Annotated record of the detailed examination of Mn deposits from the Snellius II - Cruise 4 stations in the vicinity of the island of Misool, Eastern Indonesia

The chemical analyses of ferromanganese encrustations found on the seabed west of Misool, eastern Indonesia, indicate that these deposits formed in a way different from that of world-wide occurring manganese nodules. Ferromanganese coated pebbles and fragments that were found in the deeper parts of the study area probably originate from nearby ridges. The ferromanganese crust on the upper part of a dolomite fragment of ?30 kg is likely to be formed by hydrogenous processes, whereas that from the lower part seems to be formed by diagenetic processes mainly. These assumptions are supported by pore-water data from two box cores taken in the same area. The manganese and iron profiles versus depth in these cores indicate a high flux of these metals to the uppermost sediment layer, and possibly into the overlying bottom water. Factor analysis for the principal components of the microprobe analytical results of the mainly hydrogenous ferromanganese crust demonstrates a strong correlation of manganese with the trace metals, of iron with phosphorus and an antipathetic relationship between iron and manganese. Similar results have also been reported for abyssal manganese nodules in the world oceans. Factor analysis for the principal components of the analytical data obtained for the diagenetic ferromanganese crust results in a clear dolomite (Ca/Mg) dilution factor only.

Seleção de características para identificação de diferentes proporções de tipos de fibras musculares por meio da eletromiografia de superfície

Skeletal muscle consists of muscle fiber types that have different physiological and biochemical characteristics. Basically, the muscle fiber can be classified into type I and type II, presenting, among other features, contraction speed and sensitivity to fatigue different for each type of muscle fiber. These fibers coexist in the skeletal muscles and their relative proportions are modulated according to the muscle functionality and the stimulus that is submitted. To identify the different proportions of fiber types in the muscle composition, many studies use biopsy as standard procedure. As the surface electromyography (EMGs) allows to extract information about the recruitment of different motor units, this study is based on the assumption that it is possible to use the EMG to identify different proportions of fiber types in a muscle. The goal of this study was to identify the characteristics of the EMG signals which are able to distinguish, more precisely, different proportions of fiber types. Also was investigated the combination of characteristics using appropriate mathematical models. To achieve the proposed objective, simulated signals were developed with different proportions of motor units recruited and with different signal-to-noise ratios. Thirteen characteristics in function of time and the frequency were extracted from emulated signals. The results for each extracted feature of the signals were submitted to the clustering algorithm k-means to separate the different proportions of motor units recruited on the emulated signals. Mathematical techniques (confusion matrix and analysis of capability) were implemented to select the characteristics able to identify different proportions of muscle fiber types. As a result, the average frequency and median frequency were selected as able to distinguish, with more precision, the proportions of different muscle fiber types. Posteriorly, the features considered most able were analyzed in an associated way through principal component analysis. Were found two principal components of the signals emulated without noise (CP1 and CP2) and two principal components of the noisy signals (CP1 and CP2 ). The first principal components (CP1 and CP1 ) were identified as being able to distinguish different proportions of muscle fiber types. The selected characteristics (median frequency, mean frequency, CP1 and CP1 ) were used to analyze real EMGs signals, comparing sedentary people with physically active people who practice strength training (weight training). The results obtained with the different groups of volunteers show that the physically active people obtained higher values of mean frequency, median frequency and principal components compared with the sedentary people. Moreover, these values decreased with increasing power level for both groups, however, the decline was more accented for the group of physically active people. Based on these results, it is assumed that the volunteers of the physically active group have higher proportions of type II fibers than sedentary people. Finally, based on these results, we can conclude that the selected characteristics were able to distinguish different proportions of muscle fiber types, both for the emulated signals as to the real signals. These characteristics can be used in several studies, for example, to evaluate the progress of people with myopathy and neuromyopathy due to the physiotherapy, and also to analyze the development of athletes to improve their muscle capacity according to their sport. In both cases, the extraction of these characteristics from the surface electromyography signals provides a feedback to the physiotherapist and the coach physical, who can analyze the increase in the proportion of a given type of fiber, as desired in each case.

