nazneen habib - Academia.edu (original) (raw)
Papers by nazneen habib
ASIAN Journal of International Peace & Security (AJIPS), Dec 16, 2020
Review of Economics and Development Studies, 2020
Non-Government Organizations (NGOs) have been considered as the key player in the provision of se... more Non-Government Organizations (NGOs) have been considered as the key player in the provision of services to address the economic, environmental and socio-cultural developmental issues. United Nations global sustainable development goals (SDGs) focused the role of partnerships between different sectors in addressing sustainable development issues. The study focuses on the role of NGOs especially the local organization called as Balochistan Rural Development & Research Society (BRDRS) in empowering community in Balochistan. We conducted a cross-sectional survey in two districts of Balochistan province to investigate role of NGOs among beneficiaries of BRDRS education projects and programs in focused communities by following the quantitative research approach. By using proportionate random sampling technique, 400 respondents were selected out of the total beneficiaries. The results indicated significant associations between BRDRS educational projects (i.e. Arranging Students Exposure Vi...
Journal of Business and Social Review in Emerging Economies, 2020
Across the cultures, parenting or child-rearing practices are considered as the concrete behavior... more Across the cultures, parenting or child-rearing practices are considered as the concrete behaviors towards the developmental process of rearing or socialization of the children. The study splits the conception of parenting practices among two domains as parental acceptance and parental rejection, depending on the behavioural outcomes under investigation. The cross sectional research was conducted on young males attending colleges in Lahore, Pakistan to understand that how parental rejection dimensions of parenting manifest the violent behavioral outcome among male college students. The research within the Pakistani indigenous culture on parenting practices and its inter-relationship between youth violent behavioural outcomes provide stems from the theoretical anchorage in the socio-psychological works. The sample of 816 male students from public colleges of Lahore was included to collect the responses through self-administered questionnaire as a tool of the study. The results indica...
1 Considerable interest has been devoted for developing a deeper understanding of the 2 dynamics ... more 1 Considerable interest has been devoted for developing a deeper understanding of the 2 dynamics of healthy biological systems and how these dynamics are affected due to 3 aging and disease. Entropy based complexity measures have widely been used for 4 quantifying the dynamics of physical and biological systems. These techniques have 5 provided valuable information leading to a fuller understanding of the dynamics of 6 these systems and underlying stimuli that are responsible for anomalous behavior. The 7 single scale based traditional entropy measures yielded contradictory results about the 8 dynamics of real world time series data of healthy and pathological subjects. Recently 9 the multiscale entropy (MSE) algorithm was introduced for precise description of the 10 complexity of biological signals, which was used in numerous fields since its inception. 11 The original MSE quantified the complexity of coarse-grained time series using sample 12 entropy. The original MSE may be unrel...
Acceleration change index (ACI) is a fast and easy to understand heart rate variability (HRV) ana... more Acceleration change index (ACI) is a fast and easy to understand heart rate variability (HRV) analysis approach used for assessing cardiac autonomic control of the nervous systems. The cardiac autonomic control of the nervous system is an example of highly integrated systems operating at multiple time scales. Traditional single scale based ACI did not take into account multiple time scales and has limited capability to classify normal and pathological subjects. In this study, a novel approach multiscale ACI (MACI) is proposed by incorporating multiple time scales for improving the classification ability of ACI. We evaluated the performance of MACI for classifying, normal sinus rhythm (NSR), congestive heart failure (CHF) and atrial fibrillation subjects. The findings reveal that MACI provided better classification between healthy and pathological subjects compared to ACI. We also compared MACI with other scale-based techniques such as multiscale entropy, multiscale permutation entro...
