Potentiometric titrations in nonaqueous cerimetry

Potassium iodide and hydroquinone can be estimated potentiometrically in nonaqueous medium using ammonium nitrato cerate as oxidant. A platinum indicator electrode coupled with either a glass electrode or an antimony electrode as reference electrode, can be used in nonaqueous medium satisfactorily, for following the potentiometric titration. Direct potentiometric titration of xanthate with ammonium nitrato cerate in nonaqueous medium yields slightly lower values than the actual values in presence of platinum indicator electrode.

Psychosocial processes of health behaviour change in a lifestyle intervention : Influences of gender, socioeconomic status and personality

Background: The onset of many chronic diseases such as type 2 diabetes can be delayed or prevented by changes in diet, physical activity and obesity. Known predictors of successful behaviour change include psychosocial factors such as selfefficacy, action and coping planning, and social support. However, gender and socioeconomic differences in these psychosocial mechanisms underlying health behaviour change have not been examined, despite well-documented sociodemographic differences in lifestyle-related mortality and morbidity. Additionally, although stable personality traits (such as dispositional optimism or pessimism and gender-role orientation: agency and communion) are related to health and health behaviour, to date they have rarely been studied in the context of health behaviour interventions. These personality traits might contribute to health behaviour change independently of the more modifiable domain-specific psychosocial factors, or indirectly through them, or moderated by them. The aims were to examine in an intervention setting: (1) whether changes (during the three-month intervention) in psychological determinants (self-efficacy beliefs, action planning and coping planning) predict changes in exercise and diet behaviours over three months and 12 months, (2) the universality assumption of behaviour change theories, i.e. whether preintervention levels and changes in psychosocial determinants are similar among genders and socioeconomic groups, and whether they predict changes in behaviour in a similar way in these groups, (3) whether the personality traits optimism, pessimism, agency and communion predict changes in abdominal obesity, and the nature of their interplay with modifiable and domain-specific psychosocial factors (self-efficacy and social support). Methods: Finnish men and women (N = 385) aged 50 65 years who were at an increased risk for type 2 diabetes were recruited from health care centres to participate in the GOod Ageing in Lahti Region (GOAL) Lifestyle Implementation Trial. The programme aimed to improve participants lifestyle (physical activity, eating) and decrease their overweight. The measurements of self-efficacy, planning, social support and dispositional optimism/pessimism were conducted pre-intervention at baseline (T1) and after the intensive phase of the intervention at three months (T2), and the measurements of exercise at T1, T2 and 12 months (T3) and healthy eating at T1 and T3. Waist circumference, an indicator of abdominal obesity, was measured at T1 and at oneyear (T3) and three-year (T4) follow-ups. Agency and communion were measured at T4 with the Personal Attributes Questionnaire (PAQ). Results: (1) Increases in self-efficacy and planning were associated with three-month increases in exercise (Study I). Moreover, both the post-intervention level and three-month increases (during the intervention) in self-efficacy in dealing with barriers predicted the 12-month increase in exercise, and a high postintervention level of coping plans predicted the 12-month decrease in dietary fat (Study II). One- and three-year waist circumference reductions were predicted by the initial three-month increase in self-efficacy (Studies III, IV). (2) Post-intervention at three months, women had formed more action plans for changing their exercise routines and received less social support for behaviour change than men had. The effects of adoption self-efficacy were similar but change in planning played a less significant role among men (Study I). Examining the effects of socioeconomic status (SES), psychosocial determinants at baseline and their changes during the intervention yielded largely similar results. Exercise barriers self-efficacy was enhanced slightly less among those with low SES. Psychosocial determinants predicted behaviour similarly across all SES groups (Study II). (3) Dispositional optimism and pessimism were unrelated to waist circumference change, directly or indirectly, and they did not influence changes in self-efficacy (Study III). Agency predicted 12-month waist circumference reduction among women. High communion coupled with high social support was associated with waist circumference reduction. However, the only significant predictor of three-year waist circumference reduction was an increase in health-related self-efficacy during the intervention (Study IV). Conclusions: Interventions should focus on improving participants self-efficacy early on in the intervention as well as prompting action and coping planning for health behaviour change. Such changes are likely to be similarly effective among intervention participants regardless of gender and educational level. Agentic orientation may operate via helping women to be less affected by the demands of the self-sacrificing female role and enabling them to assertively focus on their own goals. The earlier mixed results regarding the role of social support in behaviour change may be in part explained by personality traits such as communion.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