Étude des relations entre le développement professionnel des enseignants du postsecondaire et leur bien-être psychologique au travail

Réalisé en milieu collégial (cégep)

Facial affect processing inbipolar disorder:a magnetoencephalography study

Background: Identifying biological markers to aid diagnosis of bipolar disorder (BD) is critically important. To be considered a possible biological marker, neural patterns in BD should be discriminant from those in healthy individuals (HI). We examined patterns of neuromagnetic responses revealed by magnetoencephalography (MEG) during implicit emotion-processing using emotional (happy, fearful, sad) and neutral facial expressions, in sixteen BD and sixteen age- and gender-matched healthy individuals. Methods: Neuromagnetic data were recorded using a 306-channel whole-head MEG ELEKTA Neuromag System, and preprocessed using Signal Space Separation as implemented in MaxFilter (ELEKTA). Custom Matlab programs removed EOG and ECG signals from filtered MEG data, and computed means of epoched data (0-250ms, 250-500ms, 500-750ms). A generalized linear model with three factors (individual, emotion intensity and time) compared BD and HI. A principal component analysis of normalized mean channel data in selected brain regions identified principal components that explained 95% of data variation. These components were used in a quadratic support vector machine (SVM) pattern classifier. SVM classifier performance was assessed using the leave-one-out approach. Results: BD and HI showed significantly different patterns of activation for 0-250ms within both left occipital and temporal regions, specifically for neutral facial expressions. PCA analysis revealed significant differences between BD and HI for mild fearful, happy, and sad facial expressions within 250-500ms. SVM quadratic classifier showed greatest accuracy (84%) and sensitivity (92%) for neutral faces, in left occipital regions within 500-750ms. Conclusions: MEG responses may be used in the search for disease specific neural markers.

Assessment of the Spatial and Temporal Distribution of Functional Connectivity in Resting-State BOLD fMRI

Recent research into resting-state functional magnetic resonance imaging (fMRI) has shown that the brain is very active during rest. This thesis work utilizes blood oxygenation level dependent (BOLD) signals to investigate the spatial and temporal functional network information found within resting-state data, and aims to investigate the feasibility of extracting functional connectivity networks using different methods as well as the dynamic variability within some of the methods. Furthermore, this work looks into producing valid networks using a sparsely-sampled sub-set of the original data.

In this work we utilize four main methods: independent component analysis (ICA), principal component analysis (PCA), correlation, and a point-processing technique. Each method comes with unique assumptions, as well as strengths and limitations into exploring how the resting state components interact in space and time.

Correlation is perhaps the simplest technique. Using this technique, resting-state patterns can be identified based on how similar the time profile is to a seed region’s time profile. However, this method requires a seed region and can only identify one resting state network at a time. This simple correlation technique is able to reproduce the resting state network using subject data from one subject’s scan session as well as with 16 subjects.

Independent component analysis, the second technique, has established software programs that can be used to implement this technique. ICA can extract multiple components from a data set in a single analysis. The disadvantage is that the resting state networks it produces are all independent of each other, making the assumption that the spatial pattern of functional connectivity is the same across all the time points. ICA is successfully able to reproduce resting state connectivity patterns for both one subject and a 16 subject concatenated data set.

Using principal component analysis, the dimensionality of the data is compressed to find the directions in which the variance of the data is most significant. This method utilizes the same basic matrix math as ICA with a few important differences that will be outlined later in this text. Using this method, sometimes different functional connectivity patterns are identifiable but with a large amount of noise and variability.

To begin to investigate the dynamics of the functional connectivity, the correlation technique is used to compare the first and second halves of a scan session. Minor differences are discernable between the correlation results of the scan session halves. Further, a sliding window technique is implemented to study the correlation coefficients through different sizes of correlation windows throughout time. From this technique it is apparent that the correlation level with the seed region is not static throughout the scan length.

The last method introduced, a point processing method, is one of the more novel techniques because it does not require analysis of the continuous time points. Here, network information is extracted based on brief occurrences of high or low amplitude signals within a seed region. Because point processing utilizes less time points from the data, the statistical power of the results is lower. There are also larger variations in DMN patterns between subjects. In addition to boosted computational efficiency, the benefit of using a point-process method is that the patterns produced for different seed regions do not have to be independent of one another.