Waves in Random and Complex Media, 2021
Mathematical Biosciences and Engineering, 2021
Accurate prediction of particulate matter (PM) using time series data is a challenging task. The ... more Accurate prediction of particulate matter (PM) using time series data is a challenging task. The recent advancements in sensor technology, computing devices, nonlinear computational tools, and machine learning (ML) approaches provide new opportunities for robust prediction of PM concentrations. In this study, we develop a hybrid model for forecasting PM10 and PM2.5 based on the multiscale characterization and ML techniques. At first, we use the empirical mode decomposition (EMD) algorithm for multiscale characterization of PM10 and PM2.5 by decomposing the original time series into numerous intrinsic mode functions (IMFs). Different individual ML algorithms such as random forest (RF), support vector regressor (SVR), k-nearest neighbors (kNN), feed forward neural network (FFNN), and AdaBoost are then used to develop EMD-ML models. The air quality time series data from Masfalah air station Makkah, Saudi Arabia are utilized for validating the EMD-ML models, and results are compared with non-hybrid ML models. The PMs (PM10 and PM2.5) concentrations data of Dehli, India are also utilized for validating the EMD-ML models. The performance of each model is evaluated using root mean square error (RMSE) and mean absolute error (MAE). The average bias in the predictive model is estimated using mean bias error (MBE). Obtained results reveal that EMD-FFNN model provides the lowest error rate for both PM10 (RMSE = 12.25 and MAE = 7.43) and PM2.5 (RMSE = 4.81 and MAE = 3.02) using Misfalah, Makkah data whereas EMD-kNN model provides the lowest error rate for PM10 (RMSE = 20.56 and MAE = 12.87) and EMD-AdaBoost provides the lowest error rate for PM2.5 (RMSE = 15.29 and MAE = 9.45) using Dehli, India data. The findings also reveal that EMD-ML models can be effectively used in forecasting PM mass concentrations and to develop rapid air quality warning systems.
Journal of Pharmaceutical Research International, 2020
Aims: This study is aimed to determine the prevalence of anemia and to analyze its socio-cultural... more Aims: This study is aimed to determine the prevalence of anemia and to analyze its socio-cultural determinants among under five children to devise targeted delivery plan for pharmaceutical interventions to combat anemia. Study Design: To investigate the socio-cultural risk factors, a cross-sectional field survey was conducted to gather data from 384 women and their last child up to five years of age in Muzaffarabad district of Azad Jammu & Kashmir (AJK), Pakistan. Methodology: A pretested interview schedule was constructed to collect socio-cultural characteristics of the women and their children. We use convenience sampling which is a non-probability sampling technique for data collection. Two government hospitals were selected for data and blood samples collection from respondents. We use univariate analysis for descriptive statistics and perform bivariate analysis to find the association of anemia with the socio-cultural risk factors. Binary logistic regression is used to calculat...
Traitement du Signal, 2020
Journal of Pharmaceutical Research International, 2020
Aims: To study societal determinants of anemia among women of reproductive age (WRA) and elaborat... more Aims: To study societal determinants of anemia among women of reproductive age (WRA) and elaborate the role of community pharmacist for its management. Study Design: To investigate the societal determinants of anemia, a cross-sectional study was conducted in the Muzaffarabad district of AJK, Pakistan. Methodology: We collected the data from 384 women of reproductive age (15-49 years) having at least one child using a self- constructed interview schedule. The population sample size was calculated using Krejcie formula and purposive sampling was used for data collection. Two hospitals, Abbas Institute of Medical Sciences and combined military hospital Muzaffarabad were selected for blood samples to screen the hemoglobin (Hb) level of the respondents and data collection. Univariate analysis was performed to examine the frequency distributions and percentages of cases depending on a single variable at a time. The bivariate analysis was performed using chi-square test to determine empiri...