The effects of organic environmental toxicants on hard tissue formation in developing tooth : An in vitro study in mice

Dioxins are organic toxicants that are known to impair tooth development, especially dental hard tissue formation. The most toxic dioxin congener is 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Further, clinical studies suggest that maternal smoking during pregnancy can affect child s tooth development. One of the main components of tobacco smoke is the group of non-halogenated polycyclic aromatic hydrocarbons (PAHs), a representative of which is 7,12-dimethylbenz[a]anthracene (DMBA). Tributyltin (TBT), an organic tin compound, has been shown to impair bone mineralization in experimental animals. In addition to exposure to organic toxicants, a well-established cause for enamel hypomineralization is excess fluoride intake. The principal aim of this thesis project was to examine in vitro if, in addition to dioxins, other organic environmental toxicants, like PAHs and organic tin compounds, have adverse effects on tooth development, specifically on formation and mineralization of the major dental hard tissues, the dentin and the enamel. The second aim was to investigate in vitro if fluoride could intensify the manifestation of the detrimental developmental dental effects elicited by TCDD. The study was conducted by culturing mandibular first and second molar tooth germs of E18 NMRI mouse embryos in a Trowell-type organ culture and exposing them to DMBA, TBT, and sodium fluoride (NaF) and/or TCDD at various concentrations during the secretory and mineralization stages of development. Specific methods used were HE-staining for studying cell and tissue morphology, BrdU-staining for cell proliferation, TUNEL-staining for apoptosis, and QPCR, in situ hybridization and immunohistochemistry for the expressions of selected genes associated with mineralization. This thesis work showed that DMBA, TBT, TCDD and NaF interfere with dentin and enamel formation of embryonic mouse tooth in vitro, and that fluoride can potentiate the harmful effect of TCDD. The results suggested that adverse effects of TBT involve altered expression of genes associated with mineralization, and that DMBA and TBT as well as NaF and TCDD together primarily affect dentin mineralization. Since amelogenesis does not start until mineralization of dentin begins, impaired enamel matrix secretion could be a secondary effect. Dioxins, PAHs and organotins are all liposoluble and can be transferred to the infant by breast-feeding. Since doses are usually very low, developmental toxicity on most of the organs is difficult to indentify clinically. However, tooth may act as an indicator of exposure, since the major dental hard tissues, the dentin and the enamel, are not replaced once they have been formed. Thus, disturbed dental hard tissue formation raises the question of more extensive developmental toxicity.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Arrested Drunk Drivers : Trends, social background, recidivism and mortality

The aim of this study was to examine the trends, incidence and recidivism of drunken driving during a 20-year period (1988 - 2007) using the data on all suspected drunken driving in this period. Furthermore, the association between social background and drunken driving, and the mortality of drunk drivers were studied by using administrative register data provided by Statistics Finland. The study was completely register-based. In 1989 - 1991, every year 30,000 drivers were suspected of drunken driving, but the number fell to less than 20,000 by 1994, during the economic recession. The changes in the arrest incidence of the youngest age groups were especially pronounced, most of all in the age group of 18 - 19-year olds. Even though the incidence among youth decreased dramatically, their incidence rate was still twice that of the general population aged 15 - 84 years. Drunken driving was associated with a poor social background among youth and working-aged men and women. For example, a low level of education, unemployment, divorce, and parental factors in youth were associated with a higher risk of being arrested for drunken driving. While a low income was related to more drunken driving among working-aged people, the effect among young persons was the opposite. Every third drunk driver got rearrested during a 15-year period, whereas the estimated rearrest rate was 44%. Findings of drugs only or in combination with alcohol increased the risk of rearrest. The highest rearrest rates were seen among drivers who were under the influence of amphetamines or cannabis. Also male gender, young age, high blood alcohol concentration, and arrest during weekdays and in the daytime predicted rearrest. When compared to the general population, arrested drunk drivers had significant excess mortality. The greatest relative differences were seen in alcohol-related causes of death (including alcohol diseases and alcohol poisoning), accidents, suicides and violence. Also mortality due to other than alcohol-related diseases was elevated among drunk drivers. Drunken driving was associated with multiple factors linked to traffic safety, health and social problems. Social marginalization may expose a person to harmful use of alcohol and drunken driving, and the associations are seen already among the youth. Recidivism is common among drunk drivers, and driving under the influence of illicit and/or medicinal drugs is likely to indicate worse substance abuse problems, judging from the high rearrest rates. High alcohol-related mortality in this population shows that drunken driving is clearly an indicator of alcohol abuse. More effective measures of preventing alcohol-related harms are needed, than merely preventing convicted drunk drivers from driving again.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