This work compares four unique methods of identifying functional connectivity patterns. ICA is a technique that is currently used by many scientists studying functional connectivity patterns. The PCA technique is not optimal for the level of noise and the distribution of the data sets. The correlation technique is simple and obtains good results, however a seed region is needed and the method assumes that the DMN regions is correlated throughout the entire scan. Looking at the more dynamic aspects of correlation changing patterns of correlation were evident. The last point-processing method produces a promising results of identifying functional connectivity networks using only low and high amplitude BOLD signals.

Étude des relations entre le développement professionnel des enseignants du postsecondaire et leur bien-être psychologique au travail

Réalisé en milieu collégial (cégep)

Multivariate Techniques in Biomechanical Analysis

This work outlines the theoretical advantages of multivariate methods in biomechanical data, validates the proposed methods and outlines new clinical findings relating to knee osteoarthritis that were made possible by this approach. New techniques were based on existing multivariate approaches, Partial Least Squares (PLS) and Non-negative Matrix Factorization (NMF) and validated using existing data sets. The new techniques developed, PCA-PLS-LDA (Principal Component Analysis – Partial Least Squares – Linear Discriminant Analysis), PCA-PLS-MLR (Principal Component Analysis – Partial Least Squares –Multiple Linear Regression) and Waveform Similarity (based on NMF) were developed to address the challenging characteristics of biomechanical data, variability and correlation. As a result, these new structure-seeking technique revealed new clinical findings. The first new clinical finding relates to the relationship between pain, radiographic severity and mechanics. Simultaneous analysis of pain and radiographic severity outcomes, a first in biomechanics, revealed that the knee adduction moment’s relationship to radiographic features is mediated by pain in subjects with moderate osteoarthritis. The second clinical finding was quantifying the importance of neuromuscular patterns in brace effectiveness for patients with knee osteoarthritis. I found that brace effectiveness was more related to the patient’s unbraced neuromuscular patterns than it was to mechanics, and that these neuromuscular patterns were more complicated than simply increased overall muscle activity, as previously thought.

Expressing Sentiments in Game Reviews

Opinion mining and sentiment analysis are important research areas of Natural Language Processing (NLP) tools and have become viable alternatives for automatically extracting the affective information found in texts. Our aim is to build an NLP model to analyze gamers’ sentiments and opinions expressed in a corpus of 9750 game reviews. A Principal Component Analysis using sentiment analysis features explained 51.2 % of the variance of the reviews and provides an integrated view of the major sentiment and topic related dimensions expressed in game reviews. A Discriminant Function Analysis based on the emerging components classified game reviews into positive, neutral and negative ratings with a 55 % accuracy.

Oil Market Modelling: A Comparative Analysis of Fundamental and Latent Factor Approaches

We formally compare fundamental factor and latent factor approaches to oil price modelling. Fundamental modelling has a long history in seeking to understand oil price movements, while latent factor modelling has a more recent and limited history, but has gained popularity in other financial markets. The two approaches, though competing, have not formally been compared as to effectiveness. For a range of short- medium- and long-dated WTI oil futures we test a recently proposed five-factor fundamental model and a Principal Component Analysis latent factor model. Our findings demonstrate that there is no discernible difference between the two techniques in a dynamic setting. We conclude that this infers some advantages in adopting the latent factor approach due to the difficulty in determining a well specified fundamental model.

Obésité abdominale et autres déterminants du risque cardiométabolique dans deux populations urbaines noires apparentées : Port-au-Prince (Haïti) et Cotonou (Bénin)

