A survey on Human Mobility and its applications

Human Mobility has attracted attentions from different fields of studies such as epidemic modeling, traffic engineering, traffic prediction and urban planning. In this survey we review major characteristics of human mobility studies including from trajectory-based studies to studies using graph and network theory. In trajectory-based studies statistical measures such as jump length distribution and radius of gyration are analyzed in order to investigate how people move in their daily life, and if it is possible to model this individual movements and make prediction based on them. Using graph in mobility studies, helps to investigate the dynamic behavior of the system, such as diffusion and flow in the network and makes it easier to estimate how much one part of the network influences another by using metrics like centrality measures. We aim to study population flow in transportation networks using mobility data to derive models and patterns, and to develop new applications in predicting phenomena such as congestion. Human Mobility studies with the new generation of mobility data provided by cellular phone networks, arise new challenges such as data storing, data representation, data analysis and computation complexity. A comparative review of different data types used in current tools and applications of Human Mobility studies leads us to new approaches for dealing with mentioned challenges

Inférence des déplacements humains sur un réseau de transport multimodal par l’analyse des meta-données d’un réseau mobile

Around half of the world population is living in cities where different transportation networks are cooperating together to provide some efficient transportation facilities for individuals. To improve the performance of the multimodal transportation network it is crucial to monitor and analyze the multimodal trajectories, however obtaining the multimodal mobility data is not a trivial task. GPS data with fine accuracy, is extremely expensive to collect; Additionally, GPS is not available in tunnels and underground. Recently, thanks to telecommunication advancement cellular dataset such as Call Data Records (CDRs), is a great resource of mobility data, nevertheless, this kind of dataset is noisy and sparse in time. Our objective in this thesis is to propose a solution to this challenging issue of inferring real trajectory and transportation layer from wholly cellular observation. To achieve these objectives, we use Cellular signalization data which is more frequent than CDRs and despite their spatial inaccuracy, they provide a fair source of multimodal trajectory data. We propose 'CT-Mapper’ to map cellular signalization data collected from smart phones over the multimodal transportation network. Our proposed algorithm uses Hidden Markov Model property and topological properties of different transportation layers to model an unsupervised mapping algorithm which maps sparse cellular trajectories on multilayer transportation network. Later on, we propose ‘LCT-Mapper’ an algorithm to infer the main mode of trajectories. The area of study in this research work is Paris and region (Ile-de-France); we have modeled and built the multimodal transportation network database. To evaluate our proposed algorithm, we use real trajectories data sets collected from a group of volunteers for a period of 1 month. The user's cellular signalization data was provided by a french operator to assess the performance of our proposed algorithms using GPS data as ground truth. An extensive set of evaluation has been performed to validate the proposed algorithms. To summarize, we have shown in this work that it is feasible to infer the multimodal trajectory of users in an unsupervised manner. Our achievement makes it possible to investigate the multimodal mobility behavior of people and explore and monitor the population flow over multilayer transportation networkDans cette thèse, nous avons étudier une méthode de classification et d'évaluation des modalités de transport utilisées par les porteurs de mobile durant leurs trajets quotidiens. Les informations de mobilité sont collectées par un opérateur au travers des logs du réseau téléphonique mobile qui fournissent des informations sur les stations de base qui ont été utilisées par un mobile durant son trajet. Les signaux (appels/SMS/3G/4G) émis par les téléphones sont une source d'information pertinente pour l'analyse de la mobilité humaine, mais au-delà de ça, ces données représentent surtout un moyen de caractériser les habitudes et les comportements humains. Bien que l'analyse des metadata permette d'acquérir des informations spatio-temporelles à une échelle sans précédent, ces données présentent aussi de nombreuses problématiques à traiter afin d'en extraire une information pertinente. Notre objectif dans cette thèse est de proposer une solution au problème de déduire la trajectoire réelle sur des réseaux de transport à partir d'observations de position obtenues grâce à l'analyse de la signalisation sur les réseaux cellulaires. Nous proposons « CT-Mapper" pour projecter les données de signalisation cellulaires recueillies auprès de smartphone sur le réseau de transport multimodal. Notre algorithme utilise un modèle de Markov caché et les propriétés topologiques des différentes couches de transport. Ensuite, nous proposons « LCT-Mapper » un algorithme qui permet de déduire le mode de transport utilisé. Pour évaluer nos algorithmes, nous avons reconstruit les réseaux de transport de Paris et de la région (Ile-de-France). Puis nous avons collecté un jeu de données de trajectoires réelles recueillies auprès d'un groupe de volontaires pendant une période de 1 mois. Les données de signalisation cellulaire de l'utilisateur ont été fournies par un opérateur français pour évaluer les performances de nos algorithmes à l'aide de données GPS. Pour conclure, nous avons montré dans ce travail qu'il est possible d'en déduire la trajectoire multimodale des utilisateurs d'une manière non supervisée. Notre réalisation permet d'étudier le comportement de mobilité multimodale de personnes et d'explorer et de contrôler le flux de la population sur le réseau de transport multicouch