Against the Vagueness Argument

In this paper I offer a counterexample to the so called vagueness argument against restricted composition. This will be done in the lines of a recent suggestion by Trenton Merricks, namely by challenging the claim that there cannot be a sharp cut-off point in a composition sequence. It will be suggested that causal powers which emerge when composition occurs can serve as an indicator of such sharp cut-off points. The main example will be the case of a heap. It seems that heaps might provide a very plausible counterexample to the vagueness argument if we accept the idea that four grains of sand is the least number required to compose a heap—the case has been supported by W. D. Hart. My purpose here is not to put forward a new theory of composition, I only wish to refute the vagueness argument and point out that we should be wary of arguments of its form.

Interfacial Phenomena in Pharmaceutical Low Moisture Content Powder Processing

Powders are essential materials in the pharmaceutical industry, being involved in majority of all drug manufacturing. Powder flow and particle size are central particle properties addressed by means of particle engineering. The aim of the thesis was to gain knowledge on powder processing with restricted liquid addition, with a primary focus on particle coating and early granule growth. Furthermore, characterisation of this kind of processes was performed. A thin coating layer of hydroxypropyl methylcellulose was applied on individual particles of ibuprofen in a fluidised bed top-spray process. The polymeric coating improved the flow properties of the powder. The improvement was strongly related to relative humidity, which can be seen as an indicator of a change in surface hydrophilicity caused by the coating. The ibuprofen used in the present study had a d50 of 40 μm and thus belongs to the Geldart group C powders, which can be considered as challenging materials in top-spray coating processes. Ibuprofen was similarly coated using a novel ultrasound-assisted coating method. The results were in line with those obtained from powders coated in the fluidised bed process mentioned above. It was found that the ultrasound-assisted method was capable of coating single particles with a simple and robust setup. Granule growth in a fluidised bed process was inhibited by feeding the liquid in pulses. The results showed that the length of the pulsing cycles is of importance, and can be used to adjust granule growth. Moreover, pulsed liquid feed was found to be of greater significance to granule growth in high inlet air relative humidity. Liquid feed pulsing can thus be used as a tool in particle size targeting in fluidised bed processes and in compensating for changes in relative humidity of the inlet air. The nozzle function of a two-fluid external mixing pneumatic nozzle, typical for small scale pharmaceutical fluidised bed processes, was studied in situ in an ongoing fluidised bed process with particle tracking velocimetry. It was found that the liquid droplets undergo coalescence as they proceed away from the nozzle head. The coalescence was expected to increase droplet speed, which was confirmed in the study. The spray turbulence was studied, and the results showed turbulence caused by the event of atomisation and by the oppositely directed fluidising air. It was concluded that particle tracking velocimetry is a suitable tool for in situ spray characterisation. The light transmission through dense particulate systems was found to carry information on particle size and packing density as expected based on the theory of light scattering by solids. It was possible to differentiate binary blends consisting of components with differences in optical properties. Light transmission showed potential as a rapid, simple and inexpensive tool in characterisation of particulate systems giving information on changes in particle systems, which could be utilised in basic process diagnostics.