L’obésité est un problème de santé publique reconnu. Dans la dernière décennie l’obésité abdominale (OA) a été considérée comme une maladie métabolique qui contribue davantage au risque de diabète et de maladies cardiovasculaires que l’obésité générale définie par l’indice de masse corporelle. Toutefois, dans les populations d’origine africaine, la relation entre l’OA et les autres biomarqueurs de risque cardiométabolique (RCM) demeure obscure à cause du manque d’études chez ces populations et de l’absence de valeurs-seuils spécifiques pour juger d’une OA. Cette étude visait à comparer la prévalence des biomarqueurs de RCM (OA, hypertension artérielle, hyperglycémie, dyslipidémie, résistance à l'insuline et inflammation pré-clinique) chez les Béninois de Cotonou et les Haïtiens de Port-au-Prince (PAP), à étudier l’association de l’OA avec les autres biomarqueurs de RCM, à documenter le rôle du niveau socio-économique (NSE) et du mode de vie dans cette association et à ’identifier les indicateurs anthropométriques de l’OA -tour de taille (TT) et le ratio TT/hauteur (TT/H)- et les seuils qui prédisent le mieux le RCM à Cotonou et à PAP. Il s’est agi d’une analyse de données transversales chez 452 adultes (52 % hommes) apparemment en bonne santé, âgés de 25 à 60 ans, avec 200 sujets vivant à Cotonou (Bénin) et 252 sujets à PAP (Haïti). Les biomarqueurs de RCM considérés étaient : le syndrome métabolique (SMet) d’après les critères harmonisés de 2009 et ses composantes individuelles - une OA à partir d’un TT ≥ 94cm chez les hommes et ≥ 80cm chez les femmes, une hypertension, une dyslipidémie et une hyperglycémie; la résistance à l’insuline définie chez l’ensemble des sujets de l’étude à partir du 75e centile de l’Homeostasis Model Assessment (HOMA-IR); un ratio d’athérogénicité élevé (Cholestérol sérique total/HDL-Cholestérol); et l’inflammation pré-clinique mesurée à partir d’un niveau de protéine C-réactive ultrasensible (PCRus) entre 3 et 10 mg/l. Le ratio TT/H était aussi considéré pour définir l’OA à partir d’un seuil de 0,5. Les données sur les habitudes alimentaires, la consommation d’alcool, le tabagisme, les caractéristiques sociodémographiques et les conditions socio-économiques incluant le niveau d’éducation et un proxy du revenu (basé sur l’analyse par composante principale des biens et des possessions) ont été recueillies au moyen d’un questionnaire. Sur la base de données de fréquence de consommation d’aliments occidentaux, urbains et traditionnels, des schémas alimentaires des sujets de chaque ville ont été identifiés par analyse typologique. La validité et les valeurs-seuils de TT et du ratio TT/H prédictives du RCM ont été définies à partir des courbes ROC (Receiver Operating Characteristics). Le SMet était présent chez 21,5 % et 16,1 % des participants, respectivement à Cotonou et à PAP. La prévalence d’OA était élevée à Cotonou (52,5 %) qu’à PAP (36%), avec une prévalence plus élevée chez les femmes que chez les hommes. Le profil lipidique sérique était plus athérogène à PAP avec 89,3 % d’HDL-c bas à PAP contre 79,7 % à Cotonou et un ratio CT/HDL-c élevé de 73,4 % à PAP contre 42 % à Cotonou. Les valeurs-seuils spécifiques de TT et du TT/H étaient respectivement 94 cm et 0,59 chez les femmes et 80 cm et 0,50 chez les hommes. Les analyses multivariées de l’OA avec les biomarqueurs de RCM les plus fortement prévalents dans ces deux populations montraient que l’OA était associée à un risque accru de résistance à l’insuline, d’athérogénicité et de tension artérielle élevée et ceci, indépendamment des facteurs socio-économiques et du mode de vie. Deux schémas alimentaires ont émergé, transitionnel et traditionnel, dans chaque ville, mais ceux-ci ne se révélaient pas associés aux biomarqueurs de RCM bien qu’ils soient en lien avec les variables socio-économiques. La présente étude confirme la présence de plusieurs biomarqueurs de RCM chez des sujets apparemment sains. En outre, l’OA est un élément clé du RCM dans ces deux populations. Les seuils actuels de TT devraient être reconsidérés éventuellement à la lumière d’études de plus grande envergure, afin de mieux définir l’OA chez les Noirs africains ou d’origine africaine, ce qui permettra une surveillance épidémiologique plus adéquate des biomarqueurs de RCM.