CT-Mapper: Mapping Sparse Multimodal Cellular Trajectories using a Multilayer Transportation Network

Mobile phone data have recently become an attractive source of information about mobility behavior. Since cell phone data can be captured in a passive way for a large user population, they can be harnessed to collect well-sampled mobility information. In this paper, we propose CT-Mapper, an unsupervised algorithm that enables the mapping of mobile phone traces over a multimodal transport network. One of the main strengths of CT-Mapper is its capability to map noisy sparse cellular multimodal trajectories over a multilayer transportation network where the layers have different physical properties and not only to map trajectories associated with a single layer. Such a network is modeled by a large multilayer graph in which the nodes correspond to metro/train stations or road intersections and edges correspond to connections between them. The mapping problem is modeled by an unsupervised HMM where the observations correspond to sparse user mobile trajectories and the hidden states to the multilayer graph nodes. The HMM is unsupervised as the transition and emission probabilities are inferred using respectively the physical transportation properties and the information on the spatial coverage of antenna base stations. To evaluate CT-Mapper we collected cellular traces with their corresponding GPS trajectories for a group of volunteer users in Paris and vicinity (France). We show that CT-Mapper is able to accurately retrieve the real cell phone user paths despite the sparsity of the observed trace trajectories. Furthermore our transition probability model is up to 20% more accurate than other naive models.Comment: Under revision in Computer Communication Journa

A clinical study of the effect of Glycyrrhiza glabra plant and exercise on the quality of life of menopausal women

BACKGROUND: Most women experience significant changes during and after menopause which causes various complications of menopause and the changes in quality of their life. The aim of this study was to evaluate the effect of Glycyrrhiza glabra plant and exercise on quality of life (QOL) of menopausal women. METHODS: This clinical experiment was performed in Arak, Iran. The study subjects consisted of 120 menopausal women. The participants were selected through convenience method and randomly divided into 4 groups of 30 subjects. Group 1 participants were administered 3 Glycyrrhiza glabra tablets daily. Group 2 participants had a regular exercise program. Group 3 participants were simultaneously administered Glycyrrhiza glabr tablets like group 1 and had an exercise program like group 2. Group 4 received no intervention. The participants’ QOL was investigated before and 1 month after the intervention using the Menopause-Specific Quality of Life (MENQOL) Questionnaire. Data analysis was performed in SPSS software using Mann-Whitney, Wilcoxon, Kruskal-Wallis, and chi-square tests, and variance analysis. RESULTS: No significant difference between the four groups in terms of vasomotor, psychosocial, physical, and sexual health, and QOL based on the Kruskal-Wallis test before the intervention. However, a significant difference was observed between the groups in terms of vasomotor, psychosocial, physical, and sexual health and QOL after the intervention. CONCLUSION: The results of this study showed the efficacy of Glycyrrhiza glabra and exercise programs in controlling the symptoms of menopause. It is recommended that postmenopausal women use exercise programs and Glycyrrhiza glabra to control menopausal symptoms