Journal of Pharmaceutical Research International, 2020
Background: The medical researchers are developing different non-invasive methods for early detec... more Background: The medical researchers are developing different non-invasive methods for early detection of Neurodegenerative Diseases (NDDs) when pharmacological interventions are still possible to further prevent the disease progression. The NDDs are associated with the degradation in the complex gait dynamics and motor activity. The classification of gait data using machine learning techniques can assist the physicians for early diagnosis of the neural disorder when clinical manifestation of the diseases is not yet apparent. Aims: The present study was undertaken to classify the control and NDD subjects using decision trees based classifiers (Random Forest (RF), J48 and REPTree). Methodology: The data used in the study comprises of 16 control, 20 Huntington’s Disease (HD), 15 Parkinson’s Disease (PD), and 13 Amyotrophic Lateral Sclerosis (ALS) subjects, which were taken from publicly available database from Physionet. The age range of control subjects was 20-74, HD subjects was 36-7...
Anemia, 2020
Societal determinants of health are of recognized importance for understanding the causal associa... more Societal determinants of health are of recognized importance for understanding the causal association of society and health of an individual. Iron deficiency anemia (IDA) is a challenging public health problem across the globe instigating from a broader sociocultural background. It is more prevalent among pregnant women, children under the age of five years, and adolescent girls. Adolescent girls are vulnerable to develop IDA because of additional nutritional demand of the body needed for growth spurt, blood loss due to onset of menarche, malnourishment, and poor dietary iron intake. In this study, we explore the societal determinants of anemia among adolescent girls in Azad Jammu and Kashmir (AJK), Pakistan. A cross-sectional study was conducted in the Muzaffarabad division of AJK on randomly selected 626 adolescent girls. The data were collected using a pretested self-administered interview schedule comprising mainly closed-ended questions with a few open-ended questions. Descript...
PloS one, 2018
Considerable interest has been devoted for developing a deeper understanding of the dynamics of h... more Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals bec...
Journal of physiological anthropology, Jan 23, 2017
Epilepsy is a neuronal disorder for which the electrical discharge in the brain is synchronized, ... more Epilepsy is a neuronal disorder for which the electrical discharge in the brain is synchronized, abnormal and excessive. To detect the epileptic seizures and to analyse brain activities during different mental states, various methods in non-linear dynamics have been proposed. This study is an attempt to quantify the complexity of control and epileptic subject with and without seizure as well as to distinguish eye-open (EO) and eye-closed (EC) conditions using threshold-based symbolic entropy. The threshold-dependent symbolic entropy was applied to distinguish the healthy and epileptic subjects with seizure and seizure-free intervals (i.e. interictal and ictal) as well as to distinguish EO and EC conditions. The original time series data was converted into symbol sequences using quantization level, and word series of symbol sequences was generated using a word length of three or more. Then, normalized corrected Shannon entropy (NCSE) was computed to quantify the complexity. The NCSE ...
Pakistan journal of pharmaceutical sciences, 2015
Coronary artery disease (CAD) is a leading cause of mortality in the developing countries. The ai... more Coronary artery disease (CAD) is a leading cause of mortality in the developing countries. The aim of the study was to check the association of Myocardial infarction (MI) with several factors such as smoking & smoking exposure, blood pressure, sugar & cholesterol level, stress, anxiety & lifestyle. A cross sectional community based survey was conducted involving 469 patients having one or more risk factors or having complains regarding MI & already diagnosed MI, was taken using Multistage sampling technique from Sheikh Zaid Hospital & Abbas Institute of Medical Sciences. The Chi-square test was used to check the association of different risk factors with myocardial infarction. The multivariate Logistic regression model was also applied to find out the most significant risk factors of MI. The results revealed that MI was strongly associated with following risk factors family size (p=0.04), profession of respondent (p=0.026), smoking (p=0.028) & smoking exposure (p=0.043). The finding...