Tourism Impacts of a Portuguese World Heritage Historic Center: Residents’ Perspectives

The World Heritage List (WHL) is widely considered a powerful tool for national tourism campaigns. Sites inscribed on the WHL by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) are commonly treated as catholicons in promoting the tourism industry, which in turn helps to promote economic growth and development. This study analyzes local community perceptions of the importance of the World Heritage Site (WHS) classification of the historic center of the Portuguese city of E ́vora. The research also includes an analysis of the local residents’ perceived tourism impacts on the municipality of E ́ vora. The methodology consists of quan- titative research based on a self-administered survey applied to convenience sam- ples of local residents of the municipality of E ́ vora in the beginning of 2014. The local residents’ perceptions of the level of importance of the WHS classification to the municipality and its impact in the increase of tourists is analyzed. Positive and negative tourism impacts are then ranked and a principal components factor analysis is employed separately to the two groups of impacts in order to identify underlying dimensions associated with residents’ perceptions on tourism develop- ment. Based on the results of the factor analysis, independent sample t-tests are used to investigate differences regarding positive and negative tourism impacts between residents that live near and far from the historic center, and between residents who work/have worked in the tourism sector and residents that work/ have worked in other sectors.

A satisfação dos clientes internos e o comprometimento organizacional: um estudo à luz do modelo ASH nas indústrias alimentícias do RN

Currently the organizations are passing for continuous cycles of changes due to necessity of survival in the work market. The administration of the future points a way to the organizations of today and tomorrow, the search of the competitiveness from loyalty and motivation of its staff. Of this form, the model of the Auditoria do Sistema Humano (ASH), developed for Spanish researchers and that now it is being applied in Brazil, contemplates a series of dimensions about Human Resources management quality in the companies and the organizational effectiveness, such as the environment where the company is inserted, the strategies, the organizational drawing, the psychological and psychosocial processes, e the reached results. In this direction, the present research analyzed the factors of job satisfaction and organizational commitment, making, also, a relation of causality between the same ones. The quantitative-descriptive research had as population the employees of twenty three nourishing industries of the State of Rio Grande do Norte (Brazil), registered in the Federacy of the Industries of the state. The collection of the data occurred for the months of October of 2005 and March of 2006, by means of the application of questionnaire of model ASH. The sample was composed for 197 employees, however it was observed presence of five outliers, that they had been excluded from the analysis of the data. To extract the dimensions of the satisfaction and the commitment and identification the factorial analysis was used, with extraction method of principal components, rotation Varimax and normalization Kaiser. The gotten dimensions had been evaluated with the calculation of the coefficient Alpha of Cronbach. The factorial analysis of the pointers of the organizational commitment and identification had extracted ten factors. Of these, four had gotten significance of the analyses inside: affective commitment, values commitment, continuance commitment and necessity commitment. The result of the analysis of the pointers of job satisfaction indicated four factors: extrinsic, motivations, relation with the friends and auto-accomplishment. To deal with the data the relation between job satisfaction and organizational commitment it was used technique of multiple regression. The correlation between commitment and satisfaction was satisfactory, detaching the affective commitment with bigger index of correlation, followed of the affective one

Improving the Psychometric Utility of the Hypomania Checklist (HCL-32): a Rasch Analysis Approach

Background The HCL-32 is a widely-used screening questionnaire for hypomania. We aimed to use a Rasch analysis approach to (i) evaluate the measurement properties, principally unidimensionality, of the HCL-32, and (ii) generate a score table to allow researchers to convert raw HCL-32 scores into an interval-level measurement which will be more appropriate for statistical analyses. Methods Subjects were part of the Bipolar Disorder Research Network (BDRN) study with DSM-IV bipolar disorder (n=389). Multidimensionality was assessed using the Rasch fit statistics and principle components analysis of the residuals (PCA). Item invariance (differential item functioning, DIF) was tested for gender, bipolar diagnosis and current mental state. Item estimates and reliabilities were calculated. Results Three items (29, 30, 32) had unacceptable fit to the Rasch unidimensional model. Item 14 displayed significant DIF for gender and items 8 and 17 for current mental state. Item estimates confirmed that not all items measure hypomania equally. Limitations This sample was recruited as part of a large ongoing genetic epidemiology study of bipolar disorder and may not be fully representative of the broader clinical population of individuals with bipolar disorder. Conclusion The HCL-32 is unidimensional in practice, but measurements may be further strengthened by the removal of four items. Re-scored linear measurements may be more appropriate for clinical research.