Impedance parameters and the state-of-charge. III. Zinc-manganese dioxide and magnesium-manganese dioxide dry batteries

The problem of non-destructive determination of the state-of-charge of zinc- and magnesium-manganese dioxide dry batteries is examined experimentally from the viewpoint of internal impedance and open-circuit voltage at equilibrium. It is shown that the impedance is mainly charge-transfer controlled at relatively high states-of-charge and progressively changes over to diffusion control as the state-of-charge decreases in the case of zinc-manganese dioxide dry batteries. On the other hand, the impedance is mainly diffusion controlled for undischarged batteries but becomes charge-transfer controlled as soon as there is some discharge in the case of magnesium-manganese dioxide batteries. It is concluded that the determination of state-of-charge is not possible for both types of batteries by the measurement of impedance parameters due to film-induced fluctuations of these parameters. The measurement of open-circuit voltage at equilibrium can be used as a state-of-charge indicator for Zn-MnO2 batteries but not for Mg-MnO2 batteries.

Sedimentary zooplankton remains as indicators of lake ecological quality and trophic structure

To protect and restore lake ecosystems under threats posed by the increasing human population, information on their ecological quality is needed. Lake sediments provide a data rich archive that allows identification of various biological components present prior to anthropogenic alterations as well as a constant record of changes. By providing a longer dimension of time than any ongoing monitoring programme, palaeolimnological methods can help in understanding natural variability and long-term ecological changes in lakes. As zooplankton have a central role in the lake food web, their remains can potentially provide versatile information on past trophic structure. However, various taphonomic processes operating in the lakes still raise questions concerning how subfossil assemblages reflect living communities. This thesis work aimed at improving the use of sedimentary zooplankton remains in the reconstruction of past zooplankton communities and the trophic structure in lakes. To quantify interspecific differences in the accumulation of remains, the subfossils of nine pelagic zooplankton taxa in annually laminated sediments were compared with monitoring results for live zooplankton in Lake Vesijärvi. This lake has a known history of eutrophication and recovery, which resulted from reduced external loading and effective fishing of plankti-benthivorous fish. The response of zooplankton assemblages to these known changes was resolved using annually laminated sediments. The generality of the responses observed in Lake Vesijärvi were further tested with a set of 31 lakes in Southern Finland, relating subfossils in surface sediments to contemporary water quality and fish density, as well as to lake morphometry. The results demonstrated differential preservation and retention of cladoceran species in the sediment. Daphnia, Diaphanosoma and Ceriodaphnia were clearly underrepresented in the sediment samples in comparison to well-preserved Bosmina species, Chydorus, Limnosida and Leptodora. For well-preserved species, the annual net accumulation rate was similar to or above the expected values, reflecting effective sediment focusing and accumulation in the deepest part of the lake. The decreased fish density and improved water quality led to subtle changes in zooplankton community composition. The abundance of Diaphanosoma and Limnosida increased after the reduction in fish density, while Ceriodaphnia and rotifers decreased. The most sensitive indicator of fish density was the mean size of Daphnia ephippia and Bosmina (E.) crassicornis ephippia and carapaces. The concentration of plant-associated species increased, reflecting expanding littoral vegetation along with increasing transparency. Several of the patterns observed in Lake Vesijärvi could also be found within the set of 31 lakes. According to this thesis work, the most useful cladoceran-based indices for nutrient status and planktivorous fish density in Finnish lakes were the relative abundances of certain pelagic taxa, and the mean size of Bosmina spp. carapaces, especially those of Bosmina (E.) cf. coregoni. The abundance of plant-associated species reflected the potential area for aquatic plants. Lake morphometry and sediment organic content, however, explained a relatively high proportion of the variance in the species data, and more studies are needed to quantify lake-specific differences in the accumulation and preservation of remains. Commonly occurring multicollinearity between environmental variables obstructs the cladoceran-based reconstruction of single environmental variables. As taphonomic factors and several direct and indirect structuring forces in lake ecosystems simultaneously affect zooplankton, the subfossil assemblages should be studied in a holistic way before making final conclusions about the trophic structure and the change in lake ecological quality.