ABSTRACT Obesity is a condition of the body in which it has excess of body fats. Obesity is direc... more ABSTRACT Obesity is a condition of the body in which it has excess of body fats. Obesity is directly associated with life-expectancy, public and private expenditure on health and life risking diseases including cardiovascular diseases. Obesity has a harmful effect on labor outcomes which reduces the efficiency and productivity of labor. Therefore the present study was conducted to have an idea regarding awareness about obesity and to assess different social and physical risk factors of obesity in the young population of district Muzaffarabad Azad Kashmir. A sample of 260 respondents was collected from the students of AJK University Muzaffarabad based on convenience sampling technique. A close ended structure questionnaire was used to collect the information from the students. Descriptive statistics was used to assess the different demographic characteristics of the respondent, Chisquare test was performed to check the association between BMI and different factors. Ordinal logistic regression is used for empirical analysis. The finding revealed that most of the youth perceives that major diseases like hypertension and diabetes attack due to obesity. The majority of youth reported obesity as a factor causing depression. More than 75% reported lack of physical activities and overeating as reason of obesity. The results showed that females are more obese than males. The findings of study are useful for policy makers who are interested in creating awareness on obesity among youth.
Acta Biologica Hungarica, 2014
The dynamical fluctuations of biological signals provide a unique window to construe the underlyi... more The dynamical fluctuations of biological signals provide a unique window to construe the underlying mechanism of the biological systems in health and disease. Recent research evidences suggest that a wide class of diseases appear to degrade the biological complexity and adaptive capacity of the system. Heart rate signals are one of the most important biological signals that have widely been investigated during the last two and half decades. Recent studies suggested that heart rate signals fluctuate in a complex manner. Various entropy based complexity analysis measures have been developed for quantifying the valuable information that may be helpful for clinical monitoring and for early intervention. This study is focused on determining HRV dynamics to distinguish healthy subjects from patients with certain cardiac problems using symbolic time series analysis technique. For that purpose, we have employed recently developed threshold based symbolic entropy to cardiac inter-beat interval time series of healthy, congestive heart failure and atrial fibrillation subjects. Normalized Corrected Shannon Entropy (NCSE) was used to quantify the dynamics of heart rate signals by continuously varying threshold values. A rule based classifier was implemented for classification of different groups by selecting threshold values for the optimal separation. The findings indicated that there is reduction in the complexity of pathological subjects as compared to healthy ones at wide range of threshold values. The results also demonstrated that complexity decreased with disease severity.
IOSR Journal of Nursing and Health Science, 2013
ASIAN Journal of International Peace & Security (AJIPS), Dec 16, 2020
Review of Economics and Development Studies, 2020
Non-Government Organizations (NGOs) have been considered as the key player in the provision of se... more Non-Government Organizations (NGOs) have been considered as the key player in the provision of services to address the economic, environmental and socio-cultural developmental issues. United Nations global sustainable development goals (SDGs) focused the role of partnerships between different sectors in addressing sustainable development issues. The study focuses on the role of NGOs especially the local organization called as Balochistan Rural Development & Research Society (BRDRS) in empowering community in Balochistan. We conducted a cross-sectional survey in two districts of Balochistan province to investigate role of NGOs among beneficiaries of BRDRS education projects and programs in focused communities by following the quantitative research approach. By using proportionate random sampling technique, 400 respondents were selected out of the total beneficiaries. The results indicated significant associations between BRDRS educational projects (i.e. Arranging Students Exposure Vi...
Journal of Business and Social Review in Emerging Economies, 2020
Across the cultures, parenting or child-rearing practices are considered as the concrete behavior... more Across the cultures, parenting or child-rearing practices are considered as the concrete behaviors towards the developmental process of rearing or socialization of the children. The study splits the conception of parenting practices among two domains as parental acceptance and parental rejection, depending on the behavioural outcomes under investigation. The cross sectional research was conducted on young males attending colleges in Lahore, Pakistan to understand that how parental rejection dimensions of parenting manifest the violent behavioral outcome among male college students. The research within the Pakistani indigenous culture on parenting practices and its inter-relationship between youth violent behavioural outcomes provide stems from the theoretical anchorage in the socio-psychological works. The sample of 816 male students from public colleges of Lahore was included to collect the responses through self-administered questionnaire as a tool of the study. The results indica...