Oral hygiene status in a general population of Iran, 2011: a key lifestyle marker in relation to common risk factors of non-communicable diseases

Background: To estimate Oral Hygiene (OH) status in the Iranian population in 2011, and to determine the influence of socio-economic characteristics on OH, and its interrelation with common risk factors of Non-Communicable Diseases (NCDs). Methods: Data including a total of 12,105 individuals aged 6-70 years were obtained from the sixth round of the surveys of NCDs risk factors in Iran. OH was recorded through a structured questionnaire measuring daily frequencies of tooth brushing and dental flossing. Descriptive analyses were performed on demographic characteristics in the complex sample survey setting. We also employed weighted binary logistic regression to compute Odds Ratio (OR) as a measure of association between the response and explanatory factors. Furthermore, to construct an asset index, we utilized Principal Component Analysis (PCA). Results: The percentage with minimum recommended daily OH practices was 3.7% among men and 7.7% among women (OR= 2.3; P < 0.001). Urban citizens were more likely to have their teeth cleaned compared to rural people (OR= 2.8; P < 0.001). For both genders, a relatively better condition was observed in the 25–34 age group (male: 5.6%; female: 10.3%). In addition, OH status improved significantly by increase in both level of education ( P < 0.001) and economic status ( P < 0.001). There were also apparent associations between self-care practices and specific behavioral risk factors, though the correlation with dietary habits and tobacco use could be largely explained by socio-economic factors. Conclusion: OH situation in Iran calls for urgent need to assign proper interventions and strategies toward raising public awareness and reducing disparities in access to health facilities

A clinical study of the effect of Glycyrrhiza glabra plant and exercise on the quality of life of menopausal women

BACKGROUND: Most women experience significant changes during and after menopause which causes various complications of menopause and the changes in quality of their life. The aim of this study was to evaluate the effect of Glycyrrhiza glabra plant and exercise on quality of life (QOL) of menopausal women. METHODS: This clinical experiment was performed in Arak, Iran. The study subjects consisted of 120 menopausal women. The participants were selected through convenience method and randomly divided into 4 groups of 30 subjects. Group 1 participants were administered 3 Glycyrrhiza glabra tablets daily. Group 2 participants had a regular exercise program. Group 3 participants were simultaneously administered Glycyrrhiza glabr tablets like group 1 and had an exercise program like group 2. Group 4 received no intervention. The participants’ QOL was investigated before and 1 month after the intervention using the Menopause-Specific Quality of Life (MENQOL) Questionnaire. Data analysis was performed in SPSS software using Mann-Whitney, Wilcoxon, Kruskal-Wallis, and chi-square tests, and variance analysis. RESULTS: No significant difference between the four groups in terms of vasomotor, psychosocial, physical, and sexual health, and QOL based on the Kruskal-Wallis test before the intervention. However, a significant difference was observed between the groups in terms of vasomotor, psychosocial, physical, and sexual health and QOL after the intervention. CONCLUSION: The results of this study showed the efficacy of Glycyrrhiza glabra and exercise programs in controlling the symptoms of menopause. It is recommended that postmenopausal women use exercise programs and Glycyrrhiza glabra to control menopausal symptoms

Distributions of High-Sensitivity C-Reactive Protein, Total Cholesterol-HDL Ratio and 10-Year Cardiovascular Risk: National Population-Based Study