Analysis of Molecular Dynamics Simulations of Protein Folding

Microsecond long Molecular Dynamics (MD) trajectories of biomolecular processes are now possible due to advances in computer technology. Soon, trajectories long enough to probe dynamics over many milliseconds will become available. Since these timescales match the physiological timescales over which many small proteins fold, all atom MD simulations of protein folding are now becoming popular. To distill features of such large folding trajectories, we must develop methods that can both compress trajectory data to enable visualization, and that can yield themselves to further analysis, such as the finding of collective coordinates and reduction of the dynamics. Conventionally, clustering has been the most popular MD trajectory analysis technique, followed by principal component analysis (PCA). Simple clustering used in MD trajectory analysis suffers from various serious drawbacks, namely, (i) it is not data driven, (ii) it is unstable to noise and change in cutoff parameters, and (iii) since it does not take into account interrelationships amongst data points, the separation of data into clusters can often be artificial. Usually, partitions generated by clustering techniques are validated visually, but such validation is not possible for MD trajectories of protein folding, as the underlying structural transitions are not well understood. Rigorous cluster validation techniques may be adapted, but it is more crucial to reduce the dimensions in which MD trajectories reside, while still preserving their salient features. PCA has often been used for dimension reduction and while it is computationally inexpensive, being a linear method, it does not achieve good data compression. In this thesis, I propose a different method, a nonmetric multidimensional scaling (nMDS) technique, which achieves superior data compression by virtue of being nonlinear, and also provides a clear insight into the structural processes underlying MD trajectories. I illustrate the capabilities of nMDS by analyzing three complete villin headpiece folding and six norleucine mutant (NLE) folding trajectories simulated by Freddolino and Schulten [1]. Using these trajectories, I make comparisons between nMDS, PCA and clustering to demonstrate the superiority of nMDS. The three villin headpiece trajectories showed great structural heterogeneity. Apart from a few trivial features like early formation of secondary structure, no commonalities between trajectories were found. There were no units of residues or atoms found moving in concert across the trajectories. A flipping transition, corresponding to the flipping of helix 1 relative to the plane formed by helices 2 and 3 was observed towards the end of the folding process in all trajectories, when nearly all native contacts had been formed. However, the transition occurred through a different series of steps in all trajectories, indicating that it may not be a common transition in villin folding. The trajectories showed competition between local structure formation/hydrophobic collapse and global structure formation in all trajectories. Our analysis on the NLE trajectories confirms the notion that a tight hydrophobic core inhibits correct 3-D rearrangement. Only one of the six NLE trajectories folded, and it showed no flipping transition. All the other trajectories get trapped in hydrophobically collapsed states. The NLE residues were found to be buried deeply into the core, compared to the corresponding lysines in the villin headpiece, thereby making the core tighter and harder to undo for 3-D rearrangement. Our results suggest that the NLE may not be a fast folder as experiments suggest. The tightness of the hydrophobic core may be a very important factor in the folding of larger proteins. It is likely that chaperones like GroEL act to undo the tight hydrophobic core of proteins, after most secondary structure elements have been formed, so that global rearrangement is easier. I conclude by presenting facts about chaperone-protein complexes and propose further directions for the study of protein folding.

Obésité abdominale et autres déterminants du risque cardiométabolique dans deux populations urbaines noires apparentées : Port-au-Prince (Haïti) et Cotonou (Bénin)