1 Considerable interest has been devoted for developing a deeper understanding of the 2 dynamics ... more 1 Considerable interest has been devoted for developing a deeper understanding of the 2 dynamics of healthy biological systems and how these dynamics are affected due to 3 aging and disease. Entropy based complexity measures have widely been used for 4 quantifying the dynamics of physical and biological systems. These techniques have 5 provided valuable information leading to a fuller understanding of the dynamics of 6 these systems and underlying stimuli that are responsible for anomalous behavior. The 7 single scale based traditional entropy measures yielded contradictory results about the 8 dynamics of real world time series data of healthy and pathological subjects. Recently 9 the multiscale entropy (MSE) algorithm was introduced for precise description of the 10 complexity of biological signals, which was used in numerous fields since its inception. 11 The original MSE quantified the complexity of coarse-grained time series using sample 12 entropy. The original MSE may be unrel...
Acceleration change index (ACI) is a fast and easy to understand heart rate variability (HRV) ana... more Acceleration change index (ACI) is a fast and easy to understand heart rate variability (HRV) analysis approach used for assessing cardiac autonomic control of the nervous systems. The cardiac autonomic control of the nervous system is an example of highly integrated systems operating at multiple time scales. Traditional single scale based ACI did not take into account multiple time scales and has limited capability to classify normal and pathological subjects. In this study, a novel approach multiscale ACI (MACI) is proposed by incorporating multiple time scales for improving the classification ability of ACI. We evaluated the performance of MACI for classifying, normal sinus rhythm (NSR), congestive heart failure (CHF) and atrial fibrillation subjects. The findings reveal that MACI provided better classification between healthy and pathological subjects compared to ACI. We also compared MACI with other scale-based techniques such as multiscale entropy, multiscale permutation entro...
Waves in Random and Complex Media, 2021
Mathematical Biosciences and Engineering, 2021
Accurate prediction of particulate matter (PM) using time series data is a challenging task. The ... more Accurate prediction of particulate matter (PM) using time series data is a challenging task. The recent advancements in sensor technology, computing devices, nonlinear computational tools, and machine learning (ML) approaches provide new opportunities for robust prediction of PM concentrations. In this study, we develop a hybrid model for forecasting PM10 and PM2.5 based on the multiscale characterization and ML techniques. At first, we use the empirical mode decomposition (EMD) algorithm for multiscale characterization of PM10 and PM2.5 by decomposing the original time series into numerous intrinsic mode functions (IMFs). Different individual ML algorithms such as random forest (RF), support vector regressor (SVR), k-nearest neighbors (kNN), feed forward neural network (FFNN), and AdaBoost are then used to develop EMD-ML models. The air quality time series data from Masfalah air station Makkah, Saudi Arabia are utilized for validating the EMD-ML models, and results are compared with non-hybrid ML models. The PMs (PM10 and PM2.5) concentrations data of Dehli, India are also utilized for validating the EMD-ML models. The performance of each model is evaluated using root mean square error (RMSE) and mean absolute error (MAE). The average bias in the predictive model is estimated using mean bias error (MBE). Obtained results reveal that EMD-FFNN model provides the lowest error rate for both PM10 (RMSE = 12.25 and MAE = 7.43) and PM2.5 (RMSE = 4.81 and MAE = 3.02) using Misfalah, Makkah data whereas EMD-kNN model provides the lowest error rate for PM10 (RMSE = 20.56 and MAE = 12.87) and EMD-AdaBoost provides the lowest error rate for PM2.5 (RMSE = 15.29 and MAE = 9.45) using Dehli, India data. The findings also reveal that EMD-ML models can be effectively used in forecasting PM mass concentrations and to develop rapid air quality warning systems.