The present study aimed to evaluate the distributions of High-Sensitivity C-reactive protein, TC-HDL ratio and 10-year risk of cardiovascular diseases among Iranian adult population. We conducted a cross-sectional study on a total of 2125 adults aged 25 to 65. Data of the Third National Surveillance of Risk Factors of Non-Communicable Diseases (SuRFNCD-2007) was used. Anthropometric indices, blood pressure and biochemical measurements had been obtained. Ten-year risk of cardiovascular events was also calculated using different models. Median (interquartile range) and geometric means (95% CI) of hs-CRP were 5.1(3.9) and 4.1(4.38-4.85), respectively. Mean TC-HDL ratio±(SD) was 5.94±2.84 in men and 5.37±1.97 in women (P<0.001). In spite of risk scores (FRS and SCORE), no significant gender and age-related differences were observed in hs-CRP levels. Exclusion of CRP levels≥10 did not change the results. The proportion of high-risk categories using SCORE and FRS models were 3.6 % and 8.8 %, respectively. In comparison with other published data, greater means and median values of High-Sensitivity C-reactive protein were observed. Higher TC-HDL ratio and cardiovascular risk in men than in women were also demonstrated. The issue of screening for cardiovascular diseases has yet to be addressed due to considerable prevalence of elevated CRP and increased risk of cardiovascular events among various subgroups

Blood pressure percentiles by age and body mass index for adults

Since no comprehensive study has been conducted on blood pressure (BP) percentiles established upon nationally representative sample population of adults, the present study aimed to construct the blood pressure percentiles by age, sex and body mass index (BMI) of the subjects. Analyses were based on data collected in 2011 from 8,425 adults aged 25 to 69 years old. Data on demographic characteristics, anthropometric measurements, and blood pressure was recorded for each subject. Linear Regression analysis was used to assess the adjusted relationship of age-sex-specific standard deviation scores of BMI, height, and weight with blood pressure. Four separate models for systolic blood pressure (SBP) and diastolic blood pressure (DBP) of men and women were constructed for BP percentiles according to age and BMI. Blood pressure increased with the rise in BMI and weight, but showed a negative correlation with height. SBP and DBP rose steadily with increasing age, but the rise in SBP was greater than DBP. Overweight and obese population, seem to fall into the category of hypertensive. The findings of present study show that BP percentiles are steadily increased by age and BMI. In addition, most obese or overweight adults are hypertensive

Third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007) in Iran: methods and results on prevalence of diabetes, hypertension, obesity, central obesity, and dyslipidemia

<p>Abstract</p> <p>Background</p> <p>The burden of non-communicable diseases is rising globally. This trend seems to be faster in developing countries of the Middle East. In this study, we presented the latest prevalence rates of a number of important non-communicable diseases and their risk factors in the Iranian population.</p> <p>Methods</p> <p>The results of this study are extracted from the third national Surveillance of Risk Factors of Non-Communicable Diseases (SuRFNCD-2007), conducted in 2007. A total of 5,287 Iranian citizens, aged 15–64 years, were included in this survey. Interviewer-administered questionnaires were applied to collect the data of participants including the demographics, diet, physical activity, smoking, history of hypertension, and history of diabetes. Anthropometric characteristics were measured and serum biochemistry profiles were determined on venous blood samples. Diabetes (fasting plasma glucose ≥ 126 mg/dl), hypertension (systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or use of anti-hypertensive drugs), dyslipidemia (hypertriglyceridemia: triglycerides ≥ 150 mg/dl, hypercholesterolemia: total cholesterol ≥ 200 mg/dl), obesity (body mass index ≥ 30 kg/m²), and central obesity (waist circumference ≥ 80 cm in females and ≥ 94 cm in males) were identified and the national prevalence rates were estimated.</p> <p>Results</p> <p>The prevalence of diabetes, hypertension, obesity, and central obesity was 8.7% (95%CI = 7.4–10.2%), 26.6% (95%CI = 24.4–28.9%), 22.3% (95%CI = 20.2–24.5%), and 53.6% (95%CI = 50.4–56.8%), respectively. The prevalence of hypertriglyceridemia and hypercholesterolemia was 36.4% (95%CI = 34.1–38.9%) and 42.9% (95%CI = 40.4–45.4%), respectively. All of the mentioned prevalence rates were higher among females (except hypertriglyceridemia) and urban residents.</p> <p>Conclusion</p> <p>We documented a strikingly high prevalence of a number of chronic non-communicable diseases and their risk factors among Iranian adults. Urgent preventive interventions should be implemented to combat the growing public health problems in Iran.</p

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic