the charging process more closely. Model charging programs were simulated using DEM and compared with the results from small-scale experiments. The mixed layer was defined and the voidage of mixed layers was estimated. The mixed layer was found to have about 12% less voidage than layers of the individual burden components. Finally, a model for predicting the extent of coke collapse when heavier pellets are charged over a layer of lighter coke particles was formulated based on slope stability theory, and was used to update the coke layer distribution after charging in the mathematical model. In designing this revision, results from DEM simulations and charging experiments for some charging programs were used. The findings from the coke collapse analysis can be used to design charging programs with more stable coke layers.