Journal of Pharmaceutical Research International, 2020
Aims: This study is aimed to determine the prevalence of anemia and to analyze its socio-cultural... more Aims: This study is aimed to determine the prevalence of anemia and to analyze its socio-cultural determinants among under five children to devise targeted delivery plan for pharmaceutical interventions to combat anemia. Study Design: To investigate the socio-cultural risk factors, a cross-sectional field survey was conducted to gather data from 384 women and their last child up to five years of age in Muzaffarabad district of Azad Jammu & Kashmir (AJK), Pakistan. Methodology: A pretested interview schedule was constructed to collect socio-cultural characteristics of the women and their children. We use convenience sampling which is a non-probability sampling technique for data collection. Two government hospitals were selected for data and blood samples collection from respondents. We use univariate analysis for descriptive statistics and perform bivariate analysis to find the association of anemia with the socio-cultural risk factors. Binary logistic regression is used to calculat...
Traitement du Signal, 2020
Journal of Pharmaceutical Research International, 2020
Aims: To study societal determinants of anemia among women of reproductive age (WRA) and elaborat... more Aims: To study societal determinants of anemia among women of reproductive age (WRA) and elaborate the role of community pharmacist for its management. Study Design: To investigate the societal determinants of anemia, a cross-sectional study was conducted in the Muzaffarabad district of AJK, Pakistan. Methodology: We collected the data from 384 women of reproductive age (15-49 years) having at least one child using a self- constructed interview schedule. The population sample size was calculated using Krejcie formula and purposive sampling was used for data collection. Two hospitals, Abbas Institute of Medical Sciences and combined military hospital Muzaffarabad were selected for blood samples to screen the hemoglobin (Hb) level of the respondents and data collection. Univariate analysis was performed to examine the frequency distributions and percentages of cases depending on a single variable at a time. The bivariate analysis was performed using chi-square test to determine empiri...
Journal of Pharmaceutical Research International, 2020
Background: The medical researchers are developing different non-invasive methods for early detec... more Background: The medical researchers are developing different non-invasive methods for early detection of Neurodegenerative Diseases (NDDs) when pharmacological interventions are still possible to further prevent the disease progression. The NDDs are associated with the degradation in the complex gait dynamics and motor activity. The classification of gait data using machine learning techniques can assist the physicians for early diagnosis of the neural disorder when clinical manifestation of the diseases is not yet apparent. Aims: The present study was undertaken to classify the control and NDD subjects using decision trees based classifiers (Random Forest (RF), J48 and REPTree). Methodology: The data used in the study comprises of 16 control, 20 Huntington’s Disease (HD), 15 Parkinson’s Disease (PD), and 13 Amyotrophic Lateral Sclerosis (ALS) subjects, which were taken from publicly available database from Physionet. The age range of control subjects was 20-74, HD subjects was 36-7...
Anemia, 2020
Societal determinants of health are of recognized importance for understanding the causal associa... more Societal determinants of health are of recognized importance for understanding the causal association of society and health of an individual. Iron deficiency anemia (IDA) is a challenging public health problem across the globe instigating from a broader sociocultural background. It is more prevalent among pregnant women, children under the age of five years, and adolescent girls. Adolescent girls are vulnerable to develop IDA because of additional nutritional demand of the body needed for growth spurt, blood loss due to onset of menarche, malnourishment, and poor dietary iron intake. In this study, we explore the societal determinants of anemia among adolescent girls in Azad Jammu and Kashmir (AJK), Pakistan. A cross-sectional study was conducted in the Muzaffarabad division of AJK on randomly selected 626 adolescent girls. The data were collected using a pretested self-administered interview schedule comprising mainly closed-ended questions with a few open-ended questions. Descript...
PloS one, 2018
Considerable interest has been devoted for developing a deeper understanding of the dynamics of h... more Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals bec...
Journal of physiological anthropology, Jan 23, 2017
Epilepsy is a neuronal disorder for which the electrical discharge in the brain is synchronized, ... more Epilepsy is a neuronal disorder for which the electrical discharge in the brain is synchronized, abnormal and excessive. To detect the epileptic seizures and to analyse brain activities during different mental states, various methods in non-linear dynamics have been proposed. This study is an attempt to quantify the complexity of control and epileptic subject with and without seizure as well as to distinguish eye-open (EO) and eye-closed (EC) conditions using threshold-based symbolic entropy. The threshold-dependent symbolic entropy was applied to distinguish the healthy and epileptic subjects with seizure and seizure-free intervals (i.e. interictal and ictal) as well as to distinguish EO and EC conditions. The original time series data was converted into symbol sequences using quantization level, and word series of symbol sequences was generated using a word length of three or more. Then, normalized corrected Shannon entropy (NCSE) was computed to quantify the complexity. The NCSE ...