The potential of microbial ecological indicators to guide ecosophisticated management of hydrocarbon-contaminated soils

Soil is an unrenewable natural resource under increasing anthropogenic pressure. One of the main threats to soils, compromising their ability to provide us with the goods and ecosystem services we expect, is pollution. Oil hydrocarbons are the most common soil contaminants, and they disturb not just the biota but also the physicochemical properties of soils. Indigenous soil micro-organisms respond rapidly to changes in the soil ecosystem, and are chronically in direct contact with the hydrophobic pollutants on the soil surfaces. Soil microbial variables could thus serve as an intrinsically relevant indicator of soil quality, to be used in the ecological risk assessment of contaminated and remediated soils. Two contrasting studies were designed to investigate soil microbial ecological responses to hydrocarbons, together with parallel changes in soil physicochemical and ecotoxicological properties. The aim was to identify quantitative or qualitative microbiological variables that would be practicable and broadly applicable for the assessment of the quality and restoration of oil-polluted soil. Soil bacteria commonly react on hydrocarbons as a beneficial substrate, which lead to a positive response in the classical microbiological soil quality indicators; negative impacts were accurately reflected only after severe contamination. Hydrocarbon contaminants become less bioavailable due to weathering processes, and their potentially toxic effects decrease faster than the total concentration. Indigenous hydrocarbon degrader bacteria, naturally present in any terrestrial environment, use specific mechanisms to improve access to the hydrocarbon molecules adsorbed on soil surfaces. Thus when contaminants are unavailable even to the specialised degraders, they should pose no hazard to other biota either. Change in the ratio of hydrocarbon degrader numbers to total microbes was detected to predictably indicate pollutant effects and bioavailability. Also bacterial diversity, a qualitative community characteristic, decreased as a response to hydrocarbons. Stabilisation of community evenness, and community structure that reflected clean reference soil, indicated community recovery. If long-term temporal monitoring is difficult and appropriate clean reference soil unavailable, such comparison could possibly be based on DNA-based community analysis, reflecting past+present, and RNA-based community analysis, showing exclusively present conditions. Microbial ecological indicators cannot replace chemical oil analyses, but they are theoretically relevant and operationally practicable additional tools for ecological risk assessment. As such, they can guide ecologically informed and sustainable ecosophisticated management of oil-contaminated lands.

Effect of microstructure and hardness on the grinding abrasive wear resistance of a ball bearing steel

Grinding media wear appears to be non-linear with the time of grinding in a laboratory-scale ball mill. The kinetics of wear can be expressed as a power law of the type w=atb, where the numerical constant a represents wear of a particular microstructure at time t = 1 min and b is the wear exponent which is independent of the particle size prevailing inside a ball mill at any instant of time of grinding. The wear exponent appears to be an indicator of the cutting wear mechanism in dry grinding: a plot of the inverse of the normalised wear exponent (Image ) versusHs (where Hs is the worn surface hardness of the media) yields a curve similar to that of a wear resistance plot obtained in the case of two-body sliding abrasive wear. This method of evaluating the cutting wear resistance of media is demonstrated by employing 15 different microstructures of AISI-SAE 52100 steel balls in dry grinding of quartz in a laboratory-scale ball mill.

A new Fuzzy-LOGIC based Model for Chlorophyll-a in Pulicat Lagoon, India

Coastal lagoons are complex ecosystems exhibiting a high degree of non-linearity in the distribution and exchange of nutrients dissolved in the water column due to their spatio-temporal characteristics. This factor has a direct influence on the concentrations of chlorophyll-a, an indicator of the primary productivity in the water bodies as lakes and lagoons. Moreover the seasonal variability in the characteristics of large-scale basins further contributes to the uncertainties in the data on the physico-chemical and biological characteristics of the lagoons. Considering the above, modelling the distributions of the nutrients with respect to the chlorophyll-concentrations, hence requires an effective approach which will appropriately account for the non-linearity of the ecosystem as well as the uncertainties in the available data. In the present investigation, fuzzy logic was used to develop a new model of the primary production for Pulicat lagoon, Southeast coast of India. Multiple regression analysis revealed that the concentrations of chlorophyll-a in the lagoon was highly influenced by the dissolved concentrations of nitrate, nitrites and phosphorous to different extents over different seasons and years. A high degree of agreement was obtained between the actual field values and those predicted by the new fuzzy model (d = 0.881 to 0.788) for the years 2005 and 2006, illustrating the efficiency of the model in predicting the values of chlorophyll-a in the lagoon.