L’obésité est un problème de santé publique reconnu. Dans la dernière décennie l’obésité abdominale (OA) a été considérée comme une maladie métabolique qui contribue davantage au risque de diabète et de maladies cardiovasculaires que l’obésité générale définie par l’indice de masse corporelle. Toutefois, dans les populations d’origine africaine, la relation entre l’OA et les autres biomarqueurs de risque cardiométabolique (RCM) demeure obscure à cause du manque d’études chez ces populations et de l’absence de valeurs-seuils spécifiques pour juger d’une OA. Cette étude visait à comparer la prévalence des biomarqueurs de RCM (OA, hypertension artérielle, hyperglycémie, dyslipidémie, résistance à l'insuline et inflammation pré-clinique) chez les Béninois de Cotonou et les Haïtiens de Port-au-Prince (PAP), à étudier l’association de l’OA avec les autres biomarqueurs de RCM, à documenter le rôle du niveau socio-économique (NSE) et du mode de vie dans cette association et à ’identifier les indicateurs anthropométriques de l’OA -tour de taille (TT) et le ratio TT/hauteur (TT/H)- et les seuils qui prédisent le mieux le RCM à Cotonou et à PAP. Il s’est agi d’une analyse de données transversales chez 452 adultes (52 % hommes) apparemment en bonne santé, âgés de 25 à 60 ans, avec 200 sujets vivant à Cotonou (Bénin) et 252 sujets à PAP (Haïti). Les biomarqueurs de RCM considérés étaient : le syndrome métabolique (SMet) d’après les critères harmonisés de 2009 et ses composantes individuelles - une OA à partir d’un TT ≥ 94cm chez les hommes et ≥ 80cm chez les femmes, une hypertension, une dyslipidémie et une hyperglycémie; la résistance à l’insuline définie chez l’ensemble des sujets de l’étude à partir du 75e centile de l’Homeostasis Model Assessment (HOMA-IR); un ratio d’athérogénicité élevé (Cholestérol sérique total/HDL-Cholestérol); et l’inflammation pré-clinique mesurée à partir d’un niveau de protéine C-réactive ultrasensible (PCRus) entre 3 et 10 mg/l. Le ratio TT/H était aussi considéré pour définir l’OA à partir d’un seuil de 0,5. Les données sur les habitudes alimentaires, la consommation d’alcool, le tabagisme, les caractéristiques sociodémographiques et les conditions socio-économiques incluant le niveau d’éducation et un proxy du revenu (basé sur l’analyse par composante principale des biens et des possessions) ont été recueillies au moyen d’un questionnaire. Sur la base de données de fréquence de consommation d’aliments occidentaux, urbains et traditionnels, des schémas alimentaires des sujets de chaque ville ont été identifiés par analyse typologique. La validité et les valeurs-seuils de TT et du ratio TT/H prédictives du RCM ont été définies à partir des courbes ROC (Receiver Operating Characteristics). Le SMet était présent chez 21,5 % et 16,1 % des participants, respectivement à Cotonou et à PAP. La prévalence d’OA était élevée à Cotonou (52,5 %) qu’à PAP (36%), avec une prévalence plus élevée chez les femmes que chez les hommes. Le profil lipidique sérique était plus athérogène à PAP avec 89,3 % d’HDL-c bas à PAP contre 79,7 % à Cotonou et un ratio CT/HDL-c élevé de 73,4 % à PAP contre 42 % à Cotonou. Les valeurs-seuils spécifiques de TT et du TT/H étaient respectivement 94 cm et 0,59 chez les femmes et 80 cm et 0,50 chez les hommes. Les analyses multivariées de l’OA avec les biomarqueurs de RCM les plus fortement prévalents dans ces deux populations montraient que l’OA était associée à un risque accru de résistance à l’insuline, d’athérogénicité et de tension artérielle élevée et ceci, indépendamment des facteurs socio-économiques et du mode de vie. Deux schémas alimentaires ont émergé, transitionnel et traditionnel, dans chaque ville, mais ceux-ci ne se révélaient pas associés aux biomarqueurs de RCM bien qu’ils soient en lien avec les variables socio-économiques. La présente étude confirme la présence de plusieurs biomarqueurs de RCM chez des sujets apparemment sains. En outre, l’OA est un élément clé du RCM dans ces deux populations. Les seuils actuels de TT devraient être reconsidérés éventuellement à la lumière d’études de plus grande envergure, afin de mieux définir l’OA chez les Noirs africains ou d’origine africaine, ce qui permettra une surveillance épidémiologique plus adéquate des biomarqueurs de RCM.