Pakistan journal of pharmaceutical sciences, 2015
Coronary artery disease (CAD) is a leading cause of mortality in the developing countries. The ai... more Coronary artery disease (CAD) is a leading cause of mortality in the developing countries. The aim of the study was to check the association of Myocardial infarction (MI) with several factors such as smoking & smoking exposure, blood pressure, sugar & cholesterol level, stress, anxiety & lifestyle. A cross sectional community based survey was conducted involving 469 patients having one or more risk factors or having complains regarding MI & already diagnosed MI, was taken using Multistage sampling technique from Sheikh Zaid Hospital & Abbas Institute of Medical Sciences. The Chi-square test was used to check the association of different risk factors with myocardial infarction. The multivariate Logistic regression model was also applied to find out the most significant risk factors of MI. The results revealed that MI was strongly associated with following risk factors family size (p=0.04), profession of respondent (p=0.026), smoking (p=0.028) & smoking exposure (p=0.043). The finding...
ABSTRACT Obesity is a condition of the body in which it has excess of body fats. Obesity is direc... more ABSTRACT Obesity is a condition of the body in which it has excess of body fats. Obesity is directly associated with life-expectancy, public and private expenditure on health and life risking diseases including cardiovascular diseases. Obesity has a harmful effect on labor outcomes which reduces the efficiency and productivity of labor. Therefore the present study was conducted to have an idea regarding awareness about obesity and to assess different social and physical risk factors of obesity in the young population of district Muzaffarabad Azad Kashmir. A sample of 260 respondents was collected from the students of AJK University Muzaffarabad based on convenience sampling technique. A close ended structure questionnaire was used to collect the information from the students. Descriptive statistics was used to assess the different demographic characteristics of the respondent, Chisquare test was performed to check the association between BMI and different factors. Ordinal logistic regression is used for empirical analysis. The finding revealed that most of the youth perceives that major diseases like hypertension and diabetes attack due to obesity. The majority of youth reported obesity as a factor causing depression. More than 75% reported lack of physical activities and overeating as reason of obesity. The results showed that females are more obese than males. The findings of study are useful for policy makers who are interested in creating awareness on obesity among youth.
Acta Biologica Hungarica, 2014
The dynamical fluctuations of biological signals provide a unique window to construe the underlyi... more The dynamical fluctuations of biological signals provide a unique window to construe the underlying mechanism of the biological systems in health and disease. Recent research evidences suggest that a wide class of diseases appear to degrade the biological complexity and adaptive capacity of the system. Heart rate signals are one of the most important biological signals that have widely been investigated during the last two and half decades. Recent studies suggested that heart rate signals fluctuate in a complex manner. Various entropy based complexity analysis measures have been developed for quantifying the valuable information that may be helpful for clinical monitoring and for early intervention. This study is focused on determining HRV dynamics to distinguish healthy subjects from patients with certain cardiac problems using symbolic time series analysis technique. For that purpose, we have employed recently developed threshold based symbolic entropy to cardiac inter-beat interval time series of healthy, congestive heart failure and atrial fibrillation subjects. Normalized Corrected Shannon Entropy (NCSE) was used to quantify the dynamics of heart rate signals by continuously varying threshold values. A rule based classifier was implemented for classification of different groups by selecting threshold values for the optimal separation. The findings indicated that there is reduction in the complexity of pathological subjects as compared to healthy ones at wide range of threshold values. The results also demonstrated that complexity decreased with disease severity.
IOSR Journal of Nursing and Health Science, 2013