Dietary habits and obesity: the role of emotional and cognitive factors

In post-industrialised societies, food is more plentiful, accessible and palatable than ever before and technological development has reduced the need for physical activity. Consequently, the prevalence of obesity is increasing, which is problematic as obesity is related to a number of diseases. Various psychological and social factors have an important influence on dietary habits and the development of obesity in the current food-rich and sedentary environments. The present study concentrates on the associations of emotional and cognitive factors with dietary intake and obesity as well as on the role these factors play in socioeconomic disparities in diet. Many people cognitively restrict their food intake to prevent weight gain or to lose weight, but research on whether restrained eating is a useful weight control strategy has produced conflicting findings. With respect to emotional factors, the evidence is accumulating that depressive symptoms are related to less healthy dietary intake and obesity, but the mechanisms explaining these associations remain unclear. Furthermore, it is not fully understood why socioeconomically disadvantaged individuals tend to have unhealthier dietary habits and the motives underlying food choices (e.g., price and health) could be relevant in this respect. The specific aims of the study were to examine 1) whether obesity status and dieting history moderate the associations of restrained eating with overeating tendencies, self-control and obesity indicators; 2) whether the associations of depressive symptoms with unhealthier dietary intake and obesity are attributable to a tendency for emotional eating and a low level of physical activity self-efficacy; and 3) whether the absolute or relative importance of food choice motives (health, pleasure, convenience, price, familiarity and ethicality) contribute to the socioeconomic disparities in dietary habits. The study was based on a large population-based sample of Finnish adults: the participants were men (N=2325) and women (N=2699) aged 25-74 who took part in the DILGOM (Dietary, Lifestyle and Genetic Determinants of Obesity and Metabolic Syndrome) sub-study of the National FINRISK Study 2007. The participants weight, height, waist circumference and body fat percentage were measured in a health examination. Psychological eating styles (the Three-Factor Eating Questionnaire-R18), food choice motives (a shortened version of the Food Choice Questionnaire), depressive symptoms (the Center for Epidemiological Studies Depression Scale) and self-control (the Brief Self-Control Scale) were measured with pre-existing questionnaires. A validated food frequency questionnaire was used to assess the average consumption of sweet and non-sweet energy-dense foods and vegetables/fruit. Self-reported total years of education and gross household income were used as indicators of socioeconomic position. The results indicated that 1) restrained eating was related to a lower body mass index, waist circumference, emotional eating and uncontrolled eating, and to a higher self-control in obese participants and current/past dieters. In contrast, the associations were the opposite in normal weight individuals and those who had never dieted. Thus, restrained eating may be related to better weight control among obese individuals and those with dieting experiences, while among others it may function as an indicator of problems with eating and an attempt to solve them. 2) Emotional eating and depressive symptoms were both related to less healthy dietary intake, and the greater consumption of energy-dense sweet foods among participants with elevated depressive symptoms was attributable to the susceptibility for emotional eating. In addition, emotional eating and physical activity self-efficacy were both important in explaining the positive association between depressive symptoms and obesity. 3) The lower vegetable/fruit intake and higher energy-dense food intake among individuals with a low socioeconomic position were partly explained by the higher priority they placed on price and familiarity and the lower priority they gave to health motives in their daily food choices. In conclusion, although policy interventions to change the obesogenic nature of the current environment are definitely needed, knowledge of the factors that hinder or facilitate people s ability to cope with the food-rich environment is also necessary. This study implies that more emphasis should be placed on various psychological and social factors in weight control programmes and interventions.